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DOE Symposium Series 



ENERGY AND ^ 
ENVIRONMENTAL 



AQUATIC SYSTEMS 




TECHNICAL INFORMATION CENTER/DEPARTMENT OF ENE'RG 



CONF-771114 -7 




ENERGY AND 
ENVIRONMENTAL 

IN 
AQUATIC SYSTEMS 



Selected papers from a symposium held at Augusta, Georgia 
November 2-4, 1977 

Edited by 

James H. Thorp 
and 

J. Whitfield Gibbons 

Savannah River Ecology Laboratory and University of Georgia 



Sponsored by 

Savannah River Ecology Laboratory 

Institute of Ecology, University of Georgia 

Assistant Secretary for Environment 
U. S. Department of Energy 

Savannah River National Environmental Research Park 

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1978 






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Published by 

Technical Information Center 

U. S. Department of Energy 



Library of Congress Cataloging in Publication Data 

Main entry under title: 

Energy and environmental stress in aquatic systems. 

(DOE Symposium series; 48) 

"CONF-771114" 

Includes indexes. 

1. Aquatic ecology Congresses. 2. Power resources Envi- 
ronmental aspects Congresses. 3. Environmental engineering 

Congresses. I. Thorp, James H. II. Gibbons, J. Whitfield, 1939- 
III. Savannah River Ecology Laboratory. IV. Series: United States. 
Dept. of Energy. DOE symposium series; 48. 
QH541.5.W3E53 574.5'263 78-27913 

ISBN 0-87079-1 15-X 



Available as CONF-771 1 14 for $1 5.00 from 
National Technical Information Service 
U. S. Department of Commerce 
Springfield, Virginia 22161 



DOE Distribution Category UC-11 



International Copyright, © U. S. Department of Energy, 1978, under the 
provisions of the Universal Copyright Convention. United States copyright 
is not asserted under the United States Copyright Law, Title 17, United 
States Code. 



Printed in the United States of America 
December 1978 



PREFACE 



The United States and most industrially developed 
nations of the world are confronted by crucial decisions 
on the use of alternative sources of energy. Both short- 
and long-term effects on human and environmental 
health, and frequently on the international balance of 
payments, hinge on the outcome of these decisions. Too 
often policy is made as a reflex response to the clamor 
created in the public realm by industrialists, economists, 
or environmentalists, without giving due consideration 
to the overall impact and compromises associated with 
the choice of one fuel over another energy option. For 
example, many environmentalists oppose large central 
power plants because high temperatures increase mortal- 
ity for certain aquatic organisms but do not consider the 
potential for increased growth rates or higher species 
diversity from moderate thermal inputs. In contrast, 
some industrialists view nuclear central power stations 
as the most viable energy option because the probability 
of an accident is minimal and the long-term efficiency is 
high. However, the exceedingly long-term impact of a 
radioactive leak and the difficulty of cleanup magnify 
the significance of a single "low-probability" accident. 
Finally, the environmental impact of nuclear power 
must be evaluated with respect to that of other fuels, 
e.g., the environmental effects of acid mine drainage and 
acid rainfall that can result from the procurement and 
conversion of coal or the effects of thermal effluents 
from fossil-fueled power plants. 

This symposium, Energy and Environmental Stress 
in Aquatic Systems, served as a forum for discussions of 



IV 



PREFACE 



the environmental effects of alternative sources of 
energy. This exchange of information promotes a proper 
perspective in which to make critical judgments affect- 
ing a country's energy and environmental policies. 
The symposium was ideal for comparing effects of 
various stressors and for enabling researchers in one 
discipline to become acquainted with those in another 
area. Because of the broad nature of the meeting, we 
were able to define six central topics around which the 
160 oral presentations were organized. Each of the six 
core areas was represented by an invited speaker, who 
reviewed the effects of specific stressors or discussed 
methods of modeling stress. These speakers were en- 
couraged to speculate on future avenues of research and 
to make generalizations where appropriate. Thus, each 
topic was addressed first by a general synthesis and then 
by a series of detailed, specific studies. The final 49 
papers in this volume were selected from an initial group 
of 80 papers submitted for publication from that 
symposium and were included only after vigorous 
review by outside referees. 

The theme of the symposium was environmental 
stress, but, as evidenced by this volume, little unifor- 
mity exists in application of the term "stress." Three of 
the core papers distinguished between the action and 
response involved in stress, two equating the action with 
the term "stressor" and the response with the term 
"stress," but another core paper described action as 
"stress" and response as "strain." Differentiation in 
terms may seem superfluous, but the dual meaning is 
common in the ecological literature and has implications 
for understanding system specificity in response to 
environmental fluctuations. For example, Esch and 
Hazen, in their core paper, characterized the response to 
a stressor as "either an enhancement or a diminishment 
in the probability of mortality, natality, or permanent 
change." This concept of stress as either a positive or 
negative response is controversial to say the least, but, if 
the action or stressor is defined as a neutral, time- 
varying input, then the response to it can be either 
positive, neutral, or negative depending on the charac- 
teristics of the receiving system. We believe that stress 
always represents a negative effect on some specific 
component of the system but that the ultimate response 



PREFACE V 

of the other components or of the overall system may 
be positive. For instance, species diversity or equita- 
bility may increase during periods of stressful environ- 
mental fluctuations if the average compensatory effi- 
ciency of the community members is superior to that of 
a species which is normally dominant in less-extreme or 
more-constant conditions. 

Operational definitions of stress or strain frequently 
reflected the subdisciplines and areas of interest of the 
investigators. For example, Lugo, w^ho classified envi- 
ronments by their "energy signatures," defined stress in 
terms of a drain of potential energy from a system; 
whereas Esch and Hazen described the homeostatic 
stress response of largemouth bass to thermal effluents 
and bacterial infection. Ulanovdcz, however, was con- 
cerned with linear and nonlinear modeling of inputs and 
the resultant strain, in a mechanistic sense, imposed on 
the ecosystem. We will not provide here an additional 
definition of stress, but we caution the readers to 
consider the operational definitions carefully before 
comparing individual studies. 

The first section of this volume is devoted to 
modeling stress, because ultimately the ability to model 
and, thus, predict the stress response is a primary raison 
d'etre for funding stress research. In his review paper on 
modeling stress, Ulanowicz classifies existing models 
according to whether they track local or far-field stress. 
He also discusses the success of various attempts at 
linear and nonlinear modeling of the effects on ecosys- 
tem properties of endogenous and exogenous stressors. 
Dv^er et al., however, contend that an "adequate 
description of ecosystem stability properties cannot 
always be derived from a linearized model of the 
ecosystem." They used techniques of spectral analysis 
to analyze phytoplankton abundance in a system 
exposed to time-varying inputs. 

Accurate prediction of a system's response to 
anthropogenic stressors frequently requires an under- 
standing of the nature of a system's response to natural 
perturbations. In his review of studies of stressed 
ecosystems, Lugo proposes that the energetic quality of 
both the stressor and the receiving system determines the 
severity of response to a perturbation. He also maintains 
that the stability of an ecosystem depends on the 



VI 



PREFACE 



stability of the main energy source. Leffler, however, 
concludes from a series of microcosm experiments that 
"no relationships between diversity, nutrient avail- 
ability, or system mass and ecosystem stability or 
between ecosystem resistance and resilience stabilities 
were demonstrated." Norse, examining the effects of 
biological stressors and natural physicochemical stress 
gradients on the distribution of tropical portunid crabs, 
shows that biological stress increased as physicochemical 
stress decreased. 

The rapid proliferation in the past few years of 
studies of the environmental impact resulting from the 
procurement, conversion, burning, and disposal of coal 
is indicative of the reemerging importance of this energy 
source in many industrial nations. Gehrs concludes from 
a literature review of studies on organic contaminants 
produced by conversion of coal to hydrocarbon com- 
pounds with higher hydrogen-to-carbon ratios, that 
toxicological investigations of individual compounds can 
be made manageable by first grouping the compounds 
on the basis of chemical structure and then studying 
representative compounds. Schultz, Dumont, and Kyte 
demonstrate that a 2% concentration of untreated 
coal-conversion gasifier condensate decreased motility 
and increased cell lysis in a ciliate protozoan. The 
procurement of coal can result in acid mine pollution, 
which has been demonstrated to reduce severely species 
richness of invertebrate communities in Ohio streams 
(Hummon etal.) but to have a much lesser impact on 
Colorado streams (Ward, Canton, and Gray). 

Toxicological aspects of trace metals introduced 
into streams by natural and anthropogenic processes 
have received considerable attention in recent years. 
Eisler reviews the effects of mercury on marine biota 
and suggests more severe restrictions on the discharge of 
mercury compounds in general and methyl mercury 
compounds in particular. In a separate paper, Zubarik 
and O'Connor discuss the uptake of mercury by Hudson 
River biota. Other papers examine the effects of various 
trace elements on survival of fish and amphibian eggs 
(Birge), mortality of adult Pacific oysters (Harrison and 
Rice), nitrification by aquatic, autotrophic bacteria 
(Holm and Cox), and species diversity of zooplankton 



PREFACE vii 

communities (Marshall and Mellinger). Generalizations 
about the uptake and toxicity of various trace metals 
are difficult to make because of the specificity in action 
of individual elements. However, current efforts in this 
area center on similarities in uptake and toxicity in 
relation to atomic structure of the elements and to the 
chemical requirements of the biota being studied. 

Two of the previous volumes in the Savannah River 
Ecology Laboratory Symposium Series on Ecological 
Research, and approximately half this volume, are 
devoted to studies of the response of organisms and 
communities to thermal effluents. The papers in this 
section of this volume are roughly grouped by their 
emphasis on functional (i.e., primary productivity, 
growth, genetics, reproduction, and behavior), struc- 
tural, and toxic ological aspects of thermal ecology. The 
diversity of these studies demonstrates that thermal 
effluents have a comprehensive effect on most func- 
tional and structural aspects of aquatic systems. 

Difficulties in design and analysis have impeded the 
spread of studies on multiple and synergistic stresses, 
and yet, in most of our "less-than-pristine" environ- 
ments, the simultaneous presence of various stressors is 
undoubtedly the norm rather than the exception. 
Vernberg's review of recent research on the effects of 
multiple stressors shows the reduction that can occur in 
an organism's zones of lethality and compatibility as a 
result of previous or concurrent exposure to multiple 
stressors. Three papers demonstrate differential effects 
on fish or Cladocera from multiple stressors associated 
with entrainment (Poje, Ginn, and O'Connor and 
Buikema etal.) or presence near the discharge (Cherry 
et al.) of fossil-fueled or nucleair power plants compared 
with the effects of single factors. This multiple-factor 
effect is also shown for the benthic macroinvertebrates 
in streams in Ohio (Beckett) and Pennsylvania (Bradt) 
which had been subjected to a variety of physical and 
chemical stressors as a result of channelization and 
urbanization. 

We see a need for additional symposia that will serve 
as forums for comparing and contrasting the effects of a 
variety of stressors rather than focusing on individual 
perturbations. The task of selecting the energy source 



VIII 



PREFACE 



that best balances economic and environmental con- 
cerns in a given situation will be facilitated by such 
discussions. The emphasis of future meetings should 
differ from this one since the economic and environ- 
mental problems that industrial nations face continue to 
evolve vi^ith our changing world. 



J. H. Thorp 
J. W. Gibbons 
Editors 



ACKNOWLEDGMENTS 



To be successful, a symposium requires the enthusiasm 
and unselfish assistance of numerous individuals. The 
major portion of effort necessary to make this particular 
meeting an outstanding one came from the staff and 
students of the Savannah River Ecology Laboratory. 
Contributions of time and work were given by all 
individuals at SREL prior to, during, and in the 
follow-up aspects of the symposium. We also appreciate 
the cooperative spirit of the Department of Energy's 
Savannah River Operations Office, without whose sup- 
port this meeting could not have been held. In addition, 
we thank the individuals at DOE Headquarters for their 
encouragement. We especially thank the six invited 
speakers and numerous session chairmen for their 
participation in the program. 

We feel a particular indebtedness to Eleanor Cato 
for her constant vigil to ensure attention to all details 
and her persistence in carrying out the plethora of jobs 
related to the symposium and to the publication of this 
volume. We thank Robert I. Nestor for his handling of 
the innumerable routine, but critical, exigencies that 
arise before and during a symposium. Once again we 
thank the highly competent redactory editorial staff of 
the DOE Technical Information Center in Oak Ridge, 
Tennessee. Dee Jared, Anne Goulden, and their associ- 
ates successfully carried the total volume through to 
completion. 

Finally, we are particularly grateful to those who 
assisted in the intensive review process through which all 
papers passed. We feel that many authors in the volume 



ACKNOWLEDGMENTS 



also owe a debt of thanks to these individuals. The 
following reviewed manuscripts at our request: 

L. G. Abele, Florida State University, Tallahassee, FL 
W. D. Adair, Duke Power Company, Huntersville, NC 
S. M. Adams, Oak Ridge National Laboratory, Oak 

Ridge, TN 
D. F. Alderdice, Pacific Biological Station, Nanaimo, 

British Columbia 
D. E. Alston, Auburn University, Auburn, AL 
A. W. Andren, University of Wisconsin, Madison, WI 
N. E. Armstrong, University of Texas, Austin, TX 
W. M. Barnard, State University College, Fredonia, NY 
L. W. Barnthouse, Oak Ridge National Laboratory, Oak 

Ridge, TN 
K. E. Biesinger, U. S. Environmental Protection Agency, 

Duluth, MN 
W. J. Birge, University of Kentucky, Lexington, KY 
P. C. Bradbury, North Carolina State University, 

Raleigh, NC 
P. T. Bradt, Lehigh University, Bethlehem, PA 
R. A. Brechbill, U. S. Department of Energy, Oakland, 

CA 
J. C. Britton, Texas Christian University, Fort Worth, 

TX 
I. M. Brook, University of Miami, Miami, FL 
W. A. Brungs, U. S. Environmental Protection Agency, 

Duluth, MN 

A. L. Buikema, Jr., Virginia Polytechnic Institute and 
State University, Blacksburg, VA 

D. L. Bunting, University of Tennessee, Knoxville, TN 
D. T. Burton, Benedict Estuarine Research Laboratory, 

Benedict, MD 
J. Cairns, Jr., Virginia Polytechnic Institute and State 

University, Blacksburg, VA 
W. D. Claus, Delray Beach, FL 
J. L. Cooley, University of Georgia, Athens, GA 
W. E. Cooper, Michigan State University, East Lansing, 

MI 

B. C. Coull, University of South Carolina, Columbia, SC 
R. A. Coulson, Louisiana State University School of 

Medicine, New Orleans, LA 

C. C. Coutant, Oak Ridge National Laboratory, Oak 
Ridge, TN 



ACKNOWLEDGMENTS xi 

F. A. Cross, National Marine Fisheries Service, Beaufort, 
NC 

C. E. Gushing, Battelle Pacific Northwest Laboratories, 
Richland, WA 

M. D. Dahlberg, U. S. Fish and Wildlife Service, La 

Crosse, WI 
W. M. Darley, University of Georgia, Athens, GA 
H. C. Dessauer, Louisiana State University Medical 

Center, New Orleans, LA 
K. L. Dickson, Virginia Polytechnic Institute and State 

University, Blacksburg, VA 

D. R. Dreesen, Los Alamos Scientific Laboratory, Los 
Alamos, NM 

R. S. Driscoll, U. S. Forest Service, Fort Collins, CO 

R. A. Drummond, U. S. Environmental Protection 

Agency, Duluth, MN 
K. F. Ehrlich, Lockheed Center for Marine Research, 

Avila Beach, CA 
R. Eisler, U. S. Environmental Protection Agency, 

Narragansett, RI 
J. W. Elwood, Oak Ridge National Laboratory, Oak 

Ridge, TN 
D. W. Engel, National Marine Fisheries Service, Beau- 
fort, NC 
D. W. Evans, Savannah River Ecology Laboratory, 

Aiken, SC 
C. L. Fergus, Pennsylvania State University, University 

Park, PA 
J. M. Ferris, Purdue University, West Lafayette, IN 

C. B. Fliermans, E. I. du Pont de Nemours and Co., Inc., 

Aiken, SC 
J. L. Gallagher, U. S. Environmental Protection Agency, 

Corvallis, OR 
C. I. Gibson, Battelle Pacific Northwest Laboratory, 

Sequim, WA 
J. M. Giddings, Oak Ridge National Laboratory, Oak 

Ridge, TN 
J. P. Giesy, Savannah River Ecology Laboratory, Aiken, 

SC 

J. J. Gift, Ecological Analysts, Inc., Melville, NY 
R. J. Gilbert, University of Georgia, Athens, GA 
J. L. Gilio, Florida Institute of Technology, Jensen 
Beach, FL 



XII 



ACKNOWLEDGMENTS 



J. M. Glime, Michigan Technological University, Hough- 
ton, MI 

D. Goodman, Scripps Institution of Oceanography, La 
JoUa, CA 

R. A. Greig, National Marine Fisheries Service, Milford, 
CT 

C. A. S. Hall, Cornell University, Ithaca, NY 

J. Harte, Lawrence Berkeley Laboratory, Berkeley, CA 

D. S. Haven, Virginia Institute of Marine Science, 
Gloucester Point, VA 

T. C. Hazen, Wake Forest University, Winston-Salem, 

NC 
G. R. Hendry, Brookhaven National Laboratory, Upton, 

NY 
W. F. Hettler, National Marine Fisheries Service, Beau- 
fort, NC 
K. E. F. Hokanson, U. S. Environmental Protection 

Agency, Monticello, MN 
R. W. Holmes, University of California, Santa Barbara, 

CA 
T. J. Horst, Stone & Webster Engineering Corporation, 

Boston, MA 
D. E. Hoss, National Marine Fisheries Service, Beaufort, 

NC 

F. G. Howell, University of Southern Mississippi, Hat- 
tiesburg, MS 

P. L. Hudson, U. S. Fish and Wildlife Service, Clemson, 

SC 
W. D. Hummon, Ohio University, Athens, OH 

G. R. Huntsman, National Marine Fisheries Service, 
Beaufort, NC 

G. S. Innis, Utah State University, Logan, UT 

L. D. Jensen, Ecological Analysts, Inc., Towson, MD 

R. G. Kazman, Louisiana State University, Baton 

Rouge, LA 
J. R. Kennedy, University of Tennessee, Knoxville, TN 

D. L. King, Michigan State University, East Lansing, MI 
R. T. Lackey, Virginia Polytechnic Institute and State 

University, Blacksburg, VA 
H. V. Leland, U. S. Geological Survey, Menlo Park, CA 
D. R. Lenat, University of North Carolina, Chapel Hill, 

NC 
M. W. Lorenzen, Tetra Tech, Inc., Lafayette, CA 



ACKNOWLEDGMENTS xiii 

H. A. Loyacano, Clemson University, Clemson, SC 

D. L. Lush, Beak Consultants Limited, Mississauga, 

Ontario 
D. B. McDonald, University of lov^a, Iowa City, lA 
R. W. McFarlane, Brown & Root, Inc., Houston, TX 
I. A. McLaren, Dalhousie University, Halifax, Nova 

Scotia 

C. P. McRoy, University of Alaska, Fairbanks, AK 

J. S. Marshall, Argonne National Laboratory, Argonne, 

IL 
J. S. Mattice, Oak Ridge National Laboratory, Oak 

Ridge, TN 

0. E. Maughan, Oklahoma State University, Stillwater, 
OK 

N. A. Mercando, Pennsylvania State University, Abing- 

ton, PA 
J. A. Mihursky, Chesapeake Biological Laboratory, 

Solomons, MD 
P. C. Miller, San Diego State University, San Diego, CA 

J. D. Milligan, Tennessee Valley Authority, Chatta- 
nooga, TN 

F. J. Molz, Auburn University, Auburn, AL 

R. P. Morgan, William F. Clapp Laboratories, Inc., 
Duxbury, MA 

1. Morris, Bigelow Laboratory for Ocean Sciences, West 
Boothbay Harbor, ME 

D. H. Nelson, University of South Alabama, Mobile, AL 
S. J. Nepszy, Ontario Ministry of Natural Resources, 

Wheatley, Ontario 
W. A. Niering, Connecticut College, New London, CT 
J. M. O'Connor, New York University Medical Center, 

Tuxedo, NY 
R. G. Otto, Johns Hopkins University, Baltimore, MD 
D. S. Peters, National Marine Fisheries Service, Beau- 
fort, NC 
J. E. Pinder, III, Savannah River Ecology Laboratory, 
Aiken, SC 

G. V. Poje, New York University Medical Center, 
Tuxedo, NY 

T. T. Polgar, Martin Marietta Corporation, Baltimore, 

MD 
L. R. Pomeroy, University of Georeia, Athens, GA 



XIV 



ACKNOWLEDGMENTS 



C. W. Reimer, Academy of Natural Sciences, Philadel- 
phia, PA 

N. L. Richards, U. S. Environmental Protection Agency, 
Gulf Breeze, FL 

E. B. Rodgers, Tennessee Valley Authority, Decatur, AL 
P. A. Sandifer, South Carolina Wildhfe and Marine 

Resources Department, Charleston, SC 

C. E. Sansbury, South Carolina Department of Health 
and Environmental Control, Columbia, SC 

W. E. Schaaf, National Marine Fisheries Service, Beau- 
fort, NC 

C. L. Schelske, University of Michigan, Ann Arbor, MI 

D. W. Schindler, Freshwater Institute, Winnipeg, Mani- 
toba 

M. J. Schneider, Battelle Pacific Northwest Labora- 
tories, Richland, WA 
P. B. Schroeder, University of Miami, Miami, FL 
J. R. Schubel, State University of New York, Stony 
Brook, NY 

F. J. Schwartz, University of North Carolina, Morehead 
City, NC 

K. P. Sebens, Harvard University, Cambridge, MA 

E. D. Seneca, North Carolina State University, Raleigh, 
NC 

A. H. Seymour, University of Washington, Seattle, WA 

J. Shapiro, University of Minnesota, Minneapolis, MN 
R. R. Sharitz, Savannah River Ecology Laboratory, 

Aiken, SC 
W. L. Shelton, Auburn University, Auburn, AL 

J. M. Shick, University of Maine, Orono, ME 
J. B. Shrode, Occidental College, Los Angeles, CA 
L. B. Slobodkin, State University of New York, Stony 
Brook, NY 

D. H. Smith, Stony Creek, VA 

M. H. Smith, Savannah River Ecology Laboratory, 

Aiken, SC 
J. R. Spotila, State University College, Buffalo, NY 
J. B. Sprague, Guelph, Ontario 

E. A. Standora, Savannah River Ecology Laboratory, 
Aiken, SC 

R. H. Stavn, University of North Carolina, Greensboro, 
NC 



ACKNOWLEDGMENTS xv 

C. E. Stephan, U. S. Environmental Protection Agency, 
Duluth, MN 

J. S. Suffern, Oak Ridge National Laboratory, Oak 

Ridge, TN 
R. M. Sykes, Ohio State University, Columbus, OH 
M. R. Tansey, Indiana University, Bloomington, IN 
K. R. Tenore, Skidaway Institute of Oceanography, 

Savannah, GA 
J. H. Tietjen, City College of New York, New York, NY 
L. J. Tilly, E. I. du Pont de Nemours and Co., Inc., 

Aiken, SC 
F. R. Trainor, University of Connecticut, Storrs, CT 
R. E. Ulanowicz, Chesapeake Biological Laboratory, 

Solomons, MD 
T. J. Vigerstad, E. I. du Pont de Nemours and Co., Inc., 

Aiken, SC 
J. V. Ward, Colorado State University, Fort Collins, CO 
R. S. Warren, Connecticut College, New London, CT 
J. R. Webster, Virginia Polytechnic Institute and State 

University, Blacksburg, VA 
I. M. Weis, University of Windsor, Windsor, Ontario 
M. O. Welch, Rice University, Houston, TX 
J. L. Wilhm, Oklahoma State University, Stillwater, OK 

D. R. Wiseman, College of Charleston, Charleston, SC 
T. E. Wissing, Miami University, Oxford, OH 

T. G. Wolcott, North Carolina State University, Raleigh, 
NC 

D. A. Wolfe, National Oceanic and Atmospheric Ad- 
ministration, Boulder, CO 

E. A. Woolson, U. S. Department of Agriculture, 
Beltsville, MD 

J. C. Zieman, University of Virginia, Charlottesville, VA 

R. G. Zingmark, University of South Carolina, Colum- 
bia, SC 

V. Zitko, Environment Canada Biological Station, St. 
Andrews, New Brunswick 

L. S. Zubarik, New York University Medical Center, 
Tuxedo, NY 



CONTENTS 



Modeling Stresses 

Modeling Environmental Stress 1 

R. E. Ulanowicz* 
Frequency Response of a Marine Ecosystem 
Subjected to Time-Varying Inputs 19 

R. L. Dwyer, S. W. Nixon, C. A. Ouiatt, 

K. T. Perez, and T. J. Smayda 
Applying Survival Curves to Assessment of 
Fish Larval Entrainment Impact 39 

M. D. Dahlberg 
A Simple Model for Assessing the Potential 
Loss of Adult Fish Resulting from 
Ichthyoplankton Entrainment 49 

W. P. Saunders, Jr. 

Natural Stresses and Environmental Fluctuations 

Stress and Ecosystems 62 

A. E. Lugo"^ 
Ecosystem Responses to Stress in Aquatic 
Microcosms 102 

J. W. Leffler 
Physicochemical and Biological Stressors as 
Distributional Determinants of Caribbean and 
Tropical Eastern Pacific Swimming Crabs .... 120 

E. A. Norse 
Effects of Fluctuating Flow Rates and Water 
Levels on Chironomids: Direct and Indirect 
Alterations of Habitat Stability 141 

A. P. Covich, W. D. Shepard, E. A. Bergey, 

and C. S. Carpenter 

*Invited speaker. 

xvii 



XVIII 



CONTENTS 



Fossil- Fuel Stresses 

Environmental Implications of Coal-Conversion 
Technologies: Organic Contaminants 157 

C. W. Gehrs'' 
The Stream Environment and Macro invertebrate 
Communities: Contrasting Effects of Mining in 
Colorado and the Eastern United States .... 176 

J. V. Ward, S. P. Canton, and L. J. Gray 
Meiofaunal Abundance in Sandbars of Acid 
Mine Polluted, Reclaimed, and Unpolluted 
Streams in Southeastern Ohio 188 

W. D. Hummon, W. A. Evans, M. R. Hummon, 

F. G. Doherty, R. H. Wainberg, and 

W. S. Stanley 
Cytotoxicity of Untreated Coal-Conversion 
Gasifier Condensate 204 

T. W. Schultz, J. N. Dumont, and 

L. M. Kyte 
Aquatic Toxicology of Trace Elements of Coal 
and Fly Ash 219 

W. J. Birge 



Heavy-Metal Stresses 

Mercury Contamination Standards for Marine 
Environments 241 

R. Eisler* 
A Radioisotopic Study of Mercury Uptake 
by Hudson River Biota 273 

L. S. Zubarik and J. M. O'Connor 
Impact of Arsenicals on Nitrification in 
Aqueous Systems 290 

H. W. Holm and M. F. Cox 
Copper Sensitivity of Adult Pacific 
Oysters 301 

F. L. Harrison and D. W. Rice, Jr. 
An In Situ Study of Cadmium Stress in a 
Natural Zooplankton Community 316 

J. S. Marshall and D. L. Mellinger 



*Invited speaker. 



CONTENTS xix 



Thermal Stresses 



Thermal Ecology and Stress: A Case History 

for Red-Sore Disease in Largemouth Bass .... 331 

G. W. Esch"^ and T. C. Hazen 
Size-Fractionated Primary Productivity in 
Lake Michigan near the Kewaunee Nuclear 
Power Plant 364 

S. I. Zeeman and R. Grunewald 
Primary Productivity: Analysis of 
Variance in a Thermally Enriched 
Reservoir 381 

M. O. Welch and C. H. Ward 
Nitrate Reductase Activity and Primary 
Productivity of Phytoplankton Entrained 
Through a Nuclear Power Station on 
Northeastern Long Island Sound 392 

B. B. Peck and R. S. Warren 
Growth of Duckweed Under Constant and 
Variable Temperatures 410 

R. R. Sharitz and J. C. Luvall 
Growth and Ecology of Spartina alterniflora 
in Maine After a Reduction in Thermal Stress . . 420 

M. Keser, B. R. Larson, R. L. Vadas, and 

W. McCarthy 
Effects of Reduced Temperatures on Previously 
Stressed Populations of an Intertidal Alga . . . 434 

R. L. Vadas, M. Keser, and B. Larson 
Genetic and Physiological Flexibility of 
a Calanoid Copepod in Thermal Stress 452 

B. P. Bradley 
Effects of Thermal Effluents on Reproduction 
in a Sea Anemone 470 

B. L. Jennison 
A Comparison of Morphometric, Biochemical, 
and Physiological Indexes of Condition 
in Marine Bivalve Molluscs 484 

R. Mann 
Response of Mosquitofish to Thermal 
Effluent 498 

D. H. Bennett and C. P. Goodyear 



*Invited speaker. 



CONTENTS 



Response of a Mobile Invertebrate to 

Heterothermal Conditions 511 

S. J. Lozano and J. F. Kitchell 

Temperature Selection by Young Topsmelt: 
Laboratory and Field Investigations 522 

K. F. Ehrlich, G. E. McGowen, and 

G. Muszynski 

Movement of Three Species of Fishes Past a 

Thermally Influenced Area in the Coosa 

River, Alabama 534 

J. L. Moss, S. Boonyaratpalin, and 

W. L. Shelton 

Effects of Thermal Effluent on Benthic 
Marine Invertebrates Determined from 

Long-Term Simulation Studies 546 

R. F. Ford, D. G. Foreman, K. J. Grubbs, 

C. D. Kroll, and D. G. Watts 

Effects of Thermal Alteration on 

Macroinvertebrate Fauna in Three Artificial 

Channels 569 

D. E. Alston, J. M. Lawrence, D. R. Bayne, 
and F. F. Campbell 

Effects of Power-Plant Operation on the 

Littoral Benthos of Belews Lake, 

North Carohna 580 

D. R. Lenat 
Effects of Power-Plant Operation on the 
Phytoplankton Community of Belews Lake, 
North Carohna 597 

P. H. Campbell 

Effects of Power-Plant Operation on the 
Zooplankton Community of Belews Lake, 

North Carolina 618 

T. P. Anderson and D. R. Lenat 

Stochastic Approach to Predict Survival of 
Estuarine Animals Exposed to Hot Discharge 

Effluent 642 

K. S. Chung and K. Strawn 

Pathogenic Species of Thermophilic and 
Thermotolerant Fungi in Reactor Effluents 

of the Savannah River Plant 663 

M. R. Tansey and C. B. Fliermans 



CONTENTS xxi 

Responses of the Alligator to Infection and 

Thermal Stress 691 

A. B. Glassman and C. E. Bennett 

Acclimation States of Juvenile Striped Bass 
Held in Constant and Fluctuating Temperature 

Regimes 703 

D. K. Cox 

Effects of Acute and Chronic Thermal Exposures 
on the Eggs of Three Hudson River Anadromous 
Fishes 714 

R. L. Kellogg, J. J. Salerno, and 

D. L. Latimer 



Multiple and Synergistic Stresses 

Multiple-Factor and Synergistic Stresses in 

Aquatic Systems 726 

F. J. Vernberg* 

Ordination of Macroinvertebrate Communities 

in a Multistressed River System 748 

D. C. Beckett 

Longitudinal Variation in the Macroinvertebrate 
Fauna and Water Chemistry of an Eastern 

Pennsylvania Trout Stream 771 

P. T. Bradt 

The Effect of Ionizing Radiation on the 

Thermal Tolerance of Mosquitofish 785 

B. G. Blaylock and M. L. Frank 

Responses of Ichthyoplankton to Stresses 
Simulating Passage Through a Power-Plant 
Condenser Tube 794 

G. V. Poje, T. C. Ginn, and 
J. M. O Vonnor 

Effects of Simulated Entrainment on the 

Biology of a Freshwater Cladoceran 809 

A. L. Buikema, Jr., S. R. Sherberger, 

G. W. Knauer, L. A. Newbern, J. T. Reading, 

and J. Cairns, Jr. 



* Invited speaker. 



XXII 



CONTENTS 



The Avoidance Response of the Common Shiner to 

Total and Combined Residual Chlorine in 

Thermally Influenced Discharges 826 

D. S. Cherry, S. R. Larrick, J. D. Giattina, 

K. L. Dickson, and J. Cairns, Jr. 

Author Index 838 

Subject Index 840 



MODELING ENVIRONMENTAL STRESS 



ROBERT E. ULANOWICZ 

University of Maryland, Center for Environmental and Estuarine Studies, 

Solomons, Maryland 



ABSTRACT 

The word stress when applied to ecosystems is ambiguous. Stress may be 
low-level, with accompanying near-linear strain, or it may be of finite magnitude, 
with nonlinear response and possible disintegration of the system. Since there 
are practically no widely accepted definitions of ecosystem strain, classification 
of models of stressed systems is tenuous. Despite appearances, most ecosystem 
models seem to fall into the low-level linear response category. Although they 
sometimes simulate systems behavior well, they do not provide necessary and 
sufficient information about sudden structural changes nor structure after 
transition. Dynamic models of finite-amplitude response to stress are rare 
because of analytical difficulties. Some idea as to future transition states can be 
obtained by regarding the behavior of unperturbed functions under limiting 
strain conditions. Preliminary work shows that, since community variables do 
respond in a coherent manner to stress, macroscopic analyses of stressed 
ecosystems offer possible alternatives to compartmental models. 



Unfortunately, the term stress is not used uniformly in ecological 
discussions. It comes to our discipline from mechanics, physiology, 
and psychology and brings different shades of meaning from each 
source. In clarifying what is meant by stress and its consequences, it 
is useful to refer to the meaning given to the word by nineteenth 
century engineers. 

Stress represented "the forces or pressures exerted upon a 
material" (Meier, 1972). In mechanics, stress had no utility without 
its conjugate, strain, "a measure of the deformation brought about 
by the action of the stresses." The relationship between applied 
stress and observed strain (e.g., the elongation of a metal rod under 



2 ULANOWICZ 

tensile stress) was presumed linear. Twice the stress resulted in twice 
the strain. 

The modulus of elasticity (the ratio of strain to stress) as a 
property of a solid is useful if we are designing a structure such as a 
bridge, but it is often necessary to know also the behavior of a solid 
system under extreme stresses. In fact, as the stress on a metal rod 
increases, a point is reached where the strain becomes dispropor- 
tionately larger than the applied force. Not long thereafter the rod 
reaches the critical point; i.e., the strain is such that the rod will no 
longer return to its original state. Still further stress leads to 
increasingly disproportionate strain, culminating in a catastrophe 
when the rod loses its identity (yield point). 

The behavior of a simple mechanical system under heavy stress 
differs markedly from its corresponding response to low stress. It is 
significantly nonlinear, and it culminates in loss of system structure. 
It is this response to heavy stress that is important to psychologists 
and physiologists, for whom stress has come to mean a "response to 
external or internal processes which reach those threshold levels that 
strain its physiological and psychological integrative capacities close 
to or beyond their limits" (Basowitz et al., 1955). 

Stress, therefore, takes on different connotations for the engineer 
and the psychologist. Although it may not be obvious, this dual 
meaning of stress is found in ecological research. Ecologists have 
been slow to define and accept a useful measure of the response of 
the ecosystem to stress, i.e., ecological strain. Just as it is impossible 
to discuss mechanical stress without considering its conjugate, strain, 
the discussion of stress in ecological systems is fragmentary without 
some hypothetical measure of system strain. Before attempting a 
working definition of strain, however, we should consider how stress 
arises in ecosystem models. 

Although ecosystem models may be stochastic, discrete, spatially 
heterogeneous, etc., much of systems analysis, following the lead of 
the early modelers, has concentrated on deterministic, first-order, 
ordinary differential equations, such as (see Lotka, 1957), 

X = f(X,P,t) (1) 

where X is a vector of state variables, t is time, and P is a vector of 
parameters. Parameters of a model include initial conditions, fluxes 
into and out of the system, and characteristics of the functional form 
of f (such as exponents or multiplicative constants). 

The external world may impinge on the ecosystem (exogenous 
stress) through arbitrary variations in P and X; X may change 



MODELING ENVIRONMENTAL STRESS 3 

through cropping or mass infusion of a species; and P may change in 
a number of ways. For example, the multiphers and exponents are 
often strongly dependent on abiotic variables, such as temperature, 
salinity, light, etc. These forcing functions, in turn, may possess both 
regular and stochastic components. The input fluxes, necessary to 
every living system, vary similarly. 

Occasionally complex systems will exhibit the characteristics of 
strain without any apparent imposed stress. The term endogenous 
stress has been coined to describe such phenomena, but the previous 
discussion reveals this to be a misnomer. Nonlinear systems some- 
times produce an output without any corresponding input. "Endoge- 
nous strain" would, therefore, be a more accurate descriptor for such 
behavior. 

Attempting to provide a workable definition for strain in an 
ecosystem, Innis (1975) found it useful to invoke an arbitrary 
function of the state of the system, 

H = h(X, X) (2) 

to measure the deviation from some prescribed state, H*, character- 
ized as unstressed. For example, H* might be taken to be a 
stationary state, i.e., 

H* = h(X*,0) (3) 

where X* is the solution of f(X*, P, t) = 0. Any suitably defined 
metric could be used to describe the distance between H and H*, i.e., 
the ecological strain: 

S= ||H-H*|| (4) 

As Innis remarked, whether any particular deviation is indicative 
of a stressed system is somewhat arbitrary and depends largely on the 
context of the discussion. Woodwell (1975), for example, argued 
against the threshold concept in ecology. In his view, any chronic 
stress takes its toll on the ecosystem in the form of a chronic, albeit 
sometimes small, deviation. The linear view of stress would be quite 
useful for his purposes. 

In contrast, HoUing (1973) cited the possibility of multiple 
stationary states for a given ecosystem — several H*, each with its 
own "domain of attraction" characterized by a finite deviation, 
Scrit- Deviations in excess of the critical strain can lead to transition 
into another domain. Furthermore, such transition may incur a 



4 ULANOWICZ 

change in dimensionality of the problem and/or the necessity for a 
new functional descriptor, f, of the system dynamics. Deviations in 
the neighborhood of Scrit are signs of a stressed ecosystem in the 
physiological sense of the word. 

Thus two classes of stress analyses are readily identifiable. In the 
first, there is no explicit mention of a critical deviation, a change in 
dimensionality, or a switch in function (topological form). The 
second class is identified by the prominence of at least one of these 
characteristics. The first class of models will be referred to as local 
and the second as far-field. 

Unfortunately, not all ecosystem stress analyses fall neatly into 
these two classes. There are critics (e.g., Mann, 1975) who find 
compartmental modeling reductionistic. They claim that time would 
be better spent searching for emergent properties of the ecosystem as 
a whole and that these properties would serve as more reliable 
indicators of the response of the community to stress. To press the 
earlier analogy (perhaps a little far!), this is akin to observing the 
strain response of an assemblage of metal rods (such as a bridge truss) 
to various imposed stresses without being concerned with the 
properties of the individual members. Certainly there are character- 
istic dimensions or dimensionless ratios of the total structure at 
which strain responses are indicative of impending collapse. Such 
approaches to ecosystem stress will be termed macroscopic in nature. 

Finally, I indulge in speculation on a principle that I believe 
would crystallize research on ecosystem response and, more impor- 
tantly, might provide a theoretical basis to bridge the gap between 
ecological systems research and evolutionary theory. 

LOCAL ANALYSES OF STRESS 

Most of the ecosystem models in existence today were con- 
structed to elucidate the response of the community to a stress. As I 
see it, most of these efforts have been local in nature. This is not to 
imply that local analyses are necessarily uninteresting or uninforma- 
tive. In fact, some appear to be nonlinear and have been quite 
successful in portraying the response to exogenous stresses. For 
example, the highly reeilistic aquatic ecosystems models of Nixon and 
Kremer (1977), Di Toro et al. (1975), and Park, Scavia, and Clesceri 
(1975) are capable of predicting significant changes in response to 
exogenous stresses (e.g., temperature, nutrient input, and light 
availability). 

As an analysis of stress, however, these simulations are basically 
local. To see this, we should appreciate that most of the exquisite 



MODELING ENVIRONMENTAL STRESS 5 

architecture of the models is in their pairameter specifications. Thus, 
with changing driving forces, the "normal" state, H*, may vary 
considerably according to how^ the instantaneous stationary state, 

f(X*,P, t) = (5) 

varies as P changes with exogenous stress. The behavior function, H, 
will tend to track H* closely. The hypothetical deviation may never 
be large, and the system is not stressed in the far-field sense of the 
word. 

Nevertheless, the dramatic responses of some systems commonly 
referred to as stressed can be shown by a judicious choice of the 
functional dependence of the parameters on exogenous stress. 
Bierman et al. (1973), for example, chose Chlorella and Microcystis 
as two compartments of a nutrient-uptake model. Using separate 
laboratory information to describe the nutrient-uptake kinetics and 
the response to temperature, they investigated zones where one of 
the species dominated starkly. Lassiter and Kearns (1973) simulated 
an annual progression of six species as they dominated the 
phytoplankton of a hypothetical limnetic system. Falco and Mulkey 
(1976), using the law of mass action, anticipated the significant 
differential effect that pesticides can have on populations of bass and 
bluegills. 

In these models all the information about the behavior of the 
system is contained in the functional form f and the parameter 
dependencies. Even when the population structure is predicted to be 
quite unbalanced (e.g., practically all blue-green algae), the system 
may be very near its stationary point, and, hence, by our definition it 
is only slightly stressed. Furthermore, the response is usually almost 
reversible (perhaps retrievable is a better word), meaning that, when 
the external influence is removed, the system returns to near its 
original condition. 

The introductory examples of local low-stress models were 
purposely chosen for their nonlinear construction, but we more 
naturally associate low stress with linearity and, consequently, with 
linear models. Mathematically speaking, linear models have the form 

X = AX (6) 

where the matrix of coefficients is allowed to vary parametrically, 
i.e., A = A(E, t). Any well-behaved nonlinear f can be approximated 
by a~linear system in the neighborhood of a given point in phase 
space. The tremendous advantage of linear systems is the well- 



6 ULANOWICZ 

developed mathematical tools that can be brought to bear on 
them — especially linear stability analysis. 

In terms of the effects of low-level stress on a system, there is 
one key question, "Will the response to the stress remain small, or 
will it grow to the point of disrupting the integrity of the 
community?" For linearized systems the procedure for answering 
this question is well defined and has been reviewed by May (1971). 
All the eigenvalues of the matrix A must have negative real parts. If 
the linear ecosystem model has constant coefficients, this test will 
show whether the model is properly behaved. More frequently, 
however, the coefficients of A vary because of exogenous driving 
forces. In this case the eigenvalues vary also, and, under changing 
conditions, it is possible that some eigenvalue will acquire a positive 
real part (Hcilfon, 1976). Thus we can map out domains of driving 
forces for which the systems response is possibly unstable. 

Much of the literature involving linear stability theory in 
ecosystems has been given over to debating the question of whether 
diversity will better enable an ecosystem to cope with an applied 
stress. MacArthur (1955) suggested such a causal link, and May 
(1973) reviewed the use of linear stability analysis to question this 
hypothesis. Central to the counter argument is the observation that 
increasing the dimensionality and connectivity of a randomly 
assembled system decreases the probability that all eigenvalues will 
be negative. Gardner and Ashby (1970) sampled randomly con- 
structed matrixes to illustrate this point. Others have argued that 
ecosystems are not randomly constructed and that constraints on the 
form of A can lead to different conclusions (Roberts, 1974; 
McMurtrie,~1975; Saunders and Bazin, 1975; Jeffries, 1974). 

The diversity— stability controversy is actually a macroscopic 
issue, and further discussion is best deferred to that section of this 
paper. What is important here is that linear stability results are 
neither necessary nor sufficient to determine the persistence of an 
ecosystem under stress. 

Despite their simplicity, linear models remain a popular medium 
for modeling total ecosystems (Patten, 1975). In fact, there are 
instances where linear models seem preferable for simulating total 
system behavior (Patten, 1976; Ulanowicz et al., 1978). Patten's 
success with linear descriptions led him to propose linearity as an 
evolutionary design criterion (Patten, 1975) — a much criticized 
stance (e.g., Wiegert, 1975). Leaving philosophical considerations 
aside, we see that the preceding discussion of local models of stress 
may help illuminate why linear models are such popular tools. As 
stated earlier, thus far most attempts to model ecosystem response to 



MODELING ENVIRONMENTAL STRESS 7 

stress have been local in nature; i.e., the system closely tracks the 
normal state, H*. Locally there is little difference between linear and 
nonlinear representations. Nonlinear representations tend to be more 
sensitive to parameter changes, however, and sensitivity and stability 
are closely related (Estberg and Patten, 1975). Thus a higher 
percentage of linear attempts at modeling are likely to survive into 
the final stages of an investigation. 

Although they have served ecosystem science well, local models 
of stress response still leave much to be desired. The instability of a 
system to small stress serves as nothing more than a warning signal to 
the ecosystem manager. Local instability is neither necessary nor 
sufficient to cause a system to switch to a different configuration 
when subjected to a finite stress. Furthermore, the analysis reveals 
nothing about the future structure of the system if it should change 
character. Finally, in most local considerations little emphasis can be 
placed on endogenous strain, which may arise from finite excursions 
from the normal state. 



FAR-FIELD STRESS ANALYSIS 

The deficiencies of low-stress models are the cause of many 
ecological managers' suspicions of the modeling process. This point 
was underscored at a recent symposium on ecological modeling in a 
resource-management framework when three investigators — Schaaf 
(1975), O'Neill (1975), and Orlob (1975) — independently cited 
Rolling's multiple steady-state hypothesis and the burning desire of 
ecologist and manager alike to understand more about the "collaps- 
ing" ecosystem syndrome. Managers are necessarily concerned with 
species changes within the systems in their charge. The conditions 
leading to structural changes in the system and the configuration of a 
collapsed or new ecosystem are matters of utmost importance in 
their eyes. 

At the time of the symposium (1975), practically no research on 
the problem of switching between domains of attraction caused by 
finite amplitude stress was widely known. All investigators agreed on 
the need for theoretical research. In addition, Orlob called for 
controlled experimentation on collapsing ecosystems and systems 
subjected to low-level chronic stress. 

The problem of mapping domains of attraction for an ecosystem 
is a formidable task. It is enough to cause a theoretical ecologist like 
May (1975) to remark: "I find it difficult to envision any simple 
number, or handful of numbers, which will quantify the resilience of 
a complicated natural ecosystem." There have been no major break- 



8 ULANOWICZ 

throughs since May's comment to characterize the domain of 
attraction for a given stationary point. The task is as intriguing as it is 
important and formidable, however, and should continue to demand 
the attention of ecologists for several years to come. Nor will the 
problem remain of interest only to theoreticians. Lawton, Bedding- 
ton, and Bower (1974) and Sutherland (1974), for example, have 
shown from empirical data that switching behavior occurs even 
among invertebrates. 

Preliminary is perhaps the best word to describe the investiga- 
tions on finite perturbations to date. An example of the nonreversi- 
bility of a nonlinear system is provided by McQueen (1975). His 
model for competition between two species of cellular slime mold 
exhibits two ranges of persistence in the sense of Rolling. When he 
made the birthrate of one of the species highly dependent on climate 
and then shocked the model with a short burst of favorable climate, 
the model underwent transition from one domain to another where 
the favorably perturbed population was higher. Most interesting, 
however, was the model behavior that 

. . . suggests that a population might fluctuate for long periods of time at a 
low level as it tracks the lower-stable [stationary] point, but given a short 
burst of favorable climatic conditions it could escape and rapidly grow to 
an upper-stable [stationary] level. From that point on, the population will 
remain at a high level tracking the high-stable [stationary point] as it 
moves in response to changing climate. Return to a low level is only 
possible when negative forces increase or when climate is very unfavorable 
to birthrate. 

We can easily envision the reverse situation occurring in a collapsing 
ecosystem. 

Although we cannot yet say with confidence how an ecosystem 
will be structured after it has undergone transition, there are two 
notable attempts to answer this question. 

In the first. Smith (1975) occupied himself with species 
extinctions and the realm of possible stable subsystems that a known 
system may possess. He defined stability in a very fundamental way 
(see also Ulanowicz, 1972); a system is considered stable with regard 
to some defined stress if none of the component species become 
extinct as a result of that stress. In general, when one or more species 
of an ecosystem is removed, either a subsystem that is itself stable (in 
the sense just mentioned) results or one or more of the remaining 
species will drive the subsystem to collapse. Smith began by 
enumerating all possible subsystems by dropping various combina- 
tions of state variables in turn. To test whether any of these is a 
stable subsystem, we must view the behavior. of the system when 



MODELING ENVIRONMENTAL STRESS 9 

stressed arbitrarily near the extinction of one or more species (stress 
in the second sense of the word). That is, if 

Xi = fi(Xi,X2,. .., Xm,Xm+,,. ..,Xn) i=l,2, . ..,n (7) 

then we observe 

Xi = fi(Xi , X2 , . . ., Xm , 0, . . ., 0) i = 1, 2, . . ., n (8) 

where variables Xm+i through Xn were chosen (without loss of 
generality) as those arbitrarily driven to near extinction. Smith then 
listed four criteria the reduced system must satisfy to be stable. For 
example, a stable subsystem cannot be obtained if any one of the fi 
describing an extinct species has become positive as a consequence 
of extinction, i.e., if any 

Xi = fi(Xi , X2 , . . ., Xm, 0, . . ., 0) > i = m + 1, . . ., n (9) 

He concluded his remarks by performing an analysis on a hypotheti- 
cal four-species subsystem and identified three possible stable 
subsystems to which the original system might collapse. 

Concern with environmental degradation in recent years has 
caused ecologists to become somewhat jaded and to focus on 
exogenous stress and its consequent simplification of the impacted 
ecosystem. In far- from -equilibrium nonlinear systems, however, 
endogenous strains occur which allow a chance perturbation (a 
mutant or migration) to flourish suddenly and to become an added 
dimension of the community. In the second example, Prigogine 
(1976) and Eigen (1971) examined this phenomenon as the crucial 
element in the prebiotic evolution of polymers, and Allen (1976) 
extended the analysis to the evolution of new populations in 
ecosystems. The methods used are similar to those used by Smith for 
collapsing systems. 

Despite these interesting insights, the basic nature of structural 
transitions remains an enigma. This is caused in large measure by an 
inclination to think in terms of linear systems. It is not foreign to 
think of a system, an input (exogenous stress), and an output which 
results from that input (stability or instability), but it is discomfiting 
to be confronted with an output whose origin lies predominately 
within the system itself. 

MACROSCOPIC TREATMEIMT OF ECOSYSTEM RESPONSE 

In his presentation of evidence for multiple stable points and 
domains of attraction, Holling (1973) described the system from the 



10 ULANOWICZ 

species or population level. The enormous analytical difficulties in 
properly describing most multistable systems, coupled with the high 
dimensionality of most real ecosystems, has led a number of 
investigators to explore the possibility that response to stress is best 
described in terms of macroscopic or emergent variables. Macro- 
scopic variables are characteristic of the ecosystem as a whole and 
not just parts of it. They may and often do involve some 
combination of lesser order variables, however. There is still no 
consensus as to what consitutes a proper macroscopic variable. 

Several investigators have suggested semiquantitative candidates 
for macroscopic variables as a consequence of their empirical studies. 
Kerr (1974) referred to structural transitions as "emergent surprises" 
and believed that they can be encompassed only by macroscopic 
theory. He cited the particle-size spectrum of an ecosystem as a 
convenient indicator of stress in a community. Exogenous stress 
seems to always affect the larger size organisms disproportionately. 
Jordan, Kline, and Sasscer (1972) emphasized the ratio of recycling 
to input as a system variable that characterizes the recovery time of 
an ecosystem from a temporary stress. Golley (1974) went further; 
he suggested a temporal hierarchy of three system properties to 
describe recovery from traumatic stress. First, the system responds to 
restore its extensive variables (mass); second, the functional options 
(topological diversity) increase; and, in the final stages of return to 
undisturbed climax, its response time to disturbance lengthens. 

Presently the reconciliation of microscopic and macroscopic 
properties of an ecosystem is hampered by the inability of ecological 
theory to provide appropriate methods for observing community 
properties (Kerr, 1974). Actually this hierarchical problem has 
always been extremely important in ecological modeling. There are 
many opinions on how to aggregate organisms, species, etc., into 
trophic compartments or functional units (see Halfon, 1978), and it 
is especially difficult in highly connected or "webbed" ecosystems. 

To address this problem, Kemp and Homer (1977) devised a 
method for assigning fractions of the energy storage in a given species 
compartment to various trophic levels. The key to their algorithm is 
the matrix of partial feeding coefficients, which describes the 
percentage of the total input to a given species, i, that flows from 
another species, j. To identify the contents of the fourth trophic 
level, for example, we identify all pathways three steps removed 
from a primary producer. The fraction of the end-point species to be 
assigned to the fourth trophic level is the product of the partial 
feeding coefficients of the three links along a pathway summed over 
all existing three-step pathways. Operationally the transformation is 



MODELING ENVIRONMENTAL STRESS 11 

calculated in a manner similar to Goh's (1975) vulnerability matrix 
(Ulanowicz and Kemp, 1978). 

When Kemp and Homer's transformation is performed on 
energetics data from two comparable marsh ecosystems, one of 
which is impacted by thermal effluent, the results are striking. 
Energy flows through the lower trophic levels remain almost 
unchcQiged, but those through the higher levels fall off drastically 
under the thermal stress. 

The observations of Kerr (1974), Golley (1974), and Kemp and 
Homer (1977) lead to the common conclusion that stress tends to 
result in more-simplified ecosystems. A great deal of debate has been 
devoted to the converse of this proposition, i.e., that more-diverse 
ecosystems are more resilient to stress. This proposition is properly 
macroscopic; i.e., diversity and stability are legitimate community 
properties. Few of the papers addressing this issue treat stability as a 
calculatable characteristic of the system, however. Two exceptions to 
this trend are MulhoUand (1975) and Jorgensen and Mejer (1977). 

Mulholland related the conditional entropy of an ecosystem to 
its buffering capacity. The conditional entropy, which comes from 
information theory, is the difference between the now-familiar 
Shannon— Wiener diversity index and the average mutual informa- 
tion, i.e., the amount of uncertainty about the distribution of energy 
from the various sources resolved by observing the behavior of the 
systems over a given time interval. Rutledge (1974) applied this 
measure to two short-grass prairie ecosystems, one under low- 
moisture stress. Surprisingly enough, the stressed system had higher 
conditional entropy (effective choice of pathways). Mulholland 
resolved this apparent contradiction by hypothesizing that the 
"ecological resilience of a system [which has not undergone 
transition] is maximum when conditions are harshest." 

Jorgensen and Mejer defined the buffering capacity of a 
freshwater lake as the ratio of total phosphorous in the lake plus 
sediments to the steady-state value of soluble phosphorous in the 
lake. They found a tight correlation of this quantity with the exergy 
of the system (exergy is a measure of the mechanical energy 
equivalent of the distance from thermodynamic equilibrium). 

In a third study of change in macroscopic variables in response to 
stress, Lane, Lauff, and Levins (1975) described the changes in 
several of Levins's (1968) community niche values in response to the 
eutrophication of a freshwater lake. Mean niche overlap, average 
competitive success, and mean number of organisms per unit of 
ecological space if no competitors were present, all increased 
significantly with increasing nutrient loading. 



12 ULANOWICZ 

Finally, Harte and Levy (1975), borrowing from an analysis 
popular in physics around the turn of the century, constructed for 
three hypothetical ecosystems a community function whose exis- 
tence ensured that the system would be stable to finite perturbations 
within a given domain. Briefly, if the differential equation 

X = f(X, P) (10) 

possesses a steady state or limit cycle, Xg, and is perturbed to 
Xg + AX, it may or may not return to the neighborhood of Xg. If we 
can construct a function L(AX) (called a Liapunov function) which 
vanishes at the origin, is positive and monotonically increasing with 
AX in some domain about the origin, and has a negative time 
derivative, then the system is stable with respect to perturbations 
within that domain. The function L is not necessarily unique but is a 
conservative estimator of the stability properties of the system (and 
likewise a conservative estimator of the domain of stability). For 
certain classes of functions, f, there are st£indard methods for 
determining whether or not Liapunov functions exist. For these 
particular systems the question of stability is unequivocally resolved. 
In general, however, failure to find a Liapunov function does not 
imply instability of the system. The function may exist but may defy 
analytical description. 

Despite these analytical difficulties, the Liapunov method has 
two things to recommend it. First, it bridges the gap between the 
microscopic (species level) and the macroscopic (L being a commu- 
nity function). Second, it offers the hope of ordinating the various 
domains of stability. Harte and Levy (1975) speculated that if 
succession is in the direction of ever more resiliency to stress, then 

A= -min (i ^ In l)/AX (11) 

provides a measure of the maturity of the system. 

SUMMARY AIMD SPECULATIONS 

There is a historical duality in the scientific meaning of the term 
stress, and this is reflected in the various models of ecosystem 
response to stress. Since strain, the conjugate to stress, is not well 
defined in ecology, discussion of the topic is difficult. If we assume a 
measure of system response to stress, two distinct groups of stress 
analysis arise, local and far-field. 

I have classified most existing models of total ecosystems as local 
because either they are linear or they track the instantaneous 



MODELING ENVIRONMENTAL STRESS 13 

stationary state closely. Analysis of local systems is quite well 
developed, but application of the analytical results to real ecosystems 
is not free from ambiguities. Some of the models exhibit consider- 
able realism and can be used as management tools to identify 
exogenous stresses that might jeopardize ecosystem integrity. 

The observation that ecosystems undergo sudden, radical struc- 
tural changes makes a nonlinear analysis of finite amplitude stress 
imperative. This endeavor is bound to be wrought with analytical 
difficulties. Even the simplest nonlinear model can exhibit bizzare 
behavior (May, 1974), To analyze finite amplitude stress, the 
mathematical ecologist may have to enlarge his skills to include such 
subjects as statistical mechanics, topology, nonlinear optimization 
theory, and variational calculus. The progress in this field treats the 
feasibility of alternate stable states. 

The need for a holistic approach to ecosystem response has long 
been recognized (Odum, 1977), but the development of a macro- 
scopic theory remains in its preliminary stages. Some correlation of 
total system variables to imposed stress has been noted, but much 
more empiricism seems necessary before the inductive leap to 
fundamental principles can be made. 

Despite the remoteness of holistic principles, this review brings 
up several questions that may indicate a fruitful approach to 
macroscopic laws. 

First, the language used in discussing nonlinear ecosystem 
response [e.g., "domain of attraction," "adsorbing set" (Botkin and 
Sobel, 1975), "strange attractor" (May and Oster, 1976)] is intrigu- 
ing. If much of the experimentation with dynamic systems leads to 
the recognition of attractor surfaces, why not make an effort to 
describe the attractor surface, both mathematically and biologically? 

Second, Kerr's (1974) emphasis on reconciling microscopic and 
macroscopic approaches to ecosystem research deserves considera- 
tion. Is it necessary to wait until theories at both levels are well 
developed before the two can be related, or can a single principle 
bridge the gap between them? 

Third, Harte and Levy's (1975) speculation on the ordination of 
various stable states is appealing. What ecosystems manager would 
not rejoice at a quantitative comparison between two ecosystem 
states which distinguishes the more mature? 

Fourth, and most relevant to this discussion, what is a definition 
of total system strain, H, which can be closely related to the 
dynamics of the system? 

Finally, how might the gulf between the systems ecologists and 
the evolutionary biologists be bridged? Like the fluid dynamicist 



14 ULANOWICZ 

who has the field representation of Newton's laws of motion from 
which to deduce the behavior of particular flows, most classically 
trained ecologists explain various species behavior in terms of 
Darwinian selection. Ecosystem models do not derive from any 
fundamental principle, however; they are a patchwork of empirical 
analogies and educated guesses. 

No finished solutions are readily forthcoming, but I would like to 
speculate that all these questions can be addressed by a variational or 
optimizational statement. The clues that this might be so are found 
in the language of both the modeler and the evolutionist. Attractors 
can be described as points or surfaces of maximal properties. The 
evolutionist, in turn, is forever speaking in the superlative. 

Others have hinted at an ecosystem variational principle 
(Glansdorf and Prigogine, 1971; Kemer, 1964; Ulanowicz, 1972). As 
early as 1925, Lotka suggested that living systems act to maximize 
the rate of energy capture. Odum and Pinkerton (1955) elaborated 
on this theme, and H. T. Odum treated the Lotka principle as 
axiomatic in many of his analyses. Energy is used in a very loose 
sense in these discussions. It is likely that one of the later definitions 
[e.g., exergy (Rant, 1956), the energetic measure of the departure of 
a system from the thermodynamic equilibrium state] is more suited 
to the descriptional task. 

Thus we can envision a surface H(X, X) in phase hyperspace such 
that any spontaneous movement along the surface maximizes the 
rate of energy storage (or some other suitable property). Domains of 
attraction are delimited by relative minimums. Attractors are points 
or surfaces of relative maximums. Strain in the ecosystem is defined 
as the distance between H and H*. Presumably H would have its zero 
level at thermodynamic equilibrium so that the values of the relative 
maximums would indicate the maturity of each domain of attrac- 
tion, allowing us to compare different ecosystem structures. Like 
Liapunov functions, H would be a system property defined from the 
components. 

The requisite variational principle would be an extension of 
evolutionary theory. That is, current evolutionary dogma would be 
necessary but not sufficient to explain all the phenomena the new 
principle would presumably encompass. Surely such extension would 
be objected to by many as unnecessary. Some might even complain 
that an ecosystem variational principle smacks of teleology, but a 
glance at the application of variational principles in inanimate 
physics shows this fear to be groundless. Ultimately, however, the 
burden of proof is upon the proponents of the new principle to 
demonstrate the unifying powers alluded to. 



MODELING ENVIRONMENTAL STRESS 15 

Viewed in the context of such a unifying theory, labors with 
disturbed ecosystems take on an added importance. Beyond yielding 
answers to temporal questions of how best to manage impacted 
ecosystems, they provide pieces for the unending puzzle of where we 
come from and where we are headed. 

ACKNOWLEDGMENT 

This is contribution No. 808 of the University of Maryland, 
Center for Environmental and Estuarine Studies. 

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FREQUENCY RESPONSE OF A MARINE 
ECOSYSTEM SUBJECTED 
TO TIME-VARYING INPUTS 



ROBERT L. DWYER,*t SCOTT W. NIXON,* CANDACE A. OVIATT,* 
KENNETH T. PEREZ,t and THEODORE J. SMAYDA* 
*Graduate School of Oceanography, University of Rhode Island, Kingston, 
Rhode Island; and tEnvironmental Protection Agency, Environmental Research 
Laboratory, Narragansett, Rhode Island 



ABSTRACT 

Recent studies have drawn conclusions about the stability and linearity of 
ecosystem response to environmental fluctuations, on the basis of analyses of 
linear mathematical models of several different ecosystems. The validity of 
model stability estimates can be verified only by an independent method that is 
not based on assumptions implicit in the formulation of the model. An 
independent method for deriving frequency response which uses time-series data 
for an environmental input to and biological response from an ecosystem is 
presented. Time series of solar radiation, water temperature, ammonia, and 
phytoplankton abundance, from weekly samples taken in Narragansett Bay, 
Rhode Island, over a 17-year period, and time series of ammonia and chlorophyll 
a from a 6-month sewage-perturbation experiment in 150-liter microcosms 
simulating Narragansett Bay were analyzed by spectral analysis. Spectra for the 
environmental inputs to the bay ecosystem showed periodicities only at 1 
cycle/year, whereas the spectrum for phytoplankton abundance showed addi- 
tional significant periodicities at 2 and 4 cycles/year. These were judged to be 
harmonics resulting from a nonlinearity in the ecosystem. Cross-spectral analysis 
of inputs vs. phytoplankton abundance showed no evidence of linear frequency 
response. Inadequacies in experimental design for the microcosm experiment 
hindered quantitative estimation of microcosm frequency response, but the 
advantage of microcosms in allowing full control during input — response 
experiments is shown. 



The last two decades have been marked by a quantum jump in the 
apphcation of dynamic systems theory to the analysis of ecosystems. 
Mathematical modeling of ecosystems has been undertaken for two 

19 



20 DWYER, NIXON, OVIATT, PEREZ, AND SMAYDA 

purposes, to describe mechanisms regulating the behavior of the 
ecosystem and to predict the effects of disturbances to the system 
(Wiegert, 1975). Debate concerning optimal methods for achieving 
these goals continues. In particular, the level of detail included in the 
model (e.g., the number of state variables or compartments, the form 
of the interaction equations, the possible inclusion of uncertainty in 
model structure and function, the importance of spatial and 
temporal heterogeneity, and methods for model validation and 
sensitivity analysis) has been a topic for lively discussion (Wiegert, 
1975). 

We have focused this study on one controversial aspect of 
modeling philosophy — the usefulness of limiting ecosystem models 
exclusively to systems of linear equations. We show^ that an adequate 
description of ecosystem stability properties cannot always be 
derived from a linearized model of the ecosystem. 

The advantages and drawbacks of linear modeling methods were 
discussed in detail by Wiegert (1975), O'Neill (1975), and Bledsoe 
(1976). They agree that a variety of techniques exist for dealing with 
systems of linear equations and that linear analysis may be valuable 
for the range of behavior over which an ecosystem is known to 
respond linearly. All conclude, however, that there is little a priori 
justification for applying linear methods to all ecosystem studies and 
that the convenience of linear methods is one major reason for their 
use in many ecosystem studies. 

One technique frequently employed is linear frequency response 
analysis. In this paper we evaluate the usefulness of this methodology 
in an instance when the linearity of ecosystem behavior is not 
apparent. 

Child and Shugart (1972) estimated the frequency response of 
their linear model of magnesium cycling in a tropical forest by 
perturbing it with a spectrum of sinusoidal inputs. They used plots of 
response amplitude, normalized with respect to input amplitude, vs. 
frequency and of phase shift vs. frequency to provide information 
about linear system properties. These are the Bode plots familiar to 
engineers [see Fig. 7(a)] and can be used to write a transfer function 
for the system, which is a Laplace-transformed, linear differential- 
equation model. Child and Shugart (1972), Shinners (1972), Brewer 
(1974), or any elementeiry systems text will provide a more thorough 
discussion of Bode plots and frequency-response techniques. 

Waide et al. (1974) used similar frequency domain methods to 
evaluate the stability and sensitivity to perturbations of a linear 
model of calcium cycling in the Hubbard Brook, New Hampshire, 
watersheds, a temperate forest. Webster, Waide, and Patten (1975) 
extended the linear frequency response methods used by Child and 



FREQUENCY RESPONSE OF A MARINE ECOSYSTEM 21 

Shugart (1972) to estimate ecosystem stability and merged with 
them ideas about two aspects of ecosystem stability discussed by 
Holling (1973). These ideas concern the ability of an ecosystem to 
resist displacement from a stable point and its speed of return to the 
stable point after perturbation. 

Holling viewed ecosystems as nonlinear entities capable of 
reorganizing structurally and of assuming different stable states in 
response to perturbation. A system displaced far beyond changes 
caused by normal environmental fluctuations can adapt by modifying 
its structure or function. It may move, perhaps irreversibly, into the 
attractive domain of a new stable point. 

In contrast, Webster, Waide, and Patten (1975) considered 
ecosystem stability in a more restricted sense. They viewed normal 
ecosystem behavior as a linear response to normally occurring 
environmental fluctuations (Patten, 1975). A perturbation large 
enough to cause a structural change as an adaptation replaces the 
original ecosystem with a new one, whose dynamics should be linear 
about a new stable point. 

In this sense, Webster, Waide, and Patten (1975) redefined 
Rolling's two aspects of stability and used two parameters from 
linear frequency -response analysis as estimators of normal ecosystem 
stability: (1) Resistance is the ability of an ecosystem to withstand 
displacement by an input and is estimated, inversely, by the 
undamped natural frequency, cOp, of the system. (2) Resihence is the 
ability of the ecosystem to return to equilibrium once displaced and 
can be estimated by the system damping ratio, ^. Both these 
parameters can be estimated numerically from Bode amplitude and 
phase plots calculated from linear models (see Child and Shugart, 
1972; Waide et al., 1974). Webster, Waide, and Patten derived these 
frequency response parameters for eight different ecosystem models 
by analytical solution of the linear systems of equations. 

Harwell, Cropper, and Ragsdale (1977), using digital and analog 
simulations of the same eight linear models, generated stability 
rankings for the ecosystems which differed from those of Webster, 
Waide, and Patten (1975). The discrepancies may be partially 
explained by the presence of nonlinearities in ecosystem response to 
normal fluctuations. An alternate method for quantifying ecosystem 
stability, one that can verify stability estimates independently of 
assumptions in a linear model, would be useful. 

In this paper we apply a method well known in the physical 
sciences to evaluate the linearity of response to seasonal environ- 
mental fluctuations of one compartment in a natural ecosystem, 
Narragansett Bay, Rhode Island. This method, which is based on 
spectral analysis of time series of input— response data, does not 



22 DWYER, NIXON, OVIATT, PEREZ, AND SMAYDA 

require a quantitative compartment model for the ecosystem. Thus i 
is a "black-box" approach and minimizes the effects of thi 
investigator's biases about the structure and function of the ecosys 
tem under study. 

Since spectral frequency response analysis of ecosystem behavio 
in response to year-to-ye£ir fluctuations provides little informatioi 
about its linearity or stability in response to fluctuations at highe 
amplitudes or frequencies of input, ecosystem experiments usinj 
artificicil inputs of the desired characteristics are required. Eisne 
(1971) proposed this approach to examine the dynamios of ai 
ecosystem perturbed far from a stable point and outlined criteria fo 
input design which optimize the detection of response abov( 
background noise. 

Applying a time-varying input to a whole ecosystem usualh 
presents significant methodological problems. Using controlled 
replicated microcosms to simulate an ecosystem alleviates some o 
the difficulties. Potentially, microcosm "models" can be used t( 
delineate the boundaries of the ecosystem's stable domain, h 
addition to spectral analysis of the Narragansett Bay time series, W( 
describe the results of a first experiment using a sewage input tc 
perturb 150-liter microcosms simulating Narragansett Bay beyonc 
their nominal dynamics. 

MATERIALS AND METHODS 

Description of Data 

The dynamics of phytoplankton abundance in Narragansett Bay 
have been described in detail (Smayda, 1976, and the literature cited 
therein). Smayda and his students have sampled a station in the West 
Passage of the bay at weekly intervals since 1959. Using this long 
time series of physical and biological data, we discuss solar radiation, 
surface water temperature, surface ammonia concentration, cind total 
phytoplankton abundance (Fig. 1). Solar-radiation and water- 
temperature values are for the day of sampling and represent ar 
essentially complete record for the period from 1959 to 1975 
Averages of solar radiation and temperature weighted over the days 
preceding sampling would probably model phytoplankton growth 
processes more realistically. Complete temperature data and informa 
tion to generate the appropriate weighting functions were not readily 
available, however, so unweighted grab measurements were used in 
these analyses. Surface nutrient sampling was begun in 1972. 
Ammonia, nitrate, nitrite, and phosphate all show the same 
qualitative pattern. Ammonia alone is used because its fluctuations 



FREQUENCY RESPONSE OF A MARINE ECOSYSTEM 



23 



800 



o ™ 

QC — "D 

< I- ^ 400 
S Q °' 




(a) 




(b) 



SURFACE 

AMMONIA, 
jug atom N/liter 

o o c 


1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 


1 1 1 1 1 1 1 1 1 1 1 _i — 1 — 1 — 1 — 1 — 



64,000 




I I I I I "ll i I I I I T 
1960 1962 1964 1966 1968 1970 1972 1974 



Fig. 1 Time-series data taken at weekly intervals in Narragansett 
Bay, Rhode Island, from 1959 to 1975. Ammonia (c) sampling was 
begun in 197 2. Phytoplankton cell abundances (d) were counted 
beginning in 1960. Samples for 1975 have yet to be counted. 



24 DWYER, NIXON, OVIATT, PEREZ, AND SMAYDA 

are most pronounced and because there is evidence that it cycles 
more rapidly than other nutrients in the bay. Phytoplankton 
abundcinces, by species, were counted beginning in 1960. Since 
samples for 1975 have yet to be processed and digitized, they are not 
included in the cell-count time series. 

Since spectral analysis requires complete time-series data, it was 
necessary to interpolate missing data points linearly. For each time 
series the total number of interpolated points was less than 10% of 
the total number of data points. 

Solar-radiation and temperature time series show strong deter- 
ministic oscillations at 1 cycle/year, but the periodicity for ammonia 
is less clear, and that for total phytoplankton abundance is 
undistinguishable. The frequency structure of these time series is 
manifest only after transformation to the frequency domain by 
spectral analysis. 

As part of a multiphase approach to studying the Narragansett 
Bay ecosystem, a set of 150-liter, scaled, benthic— pelagic micro- 
cosms were developed and are being used in perturbation experi- 
ments (Nixon et al., 1978; Oviatt, Perez, and Nixon, 1977; Perez 
et al., 1977). Data used here are from a sewage stress— relaxation 
experiment described by Oviatt, Perez, and Nixon (Fig. 2). We chose 
ammonia and chlorophyll time series from a microcosm receiving a 
high sewage step input (microcosm 2, Fig. 2). Since the microcosms 
were not sampled at regular intervals (there was sometimes a day's 
delay in sampling), it was necessary to approximate the complete 
time series by use of linearly interpolated points (11% of the total 
time series). These microcosm time series are much shorter than 
those from Narragansett Bay, and the ammonia series was sampled 
twice per week. 

Systems and Holistic Responses 

The trend toward developing holistic measures of natural 
ecosystem dynamics has led to perturbation experiments on ecosys- 
tem models (Child and Shugart, 1972; Waide etal., 1974; Harwell, 
Cropper, and Ragsdale, 1977) in which one or more model 
compartments or inputs are artificially displaced. Harwell, Cropper, 
and Ragsdale showed that estimated model stability (e.g., in terms of 
natural frequency and damping ratio) may depend crucially on what 
is perturbed, how large the perturbation amplitude is, and what is 
measured as the response. Perturbations applied to real ecosystems 
may generate responses that are functions of the timing of 
application as well as of system state. This may be especially 



FREQUENCY RESPONSE OF A MARINE ECOSYSTEM 



25 




> 

I 

O- 

O 

cc 
O 

_i 
X 



(a) 




3/15 " 4 4 I 4/24 ' 5/14 ' 6/3 ' 6/23 ' 7/13 ' 8/2 ' 8/22 ' 9/11 ' 10/1 
3/25 4 '14 5 '4 5/24 6/13 7/3 7/23 8/12 9/1 9/21 

SAMPLING DATES 

(b) 

Fig. 2 Ammonia (a) and chlorophyll (b) concentrations in one of 
several replicate microcosms (No. 2) receiving a 3-month sewage 
input (between arrows). One representative control, microcosm 
No. 5, is also shown (adapted from Oviatt, Perez, and Nixon, 1977). 



important for perturbations that temporarily or permanently disrupt 
feedback pathways (e.g., clear-cutting of forests). 

In practice, defining system boundaries, inputs, and outputs can 
be troublesome. An exogenous environmental input, by definition, is 
one that affects, but is not affected by, system state. Solar radiation, 
rainfall, and temperature fit this definition. An output can be any 
compartment monitored by the investigator, or it can be transport of 
material beyond the system boundary, where it no longer modifies 
system functions. 

Thus the operational definition of ecosystem response has 
depended to a great extent on what outputs researchers were 
equipped to measure. As yet, not a great deal of thought has been 
given to defining which outputs or compartments should be 
monitored to elucidate important aspects of ecosystem stability. The 
response linearization hypothesis of Patten (1975) may be correct 
for some types of outputs but not for others. 



26 DWYER, NIXON, OVIATT, PEREZ, AND SMAYDA 

Defining boundaries, inputs, and outputs is obviously easier for 
some ecosystems. For example, the Hubbard Brook watersheds 
(Waide etal., 1974) have easily measurable inputs, and all material 
output flows through a weir where it can be monitored. Defining 
system boundaries in Narragansett Bay is much more difficult, and 
defining fluxes across an operationally established estuarine— oceanic 
boundary is a major research task in itself (Kremer and Nixon, 
1977). 

Our spectral analysis of Narragansett Bay is constrained by the 
availability of suitable data. The analysis is a detailed examination 
of the in-system and closed feedback-loop dynamics (Child and 
Shugart, 1972; Shinners, 1972) of the primary producer compart- 
ment of the Narragansett Bay ecosystem. We make no claims that the 
frequency responses we calculated represent those of the whole 
system. If Patten's (1975) linearization proposal is correct, however, 
the many nonlinear submechanisms governing this compartment 
(e.g., pronounced high-frequency phytoplankton species succession 
and saturation kinetics for light and nutrients) will be minimized in a 
tendency toward linearization of the frequency response of primary 
production. 

One input to primary production, surface ammonia, is an 
integrating compartment in the ecosystem. It is taken up preferen- 
tially by phytoplankton in Narragansett Bay and is limiting most of 
the year. Through feedback mechanisms, ammonia concentration is 
affected by primary producers. Ammonia concentration is also 
modified by an exogenous input (i.e., river runoff), which carries 
ammonia from numerous sewage treatment plants, and by wind- 
driven water turbulence, which modifies nutrient regeneration by 
benthic sediments. Exact analysis of this problem requires a detailed 
signal -theory approach, which was not attempted for this analysis. 
Thus we must make the simplifying assumption that the effect on 
ammonia concentration of primary production fed back through the 
food web is small compared v^th the direct effect of ammonia on 
primary producers. This assumption is supported by measurements 
of zooplankton ammonia excretion, which show that throughout 
most of the year only a small portion of the primary production in 
the bay is supported by nitrogen that has been rapidly regenerated 
through the herbivores (Vargo, 1976). The assumption is even more 
nearly correct for the microcosm experiments, in which high levels of 
ammonia were added artificially. Ammonia levels in control micro- 
cosms (modified only by internal feedback mechanisms) remained 
much lower than those in microcosms receiving an artificial input 
(Fig. 2). 



FREQUENCY RESPONSE OF A MARINE ECOSYSTEM 27 

Spectral-Analysis Methods 

Spectral analysis may be considered a statistical method for 
partitioning the variance of a time series of data among a range of 
frequencies of oscillation. Spectral analysis performs a function 
analogous to that of a prism breaking a beam of light into its 
component fractions at various wavelengths (colors) (see Fig. 3). For 
the interested reader without a strong mathematical background, we 
suggest several relatively nontechnical papers on spectral analysis 
(e.g., Gunnerson, 1966; Wastler, 1969; Piatt and Denman, 1975). In 
our presentation here we minimize the mathematics underlying 
spectral analysis. Unless otherwise noted, all techniques, including 
equations incorporated into FORTRAN IV computer programs 
(Weisberg, 1974), are taken directly from Bendat and Piersol (1971). 

Basically, spectral analysis takes time-series data sampled at 
regular intervals from a repeating periodic process, filters it to 
remove unwanted contaminating signals, removes aiiy linear trend, 
tapers the two ends of the data smoothly to zero (to avoid placing a 
spurious artifact in the frequency spectrum), and computes the 
coefficients of a discrete Fourier series with one of several available 
numerical algorithms (see Piatt and Denman, 1975). We used a Fast 
Fourier Transform (FFT), which yields a series of Fourier coef- 
ficients equal in length to one-half the number of data points. These 
coefficients yield the variance spectrum for the time series directly. 

A confidence interval about the height of each spectral estimate 
can be calculated by a moving average of several adjacent spectral 
estimates. However, decreasing the width of the confidence interval 
necessitates broadening the frequency bandwidth resolution of the 
analysis. Thus, typically, an investigator must decide between 
estimating the heights of a few spectral peaks with great confidence 
or estimating more peak heights with a corresponding decrease in 
confidence. 

Once calculated in this manner, spectral estimates for two time 
series connected by a causal relationship can be analyzed using 
cross-spectral techniques. A detailed derivation is beyond the scope 
of this paper, but several resulting parameters are of great interest. 
Coherence squared (7^ ) can be considered as a correlation coefficient 
between the two time series, varying from 0.0 to 1.0; i.e., as an 
estimate at each frequency of the proportion of the variance in one 
time series which can be explained in terms of variance in the other. 
When a significance test of the squared coherence between two time 
series can be shown to be statistically different from zero over a 
range of frequencies (Amos and Koopmans, 1963), a cause— effect or 
input— response relationship exists between the two variables at the 



28 



DWYER, NIXON, OVIATT, PEREZ, AND SMAYDA 



INTENSITY OF LIGHT 



LIGHT 
BEAM 




LIGHT 
BEAM 



RED 

ORANGE 

YELLOW 

GREEN 

BLUE 

VIOLET 



LIGHT 
FREOUENCY 
SPECTRUM 



(a) 





RED 
YELLOW 

VIOLET 



LIGHT 
FREQUENCY 
SPECTRUM 



o>- 


7' 


U 


to 
< 

LU 
IT 


LU 

a 


7" 


LU 








 



(b) 



LIGHT 
INTENSITY 
SPECTRUM 



INTENSITY OF LIGHT 















SPECTRAL 
ANALYSIS 


t^^y^^ 


. <'± 


DATA 




± LL 


RECORD 







LIGHT 
INTENSITY 
SPECTRUM 



MAGNITUDE OF VARIANCE 




t POWER SPECTRUM 

OR 
VARIANCE SPECTRUM 



(0 



Fig. 3 Spectral analysis operating on time-series data is analogous to 
a prism breaking a beam of light into its colors or wavelengths (from 
Wastler, 1969). (a) Prismatic resolution of a beam of sunlight, (b) 
Prismatic resolution of a beam of light, (c) Resolution of a data 
record by spectral analysis. 



FREQUENCY RESPONSE OF A MARINE ECOSYSTEM 



29 



INPUT TIME- 
SERIES DATA 




RESPONSE 

TIME-SERIES 

DATA 


\ 




1 


CALCULATE 
VARIANCE 
SPECTRUM 




CALCULATE 
VARIANCE 
SPECTRUM 




' 






, , 






CALCULATE 

COHERENCE SQUARED, 

PHASE, AND AMPLITUDE 

OF TRANSFER FUNCTION 






NO 



NONLINEAR MODELING 

AND FREQUENCY 

RESPONSE METHODS 



ESTIMATE 

NATURAL FREQUENCY 

AND DAMPING RATIO 



Fig. 4 Input— response spectral methodology for verifying linearity 
of ecosystem response and estimating frequency response of 
ecosystem. 



significant frequencies. If squared coherence is significant over a 
broad band of frequencies, two more statistics can be calculated. 
These are the amplitude ratio and phase as functions of frequency. 
When plotted, these are the Bode frequency response plots described 
previously (see Fig. 7). Rather than being generated from a mathe- 
matical model, however, they are calculated directly from real data 
measured in the field or the laboratory. If the input— response 
transfer behaves linearly (i.e., if it has a significant squared coherence 
and amplitude and phase plots resembling those of linear systems), 
then a Laplacian transfer function model, the natural frequency 
(cOn), and the damping ratio (f), all can be estimated graphically 
(Brewer, 1974). Again, we should note that this whole process 
(Fig. 4) represents a black-box approach in which only a qualitative 
cause— effect hypothesis is necessary. We use it to evaluate the 
linearity of the Narragansett Bay ecosystem. 



30 DWYER, NIXON, OVIATT, PEREZ, AND SMAYDA 

RESULTS 

All time-series data were tested for stationarity (constant mean 
and variance) and for long-term linear trends. No time series showed 
a significant slope over its entire length. Phytoplankton cell 
abundance, the most variable time series, was broken arbitrarily into 
six segments, each 2.5 years long, and slope, mean, and variance were 
calculated for each segment. Since there were no significant 
differences among any of the three statistics, the phytoplankton was 
judged to be stationary. The solar-radiation, temperature, and 
ammonia data were judged to be stationary by inspection (Fig. 1), as 
were the time series for ammonia and chlorophyll in microcosm 2 
(Fig. 2). 

Variance spectra were computed for the four bay time series 
(Fig. 5), as previously described, by modifying the Weisberg (1974) 
computer programs and were plotted with the graphics program of 
Kramer and Weisberg (1975). A 95% confidence interval, used in 
testing peak-height significance, is shown around phytoplankton 
spectral estimates [Fig. 5(d)] . The resolvable frequency bandwidth B 
and the number of adjacent spectral estimates over which moving 
averaging was done are given in the figure legend. 

Variance spectra for solar radiation, temperature, and ammonia 
[Fig. 5(a), 5(b), and 5(c)] are similar in that they all show only one 
peak centered at 1 cycle/year. The flat, low-variance portion of the 
spectra at higher frequencies (up to 26 cycles/year) is an example of 
"white noise" or of a random process having variance equally 
distributed over all frequencies (or "colors"). White noise represents 
measurement errors, spatial heterogeneities, or other random errors. 
The errors are quite small for easily measured, relatively determinis- 
tic variables like solar radiation, temperature, and ammonia. 

The variance spectrum for phytoplankton abundance [Fig. 5(d)] 
shows many more peaks and a high-frequency background white- 
noise spectrum (e.g., > 10 cycles/year) of higher amplitude than the 
input data. In particular, spectral peaks centered at 1, 2, and 4 
cycles/year all appear to have confidence intervals that do not 
overlap those of the background white noise or of the "valleys" on 
either side of the peaks. We have found no evidence to indicate that 
these higher frequency peaks are an artifact of our method of 
analysis. A tendency for spectral peaks to "leak" variance to adjacent 
frequency bands was almost completely suppressed by use of a 10% 
cosine taper window (Bendat and Piersol, 1971). We know of no 
environmental inputs that might pulse the Narragansett Bay ecosys- 
tem at 2 or 4 cycles/year. Other possible environmental inputs, river 



FREQUENCY RESPONSE OF A MARINE ECOSYSTEM 



31 



1000 



500 - 




(a) 



3000 




1 



24 26 



4 8 12 16 

FREQUENCY, cycles/year 

(d) 

Fig. 5 Variance spectra for four Narragansett Bay time series. Each 
spectral estimate smoothed over seven adjacent frequency bands, (a) 
Solar radiation (1959—1975), B = 0.325 cycles/year, (b) Surface 
water temperature (1959—1975), B = 0.325 cycles/year, (c) Surface 
ammonia concentration (1972—1975), B = 1.31 cycles/year, (d) 
Phytoplankton cell abundance (1960—1974), with 95% confidence 
interval; B = 0.325 cycles/year. 



32 DWYER, NIXON, OVIATT, PEREZ, AND SMAYDA 

runoff and wind-driven water turbulence being probably the most 
important, have not been analyzed quantitatively. River flow varies 
seasonally, however, with an apparently random storm-runoff com- 
ponent superimposed on the yearly sinusoid. 

These higher frequency processes appear to be harmonics of the 
fundamental driving frequency of 1 cycle/year. The presence of 
significant oscillations in the phytoplankton data at frequencies not 
found in any of the major environmental inputs indicates the 
existence of a nonlinearity in the primary production of the 
ecosystem. These even harmonics are commonly observed in systems 
where the response is proportional to the square of an input or to a 
cross product of two inputs. We have not as yet found a specific 
mechanism in Narragansett Bay which might generate these harmon- 
ics. 

Sampling of sewage input and phytoplankton response in the 
6-month microcosm experiment was not designed with spectral 
analysis in mind. A square-wave sewage input of 3-month 's duration 
(between arrows. Fig. 2) was attempted. One microcosm receiving 
sewage and one control (representing many replicates) are shown. 
The Fourier transformation used in spectral analysis treats this single 
square wave as a repeating process occurring twice per year; this is 
the primary spectral peak in both ammonia input and chlorophyll 
response (Fig. 6). Although theoretically an impulse or step input to 
a system can yield all the information necessary to calculate system 
frequency response, the actual generation of the infinite slope 
characteristic of impulses and step inputs is virtually impossible in 
the real world. Spectra for both ammonia input and chlorophyll 
response show secondary peaks at even multiples of 2 cycles/year 
and a large variance (caused by lack of stationarity) at zero 
frequency. These tend to mask the possible presence of true 
harmonics caused by ecosystem nonlinearities. 

Despite our inability to ascertain through this experiment the 
degree of linearity in our microcosm models, we feel that input of a 
true sinusoid that repeats many times in the course of an experiment, 
combined with regular high-frequency sampling, will yield time-series 
data adequate for estimating ecosystem stability and linearity. 

In another attempt to find linear behavior, cross-spectral 
analysis for the bay and microcosm time series were performed for 
all possible single inputs to the phytoplankton compartment. Three 
examples, representative of the other results, are presented here. 

First, portions of the ammonia and phytoplankton time series 
which overlap (1972—1974) were used to compute spectra. Cross- 
spectral analysis of these two spectra generated estimates of 



FREQUENCY RESPONSE OF A MARINE ECOSYSTEM 



33 



6000 



4800 



3600 - 




T 

20 30 

FREQUENCY, cycles/year 

(b) 



r 

40 



T 

50 



Fig. 6 Variance spectra, with 95% confidence interval, for ammonia 
(a) and chlorophyll (b) in microcosm 2. Each spectral estimate is 
smoothed over three adjacent frequency bands. B = 4.21 cycles/year. 
These are similar to spectra for other sewage treatment replicates. 
Spectra for control replicates were much less peaked. 



34 DWYER, NIXON, OVIATT, PEREZ, AND SMAYDA 

coherence squared and the Bode amplitude and phase plots 
[Fig. 7(b)] . Coherence squared was not significant over most of the 
frequency range. Since cross-spectral frequency response analysis 
evaluates the linear dependence, measured by coherence squared, of 
response on the input, there appears to be little linear relation 
between the two spectra. The Bode plots show chaotic behavior at 
frequencies higher than 1 cycle/year; this again indicates a poor 
linear relation. Cross-spectral analyses of the complete solar-radiation 
and phytoplankton-abundance time series [Fig. 7(c)] and of the 
microcosm ammonia and chlorophyll time series [Fig. 7(d)] show 
similar random frequency responses. 

Bode amplitude and phase plots show very definite forms when a 
linear relation exists [see Child and Shugart, 1972; Fig. 7(a)] . When 
calculated from time-series data from a quasilinear system, they can 
provide information on the minimum complexity needed in an 
ecosystem model, as well as estimates of system stability properties. 
Our inability to use them here stems from the nonlinearity of the 
system and from the fact that significant periodicities are represented 
in only a very narrow frequency range in the data (1 to 4 
cycles/year). Variance at higher frequencies represents only the 
random portion of the data, and, by definition, the coherence 
between two random time series is not significant. Thus the 
high-frequency portions of the Bode plots represent essentially 
random variation. 



DISCUSSION 

A major difficulty in applying cross-spectral methods to data 
from natural ecosystems, as pointed out by the results of this study, 
is the fact that natural environmental inputs fluctuate only at a few 
frequencies. Marine ecosystems receive few stationary inputs at 
frequencies other than once per year, once per day, or once per tidal 
cycle. [Although wind-driven turbulence inputs can influence 
phytoplankton at very high frequencies (Piatt and Denman, 1975, 
and the literature cited therein), these fluctuations cannot be 
resolved with the 1-week sampling used here.] Coherence between 
natural-input time series and ecological responses will be significant 
only at these input frequencies, regardless of what other periodicities 
are present in response spectra. The high-frequency portions of the 
spectra in this study (Figs. 5 and 6) show no significant variance 
other than that associated with sampling errors. 

In practice, applying artificial periodic inputs to natural ecosys- 
tems presents many logistical difficulties. The use of laboratory 



FREQUENCY RESPONSE OF A MARINE ECOSYSTEM 



35 




T 1 r 

0.1 CO CO 10 - 




(a) 



n 1 r 

0.1 CO CO 10 CO 



< 

□c 

LU 
D 

I 10 
< 

10^ 
10" 
10" 




II 1! 


[ 
0.5 


5 



1 10 




(b) 



< 4 

Q. 



T1 — n 




(c) 



— n — *" 

0.5 I 5 I 

1 10 



10' 



10^ 



1 — \ — r 




io""-i — |— 

2 5 10 




-4 



FREQUENCY, cycles/year 



-| — I — r 

2 5 10 



(d) 



Fig. 7 Bode amplitude and phase plots generated by cross-spectral 
analysis of an input and a response, (a) Plots from a hypothetical 
second-order linear system, oj^ ^nd <;" can be estimated graphically, 
(b) Plots of Narragansett Bay ammonia vs. cell abundance, (c) Plots 
of Narragansett Bay solar radiation vs. cell abundance, (d) Plots of 
microcosm 2 ammonia vs. chlorophyll. 



36 DWYER, NIXON, OVIATT, PEREZ, AND SMAYDA 

microcosms alleviates most problems by permitting complete envi- 
ronmental control and making frequent sampling easy. Replicated 
laboratory microcosms subjected to broad-band white-noise inputs 
produce flatter response spectra than those produced by natural 
narrow-band inputs [Fig. 5(d)]. The flatter input and response 
spectra tend to show more coherence and, thus, are more amenable 
to cross-spectral frequency response analysis. 

Since there is evidence of a nonlinearity in the Narragansett Bay 
ecosystem, we investigated the possible use of some nonlinear 
frequency response methods. The most promising appeared to be the 
describing function (Shinners, 1972; Brewer, 1974), but its applica- 
tion produced no useful results. 

Patten (1975), in describing natural ecosystems as linear because 
frequencies present in the inputs are always present in the output, 
ignored the possible presence of additional variance at other 
frequencies in the response spectrum. Another example of the 
presence of additional variance was recently described by Ollason 
(1977), who performed a frequency-domain analysis of three 
freshwater microcosms, each subjected to a different amplitude of an 
incident-light sinusoid with a period of 4 days. Variance spectra were 
calculated for time series of the phytoplankton component and three 
protozoan taxa for each microcosm. The spectrum for phyto- 
plankton in the microcosm receiving the lowest amplitude sinusoid 
showed variance only at the input frequency (1 cycle/4 days). 
Spectra for the other three components of that microcosm and all 
spectra for the other two microcosms showed substantial variance at 
frequencies other than the input frequency. Thus the characteristics 
of the response spectra appear to be functions of the frequency of 
the input sinusoid, as well as of the system compartment being 
monitored. We concluded that linearity of response is not a universal 
ecosystem property and that we must test for it with data from the 
natural ecosystem before we attempt to model its near-equilibrium 
dynamics linearly or to estimate its stability properties. 

Spectral analysis is a valuable testing method. Its major drawback 
is the number and frequency of samples needed to resolve significant 
peaks in variance spectra. Many studies have already been done, 
however, in which useful spectra have been computed from 
ecological time-series data (see Piatt and Denman, 1975). Rapid 
technological development of automated sampling equipment and 
phenomenal price decreases for minicomputer systems capable of 
automated data acquisition will make good environmental time series 
available to most researchers. As physical scientists have already 
learned, frequency-domain analyses provide versatile tools for reduc- 
ing and interpreting these data. 



FREQUENCY RESPONSE OF A MARINE ECOSYSTEM 37 

ACKIMOWLEDGMEMTS 

The research reported here was supported by a National Science 
Foundation (NSF) graduate fellowship and an Environmental Protec- 
tion Agency (EPA) research traineeship to R. L. Dwyer. Support for 
the Narragansett Bay sampling was provided by NSF grant GA- 
731319X to T. J. Smayda. Support for development and experi- 
mentation on the bay microcosms was provided through EPA 
Environmental Research Laboratory intramural funding of K. T. 
Perez and a grant to S. W. Nixon and C. A. Oviatt (grant No. 
R803143030). 

REFEREWCES 

Amos, D. E., and L. H. Koopmans, 1963, Tables of the Distribution of the 

Coefficient of Coherence for Stationary Bivariate Gaussian Processes, 

Monograph SCR-483, Sandia Corp., NTIS. 
Bendat, J. S., and A. J. Piersol, 1971, Random Data: Analysis and Measurement 

Procedures, John Wiley & Sons, Inc., New York. 
Bledsoe, L. J., 197 6, Linear and Nonlinear Approaches for Ecosystem Dynamic 

Modeling, in Systems Analysis and Simulation in Ecology, B. C. Patten (Ed.), 

Vol. 4, pp. 283-298, Academic Press, Inc., New York. 
Brewer, J. W., 1974, Control Systems: Analysis, Design, and Simulation, 

Prentice-Hall, Inc., Englewood Cliffs, N. J. 
Child, G. I., and H. H. Shugart, Jr., 1972, Frequency Response Analysis of 

Magnesium Cycling in a Tropical Forest Ecosystem, in Systems Analysis and 

Simulation in Ecology, B. C. Patten (Ed.), Vol. 2, pp. 103-135, Academic 

Press, Inc., New York. 
Eisner, E., 1971, Experiments in Ecology: A Problem in Signal Extraction, in 

Statistical Ecology. Vol. 2: Sampling and Modeling Biological Populations 

and Population Dynamics, Proceedings of the International Symposium on 

Statistical Ecology, New Haven, Conn., August 1969, G. P. Patil, E. C. 

Pielou, and W. E. Waters (Eds.), pp. 237-251, Pennsylvania State University 

Press, University Park. 
Gunnerson, C. G., 1966, Optimizing Sampling Intervals in Tidal Estuaries, J. 

Sanit. Eng. Div., Am. Soc. Civ. Eng., 92(SA2): 103-125. 
Harwell, M. A., W. P. Cropper, Jr., and H. L. Ragsdale, 1977, Nutrient Recycling 

and Stability: A Reevaluation, Ecology, 58: 660-666. 
Holling, C. S., 1973, Resilience and Stability of Ecological Systems, Annu. Rev. 

Ecol. Systemat., 4: 1-23. 
Kramer, W. P., and R. H. Weisberg, 1975, Fortran Graphics Progi'ams for 

Physical Oceanographic and Time Series Data, Marine Technical Report 46, 

Graduate School of Oceanography, University of Rhode Island, Kingston. 
Kremer, J. N., and S. W. Nixon, 1977, A Coastal Marine Ecosystem: Simulation 

and Analysis, Springer- Verlag, New York. 
Nixon, S. W., C. A. Oviatt, J. N. Kremer, and K. T. Perez, 1978, The Use of 

Numerical Models and Laboratory Microcosms in Estuarine Ecosystem 

Analysis— Simulations of a Winter Phytoplankton Bloom, in Marsh— 

Estuarine Systems Simulations, Eighth Belle W. Baruch Institute of Marine 



38 DWYER, NIXON, OVIATT, PEREZ, AND SMAYDA 

Biology and Coastal Research Symposium, Georgetown, S. C, January 1977, 

R. Dame (Ed.), University of South Carolina Press, Columbia, in press. 
Ollason, J. G., 1977, Freshwater Microcosms in Fluctuating Environments, 

Oikos, 28: 262-269. 
O'Neill, R. v., 1975, Dynamic Ecosystem Models: Progress and Challenges, in 

Ecosystem Analysis and Prediction, Proceedings of a SIAM— SIMS Con- 
ference, Alta, Utah, July 1-5, 1974, S. A. Levin (Ed.), pp. 280-296, Society 

for Industrial and Applied Mathematics, Philadelphia. 
Oviatt, C. A., K. T. Perez, and S. W. Nixon, 1977, Multivariate Analysis of 

Experimental Ecosystems, He/go/. Wiss. Meeresunters., 30: 30-46. 
Patten, B. C, 197 5, Ecosystem Linearization: An Evolutionary Design Problem, 

Am. Nat., 109: 529-539. 
Perez, K. T., G. Morrison, C. A. Oviatt, S. W. Nixon, and B. Buckley, 1977, The 

Importance of Physical and Biotic Scaling to the Experimental Simulation of 

a Coastal Marine Ecosystem, Helgol. Wiss. Meeresunters., 30: 144-162. 
Piatt, T., and K. L. Denman, 1975, Spectral Analysis in Ecology, Anna. Rev. 

Ecol. Systemat., 6: 189-210. 
Shinners, S. M., 1972, Modern Control System Theory and Application, 

Addison-Wesley, Inc., Reading, Mass. 
Smayda, T. J., 1976, Plankton Processes in Mid-Atlantic and Shelf Waters and 

Energy-Related Activities, in Effects of Energy-Related Activities on the 

Atlantic Continental Shelf B. Manowitz (Ed.), ERDA Report BNL-50484, 

pp. 70-95, Brookhaven National Laboratory, NTIS. 
Vargo, G. A., 1976, The Influence of Grazing and Nutrient Excretion by 

Zooplankton on the Growth and Production of the Marine Diatom 

Skeletonema costatum (Greville) Cleve in Narragansett Bay, Ph.D. Thesis, 

University of Rhode Island, Kingston. 
Waide, J. B., J. E. Krebs, S. P. Clarkson, and E. M. Setzler, 1974, A Linear 

Systems Analysis of the Calcium Cycle in a Forested Watershed Ecosystem, 

in Progress in Theoretical Biology, R. Rosen and F. M. Snell (Eds.), Vol. 3, 

pp. 261-345, Academic Press, Inc., New York. 
Wastler, T. A., 1969, Spectral Analysis, Applications in Water Pollution Control, 

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Webster, J. R., J. B. Waide, and B. C. Patten, 1975, Nutrient Recycling and the 

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Gentry, and M. H. Smith (Eds.), pp. 1-27, CONF-740513, NTIS. 
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Systemat., 6: 311-338. 



APPLYING SURVIVAL CURVES 
TO ASSESSMENT OF FISH LARVAL 
ENTRAINMENT IMPACT 



MICHAEL D. DAHLBERG 

Ecological Sciences Division, NUS Corporation, 

Pittsburgh, Pennsylvania 



ABSTRACT 

The equivalent-adults model for approximating numbers of fish larvae entrained 
at povirer plants and survival rates from larva to adult is assessed in regard to 
predicting the numbers of adults represented by entrained larvae. The accuracy 
of this model, in relation to other proposed approaches, depends on the proper 
selection of methods for calculating larval losses, lifetime fecundity, and 
larva-to-adult survival. Additional approaches are recommended when sufficient 
population data are available. Until questionable assumptions can be resolved, a 
reasonable approach is to calculate a possible range for the number of equivalent 
adults lost. These numbers can be compared to a reference of acceptability, such 
as year-to-year variability of stock size. 



Entrainment of fish eggs and larvae is one of the major impacts of 
power-plant operation. Potential effects are generally assessed by 
translating entrained eggs and larvae to the potential number of 
adults they represent. The calculations are accomplished with 
complex models and a simplistic equivalent-adults method proposed 
by Horst (1975). Horst's method has been recommended by the 
Environmental Protection Agency (1976) and is widely applied in 
impact calculations. This paper examines problems encountered in 
applying the Horst model and discusses alternative procedures. Data 
for the walleye population of Oneida Lake, New York (Forney, 
1976a; 1976b) are used as an example. 

39 



40 DAHLBERG 

SURVIVAL CURVES AIMD ENTRAIIMMEIMT LOSSES 

Constructing egg-to-adult survival curves (e.g., Fig. 1 and Table 1) 
is recommended as the first step in assessing larval entrainment 
impact. The curves in the figure illustrate a snapshot approach in 
which ratios of adults and earlier stages represent survival rates. 
Families of such curves permit graphic comparison of such variables 
as year-to-year differences, augmentation, and biased sampling, e.g., 
avoidance of sampling gear. The latter is a common source of error in 
lacustrine studies (Hackney, 1977) and may be responsible for the 
high mortality rate determined by Noble (1972) for walleye 
postlarvae in one bay of Oneida Lake (see Fig. 1). 

The predictive value of survival curves is greatest in stable 
populations (Horst, 1977a). When we are restricted to specific 
population data, we can construct representative survival curves by 
averaging data acquired over several years, as in Fig. 1, or by selecting 
data for a typical year. Survival curves for naturally spawned (1969, 
1971, and 1973) and augmented (1968, 1970, and 1972) popula- 
tions of walleyes (Forney, 1976a) are presented in Fig. 1. 

Egg production (13 x 10^) of walleyes in Oneida Lake was 
estimated by Forney (1976a) from fecundity-at-age data. Walleyes 
hatched near May 10 (day in Fig. 1) and were pelagic for 
approximately 40 days. The larvae occupied 971 x 10^ m^ of water, 
which is the upper 5.5 m (Clady, 1975) and 64% of the total lake 
volume. Postlarvae were transported by surface currents and yolk-sac 
larvae by subsurface currents (Houde and Forney, 1970). 

Since larvae were not fully recruited into the plankton until the 
swim-up stage (day 10), numbers of larvae at hatching and survival 
from hatching to swim-up (13.6%) were estimated from the ratio of 
these stages in the augmented population. Assuming the difference in 
numbers of 10-day-old larvae in augmented and unstocked popula- 
tions (3.192 X 10"^) resulted from the stocking of 2.347 x 10^ 1- to 
3-day-old larvae (Forney, 1976a), the survival rate was 13.6%. There 
is a possibility that stocked larvae experience higher mortality than 
wild larvae (Forney, 1976a). 

Populations of demersal young-of-the-year and age I juveniles 
were estimated from trawl studies (Forney, 1976a). Survival to 
adults is shown in Fig. 1 by plotting parent stock size, including all 
mature age classes (age IV and older), as determined by mark and 
recapture studies (Forney, 1976b). 

Assuming a feasible open-cycle cooling-water-intake flow of 
1 million gpm (5.45 x 10^ m^/day), cumulative numbers of larvae 
entrained were calculated and illustrated by a survival curve (Fig. 1). 



APPLYING SURVIVAL CURVES 



41 



CO 




3 7 — 



o 
o 



-/O 10 20 30 40 50 60 70 80 90 100110 120130140150160170 

DAYS 



520 TOTAL 
ADULTS 



Fig. 1 Survival curves for augmented and naturally spawned popula- 
tions of walleye in Oneida Lake, New York. Sizes of entrained 
populations are indicated by dotted lines. 



TABLE 1 

NUMBERS OF EGGS, LARVAE, AND ADULTS IN UNSTOCKED 
AND AUGMENTED WALLEYE POPULATIONS IN ONEIDA 

LAKE, NEW YORK* 



Unstocked 
population 



Augmented 
population 



Egg productiont 
Larval production: 
Swim-up larvae 

(10daysold)51 
35-mm larvae 

(40 days old)§ 
Adults 



13 X 10^ 
5.4775 X 10^ 



7.4500 X 10' 



3.0 X 10' 
466,000 



8 



13 X 10' 
2.8944 X 10 

3.9368 X lO"^ 

13.5 X 10^ 
574,000 



*Based on data from Forney (1976a; 1976b). 
fFrom fecundity-at-age data. 

I From densities of swim-up larvae in net samples, at 13.6% survival from 
hatching to swim-up. 
51 From net samples. 
§Estimated from survival curve in Fig. 1. 



42 DAHLBERG 

The calculations required the assumption that entrainment is 
randomly exploiting the larval population, i.e., all larvae have an 
equal chance of being entrained. Number of larvae entrained (Nl) is 

Nl= f diVi (1) 

i=l 

where d, is average number of larvae during the ith sample period and 
Vj is the corresponding volume of cooling water (Hackney, 1977). 
Calculated on a daily basis, Nl is 2.26 x 10^ in the unstocked 
population and 12.08 x 10*^ in the augmented population. 

Sizes of the exploited larval populations (Fig. 1) were calculated 
from reductions in population size: 

Lp-^x 100 (2) 

where Lp is percent reduction of larval population, Vi is volume of 
water entrained (5.45 x 10'' mVday), and V is volume of occupied 
water (971 x 10^ m^). Thus Lp is 0.5613%/day and 22.45% in 
40 days. 



EQUIVALENT-ADULTS MODEL 

The equivalent-adults model was proposed by Horst (1975) to 
provide a simple first approximation of fish egg and larval entrain- 
ment impact in terms of potential adult loss. The basic approach is 
multiplying numbers of eggs and larvae entrained by egg and 
larva-to -adult survival rates to estimate the number of equivalent 
adults. The following assumptions, summarized from Horst (1977a), 
are made when this model is applied to larval entrainment: 

1. The population is in equilibrium and has a stable age 
distribution. 

2. Lifetime of a fish is the average age or mean generation time. 

3. Numbers of males and females are equal. 

4. Entrainment of larvae occurs at the time of hatching. 

5. The calculated equivalent adults are distributed in proportion 
to the stable age distribution of adults. 

Horst (1975) proposed the formula 

Na=NlSla (3) 



APPLYING SURVIVAL CURVES 43 

where N^ is potential adult loss, Nl is number of larvae entrained, 
and Sla is survival from hatching to adult. It was proposed that Sla 
be estimated indirectly from 



Ska 
Sla = Sit W 



where Sea (survival from egg to adult) is 2/F and Sel is an 
estimated or observed survival rate from egg to hatching of larvae. 
Lifetime fecundity, F, is 



F = G L P.Ei (5) 

i=l 

where Pj is fraction of population in each age class, E, is egg 
production or fecundity for each age class, and G is mean generation 
time in years. Since appropriate data for Oneida Lake walleyes are 
lacking, F is calculated for Lake Erie walleyes (Table 2). Mean 
generation time is estimated as 3 years in this case to correspond to 
the age of maximum eggs per female. An intermediate adult age, such 
as 5 years, can also be selected to provide possible minimum and 
maximum generation times (Horst, 1977b). This procedure yields 
Sea values of 4.3728 x IQ-^ and 2.6240 x 10^^ The utility of 
this approach is supported by an independent calculation of 
egg-to-adult survival (3.5846 x 10~^), which represents the ratio of 
adults and egg production in the unstocked population, as shown in 
Table 1. 

If we limit further calculations to the unstocked population, 

_ Sea _ 4.372 x IQ-' _ 0.00004372 _ ^ ^, ^^„ 
^LA = S^ ^ 4.213 X 10-^ ^ 0.004213 = ^'^^^^^ 

where Sel is ratio of larva at hatching and egg production (Table 1). 
This value of Sla is approximated by the ratio of adults to larvae at 
hatching (0.0085) in Table 1. The product of Sla and the number 
of larvae entrained (Nl = 2.26 x 10*"), as in Eqs. 1 and 3, yields a 
potential adult loss of 23,436. 

The use of hatching-to-adult survival for Sla is questionable 
since survival to adulthood increases from 1 to 15.5% through the 
pelagic larva period (survival rate is the ratio of adults to larvae). To 
make the calculation of larval entrainment losses correspond with the 



44 DAHLBERG 

Sla parameter used in the Horst model, we can calculate larval 
losses (Np) from 

Np = Lh X Lp (6) 

where Lh is total larval production or number of larvae hatched 
(5.4775 X 10^) and Lp is percent reduction (Eq. 2). Thus Np is 
5.4775 X 10"^ X 22.45% or 1.2297 x 10\ and the number of adults 

(NA)is 

Na =Sla X Np- 127,520 (7) 

Composition data in Table 2 indicate that Na would be 
distributed among age classes as follows: age III, 0.757; age IV, 
0.138; age V, 0.069; age VI, 0.014; age VII, 0.021; age VIII, 0.003. 



TABLE 2 

CALCULATING MEAN LIFETIME FECUNDITY AND SURVIVAL 
FROM EGG TO ADULT FOR WALLEYES IN WESTERN LAKE 

ERIE, 1955-1970* 





Fraction of 


Eggs per 


Weighted eggs 


Age 


population 


female 


per female 


I 


0.52 








II 


0.34 








III 


0.11 


91,000 (X 0.86)t 


8,608.6 


IV 


0.02 


140,000 


2,800.0 


V 


0.01 


213,000 


2,130.0 


VI 


0.002 


261,000 


522.0 


VII 


0.003 


374,000 


1,122.0 


VIII 


0,0004 


364,000 


145.6 



* 



Total 1.0054 15,328.2 

Data are from Busch, Scholl, and Hartman (1975) and Wolfert (1969): 



Mean fecundity (F) = l^'^f^ = 15,246 

Mean lifetime fecundity = Mean generation time (G) X Mean fecundity 

= 3 X 15,328.2 = 45,984.6 
= 5 X 15,328.2 = 76,641.0 
2 
Survivorship egg to adult (Sg^) = — 

F 

Sea = 4.3728 X 10~^ (1 per 22,869 eggs) for G of 3 

Sea = 2.6240 X 10~^ (1 per 38,110 eggs) for G of 5 

tCorrection for 86% maturity. 



APPLYING SURVIVAL CURVES 45 

CALCULATING DAILY POTEIMTIAL ADULT LOSSES 

Potential adult loss can be calculated on a daily basis (N^i) 
through the entrainment period. Numbers of larvae entrained each 
day are multiplied by increasing survival rates calculated from the 
ratio of adults to larvae occurring each day: 

NAi = NLiSLAi-NLi^ (8) 

where Nli = number of larvae entrained each day 
^LAi ~ survival rate from larva to adult 
A = number of adults 
Li = larval population size 

However, since NLi/Li is a constant (0.5617o) representing the 
percentage of occupied waters, and presumably larvae, entrained 
each day, Nai = 0.00561 x A = 2614 and Na = Nai x 
40 = 104,560. 

LARVAL REDUCTIOIM METHOD 

Actual reduction of a larval population caused by entrainment is 
less than total numbers entrained because the total numbers include 
larvae that would have died from natural causes by the end of the 
pelagic period; e.g., the number of walleye larvae entrained in 
40 days is 2.26 x 10^, and larval reduction is 673,500. Larval 
reduction is csilculated by multiplying the estimated number of 
40-day-old larvae (3.0 x 10^) by the percent reduction, 22.45% (as 
described in Eq. 2). 

Multiplying larval reduction by survival rate from 40-day-old 
larva to adult (0.1553) gives an Na value of 104,595. The survival 
rate used is the ratio of adults and 40-day-old larvae (Table 1). 

The simplest approach for calculating Na is to assume that the 
percent reduction of adults is equivalent to the percent reduction of 
larvae (22.45%). This calculation yields a potential adult loss of 
104,617. 

DISCUSSION 

Interpretations of the equivalent-adults model of Horst (1975) 
have generally resulted in minimal projections of potential adult loss. 
The primary causes are using high fecundity values, representing the 



46 DAHLBERG 

maximum egg production of a species, and applying low larva-to- 
adult survival rates. These problems are corrected by using mean 
lifetime fecundities and applying appropriate combinations of 
survival rates and larval reductions. 

Applying the survival rate for the hatching-to-adult period is 
reasonable v^hen larval entrainment losses are based on the reduction 
of total larval production rather than the number of larvae actually 
entrained. This reduction in larval production can be estimated by 
multiplying larval production by the fraction of larvae entrained 
throughout the pelagic period. The results are in reasonable 
agreement with projections based on the assumption that the 
percentage reduction of adults is equivalent to the percentage of 
larval exploitation. Interpretations of these results should consider 
that the projected adult loss is distributed among all mature age 
classes and is in proportion to the adult age-class composition in a 
stable population. 

With the exception of the general mode of application of the 
Horst model (Eqs. 1 and 3), the calculations of N^ are probably 
biased toward a possible maximum or worst-case estimate by the 
assumptions that (1) an intake randomly draws on the total larva 
population, (2) there is no avoidance reaction to induced intake 
currents, and (3) there are no compensatory responses. 

Although larvae are transported by wind-generated lake currents 
(Houde and Forney, 1970) and by power-plant-induced currents, it is 
unlikely that they will be randomly recruited into an intake 
throughout the pelagic period. Spatial distribution and movements of 
larvae should be considered when possible. In Oneida Lake, postlarvae 
concentrate in shallow bays along the southern shore (Noble, 1972). 

Avoidance of an intake probably increases with size of larvae, as 
does avoidance of sampling gear (Noble, 1972). Although young 
walleyes are pelagic up to 40 days and to 35 mm in length (Fig. 1), 
Noble did not capture postlarvae over 18 mm long. 

Natural compensation for entrainment exploitation may occur in 
the exploited year class as increased survival or growth or in 
subsequent generations if fecuiidity also increases with grovii^h. 
McFadden (1976) indicated that only partial compensation can be 
expected. High compensation is apparent in Lake Erie walleyes, 
which maintained their stock size despite total mortality rates of 
50% in yearlings and 80% in older fish (Regier, Applegate, and 
Ryder, 1969). Additional growth compensation would not be 
expected, however, if this population had reached its physiological 
maximum for growth (Regier, Applegate, and Ryder, 1969) or if the 
supply of forage fish was low (Moyle, 1949). 



APPLYING SURVIVAL CURVES 47 

Until sufficient information is available to correct for compensa- 
tion and avoidance, potential adult loss should be expressed as a 
possible range, such as those obtained with Eqs. 3 and 7 and with the 
methods proposed here, e.g., 23,000 to 127,000. The calculated 
adult losses can then be compared with some reference for 
acceptability, such as year-to-year variation in population size 
(Environmental Protection Agency, 1976). Since the average year- 
to-year variability of the Oneida Lake adult walleye population was 
approximately 156,000 during 1957-1974 (Forney, 1976b), it 
appears that our calculation of potential adult loss would be 
acceptable. 



ACKNOWLEDGMENTS 

The background for this study was achieved through the 
preparation and review of impact statements for the Ecological 
Sciences Division of NUS Corporation, of which P. V. Morgan is vice 
president and general manager. The manuscript was reviewed by 
P. V. Morgan, B. C. Marcy, P. A. Dahlberg, L. K. Davis, V. R. Kranz, 
and H. A. Haerer of NUS Corporation; P. A. Hackney of the 
Tennessee Valley Authority; and T. J. Horst of Stone and Webster 
Engineering Corp. W. J. B. Johnson of NUS Corporation drafted the 
figure. 



REFERENCES 

Busch, W. N., R. L. Scholl, and W. L. Hartman, 1975, Environmental Factors 
Affecting the Strength of Walleye {Stizostedion vitreum vitreum) Year -Class 
in Western Lake Erie, 1960-70, J. Fish. Res. Board Can., 32(10): 1733-1743. 

Clady, M. D., 1975, Population Dynamics of Walleye and Yellow Perch in 
Oneida Lake, April 1, 19 70, to March 31, 1975, Federal Aid Project F-17-R, 
Job I-e, New York State Conservation Department, Albany. 

Environmental Protection Agency, 1976, Development Document for Best 
Technology Available for the Location, Design, Construction and Capacity 
of Cooling Water Intake Structures for Minimizing Adverse Environmental 
Impact, Sect. 316(b), P. L. 92-500, Washington, D. C. 

Forney, J. L., 1976a, Year-Class Formation in the Walleye (Stizostedion vitreum 
vitreum) Population of Oneida Lake, New York, 1966—1973, J. Fish. Res. 
Board Can., 33: 783-792. 

, 1976b, Population Dynamics of Walleye and Yellow Perch in Oneida Lake, 

April 1, 19 75, to March 31, 1976, Federal Aid Project F-17-R, Job I-a, New 
York State Conservation Department, Albany. 

Hackney, P. A., 1977, Methods for Calculating Survival Rate, Biomass Produc- 
tion, and Proportion Entrained of Lacustrine Ichthyoplankton, in Proceed- 
ings of the Conference on Assessing the Effects of Power-Plant-Induced 



48 DAHLBERG 

Mortality on Fish Populations, W. Van Winkle (Ed.), Pergamon Press, Inc., 

New York. 
Horst, T. J., 1975, The Assessment of Impact Due to Entrainment of 

Ichthyoplankton, in Fisheries and Etiergy Production, S. B. Saila (Ed.), 

pp. 107-118, D. C. Heath & Co., Lexington, Mass. 
— , 1977a, Mathematical Modeling of Power Station Impacts on Fisheries 

Resources of the United States, International Federation for Information 

Processing Working Conference on Modeling and Simulation of Land, Air 

and Water Resource Systems, Ghent, Belgium, preprint. 

, 1977b, Stone and Webster Engineering Corp., personal communication. 

Houde, E. D., and J. L. Forney, 1970, Effects of Water Currents on Distribution 

of Walleye Larvae in Oneida Lake, J. Fish. Res. Board Can., 27: 445-456. 
McFadden, J. T., 1976, Environmental Impact Assessment for Fish Populations, 

in Proceedings of the Workshop on the Biological Significance of Environ- 
mental Impacts, R. K. Sharma, J. D. Buffington, and J. T. McFadden (Eds.), 

pp. 89-138, Report NR-CONF-002, U. S. Nuclear Regulatory Commission, 

Washington, D. C. 
Moyle, J. B., 1949, Fish Population Concepts and Management of Minnesota 

Lakes for Sport Fishing, Trans. North Am. Wildl. Conf., 14: 283-294. 
Noble, R. L., 197 2, Mortality Rates of Walleye Fry in a Bay of Oneida Lake, 

New York, Trans. Am. Fish. Soc, 101: 720-723. 
Regier, H. A., V. C. Applegate, and R. A. Ryder, 1969, The Ecology and 

Management of the Walleye in Western Lake Erie, Technical Report 15, 

Great Lakes Fisheries Commission. 
Wolfert, D. R., 1969, Maturity and Fecundity of Walleyes from the Eastern and 

Western Basins of Lake Erie, J. Fish. Res. Board Can., 26: 1877-1888. 



A SIMPLE MODEL FOR ASSESSING 
THE POTENTIAL LOSS OF ADULT FISH 
RESULTING FROM ICHTHYOPLANKTON 
ENTRAINMENT 



W. PETER SAUNDERS, JR.* 

Environmental Research and Technology, Inc., Concord, Massachusetts 



ABSTRACT 

A mathematical model for estimating potential survival of fish eggs and larvae to 
reproducing adults is examined in the context of predicting the potential loss 
from power-station entrainment. It is demonstrated that violating one 
assumption of the model can result in gross underestimates of potential adult 
loss. High rates of natural mortality occurring during the egg and larval life stages 
are considered in relation to the assumption that all exploitation by the powder 
plant occurs instantaneously at spawning or hatching. The sensitivity of 
potential loss estimates to various time— mortality-rate regimes is examined on 
the basis of the natural mortality rates observed in young life stages of several 
species. An alternative model is proposed, and its sensitivity to underlying 
assumptions is examined. This model is shown to consistently overestimate loss 
of equivalent adults. The magnitude of the overestimation depends on 
species-specific conformity of the model assumptions to actual planktonic 
mortality and first-year survival. 



Many aquatic species that produce planktonic eggs and/or larvae have 
very high mortality of the young organisms. Of the many thousands 
of offspring initially produced, only a few individuals survive to 
reproductive maturity. Since we are usually familiar with the portion 
of a population potentially subject to exploitation by a fishery, the 
entrainment loss of large numbers of planktonic young may be more 
meaningful in the impact assessment process if considered in relation 
to the numbers of reproducing adults that could potentially result 



♦Current address: Massachusetts Cooperative Fisheries Research Unit, 
University of Massachusetts, Amherst, Mass. 

49 



50 SAUNDERS 

from the entrained plankters. Horst (1975) suggested using an 
equivalent-adults model to translate the number of eggs and larvae 
entrained to an equivalent number of adults lost. 
The reduced form of the model is 

Na = (Ne X Sea) + (Nlx Sla) (1) 

where Na = number of adults potentially lost as a result of entrain- 
ment 
Ne = number of newly spawned eggs entrained 
Sea ~ survival from egg to adult 

Nl = number of newly hatched larvae entrained 
Sla ^ survival from larva to adult 



and 



SEA = (Pf X F5^x L)-i (la) 



where Pf is the proportion of the population which is female, Fx is 
the average fecundity per female per year, and L is the reproductive 
life expectancy of an average organism. 

The term Sla can be defined as 

Sla = Sea x Sel (lb) 

where Sel is the survival from egg to larva. 

The equivalent-adults model provides an approach to the 
assessment of entrainment impact on a species population in 
instances where little information is available on the life history of 
the species. The only life-history information required to use the 
model is the fecundity of a female, the reproductive life span, and 
the sex ratio. A number of other life-history parameters can be 
incorporated into the model's calculations, however. Thus the 
equivalent-adults model is a valuable expedient that can be used in 
the impact-assessment process when data are insufficient to allow a 
more sophisticated approach, such as the Leslie (1945) model (Horst, 
1978). 

A number of assumptions implicit in its formulation must be 
recognized and addressed when we use the equivalent-adults model: 

1. The adult population is at equilibrium, with no change in its 
size occurring over time. 

2. The population maintains a stable age distribution. 

3. The ratio of males to females is constant through time. 



SIMPLE MODEL FOR ASSESSING POTENTIAL LOSS 51 

4. The life span of an individual is equivalent to the mean 
generation time (MGT) for females in the population. 

5. Exploitation of planktonic eggs occurs instantaneously at 
spawning, and exploitation of larvae occurs instantaneously at 
hatching (becoming planktonic). 

Horst (1978) discussed methods of dealing wdth departures from 
several of these assumptions. In many instances the method involves 
a simple modification of the calculated survival rate from egg to 
adult. Horst also discussed modifying the modeling procedure to 
approximate MGT. 

In this paper I discuss aspects of the equivalent-adults model 
associated with the mortality of eggs and larvae, A conflict exists 
between assumption 5 and the "real-world" case; i.e., continuous 
exploitation of planktonic Hfe stages by the power plant. I ex- 
amine the effect of commonly observed egg and larval mortality 
rates on the results of the model and suggest an alternative method 
of computing the loss of equivalent adults which requires no 
additional data. 



EFFECT OF EGG AND LARVAL MORTALITY OIM THE RESULTS 
OF THE EQUIVALENT-ADULTS MODEL 

I have found that very seldom are data available to allow a 
detailed estimate of rates of egg and larval mortality. Two cases with 
which I am familiar are the analysis of egg and larval mortality of the 
Atlantic mackerel, Scomber scombrus (Sette, 1943), and the analysis 
of larval mortality of winter flounder, Pseudopleuronectes ameri- 
canus (Pearcy, 1962). In both these cases mortality conforms to the 
exponential model. My discussion here assumes that all mortality of 
eggs and larvae follows this model. This allows the survivorship to the 
end point of a life stage (e.g., hatching success) to be converted to an 
instantaneous mortality rate: 

M = ^J^ (2) 

where M is the instantaneous natural mortality rate, S is the 
survivorship to the end of the life stage, and t is the duration of the 
life stage in days. 

Table 1 gives the results of a survey of daily natural mortality 
rates for the entrainable (planktonic) life stages of several species. 
The information in the table indicates that natural mortality rates for 



52 



TABLE 1 

OBSERVED RATES OF NATURAL MORTALITY 
FOR PLANKTONIC LIFE STAGES OF FISH 







Mortality 


Survival* 




Species and 


Duration, 


rate. 


(to end of 




life stage 


days 


%/day 


stage) 


Reference 


Atlantic mackerel 










Egg 


7 


14 




Sette, 1943 


Larva 










Pre fin fold 


28 


14 




Sette, 1943 


During fin fold 


5.5 


44 




Sette, 1943 


Post fin fold 


41 


10 




Sette, 1943 


Egg— juvenile 


85 


14 


0.000004 


Sette, 1943 


Winter flounder 










Larva 










0-25 days 


25 


21 




Pearcy, 1962 


26-53 days 


28 


4 




Pearcy, 1962 


Haddock 










Larva 




10 




Gushing and 
Walsh, 1976 


Plaice 










Larva 


30 


5 


20%/ month 


Gushing, 1975 


Juvenile 


60 


2 


62%/month 


Gushing, 1975 


Fishes (marine) 










Egg and early 




5-10 




Gushing, 1975 


larva 










Gunner 










Egg 


2-7 


35-78 


0.05 


Williams, Williams, 
and Miller, 1973 


Northern pikef 










Alevin 


16 


17 


0.052 


Franklin and 
Smith, 1963 




20 


24 


0.004 


Franklin and 
Smith, 1963 




22 


8 


0.156 


Monten, 1948 




35 


5 


0.167 
(mean) 


Monten, 1950 




35 


3-10 


0.22-0.386 
(range) 


Monten, 1950 


Striped bass 










Egg and yolk-sac 


10 


25 


0.058 


Saila and Lorda, 


larva 








1977 


Post yolk-sac 


24 


13 


0.037 


Saila and 


larva 








Lorda, 1977 


Juvenile 1 


30 


5 


0.200 


Saila and 
Lorda, 1977 


Smallmouth bass 










Fry 


90 


7 


0.0014 


Fajen, 1975 




120 


5 


0.0016 


Fajen, 1975 



*Survival to end of life stage is provided only for those instances where it 
was used to back calculate mortality rate. 

fFranklin and Smith (1963) and Monten (1948; 1950) dealt with hatchery- 
reared populations, which would, presumably, have lower mortality rates than 
naturally spawned fish. 



SIMPLE MODEL FOR ASSESSING POTENTIAL LOSS 
1000.0 



53 



100.0 — 




10.0 — 



60 90 

t, days 



150 



Fig. 1 Values of U, the factor by which adult loss is underesti- 
mated, for specific daily natural mortality rates (n), occurring over 
varying periods of entrainment (t). 



planktonic eggs and larvae often exceed 5%/day. Particularly high 
mortality rates are evident early in the planktonic life stage or when 
the planktonic life stage is of short duration. 

Figure 1 shov^^s a series of curves computed by varying the 
duration of exploitation of planktonic life stages by the power 
station. These curves indicate the factor U, by which the equivalent- 
adults model will underestimate potential adult loss at specific 
natural mortality rates. In calculating this factor we assume constant 
vulnerability to entrainment and immediate removal (through decay, 
predation, or loss of buoyancy) of eggs or larvae that die naturally: 



U 



,Mt/2 



(3) 



where M is the instantaneous natural mortality rate and t is the 
duration of entrainment in days. 

In Eq. 3, U represents a factor that, when multiplied by the 
number of eggs or larvae entrained, is equivalent to the number of 
eggs or larvae originally produced and which would have been 



54 



SAUNDERS 



entrained had all entrainment taken place immediately after spawn- 
ing or hatching. 

At natural mortality rates of 5%/day or greater and for an 
entrainable life-stage duration of 30 days, the equivalent-adults 
model underestimates potential adult loss by a factor greater than 2 
(Fig. 1). In assessing larval entrainment of winter flounder, which has 
a larval mortality rate of 21%/day during the first 25 days after 
hatching (Pearcy, 1962), the model would underestimate potential 
adult loss by a factor of 18. 

These facts suggest that the equivalent-adults model is very 
sensitive to the assumption that exploitation occurs instantaneously 
when eggs are spawned or larvae hatch. Because the model could 
grossly underestimate adult loss, it may be of questionable value 
from a regulatory viewpoint since, in a proceeding intended to 
protect the environment from adverse effects, acceptable impact 
predictions usually must be able to assert that impact in the 
real-world case will not be greater than that predicted. Therefore, to 
assure this "conservatism," we must provide for relaxation of the 
assumption of immediate exploitation. 

REVISION OF THE EQUIVALENT-ADULTS MODEL 

When sufficient data are available to calculate mortality rates for 
planktonic life stages, the equivalent-adults model can be modified 
by incorporating U (Eq. 3) into the loss calculation. This can be 
accomplished by using data available in the literature or by 
estimating planktonic mortality rates directly from field-survey data, 
as discussed by Polgar (1977) and Hackney (1977). When restrictions 
of time or resources prevent direct estimation of U, however, 1 
propose that an alternative form of the equivalent-adults model be 
used. 

My model requires an estimate of survival through the first year 
(So). To relax the assumption concerning time of entrainment 
without introducing a number of new factors into the model, 1 have 
taken a pragmatic approach to estimating Sq • Since first-year 
mortality is high in comparison with mortality in older fish, I use the 
survival from egg to adult (Sea)' based on fecundity and life span 
(Eq. 1), as an estimator of Sq . If we then assume that all first-year 
mortality occurs during the planktonic life stage, a correction factor 
(U') can be calculated for the model: 

U' = g-lnSEA/2 (4) 

where Sea is the egg-to-adult survival as defined by Eq. la. 



SIMPLE MODEL FOR ASSESSING POTENTIAL LOSS 55 

This equivalent- adults model can be expressed as 

Na - U' [(Ne X Sea) + (Nl x Sla)] (5) 

For purposes of illustration, Table 2 compares the results 
generated by the equivalent-adults model of Horst (1975) without 
providing for relaxation of the exploitation assumption; by the Horst 
model with relaxation based on published planktonic mortality rates, 
and by my version of the model for five of the species from Table 1. 

SENSITIVITY ANALYSIS OF THE ALTERNATIVE MODEL 

The equivalent-adults model I propose assumes (1) that all 
mortality occurring during the first year of life takes place during the 
planktonic life stage and (2) that Sea approximates Sq. The 
sensitivity of the model to each of these assumptions was examined. 
Sensitivity is expressed in terms of the ratio of the predicted impact 
to the "actual" impact resulting when the model assumptions are not 
satisfied by the natural situation. 

Figure 2 shows the relationship between the prediction of 
equivalent-adult loss based on assumption 1 and the actual loss that 
would result when planktonic mortality comprises only a specified 
portion of estimated first-year mortality. This figure indicates that 
the proposed model will always overestimate loss. The magnitude of 
the overestimation is based on the relationship 

r = p-'^ (6) 

where p is the proportion of first-year mortality actually occurring 
during the planktonic life stage(s) and r is the ratio of predicted to 
actual loss. 

For example, if 25% of the total first-year mortality occurred 
during the planktonic life stages, the proposed model would 
overestimate loss by a factor of 2, or, if 1% of the total first-year 
mortality occurred during the planktonic life stages, the proposed 
model would overestimate loss by a factor of 10. This relationship is 
independent of Sq . 

The effect on the model prediction resulting from the use of Sea 
as an estimator of Sq is similar to that described. This relationship, 
expressed in terms of the ratio of Sea to Sq , is 



(W 



So 
where r is the ratio of predicted to actual loss. 



(7) 



56 



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SIMPLE MODEL FOR ASSESSING POTENTIAL LOSS 



57 



100.0 



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Fig. 2 The ratio (r) of predicted to actual loss when planktonic 
mortality comprises a specific proportion (p) of the mortality 
assumed by the alternative model. 



The potential relationships of Sea to Sq can be examined by 
comparing Sea to Sq values calculated with the Leslie Matrix 
(Vaughan and Saila, 1976). Table 3 shows the results of comparisons 
for seven species [I used the method described by Horst (1978) to 
estimate the range of Sea! » along with the quantity r, the ratio of 
predicted to actual loss. The information in Table 3 indicates that 
Sea is highly variable in its ability to estimate Sq , but it appears that 
in most cases use of Sea to approximate Sq will not result in large 
overestimates of impact. 



DISCUSSION 

In proposing a revised form of the equivalent-adults model, I 
have introduced several new assumptions that must be considered 
when using the model: 

1. Survival corresponds to an exponential model during all 
planktonic life stages. 

2. All mortality during the first year of life occurs during the 
planktonic life stages. 

3. Vulnerability of plankton to entrainment remains constant 
throughout the planktonic life stages. 

4. Plankton that are the victims of natural mortality are not 
entrained. 

5. Survival from egg to adult is an approximate estimator of 
first-year survival, Sq . 

Assumption 1 is relatively straightforward and requires no 
discussion, and assumptions 2 and 5 were examined in the sensitivity 
analysis. 



58 



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SIMPLE MODEL FOR ASSESSING POTENTIAL LOSS 59 

Assumption 3 requires that the vuhierability of planktonic 
organisms to entrainment does not change. This is not valid since, as 
planktonic fish grow, swimming (avoidance) ability increases and 
vulnerability decreases. This would result in an adult loss lower than 
that predicted by the model. 

Assumption 4 requires that plankton which die naturally not be 
entrained. Inclusion of organisms already dead in the estimated 
number of organisms entrained would bias the model toward an 
overestimation of loss. The magnitude of this increase of predicted- 
vs. -actual impact depends on the proportion of dead organisms 
entrained. 

The sensitivity analysis and these observations indicate that my 
alternative version of the equivalent-adults model is biased toward 
overestimating potential adult losses. Such bias should be generally 
acceptable in terms of determining (in a "first-cut" approach) 
whether or not entrainment at a particular facility is potentially 
damaging to local fish populations. Use of this model will possibly 
generate order-of-magnitude overestimates of loss in some cases (as 
opposed to order-of-magnitude underestimates with the unrevised 
model). For this reason, I suggest using this form of the equivalent- 
adults model only in cases where information on planktonic 
mortality rates or population dynamics does not exist. 

I do not consider this discussion to constitute a complete 
treatment of the equivalent-adults model and its application in 
impact-assessment situations. For a thorough discussion of other 
aspects of the model, see Horst (1978). 

SUMMARY 

An examination of one of the assumptions inherent in applica- 
tion of the equivalent-adults model of Horst (1975) indicated that 
failure to satisfy the assumption could result in underestimates of 
potential adult loss by a factor greater th£in ten. I suggest using an 
alternative form of the model which requires no additional data. 
Analysis of the assumptions of the alternative model shows that it 
will overestimate impact, but such overestimates are considered 
acceptable in using this model as a preliminary impact-assessment 
tool. 

ACKNOWLEDGMENT 

I would like to thank Tom Horst and Carol Blakely for their 
encouragement and comments. 



60 SAUNDERS 

REFEREIMCES 

Gushing, D. H., 1975, Marine Ecology and Fisheries, Cambridge University Press, 
New York. 

, and J. J. Walsh, 1976, The Ecology of the Seas, W. B. Saunders Company, 

Philadelphia. 

Fajen, O., 1975, Population Dynamics of Bass in Rivers and Streams, in Black 
Bass Biology and Management, R. H. Stroud and H. Clepper (Eds.), 
pp. 195-203, Sport Fishing Institute, Washington, D.C. 

Franklin, D. R., and L. L. Smith, Jr., 1963, Early Life History of the Northern 
Pike, Esox lucius L., with Special Reference to the Factors Influencing the 
Numerical Strength of Year Classes, Trans. Am. Fish. Soc, 92(2): 91-110. 

Hackney, P. A., 1977, Methods for Calculating Natural Mortality Rate, Biomass 
Production, and Proportion Entrained of Lacusterine Ichthyoplankton, in 
Proceedings of the Conference on Assessing the Effects of Power-Plant- 
Induced Mortality on Fish Populations, W. Van Winkle (Ed.), Abstract, 
p. 127, Pergamon Press, Inc., New York. 

Horst, T. J., 1975, The Assessment of Impact Due to Entrainment of 
Ichthyoplankton, in Fisheries and Energy Production, S. B. Saila (Ed.), 
pp. 107-118, D. C. Heath and Company, Lexington, Mass. 

, 1977, Effects of Power Station Mortality on Fish Population Stability in 

Relationship to Life History Strategy, in Proceedings of the Conference on 
Assessing the Effects of Power-Plant-Induced Mortality on Fish Populations, 
W. Van Winkle (Ed.), pp. 297-310, Pergamon Press, Inc., New York. 

, 1978, Mathematical Modeling of Power Station Impacts on Fisheries 

Resources in the United States, in Proceedings of an International 
Federation for Information Processing Workifig Conference on Modeling and 
Simulation of Land, Air and Water Resources Systems, Ghent, Belgium, 
1977, North Holland Publishing Company, Amsterdam, in press. 

Leslie, P. H., 1945, On the Use of Matrices in Certain Population Mathematics, 
Biometrika, 33: 183-212. 

Monten, E., 1948, Undersokningar over gaddynglets biologi samt nagra darmed 
sammahangande problem, S/?r. ut. av Sbdra Sver. Fiskerifor., 1948: 3-38. 
, 1950, Studier over yngefbrlusternas orsaker i fria vattan och i dammer. (II), 
Skr. ut. av Sodra Sver. Fiskerifor., 1949: 20-101. 

Pearcy, W. G., 1962, Ecology of an Estuarine Population of Winter Flounder, 
Pseudopleuronectes americanus (Walbaum), Bull. Bingham Oceanogr. Col- 
lect., 18(1): 5-78. 

Polgar, T. T., 1977, Striped Bass Ichthyoplankton Abundance, Mortality and 
Production Estimation for the Potomac River Population, in Proceedings of 
the Conference on Assessing the Effects of Power-Plant-Induced Mortality 
on Fish Populations, W. Van Winkle (Ed.), pp. 110-126, Pergamon Press, 
Inc., New York. 

Saila, S. B., and E. Lorda, 1977, Sensitivity Analysis Applied to a Matrix Model 
of the Hudson River Striped Bass Population, in Proceedings of the 
Conference on Assessing the Effects of Power-Plant-Induced Mortality on 
Fish Populations, W. Van Winkle (Ed.), pp. 311-332, Pergamon Press, Inc., 
New York. 

Sette, O. E., 1943, Biology of the Atlantic Mackerel (Scomber scombrus) of 
North America. Part I, Fish. Bull., 51(49): 251-358. 

Vaughan, D. S., and S. B. Saila, 1976, A Method for Determining Mortality 
Rates Using the Leslie Matrix, Trans. Am. Fish. Soc, 105(3): 380-383. 



SIMPLE MODEL FOR ASSESSING POTENTIAL LOSS 61 

Williams, G. C, D. C. Williams, and R. J. Miller, 1973, Mortality Rates of 
Planktonic Eggs of the Gunner, Tautogolabrus adspersus (Walbaum), in Long 
Island Sound, in Proceedings of a Workshop on Egg, Larval and Juvenile 
Stages of Fish in Atlantic Coast Estuaries, A. L. Pacheco (Ed.), Technical 
Publication No. 1, Middle Atlantic Goastal Fisheries Genter, National Marine 
Fisheries Service. 



STRESS AND ECOSYSTEMS 



ARIEL E. LUGO* 

Department of Botany and Center for Wetlands, University of Florida, 

Gainesville, Florida 



ABSTRACT 

The literature dealing with issues of stress as it affects ecosystems is reviewed. 
Definitions of stress are discussed. Models and literature examples are presented 
to illustrate the push — pull (positive — negative) effects of most stressors and to 
suggest that the point of attack and the type of stressor determine the rate of 
response of the ecosystem. Stressors with high-quality energies (highly concen- 
trated energy sources) that divert low-quality energy flows in a system appear to 
have a greater impact than stressors with low-quality energy (diluted energy 
sources) that impact high-quality energy flows. It is suggested that ecosystem 
complexity (including species diversity, physiognomy, three dimensional organi- 
zation, etc.) is a function of the balance between energies that contribute to 
growth and organization and those that contribute to disorder. The classification 
of environments by their "energy signatures" (the sum of all incoming energy 
flows into a system and the pattern of their delivery expressed on equal 
energy-quality basis) is presented as the best way to arrange and analyze 
ecosystems hierarchically according to their capacity to develop complexity and 
to tolerate stress. The patterns of ecosystem response to stressors, including 
positive, steady-state, and declining responses and possible extinction, are 
discussed. It is argued that, to solve the problems of ecosystem management and 
the issues of environmental impact, studies and analyses must be done at the 
level of the ecosystem and care should be taken to quantify both the stressor 
and the stress with units of comparable energy quality. 

Today most of the biosphere has been altered in some way by the 
activities of man. With human impact on ecosystems becoming more 
obvious and more damaging to the economy of nations, the 
ecologist's interests are changing from descriptions of steady-state 
ecosystems to studies of ecosystem perturbations and their imphca- 



*Current address: Council on Environmental Quality, Washington, D. C. 

62 



STRESS AND ECOSYSTEMS 63 

tions to ecosystem structure, function, and stability. Sectors of the 
biosphere that are relatively more sensitive to human alteration (e.g., 
atmospheric and aquatic systems) initially received the greatest 
public attention. Terrestrial systems have been studied in relation to 
the impacts of ionizing radiation and radionuclide contamination 
(Woodwell, 1970). Marine and coastal systems are now under intense 
study as human population centers continue to grow in coastal areas 
and the demands for fossil fuel increase the intensity and frequency 
of oil and thermal pollution incidents (Cowell, 1971; Gibbons and 
Sharitz, 1974; Ferguson-Wood and Johannes, 1975). Another line of 
research uses laboratory microcosms to study the impact of heat, 
radiation, oil, and other pollutants on microecosystems (Byers, 1962; 
Moore, 1964; Copeland, 1965; Ferens and Byers, 1972; H. T. Odum, 
1974). 

Piatt (1965), H. T. Odum (1967), Woodwell (1970), and others 
suggested that ecosystem response to external impact follows certain 
common patterns regardless of ecosystem type or type of impact. If 
they are correct, it would be unwarranted to continue to duplicate 
certain types of studies every time a new perturbation to the 
biosphere is introduced by man. If there are patterns of ecosystem 
response to stressors, we should use this knowledge to anticipate 
human impact on natural ecosystems. This paper has two objectives, 
first, to review the information available on the response of 
ecosystems to stressors to determine whether there are recurrent 
patterns of response, and, second, to suggest some approaches for the 
study of stress and natural ecosystems. The synthesis highlights 
controversial ideas with the hope of stimulating further research on 
the issue. 

DEFINING STRESS AND STRESSORS 

The concept of stress is commonly applied to describe the 
behavior of systems of all kinds. Meier (1972) summarized a number 
of definitions of stress: Stress was initially defined as "the forces or 
pressures exerted upon a material." Later, biological stress was 
defined as "the rate of all the wear and tear caused by life." In social 
studies, stress characterizes "physical, social, and cultural conditions 
likely to be discomforting for most people living within a specific 
group." Stress is also viewed as "a response to external or internal 
processes which reach those threshold levels that strain psychological 
and physiological integrative capacities close to or beyond their 
limits." Finally, stress can be defined as "any force that pushes the 
functioning of a critical subsystem beyond its ability to restore 



64 LUGO 

homeostasis through ordinary, nonemergency adjustment processes." 
Selye (1956) and Fitch and Johnson (1977) distinguished 
between stress and stressors. A stressor is any condition or situation 
that causes a system to mobihze its resources and increase its energy 
expenditure. Stress is the response of the system to the stressor. 
Responses to stressors may include adaptation or functional disorder. 
Adaptations allow the system to overcome the stress or to avoid it. 
Functional disorders can be ameliorated or can eventually lead to 
exhaustion and death. H. T. Odum (1967) pointed out that, although 
different stressors had different impacts on an ecosystem (e.g., 
removal of organisms, higher respiration rates, or diversion of 
incoming resources), they all diverted potential energy flows that 
otherwise could do useful work in the system. He then defined stress 
as a drain of calories of potential energy flow. According to his 
definition, stress can be measured by changes in the flows of energy 
in a system, disappearance of previously existing flows, or ac- 
celeration of repair work. 

TYPES OF STRESSES AIMD STRESSORS 

Regardless of how stress is defined or of the stressor involved, the 
concept of stress as normally used invokes an interference wdth the 
normal function of a system; its effects are most dramatically 
observed after certain thresholds of tolerance are exceeded; and it 
appears that beyond these thresholds recovery is usually difficult. 
When systems are stressed for short periods of time and have an 
opportunity to recover during periods of low stress, the stressor is 
said to be acute. Other systems are exposed to the effects of 
continuous or chronic stressors. When organisms function despite the 
presence of a chronic or acute stressor, the intensity and the type of 
stressor are said to be adaptable because they allow the systems to 
survive. Surviving systems are equipped to overcome the drain of 
potential energy and still remain competitive. Adaptability does not 
imply absence of an energy drain, however. All stressors are 
analogous to energy barriers that organisms and ecosystems must 
continuously overcome if they are to survive. For example, a 
halophyte must constantly deal with the problem of salinity even if 
it is adapted to salinity, just like wetlands and certain forests must 
overcome flooding or fire even though they have adaptations to cope 
with these factors. Morowitz (1968) said that the rate of protein 
turnover in organisms follows an exponential function of tempera- 
ture which rises rapidly above 40"^ C for most animals. Thermophilic 
bacteria, however, can survive higher temperatures because their 



STRESS AND ECOSYSTEMS 65 

rapid rise in protein turnover occurs above 50° C. The cost of 
high-temperature survival in terms of protein synthesis is staggering, 
how^ever, and only a few species w^ith very low biomass and a fast 
turnover of this mass can survive such conditions. If the pH of the 
water changes, then an aquatic organism's tolerance to high tempera- 
ture decreases (Brock, 1970), presumably because of a synergistic 
effect of one stressor on another (Vernberg and Vernberg, 1974). 

Thus it appears that we need to distinguish between the stressors 
that are part of an ecosystem's "normal" everyday environment and 
those added by man or by acute events with infrequent recurrence. 
Both types cause energy drains, but the effects of natural stressors 
are not as immediately obvious to an observer as are those of 
additional energy drains imposed allogenically on a system. 



ENERGY COST OF STRESS 

The energy cost of stress to a system is probably a function of 
the intensity of the stressor (i.e., how much energy it drains per unit 
area and unit time), the multiplicative or additive effect of this 
energy drain on the overall function and homeostasis of the system, 
the frequency of its occurrence, the type of ecosystem being 
stressed, the condition of the system at the time of impact, the 
intensity of other stressors at the time of impact, the residual effects 
of other stressors on the system, and the frequency of return of these 
particular stressors. Chronic stressors, which operate for longer time 
periods than acute stressors, usually drain more energy from a 
system. Acute stressors may be very damaging, however, depending on 
the intensity of the stress, the time interval at which it reoccurs, and 
the adaptability of the stressed system. Also, the multiplicative 
impact of energy drains on the overall function and homeostasis of 
the system deserves careful consideration since a small energy drain 
in a component with large amplification value on the function of the 
ecosystem may be more damaging than a large energy drain in one 
with less influence on other properties of the system. An example 
would be the relative impact of a poison vs. that of a fire on the 
growth of an ecosystem. 

PREDICTABLE AND UNPREDICTABLE ENVIRONMENTS 

Some investigators have differentiated environments on the basis 
of predictability and used this difference as a measure of stress 
(Slobodkin and Sanders, 1969; Sanders, 1969; Colwell, 1974). They 



66 LUGO 

give as examples of unpredictable environments boreal and tropical 
sea bottoms with low dissolved-oxygen concentrations (<2 to 5% 
saturation) and seasonal temperature fluctuation (~5.5°C), sewer 
outfalls and outfalls of canneries, the edges of anoxic zones in 
estuaries and lakes, and deserts. Hickman (1975) considered the 
shallow soils of the upper slopes of mountain peaks to be 
unpredictable environments for plants growing on them. Bleakney 
(1972) suggested that acyclic extreme tides prevented the occurrence 
of genetic selection and behavioral adaptation in littoral commu- 
nities. Ehrlich et al. (1972) documented the extinction of butterflies 
and the lowering of population densities in subalpine ecosystems as a 
result of unusual weather (a wet June followed by heavy, late 
snows). 

These environments are obviously harsh, v^th factors that exhibit 
a relatively wide amplitude of variation, but are they really 
unpredictable? Slobodkin and Sanders (1969) defined an unpredict- 
able environment as one in which "the variance of environmental 
properties around their mean values are relatively high and unpredict- 
able both spatially and temporally." This definition is subjective and 
presents a few problems when it is used to evaluate the degree of 
unpredictability of natural environments. First, data are usually 
meager and do not allow the necessary calculations. Second, seasonal 
variations may appear to be unpredictable when they are, in fact, 
very predictable over a longer period of observation. Third, how do 
we know what is unpredictable to a natural system? The problem 
with the use of the terms predictable and unpredictable was made 
obvious in the discussion following the presentation of the paper by 
Slobodkin and Sanders at the Brookhaven symposium in 1969. 
Slobodkin could not agree with L. C. Cole on whether cave, 
hot-springs, and salt-lake ecosystems were or were not predictable 
environments. Yet, we would intuitively consider them very stable 
environments. In fact. Brock (1970) showed this to be true for hot 
springs, and Poulson and Culver (1969) described the environmental 
constancy of the cave environment. 

Colwell (1974) conceptualized the term predictability as the sum 
of two separate components, constancy and contingency. Contin- 
gency represents the degree to which time determines a state (the 
value is minimal when the probability of occurrence of each state is 
independent of season), and constancy is a measure of sameness of 
state from year to year. Predictabihty, according to Colwell, is 
essentially a measure of the variation among successive periods in the 
pattern of a periodic phenomenon. When the variation is low, 
predictability is high. He argues that the same degree of predict- 



STRESS AND ECOSYSTEMS 67 

ability can have different effects on different organisms and that 
constancy and contingency may be as important as elements of 
adaptive strategies as they are as environmental constraiints on 
evolution. 

Since predictability implies anticipation, predictable environ- 
ments can be anticipated, but unpredictable environments cannot. 
The abihty to anticipate rests on the system subjected to the 
environment; thus the relationship between the system and its 
environment becomes crucial in defining the degree of predictability 
or unpredictability an environment represents to a system. Slobodkin 
and Sanders (1969) said that predictabiUty v^as partly dependent on 
the organism and was not necessarily an environmental property. We 
would expect that, all other conditions being equal, the smaller and 
simpler the system, the greater its susceptibility to short-term 
environmental variability. However, miniaturization may be a suc- 
cessful evolutionary response to a long history of wide fluctuations. 
Regardless of strategy, if we assume that survival implies adaptability 
and that adaptability enhances anticipation of the environment, we 
would call the same environment an unpredictable one for the 
system that perishes and a predictable one for the system that 
survives. 

Environments have also been described as constant, inconstant, 
cycUc, and randomly fluctuating or as being in any intermediate 
state. Stearns (1978) showed that it is incorrect to think in terms of 
just two contrasting situations (predictable or unpredictable). He 
found that even within one type of ecosystem (reservoirs) analysis of 
four variables separated 19 of them into distinct classes of variation 
that formed a diverse mosaic of environments. Stearns concluded 
that different environments could rank differently for any measure 
of fluctuation or stability for each significant environmental 
variable. Whittaker (1975) pointed out several possible characteristics 
of fluctuations that need consideration — quahty and duration, 
relative amplitude of a regular fluctuation, relative irregularity, and 
duration of the pattern in evolutionary time. Obviously the number 
of points along a continuum of possible intensities of stress 
associated with these types of environmental situations is significant 
to any analysis of stress and ecosystems. 

The classification of an environment in any category depends on 
our abihty to analyze and understand data and on the completeness 
of the data sets. Complex time-series analyses are required to detect 
long-term cyclic events on data sets that before analysis appear to be 
random and unpredictable. The long-term cycles, although perhaps 
not important to organisms, may be significant to populations or 



68 LUGO 

whole ecosystems, as shown, e.g., by Stearns (1975) in his discussion 
of the effects of reservoir fluctuations on the evolution of popula- 
tions of mosquitofish. Analyses of this type are becoming very 
common in the hterature (Colwell, 1974; Sneyers, 1976; Dyer and 
Tyson, 1977). Findings indicate that such potential stressors as 
drought (Dyer and Tyson, 1977), fire (Houston, 1973), hurricanes 
(Thomas, 1974; Gentry, 1974), flash floods (John, 1964), storms 
that cause catastrophic drifts (Anderson and Lehmkuhl, 1968), or 
rainfall (Beatley, 1974; Colwell, 1974) have recurrent, predictable 
patterns to which ecosystems can adapt and which they depend on 
for their survival and maintenance. 

Living systems "track" the environment through a number of 
adaptations that have bearing on environmental anticipation, e.g., 
storages of energy, life forms, strategies of life cycles, phenological 
patterns, migrations, successional recovery, alterations in rates of 
physiological processes, and lowering of productivity-to-biomass 
ratios. At the population level, e.g., Bott (1975) showed that bacteria 
in a stream with a fluctuating thermal event (up to 23°C/year) had 
adapted to a temperature 5 to 20° C higher than the mean 
temperature of the stream. An optimum growth temperature near 
the lethal temperature becomes a predictive mechanism for random 
temperature fluctuations; temperature increases have less likelihood 
of exceeding the higher tolerance limit. 

Environmental fluctuations are stressful to ecosystems (Dunbar, 
1960), and, as the environment becomes more variable, the cost of 
anticipation should increase. Anticipating a changing environment 
remains an essential prerequisite of life, however, if the organism or 
the ecosystem is to survive. 

I agree with Margalef's idea (1969; 1975) that, as they develop 
toward the steady state, ecosystems gain information that, in part, 
allows them to anticipate fluctuations in their environments. At the 
ecosystem level an event may cause mortality in certain sectors of 
the system, but the system as a whole may be able to adapt to it. For 
example, hurricanes kill mangrove trees, but they are essential for the 
survival of the mangrove forest (Cintron et al., 1978). The annual 
migration of the thermocline in a temperate dimictic lake creates 
severe problems for certain populations of bacteria, zooplankton, 
and phytoplankton, but, for the lake as a whole, this event is 
predictable and essential for the distribution of heat, nutrients, and 
organic fuels. Thus, if we select the whole ecosystem as a point of 
reference, there cannot be naturally unpredictable environments that 
are colonized by steady-state ecosystems. Harshness of the environ- 
ment should not be confused with unpredictability. 



STRESS AND ECOSYSTEMS 69 

Truly unpredictable events are, perhaps, earthquakes and many 
human impacts. Human interferences with natural ecosystems are 
unpredictable because they do not necessarily follow a recognizable 
pattern and they do not operate long enough to allow for 
adaptations to develop. Many activities of man, while nonadaptable 
for many natural systems, however, do select for interface ecosys- 
tems that quickly adjust to human interference and develop 
short-term steady states depending on continuous human interven- 
tion. These systems have many of the characteristics of the 
physically controlled communities described by Sanders (1969, 
Table 1 ) and are dominated by exotic or successional species. 



TABLE 1 

PROPERTIES OF PHYSICALLY CONTROLLED, BIOLOGICALLY 
ACCOMMODATED, AND STRESSED ECOSYSTEMS* 

Physically Controlled 

Small numbers of species per numbers of individuals 

Widely fluctuating physical conditions that are not rigidly predictable 

Organisms exposed to severe physiological stress 

Environment of recent past history 

Biologically Accommodated 

Large numbers of species per numbers of individuals 

Physical conditions constant and uniform for long periods of time 

Environment of high predictability 

Ecosystems Under Stress 

Succession arrested or set back periodically 

Few successional stages between pioneers and climax; autosuccession and cyclic 

succession common 
Plants may show stress by aberrations or leaf deformations 
Changes in the intensity of stressors cause shifts in species composition; 

generally species diversity decreases with successional time 
P/R ratios of 1, > 1, or < 1 at steady state 
Speed of succession is a function of physical environment and the point in the 

system where disordering energies act 
Species show zonations that reflect gradients of stress; zones should not be 

confused with successional stages 

*Data on "physically controlled" and "biologically accommodated" eco- 
systems are from Sanders (1969). 



70 LUGO 

ENERGY BASIS OF STRESS 

H. T. Odum's (1967) definition of stress as a drain of potential 
energy has an advantage over all other definitions because it provides 
a common basis (energy) on which to evaluate all types of stress in 
all kinds of systems. More significant, however, is that the energy 
required for all natural processes behaves according to well-defined 
laws that provide a quantitative basis for evaluating ecosystem 
function and response to stressors. The capacity of a system to 
overcome stress, then, depends on the balance between the rate of 
recovery of its energy stores and the magnitude of the energy drain 
caused by the stressor. 

We could argue against Odum's definition of stress by pointing 
out that many drains of potential energy are not normally called 
stress but would be by his definition, e.g., the energy drain of 
nighttime respiration in plants. We would not normally identify 
nighttime darkness as a stressor, but shading of a plant or an 
ecosystem for a prolonged time period certainly would be considered 
one. Rogers (1977), for example, after shading a coral reef for 35 
days, found significant rates of mortality and slow rates of recovery. 

The health of ecosystems that are normally considered highly 
stressed could also be used to illustrate the futility of identifying 
stressors and defining what they do to a system. Salt springs, thermal 
springs, or deserts actually become stressed if the "stressful condi- 
tions" to which they are adapted are changed. The usefulness of the 
concept of stress is obviously limited if we cannot deal with the 
apparent subjectivity and relativity of the term. 

Selye (1956) suggested that most environmental situations can 
become stressful to given individuals and that stress is a normal 
condition of anyone's environment. The realization that stressors and 
energy drains are part of any natural environment is an important 
step in generalizing about stressors and their impact on ecosystems. 
This is the basis for my earlier suggestion that we differentiate 
between background or normal stress and additional stress caused by 
allogenic forces. In fact, as discussed in the following section, 
stressors may become subsidies to certain ecosystems, and their 
productivity and growth may decrease if the stressors are removed 
(Fig. 1). 

Push-Pull Model of Stress 

Figure 2 is a model of the push— pull (positive— negative) effect 
of ordering and disordering factors in the environment (in this case, 
temperature) proposed by H. T. Odum (1974). The model depicts 



STRESS AND ECOSYSTEMS 



71 



POSITIVE RESPONSE 



NEGATIVE 
STEADY STATE RESPONSE AND EXTINCTION 




INTENSITY OF STRESSOR 

. -^" 

Fig. 1 Response of living systems to stressors. Similar curves of 
response were proposed by E. P. Odum (1971), Gibbons (1976), and 
Odum and Kroodsma (1976). Examples of positive response with 
increasing stress intensity were reported by Yentsch et al. (1974) for 
algal populations under temperature stress and by Carpelan (1964) 
for algae under salinity stress. Conditions of steady-state response 
are common in most stress experiments [e.g., Woodwell and Rebuck 
(1967) for radiation and Erdman (1966) for DDT and Xrays]. 
Rapid declines and extinction are equally common (Woodwell and 
Marples, 1968; Coutant and Cox, 1976). Few studies cover the 
whole spectrum of response for a given environmental factor. 



the well-known facts that all structures have a natural tendency to 
deteriorate and that Ufe as we recognize it represents an improbable 
state of organization whose maintenance requires continuous energy 
flows. The implication is that certain drains of potential energy that 
we call stresses when they irreversibly alter a system are, in fact, 
necessary and constantly present components of all life processes. 
H. T. Odum (1976) suggested that disordering stimulates ordering 
and, thus, questioned the tendency to regard stress as bad and 
disorder as evil. 

The push— pull model of stress proposes that stressors, such as 
temperature, may initially accelerate and then decelerate processes. 



72 



LUGO 




k,IJD 



kjlJD 



Fig. 2 Model of push— pull effects of thermal energy on ecosystems 
proposed by H. T. Odum (1974). Note that ordering and disordering 
processes depend on each other. Arrows show the direction of 
energy flows; tanks are state variables; the large double arrowhead 
represents multiplicative energy interactions; and the circle repre- 
sents the energy source. 



Depending on the characteristics or state of the stressed system, the 
energy influx of the stressor may or may not benefit the system. 
H. T. Odum (1974) pointed out, for example, that high-temperature 
stress may be useful in accelerating rates of respiration, thus causing 
the release of minerals for photosynthesis. This function would be a 
positive asset to an oligotrophic aquatic system but not to a 
eutrophic system. Nixon (1969) and Odum, Nixon, and DiSalvo 
(1970) postulated a similar role for photorespiration in ohgotrophic 
hypersaline systems rich in organic matter. In this case, the energy 
drain of photorespiration was shown to benefit mineral availability in 
an otherwise nutrient-poor system. Disruptive stressors, such as fires, 
tides, floods, water currents, volcanic eruptions, and hurricanes, also 
have a positive role at the ecosystem level. Without a periodic 
disruption ecosystem growth processes stagnate as resources are 
immobilized by their structure. Bursts of growth and high net 
productivity usually follow disturbances, and rejuvenated systems 
replace senescent systems. To have a positive effect, the energy input 



STRESS AND ECOSYSTEMS 



73 



to a system must be coupled with increased availability of other 
essential resources. Otherwise the input energies cannot be usefully 
converted. Table 2 summarizes literature examples of push— pull 
effects of different stressors. 

These examples suggest that, as the inputs of energy to a system 
change (including energies that push and/or pull), the biotic 

TABLE 2 

EXAMPLES OF POSITIVE (PUSH) AND NEGATIVE (PULL) 

EFFECTS OF STRESSORS ON ECOSYSTEMS 

AND POPULATIONS* 



Stressor 



Pushing effect 



Pulling effect 



Ionizing 
radiation 



Tidal 
extremes 



Water flow 



Flooding 



Volcanic 
eruptions 

Denudation, 
clipping, 
herb ivory, 
or defolia- 
tion 

Salinity 



Observed faster decomposition, 
leaf fall, gi-owth, and recovery 
rates for a variety of dosages 
(Woodwell and Marples, 1968) 

Redistribute nutrients, sedi- 
ments, organic matter, and 
organisms (Odum, Copeland, 
and McMahan, 1974) 

Brings nutrients and redistributes 
larvae (Anderson and 
Lehmkuhl, 1968); brings food 
and O2 and removes toxic 
substances (H. T. Odum, 1955) 

Removes competition; signals 
the beginning of phenological 
events (John, 1964) 



Allow for better nutrient, 
moisture, and competitive 
environments (Eggler, 1967) 

Stimulates plant productivity 
(Churchill et al., 1964); 
diversifies community at 
low rates (Penfound, 1964) 

Allows higher gross productivity 
in mangroves up to about 
seawater strength (Hicks 
and Burns, 1975) 



Can be lethal; disrupts 
structure and increases 
respiration rates; changes 
species composition 
(Ferens and Byers, 1972) 

Exposes organisms to 
lethal conditions 
(Glynn, 1968) 

Removes structure; causes 
high energy maintenance 
costs in plants and 
animals (Anderson and 
Lehmkuhl, 1968; 
Moore, 1964) 

Increases energy mainte- 
nance costs; temporarily 
decreases number of 
taxa and individuals 
(Hoopes, 1974) 

Suffocate and kill plants 
and animals (Eggler, 
1967) 

Removes structure and 
reduces diversity at high 
rates; causes mortality 
(Churchill et al., 1964) 

At values higher than 35 /qq, 
increases respiration rates 
and decreases transpira- 
tion and net productivity 
rates (Lugo and 
Snedaker, 1974) 
(Table continues on following page.) 



74 



LUGO 



Table 2 (Cont.) 



Stressor 



Pushing effect 



Pulling effect 



Eutrophi- 
cation 



Fire 



Herbicides, 
oil, and 
other 
poisons 



Heavy 
rains 



High tem- 
perature 

Low tem- 
perature 



Temperature 
amplitude 



Hurricanes 



Insecticide 



Stimulates primary productivity 
and growth of consumers 
(E. P. Odum, 1971) 



Makes nutrients and moisture 
more available; reduces 
competition (Wright, 1976) 

Select for certain life forms over 
others, survivors grow faster 
(Wein and Bliss, 1973; 
Niering and Goodwin, 1974; 
Burk, 1977) 



Act as a clue for starting pheno- 
logical events in deserts 
(Beatley, 1974); relieve 
salinity in coastal situations 
and redistribute nutrients 
(Chabreck and Palmisano, 
1973) 

Accelerates processes, particu- 
larly respiration and recycling 
(Smith et al., 1974) 

By slowing down processes, 
allows for conservation of 
storages (Mooney and 
Billings, 1965) 

If short-term, fluctuations may 
stimulate metabolism 
(Sweeney and Schnack, 1977); 
increases resistance to thermal 
shock (Hubbs, 1964) 

Bring water, nutrients, sedi- 
ments, and propagules 
(Chabreck and Palmisano, 1973) 

DDT (5 — 10 ppm) enhances 
resistance to X-ray radiation 
(Erdman, 1966) 



Shifts species composition, 
causes anoxic conditions, 
and eventually reduces 
species diversity and 
complexity (E. P. Odum, 
1971) 

Removes structure 
(Wright, 1976) 

Reduce productivity by 
altering behavior and 
physiology, poisoning, 
and killing organisms 
(Krebs and Burns, 1977); 
lowers species diversity 
(Tomkins and Grant, 1977) 

Remove structure and may 
cause other stresses, such 
as flooding, which affect 
gas exchange of wetlands 
sediments and the 
turbidity in aquatic 
systems (Hoopes, 1974) 

Can be lethal; reduces 
species diversity 
(KuUberg, 1968) 

Freezes can be lethal 



If amplitude is wide and 
change is rapid, it can be 
lethal (Hubbs, 1964; 
Sastry, 1976) 

Structure is removed 
(Craighead, 1964) 

Eventually lethal (Erdman, 
1966) 



*Literature citations are not intended to imply that these are the only or the 
most significant documentations of the example. 



STRESS AND ECOSYSTEMS 



75 



components selected for are those that somehow maximize energy 
flow despite the presence of stressors. This is done either by diverting 
all incoming energies to overcome stress or by extracting useful work 
from the disordering force. Energy drains are normal processes 
affecting living systems and should be identified as such even if they 
normally do not reach critical thresholds beyond which recovery is 
difficult. 

To evaluate the relative impact of push— pull effects on ecosys- 
tems and to gain insight into the cost of recovery and ecosystem 
resilience, we can calculate ratios of disordering-to-ordering energies 
(Richey, 1970). This involves calculating the magnitude of energy 

TABLE 3 

RATIO OF DISORDER TO ORDER IN ECOSYSTEMS 
SUBMITTED TO STRESS 



Ecosystem 


Stressor 


Disorder/ order 


Reference 


Subtropical dry forest 


Cutting 


1 : 1,270 


Ewel, 1971a 


Subtropical dry forest 


Herbicides 


1 : 17 


Ewel, 1971a 


Subtropical moist forest 


Gamma radiation 


1 : 10,000 


H. T. Odum, 
1970 


Microcosms (terrestrial) 


Burning 


1 : 13 


Richey, 1970 


Microcosms (aquatic) 


Sonication and 
temperature 


1 : 10,000 


Richey, 1970 


Vietnam (whole 


War (including 


1 : 8.7 


Brown, 1977 


country)* 


bombs and 
herbicides) 







*Reduced to fossil fuel equivalents. 



flows that disrupt ecosystem structure and function and the 
magnitude of energy costs associated with reordering and maintain- 
ing order in the system. Table 3 summarizes literature reports on this 
ratio. Most values are derived from experimental situations, where 
the disordering input can be computed easily. Results show that 
disordering energies have considerable amplification and that build- 
ing and maintaining order is extremely expensive relative to the cost 
of destruction. Obviously, the capacity of a system to regenerate 
depends on the availabihty of enough energy sources to reorganize 
the disordered structure. Since the availability of energy is a function 
of the environment, the type of environment dictates rates of 
recovery and degree of complexity at the steady state. In the term 
complexity, I include such measures of ecosystem organization as 



76 LUGO 

species diversity, structural organization, physiognomy, and pheno- 
logical organization. 

The concept of stress should, then, be applied in a hierarchical 
fashion relative to the various levels of biological organization. As 
ecologists, we are interested in stressors as they relate to life zones, 
individual ecosystems, and populations. Other scientists do their 
analysis at the organismal, cellular, or molecular and atomic levels of 
organization. To avoid the pitfalls of subjectivity, we need to develop 
appropriate criteria for evaluating the relative effects of stressors on 
the complexity and rate of recovery of systems at each of these levels 
of organization. 

The Energy Signature of Ecosystems 

The push— pull model (Fig. 2) suggests that the amount of 
structure and complexity a system is capable of building and 
maintaining depends on the net effect of positive and negative forces 
in the environment. 

The sum of all incoming energy flows to a system and the pattern 
of their delivery expressed on an equal energy- quality basis is called 
the "energy signature" of the system (H. T. Odum et al., 1977). The 
quality of an energy source depends on its concentration (Odum 
et al., 1977). High-quality sources have a high energy content per 
unit volume, and low quality sources, like solar energy, are diluted 
and, thus, perform less work per unit volume. Energy signatures must 
be expressed on an equal energy-quality basis to show the relative 
ability of the components to generate work and control the system. 
The energy signature provides a way to categorize ecosystems 
according to environmental carrying capacity or capacity to deal 
with stress, e.g., as Odum, Copeland, and McMahan (1974) did for 
coastal systems. As the energy signature changes, the loss or gain of 
energy may become a source of stress or a subsidy to the system. 

Since the actual intensity of background or normal disordering 
energies in a given environment may be impossible to measure, the 
measure of stress at the level of the life zone must be made relative 
to the most complex systems on earth, because they represent the 
best that can be done with the energy flows and resources available 
to all natural systems. Other life zones could then be arranged in a 
hierarchical and relative scale. 

Perhaps the best system for classifying terrestrial and wetland 
ecosystems is Holdridge's life-zone system (1967) (Fig. 3). This 
system has worldwide application, is an objective determination of 
life zones based on climatic data (which approximate the energy 



STRESS AND ECOSYSTEMS 



77 



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78 LUGO 

signature), attempts to account for the factors that control ecosys- 
tem productivity, and has been tested widely (Holdridge et al., 
1971). The life zone is a bioclimatic zone of the earth with a unique 
set of conditions and capacities to support biological complexity. 
For each climatic life zone of the world (Holdridge identifies about 
120), a maximum level of ecosystem performance is possible. 
Performance can be measured in terms of gross energy flow or total 
ecosystem complexity. Holdridge (1967) has already shown that the 
complexity of forested terrestrial systems varies according to life 
zone. This complexity is equal to the product of maximum tree 
height (m), number of species per 0.1 ha, basal area (m' /O.l ha), tree 
density per 0.1 ha, and a constant, 10~^ . Life zones can be compared 
with one another in terms of their relative potential to support 
ecosystems of different complexity. The impact of additional 
stressors on a given type of ecosystem should vary with life zone. 
Ecosystems in humid life zones obviously respond differently from 
those in arid life zones. For example, Ewel (1977) reported slower 
responses to stressors (cutting and herbicides) in dry tropical climates 
than in humid tropical climates and described two different 
successional strategies for ecosystems in these two contrasting 
environments. 

His results and those of others suggest that care should be taken 
in comparing ecosystems across latitudinal or climatic gradients since 
they should not be expected to exhibit the same speed of response to 
stressors. The optimism of Slobodkin and Sanders (1969), who 
suggest that latitude has no fundamental importance on species 
diversity considerations, is premature. They believe that environ- 
mental constancy is more important; however, environmental con- 
stancy per se, without adequate energy inputs, cannot sustain 
complexity. 

The life-zone concept has not been applied to lakes and streams, 
but these systems are so dependent on external inputs that there is 
no reason not to expect a life-zone pattern within them. Since 
climate controls water availability and runoff, nutrient runoff from 
the land, and evapotranspiration, it should also influence the patterns 
of response of lakes and rivers. 

Model of the Action of Stressors on Ecosystems 

The analysis of individual ecosystems requires detailed examina- 
tion of the forces acting on them. To analyze the possible ways in 
which stressors affect individual ecosystems, I first develop a 
conceptual model of an idealized unstressed ecosystem (Fig. 4). In 
this simple model, we can see the relationship between four state 



STRESS AND ECOSYSTEMS 



79 



/ V 




Fig. 4 Simplified model of an ecosystem without stress. The large 
bullet-shaped outline is the boundary of the system; P is photo- 
synthesis; and R is respiration (for other symbols, see Fig. 2, and, for 
a discussion of the model, see the text). All energy inputs are 
eventually dissipated into degraded heat, according to the second 
law of thermodynamics. 



variables and three ecosystem processes. The state variables are 
nutrient concentrations and water availability (a measure of fertil- 
ity), live biomass, dead organic matter, and a hypothetical variable 
called organic complexity, which includes measures of species 
diversity and three-dimensional diversity and complexity discussed 
by Whittaker (1969). It is included here simply to point out that 
the organization of the ecosystem is an energy-demanding process 
and, thus, is subject to the impact of stressors. The cost of this 
variable is borne by each of the living components of the system, but 
this does not invalidate the fact that complexity of function and 
organization is an ecosystem property that responds to its energy 
signature. All state variables have a positive role in the system and 
provide positive feedback to its productive sector. The processes 
illustrated in the model are the photosynthetic conversion of solar 



80 LUGO 

energy into chemical energy (P), the respiratory process (R), and the 
many cycles and feedbacks of the system which contribute to its 
homeostasis. 

In a system like this, there is a high cost of depreciation to 
support live biomass and organization. In steady-state systems the 
quality of energy feedbacks among ecosystem components increases 
relative to those of successional systems. Higher quality energy flows 
contribute to a higher rate of energy flow through the system as a 
whole. The respiration of the system increases on a unit-area basis 
with age because of the increasing cost of upgrading energy qualities 
in the system (i.e., the cost of converting low-quality forms to higher 
quality states). 

In Fig. 5 stressors are added to the model. The energy signature 
of the system is subdivided into five potential sources of stress. 
Source 1 delivers the primary energy of the system, which in this 
example is solar energy for photosynthesis; source 2 diverts solar 
energy before it is transformed to chemical energy by plants (e.g., by 
shading); source 3 diverts energy after it is transformed into chemical 
energy but before it is incorporated into structure (e.g., by the 
harvest of labile sugars by a consumer, such as man); source 4 
removes storages (e.g., by harvests or by drainage of water); and 
source 5 accelerates the respiration of the system (e.g., by changes in 
temperature). Each of these external sources impinges on the 
ecosystem at a certain rate and with a certain periodicity of delivery 
which depends on the type of life zone. When the energy signature 
changes, the change may become stressful. 

The model of stress in Fig. 5 suggests that different stressors 
affect different functional sectors of the ecosystem and that perhaps 
the response of the system to these different types of drains also 
changes according to the type of stressor. Causal relationships must 
then be analyzed relative to the type of stressor, its pattern of 
delivery, its intensity, and the kinds of changes that it causes in the 
system. After a certain threshold is exceeded, the stressor causes 
energy flows to be diverted away from the system and diminishes the 
ability of the system to continue to upgrade internal energy stores. 
Thus the overall organization and homeostasis of the system is 
altered. There is flexibility in each system, however, vdth regard to 
its response to and the ultimate impact of the stressor. According to 
Fig. 5, more energy may be diverted into living mass, less into 
complexity, or more into respiration, or there may be an increase in 
the amount of dead organic material. The ultimate strategy probably 
depends on the type of stressor and where in the system it operates. 



STRESS AND ECOSYSTEMS 



81 




Fig. 5 Simplified model of an ecosystem influenced by a number of 
stressors. (For identification of symbols, see Fig. 2, and, for a 
discussion of the model, see the text.) Each stressor, by draining 
energy from a different sector of the ecosystem, affects the response 
in a unique way. Stressorr 4A, for example, has a stronger effect on 
the system than stressors 4B or 4D because it directly affects the 
photosynthetic process and, thus, decreases the ability of the system 
to restore its energy stores. Stressors 1 to 3 are equally damaging to 
ecosystems relative to the effects of stressors 4B to 4D and 5. 



The point we need to emphasize is that, although all stressors 
divert potential energy away from the system, not all stressors 
handicap the system to the same degree, even though they drain 
equal amounts of energy. For example, a stressor that removes 
structure but does not alter the primary productivity of the system 
may not have as much impact as one that reduces the ability of the 
system to photosynthesize and, thus, to replenish its energy stores. 
In the first case the system will recover rapidly, but in the second 
recovery may be slow. This aspect of the problem has important 
implications for rates of recovery from stress and for management of 
natural ecosystems. Table 4 lists a number of naturally stressed 
ecosystems and classifies their respective natural stressors by type. I 
have tried to illustrate the rate at which the systems respond to stress 



82 



LUGO 






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84 LUGO 

through successional recovery. Note that systems stressed by removal 
of structure or by acceleration of respiration can still function and 
will recover rapidly because there has been no direct impact on 
factors regulating primary productivity. Systems submitted to 
stressors that do alter their productive capacity, however, have little 
ability to recover or to negotiate further stress. If this is true, 
stressors affecting high-quality energy stores appear to have a lesser 
impact on a system than those affecting low energy-quality sectors of 
the system. 

Change of Energy Signature 

Examples of changes in the energy signature of an ecosystem are 
slow changes in climate (see Singer, 1970); changes caused in 
downstream sites by construction of a dam, e.g., the change in 
estuarine circulation patterns caused by the Aswan Dam (Sharaf El 
Din, 1977); and regional changes caused by alteration of water 
tables, e.g., in south Florida estuaries (Carter et al., 1973). 

Cooper and Copeland (1973), experimenting with microcosms, 
simulated regional drainage changes for Trinity Bay in Texas. They 
found more changes in the respiration and productivity of the system 
than in species composition. Later, as stressors became more intense 
(simulated by lack of freshwater nmoff or large organic-pollutant 
inputs), diversity index changed significantly and so did species 
composition. Alterations in energy flow rates before any significant 
changes in species composition were documented in the field by 
Carter et al. (1973). Apparently the substitution of species results 
from altered energy flows through the system. New ecosystem 
boundaries develop slowly in response to a different energy signature 
impinging on the ecosystem. 

Under some circumstances a change in an energy signature could 
result in a new ecosystem, with higher complexity and productivity 
than the original system it replaced, e.g., the drainage of certain (but 
not all) wetlands, which creates mesic ecosystems. In this case the 
overall carrying capacity of the environment increases; the original 
ecosystem is selected against by the stressor; and the new system is 
more vigorous because it is better adapted to the new energy 
signature. J. Ewel (1978) documented such a succession in the 
Everglades of Florida. 

Figure 6 shows as an example the energy signature of a marsh 
ecosystem subjected to thermal stress. It is obvious that, when 
energy quality is taken into consideration, tidal energy becomes the 
main energy source to a marsh, and fossil-fuel stress was not as 
significant as it appeared to be initially from its heat equivalence. 



STRESS AND ECOSYSTEMS 



85 




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Fig. 6 Calculation of the energy signature of a marsh ecosystem 
under the influence of thermal pollution (a) [data from H. T. Odum 
et al. (1977)]. The symbols in (a) are described in Fig. 2. Note that, 
when all the energies are expressed on the basis of equal quality 
(fossil fuel equivalents), their relative importance (c) changes in 
comparison to calculations based on heat equivalents (b). 



86 LUGO 

The change in the magnitude of an energy source when energy 
quality is taken into consideration raises an important question. Do 
energy-quality differences in stressors affect their impact on the 
ecosystem? For example, do poisons owe their effectiveness as 
stressors to their higher energy quality? The data in Table 3 do not 
allow for any valid generalizations, but the hypothesis could remain 
that stressors with high energy quality may be more effective than 
those with lower energy quality. Since I have already postulated the 
opposite effect when the quality of the stressed component is 
considered, it is possible that maximum stress results when a stressor 
with high-quality energy delivery affects a sector of the system with 
energy flow of low quality. 

PATTERNS OF ECOSYSTEM RESPONSE TO STRESSORS 

The response of cells, organisms, populations, and ecosystems to 
a wide variety of stressors may follow a common pattern (Fig. 1). 
This has been pointed out by a number of investigators (Selye, 1956; 
Piatt, 1965; H. T. Odum, 1967; Woodwell, 1970), who also 
identified patterns of response. Usually, when a system is stressed, it 
overcomes the initial low intensity of the stressor by activating 
internal homeostatic mechanisms. These were described for cells, 
organisms, and populations by Selye (1956) and for ecosystems by 
Piatt (1965) and Woodwell (1970). Many times low intensities of 
stress actually stimulate a system to performance above that of 
controls, probably because of higher internal physiological activity 
induced by the higher energy input (Fig. 1). As the intensity of the 
stressor increases, there is a period of steady state, when homeostatic 
mechanisms compensate for the energy drain, then a period of 
decline, and finally, if the stressor continues to intensify, a point of 
irreversible change. The point of collapse may be when energy 
reserves are exhausted or when the system reaches the limits of its 
adaptability. Figure 1 suggests that different stress response patterns 
reported in the literature may represent different sections of one 
single response curve that extends for the whole range of intensity of 
a given stressor. 

Ewel (1971a), describing the pattern of ecosystem response to an 
intermittent stressor (Fig. 7), showed that, if the stress condition is 
repeated before full recovery, the system gradually loses its capacity 
to recover and slowly degenerates into a low-biomass steady state. 
This same pattern of response has been reported in salt marshes 
receiving chronic exposure to oil pollution (Baker, 1971) and in 
floodplains exposed to chronic flooding (Gardner et al., 1972). 



STRESS AND ECOSYSTEMS 



87 



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MONTH 

Fig. 7 Model and simulation of the effects of a chronic stressor 
(continuous cutting at 1-year intervals) on tropical terrestrial 
ecosystems [data from Ewel (1971a)]. (For identification of 
symbols, see Fig. 2.) Cutting is a type 4 stress (see Fig. 5). As 
structure is continuously removed, the system develops a steady 
state at a lower amount of biomass. 



Stressors can also weaken systems and make them more 
susceptible to further stress. Woodwell and Brower (1967), for 
example, reported aphid population explosions induced by gamma 
radiation stress. The same phenomenon occurs in mangroves stressed 
by high salinity, frost, or alterations in drainage patterns (Lugo and 
Patterson Zucca, 1977). Involved in these responses are additive 
and/or synergistic effects among stressors vv^hich accelerate energy 
losses and rapidly reduce the system's capacity to negotiate more 
stress. 

STRESS AND ECOSYSTEM COMPLEXITY 



Ecologists use a variety of indexes to measure ecosystem 
response to stressors. Much attention has been placed on finding 
relationships betvi^een environmental change and species diversity or 
the stability of the system. [Consult the work of Baker (1970) and 



88 LUGO 

the volumes edited by Woodwell and Smith (1969) and Van Dobben 
and Lowe-McConnell (1975) for summaries of the various theories 
and arguments.] Sanders (1969), for example, listed the character- 
istics of physically controlled and biologically accommodated com- 
munities (Table 1). The idea that stressors have the effect of reducing 
species diversity by increasing adaptation costs is probably correct, 
because a stressor, by imposing energy barriers on a system, decreases 
its ability to support complexity. Too much emphasis has been given 
to the role of a stable environment, how^ever, without also acknowl- 
edging the balance between energy subsidies and energy drains in a 
given environment. All the energy flows entering the system and the 
variety of possible ecosystem responses to stress have been ignored in 
such efforts as that depicted at the top of Table 1. 

Slobodkin and Sanders (1969) suggested that short-term stability 
(a duration of about five generations) in an otherwise unpredictable 
environment decreased species diversity because opportunist species 
would temporarily gain dominance over the normal animal com- 
ponent of the system. If we assume that by "periods of predictable 
conditions" they mean a relaxation of stress, then their conclusions 
do not hold in theory or in practice. Theoretically, lower stress 
(higher predictability?) should increase the carrying capacity of an 
environment. Observations in rocky tidal shores (Connell, 1972; 
Dayton, 1971) showed that removal of dominants by a stressor 
results in a temporary increase in diversity. This also occurs in 
high-salinity environments after a storm decreases salinity stress. At 
these times species diversity increases for a short period but then 
returns to its lower value as stressful conditions return to high 
intensity. Thus a property of chronically stressed ecosystems is that, 
during their successional patterns, species diversity may decrease 
rather than increase (bottom of Table 1). 

Conflicting arguments about the causes of ecosystem complexity 
can be clarified if analyses are based on the total energy flow 
through the system. The productivity hypothesis of Connell and 
Orias (1964) was criticized by Sanders (1969), who argued that 
highly productive systems, such as marshes, are not necessarily 
diverse, as inferred from the productivity theory of ecosystem 
diversity. Others have argued that diverse systems are not necessarily 
stable (e.g.. May, 1975). The argument can be restated by substituting 
whole ecosystem analysis for generalizations based on population 
studies and total energy flow per unit area (the energy signature 
concept) for criteria of organic productivity. 

Ecosystem complexity is a function of the net energy available to 
a system. Net energy is the balance between the energy expenditures 



STRESS AND ECOSYSTEMS 89 

associated with normal respiration and all incoming energies that 
contribute to ecosystem growth and complexity minus all incoming 
energies that tax the energy budget of the system. Slobodkin and 
Sanders (1969) asked the question, Why don't more species adapt to 
stress? The answer must be related to the high energy cost of certain 
adaptations vs. the energy limitations to which ecosystems and 
populations are exposed. In highly stressed environments we would 
expect strong selective pressure for the most energy-efficient solution 
to the stress problem; this adaptation would then win over 
less-efficient competitors. High efficiency, however, is not conducive 
to the fast rates of energy flow which are associated with lower 
efficiency systems. 

Figure 8 presents a model that summarizes the proposed 
interactions and assumptions involved in maintaining ecosystem 
complexity. The first assumption is that the development and 
maintenance of ecosystem complexity involves energy expenditure. 
H. T. Odum (1970) proposed a formula to illustrate the rapid rise in 
the cost of ecosystem organization with increasing species diversity: 

N^ - N _ fEaA 
2 K 

where N = number of species 

f = fraction of the energy budget allocated to organization 
Ea = energy input per unit area 
A = total area of the system 
K = daily cost of maintaining species interactions 

The terms on the left side of the equation represent the number 
of possible interactions between species if organization is complete, 
and the terms on the right represent the amount of energy available 
for organization. Since the input of energy to a system is limited on a 
unit-area basis, the strategy of energy -resource allocation and the 
amount of work derived from energy transformations become 
significant factors in determining the competitive survival of a 
system. 

H. T. Odum (1970) stated that, when a system has a low number 
of species, only a small amount of energy is allocated to organization 
and a larger fraction of its energy resource goes to other work 
functions; thus more energy is needed to eliminate a species and 
more energy is available to compensate for stress. Hickman (1975), 
for example, showed that energy allocation for reproduction 
increased with stress in Polygonum plants; he reported that as much 
as 71% of the energy stores goes into this function. 



90 



LUGO 



Recycling 




Total 
Respiration 

Fig. 8 Model illustrating energy flows associated with the develop- 
ment and maintenance of structural complexity in ecosystems. (For 
identification of symbols, see Fig. 2, and, for a discussion of the 
figure, see the text.) The gross energy flow of the system (i.e., all 
incoming energies that contribute to order) can be allocated to 
overcome disordering energies (flow 1), to develop the initial 
amount of structure required for survival (flow 2) and/or to develop 
additional complexity and species diversity (flow 3). Each of the 
state variables feeds back positive work that increases the ability of 
the system to process more energy and to use resources more 
efficiently. Energy allocation for structural development and com- 
plexity increases if there is net energy and if the energy investment 
in the feedbacks (flows 4 to 6) are offset by the increase in the 
energy capture and conversion efficiency of the system. As the net 
energy of the gross energy conversion increases (flows 1 to 3 minus 
flows 4 to 6), the capacity to develop more complexity and diversity 
also increases. Ultimately the balance between all energy sources and 
all stressors will determine ecosystem complexity. 



A second assumption is that ecosystem complexity pays off by 
allowing higher efficiency in the use of energy resources and in the 
recycling of matter. This widely held working principle of ecology 
has been discussed many times (e.g., E. P. Odum, 1969; Margalef, 
1969; 1975) and still makes sense to me. 



STRESS AND ECOSYSTEMS 91 

The third assumption is the existence of some kind of priority 
development of structure in an ecosystem. Initially a minimal 
amount of structure necessary for survival develops. Later in 
successional time, if there is more net energy, complexity and 
diversity develop if the cost of development and maintenance do not 
exceed the gains that result from their feedback work. Ewel (1971b) 
provided evidence for the sequential development of biomass 
compartments in the succession of tropical ecosystems. He found 
that leaf biomass was the first compartment to reach steady-state 
values, then stems, and finally roots. The result of sequential 
development of compartments is a steady increase in the system's 
ability to use all the resources available in its surroundings. Another 
implication of this model is that ecosystems appear to reach 
functional and structural steady states early in succession, and later, 
with considerable lag, floristic complexity reaches its steady-state 
value. 

In discussing ecosystem stability, we must realize that complex 
systems can survive only in locations with high environmental energy 
subsidies and low intensities of stress. An environmental change that 
reduces total energy flow results in a rapid decrease in structural 
complexity, particularly if the system loses its main power source. A 
decrease in complexity is interpreted as ecosystem instability. 
Complex cities that lose monetary subsidies, coral reefs that lose 
solar input energies, or complex forests growing on leached soils that 
lose their nutrients rapidly, lose their complexity, as expected from 
the behavior of the model in Fig. 8. Systems with high organic 
productivity but low species diversity and complexity usually export 
their production to other systems and, in so doing, lose the capacity 
to diversify. This is certainly true for mangrove forests, marshes, 
freshwater wetlands, some lakes, rivers, and systems stressed with 
high organic-matter loads. All these systems either store organics 
without using their potential energy or constantly export organics 
and receive inorganic nutrients to subsidize their primary produc- 
tivity. The apparent stability of these systems is caused by the 
uninterrupted input of certain energy sources that represent a 
significant fraction of their total energy signature. Figure 6 shows 
evidence for this idea in relation to the role of tidal energy in 
maintaining stability in marshes. As long as tidal circulation 
continues, the marsh is capable of resisting other types of stress and 
recovers quickly after being subjected to a harvest or to other acute 
stressors. Stability is a function of stable energy input, and in most 
systems stability disappears when the main energy source is diverted 
(e.g., stress of type 1 in Fig. 5). 



92 LUGO 

We have discussed how each Ufe zone has a different background 
of stress which determines the potential for structural development 
in that locality. As more stressors are added to the background, the 
capacity to recover and to achieve maximum developmental poten- 
tial decreases. In lowland tropical life zones, high temperatures 
prevail and accelerate physiological processes. For aquatic ecosys- 
tems this has serious implications for their capacity to absorb 
additional stress. Johannes and Betzer (1975) elaborated this point 
with respect to tropical marine ecosystems. Small temperature 
increases are very damaging to these systems; e.g., 37°C is lethal to 
Thallasia beds (Schroeder, 1975) and mangrove seedhngs (Banus and 
Kolehmainen, 1976). These researchers also pointed out that in the 
tropics a higher ambient temperature and higher ambient salinity 
mean that a given concentration of pollutant causes a faster and 
greater decrease in dissolved oxygen concentration than in higher 
latitudes. At comparable dilution and dispersion rates, however, the 
pollutant concentration decreases more quickly with time and 
distance from the source. Thus the margin of error is smaller in 
tropical waters. The margin of error is equally small in ecosystems 
that are naturally stressed to a point near their limit of tolerance. 
Mangroves tolerate a more severe frost stress if they grow in 
low-salinity environments; they may not survive low temperatures at 
high soil salinities. In this case the lower salinity subsidizes high 
energy drains caused by frost (Lugo and Patterson Zucca, 1977). 



MEASUREMENT OF STRESS AND STRESSORS AND 
RESEARCH NEEDS 

The broad regional impact of man on the biosphere is probably 
why there is so much interest in studies of ecosystems and stress. 
Much of the research appears to ignore this broad issue, however, and 
instead focuses much effort on specific details that provide elegant 
results but do not really help society to solve the problem of 
coupling man to natural systems. We must document ecosystem 
responses to known intensities of stressors and test the ideas 
presented here. The researcher must take into consideration not only 
the intensity of the stress and the stressor but also their energy- 
quality characteristics relative to other energy sources impinging on 
the ecosystem. The points of attack in the system also require 
attention, and particular care should be given to the presence of 
feedback mechanisms and possible push— pull effects at the eco- 
system level. 



STRESS AND ECOSYSTEMS 93 

Table 5 summarizes some attempts at quantifying a number of 
stresses in natural systems and some important threshold values for 
specific stressors. Data of this kind, although important, are very 
meager. Biologists are good at counting dead or sick organisms, but 
little effort is made to calculate impacts per unit area or to correlate 
mortality with given intensities of stressors under natural conditions. 
Some calculations in Table 5 are based on the amount of energy 
actually drained from the system, but others also consider the energy 
the system loses when one of its components is not functioning. 
These unrealized energy flows are usually higher than the actual 
energy lost after the stressor's action. In few studies were measure- 
ments of stressor intensity and ecosystem response made (all in the 
same comparable units). Until researchers make these measurements, 
I cannot see how they will be in a position to develop a predictive 
capacity. For example, What is the maximum amount of energy that 
can be drained from an ecosystem without damaging its ability to 
recover? If we can learn to categorize stressors by the quality and 
intensity of their energy and by their point of attack in a given 
ecosystem and to categorize ecosystems by their energy signatures 
and their capacity to bounce back, then I believe we can begin to 
answer some of the questions about management and pollution that 
are being asked by those who manage natural ecosystems. 

ACKNOWLEDGMENTS 

I am grateful to the following colleagues for their contributions, 
through informal discussions, to the development of this manuscript: 
H. T. Odum, J. J. Ewel, S. L. Brown, C. S. Rogers, F. F. Benedict, 
C. A. S. Hall, S. C. Snedaker, and R. R. Twilley. None of them, 
however, agrees with most of this manuscript. Alma L. Lugo did 
most of the art work. 



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94 



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STRESS AND ECOSYSTEMS 101 

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ECOSYSTEM RESPONSES TO STRESS 
IN AQUATIC MICROCOSMS 



JOHN W. LEFFLER* 

Institute of Ecology, University of Georgia, Athens, Georgia 



ABSTRACT 

Ecosystem stress is defined as any change in exogenous inputs which produces 
an output significantly different from the system's normal response. Any 
discussion of stress requires a description of the state space in which the 
ecosystem normally functions. This normal operating range can be either static 
or dynamic, depending on the time scale of interest. Ecosystem stress responses 
can be discussed in terms of the system's relative stability. Hypotheses regarding 
such responses can be empirically evaluated by use of microcosm models. 
Experiments using aquatic microcosms to evaluate the stabilizing effects of 
species diversity and nutrient availability are described as examples of this 
technique. Contrary to previously proposed hypotheses, no relationships 
between diversity, nutrient availability, or system mass and ecosystem stability 
or between ecosystem resistance and resilience stabilities were demonstrated. 
Data from microcosm studies illustrate the importance of specifying the nature 
of the perturbation, the parameters used to characterize the system, and the 
prior history of the system in discussions of an ecosystem's response to stress. 



Although stress is a term wdth an obvious meaning, it is difficult to 
define precisely. Dictionaries provide definitions such as "the action 
on a body of any system of balanced forces whereby strain or 
deformation results" and "the internal resistance or reaction of an 
elastic body to the extenial forces applied to it" (Barnhart and Stein, 
1964). Medical textbooks consider stress to be any force that elicits 
increased levels of epinephrine, glucocorticoids, blood glucose, blood 
coagulation, arterial pressure, and cellular metabolism (Guyton, 
1971; Smith, Jones, and Hunt, 1972). In most definitions of stress, it 



♦Present address: Department of Biology, Ferrum College, Ferrum, Virginia. 

102 



ECOSYSTEM RESPONSES TO STRESS 



103 



is the response of the organism or system which is used as a criterion 
for identifying a specific force as a stress. Certain characteristic 
parameters must display abnormal behavior before a system can be 
considered stressed. At an organismal level, epinephrine, glucocorti- 
coids, and blood glucose are such parameters. To identify stress at an 
ecosystem level, we must monitor appropriate ecosystem-level 
parameters. Ecosystem stress studies should consider some character- 
ization of the total community metabohsm, the nutrient-cycling 
mechanisms, and the structural properties of the system. Deviations 
of such parameters from some normal condition can be used to 
identify exogenous inputs as stresses and to describe ecosystem 
responses to those stresses. 

THE CONCEPT OF ECOLOGICAL STRESS 

As used here, stress is defined as amy deviation in input variables 
which produces an output different from the system's normal 
response. Obviously this definition depends on the description of the 
normal, unstressed state. The region of state space within which an 
ecosystem normally functions is called its normal operating range. 
The dashed lines in Fig. 1 delineate such a region for the very simple 



Period of 
perturbation 




l-cH 



TIME 



Fig. 1 Diagram of five measures of relative stability. Dashed lines 
are boundaries of the normal operating range. Letters refer to 
quantitative stability measures: A, constancy; B, resistance; C, 
response time; D, resilience; and E, total relative stability. 



104 LEFFLER 

case of an ecosystem in a nonoscillating steady state. This range can 
be calculated as confidence bounds about the mean of all prepertur- 
bation observations, assuming the system is in steady state. The 
width of the region or the coefficient of variation of the observations 
can be regarded as a measure of the relative constancy of the 
ecosystem. 

Description of an ecosystem's normal operating range provides a 
standard for judging whether a particular input should be considered 
a stress. The criterion is whether the input causes the system's 
trajectory to vary significantly from its normal operating range. Since 
both the normal operating range and the system trajectory can be 
described statistically, desired confidence levels can be placed on 
such deviations. On the basis of this discussion and analysis, it is 
obvious that the same quahtative input may or may not be a stress. 
Temperature, for example, is an inevitable input to all ecosystems. A 
normal operating range can be defined under conditions of tempera- 
ture fluctuations that are typical for the system. Temperature can 
become a stress, however, if the quantitative level of this input 
assumes a value that causes system response to exceed the normal 
operating bounds. 

The description of the normal operating range is also extremely 
observer dependent. The width of such a region is a function of the 
characteristics used to describe the ecosystem and of the ability of 
the observer to discriminate differences in these parameters. For 
example, an algal culture can be classified on the basis of "greenness" 
or in terms of milligrams of chlorophyll per liter, depending on the 
observer. Of perhaps greater importance is the choice of a time scale 
for describing the normal operating range. Since the rate of change of 
dissolved oxygen in aquatic systems typically displays diel variation, 
an hourly description gives an oscillating normal operating range and 
permits a dynamic analysis. In this case, an input can become a stress 
on the system only at certain times in the daily cycle. Depending on 
the observer's objective, the same system can be described on a daily 
time scale. This gives a more static and much broader normal 
operating range at all time points. Such a concept is flexible enough 
to be applied to ecosystems undergoing oscillations, seasonal 
changes, developmental sequences, or even cychc succession. Simi- 
larly, the width of the normal operating range need not remain 
constant at all times. It is plausible, for example, to believe that early 
serai stages possess broader operating ranges than climax systems. 

It becomes evident that the concept of ecological stress cannot 
be discussed in a general sense. Both the change of system inputs aiid 
the properties of the system itself determine the ecosystem's stress 



ECOSYSTEM RESPONSES TO STRESS 105 

response. The stress of a specific ecosystem cannot be discussed 
without reference to the nature of the input changes, the system's 
past and present states, and the observer's characterization of the 
system, abihty to detect changes in the system, and his time scale. 
These considerations not only require that the concept of ecological 
stress be discussed in precise terms but also provide a practical 
approach to assessing stress in a specific ecosystem. 

An ecosystem's stress response can be described in several ways. 
A system's ability to resist the effects of exogenous input changes 
can be measured by the magnitude of its deflection from the normal 
operating range (Webster, Waide, and Patten, 1975) and by the time 
required for an initial displacement to occur (Hurd and Wolf, 1974). 
The first characteristic can be referred to as resistance and the second 
response time. The trajectory of the stressed system must be 
statistically defined so that significant deviations from the normal 
operating range can be assessed. After a system has been displaced 
from its normal operating range, it may or may not return to its 
original, statistically defined condition. If it fully recovers to its 
original normal operating range, the time required is a measure of its 
resihence to the stress (Webster, Waide, and Patten, 1975). (These 
concepts are depicted in Fig. 1.) 

Since resistance and resilience are not mutually exclusive 
properties, another measure is necessary to describe the divergence of 
the perturbed trajectory from that of the unstressed system. The 
integral difference between the normal operating range and the 
perturbed trajectory can be defined as total relative stability 
(Webster, 1975), which is illustrated by the shaded area in Fig. 1. 
This reflects the total impact of a stress on an ecosystem and is a 
function of both the specific system and the altered input. 
Ecosystems can be compared by dividing resistance and total relative 
stability measures by the mean of the observations used to define the 
normal operating range. The resilience measure can be made 
independent of resistance by dividing the recovery time by the 
relative resistance. This model provides a means of identifying 
stresses and of describing an ecosystem's stress response. 

Many hypotheses have been proposed to describe system 
characteristics that influence an ecosystem's stress response or 
stability. The best known of these has been the hypothesis that 
increased diversity leads to increased stability [see the review by 
Goodman (1975)]. Large abiotic nutrient reserves have also been 
proposed as a major influence on an ecosystem's response to stress. 
Pomeroy (1975) suggested that increased nutrient availability leads 
to increased resistance and resilience, but Webster, Waide, and Patten 



106 LEFFLER 

(1975) hypothesized that resistance would increase and resihence 
would decrease. They believed that resistance is a function of the 
mass of the system and resilience is related to functional dynamics, 
especially turnover rates. Thus resistance and resilience might be 
considered inverse concepts. Other investigators have discussed the 
effect of environmental constancy on ecosystem stability. Systems 
adapted to less variable environments often exhibit high levels of 
constancy stability but very poor resistance and resilience in the 
event of a major perturbation (Copeland, 1970; Jernelov and 
Rosenberg, 1976; Larsen, 1974). Estuaries, on the other hand, 
typically exhibit low constancy stability because of their highly 
variable environment but high levels of resistance and resilience 
(Boesch, 1974). 

THE MICROCOSM APPROACH TO ECOSYSTEM THEORY 

Ecologists have had difficulty in testing the validity of hypothe- 
ses that describe an ecosystem's response to stress. Most of these 
propositions were derived either by an intuitive synthesis of field 
observations or by mathematical simulation. Rigorous experimental 
evaluation is rare because of problems typical of all ecosystem-level 
studies, e.g., long time scales, lack of replication, difficulty of 
ecosystem parameter measurement, lack of control over extraneous 
environmental conditions and system histories, and economic feasi- 
bility. One means of testing the generality of a hypothesis is to use 
microcosms as living analogs of ecosystems. I have used several types 
of aquatic microecosystems to evaluate hypotheses regarding ecosys- 
tem stress responses. Microcosms can be designed to meet all 
requirements of standard ecosystem definitions (Odum, 1971) and to 
overcome the examples cited of experimental difficulties in field 
studies. By designing microcosm systems in which extraneous 
variables can be controlled, we can focus on the specific concept to 
be evciluated. No effort is made to duplicate any specific natural 
ecosystem; the microcosms are merely models of general ecosystem 
properties, such as energy flow through a trophic structure, nutrient 
cycling, and species diversity. In addition, the hypothetical factors 
influencing stability can be modeled by subjecting microcosms to 
different treatment levels of a factor, e.g., nutrient availabihty. 
Ecosystems developed under each treatment level can be subjected to 
identical stresses, and their respective responses can be compared. 

The goal of such experiments is not to extrapolate from 
microcosm results to all ecosystems but to determine whether a 
hypothesis derived by nonempirical methods is empirically falsifi- 



ECOSYSTEM RESPONSES TO STRESS 107 

able. This approach is subject to the appropriateness of the 
experimental treatments for simulating mechanisms postulated by 
the hypothesis. Negation of a hypothesis by microcosm experiments 
limits its generality and, at least, indicates that caution is advisable in 
extrapolating the hypothesis to all types of ecosystems. Several 
examples of this procedure will illustrate the microcosm approach. 

The Diversity-Stability Hypothesis 

The diversity— stability hypothesis states that increasing diversity 
within an ecosystem increases the system's stability. The first step in 
evaluating this proposal by microcosm experiments was to define 
operationally and to clarify the statement to be tested. Diversity was 
defined simply as the total number of species within each micro- 
cosm. Each of the five stability measures in Fig. 1 were evaluated. 
Thus the hypothesis predicted that microcosms with greater numbers 
of species should have greater constancy stability and that under 
stressed conditions they should have greater resistance, response 
time, resilience, and total relative stability. 

Four types of microcosms, each containing a different number of 
taxonomic groups, including algae, protozoans, metazoans, and 
bacteria, were established in 500-ml cotton-stoppered Erlenmeyer 
flasks. System A contained 10 species; system B, 17; system C, 21; 
and system D, 25. Each system was developed from stock cultures 
that were originally derived intact from natural sources but had been 
grown in flasks in the laboratory for a minimum of 6 months. Thus 
the organisms had coevolved histories and were adapted to the 
laboratory environment. Sterile techniques ensured against invasion 
by additiongJ taxa. 

Fifty -four replicates of each system were used in the study. All 
microcosms were maintained under identical environmental condi- 
tions. After inoculation the systems underwent a 12-week succession 
to allow each to attain a steady-state condition. The normal 
operating range and constancy stability were determined for each of 
the four systems by sacrificing unperturbed control microcosms 
during weeks 13 to 18. Other microcosms were stressed by raising 
their temperatures from 24 to 45°C during weeks 14 to 16. These 
systems were sacrificed at intervals from weeks 13 to 40 to monitor 
their response to the stress. Each microcosm was characterized by its 
net day production, night respiration, production-to-respiration 
(P/R) ratio, microscopic counts of dominant organisms, and nutrient 
agar plate counts of bacterial types. An element distribution index 
(EDI) was used to characterize the cycling of phosphorus and iron. 
This is an isotope technique that is sensitive to changes in the size of 



108 



LEFFLER 



TABLE 1 

STABILITY RANK ORDERING OF FOUR DIVERSITY 
LEVELS IN AN AQUATIC MICROCOSM EXPERIMENT* 







Measure 


of stability 












Total relative 


Parameter 


Constancy 


Resistance 


Resilience 


stability 


Net day production 


A-B-C-D 


A-D-C-B 


(C,D)-B-A 


D-C-B-A 


Night respiration 


A-D-C-B 


D-A-B-C 


(A,B,C,D) 


B-A-D-C 


P/R ratio 


A-D-B-C 


A-B-C-D 


(B,C)-D-A 


C-B-D-A 


Iron EDI 


A-C-D-B 


B-A-C-D 


(A,B,C,D) 


B-A-C-D 


Phosphorus EDI 


C-D-A-B 


D-A-(B,C) 


(B,C)-A-D 


B-D-C-A 


Species composition 










Microscopic counts 
Bacterial counts 


C-D-A-B 
A-C-B-D 


A-D-C-Bt 


B-(A,C)-Dt 


t 



*System A contained 10 species; system B, 17; system C, 21; and system D, 
25. The predicted ordering for all stability measures from least to most stable is 
A-B-C-D. Parentheses indicate ties in ranking. 

fMicroscopic and bacterial counts were combined. 

:|:Data were not determined. 



nutrient storage compartments and the rates of nutrient movement 
through them. Details of these experiments are described elsewhere 
(Leffler, 1977). 

Microcosm behavior was plotted for each of the four types of 
systems and was analyzed according to the criteria described in 
Fig. 1. Constancy, resistance, response time, resilience, and total 
relative stability of each parameter were calculated for each 
microcosm type to rank each of the four diversity levels from most 
stable to least stable. Results of this analysis are shown in Table 1. 
Observed rankings seldom correlated with predicted rankings. No 
significant relationship between taxonomic diversity and any of the 
five stability measures could be demonstrated. These results were 
interpreted to refute the generality of the diversity— stability 
hypothesis. This does not deny that under some circumstances 
diversity and stability may be related, but confident estimates of 
ecosystem stability based on counting taxonomic units do not appear 
justified by these results. 



The Relation Between Nutrient-Energy Subsidies and Ecosystem Stability 

Several researchers have proposed that large abiotic nutrient 
reserves, together with such energy subsidies as tidal action, may 



ECOSYSTEM RESPONSES TO STRESS 109 

affect ecosystem stability (e.g., Pomeroy, 1975; Webster, Waide, and 
Patten, 1975). They suggest that increased nutrient availabihty 
would increase the constancy and resistance of ecosystems. As 
mentioned previously, through intuitive syntheses, Pomeroy pre- 
dicted increased resilience, v^hereas Webster, Waide, and Patten 
postulated an inverse relationship between resistance and resilience 
on the basis of mathematical simulations. I have evaluated these 
hypotheses experimentally with aquatic microcosms (Leffler, manu- 
script in preparation). 

Four-liter, open, flow-through systems were used in the study. 
All microcosms initially contained identical chemical mediums, and 
each was inoculated from the same stocks. Cross-seeding improved 
replication. Three levels of nutrient subsidy and three levels of 
energy subsidy were used. Nutrients were added in the form of 
Taub's #36 microcosm medium (Taub and Dollar, 1964). Concentra- 
tions of the inflow solutions were set at one-tenth, normal, and ten 
times the normal strength of this medium. Turnover time for each 
system was 7 days. Energy subsidies were provided by Teflon stir 
bars and magnetic stirrers, which operated constantly, for 2 hr on 
alternating days, and not at all. Each combination of nutrients 
and energy was replicated four times, for a total of 36 microcosms. 
After inoculation, all systems experienced a 90-day succession and 
were then monitored at steady state for an additional 90 days. A 
thermal stress was induced by increasing the temperature from 22 to 
40° C for 48 hr and then returning it to normal. Stress response was 
monitored for 75 days. At the end of this period, new normal 
operating ranges were described for each system by further observa- 
tion for 70 days. Another thermal stress of the same magnitude but 
of 7-day s duration was induced. The microcosms' responses were 
followed for 50 days. 

A variety of parameters characterized ecosystem dynamics— net 
day production, night respiration, P/R ratio, chlorophyll a, particu- 
late matter, heterotrophic bacterial numbers, and inflow-to-outflow 
ratios of ammonia, nitrate, phosphorus, and magnesium. The 
responses of the microcosms to the thermal stresses were analyzed as 
described for the diversity experiment. Nonparametric tests were 
used to determine the significance of the ordering of nutrient 
treatments, energy treatments, and nutrient— energy combinations 
for the five measures of stability for each parameter. Few consistent 
generalizations could be drawn from this analysis. Effects of energy 
subsidies were seldom significant for any parameter or stability 
measure. Constancy stability was enhanced for all chemical inflow- 
to-outflow ratios by increasing nutrient subsidies and by increasing 
the level of nutrient— energy combinations. 



110 LEFFLER 

All parameters were combined, and rankings of each treatment 
level were assessed by Friedman nonparametric analyses of variance 
and by sign tests (P < 0.200) (Siegel, 1956). These results are shown 
in Table 2. Energy subsidies were not significantly related to any 
type of stability. Constancy stability and to a lesser extent resilience 



TABLE 2 

EFFECTS ON ECOSYSTEM STABILITY OF 

INCREASING NUTRIENT AND ENERGY SUBSIDIES 

IN AN AQUATIC MICROCOSM EXPERIMENT* 



Measure of stability 


Nutrient 


Energy 


Nutrient + energy 


Constancy 


H-M-L 
(P < 0.01) 


NS 


NS 


Resistance 


NS 


NS 


L-H 
(P = 0.105) 


Response time 


L-M-H 


NS 


L-H 




(P = 0.04) 




(P = 0.019) 


Resilience 


H-(M,L) 
(P = 0.19) 


NS 


NS 


Total relative stability 


NS 


NS 


NS 



*Based on summation of all measured parameters. Friedman 
analyses of variance and the sign test were used to detect significance 
at the P < 0.200 level. Abbreviations H, M, and L are high, medium, 
and low, respectively; NS is not significant. The predicted rankings 
from most to least stable are H-M-L or H-L. Parentheses indicate ties 
in ranking. 



stability increased with increasing nutrient subsidies, but response 
times decreased. Increased levels of nutrient— energy combinations 
led to decreases in resistance stability and response time. Table 3 
summarizes the behavior predicted by the hypotheses for large 
abiotic nutrient reserves and the empirically determined results of 
the microcosm experiments. The observed increase in constancy 
stability with increasing nutrients verified the predictions of both 
Pomeroy (1975) and Webster, Waide and Patten (1975). This 
suggests that nutrient availability may play an important role in 
ecosystem dynamics. It is obvious, however, that the mechanisms by 
which nutrient reserves and energy subsidies affect ecosystem 
stability are poorly understood, as evidenced by contradictions 
between observations and hypotheses for the four types of ecosys- 
tem stress response. 



ECOSYSTEM RESPONSES TO STRESS 



111 



TABLE 3 

SUMMARY OF PREDICTED AND OBSERVED EFFECTS OF 

LARGE ABIOTIC NUTRIENT RESERVES ON 

ECOSYSTEM STABILITY* 







Predicted 




Measure of stability 


Pomeroy (1975) 


Webster, Waide, 
and Patten (1975) 


Observed 


Constancy 

Resistance 

Response time 

Resilience 

Total relative stability 


Increase 
Increase 

t 
Increase 
Increase 




Increase 
Increase 
Increase 
Decrease 

t 


Increase 
No effect 
Decrease 
Increase 
No effect 



*Observations are based on the results of the nutrient — energy subsidy 
experiment described in Table 2 and in text. 
fNot discussed. 



OTHER INFLUENCES ON ECOSYSTEM STRESS RESPONSE 



Mass of the System 

Many other factors may influence an ecosystem's response to 
stress. Data derived from the previously described experiments has 
been used to evaluate some of these influences. GoUey (1974) and 
Webster, Waide, and Patten (1975) related resistance and resiUence 
of ecosystems to nutrient storages represented by standing-crop 
biomass within the system. They proposed that a large biomass 
v^^ould damp fluctuations induced by the external environment and, 
thus, confer greater resistance to stresses impinging on the system, 
Webster, Waide, and Patten also suggested that resilience has an 
inverse relationship to resistance. The biomass-derived inertia that 
increases a system's resistance to stress would also slow its recovery 
from a stress, thereby decreasing its resilience. 

On the basis of these hypotheses, I would predict that 
resistance and resilience rankings of treatments in the nutrient- 
energy experiments would be correlated with the amount of 
particulate matter in the microcosms of those treatments. The 
stability rankings for each of the nine treatments were correlated 
with the mean amount of particulate matter in the microcosms under 
steady-state conditions by use of Kendall's rank correlation coeffi- 



112 LEFFLER 

cient. The probability of a significant correlation (P< 0.100) was 
also calculated. The binomial test was used to detect trends across all 
parameters. The only significant correlation was a positive relation- 
ship between particulate matter and constancy stability during the 
first perturbation (P = 0.020). I must conclude that a generaliza- 
tion that attempts to explain an ecosystem's stress response as a 
function of its mass is not justified by these results. Neither 
resistance nor resilience showed any tendencies toward such a 
correlation. This contradicts the hypotheses of GoUey (1974) and 
Webster, Waide, and Patten (1975). Harwell, Cropper, and Ragsdale 
(1977) reported similar conclusions based on mathematical argu- 
ments. 



Relationships Among Types of Stability 

The relationships among the five different measures of stability 
were also investigated. Kendall's rank correlations were calculated 
for each measured parameter and each pairing of stability results 
based on the stability ordering of treatments for both the diversity 
and the nutrient— energy studies. Few significant correlations 
(P < 0.100) were discovered. Again, binomial tests across all parame- 
ters from both studies were used to detect significant (P< 0.100) 
trends. No such relationships were found. The most highly correlated 
(P = 0.132) pair of stabilities was resistance and total relative 
stability. This was not unexpected considering their definitions. No 
significant relationship between resistance and resilience was discern- 
ible based on all 22 parameters. This appai'ently contradicts the 
generality of the inverse relationship postulated by Webster, Waide, 
and Patten. 

It has been suggested that an ecosystem's ability to resist and to 
recover from a stress may be a function of habitat predictability 
(O'Neill, 1976). Such ecosystems as estuaries, which are subjected to 
highly variable environments, typically exhibit low constancy stabil- 
ity but high levels of resistance and resilience (Boesch, 1974; 
Copeland, 1970; Larsen, 1974). It may be worthwhile to consider 
whether a system's response to stress can be predicted by monitoring 
its variability under unstressed steady-state conditions. An inverse 
relationship between constancy stability and the perturbation 
response stabilities might be postulated. Correlation results, however, 
indicate that such a generalization is not justified, at least in terms of 
the two microcosm studies considered. Constancy stability fails to 
correlate with any of the measures that characterize an ecosystem's 
stress response. 



ECOSYSTEM RESPONSES TO STRESS 113 

EVALUATIOIM OF AIM ECOSYSTEM'S STRESS RESPONSE 

The examples discussed demonstrate how an empirical approach 
can be used to evaluate general theories of ecosystem stress response. 
Microcosms can be used to model ecological processes common to all 
ecosystems. They provide the advantage of controlling many 
extraneous variables that complicate attempts at rigorous field 
experiments. Studies of an ecosystem's response to stress must also 
be of sufficient duration for dynamics to be observed. This factor, as 
well as ease of replication, make microcosms a practical and 
economically feasible approach for studying the theory of stress 
ecology. A researcher must be aware, however, of the many factors 
that influence interpretation of a system's response to stress. 
Foremost is the validity of the microcosm as an accurate analog of 
the natural systems of primary concern. In addition, such factors as 
the type of perturbation, the parameters used to characterize the 
system, and the historical development of the system must be 
considered in discussing the stress response of any ecosystem. 



Nature of the Stress 

Although theoreticians tend to generalize about ecosystem 
dynamics, it is not surprising that the specific type of stress to which 
a system is subjected will greatly influence its response. Figure 2 
shows the differing responses of replicate microcosms of the 
21-species system from the diversity experiment after being sub- 
jected to several types of perturbations. Each trajectory represents 
two microcosms receiving the same perturbation. The ordinate scale 
is a subjective evaluation of microcosm health based on a grading 
system from 1 to 4, with plus (+) or minus (— ) indicating variation 
within a category; the categories are 1, yellow and brown colors 
dominant, much debris, metazoans dead; 2, green color dominant 
but yellow and brown colors common, debris present; 3, normal, no 
different from controls; and 4, dark green color, suggesting high 
productivity, structure similar to controls. Stresses on the various 
microcosms included increasing the pH to 8.8 by adding sodium 
hydroxide (curve A in the figure); introducing 10 amphipods 
{Gammarus sp.) into microcosms (curve B); increasing the tempera- 
ture from 22 to 35°C for 2 weeks and then returning it to normal 
(curve C); and increasing the temperature to 40°C for 1 week and 
then returning it to normal (curve D). Although the qualitative 
nature of the stress is obviously important, curves C and D illustrate 
the effect of different intensities of the same perturbation. The 



114 



LEFFLER 



+ 


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4 


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- 


- 






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+ 


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- 


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1 1 2 3456789 10 11 12 



PERTURBATION RECOVERY 
PERIOD PERIOD 



WEEKS 



Fig. 2 Effects of different perturbations on replicate microcosms as 
described by a subjective evaluation of microcosm health. The 
stresses illustrated are A, pH of system increased by addition of 
sodium hydroxide; B, 10 amphipods introduced to each system; C, 
temperature increased from 22 to 35 C for 2 weeks; and D, 
temperature increased from 22 to 40 C for 1 week. (See text for 
discussion of the evaluation.) 



duration, the frequency of occurrence, and the synergistic effects of 
different stresses also must be considered. 



Parameters Characterizing the Ecosystem 

Understanding ecosystem behavior depends on the parameters 
used to characterize the system, but this is seldom pointed out in 
discussions of ecosystem dynamics. This was obvious in the diversity 
study illustrated by Table 1, where stability rankings of the four 
treatments varied greatly depending on which parameter was 
considered. The relative sensitivity of each parameter is also worth 
noting, especially if microcosm experiments continue to be used for 
studies of ecosystem dynamics. To evaluate parameter sensitivity, I 
examined data from the nutrient— energy subsidy studies. For each 
parameter and each of the nine treatments, coefficients of variation 
of the steady-state observations were used to rank the treatments in 
terms of constancy stability. The median coefficient of variation 
from the first and second perturbations combined was calculated for 



ECOSYSTEM RESPONSES TO STRESS 



115 



every parameter. A comparison of these numbers led to the rankings 
in Table 4. The P/R ratio, night respiration, and magnesium 
input-to-output ratio were the least variable parameters during steady 
state. Ammonia, nitrate, and chlorophyll a fluctuated most. These 
reinkings, of course, are partially a function of the specific methods 



TABLE 4 

RANKING OF PARAMETER SENSITIVITIES FOR 

STEADY-STATE VARIABILITY, RESISTANCE TO STRESS, 

AND RECOVERY FROM STRESS* 







Steady -state 


Resistance 


Resilience 




Number of 


variability 


(least to 


(least to 


Parameter 


cases 


(least to most) 


most) 


most) 


Net day production 


18 


4 


4 


5 


Night respiration 


18 


2 


5 


3 


P/R ratio 


18 


1 


2 


6 


Chlorophyll a 


18 


7 


8 


2 


Particulate matter 


18 


6 


9 


4 


Ammonia input-to- 










output ratio 


18 


9 


7 


1 


Nitrate input-to- 










output ratio 


9 


8 


1 


9 


Phosphorus input-to- 










output ratio 


9 


5 


3 


8 


Magnesium input-to- 










output ratio 


9 


3 


6 


7 



*The ranking is based on all treatments from both perturbations in the 
nutrient— energy subsidy experiment. The median coefficient of variation of 
steady-state observations, the median relative resistance, and the median 
resilience for these treatments were compared for each parameter to arrive at 
a ranking. 



used in this study. The median relative resistance and median relative 
resilience, similarly calculated for each parameter, were compared. 
The nitrate, P/R ratio, and phosphorus parameters were most 
sensitive to stress (i.e., least resistant), and particulate matter, 
chlorophyll a, and ammonia were least sensitive. Ammonia, chloro- 
phyll a, and night respiration recovered most slowly, but nitrate, 
phosphorus, and magnesium returned rapidly to their normal 
operating ranges. Differences in response of various parameters 
should be considered during the design of a microcosm experiment. 



116 



LEFFLER 



System History 

A third consideration in the assessment of an ecosystem's stress 
response is the effect of history. We might expect that prior exposure 
to stress would alter a system's future response to similar distur- 
bances. Data from the nutrient— energy subsidy experiment were 
examined for such evidence. Coefficients of variation of the 
steady-state observations were compared by treatment for each of 
the two perturbations to evaluate the increase or decrease in 
steady -state variability before and after the first perturbation of each 
of the nine treatments. The binomial test was used to detect whether 
a significant (P < 0.100) change in constancy stability had occurred. 
As shown in Table 5, only the P/R ratio was changed significantly; 
the perturbation caused a decrease in steady -state constancy. Similar 
procedures allowed comparisons of resistance, resilience, and total 
relative stability after the first and second stress periods. The 
occurrence of a prior disturbance caused night respiration to be less 
resistant to a second perturbation, but the P/R ratio became more 
resistant. Resilience and total relative stability were also affected for 



TABLE 5 



EFFECTS OF PRIOR PERTURBATION ON AN 

ECOSYSTEM'S RESPONSE TO STRESS IN THE 

MICROCOSM NUTRIENT-ENERGY 

SUBSIDY EXPERIMENT* 











Total 










relative 


Parameter 


Constancy 


Resistance 


Resilience 


stability 


Net day production 


NS 


NS 


NS 


— 


Night respiration 


NS 


— 


+ 


— 


P/R ratio 


— 


+ 


— 


— 


Chlorophyll a 


NS 


NS 


NS 


NS 


Particulate matter 


NS 


NS 


NS 


NS 


Ammonia input-to- 










output ratio 


NS 


NS 


+ 


NS 



*The coefficient of variation of steady-state observations, the 
relative resistance, the relative resilience, and the total relative stability 
of each of the nine treatments were compared for the first and second 
perturbations. Significant trends for all treatments were detected with 
the binomial test at the P=^ 0.100 level. Plus ( + ) indicates that the 
stability of the microcosms was greater for the second stress than for 
the first; minus ( — ) indicates that the stability was less for the second 
stress than for the first; and NS is no significant change. 



ECOSYSTEM RESPONSES TO STRESS 117 

certain parameters. It is perhaps worth noting that the total relative 
stability of all three metabolic parameters was less for the second 
stress than for the first. 

For each of the nine treatments, median coefficients of variation 
among replicate microcosms were also compared before and after 
perturbations. The binomial test again indicated significant 
(P< 0.100) trends. The thermal stress increased replicate variation 
for net day production but reduced variation for the chlorophyll a, 
phosphorus, and magnesium parameters. Although no general trends 
are obvious from these studies, we must certainly consider the 
influence of prior events (i.e., history) when assessing an ecosystem's 
stress response. 

SUMMARY 

Most of the current theory that seeks to describe and predict the 
response of ecosystems to stress conditions has been developed by 
mathematical or intuitive reasoning. I attempted to clarify the stress 
concept and advocated an empirical approach complementing these 
methodologies. This approach requires that strict operational defini- 
tions be developed to clarify theoretical concepts. Relations between 
concepts must be expressed as falsifiable hypotheses. Five measures 
of relative stability can be used to quantify a system's response to 
stress. Microcosms are proposed as living models of large natural 
ecosystems. Since in any type of model (mathematical, verbal, or 
physical) some behavior is specific to the model, results must be 
extrapolated cautiously. Microcosms are potentially valuable tools, 
however, both conceptually and pragmatically, for developing and 
testing theories of ecosystem dynamics. 

The two microcosm experiments briefly described to illustrate 
how such models can be used failed to support several hypotheses 
that were derived by mathematical or intuitive approaches. The 
relative stability of these experimental systems was not related 
simply to their species diversity, nutrient— energy subsidies, or mass. 
Constancy stability, however, was directly related to nutrient 
availability. No relationship could be demonstrated between resis- 
tance and resilience of stressed microcosms or between their 
steady-state variability and any measure of their perturbed behavior. 
These empirically derived results suggest that some hypotheses that 
seek to describe an ecosystem's stress response are not correct as 
generalities and require further clarification. 

Several factors influence an ecosystem's response to stress. 
Among these are the type of perturbation, the parameters used to 



118 LEFFLER 

characterize the ecosystem, and the history of the system. Each 
factor must be rigorously specified before predictions about an 
ecosystem's stress response can be made. This recognition greatly 
limits our ability to generalize about the perturbed behavior of 
ecological systems. Data from microcosm studies were used to 
illustrate the possible effects of these three factors. Empirical 
evaluation of hypotheses concerning an ecosystem's response to 
stress is sorely needed. The rigorous design and specificity of 
analysis required limit generalization of results but may enhance 
understanding of ecosystem dynamics when used in conjunction with 
mathematical and intuitive methods. 

ACKNOWLEDGMENTS 

I thank G. T. Auble, M. C. Chase, F. B. Golley, J. V. Nabholz, 
and C. L. Thomas for their critical comments on earlier drafts of this 
paper. Microcosm research was supported by grant BMS-75-19765 
from the National Science Foundation. 

REFERENCES 

Barnhart, C. L., and J. Stein (Eds.), 1964, The American College Dictionary, 

p. 1197, Random House, Inc., New York. 
Boesch, D. F., 1974, Diversity, Stability and Response to Human Disturbance in 

Estuarine Ecosystems, in Proceedings of the First International Congress on 

Ecology, The Hague, Sept. 8—14, 1974, pp. 109-114, Centre for Agricultural 

Publishing and Documentation, Wageningen, The Netherlands. 
Copeland, B. J., 1970, Estuarine Classification and Responses to Disturbances, 

Truns. Am. Fish. Soc, 99: 826-835. 
Golley, F. B., 1974, Structural and Functional Properties as They Influence 

Ecosystem Stability, in Proceedings of the First International Congress on 

Ecology, The Hague, Sept. 8—14, 1974, pp. 97-102, Centre for Agricultural 

Publishing and Documentation, Wageningen, The Netherlands. 
Goodman, D., 1975, The Theory of Diversity— Stability Relationships in 

Ecology, Q. Rev. Biol., 50: 237-266. 
Guyton, A. C, 1971, Textbook of Medical Physiology, 4th ed., pp. 700-701, 

W. B. Saunders Co., Philadelphia. 
Harwell, M. A., W. P. Cropper, Jr., and H. L. Ragsdale, 1977, Nutrient Recycling 

and Stability: A Reevaluation, Ecology, 58: 660-666. 
Hurd, L. E., and L. L. Wolf, 1974, Stability in Relation to Nutrient Enrichment 

in Arthropod Consumers of Old-Field Successional Ecosystems, Ecol. 

Monogr., 44: 465-482. 
Jernelov, A., and R. Rosenberg, 1976, Stress Tolerance of Ecosystems, Environ. 

Conserv., 3: 43-46. 
Larsen, P. F., 1974, Structural and Functional Responses of an Oyster Reef 

Community to a Natural and Severe Reduction in Salinity, in Proceedings of 

the First International Congress on Ecology, The Hague, Sept. 8—14, 1974, 



ECOSYSTEM RESPONSES TO STRESS 119 

pp. 80-85, Centre for Agricultural Publishing and Documentation, Wagenin- 
gen. The Netherlands. 

Leffler, J. W. , 1977, A Microcosm Approach to an Evaluation of the 
Diversity— Stability Hypothesis, Ph.D. Thesis, University of Georgia, Athens. 

Odum, E. P., 1971, Fundamentals of Ecology, 3rd ed., p. 8, W. B. Saunders Co., 
Philadelphia. 

O'Neill, R. v., 1976, Ecosystem Persistence and Heterotrophic Regulation, 
Ecology, 57: 1244-1253. 

Pomeroy, L. R., 1975, Mineral Cycling in Marine Ecosystems, in Mineral Cycling 
in Southeastern Ecosystems, ERDA Symposium Series, Augusta, Ga., 
May 1-3, 1974, F. G. Howell, J. B. Gentry, and M. H. Smith (Eds.), 
pp. 209-223, CONF-740513, NTIS. 

Siegel, S., 1956, Nonparametric Statistics for the Behavioral Sciences, McGraw- 
Hill Book Company, New York. 

Smith, H. A., T. C. Jones, and R. D. Hunt, 1972, Veterinary Pathology, 4th ed., 
pp. 186-187, Lea & Febiger, Philadelphia. 

Taub, F. B., and A. M. Dollar, 1964, A Chlorella—Daphnia Food Chain Study: 
The Design of a Compatible Chemically Defined Culture Medium, Limnol. 
Oceanogr., 9: 61-74. 

Webster, J. R., 1975, Analysis of Potassium and Calcium Dynamics in Stream 
Ecosystems on Three Southern Appalachian Watersheds of Contrasting 
Vegetation, Ph.D. Thesis, University of Georgia, Athens. 

, J. B. Waide, and B. C. Patten, 1975, Nutrient Recycling and the Stability of 

Ecosystems, in Mineral Cycling in Southeastern Ecosystems, ERDA Sym- 
posium Series, Augusta, Ga., May 1—3, 1974, F. G. Howell, J. B. Gentry, 
and M. H. Smith (Eds.), pp. 1-27, CONF-740513, NTIS. 



PHYSICOCHEMICAL AND BIOLOGICAL 
STRESSORS AS DISTRIBUTIONAL 
DETERMINANTS OF CARIBBEAN 
AND TROPICAL EASTERN PACIFIC 
SWIMMING CRABS 



ELLIOTT A. NORSE 

Department of Zoology, University of Iowa, Iowa City, Iowa 



ABSTRACT 



Zones where influences of terrestrial— limnetic and marine ecosystems overlap 
provide natural physicochemical stress gradients for groups that evolved at either 
end. Portunid crabs, originally a marine gi'oup, now occur from equable offshore 
marine biotopes to stressful rivers and streams. Field studies on population and 
community structure in coastal areas of the eastern Pacific (Colombia, Panama, 
and Mexico) and the Caribbean (Jamaica, Florida, Curagao, and Colombia) and 
experiments on physiological tolerances and biological interactions of Caribbean 
portunids showed that Euphylax robustus in the Pacific and Portunus, Arenaeus, 
and Cronius spp. in both oceans occur predominantly farther offshore, deeper, 
or in higher salinities than CalUnectes spp., which are more euryhaline than 
members of the other genera. Among CalUnectes, high-temperature and 
desiccation tolerances are much less important than hyposalinity tolerances in 
permitting species to penetrate estuaries and shallow areas, and likelihood of 
severe dilution directly or indirectly limits distributions as stress increases. 
Seaward distributional limits result from increased interference and exploitation 
competition, predation, parasitism, decreasing food quantity and quality, and 
the interactions of these factors. Thus biological stress increases as physico- 
chemical stress decreases. Distributions of populations along gradients are 
envisioned as responses to risk of mortality from physicochemical and biological 
stressors, with abundance peaks corresponding to zones of minimum combined 
risk. 



When a species belonging to a group that evolved in marine 
environments leaves the sea for land or freshwater, it has an 
opportunity to exploit new resources and leave behind old problems. 

120 



PHYSICOCHEMICAL AND BIOLOGICAL STRESSORS 121 

There is an admission price, however; the species must have 
morphological, physiological, behavioral, or life-historic adaptations 
to abiotic and biological conditions that are increasingly alien and 
stressful with increasing departure from the sea. If the group were in 
some way preadapted for ecological expansiveness (weedy), repeated 
invasions of the gradient extending from marine dominated to 
terrestrially dominated aquatic climates would lead either to 
one species' eliminating the others or to partitioning of the gradient. 
This paper considers one group, bottom-dwelling swimming crabs of 
the family Portunidae, which has repeatedly invaded this gradient. 
Observations are given on species distributions, factors limiting 
portunid incursions into estuaries, and factors resulting in coexis- 
tence rather than in monopolization by a single species. Some of the 
principles illustrated should be valid for other groups inhabiting 
natural physicochemical gradients as well. 

The tropical American coasts have a small share of the world's 
~300 portunid species (Norse, 1977), but they do have most of the 
species (members of the genus Callinectes) which are known or 
believed to invade estuaries. The taxonomy of American portunids, 
although less fluid than that of portunids from the Indo-West Pacific, 
has been complicated by variations in areal distributions, abundance, 
temporal fluctuations, and intensities of collecting. Many species are 
sexually dimorphic and dichromatic, have allometric growth and vary 
geographically, and, therefore, require considerable experience to 
identify with confidence. In fact, newly described Portunus 
(Holthuis, 1959; 1969) and Callinectes spp. (Williams, 1966; 
Taissoun, 1972) have been added to the tropical west Atlantic fauna 
in recent years. Unfortunately, C. sUjiilis Williams is still misidenti- 
fied as C. ornatus Ordway or C. danae Smith by some scientists, and 
I failed to realize fully that C maracaiboensis Taissoun, ostensibly a 
Lake Maracaibo area endemic, was common in my main study area 
(Norse, 1975; 1977). This taxonomic uncertainty has confused our 
already limited view of the group's ecology, but identification of 
eastern Pacific portunids and the world's Callinectes has been 
greatly facilitated by the monographs of Garth and Stephenson 
(1966) and Williams (1974). 

After studying the taxonomy of Callinectes, I visited Florida, 
Jamaica, Curacao, both the Caribbean and Pacific coasts of Colom- 
bia, and the Pacific coasts of Mexico and Panama (Fig. 1) to delimit 
the ecological distributions of demersal portunids and the roles of 
environmental factors contributing to them. This paper synthesizes 
some of the results I have discussed in greater detail elsewhere 
(Norse, 1975; 1977; in preparation; Norse and Estevez, 1977). 



122 



NORSE 



v 


Q 








^^^^:^::W. 


1000 km 



Fig. 1 The study areas in the east Pacific: (1) Northern Gulf of 
California, Mexico; (2) Panama; and (3) Colombia; and the west 
Atlantic: (4) Miami area and Florida keys; (5) Jamaica; (6)CuraQao; 
and (7) Colombia. 



METHODS 



Distributions 

On Colombia's Pacific coast, I worked with Mario Estevez, a 
biologist then a member of the Colombian Marine Fisheries 
Development Project, using the Colombian government's shrimp 
trawler Inderena to sample in the lower reaches of four large rivers, 
Guafui, Timbiqui, Saija, and Naya, and on the adjacent continental 
shelf. We planned four transects, each having seven trawls from as far 
upriver as nets could be operated to the 20-fathom (37-m) contour 
on the shelf (upriver, midriver, river mouth, and at 9, 18, 27, and 
37 m), but two of the transects were only partially completed. To 
assure sufficient depth for shrimp-trawl operation and to minimize 
the effects of running tides on crab movements, we made all 
estuarine trawls within 1 hr of high slack tide. We did shelf trawls 
during daylight hours irrespective of tides. We trawled without 
tickler chains at equal speeds for equal periods to cover equal areas 
of bottom. At the midpoint of most trawls, we took surface 
temperatures and water samples, but the water samples were lost 



PHYSICOCHEMICAL AND BIOLOGICAL STRESSORS 123 

before salinities were determined. Supplemental eastern Pacific 
collections were made by a shrimp trawler in Mexico and by hand 
netting and trapping in Colombia, Mexico, and Panama. 

Jamaica was the main Caribbean study area. I sampled lower 
reaches of rapidly flowing through nearly stagnant lotic waters, a 
coastal salt pond, periodically exposed mangrove mud flats, sea grass 
and algal beds, and featureless bottoms in both estuarine and 
nonestuarine bays and lagoons, and among coral reefs, by wading, 
snorkeling, and scuba diving. I used a gill net and traps at one site but 
trapped and/or hand netted at all others. By standardizing the 
trapping procedure (using the same trap designs, trapline pattern, 
bait, and period throughout), I was able to compare crab densities (in 
number per trap-hr) among sites. Temperatures and water samples 
were taken from bottom waters in the middle of each site. Most 
salinities were measured with a refracto meter, but a few were 
measured by titration. I made supplemental collections in Jamaica, in 
the Miami area and the middle Florida keys, on the Colombian coast 
between the Cienaga Grande de Santa Marta and Bahia Concha, and 
in Curacao. 

At all sites the physical conditions and presence of other species 
were noted, and, in quantitative Jamaican and Pacific Colombian 
sites, crabs were sexed, and their carapace lengths were measured 
immediately after capture. 

Physiological Tolerances 

The hyposalinity tolerances of the common portunids of 
Jamaica and the Florida keys were tested by acclimating them for at 
least 30 hr in running seawater (X = 34.5%o in Jamaica and 36.25%o 
in the keys), then placing them into 10, 25, 37.5, or 50% seawater, 
and noting survival after 24 hr. 

High-temperature tolerances of Jamaican Callinectes were tested 
by acclimating them for at least 21 days in the Discovery Bay Marine 
Laboratory's running seawater system (X = 28.9° C), placing them in 
39.0° C aerated seawater for 60 min, replacing them in acclimation- 
temperature running seawater for 24 hr, and examining for survival. 

Desiccation tolerances were tested by acclimating Jamaican 
Callinectes for at least 30 hr in running seawater, weighing one of 
each species and replacing it in seawater to recover water lost during 
weighing, then placing each crab in an individual compartment in a 
wire-mesh cage in a breezy but shaded corridor between buildings, 
and noting time until death and lethal weight losses for each species. 



124 NORSE 

Interspecific Agonism 

Male Jamaican Callinectes of varied known sizes were placed in a 
fenced-off "arena" in a concrete seawater table, and each crab's 
retreats from approach, display by, or contact with each individual 
of the other species were tallied. When agonism in the arena 
diminished, increasing concentrations of conch, fish, and crab 
extracts were added to increase agonistic activity. Only repeatedly 
decisive results were considered a victory for one of the combatants. 



AREA DESCRIPTIONS 

The Pacific Colombian coastal state of Cauca has an extensive 
depositional shoreline. Rainfall is very heavy, particularly on the 
western range of the Andes, which peak about 80 km inland. Many 
mangrove-lined rivers pour enormous amounts of freshwater into the 
turbid sea overlying the gently sloping continental shelf. The Pacific 
coast of Panama (the coastal areas of the Canal Zone and Taboga 
Island) has considerable rain but is much less affected by upland 
rainfall and has less freshwater mixing with the turbid shelf waters 
than the Colombian coast. The northern Gulf of California, in the 
San Felipe, Baja California Norte, and Puerto Pehasco, Sonora, areas 
of Mexico, has clearer, shghtly hypersaline waters over the gently 
sloping shelf, but there is very little freshwater input in this desert 
area. 

In contrast, inshore areas in Jamaica have varied aquatic climates. 
The island is mountainous and fairly wet, but, where permanent and 
temporary streams are few, coastal waters are oceanic in character, 
particularly on the steeply sloping, coral-reef-fringed north coast. 
The Caribbean Colombian coast has adjacent areas of markedly 
different aerial and aquatic climate. The area of Cienaga Grande de 
Santa Marta, a large estuarine lake, is a fairly wet, depositional coast. 
To the east, near the city of Santa Marta, the edges of a very tall, 
isolated mountain massif slope steeply into the sea. Since the aerial 
climate is semiarid, coastal waters are largely oceanic. Curagao is a 
geologically complex semiarid island; oceanic waters abut both 
coasts, which are indented by protected, turbid bays that lack 
permanent freshwater input. In the fairly wet Miami area, the Oleta 
River, which has intermittent flow, empties into Biscayne Bay, a 
large, culturally stressed shallow bay. Shore areas may be estuarine, 
but the central and eastern parts usually have little seawater dilution. 
The keys are emergent points on the eastern edge of the Florida 
plateau. Although they receive moderate rainfall, their small size, 



PHYSICOCHEMICAL AND BIOLOGICAL STRESSORS 125 

lack of topographic relief, and geologic composition (permeable 
limestones) prevent continuing existence of hyposaline biotopes (for 
more detailed descriptions, see Norse, 1975, and Norse and Estevez, 
1977). 

RESULTS AND DISCUSSION 

Since 1969, 1 have examined and measured the Callinectes 
collections in the Allan Hancock Foundation of the University of 
Southern California, the Harvard Museum of Comparative Zoology, 
and the American Museum of Natural History and have collected 
and/or observed in the field about 8000 portunids belonging to 26 
tropical American species (Table 1). Tv^o species are not primarily 
demersal; Euphylax dovii Stimpson is an epipelagic species that 
enters inshore v^aters to spaw^n (Norse and Fox-Norse, 1977), and 
Portunus sayi (Gibbes) lives in floating Sargassum patches that 
occasionally drift ashore (Williams, 1965). Several species w^ere too 
rarely found or locally distributed to permit any but tentative 
conclusions about their distributions. Some species are commonly 
associated w^ith particular plant communities or substrate types, but, 
except to note that most occur mainly on soft bottoms, 1 will 
concentrate on distributions w^ith regard to cUmatic and biological 
stressors. 

From upriver to continental-shelf Pacific Colombian waters, 
surface temperatures increased steadily from 26.3 to 28.4°C. This 
small change would not be likely to cause great changes in species 
compositions of demersal crabs, but rather indicates the change in 
the ratio of cooler freshwater to warmer seawater. The surface 
conditions, which directly affect benthos only in the shallows, reflect 
deeper bottom conditions, depending on the hydrographic character- 
istics of the estuaries (Gibbs, 1970). The most obvious major climatic 
difference between river water and shelf water is salinity. 

Distributions of portunids and other groups reflect this salinity 
gradient. Portunids comprised nearly 99% of the total of benthic 
brachyuran crabs. Table 2 gives the species compositions (mean 
relative abundances) of demersal portunids along the transects. 
Callinectes toxotes Ordway dominates the freshest sites but is 
replaced by C. arcuatus Ordway, which is then replaced by Euphylax 
robustus A. Milne Edwards and Portunus asper (A. Milne Edwards) in 
increasingly equable biotopes. 1 found a few C. arcuatus inshore in 
Panama, but, in the northern Gulf of California, there is a clear 
ecological separation between Callinectes spp. Tidal channels drain- 
ing salt marshes and shallow areas of both bays and the open gulf are 





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PHYSICOCHEMICAL AND BIOLOGICAL STRESSORS 



127 



TABLE 2 

SPECIES COMPOSITION (%) OF DEMERSAL PORTUNIDS 
ALONG PACIFIC COLOMBIAN TRANSECTS 



Species 



River 



Continental shelf 



Upriver Midriver mouth 9m 18m 27 m 37 m 



Callinectes 








toxo tes 


94.6 


43.5 


34.0 


Callinectes 








arcuatus 


5.4 


56.5 


64.3 


Euphylax 








robustus 








Portunus 








asper 








Arenaeus 








mexicanus 








Cronius 








ruber 






1.7 



0.9 



;5.7 43.2 31.5 



6.1 49.9 61.3 87.4 



7.6 



0.6 



5.3 



0.7 



7.2 12.6 



strongly dominated (>95%) by C. bellicosus (Stimpson), which was 
completely absent from offshore trawl hauls in which I found great 
numbers of C. arcuatus, some Portunus xantusii minimus Rathbun, 
an E. robustus, and a handful of nonportunid brachyurans. Brusca 
(1973) noted that E. robustus can be abundant in shrimp trawl hauls 
in the northern gulf, presumably in deeper waters than I sampled. 
Thus the Colombian and northern gulf gradients, although 
~5000 km apart, show striking similarities. The most terrestrially 
influenced biotopes are dominated by different species (C toxotes 
vs. C. bellicosus), but these are replaced to seaward by C. arcuatus, a 
Portunus sp. {P. asper vs. P. xantusii minimus), and E. robustus. 

Although the Caribbean has more portunid species than the east 
Pacific, salinity distributions (aside from the absence of extant 
Caribbean Euphylax) in tropical and warm temperate areas are 
similar at the generic level. Callinectes monopolize terrestrially 
dominated waters, and Arenaeus, Portunus, Cronius, and fully 
aquatic brachyurans in many other famihes make, at most, limited 
incursions into hyposaline waters (Table 3). Among Jamaican 
Callinectes, C. maracaiboensis, C. bocourti A. Milne Edwards, and C 
sapidus Rathbun dominate the freshest sites. Ail seven common 
species occur in the brackish range, C. exasperatus (Gerstaecker) 
being the most abundant. In waters usually diluted slightly below 
seawater values, C. marginatus (A. Milne Edwards), C. danae, and C. 



128 



NORSE 



exasperatus dominate. Callinectes ornatus, C. marginatus, and C. 
exasperatus dominate biotopes having virtually undiluted seaw^ater. 
Similar patterns exist in regions having long-lasting hyposaline 
environments (e.g., Miami; Cienaga Grande de Santa Marta, 
Colombia). In areas lacking permanent hyposaline vi^aters (e.g., the 
keys; areas near Santa Marta, Colombia; and Curagao), however, the 
portunid species composition changes with the degree of exchange 
with the sea. Thus the back bays most tenuously connected with the 
sea have only the Callinectes that occur below 10%o in wetter 
regions. 



TABLE 3 

SPECIES COMPOSITION OF JAMAICAN PORTUNIDS 
IN FOUR SALINITY CATEGORIES 







Brackish 


Near marine 


Marine 




Freshwater 


water (10.1— 


(30.1- 


(33.1- 


Species 


(0-10.0%o) 


30.0%o ) 


33.0%o) 


35.5%o) 


Callinectes 










maracaiboensis 


41.0 


10.0 


3.8 


0.4 


Callinectes 










bocourti 


34.5 


10.4 


0.4 


0.7 


Callinectes 










sapid us 


22.5 


15.2 


4.5 


1.4 


Callinectes 










exasperatus 


2.0 


29.6 


22.8 


25.2 


Callinectes 










danae 




16.0 


22.4 


1.8 


Callinectes 










marginatus 




16.6 


30.8 


26.4 


Callinectes 










ornatus 




2.4 


13.9 


32.6 


Callinectes 










similis 








0.2 


Arenaeus 










cribrarius 






1.5 


0.3 


Portunus 










sebae 








8.9 


Portunus 










anceps 








1.5 


Portunus 










depressifrons 








0.3 


Cronius 










tumidulus 








0.3 



PHYSICOCHEMICAL AND BIOLOGICAL STRESSORS 129 

Upstress Distributional Determinants 

The simplest explanation for these patterns is that species 
distributions respond to the likelihood of severe dilution. Some crabs 
must either avoid or be killed in climates having constant (always 
fresh or brackish) or occasional (e.g., back bays, where heavy rains 
cause normally marine salinities to plummet) severe dilution. Such 
patterns imply marked differences among species' tolerances of 
dilution, differences my tests confirmed. Combined results from 
Jamaica and the Florida keys give the following order of eury- 
halinity: C. maracaiboensis = C. bocourti = C sapidus > C 
exasperatus > C. danae > C. marginatus > C. ornatus > P. depressi- 
frons^P. spinimanus ^ A. cribrarius ^ P. sebae. Using data from 
experiments in which Callinectes spp. were transferred to 10% 
seawater, I found that the (arcsin transformed) proportions surviving 
are very strongly correlated with the species lowest salinity records 
(r = —0.989, v^th 5 df ; P < 0.001). In contrast, their high-tempera- 
ture tolerances are only weakly correlated with their highest 
temperature records (r = 0.397; not significant), and I could discern 
no marked relationship between species desiccation tolerances and 
their potential danger from desiccation. Unfortunately, I was unable 
to do planned experiments on anoxia tolerances, but current 
evidence indicates that upstress distributional limits are largely 
controlled directly (by mortality) or indirectly (e.g., by the 
depressing effects of physiological stress on competitive abilities) by 
the likelihood of severe dilution. 

There is a strong resemblance between taxonomic and ecophysio- 
logical relationships in portunids from both oceans, undoubtedly 
resulting from Pliocene interoceanic connection. Among Pacific 
Colombian crabs, C. toxotes, whose closest Caribbean relatives are C. 
maracaiboensis and C. bocourti, dominates the freshest estuarine 
sites; C. arcuatus, whose closest relative is C. danae, dominates 
intermediate salinities; whereas Portunus asper and Arenaeus mexi- 
canus (Gerstaecker), whose congeners are among the less euryhaline 
Caribbean portunids, occur only in equable shelf waters. 

Downstress Distributional Determinants 

Since all species can occur in marine salinities and all Caribbean 
species can survive in undiluted seawater in the laboratory, climatic 
conditions do not directly limit downstress distributions. What brings 
about the observed patterns of serial replacement in both oceans? 
Possibilities include interference and exploitation competition, pre- 
dation, parasitism, and food quantity and quality. Some investigators 



130 NORSE 

(e.g., MacArthur, 1972) have stressed the role of competition; others 
(e.g., Connell, 1975) have shov^n that predation and parasitism 
further limit distributions within the organisms' physicochemically 
limited fundamental niche space. 

Interference Competition 

To determine whether interference competition could prevent 
seaward expansion of crabs from hyposaline waters, I needed data on 
relative agonistic abilities, size structures, and relative abundances of 
species. I characterized the Caribbean species by salinity as fresh- 
water (C. maracaiboensis, C. bocourti, and C. sapidus), brackish 
water (C. exasperatus and C. danae), and marine (C. marginatus and 
C ornatus). I tested the relative agonistic abilities of the species and 
calculated the proportion of wins between combatants in adjacent 
salinity groups in size-ratio classes between 0.5 and 1.9. I arcsin 
transformed these proportions and regressed them against size ratios, 
from the highest ratio, where a salinity group won none of the 
interactions, to the lowest ratio, where it won all. By solving for a 
0.5 probability, I obtained a "combative equals ratio," the size ratio 
at which adjacent salinity groups have equal probabilities of winning 
agonistic interactions. Since crab stages range from a few millimeters 
to 50 or 75 mm, I used the method of Schoener (1969) to obtain 
mean sizes of adult males (the mean of the largest third) for 
comparisons between species groupings. Relative abundances are in 
numbers per trap-hour. 

A comparison of mean sizes, sizes of combatively equal crabs, 
and densities (Table 4) shows that, although freshwater and 
brackish- water crabs closely approach combative equality, the much 
greater population densities in brackish waters could prevent the 
seaward expansion of freshwater crabs. Using a model of slightly 
greater complexity (Norse, in preparation) in which I calculated the 
total numbers of losses which would be suffered by various-sized 
freshwater crabs as they moved through increasing salinities, I 
estimated that brackish water poses an "agonistic barrier" of 
considerable magnitude (there were up to three times as many losses 
per unit distance traveled as in freshwater). This could account for 
both the abundance and size structure of freshwater crabs along the 
gradient. 

In contrast, only marine crabs (which are less abundant than 
brackish water crabs) of well above average size Eire combatively 
equal to average brackish water crabs. Such large marine crabs are so 
few that they probably do not agonistically confine them to brackish 
water, nor does agonism seem to prevent the seaward expansion of 



PHYSICOCHEMICAL AND BIOLOGICAL STRESSORS 131 

TABLE 4 

MEAN SIZES OF ADULT MALE Callinectes, 

COMBATIVE EQUALS OF MEAN-SIZED 

MALES, AND ABUNDANCES WHERE EACH 

SALINITY GROUP IS DOMINANT 





Freshwater 


Brackish 


Mean sizes, mm 


68.3 


56.5 


Combative equals, mm 


68.3 


57.3 


Number /trap-hour 


0.42 


0.78 




Brackish 


Marine 


Mean sizes, mm 


56.5 


45.7 


Combative equals, mm 


56.5 


51.7 


Number/trap-hour 


0.78 


0.57 



the Pacific Colombian C. toxotes. It is much larger than C. arcuatus 
(X carapace length for adult males is 87.3 vs. 49.0 mm, respec- 
tively). If they were agonistically equivalent to their closest 
Caribbean relatives (freshwater Callinectes vs. C. danae), C. arcuatus 
would have to average 71.6 mm long to equal average C. toxotes 
combatively. If they were agonistically equivalent to the most 
mismatched Caribbean species (freshwater Callinectes vs. C margina- 
tus), C. arcuatus would have to average 67.4 mm to have an equal 
chance of winning against C. toxotes. Since the maximum size of C. 
arcuatus (55.5 mm) is far less than either of these, interference 
competition apparently cannot explain downstress limits of either 
Jamaican brackish-water or Pacific Colombian freshwater crabs. 

Exploitation Competition and Predation 

Although I took quantitative data only on Pacific Colombian and 
Jamaican brachyuran crabs, I repeatedly observed that numbers of 
species in groups likely to be competitors and predators of portunids 
(e.g., other reptant decapods, stomatopods, gastropods, cephalopods, 
echinoderms, and fishes) increase sharply as the likelihood of severe 
dilution decreases. In Jamaica the number of portunid species 
quadruples from the freshest to the most equable marine waters. In 
contrast, I found no obvious rise in the number of individuals along 
the gradient, although population size and structure of many species 
have undoubtedly been affected by human activities. As MacArthur 
(1972) suggested, an increase in diffuse competition (i.e., number of 



132 NORSE 

species) on a resource gradient increases the chance that one species 
sandwiched between others will be eliminated. 

By analogy, what can be called "diffuse predation" also increases 
to seaward. Activities of some crab predators (wading birds, crab- 
eating raccoons in Colombia, and crocodilians in Florida, Jamaica, 
and Colombia) are not greatly affected by the salinity of the water 
containing their prey. Distributions of many other predators are 
affected by salinity, however. Man, American eels, and Callinectes 
are the only other known Callinectes predators in Jamaican fresh 
waters. More predator species occur in brackish waters, however, 
including ariid catfishes in both oceans in Colombia; snook in both 
oceans in Colombia, in Florida, and in Curacao; tarpon and gray and 
schoolmaster snappers in the Caribbean; and some sciaenids in Pacific 
Colombia. Still more occur in marine waters; these include many 
sciaenid species along mainland coasts and moray eels, balistids, 
snappers, grunts, goatfishes, serranids, and sea turtles in all areas 
where they have not been fished out. In fact, Randall (1967) found 
that the majority of 212 Caribbean inshore and reef fish species eat 
crabs. From these observations, it appears that predation (and 
exploitation competition since many of these predators consume 
foods that would otherwise be taken by portunids) steadily increases 
to a maximum in lagoons and coral reefs, probably because many 
predators are orthostenohaline. This trend may not be so simple in 
some areas, however. Freshwaters on Caribbean islands, which are 
not easily reached by oligostenohaline fishes and decapod crusta- 
ceans, are depauperate in comparison with analogous mainland 
communities. On the continents both downstress and upstress 
distributions of freshwater Callinectes may be limited by competi- 
tion and predation from diverse marine and freshwater stenohaline 
communities. 

In addition to studying extrinsic evidence of predation pressure 
from observed instances of predation and numbers of predator 
species and individuals, we can assess its impact on a species by 
examining the intrinsic responses that have evolved to thwart 
predation. Several of these responses indicate that predation pressure 
is more intense in higher salinities. 

All Callinectes are more or less countershaded, although ventral 
surfaces of crabs in some environments may be covered with reddish 
or black fUms. Countershading is almost ubiquitous among demersal 
animals but has a unique denouement in Callinectes. In advanced 
brachyurans the abdomen is usually folded beneath the body. In 
male and immature female Callinectes, the actual dorsal abdominal 
surface and surrounding ventral sternites are indistinguishably light 



PHYSICOCHEMICAL AND BIOLOGICAL STRESSORS 133 

colored. When a female undergoes the molt of puberty, her abdomen 
darkens, becomxing virtually identical in color to the dorsal surface of 
her carapace. When she spawns, the egg mass distends the abdomen 
from her ventral surface so that it is held behind her, as in a lobster, 
thereby maintaining countershading. This must have particular 
adaptive value in higher salinities w^here females spawn and hatch 
their eggs. 

The upper surfaces of Caribbean portunids' carapaces match 
substrata to varying degrees. The freshwater Callinectes can be found 
on widely different substratum colors and textures. Coloration in 
C. bocourti (bright reddish brown and dull green tones) and in 
C. maracaiboensis (highly variable, ranging from ashen gray to dark 
chocolate brown) is cryptic in some environments but somewhat 
conspicuous in others. In contrast, portunids from higher salinities 
occur on fewer substrate types and, with one notable exception, 
are better camouflaged. For example, ground colors in Portimus 
anceps (Saussure), P. depressifrons (Stimpson), and Arenaeus 
cribrarius (Lamarck) are very light (white, gray, and tan), with 
disruptive markings that render them extremely inconspicuous 
against the light calcareous sediments on and in which they live. The 
species from the most equable climates I studied, marine lagoons 
and coral reefs, has almost completely eschewed cryptic coloration. 
Portunus sebae (H. Milne Edwards), apparently a strictly nocturnal 
species, has two unmistakable white-ringed black ocelli on the 
posterior half of its carapace; this is startle coloration, which it shares 
with some coral-reef octopuses and stomatopods and with terrestrial 
moths and mantids. These ocelli have probably evolved as deterrents 
to goatfishes and triggerfishes, which "blow" into reefal sands as 
they forage during the day. 

As Stephenson (1962) stated, swimming crabs are also diggers, 
and those I observed in the field spend a large fraction of their time 
buried in soft substrata, usually with only their eyes, antennae, and 
antennules protruding. Not surprisingly, their eyes are cryptically 
colored to varying degrees. Eyes of freshwater Callinectes have dark 
and light barred or checked patterns, which make them somewhat 
more conspicuous than the light-colored, often stippled eyes of 
species from higher salinities, including P. sebae. Demersal portunids 
have ridged, pilose, or granulose carapaces that retain sediments 
when the crabs have partly or completely emerged from the 
substratum, thereby disrupting their form and permitting a degree of 
camouflage even on substrates that their carapace colors do not 
match closely. As in carapace and eye coloration, there is a trend in 
carapace texturing among species along the gradient. Freshwater 



134 NORSE 

Callinectes have sparse granules of low relief (C sapidus) or large 
areas devoid of granulation (C. bocourti and C. maracaiboensis). 
Callinectes, Arenaeus, Portunus, gind Cronius spp. from higher 
salinities have carapaces adorned by more even, higher, or denser 
granules; strong ridges; dense pile; or depressions. 

Portunids possess another antipredation mechanism, spininess, 
for which variation in the degree of development may reflect similar 
variation in predation pressure. Spines may stimulate the release of 
improperly seized crabs or, failing that, may prevent the predator 
from swallowing the crab. Indeed, Burnett and Snyder (1954) found 
starved eider ducks with blue crabs lodged in their throats. With a 
few exceptions, American portunids in equable climates are spinier, 
having longer, sharper, and/or more spines, reaching maximum 
development in deepwater species such as P. spinicarpus (Stimpson). 

Yet despite extrinsic and intrinsic evidence that predation 
pressure (at least for islands) increases as physicochemical stress 
decreases, regions with greatly differing human fishing pressures have 
similar portunid replacement sequences along salinity gradients. This 
may imply that Callinectes have evolved proximate antipredation 
behaviors that still operate despite relaxed predation pressure (e.g., 
avoidance of higher salinities or waters with lower concentrations of 
terrigenous organics). Such behaviors may not be selected out 
because portunids seem to have long larval lives (Costlow and 
Bookhout, 1959; Bookhout and Costlow, 1974; 1977), and adults in 
one place may have hatched hundreds of kilometers distant, where 
predation pressures were not relaxed. Thus, in some areas, down- 
stress distributions may be intrinsically limited in response to 
predation pressures that no longer exist. 

Parasitism 

Parasites can be divided into two functional groups: endopara- 
sites, which receive the benefits of host osmoregulation (if present) 
and may be unaffected by salinity fluctuations of the host's 
environment, and ectoparasites (in the broad sense, epibionts that 
diminish the host's health), which must be as eurytopic as their hosts 
to survive. Some Callinectes in Pacific Colombian river-mouth sites 
had carapaces fouled with Balanus, but heavier incrustations of 
Balanus, Chelonibia (another balanomorph barnacle), bryozoans, and 
sabellid polychaetes occurred on Callinectes in shelf waters. Marine 
portunid species were much freer of external fouling organisms. 
Parasites living on the gills are also ectoparasites. I have found stalked 
(lepadomorph) barnacles of the genus Octolasmis on the gills of all 
common Jamaican and eastern Pacific Callinectes, particularly adult 



PHYSICOCHEMICAL AND BIOLOGICAL STRESSORS 135 

females, which tend to occur in higher salinities; in some cases 
gill chambers were clogged with hundreds. Stenohaline marine 
portunids, however, usually have few or no Octolasmis on their gills 
(De Turk, 1940; Humes, 1941; Walker, 1974). In low salinities 
euryhaline crabs have few external or gill foulers, but, when they 
enter higher salinities, they become susceptible to fouling. Marine 
species, however, are less vulnerable, presumably because of morpho- 
logical, physiological, behavioral, or life-historic adaptations for 
preventing larval settling. Crabs with fouled carapaces and limbs 
suffer higher energetic maintenance costs and diminished walking 
and swimming abilities. Those with gill foulers must compete with 
the parasites for oxygen, are prevented from cleaning foreign matter 
(sand grains, ciliates, nemerteans, bryozoans) from their gills, further 
diminishing their oxygen uptake, and probably have weakened gill 
discs, which provide an avenue for entry of pathogenic bacteria and 
protozoa into their circulatory systems. Not surprisingly, crabs 
having heavily fouled gills are noticeably less active than less-fouled 
conspecifics. 

Food Availability 

Both quantitative and qualitative aspects of food change along 
the gradient in terrestrial influence on aquatic climate. Available data 
show that Callinectes have varied diets (Darnell, 1958; Tagatz, 1968; 
Estevez, 1972), and V. Fox-Norse and I observed that they have 
a surprisingly varied repertoire of feeding behavior. They hunt prey 
as diverse as polychaetes and mullet, scavenge for carrion, scrape 
aufwuchs from sea-grass blades and rocks, eat detritus-rich sediments, 
and even filter feed when they encounter dense concentrations of 
zooplankton (Norse, 1975; Fox-Norse, in preparation). In the 
Caribbean study areas, water clarity permits autochthonous plank- 
tonic and benthic primary production, but much benthic macro- 
phyte productivity and allochthonous material from terrestrial plants 
overhanging streams enter detritus-based food webs (Fenchel, 1970; 
Odum and Heald, 1972). On the Pacific Colombian coast, since 
estuaries and inshore shelf waters appear too turbid to allow major 
planktonic and benthic plant production, most energy input is in the 
form of wood, bark, and leaves from mangroves and other trees. 
Since Callinectes feed largely on detritus or detritus-feeding organ- 
isms, their productivity should be a function of the amount of 
available detritus. The trawls collected animals, whose total biomass 
did not vary greatly along transects, and macroscopic terrigenous 
detritus, which far outweighed animal biomass in fresher sites but 
decreased rapidly, constituting perhaps only 1% of the hauls in deeper 



136 NORSE 

shelf sites. If the amount of smaller, edible detritus is proportional to 
that of macrodetritus, the most climatically stressful environments 
have superabundant food for their inhabitants, but species are 
increasingly likely to be food-limited to seaward. Although upriver 
species can afford to be inefficient at finding or assimilating food, 
selection should favor increased efficiency among organisms in 
climatically more equable but trophically poorer waters. Downstress 
distributional limits may correspond to the points where an 
individual's maintenance costs equal its income. 

Energy intake is affected by the availability, as well as the over- 
all quantity of potential food. In lagoons and among coral reefs, 
predation pressures have stimulated the evolution of highly devel- 
oped antipredation mechanisms in benthic invertebrates (Bakus, 

1964). Thus potential prey are usually out of reach (e.g., they bore 
into hard substrates), hard to find (cryptic), or in some way 
unpleasant to would-be predators (e.g., they have startling or warning 
coloration, sharp spines, envenomating apparatus, toxicity, or 
noxiousness). In informal experiments (Norse, 1975), I found that 
normally exposed reefal animals were immune from predation by 
Callinectes, but estuarine organisms were not. Thus an estuarine crab 
on a coral reef, hke the Ancient Mariner, could be surrounded by 
food resources but unable to use them. 

We have seen correlative evidence supporting alternate hypothe- 
ses that downstress portunid distributions are limited by interference 
competition, exploitation competition, predation, parasitism, and 
food-resource availability. Interactions of these factors could also be 
limiting since, as climatic stress decreases, eurytopic portunids 
increasingly become host to ectoparasites. This raises their main- 
tenance costs while diminishing their abilities to compete for 
increasingly scarce food resources, to win agonistic contests against 
relatively stenotopic portunids, and to escape increasingly intense 
predation. Unfortunately, if my observations are correct, we cannot 
yet reject any of the hypotheses. Even if only one of the major 
categories were correlated with changes in climatic stress and 
portunid distributions, we still would not know the precise limiting 
factors. Rather, the hypotheses generated by these observations 
should be tested rigorously so that we can continue to approach an 
understanding of the determinants of organismic distributions. 

The Callinectes spp. whose crab stages can live in the freshest 
waters at the edges of both oceans are more than transients but less 
than permanent residents; they are catadromous (Norse, 1975; 1977; 
Norse and Estevez, 1977). Although this skews their distributions to 
seaward, the species that reach peak abundances along rather than at 



PHYSICOCHEMICAL AND BIOLOGICAL STRESSORS 



137 



u 
z 
< 

Q 
Z 
Z) 

m 
< 




> 



O 



HIGH 



PHYSICOCHEMICAL 
STRESS 



LOW 



Fig. 2 Effect of risk of mortality (solid bold line) on abundance 
(thin line) of a species inhabiting a portion of a physicochemical 
gradient. Sources of risk of mortality : abiotic stressors (white area 
under bold line); biological stressors (shaded area under bold line). 



the ends of the gradient otherwise have Gaussian abundance curves, a 
feature they share with very different organisms, e.g., some trees 
(Whittaker, 1967) and birds (Terborgh, 1971) inhabiting other 
gradients. The model shown in Fig. 2 could account for these 
characteristic distribution patterns in groups that originated at one 
end of a physicochemical gradient. As the risk of mortality from 
usual or unusual weather decreases, risk from various biological 
stressors increases. The abundance of the species in question mirrors 
the combined risk of mortality from both abiotic and biological 
stressors, with peak abundance corresponding to minimum combined 
risk of mortality. The abundance curves of species result from actual 
selective mortality if they lack life-history stages that can discrimi- 
nate among habitats. In species having the potential for such 
behavior, fitness is increased by avoidance of risky portions of the 
gradient, and abundance curves result from both habitat selection 
and mortality. The positions of species along the gradient, then, 
reflect the relative degrees to which they have specialized toward 
coping with physicochemical vs. biological stressors. 

ACKNOWLEDGMENTS 



I have profitted greatly from the essential balance of knowledge, 
wisdom, and honesty provided by John S. Garth, Gerald J. Bakus, 
William Stephenson, Alan D. Havens, Hugh Dingle, and Virginia 
Fox-Norse. Many people helped in the field and laboratory, 



138 NORSE 

particularly Heather Copland, Mario Estevez, Virginia Fox-Norse, 
Alan D. Havens, Paul Sammarco, Avril Siung, Michael Weber, and 
Bernd Werding. I am indebted to the directors and staffs of the 
following institutions for providing field, laboratory, and library 
facilities and taxonomic reference collections: the University of 
Arizona— University of Sonora Cooperative Marine Station; the 
Smithsonian Tropical Research Institution; Colombia's Institute for 
the Development and Management of Natural Resources; Pigeon Key 
Marine Environmental Station, University of Miami; Discovery Bay 
Marine Laboratory, University of the West Indies; the Caraibisch 
Marien-Biologisch Instituut (CARMABI); the Instituto Colombo- 
Aleman de Investigaciones Cientificas "Punta de Betin"; the Harvard 
University Museum of Comparative Zoology; the American Museum 
of Natural History; the Allan Hancock Foundation of the University 
of Southern California; and the University of Iowa. Donald 
Doumakes, Virginia Fox-Norse, and James H. Thorp gave valuable 
criticism of the manuscript. Funds were provided, in part, by the 
Allan Hancock Foundation, University of Southern California; the 
Organization for Tropical Studies; the Society of Sigma Xi; the 
Theodore Roosevelt Memorial Fund, American Museum of Natural 
History; National Science Foundation grant BMS 74-22718 to Hugh 
Dingle; and National Institute of Mental Health grant (5 
TOl 10641-10) to the Neurobehavioral Sciences Program, University 
of Iowa. This is contribution No. 157, Discovery Bay Marine 
Laboratory. 



REFERENCES 

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spinicarpus Reared in the Laboratory, Bull. Mar. ScL, 24: 20-51. 

, 197 7, Larval Development of Callinectes similis Reared in the Laboratory, 

Bull. Mar. ScL, 27: 704-728. 
Brusca, R. C, 1973, Handbook to the Common Intertidal Invertebrates of the 

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American Eiders, A ufe, 71: 315-316. 
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Costlow, J. D., and C. G. Bookhout, 1959, The Larval Development of 

Callinectes sapidus Rathbun Reared in the Laboratory, Biol. Bull. (Woods 

Hole, Mass.), 116: 373-396. 



PHYSICOCHEMICAL AND BIOLOGICAL STRESSORS 139 

Darnell, R. M., 1958, Food Habits of Fishes and Larger Invertebrates of Lake 

Ponchartrain, Louisiana, An Estuarine Community, Publ. Inst. Mar. ScL, 

Univ. Tex., 5: 353-416. 
De Turk, W. E., 1940, The Parasites and Commensals of Some Crabs at Beaufort, 

North Carolina, Ph.D. Thesis, Duke University, Durham, N. C. 
Estevez, M., 1972, Estudio preliminar sobre la biologi'a de dos especies 

alopatricas de cangrejos brachyrhyncha del Pacifico Colombiano, Bol. Museo 

Mar (U. Bogota Jorge Tadeo Lozano, Fac. Cienc. Mar.), 4: 1-17. 
Fenchel, T., 1970, Studies on the Decomposition of Organic Detritus Derived 

from the Turtle Grass Thalassia testudinum, Limnol. Oceanogr., 15: 14-20. 
Garth, J. S., and W. Stephenson, 1966, Brachyura of the Pacific Coast of 

America Brachyrhyncha: Portunidae, Allan Hancock Monogr. Mar. Biol, 1: 

1-154. 
Gibbs, R. J., 1970, Circulation in the Amazon River Estuary and Adjacent 

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Zool. Verh. (Leiden), 44: 1-296. 
— , 1969, Portunus binoculus, N. Sp., A New Deep-Water Swimming Crab from 

the Caribbean Region (Crustacea, Decapoda, Brachyura), Bull. Mar. Sci., 19: 

409-427. 
Humes, A. G., 1941, Notes on Octolasmis mulleri (Coker), A Barnacle 

Commensal on Crabs, Trans. Am. Microsc. Soc, 60: 101-103. 
MacArthur, R. H., 1972, Geographical Ecology: Patterns in the Distribution of 

Species, Harper and Row Publishers, Inc., New York. 
Norse, E. A., 1975, The Ecology of Blue Crabs, Genus Callinectes (Brachyura: 

Portunidae) in the Caribbean, Ph.D. thesis. University of Southern 

California. 

, 1977, Aspects of the Zoogeographic Distribution of Callinectes (Brachyura: 

Portunidae), Bull. Mar. Sci., 27: 440-447. 
, and M. Estevez, 1977, Studies on Portunid Crabs from the Eastern Pacific. 

I. Zonation Along Environmental Stress Gradients from the Coast of 

Colombia, Mar. Biol., 40: 365-373. 
, and V. Fox-Norse, 1977, Studies on Portunid Crabs from the Eastern 

Pacific. II. Significance of the Unusual Distribution of Euphylax douii. Mar. 

Biol., 40: 374-376. 
Odum, W. E., and E. J. Heald, 1972, Trophic Analyses of An Estuarine 

Mangrove Community, Bull. Mar. Sci., 22: 671-738. 
Randall, J. E., 1967, Food Habits of Reef Fishes of the West Indies, Stud. Trop. 

Oceanogr., 5: 665-847. 
Schoener, T. W., 1969, Size Patterns in West Indian Anolis Lizards. I. Size and 

Species Diversity, Syst. Zool., 18: 368-401. 
Stephenson, W., 1962, Evolution and Ecology of Portunid Crabs, with Especial 

Reference to Australian Species, in The Evolution of Living Organisms, 

G. W. Leeper (Ed.), pp. 311-327, Melbourne University Press, Melbourne, 

Victoria, Australia. 
Tagatz, M. E., 1968, Biology of the Blue Crab Callinectes sapidus Rathbun in 

the St. Johns River, Florida, Fish. Bull, 67: 17-33. 
Taissoun, E., 1972, Estudio comparativo, taxonomico y ecologico entre los 

cangrejos (Dec. Brachyura. Portunidae), Callinectes maracaiboensis (nueva 

especie), C. bocourti (A. Milne Edwards) y C. rathbunae (Contreras) en el 

Golfo de Venezuela, Lago de Maracaibo y Golfo de Mexico, Bol. Cent. 

Invest. Biol., Univ. Zulia, 6: 1-45. 



140 NORSE 

Terborgh, J., 1971, Distribution on Environmental Gradients: Theory and a 

Preliminary Interpretation of the Distributional Patterns in the Avifauna of 

the Cordillera Vilcabamba, Peru, Ecology, 52: 23-40. 
Walker, G., 1974, The Occurrence, Distribution and Attachment of the 

Pedunculate Barnacle Octolasmis mulleri (Coker) on the Gills of Crabs, 

Particularly the Blue Crab, Callinectes sapidus, Biol. Bull. (Woods Hole, 

Mass.), 147: 678-689. 
Whittaker, R. H., 1967, Gradient Analysis of Vegetation, Biol. Rev. Cambridge 

Philos. Soc., 42: 207-264. 
Williams, A. B., 1965, Marine Decapod Crustaceans of the Carolinas, Fish. Bull, 

65: 1-298. 
, 1966, The Western Atlantic Swimming Crabs Callinectes ornatus, C. danae 

and a New Related Species (Decapoda, Portunidae), Tulane Stud. Zool. Bot., 

13: 83-93. 
- — , 1974, The Swimming Crabs of the Genus Callinectes (Decapoda: 

Portunidae), Fish. Bull, 72: 685-798. 



EFFECTS OF FLUCTUATING FLOW RATES 
AND WATER LEVELS ON CHIRONOMIDS: 
DIRECT AND INDIRECT ALTERATIONS 
OF HABITAT STABILITY 



ALAN P. COVICH, WILLIAM D. SHEPARD, ELIZABETH A. BERGEY, 

and CARYN S. CARPENTER 

Department of Zoology, University of Oklalioma, Norman, Oklahoma 



ABSTRACT 

Regulation of stream flow-through water storage by hydroelectric dams and 
flood-control impoundments may alter benthic macroinvertebrate communities 
that are adapted to distinct seasonal shifts in water levels. Isolating these changes 
in community structure from changes caused by alterations in water quality is 
not possible currently, because data on effects of fluctuating flow in 
uncontaminated streams are infrequently reported. Studies from February 
through August 1977 on the Grand River and two of its tributaries in Oklahoma 
were conducted at seven stations. Of the 122 taxa of macroinvertebrates 
collected, 24 were genera of chironomids. Glyptotendipes dominated most 
locations in terms of density and biomass. Fluctuations in water level and water 
flow resulting from reservoir discharges were found to influence chironomid 
populations in both the discharge-receiving river and its two tributaries. 
Decreased density, biomass, and numbers of genera characterized the most 
intensely fluctuating sites. Indirect effects on substrate size, composition, and 
movement, as well as direct washing out of organisms from the substrate, may 
have caused the relative declines in abundance. 



Many studies of macroinvertebrate community structure emphasize 
analyses of changing population densities and species diversities 
because these biological changes are known to reflect long-term 
changes in many physical and chemical parameters (Cummins, 1975; 
Edwards, Hughes, and Read, 1975; Gaufin, 1973; Goodnight, 1973; 
Hynes, 1970; Isom, 1971). Despite the recognized importance of 
fluctuations in flow rates and water levels for "catastrophic drift" 
(Waters, 1972) of aquatic invertebrates, data on fluctuations of 
natural lakes and streams are infrequently reported. Thus base-line 

141 



142 COVICH, SHEPARD, BERGEY, AND CARPENTER 

data for evaluating potential natural stresses in uncontaminated, 

unmanaged watersheds are lacking. Although ranges and mean 

discharge rates are usually reported in studies of managed reservoirs, 

the frequency of the fluctuations and their impacts on benthic 

macroinvertebrates in downstream waters is often not monitored. 

The concern expressed by Wolman (1971) is still unresolved: 

Many measurements of biological effects are done during low and 

summer flows where measurement is easy, organisms often 

flourish, and concentrations of various substances in the flow are 

high. The effect of winter flow . . . and the special significance to 

the flora and fauna of periodic floods are not well documented. 

Significantly, however, among the most common trends in river 

management is the progressive regulation of flow through the 

provision of storage. Conceivably regulation rather than pollution 

alone may have the most far-reaching effects on the character of 

many river systems .... 

Several investigators have called attention to some direct and 
indirect effects of flow rates and water-level changes on benthic 
macroinvertebrates (Baxter, 1977; Cairns et al., 1971; Trotsky and 
Gregory, 1974; Ward, 1976). For example, Neel (1963) reported that 
"reduction of winter stages below normal unregulated levels is 
common and often reduces the stream's carrying capacity for many 
forms of life .... Daily fluctuations in reservoir releases, which are 
often occasioned by power peaking, discourage littoral stream life 
and cause many readaptations." Minshall and Winger (1968) noted 
that "irrigation and reservoir management practices tend to cause 
periodic fluctuation on local stream levels, particularly during the 
summer months, when stream flows are already minimal." Ward and 
Short (1978) compared benthic communities from streams with 
constant and widely fluctuating flow regimes in the Rocky Moun- 
tains. They found that low standing-crop biomass values were 
associated with pronounced water-level fluctuations and that streams 
with regulated water flows had very different species compositions 
and lower species diversities than streams with natural flow regimes. 
In this report, we discuss the effects of varied flow rates and water 
levels on the chironomid community downstream from a large 
reservoir during a 7-month period. 

STUDY AREA 

Our seven sample stations (Fig. 1) were in the Grand (Neosho) 
River drainage basin. The watershed, located in Mayes County, 
Oklaihoma, includes two tributaries (Pryor Creek, a permanent 



EFFECTS OF FLUCTUATING FLOW RATES 



143 



LAKE HUDSON 




CHIMNEY 

ROCK 

RESERVOIR 



STATE 
HIGHWAY 33 



GRAND RIVER 



FORT GIBSON 



Fig. 1 Map of study area showing locations of seven sampling 
stations in the Grand River drainage basin, Mayes County, Okla- 
homa. U. S. Geological Survey gauging stations are located at two 
sites (A and B) along the Grand River. During period of maximal 
water storage in Fort Gibson Reservoir, water flows upstream in 
Chouteau Creek (C-1 and C-2) and Pry or Creek (P-1 and P-2), and 
the flow rate on the Grand River is slow. During periods of water 
release from both Fort Gibson Reservoir and Lake Hudson, 
downstream flow rates rapidly increase at all stations. Station G-1 is 
subject to frequent daily fluctuations in water level and flow rates as 
a result of releases from Lake Hudson. 



144 COVICH, SHEPARD, BERGEY, AND CARPENTER 

stream, and Chouteau Creek, an intermittent stream) of the Grand 
River, which flows south into the Arkansas River. Upstream from the 
study area, the Grand River is impounded by Lake Hudson and, 
downstream, by Fort Gibson Reservoir. Because the reservoir system 
is used to produce hydroelectric power (Lake Hudson generates 
100 MW, and Fort Gibson produces 45 MW), a large amount of 
storage capacity is needed. The major river flow occurs in winter and 
spring, whereas the peak power demand occurs during the summer 
months (Fredrich and Beard, 1975). 

Most of the drainage area is used for pasture (~50%) and 
rangeland (~10%). Forest covers less than 25%; cropland is ~10%, 
and the remaining 5% is urbanized. Heavy rainfall is followed by 
rapid runoff because natural vegetative cover is sparse. 

The U. S. Geological Survey collects data on mean daily 
discharge 4.0 km downstream from Lake Hudson (Fig. 1, point A) 
and 1.8 km downstream from Fort Gibson Reservoir (Fig. 1. point 
B). From March through August 1977, the maximum discharge 
occurred in late June below Lake Hudson and in early July below 
Fort Gibson Reservoir (Fig. 2). During periods when releases from 
Fort Gibson did not match those from Lake Hudson and other 
inflows, we observed upstream flow in Pryor and Chouteau creeks. 
Although we made no attempt to measure flow rate, we did note 
rapid increases in water level (up to 2 m at station G-1) after 
managed releases from upstream and downstream reservoirs. 

METHODS 

Beginning in February 1977, three prelabeled Hester— Dendy 
samplers (Hester and Dendy, 1962) were placed at each of the seven 
sample stations. Samplers were suspended ~1 m below floats tied to 
emergent trees and stumps. After a period of approximately 1 
month, allowed for colonization by invertebrates, the samplers were 
removed, and another set was exposed. The Hester— Dendy samplers 
were carefully raised, placed immediately into plastic bags, and 
washed with 70% isopropyl alcohol to preserve the specimens. 

Organisms were sorted under a dissecting microscope and 
identified to the generic level. The techniques described by Mason 
(1973), Bryce and Hobart (1972), and Beck (1975) were used for 
mounting head capsules for microscopic identification. Specimens 
were deposited in the permanent collection of the Stovall Museum of 
Science and History, University of Oklahoma. 

Results were expressed as density (number of individuals per 
square meter of sampler), biomass (total weight of each taxon 



EFFECTS OF FLUCTUATING FLOW RATES 



145 




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146 COVICH, SHEPARD, BERGEY, AND CARPENTER 

per sampler), and diversity. Diversity was measured by the 
Shannon— Weaver index (d) as described by Wilhm (1972) and Weber 
(1973). Pupae were not used in diversity calculations because of 
difficulties in identification. Biomass was determined by weighing 
ovendried (4 hr at 100°C) specimens on an electrobalance (Cahn 
Instruments, model G). Measured biomass was an underestimation 
because head capsules were removed for identification before drying 
and weighing. 

RESULTS 

Of the 122 taxa of macroinvertebrates collected, 64 were insects. 
Twenty-four genera in three subfamilies of the Chironomidae were 
collected. The most represented subfamily was the Chironominae, 
with 15 genera. Of these 15, ten were very widespread, being found 
at all seven sample stations. In contrast, five genera were found at 
only one station (Table 1). Station C-2 had the highest number of 
genera; rarer genera were restricted to one or two stations on Pryor 
and Chouteau creeks. 

The dominant chironomid, in terms of both density and biomass, 
was Glyptotendipes, which comprised over half the chironomids 
collected throughout the sampling period, except at station G-1 
(Fig. 3). Dicrotendipes was the second most abundant genus at five 
of the sampling stations, but Ablabesmyia was more common at the 
Pryor Creek stations. Glyptotendipes and Dicrotendipes are both in 
the subfamily Chironominae, and Ablabesmyia is in the subfamily 
Tanypodiriae. 

Station G-1 showed the greatest increase in water level and flow 
rate when water was released from Lake Hudson because a low-water 
dam is located immediately below this station and the river channel 
is constricted. The density and biomass values were consistently low 
at station G-1 (Figs. 4 and 5) in comparison with other stations on 
the Grand River, especially during May and June, when discharge 
rates and water-level fluctuations were maximal. Station G-2, which 
was somewhat sheltered, being located near an island among 
emergent dead trees, frequently showed a higher chironomid density 
than did the more exposed stations, G-1 and G-3. Station G-2 also 
had the highest biomass values of any Grand River station in early 
June before maximal discharge (Fig. 4). 

Although the chironomid densities of the Chouteau Creek 
stations (C-1 and C-2) were higher than those of Pryor Creek stations 
(P-1 and P-2), the patterns of chironomid density throughout the 
sampling period were quite similar for the two tributaries (Figs. 6 



EFFECTS OF FLUCTUATING FLOW RATES 



147 



TABLE 1 

TOTAL GENERIC DISTRIBUTION AND 
ABUNDANCE PER STATION* 











Station 










G-1 


G-2 


G-3 


C-1 


C-2 


P-1 


P-2 


Glyptotendipes 


1 


1 


1 


1 


1 


1 


1 


Dicrotendipes 


1 


1 


1 


1 


1 


2 


2 


Ablabesmyia 


3 


3 


3 


3 


1 


1 


1 


Polypedilum 


3 


3 


3 


4 


3 


3 


3 


Procladius 


4 


3 


3 


3 


3 


3 


3 


Psectrocladius 


3 


3 


3 


3 


3 


4 


3 


Tribelos 


3 


3 


3 


3 


3 


4 


3 


Chironomus 


3 


3 


4 


3 


4 


3 


3 


Micropsectra 


3 


3 


3 


4 


4 


4 


3 


Orthocladius 


4 


3 


4 


4 


3 


4 


3 


Cricotopus 


3 


3 


3 




3 




3 


Parachironomus 


4 


4 


4 


3 


4 


4 


4 


Trissocladius 


4 


3 




4 




3 


3 


Cryptochironomus 


4 


4 


4 


4 


3 


4 




Rheotany tarsus 








4 


4 


3 


4 


Einfeldia 




4 


4 




4 




4 


Metriocnemus 




4 




3 


4 






Pseudochironomus 










4 




4 


Phaenopsectra 








4 






4 


Clinotanypus 










4 






Kiefferulus 








4 








Endochironomus 










4 






Goeldichironomus 










4 






Trichocladius 










4 






Total genera 


14 


16 


14 


17 


21 


14 


17 


Total samples 


12 


13 


12 


11 


11 


12 


12 



*Doniinance classes, based on abundance in total samples: 1, 
dominant (1000+); 2, abundant (500 to 1000); 3, common (50 to 
500); 4, uncommon (1 to 50). 



and 7). The upstream sites (C-1 and P-1) had lower densities than 
those downstream (C-2 and P-2). Both density and biomass reached 
their highest peaks in June at station C-2 (Figs. 5 and 6), where the 
downstream flow was minimal and the stream was very broad and 
shallow. At all times density and biomass values were relatively high 
at C-1 and C-2. No sampling was conducted at Chouteau or Pryor 
creeks in August because time for sorting the samples collected 
earlier became limited. 

Another important difference among the stations was the month 
of maximum density. Maximum density peaks occurred in May at 



148 



COVICH, SHEPARD, BERGEY, AND CARPENTER 





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5000 




MAR. MAY JUNE JULY AUG. 
MONTH 

(a) 



MAR. MAY JUNE JULY AUG. 
MONTH 

(b) 



5000 




MAR. MAY JUNE JULY AUG. 
MONTH 

(0 

Fig. 5 Density values for stations G-1 (a), G-2 (b), and G-3 (c), 
based on averages of triplicate samples. Because of sampler losses 
only duplicate samples were available at G-1 and G-2 in August. Bars 
indicate range of data; black dots denote means. 



5000 




1000 



MAR. MAY JUNE JULY 
MONTH 



(a) 



> 


— 


 (b) — 


t 3000 




L 


z 

LU 

Q 




\- 


1000 


f"-v 


L 1- 



MAR. MAY JUNE JULY 
MONTH 

(b) 



Fig. 6 Density values for stations P-1 (a) and P-2 (b), based on 
averages of triplicate samples at all stations. 



EFFECTS OF FLUCTUATING FLOW RATES 



151 



5000 



3000 



Z 
Q 



1000 




> 

CO 

z 

Q 







. 


9000 












7000 






5000 


- / 


\- 


3000 


J 


r 


^- 


1000 


-/ - 



MAR. MAY JUNE JULY 
MONTH 

(a) 



MAR. MAY JUNE JULY 
MONTH 



(b) 



Fig. 7 Density values for stations C-1 (a) and C-2 (b), based on 
averages of triplicate samples, except for use of duplicates in March. 



G-3; June at C-2, P-2, and G-2; July at C-1 and P-1; and August at 
G-1. Thus the station with relatively slower and more uniform flow 
had earlier peak densities. 

Chironomid diversity (d) was relatively low throughout the 
sampling period; values ranged from 0.34 to 2.67. Only at station 
G-1 did diversity remain relatively uniform, but these values were 
strongly influenced by the relatively low densities of chironomids 
collected at this station. 

The patterns of generic distributions resemble those of chiron- 
omid density. The exposed Grand River sites generally contained 
fewer taxa (G-1 and G-3 both had only 14 genera) than did the more 
protected station (G-2 had 16 genera) and most of the tributary 
stations. The stations on Chouteau Creek had high generic 
diversity, with the maximum number (21 genera) occurring at 
C-2. Again, as for most values of density and biomass, the 
numbers of taxa were lower at the upstream stations in both 
Pryor and Chouteau creeks. 

DISCUSSION 



The high density of Glyptotendipes at most sampling stations is 
not surprising when we consider the ecological distribution of the 



152 COVICH, SHEPARD, BERGEY, AND CARPENTER 

genus (Beck, 1977; Weber, 1973). Paine and Gaufin (1956) found 
Glyptotendipes to be typical of organically enriched streams, whereas 
Kimerle and Anderson (1970) reported that G. barbipes was the 
dominant species on waste-stabilization lagoons. In Oklahoma this 
genus occurs where summer oxygen levels are lowered by high rates 
of organic productivity, e.g., in Arbuckle Lake, as reported by 
Parrish and Wilhm (1978). Thus the genus appears to be well adapted 
to the relatively nutrient-rich slow-flowing water found in most of 
our sampling area. In contrast to four of our seven stations, Harrold 
(1978) found approximately equal numbers of Glyptotendipes and 
Ablabesmyia in his Hester— Dendy samplers in the Knife River in 
North Dakota. 

Although the species of Glyptotendipes from the Grand River are 
not yet identified, at least three species (G. libiferous, G. merid- 
ionalis, and G. barbipes) are known to be opportunistic in their rapid 
invasion of new reservoirs (Aggus, 1971; Patterson and Fernando, 
1969; 1970). Presumably the species that dominate the Grand River 
share this trait and are readily able to colonize samplers placed in 
habitats with fluctuating flow rates and water levels. 

A general pattern emerges when the chironomid populations are 
compared with the relative degree of water-flow and water-level 
fluctuations at each of the seven sampling sites. First, under 
conditions of extreme fluctuation (i.e., at station G-1, where the 
Grand River is constricted), chironomid density, biomass, and 
numbers of genera present were all low and were relatively constant 
throughout our study period. A smaller degree of fluctuation occurs 
in a second group of stations. Stations G-3, which is on a relatively 
exposed, straight section of the Grand River, and C-1 and P-1, where 
the relative narrowness and shallowness of the two upstream 
tributaries make them more susceptible to water-level fluctuations 
than the downstream stations, have an intermediate level of 
chironomid densities. These densities also showed a successive series 
of changes (increasing in the tributaries and decreasing at G-3) during 
the sampling period. In addition, stations P-1 and C-1 have fewer 
genera than the downstream stations on the same streams. 

The remaining stations (G-2, P-2, and C-2), which comprise the 
third group, have a smaller degree of water-flow and water-level 
fluctuations. The two downstream tributary stations (P-2 and C-2) 
are located where the streams meet the Grand River. Both areas are 
wide and fairly deep. Each of these stations has a high chironomid 
biomass and the highest densities and largest number of genera in 
each of their respective river or stream systems. Also, each has a June 
peak in chironomid density, indicating a possible minimal effect of 



EFFECTS OF FLUCTUATING FLOW RATES 153 

washout by high discharge rates. High recruitment from hatching 
eggs in May and June, followed by late summer emergence of other 
cohorts of chironomids, would be characteristic of this pattern of 
changing density. The two downstream tributary stations (P-2 and 
C-2) appear to have a combination of both genera typical of the 
larger, slower flowing Grand River and genera typical of small, 
fast-flowing streams. 

The relatively high biomass and density of chironomid larvae in 
most of our study area apparently result from a combination of 
relatively nutrient-rich, stable substrate and slow-flowing waters. It is 
difficult to distinguish natural fluctuations of flow rates and water 
levels from managed fluctuations in this reservoir system. Other 
investigators have noted significant stresses on chironomid popula- 
tions as a result of both natural and regulated flow regimes. For 
example, Spence and Hynes (1971) concluded that, relative to 
stations farther downstream or upstream, increased numbers of 
chironomids result from greater availability of detritus and uniform 
flow below Shand Dam in the Grand River in Ontario. Unregulated 
streams may also be affected strongly by flow-rate and water-level 
fluctuations that occur after rapid runoff in foothill streams 
(Siegfried and Knight, 1977) or during flooding after heavy rainfall 
(Hoopes, 1974). 

Various types of adaptations give distinct advantages to partic- 
ular species in habitats with fluctuating waters. The end result is a 
high standing-crop biomass of only a few dominant species and a 
general pattern of low diversity. These frequent disruptions in the 
physical and chemical nature of the habitat are analogous to 
observations in plankton communities that high species diversity 
results from a "contemporgineous disequilibrium" of the open waters 
(Richerson, Armstrong, and Goldman, 1970). Benthic habitats 
exposed to intensely fluctuating waters are apparently characterized 
by low diversity, however, because of the high degree of seasonal and 
daily unpredictability in flow and because of the relative newness of 
these types of frequently exposed and inundated substrates. Fisher 
and LaVoy (1972) aptly termed these substrates freshwater "inter- 
tidal" biotopes and pointed out that a high degree of "pulse 
stability" is potentially attainable in some new habitats. Currently 
the managed freshwater "intertidal beaches" appear unstable in 
comparison with the naturally regulated streams and are dominated 
by a very restricted number of taxa. The dominant chironomids 
generally have high fecundity and are well adapted for dispersal both 
as larvae and as airborne adults. Thus they can be viewed as typical 
"r-selected" species (Baxter, 1977). 



154 COVICH, SHEPARD, BERGEY, AND CARPENTER 

CONCLUSION 

Fluctuations in water level and water flow resulting from 
reservoir discharge were found to influence the chironomid popula- 
tions in both the discharge-receiving river and its tributaries (at least 
as far upstream as water backed up from a second reservoir pool). 
The greater the degree of fluctuations, the greater the effects 
appeared to be, so that decreasing density, biomass, and numbers of 
genera characterized the most intensely fluctuating sites. 

A single chironomid genus, Glyptotendipes, clearly dominated all 
seven stations. In our study, however, we were unable to identify 
specific mechanisms responsible for this dominance. With the 
establishment of adequate base-line data, we should be able to follow 
community development in selected habitats and to learn a great deal 
about relationships between dominance and habitat stability. 



REFERENCES 

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Reservoir During the Second and Third Years of Filling, 1965—1966, in 

Reservoir Fisheries and Limnology, G. E. Hall (Ed.), Special Publication No. 

8, pp. 139-152, American Fisheries Society, Bethesda, Md. 
Baxter, R. M., 1977, Environmental Effects of Dams and Impoundments, Annu. 

Rev. Ecol. Systemat, 8: 255-283. 
Beck, W. M., 1975, Chironomidae, in Keys to the Water Quality Indicative 

Organisms of the Southeastern United States, F. K. Parrish (Ed.), Report 

EPA-657-695/5483, Environmental Protection Agency, GPO. 
, 1971 , Environmental Requirements and Pollution Tolerance of Common 

Freshwater Chironomidae, Report EPA-600/4-77-024, Environmental Pro- 
tection Agency, GPO. 
Bryce, D., and A. Hobart, 1972, The Biology and Identification of Larvae of the 

Chironomidae (Diptera), Entomol. Gaz., 23: 175-217. 
Cairns, J., J. S. Grossman, K. L. Dickson, and E. E. Herricks, 1971, The 

Recovery of Damaged Ecosystems, Assoc. Southeast. Biologists Bull., 18: 

79-106. 
Cummins, K. W., 1975, Macroinvertebrates, in River Ecology, B. A. Whitton 

(Ed.), pp. 170-198, University of California Press, Berkeley. 
Edwards, R. W., B. D. Hughes, and M. W. Read, 1975, Biological Survey in the 

Detection and Assessment of Pollution, in The Ecology of Resource 

Degradation and Renewal, M. J. Chadwick and G. T. Goodman (Eds.), 

pp. 139-156, John Wiley & Sons, Inc., New York. 
Fisher, S. G., and A. LaVoy, 1972, Differences in Littoral Fauna Due to 

Fluctuating Water Levels Below a Hydroelectric Dam, J. Fish. Res. Board 

Can., 29: 1472-1476. 
Fredrich, A. J., and L. R. Beard, 1975, Complementary Use of Hydro and 

Thermal Power, in Water Management by the Electric Power Industry, E. F. 

Gloyna, H. H. Woodson, and H. R. Drew (Eds.), pp. 65-74, University of 

Texas Press, Austin. 



EFFECTS OF FLUCTUATING FLOW RATES 155 

Gaufin, A. R., 1973, Use of Aquatic Invertebrates in the Assessment of Water 
Quality, in Biological Methods for the Assessment of Water Quality, J. Cairns 
and K. L. Dickson (Eds.), pp. 96-116, American Society for Testing and 
Materials, Philadelphia. 

Goodnight, C. J., 1973, The Use of Aquatic Macroinvertebrates as Indicators of 
Stream Pollution, Trans. Am. Microsc. Soc, 92: 1-13. 

Harrold, J. F., Jr., 1978, Relation of Sample Variations to Plate Orientation in 
the Hester— Dendy Plate Sampler, Prog. Fish-Cult., 40: 24-25. 

Hester, F. E., and J. S. Dendy, 1962, A Multiple-Plate Sampler for Aquatic 

Macroinvertebrates, Trans. Am. Fish. Soc., 91: 420-421. 
Hoopes, R. L., 1974, Flooding, as a Result of Hurricane Agnes, and Its Effects on 

a Macrobenthic Community in an Infertile Headwater Stream in Central 

Pennsylvania, L/'mno/. Oceanogr., 19: 853-857. 

Hynes, H. B. N., 1970, Ecology of Running Waters, University of Toronto Press, 

Toronto, Ont. 
Isom, B. G., 1971, Effects of Storage and Mainstream Reservoirs on Benthic 

Macroinvertebrates in the Tennessee Valley, in Reservoir Fisheries and 

Limnology, G. E. Hall (Ed.), Special Publication No. 8, pp. 179-191, 

American Fisheries Society, Bethesda, Md. 

Kimerle, R. A., and N. H. Anderson, 1970, Production and Bioenergetic Role of 
the Midge Glyptotendipes barbipes (Staeger) in a Waste Stabilization 
Lagoon, L/m no/. Oceanogr., 16: 646-659. 

Mason, W. T., 1973, An Introduction to the Identification of Chironomid 
Larvae, Environmental Protection Agency, Report EPA-758-495/1237, 
Environmental Protection Agency, GPO. 

Minshall, G. W., and P. V. Winger, 1968, The Effect of Reduction in Stream 
Flow on Invertebrate Drift, Ecology, 49: 580-582. 

Neel, J. K., 1963, The Impact of Reservoirs, in Limnology in North America, 
D. G. Frey (Ed.), pp. 575-593, University of Wisconsin Press, Madison. 

Paine, G. H., and A. R. Gaufin, 1956, Aquatic Diptera as Indicators of Pollution 
in a Midwestern Stream, Ohio J. Sci., 56: 291-304. 

Parrish, J. H., and J. Wilhm, 1978, Relationship Between Physiochemical 

Conditions and the Distribution of Benthic Macroinvertebrates in Arbuckle 

Lake, Southwest. Nat., 23: 135-144. 
Patterson, C. G., and C. H. Fernando, 1969, The Macro-Invertebrate Coloniza- 
tion of a Small Reservoir in Eastern Canada, Verh. Int. Verein. LimnoL, 17: 

126-136. 
, and C. H. Fernando, 1970, Benthic Fauna Colonization of a New Reservoir 

with Particular Reference to the Chironomidae, J. Fish. Res. Board Can., 27: 

213-232. 
Richerson, P., R. Armstrong, and C. R. Goldman, 1970, Contemporaneous 

Disequilibrium, A New Hypothesis to Explain the Paradox of the Plankton, 

Proc. Nat. Acad. Sci. U. S. A., 67: 1710-1714. 
Siegfried, C. A., and A. W. Knight, 1977, The Effects of Washout in a Sierra 

Foothill Stream, Am. Midi. Nat., 98: 200-206. 
Spence, J. A., and H. B. N. Hynes, 1971, Differences in Benthos Upstream and 

Downstream of an Impoundment, J. Fish. Res. Board Can., 28: 35-43. 

Trotsky, H. M., and R. W. Gregory, 1974, The Effects of Water Flow 
Manipulation Below a Hydroelectric Power Dam on the Bottom Fauna of 
the Upper Kennebec River, Maine, Trans. Am. Fish. Soc, 103: 318-324. 



156 COVICH, SHEPARD, BERGEY, AND CARPENTER 

Ward, J. v., 1976, Effects of Flow Patterns Below Large Dams in Stream 

Benthos: A Review, in Instream Flow Needs Symposium, J. F. Orsborn and 

C. H. AUman (Eds.), Vol. II, pp. 235-253. 
, and R. A. Short, 1978, Macroinvertebrate Community Structure of Four 

Lotic Habitats in Colorado, U. S. A., Verh. Int. Verein. Limnol., in press. 
Waters, T. F., 1964, Recolonization of Denuded Stream Bottom Areas by Drift, 

Trans. Am. Fish. Soc, 93: 311-315. 
- — , 1972, The Drift of Stream Insects, Anni/. Rev. EntomoL, 17: 253-272. 
Weber, C. I., 1973, Macroinvertebrates, in Biological Field and Laboratory 

Methods for Measuring the Quality of Surface Waters and Effluents, Report 

670/4-73-001, pp. 1-38, Environmental Protection Agency, GPO. 
Wilhm, J., 1972, Graphic and Mathematical Analyses of Biotic Communities in 

Polluted Streams, Annu. Rev. EntomoL, 17: 223-252. 
Wolman, M. G., 1971, The Nation's Rivers, Science, 174: 905-918. 



ENVIRONMENTAL IMPLICATIONS 

OF COAL -CONVERSION TECHNOLOGIES: 

ORGANIC CONTAMINANTS 



C. W. GEHRS 

Environmental Sciences Division, Oak Ridge National Laboratory, 

Oak Ridge, Tennessee 



ABSTRACT 

The Department of Energy is currently supporting development of more than 20 
major coal-conversion facilities, with many more in the exploratory and 
predesign stage. All coal-conversion processes utilize pyrolysis (destructive 
heating) to produce hydrocarbons enriched in their hydrogen-to-carbon ratio 
from the parent coal. This entails the use of high temperature, often high 
pressure, and a reducing atmosphere. The products are easier to handle than the 
parent coal and are usable in a greater variety of ways. The organic components 
may reach the aquatic environment, however, from product usage, through 
leaks, or in plant effluents. This paper briefly describes the conversion 
technologies, identifies the types of organic contaminants expected to be 
released, summarizes the literature on environmental effects, and outlines a 
research strategy for addressing the potential environmental ramifications of 
organic contaminants released by coal-conversion technologies. 



The United States contains more tlian 50% of the world's known 
reserves of coal. Although 90% of the total reserves of fossil fuels in 
the United States are coal, only 20% of the energy produced results 
from the use of this fuel. This relatively small reliance on coal as an 
energy source is expected to change drastically over the next few 
decades. Consumption is expected to increase from 600 tonnes of 
coal per year in 1975 to double that amount in the early 1980s and 
potentially to quadruple by the year 2020. Although coal is being 
considered a major source of energy over the next half century, its 
use is not without potential health and environmental ramifications. 
As early as 1750, Sir Percival Pott reported a high incidence of 
scrotal cancer among chimney sweeps in London (Henry, 1946). He 

157 



158 GEHRS 

hypothesized that the disease was associated with particulate material 
clinging to the clothing and the skin of the individuals. Butlin (1892) 
strengthened the hypothesis when he found a much higher rate of 
scrotal cancer in chimney sweeps working in countries consuming 
coal than in countries where wood was the primary fossil fuel. 
Although coal has been used for several centuries, it was not until the 
1950s that a large-scale epidemiological investigation provided 
valuable data (MacMahon, Pugh, and Ipsen, 1960). In 1952, smog over 
London resulted in several thousands of deaths related to 
emphysema. This smog was correlated with coal consumption. 

Unfortunately, quantitative and qualitative determinations of 
the environmental responses to coal are more difficult. Among the 
few exceptions have been several investigations relating acid mine 
drainage to decreases in fish and benthic communities dov^nistream 
from the source (Butler et al., 1973; Huckabee, Goodyear, and Jones, 
1975). The best-known incidences of environmental insult resulting 
from coal consumption on a regional scale is acid precipitation. In 
this respect, the Scandinavian countries offer the greatest docu- 
mentation. Decreases in productivity of forests (Tamm, 1976) and of 
aquatic environments (Schofield, 1976) were associated with 
decreases in the pH of rainfall. The changes in pH of rainfall were 
directly associated with coal consumption in the Ruhr Valley of 
central Europe and in England. Several recent studies in the eastern 
United States have postulated similar responses. For example, 
Shriner, McLaughlin, and Baes (1977) found acid precipitation with 
pH as low as 3.2 in certain episodes in eastern Tennessee. Since 
buffering Capacities of soils and waters in the eastern United States 
are similar to those in the Scandinavian countries, it is feasible that 
problems similar to those identified in the Scandinavian countries 
have Eilready occurred in the eastern United States. 

COAL-COIMVERSIOIM TECHNOLOGIES 

The United States is committed to the development of coal- 
conversion technologies, partly as a result of concern for acid 
precipitation but also from a necessity to produce usable and 
transportable fuels to replace dwindling supplies of crude oil and 
natural gas. Coal conversion is a generic term referring to any of 20 
some processes whereby coal is changed into a liquid, gaseous, or 
solid product relatively free of sulfur and inorganic particulate 
materials. 

To produce usable gaseous or liquid hydrocarbons from coal, we 
must increase the atomic ratio of hydrogen to carbon (Fig. 1), and 



ENVIRONMENTAL IMPLICATIONS 



159 



o 

[- 

o 

I 






PURE CH, 



NATURAL GAS 



LPG 



FUEL OIL 
ORDINARY GASOLINE 

HIGHLY AROMATIC GASOLINE 
CRUDE OIL 

RESIDUAL OIL 



BITUMINOUS COAL 



Fig. 1 Hydrogen-to-carbon ratios for various hydrocarbon fuels. 
(Data from Wiser, 1973.) 



the impurities and potential pollutants present in the feed coal must 
be removed. The hydrogen-to-carbon ratio can be enriched in several 
ways, e.g., by removing the volatile hydrogen-rich organic content 
through pyrolysis, adding extra hydrogen to the carbon contained in 
the coal, or producing CO and H2 from coal and catalytically 
reacting the molecules to form methane and/or higher hydrocarbons 
(Richmond, Reichle, and Gehrs, 1976). In general, the greater the 
enrichment, the higher are the energy costs. 

Although more than 20 processes for converting coal are being 
developed (Energy Research and Development Administration, 
1977), sufficient similarities exist to list only five general types 
(Fig. 2), including two for gasification and three for hque faction. 
Coal gasification can produce either low- or high-Btu gas. Low-Btu 
gasification produces a fuel usable at a stationary source, such as a 
power-generating facility. Processes for converting coal to low-Btu 



160 



GEHRS 



STEAM 
AND AIR- 



GASIFICATION -^ 



LOW-Btu 



CO, Hj, CH^, -^CLEANUP 



Nj, CO2, HjS 



STEAM AND G 



GASIFICATGN 



MEOIUM-Btu 
CG, Hj, CH^, U. 
CGj, HjS 



CLEANUP 



CLEAN GASEOUS FUEL 
[LOW (100-250) Btu] 



CLEAN GASEOUS FUEL 
[MEDIUM (250-550) Btu] 



SUBSTITUE 



METHANATION|-^ NATURAL GAS 

[HIGH (950-1000) Btu| 



COAL 



CHEMICAL 
SYNTHESIS 



.CLEAN LIQUID 
FUELS AND CHEMICALS 



GAS 

_JL_ 



H^S 



CARBOWIZATION/ 
HYDROCARBONIZATIOIM 



CHAR 



OILS 



HYDROTREATING 



CLEAN LIQUID FUEL 



HjS 



SOLVATION 



FILTRATION AND 
SOLVENT REMOVAL 



ASH 

PYRITIC SULFUR 



H^S 



± 



HYDROTREATING 



SYNCRUDE 



SOLIDIFICATION -^ CLEAN SOLID FUEL 



CATALYTIC 
HYDROGENATION 



SEPARATION 



CLEAN LIQUID 



FUEL 



RESIDUUM 



H YD ROTREATINGH" SYNCRUDE 

I 



Fig. 2 Schematic of five basic approaches for converting coal to 
gaseous or liquid fuels. (Data from Richmond, Reichle, and Gehrs, 
1976.) 



fuel are currently being used in several countries. In the United 
States attempts are being made to demonstrate the use of caking 
coals (the major type in the eastern United States) and high 
temperature. In contrast, high-Btu gas can be produced from 
gasification with oxygen and upgrading of the product. This allows 
transport of the gas to diverse sources and ultimate substitution for 
natural gas as a home-heating source. 

Coal liquefaction processes are in the early exploratory stages. 
Three general approaches are being pursued, pyrolysis or carboniza- 
tion, dissolution, and hydrogenation. All rely on high temperature, 
often high pressure, and a reducing atmosphere to produce liquid 



ENVIRONMENTAL IMPLICATIONS 161 

from coal. These are also the three major factors in the production of 
potentially hazardous organic substances during the conversion 
process. The products of coal liquefaction can be used directly as 
boiler fuel in stationary power-generating stations or upgraded and 
refined for use as gasoline or petroleum feedstock. 

The primary' source of contaminants reaching the aquatic 
environment will be aqueous effluents, which will be enriched in 
organic compounds through the process of product hydrotreating 
(Fig. 2). Leachates arising from the ultimate disposal of solid wastes 
can also contaminate water (Gehrs, 1978), as can accidental spills 
and disruption of plant operation. 

No large-scale coal-conversion facilities currently exist in the 
United States, and the smaller units that are now operating do so 
intermittently (and, thus, have atypical effluents) with no or little 
waste treatment. Although these facts pose problems for ecologists 
attempting to determine potential contamination from coal con- 
version, there is also a unique opportunity to aid in developing an 
environmentally acceptable technology(ies) if the ecologist produces 
relevant, timely data. 



HISTORIC DATA ON EIMVIROIMMEIMTAL 
HAZARDS OF COAL CONVERSION 

Although no large coal-conversion facilities are presently 
operating in the United States, Union Carbide operated a 
300-ton/day experimental facility at Institute, W. V., in the early 
1950s. The results of this experiment, which included both medical 
observations and animal testing, are reported in a series of papers by 
Sexton (1960) and Weil and Condra (1960). They suggest the need 
for health and environmental concerns related to coal conversion. 
Despite the use of an aggressive industrial hygiene program, the 
incidence of skin cancer among the approximately 364 workers was 
between 16 and 37 times that reported in the general population 
(Sexton, 1960). 

Whole animal studies on various process and product streams also 
revealed carcinogenic potential (Weil and Condra, 1960). These 
results showed that most of the carcinogenic activity was found in 
the heavy oils (boiling point >260°C). More recently, Bingham 
(1975) found the products of three liquefaction processes currently 
under development to be carcinogenic in animals, and Hueper (1956) 
identified the heavy ends as more active than the light ends. Caution 
must be taken in interpreting these data, however, since the products 



162 GEHRS 

were from small facilities that might not be indicative of commercial 
operations. Nevertheless, sufficient data exist to cause concern. 

Unfortunately, ecological data are lacking with respect to either 
the products or the effluents from the Carbide facility or from the 
surrounding environment. 

The United States, through the Department of Energy, is actively 
supporting the development of more than 20 processes for 
converting coal to liquid, gaseous, or solid fuels. Sufficient data exist 
to necessitate research concerning the possible health and 
environmental consequences of these technologies. Several unique 
characteristics of the level of development of the processes limit the 
types of research that can be conducted (Gehrs and Wells, 1977). 
The small size of the existing facilities, coupled with changes in mode 
of operating, makes conducting field studies around such units 
relatively useless. Furthermore, evaluation of effluents from a 
specific plant is tenuous because of lack of effluent treatment, little 
steady-state operation, and basic questions concerning similarity of 
effluent composition after process scale up. Engineers are unsure that 
a 20,000-ton/day facility will produce the same effluents as a 
scaled-down replica using only 50 tons/day of coal. Finally, the 
chemical composition of effluent streams is extremely complex, with 
hundreds, perhaps thousands, of compounds in each effluent (Shults, 
1976). Developing meaningful data on the ecological hazards of these 
effluents is further complicated by the myriad of potential 
interactions that may occur between the various chemical com- 
pounds (i.e., synergism, antagonism, etc.). These unique attributes of 
currently . existing coal-conversion facilities are not listed here to 
suggest that environmental research is futile; they are presented 
rather to emphasize that developing a meaningful environmental 
research program requires awareness and understanding of these 
limitations and a delineation of the purpose or goals of the research. 
Ecological research related to coal conversion has three major goals: 

1. To aid the development of amenable coal-conversion 
technologies 

2. To develop a data base for assessing the effects of 
coal-conversion technologies on biological communities 

3. To determine the form, source, and potential concentrations 
of trace contaminants that may reach man and other biota from 
environmental releases of coal-conversion effluents 

The approach chosen is determined by the specific goal of the 
research activity. 

The remainder of this paper addresses the scientific approaches 
which have been used to assess the hazards of a particular technology 



ENVIRONMENTAL IMPLICATIONS 163 

and which can be used to address coal conversion. It includes a 
description and a discussion of two major approaches that might be 
taken (including their strengths and weaknesses), a summary of the 
environmental data available on the various organic components of 
coal-conversion effluents, and a suggested approach that we have 
adopted for assessing the environmental implications of coal- 
conversion effluents. 

Historically, the potential environmental hazards of aqueous 
effluents have been evaluated by one of two approaches: (1) 
identifying and subsequently evaluating all the various effluent 
components or (2) testing the whole effluent. 

The first approach produces the data necessary to attain the 
second and third major goals of ecological research. The types of 
research involved in this approach include, in addition to determining 
sublethal effects and the mechanisms of effects, determining the 
ultimate fate of a compound within the environment and the critical 
environmental pathways that lead to exposure of various biota. This 
type of research can be referred to as mechanistic. It is essential in 
developing predictive capabilities. Unfortunately, when the number 
of compounds in an effluent stream is large, identifying all of them 
and testing each individually and in concert becomes too costly and 
time consuming. Such is the case in coal conversion, where perhaps 
thousands of compounds may be present in a particular effluent 
stream (Shults, 1976). 

The second approach, testing the whole effluent, enables us to 
determine the acute toxicity of various effluent streams. Such data 
reveal the relative toxicity of the streams although they do not allow 
determination of what component(s) is(are) most toxic, and this 
information is extremely important in assessing treatability and 
developing control technology. This approach is particularly useful 
for coal conversion where, as mentioned earlier, a great many 
processes are currently under development. Thus, if he can produce 
and deliver relevant data within the time frame the developing 
technology follows, the ecologist has a unique opportunity to help 
determine the ultimate form of- the technology(ies). For example, if 
decisions on whether to pursue a technology are to be made in early 
1980, then ecological-effects data pertaining to the technology must 
be developed before that time. 

The toxic components of complex chemical mixtures (primarily 
petroleum and synthetic petroleum) have been determined in two 
ways. The most common method uses boiling point to separate a 
mixture into smaller, similar fractions. Moore and Dwyer (1974), 
reviewing the literature on the toxicity of aromatic hydrocarbons to 



164 



GEHRS 



SAMPLE 



ORGANIC 



ETHER (OR IVIeClj) 
1/V NaOH 

AQUEOUS 






AQUEOUS 








ORGANIC 






pH 


9 












BASES 
H 




Bib 




BASES 
Et^n 


"2 










"-'2 





FLORISIL 
COLUMN 



HEXANE 



AQUEOUS 



ORGANIC 













1 




SA, 




STRONG 

ACIDS 

Et^O 








STRONG 

ACIDS 

H2O 









HEXANE/BENZENE 
(8/1) 



BENZENE/ETHER 
(4/1) 



METHANOL 



Fig. 3 Separation and fractionation process used to obtain materials 
for environmental testing. (Data from Rubin et al., 1976.) 



aquatic organisms, found an inverse association between toxicity and 
boiling point. Legore (1974) concurred with this relationship and 
suggested that solubility was the primary factor. 

More recent investigations (Gehrs, 1975; Parkhurst, Gehrs, and 
Rubin, 1978) have begun to separate complex mixtures on the basis 
of chemical similarities of compounds (Fig. 3). Rubin et al. (1976) 
adapted this chemical fractionation approach, which was developed 
for evaluating tobacco smoke, to aqueous samples. The scheme 
makes use of the differential solubility of various compounds to 
produce from three to more than 20 semidiscrete and reproducible 
fractions. Mutagenesis testing (Epler et al., 1978) has been used to 
identify the more active of these fractions, with subsequent 
subfractionation and testing allowing eventual determination of 
problematic compounds. 

Parkhurst, Gehrs, and Rubin (1978) used a similar- approach with 
Daphnia magna as the test species. They found (Table 1) that the 
neutral fraction, which comprised only 7% of the soluble materials in 



ENVIRONMENTAL IMPLICATIONS 



165 






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166 GEHRS 

the effluent, contributed 42% of the total toxicity. The acid fraction, 
which was almost 29% of the effluent, contributed about 52% of the 
toxicity. Preliminary characterization work showed naphthalenes, 
phenanthrene, and anthracene in the neutral fraction and phenols 
and cresols in the acid fraction. Such an approach provides useful 
information (identification of active components) to the design 
engineer and control technologist through a process of selective 
elimination. 

Parkhurst, Gehrs, and Rubin (1978) also compared the toxicity 
of an unfractionated effluent wdth a reconstituted effluent (various 
fractions mixed together in same concentration as initial effluent). 
That they found no significant difference in results suggests the 
validity of fractionation and toxicity testing as an initial step in 
evaluating complex chemical mixtures. 

Both approaches have several weaknesses, however. The identities 
and concentrations of the specific compounds being delivered are 
unknown. Interaction* are masked. Hence, developing predictive 
information from these types of studies is not possible. Using 
chemical fractionation rather than boiling point to separate complex 
mixtures appears to have several advantages, the most important 
being that separation is into similar groups (phenolics, aromatics, 
etc.) rather than across groups by boiling point. By combining the 
fractionation— subfractionation scheme with subsequent molecular 
weight profiles, we can obtain a rough estimate of the amount of the 
various classes, as well as the distribution (by weight) within the 
various classes. Using the data developed by Herbes, Southworth, and 
Gehrs (1977) (discussed in the following section) enables initial 
prediction of both potential effects and causative agents. 

Neither of these screening approaches provides the information 
needed to understand mechanisms of effect, however, and, hence, 
neither permits predictive capabilities. Predictions can be made only 
by using specific compounds in studies of transport, fate, and effects. 

LIQUID EFFLUENT COMPOSITION 

No data are available on the exact composition of effluents that 
might be released from coal-conversion facilities. Herbes, 
Southworth, and Gehrs (1977) used data from the coking industry 
as a surrogate to estimate potential effluent components. They 
Eirranged the compounds into five groups on the basis of chemical 
structure and used available data on anticipated concentrations in 
liquid effluents, plus efficacy of waste-water treatment methods, to 
calculate expected concentrations released to the environment. 



ENVIRONMENTAL IMPLICATIONS 



167 



TABLE 2 

CONCENTRATIONS AND WASTE-WATER TREATMENT 

EFFICIENCIES OF MAJOR CONSTITUENTS OF 

COAL-CONVERSION EFFLUENTS* 



Constituent 


Anticipated 

effluent concentration, 

mg/liter 


Waste- water 

treatment removal 

efficiency, % 


E 
in 


xpected levels 
final effluent, 
mg/liter 


Phenols 

Aromatic amines 
Monoaromatic 

hydrocarbons 
Thiophenes 
Polycyclic 

hydrocarbons 


10^ 
10^-10^ 

lo'-io^ 

10' 
10~'-10^ 


99.9+ 
30-50 

90+ 
? 

30-80 






<1 
50-700 

1-10 
1-10 

0.02-0.7 



*Adapted from Herbes, Southvi^orth, and Gehrs, 1977. 

Identities of classes and their anticipated levels in untreated and 
treated wastes are given in Table 2. Phenols will be the predominant 
class of chemicals present in the untreated effluents, with levels as 
high as 6000 mg/liter being measured (Wender, 1975). Chemical 
stripping of most of the phenolics (to retrieve them for use as 
chemical feedstocks) will be followed by biological treatment, which 
will reduce levels to <1 mg/liter. Concentrations of unsubstituted 
aromatic hydrocarbons present in untreated waste waters will be 
hmited primarily by water solubility, with the higher molecular 
weight polycyclic aromatic hydrocarbons constituting lesser 
amounts. Microbial degradation rates of aromatic hydrocarbons are 
inversely related to molecular weight as reflected in the estimated 
removal efficiencies of 90+% and 30 to 80% for monoaromatic and 
polycyclic aromatic hydrocarbons, respectively (Table 2). In- 
corporating nitrogen (aromatic amines) or sulfur (thiophenes) into 
the basic aromatic ring structure tends to increase solubility and 
decrease microbial degradation rates as compared with unsubstituted 
aromatics. Thus these two classes of compounds are expected to 
comprise a significant percentage of the total organics contained in 
treated, aqueous, coal-conversion effluents. 



POTENTIAL TOXICITY OF COAL- 
CONVERSIOIM EFFLUEIMT CLASSES 

The toxicity of phenolics to aquatic life is better defined and 
understood than is the toxicity of other organic classes expected to 



168 GEHRS 

be present in aqueous effluents. Paralysis, loss of equilibrium, 
increased respiration rates, and increased swimming rates are 
responses observed in fish exposed to phenols. Trout and salmon are 
killed by phenol at levels of 3 to 5 mg/liter, but rough fish appear 5 
to 10 times less sensitive (Albersmeyer and Erichsen, 1959). Phenolic 
toxicity is inversely related to dissolved oxygen content 
(Anonymous, 1961) and water hardness (Anonymous, 1962) and 
directly related to water temperature (Bucksteeg, Thiele, and 
Stoltzel, 1955). Available data reveal that fish are more sensitive to 
phenolics than are other aquatic organisms (McKee and Wolf, 1963). 
Although phenolics make up the largest fraction of organics 
anticipated in untreated aqueous wastes, the well-developed 
methodologies for their removal and degradation, coupled with reg- 
ulations regarding quantities that can be released to surface waters, 
suggest that they will not be a significant hazard to aquatic 
environments. 

Data on the toxicity of phenolics to aquatic life are plenti- 
ful, whereas little information on arylamines is available. 
Arylamines constitute the second largest quantity (class) of organics 
in untreated effluents. After treatment, undiluted aqueous effluents 
might contain >50 mg/liter of arylamines, constituting more than 
90% of the organic load arising from this class. Herbes, Southworth, 
and Gehrs (1977), summarizing the available data on acute toxicity 
of arylamines to aquatic life, found a good correlation between 
molecular weight and 96-hr LC5 values. A 40-unit increase in 
molecular weight resulted in a tenfold increase in acute toxicity 
(Fig. 4). Parkhurst (1977) conducted static tests on the fathead 
minnow (Pimephales promelas) for several arylamines in preparation 
for chronic exposure studies. He obtained 96-hr LC5 values of 
~1.5, 24.7, and 7.0 mg/liter for quinoline, 2-methylquinoline, and 
2,6-dimethylquinoline, respectively. 

Chronic effects of arylamines on fish have not been studied, but 
Vasilenko et al. (1972) investigated mammalian responses to sub- 
lethal exposures of aniline. Cyanosis, anemia, and neurological 
disorders were observed in these studies. Epler et al. (1977) found 
that several of the quinolines are mutagenic agents when ad- 
ministered to microbial systems. The relatively high concentrations 
of arylamines expected to be released from coal-conversion facilities 
(as a result of poor treatability) suggest the possibility that acute 
and chronic effects might occur in surrounding environments. 

The unsubstituted aromatic hydrocarbons, in particular the 
polycyclic aromatic hydrocarbons (PAH), have received the greatest 
interest with respect to their occurrence in coal-conversion liquid 



ENVIRONMENTAL IMPLICATIONS 



169 



10-^ 



10-^ 



o 



00 '" 



10^ 




O OBSERVED 
• CALCULATED 



lost sensitive fish 



60 80 100 120 140 160 

MOLECULAR WEIGHT 



180 



200 



Fig. 4 48-hr LC50 values of arylamines to fish. (Data from Herbes, 
Southworth, and Gehrs, 1977.) 



effluents. Members of this class, such as benzo(a)pyrene, are known 
carcinogens, and levels in coal-conversion products are expected to 
be substantially higher than in petroleum products (Shults, 1976). A 
preponderance of the biological activity (with mutagenesis as the test 
parameter) is associated with the PAH fraction of the liquid effluents 
(Epler et al., 1978; Epler et al., 1977; Guerin et al., 1976). 

Data relative to the toxicity of aromatic hydrocarbons to aquatic 
organisms are also sparse. Moore and Dwyer (1974), in a review of 
literature on the effects of oil on marine organisms, generalized that 
the lower the boiling point of the compound the greater the 
toxicity and suggested that the relative toxicity might be associated 



170 GEHRS 

with solubility. Compounds with low boiling points generally are 
more soluble in water and, hence, more available to be transported 
across membranes. Legore (1974) noted a good direct relationship 
between boiling point and relative toxicity, however. He found that 
naphthalene, a diaromatic hydrocarbon, was considerably more toxic 
to oyster larvae (Crassostrea gigas) than benzene, ethylbenzene, 
b-propylbenzene, isopropylbenzene, and ortho-, meta-, and para- 
xylenes, aromatic hydrocarbons with lower boiling points. 
Naphthalenes have been cited as the most toxic water-soluble 
petroleum fraction (Anderson et al., 1974). Concentrations of 
naphthalenes in effluents are expected to be below levels reported to 
cause acute toxicity to adult fish (15 to 25 mg/liter) (McKee and 
Wolf, 1963). 

Chronic effects from aromatic hydrocarbon effluents are a 
distinct possibility. Anderson et al. (1974) found increased 
respiration rates in marine Crustacea exposed to 5 to 10 mg/liter of 
aromatics. Soluble petroleum aromatics (0.01 to 0.1 mg/liter) 
disrupted social behavior in the lobster (Homarus americanus) and 
altered attraction of the snail (Nassarius obsoletus) to food at 
concentrations as low as 0.1 /ig/liter (Bresch et al., 1972; Jacobson 
and Boylan, 1973). 

Data on the toxicity of thiophenes (sulfur-substituted aro- 
matic hydrocarbons) are almost nonexistent. Thiophene is 33% 
more toxic to sunfish than benzene (Jones, 1964), and thiophene 
and 2-methylthiophene are more toxic to mammals than their 
benzene analogs. Since we can expect substantial quantities of 
thiophenes in aqueous effluents from coal-conversion facilities, 
investigations into their ecological impacts are required. 

Summarizing the data on the toxicity of the various effluent 
classes leads to several generalities. First, insufficient data are 
available to predict the potential for acute toxicity which might 
result from the various effluent chemical classes, except phenols, and 
the data that are available have resulted primarily from the testing of 
specific compounds, not "real world" effluent mixtures. Second, the 
information base for evaluating potential chronic effects is an abyss. 
If we are willing to accept the inherent weaknesses of the existing 
data base (it is sparse, does not evaluate interactions, etc.), we find 
that two apparently opposite generalities have been formulated with 
respect to toxicity. Moore and Dwyer (1974) suggested that the 
toxicity of aromatic hydrocarbons is inversely associated with boiling 
point and, hence, with solubility. Herbes, Southworth, and Gehrs 
(1977) hypothesized a direct correlation between molecular weight 
(which relates in a general manner to boiling point and solubility) 
and acute toxicity within each of the various classes of compounds 



ENVIRONMENTAL IMPLICATIONS 



171 



10" 



10-^ 



0) 



10^ 



10' 



10^ 



, 48-hr LC50 

, Solubility 



\ 



\ 



\ 



\ 



\ 



\ 



\ 



\ 



\ 



\ 



\ 



60 80 100 120 140 

MOLECULAR WEIGHT 



160 



180 



Fig. 5 Theoretical solubility and LC5 values plotted against 
molecular weights for a series of aromatic hydrocarbons. 



potentially present in coal-conversion effluents. This divergence in 
interpretation might be explained if solubility becomes the limiting 
factor in reaching concentrations in water necessary for toxicity to 
be expressed. This is show^n in Fig. 5, a theoretical plot of solubility 
and LC50 vs. molecular weight. To the right of the junction of the two 
curves, the materials would not be toxic because sufficient quantities 
would not be in solution. The finding of the preponderance of 
toxicity in materials with low boiling points (which transects all the 
chemical classes) quite possibly results from insufficient quantities in 
the water columns. 

Certain flaws or, more appropriately, certain real -world 
phenomena detract from this oversimplification. These include: 

1. Differential sensitivity of biological systems to the same 
molecule 

2. Differential response of biological systems to various isomers 
of the same compound 

3. Interactive phenomena, both toxicological and physio- 
chemical, already alluded to 

4. Transport and transformation of materials in the aquatic 
environment 

For example, quinoline, an aromatic amine, has an LCg of 1.5 
mg/liter in the fathead minnow and 17.5 mg/liter in the bluegill 



172 GEHRS 

sunfish (Parkhurst, Gehrs, and Rubin, 1978), and benzo(a)pyrene is a 
potent mutagen and carcinogen, whereas benzo(e)pyrene is virtually 
inactive. 

The complexity of developing a program for evaluating the 
environmental hazards of coal conversion is obvious. It is apparent 
that such a program should incorporate toxicity screening of 
effluents and their chemical fractions, but it is less apparent how to 
develop an approach that will produce the data necessary for 
predictive capabilities (research using individual compounds). 

Generating a manageable approach to such a large number of 
contaminants requires adopting the same philosophy that produced 
the screening approach, i.e., look first for the greatest commonalities 
among the various compounds. This allows us to arrange compounds 
in groups that are most similar in certain parameters (e.g., structure). 

Herbes, Southworth, and Gehrs (1977), adopting such a 
philosophy and arranging the compounds according to structure and 
molecular weight, were able to conduct research of a predictive 
nature for all coal conversion effluents by using approximately 30 
compounds rather than the thousands present. This is clearly a more 
manageable number. 

SUMMARY 

In summary, the term coal conversion refers to any of a group of 
processes designed to produce liquid, gaseous, or clean-burning 
solid fuels from coal. All the processes use high temperature and high 
pressure (often in a reducing atmosphere) to produce the fuel and 
give rise to a myriad of organics that may ultimately find their way 
into aquatic environments. Hundreds, perhaps thousands, of 
individual compounds may be present in aqueous effluents. 
Investigation of the potential for environmental impact of these 
effluents can be approached in one of two ways, each of which 
possesses weaknesses. The two approaches are testing the whole 
complex effluent or testing individual compounds. The first provides 
rapid data on toxicity but has little value for predictive purposes 
since neither the identities nor concentrations of materials are known. 
The second, testing individual compounds, provides the necessary 
data for developing predictions. To study all the various compounds 
(including isomers of each) and all their combinations with respect to 
effects, transport, transformation, fate, and food chain kinetics and 
including all the environmental factors that might affect these 
parameters would require a substantial percentage of the Gross 
National Product and more time than is available. Obviously the 



ENVIRONMENTAL IMPLICATIONS 173 

necessary tactic is to use certain components from each of the two 
approaches. 

Testing complex mixtures, coupled with chemical fractionation, 
allows us to determine acute toxicity and also to identify active 
components of the effluent. Investigations of individual compounds 
can be made manageable by grouping the compounds on the basis of 
chemical structure. 

ACKNOWLEDGMENT 

The research reported here was sponsored by the Division of 
Biomedical and Environmental Research, U. S. Department of 
Energy, under contract W-7405-eng-26 with Union Carbide Corpora- 
tion. Environmental Sciences Division Publication No. 1194, Oak 
Ridge National Laboratory. 

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ENVIRONMENTAL IMPLICATIONS 175 

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Vasilenko, N. M., et al., 1972, Toxic Effects of Aniline, Vrach. Delo, 1972(8): 

132-134 (In Russian). 
Weil, C. S., and N. I. Condra, 1960, The Hazards to Health in the Hydrogenation 

of Coal. II. Carcinogenic Effect of Materials on the Skin of Mice, Arch. 

Environ. Health, 1: 187-193. 
Wender, I., 1975, Quarterly Technical Progress Report, ERDA Report PERC/ 

QTR-75/1, Pittsburgh Energy Research Center. 
Wiser, W. H., 1973, Coal Characteristics and Coal Conversion Processes, 

Pennsylvania State University, Oct. 29 — Nov. 3. 



THE STREAM ENVIRONMENT 

AND MACROINVERTEBRATE COMMUNITIES: 

CONTRASTING EFFECTS OF MINING 

IN COLORADO AND THE EASTERN 

UNITED STATES 



JAMES V. WARD,* STEVEN P. CANTON,* and LAWRENCE J. GRAYt 
*Department of Zoology and Entomology, Colorado State University, 
Fort Collins, Colorado, and tDepartment of Zoology, Arizona State University, 
Tempe, Arizona 



ABSTRACT 

Studies were conducted year-round on a Colorado stream that receives drainage 
from a coal mine to assess the potential response of macroinvertebrate 
communities to mining activities in the western United States. Species 
composition, diversity, and standing crop were examined, and results are 
compared with similar studies conducted in eastern states. Generally low values 
of sulfate and iron, highly-buffered waters, and low levels of toxic substances 
characterized the Colorado stream and applied, in general, to many streams in 
the western energy-development region. Moderate inputs of soluble salts 
increased ' abundance of macroinvertebrates without significant changes in 
community structure or other discernible indications of stressed conditions. This 
is attributed to the relatively soft waters above the mine and the protection 
afforded by a buffer strip between the mine spoils and the stream. Increased 
salinity, sedimentation, and water depletion are major problems, but, with 
proper environmental considerations, mining in the West may not have the 
severe impacts on stream biota which characterize many eastern mining regions. 



The western United States has vast expanses of coal. Kauffman and 
Schaefer (1977) indicated that "70 percent of all known, high-grade, 
low-sulphur, strippable coal deposits are located in this area, as are all 
of the country's major high-grade oil shale reserves." They estimated 
that the next 10 to 25 years will be a developmental period for the 
energy resources of the western United States. 

Coal-bearing strata underlie 28% of the state of Colorado 
(Landis, 1964). Coal deposits are of the Upper Cretaceous and early 
Tertiary periods, as are the majority of surface mineable coal reserves 

176 



THE STREAM ENVIRONMENT 177 

of the Rocky Mountains and the Northern Great Plains (McWhorter, 
Skogerboe, and Skogerboe, 1975). 

The ecological impacts on aquatic ecosystems of mining and 
processing activities differ in many ways in the West from those in 
mining regions of the eastern states. Yet, although there is a plethora 
of literature documenting the effects of mining on aquatic biota in 
the eastern United States, there are relatively few data on problems 
associated with mining and resulting effects on aquatic organisms in 
the West. 

A year-round study was conducted on a Colorado stream that 
receives drainage from a strip coal mine. The objectives were (1) to 
compare macroinvertebrate communities and environmental condi- 
tions at stream locations differentially affected by mining activities 
and (2) to contrast the results with those of studies of eastern 
streams receiving coal-mine drainage. 

METHODS AND SITE DESCRIPTION 

Trout Creek, in the Upper Colorado River Basin of northwestern 
Colorado (Fig. 1), receives groundwater and surface runoff from a 
strip coal mine (Edna Mine). The area of the watershed above and 
including the mine totals approximately 1.1 x 10"* ha; the area of 
mine spoils (597 ha) is slightly more than 4% of the total watershed 
area upstream from the mine (McWhorter, Skogerboe, and 
Skogerboe, 1975). The upper portion of the basin, which lies in 
Routt National Forest, is well vegetated with aspen and conifers. The 
middle portion of the watershed is a mixture of forests and farmland. 
Lower reaches are more xeric, with sagebrush and other shrubs and 
grasses predominating. Agricultural practices (primarily grazing) 
variously affect middle and especially lower portions of the basin. At 
elevations ranging from 2160 to 2100 m, the stream is bordered on 
the east by the Edna Mine. Trout Creek progressively flows past 
spoils from mining about 30 years ago, spoils 20 to 30 years old, and 
an area of current mining activity. 

Sampling stations on Trout Creek were located on rubble riffles 
above, adjacent to, and below the mine spoils at sites from which 
water chemistry data had been collected in a previous study 
(McWhorter, Skogerboe, and Skogerboe, 1975). An additional sam- 
pling station (TC-1) was established upstream from a mine shaft (see 
Fig. 1) even though the shaft is horizontal and there was no evidence 
of seepage entering the stream. 

Macroinvertebrates were sampled monthly from July 1975 
through June 1976. High water or inclement weather precluded 



178 



WARD, CANTON, AND GRAY 



TROUT 
CREEK 



COLORADO 




km 



Fig. 1 Map of Trout Creek showing sampling stations and mine 
spoils. Station TC-7 is about 3 km downstream from TC-6. 



sampling at one or two sites on three occasions. A 929-cm^ Surber 
sampler with net mesh apertures of ~700 /jm was used to take five or 
more replicate samples at each site. The organisms in each sample 
were enumerated separately, and numbers were pooled for diversity 
index calculations. The Shannon— Weaver index with logarithms to 
base 2 (bits per individual) was used to calculate macroinvertebrate 
diversity. Analysis of variance (f-distribution) was calculated on log 
transformations of raw density data to allow use of parametric tests 
(Elliott, 1973). 

RESULTS 



A total of 88 macroinvertebrate taxa were identified from the 
seven sampling stations on Trout Creek. A list of taxa, detailed 
methods, and site descriptions are given in Canton and Ward (1978). 



THE STREAM ENVIRONMENT 



179 



8000 



6000 



c/^ 4000 — 



< 

o 

O 



2000 




TC-1 TC-2 TC-3 TC-4 TC-5 TC-6 TC-7 
SAMPLING STATIONS 



Fig. 2 Downstream changes in macroinvertebrate annual mean 
density and biomass values on Trout Creek. 



Rather than decreasing, as expected, density and biomass 
exhibited a general increase downstream (Fig. 2). Differences between 
stations were significant (P < 0.01) for total numbers of organisms 
collected during the study but were not significant on certain 
collecting dates (June, July, and January). Significant differences 
(P < 0.01) between dates reflect periods of emergence and recruit- 
ment, effects of spring runoff, and onset of winter conditions. 

Although density increased downstream, similar numbers of taxa 
occurred at all stations (Fig. 3). Shannon— Weaver index values also 
indicated no longitudinal pattern. Median values at all stations were 
between 3.0 and 4.0, the "normal" range defined by Wilhm (1970). 

Five orders of aquatic insects (Trichoptera, Diptera, Ephemer- 
optera, Plecoptera, and Coleoptera) comprised well over 90% of the 
mean annual density and biomass of macroinvertebrates at all 
sampling stations. Eight taxa at each station represented 55 to 83% 
of the density, and most of these taxa were among the most 
abundant at many stations. The mayfly Baetis was among the top 
eight at all stations. Others abundant at most stations included the 



180 



WARD, CANTON, AND GRAY 




TC-3 TC-4 TC-5 
SAMPLING STATIONS 



TC-6 



Fig. 3 Annual range of Shannon — Weaver index values ( I ) and the 
mean number of macroinvertebrate taxa per collection date (• — •) 
for sampling stations on Trout Creek. 



caddisflies Agapetus and Brachycentrus, the mayfly Rhithrogena, 
and the elmid beetle Optioseruus. Caddisflies were the most abun- 
dant order by density at all Trout Creek sampling stations (at TC-7 
trichopterans and dipterans each comprised 33% of the mean 
density) and also comprised the largest biomass (at TC-2 trichop- 
terans and ephemeropterans each comprised 28% of the mean 
biomass). Plecopterans comprised less than 10% of the macroinverte- 
brate numbers but were much more important gravimetrically. The 
reverse was true for coleopterans, which were primarily small riffle 
beetles. The relative importance of the five insect orders was similar 
at all stations and exhibited no longitudinal trend. Other orders of 
insects and noninsects were generally rare, and differences in their 
distribution patterns cannot be reliably relegated to anything except 
the sampling inadequacies inherent in studies of rocky streams 
(Hynes, 1970). Even at the generic and specific level, many of the 
common organisms were widely distributed. 



DISCUSSION 

Streams of the eastern United States which receive acid mine 
drainage are characterized by lowered diversity and density and 



THE STREAM ENVIRONMENT 181 

greatly modified macroinvertebrate species composition (Appala- 
ciiian Regional Commission, 1969; Roback and Richardson, 1969; 
Dills and Rogers, 1974; Herricks and Cairns, 1974). 

Herricks and Cairns (1974) studied macroinvertebrate communi- 
ties at locations above and below acid mine drainage in Pennsylvania 
streams (Table 1). Control stations v^^ere dominated by ephemerop- 
terans, plecopterans, and odonates; dipterans (mainly chironomids) 
and Hydropsyche were the common organisms at a station receiving 
acid mine drainage. 

In an Alabama stream an isopod (Lirceus) comprised 43% of the 
benthos at unpolluted stations, whereas acid stations were dominated 
by chironomids, ceratopogonids and megalopterans (Dills and 
Rogers, 1974). Reduced density and diversity were reported for 
polluted stations (Table 1). 

These eastern studies contrast sharply with our study of Trout 
Creek. Despite the fact that coal strip mining began about 30 years 
ago and is presently being conducted along the creek, macroinverte- 
brate communities adjacent to and below the mine spoils indicated 
no discernible detrimental effect from mining activities. The number 
of taxa was similar above, adjacent to, and below the mine. Standing 
crop increased rather than decreased downstream, and taxonomic 
composition was remarkably similar throughout the stream section 
studied. Shannon— Weaver index values gave no indication of a 
stressed macroinvertebrate community at any of the sites on Trout 
Creek. 

Chemical Conditions and Macroinvertebrates 

Wentz (1974), referring to the effects of mine drainage on the 
water quality of streams in Colorado, indicated that "approximately 
450 miles (724 kilometers) of streams in 25 different areas are 
adversely affected by metal-mine drainage. Coal-mine drainage is not 
a problem, apparently because of the low sulfur content of Colorado 
coal." 

Table 2 compares the water quality of Trout Creek with criteria 
for acid mine drainage. In streams in western energy-development 
areas, acidity is typically undetectable, and pH values generally range 
from 6.5 to 8.5, with over 85% of all pH values falling between 7.0 
and 8.0 (Skogerboe, 1976). Stream waters are well buffered, and 
major inputs of acid or base would be required to shift the pH one or 
more units. The chemoautotrophic bacteria, which greatly speed the 
production of sulfuric acid and ferric hydroxide, are effective only at 
low pH, whereas bacteria that oxidize ferrous iron at higher pH are 
relatively unimportant in acid formation (Wentz, 1974). 



182 



WARD, CANTON, AND GRAY 



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THE STREAM ENVIRONMENT 183 



TABLE 2 



CRITERIA FOR ACID MINE DRAINAGE 
COMPARED WITH WATER QUALITY OF TROUT CREEK 



Water quality 


Acid mine 


Trout Creek ij: 


characteristic* 


drednagef 


TC-3 




TC-6 


Acidity 


>3.0 


0.0 




0.0 


Alkalinity 





89.2 (41-166) 




102.4 (24-205) 


pH 


<6.0 


7.6(6.5-8.2) 




7.6 (6.8-8.3) 


Iron 


>0.5 


0.17 (<0.02-l 


.10) 


0.12(0.04-0.54) 


Sulfate 


>250 


10.6 (5-20) 




80.6(12-250) 


Total hardness 


>250 


115.9(43-270) 




169.3 (67-418) 


Suspended solids 


>250 


5.3 (0-24) 




9.8 (0-62) 


Dissolved solids 


>500 


110.4 (40—176) 




223.0(52-509) 



*A11 values except pH are in milligrams per liter. 
fHerricks and Cairns (1974). 

tSingle values are annual means; ranges at sites above and below mine 
spoils are in parentheses. 

Much of the stress on macro invertebrates associated with acid 
mine drainage in eastern streams can be attributed to low pH, per se, 
although ferric hydroxide precipitation and heavy metals also have 
adverse effects. Napier and Hummon (1976) found that mayflies did 
not occur in streams which had otherwise recovered from acid mine 
drainage but which maintained low pH values. They concluded that 
low pH was primarily responsible for the elimination of mayflies. 

From the results of a survey of Colorado sites receiving drainage 
from mines, Wentz (1974) tabulated the percentage of sample sites 
where concentrations of 15 heavy metals and pH exceeded stream 
criteria for fish and other aquatic organisms (criteria were drawn 
from various cited sources). Only one station associated with coal 
mining, the drain from an adit of an abandoned mine, exceeded these 
criteria and only for iron and manganese. Wentz found no macro- 
invertebrates in the drain, the bottom of which had a bright-orange 
coating. 

Concentrations of most heavy metals are low in Trout Creek and 
in western energy-development areas generally (Skogerboe, 1976). 
The solubilities of many heavy metals associated with acid produc- 
tion processes in eastern mining areas are limited by hydroxide or 
carbonate precipitation processes. An examination of the solubility 
equilibria of metals showed that most are least soluble from pH 7.0 
to 8.0, the range within which over 85% of all observed pH values in 
western energy areas lie (Skogerboe, 1976). The well-buffered nature 



184 WARD, CANTON, AND GRAY 



TABLE 3 



IONIC COMPOSITION (mg/liter), 

SPECIFIC CONDUCTANCE, AND 

pH OF EDNA MINE SPOILS 



Ion, mg/liter 




Edna 


Mine spoils* 


sol"- 






820 


Na+ 






41 


Mg^^ 






270 


Ca2 + 






52 


cr 






15 


HC07 






280 


K^ 






24 


Specific conduc 


:tance, 






/jmhos/cm 






3967 


pH 






8.2 



* Saturated paste analyses (MeWhorter, 
Skogerboe, and Skogerboe, 1975). 



of most western streams would require major inputs of acid or base 
to change the solubilities of most metals appreciably. In addition, 
Cairns (1976) stressed that hard, well-buffered waters reduce the 
adverse effects to biota of many toxic materials. 

There is some evidence that many elements contained in the 
mine spoils do not reach Trout Creek in large quantities. Sediment 
from runoff channels in the mine contained higher concentrations of 
all heavy metals analyzed, except mercury, than did sediment from 
Trout Creek (Skogerboe, 1976); this "implies that those elements 
contained in the runoff are largely removed from solution, perhaps 
by precipitation, before the runoff reaches the creek." The presence 
of a strip of unmined land between the mine spoils and the creek 
may considerably reduce the input of potentially toxic substances to 
the stream. 

Soluble salts from the overburden are considered by some to be 
the most significant potential pollutant of streams from strip mines in 
the West (MeWhorter, Skogerboe, and Skogerboe, 1975). Edna Mine 
spoils contain large amounts of certain ions (Table 3). Precipitation 
in more mesic regions is sufficient to leach out soluble salts as they 
form, but, in the arid and semiarid regions of the western United 
States, only the top few centimeters of soil are adequately leached. 
Surface mining exposes fresh surfaces and increases leaching of 
soluble salts; this results in an approximate doubling of total 



THE STREAM ENVIRONMENT 185 

dissolved solids in Trout Creek (Table 2). Increases in hardness and 
soluble salts may, within limits, result in increased productivity, 
especially in western streams, which often originate in mountainous 
regions of insoluble crystalline rock. Downstream increases in 
specific conductance in Trout Creek were correlated with increases in 
the density (r = 0.9) and biomass (r = 0.8) of macroinvertebrates. 

Sedimentation and Macroinvertebrates 

Coal-mine drainage often results in the production of ferric 
hydroxide, which is insoluble and forms a yellow— orange precipitate 
on the stream substrate (Wentz, 1974). This did not occur in Trout 
Creek, which had relatively low iron concentrations. Inorganic 
sediment from erosion of surfaces exposed by mining may also cover 
the substrate. Apart from any toxic effects, sedimentation decreases 
substrate heterogeneity, fills interstices with silt, may severely reduce 
algal populations, and directly affects the benthos (Ward, 1976). The 
presence of a strip of unmined land between the mine spoils and 
Trout Creek, in combination with the semiarid climate of the region, 
is apparently largely responsible for the maintenance of a heteroge- 
neous and relatively silt-free substrate. 

Climate, Groundwater, and Stream Flow 

Climatic differences between western and eastern mining regions 
undoubtedly modify effects on stream ecosystems. Differences in 
leaching efficiency between xeric and mesic regions have already 
been referred to. Herricks and Cairns (1974) stressed the importance 
of relationships between stream flow and mine drainage. The 
apparent lack of adverse effects of Edna Mine drainage on Trout 
Creek macroinvertebrates may result in part from a hydrologic 
situation in which most substances enter the stream during a 
relatively short period associated with high stream flow. For 
example, over 80% of the total salt input from the mine occurs 
during April, May, and early June. 

In summary, effects of mining on stream ecosystems in the 
western United States are different in many ways from those in 
eastern states. Acid mine drainage and ferric hydroxide precipitates 
are rarely associated with coal mines in western energy-development 
areas, partly because of the low sulfate content of western coal. 
Alkaline, highly buffered waters prevent the formation of acid 
conditions, even where sulfate values 2ire high, and reduce the 
solubihty of heavy metals. Water depletion, sedimentation, and 
increased salinity are the major potential problems associated with 
western mining. 



186 WARD, CANTON, AND GRAY 

The Trout Creek study shows that mining in the West need not 
be as seriously damaging to the stream ecosystem as mining in the 
eastern states. Although the Trout Creek basin had been mined 
for about 30 years, macroinvertebrates exhibited no definitive 
indications of stressed conditions in the stream section studied. 
Although Edna Mine spoils are extensive, we should emphasize that 
the headwaters of Trout Creek provide a source of organisms for 
recolonization of affected areas downstream. The mine spoils 
adjacent to Trout Creek are 30 to over 100 m from the stream 
channel. This buffer zone between the mine spoils and the stream 
apparently reduces sediment input and the quantities of other 
potentially harmful substances. It is postulated that physical, 
chemical, and biological processes occurring in the soil of the buffer 
zone reduce the toxicity of certain substances and retard the 
movement of potentially harmful substances into the stream channel. 
This is an area of research which merits further investigation. 

ACKNOWLEDGMEIMTS 

We wish to thank R. K. Skogerboe, Department of Chemistry, 
Colorado State University, for suggestions regarding the manuscript 
and for supplying unpublished chemical data. This research was 
funded in part by the U. S. Environmental Protection Agency, 
Environmental Research Laboratory, Duluth, Minn. (Research Grant 
No. R803950), and by a National Science Foundation Energy 
Traineeship awarded to S. P. Canton. This paper is based in part on a 
thesis submitted by S. P. Canton in partial fulfillment of require- 
ments for a M.S. degree in zoology at Colorado State University. The 
Natural Resource Ecology Laboratory, Colorado State University, 
provided support facilities and coordinated research activities. 

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Washington, D.C. 
Cairns, John, Jr., 1976, Heated Waste-Water Effects on Aquatic Ecosystems, in 

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1975, G. W. Esch and R. W. McFarlane (Eds.), pp. 32-38, CONF-750425, 

NTIS. 
Canton, S. P., and J. V. Ward, 1978, Environmental Effects of Western Energy 

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Dills, G., and D. T. Rogers, Jr., 1974, Macroinvertebrate Community Structure 

as an Indicator of Acid Mine Pollution, Environ. Pollut. (London), 6: 

239-262. 



THE STREAM ENVIRONMENT 187 

Elliott, J. M., 1973, Some Methods for the Statistical Analysis of Samples of 
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Herricks, E. E., and J. Cairns, Jr., 1974, Rehabilitation of Streams Receiving 
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Kauffman, K. O., and R. R. Schaefer, 1977, Water for Energy Western United 

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McWhorter, D. B., R. K. Skogerboe, and G. V. Skogerboe, 1975, Water Quality 
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Napier, S., Jr., and W. D. Hummon, 1976, Survival of Mayfly Larvae Under Mine 
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Roback, S. S., and J. W. Richardson, 1969, The Effects of Acid Mine Drainage 
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Ward, J. v., 1976, Effects of Flow Patterns Below Large Dams on Stream 
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Id., J. F. Orsborn and C. H. Allman (Eds.), pp. 235-253, American Fisheries 

Society, Bethesda, Md. 
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Colorado, 1971—72, Colorado Water Resources Circular No. 21, Colorado 

Water Conservation Board, Denver. 
Wilhm, J., 1970, Range of Diversity Index in Benthic Macroinvertebrate 

Populations, J. Water Pollut. Control Fed., 42: R221-R224. 



MEIOFAUNAL ABUNDANCE IN SANDBARS 
OF ACID MINE POLLUTED, RECLAIMED, 
AND UNPOLLUTED STREAMS 
IN SOUTHEASTERN OHIO 



WILLIAM D. HUMMON, WAYNE A. EVANS, MARGARET R. HUMMON, 

FRANCIS G. DOHERTY, ROBERT H. WAINBERG, AND WILLIAM S. 

STANLEY 

Department of Zoology and Microbiology, Ohio University, Athens, Ohio 



ABSTRACT 

In October and November 1976, a collection was made at each of tv^^o sites 
along seven streams in Athens, Vinton, and Hocking counties, Ohio, during a 
period of stable weather. Streams were chosen to include watersheds with no 
mining and with varying histories of mining and reclamation. Meiofaunal 
sampling followed a regular pattern. Four stations were sampled along a 
cross-stream transect; four depths were sampled at each station, and triplicate 
subsamples were taken at each depth, yielding 48 2.7-cm"' sediment subsamples 
per site collected. Physical— chemical parameters measured for stream and 
sediment at each site included temperature, pH, conductivity, carbonate 
alkalinity, sulfates, calcium and total hardness, manganese, iron, dissolved 
oxygen, biochemical oxygen demand, and stream flow. Meiofauna were 
narcotized with 1% MgCl2, extracted by multiple decantation, and tallied and 
identified to major taxon with multiple whole Sedgwick— Rafter cell counts. 

The number of major taxa recovered at the 14 sites ranged from 3 to 11; 
geometric mean abundance of total meiofauna per coring station expressed as 
organisms per 10 square centimeters of surface ranged from 21 to 443. Diptera, 
one of 16 taxa observed, total numbers of taxa present, and geometric means of 
total meiofauna were significantly correlated (negatively) with values for 
compensated noncarbonate conductivity from the 14 sites. 

In a dendrogram of Sh' similarity analysis, the unpolluted streams along 
with several sites with a past history of mining formed an eight-site complex, 
showing H' taxon diversity values of 1.6 to 2.8 with 40 to 80% in common. The 
remaining sites, all with a past history of mining, formed two groups. One group 
of four sites, dominated by rotifers, showed H' values of 1.2 to 1.6 wath 36 to 
52% in common. The second group of two sites, dominated by nematodes, 
showed H values of 1.3 to 1.5 with 46% in common. 

188 



MEIOFAUNAL ABUNDANCE 189 

Streams and other waters of areas with a history of mining and with 
sulfur-rich coal are often polluted with acid mine drainage. This 
pollutant continues to form and be washed into streams long after 
mining has ceased and may affect the fauna of such waters after the 
area has been vegetatively reclaimed (Napier and Hummon, 1976). 
Iron pyrite (FeS), present in the coal, is oxidized in the presence of 
water and oxygen and, catalyzed by bacteria, forms sulfuric acid. In 
addition to exhibiting lowered pH, waters affected by acid mine 
pollution contain various dissolved minerals, including iron, alumin- 
ium, zinc, copper, and manganese (Hill, 1968;Massey and Barnhisel, 
1972) and are characterized by high conductivity and an absence of 
buffering capacity (Parsons, 1968; Dills and Rogers, 1974; Faucon 
and Hummon, 1976). 

The effect of acid mine drainage on the occurrence of stream 
macroinvertebrates is fairly well documented (Parsons, 1968; Roback 
and Richardson, 1969; Warner, 1971; Koryak, Shapiro, and Sykora, 
1972; Nichols and Bulow, 1973; Dills and Rogers, 1974; Napier and 
Hummon, 1976). However, relatively little attention has been given 
to the effect of mine acid on stream microinvertebrates or meiofauna 
(Lackey, 1939; Hummon, 1977). 

The single best measure of the degree of acid mine pollution in a 
natural body of water and of the effect of this pollution on flora or 
fauna has generally been considered to be pH (Parsons, 1956; 
Bennett, 1969; Warner, 1971). But recently it has been suggested 
that total conductivity (Dills and Rogers, 1974) or certain combina- 
tions of conductivity and carbonate concentration (Faucon £ind 
Hummon, 1976) may be critical. 

This paper contains results from a continuing study of the 
relationship between natural and acid mine-polluted water and 
invertebrate fauna, particularly the meiofauna. Our report (1) intro- 
duces results on the abundance and taxon diversity of meiofaunal 
elements in natural and polluted stream ecosystems and (2) develops 
preliminary criteria by which the state of acid mine stream pollution 
and recovery can be assessed with respect to its meiobenthic fauna. 

MATERIAL AND METHODS 

During an extended period of stable, fair weather, 14 sites, two 
each along seven streams in Athens, Vinton, and Hocking counties, 
Ohio (Table 1), were sampled once over a month-long period 
(Oct. 23 to Nov. 20, 1976). The streams were chosen to represent a 
variety of conditions. Raccoon Creek and Sandy Run are highly acid 
mine-polluted streams. Minkers Run, subject of stripping and 



190 



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MEIOFAUNAL ABUNDANCE 191 

vegetative reclamation in the 1950s, is a chronically acid mine- 
polluted stream (Napier and Hummon, 1976), particularly the lower 
site, which is located just below an old, but extensive, tipple zone. 
Long Run is situated in an area in which there was some stripping in 
the 1950s; judging by its macrofauna (Feldner and Stanley, 1976), 
however, the stream may have recovered from some of the adverse 
effects of acid mine effluents. The unnamed stream adjacent to Tick 
Ridge receives water from a 13- to 14-ha area that was stripped during 
the 1970s and reclaimed according to current practices. Margaret 
Creek and Strouds Run are streams in watersheds with no history of 
coal mining. Five of the seven streams were sampled at upstream 
(upper) and downstream (lower) sites. For the two other streams, 
Margaret Creek and Strouds Run, sites were chosen on different 
branches. 

Both sites for a given stream were collected on the same day. 
Sites were located at least 400 m, usually 1 km or more, apart. Each 
site was sampled for meiofauna following a regular pattern. A 
transect was oriented perpendicular to stream flow, running from an 
emergent sand bar into deeper water covering submerged but 
continuous sandy substratum. Samples were taken from four coring 
stations, whose surface elevations were located at +2 cm (bar 
station), —3 cm (stream-edge station), and —10 cm and —20 cm 
(midstream stations) with respect to the stream surface. 

Four sediment cores were taken at each coring station. A 20-cm^ 
disposable plastic syringe (2.68-cm^ surface) with its tip cut off 
operated as a suction corer. Three sediment cores were fractioned, 
and the to 1, 1 to 2, 3 to 4, and 6 to 7-cm core depths were used 
for faunistic analysis. Thus there were 4 stations x 4 sample depths 
per station, or 16 samples, x 3 subsample replicates per sample, or a 
total of 48 subsamples. Replicates from eight samples were treated 
individually as splits (8x3 = 24), and those from the other eight 
samples were combined and treated as grouped subsamples 
(8 X 1 = 8). This reduced by one-third the number of entities to be 
examined. Selection of those samples in which subsample replicates 
would be grouped was made by a stratified random process, such 
that two of four samples per station and two of four samples per 
depth would be included, based on a 4 x 4 matrix of stations and 
depths. The fourth sediment core was reserved for sedimentary 
analysis. 

Physical— chemical data were also collected from the stream and 
from interstitial water allowed to seep into a hole dug in the sandbar 
adjacent to the stream. Air, stream water, sediment surface, and 
interstitial water temperatures were measured with a laboratory 



192 HUMMON et al. 

thermometer. Light transmission was measured in stream water with 
a Beckman EV-4 Envirotrans meter. Conductivity and pH were 
measured in stream and interstitial water with YSI 33 S-T-C and 
Orion 404 Specific Ion meters. Water samples from both stream and 
hole were placed in plastic bottles and BOD (biochemical oxygen 
demand) bottles for further chemical analysis in the laboratory. The 
azide modification of the Winkler technique was used on site for 
preliminary fixation of dissolved oxygen, A tvdg, meterstick, and 
stopwatch were used to measure flow rates in shallow zones having 
rather even depths, A tape and level were used to make a 
bank-to-bank stream and channel profile along the transect line. 

Samples were returned to the laboratory within 3 hr of 
collection, where fauna were narcotized with 1% MgCl2 and 
extracted from one jar into an identical jar by multiple decantation, 
using 1% MgCl2 as the decantation fluid throughout. Samples were 
fixed with enough 100% Formalin containing rose bengal to make a 
10% final solution, capped with the numbered cap from the original 
jar, and mixed thoroughly by swirling. Sieving was omitted, since 
even a 38-)um sieve results in a serious loss of small animals, including 
rotifers, nematodes, and gastrotrichs. 

Concurrently with the extraction and fixation of faunistic 
samples, bottles for BOD determination were placed in a constant- 
temperature chamber without light at 20° C. Duplicate titrations 
were made for methyl orange (total) alkalinity with bromocresol 
green— methyl red indicator and for dissolved oxygen. As soon as 
time allowed, tests for manganese, iron, and sulfates were conducted 
with Hach chemical tests modified for use with a Bausch and Lomb 
Spectronic 20, Calcium and total hardness were determined with 
unmodified Hach chemical tests. After 5 days, BOD samples were 
fixed and titrated for residual dissolved oxygen. 

Extracted and fixed faunistic samples were analyzed under a Wild 
M-8 stereomicroscope at 50 and lOOx magnification using multiple 
Sedgwick— Rafter (S— R) cell counts. Eight whole-cell counts were 
used for split samples and twelve were used for grouped samples. 
Material was prepared for the S— R cells by first decanting about 
two-thirds of the supernatant fluid. The residual material was swirled 
to determine its suspended load of organic material, silt, and clay. If 
the suspended load was great enough to impede counting efficiency, 
fluid was added back to dilute the suspended load and increase the 
counting efficiency. The fluid was swirled to randomize its contents; 
then the S— R cells were filled by a large-bore pipette, and the 
remaining fluid volume was noted. Fauna were enumerated to major 
taxon, and the resulting number of organisms in each taxon was 



MEIOFAUNAL ABUNDANCE 193 

multiplied by a correction factor to convert to organisms per cubic 
centimeter of sediment: 

(Organisms per cm^ sed.) = (organisms counted from S— R cells) 

X (total fluid, ml, from which S— R 
cells were filled) 

X [(amount of sediment, cm^ , 
represented by sample) 

X (number ml counted in S— R cells)] ~"^ 

Parenthetically, the procedure provides generous flexibihty for use 
with any predominately sandy sediments. Under light suspended 
loads it allows for the actual counting of 70 to 90% of the fauna 
contained in the sample. The procedure also gives reliable results 
with meiofauna of marine sandy sediments, requiring only two alter- 
ations: (1) the concentration of MgCl2 should be increased to 6 to 
7% and (2) the observation magnification can be reduced by one-half 
owing to the generally larger sizes of the marine meiofauna. 

Faunistic abundance per 10 square centimeters of surface 
(x 10^ = abundance per squ£ire meter of surface) was estimated sep- 
arately for each taxon and coring station. Density per cubic centi- 
meter of sediment for individually analyzed samples or subsamples was 
multiplied for each depth fraction analyzed by an appropriate factor 
(0 to 1 cm depth by 1.0, 1 to 2 cm depth by 1.5, 3 to 4 cm depth by 
2.5, and 6 to 7 cm depth by 3.5) to convert estimate from partial to 
complete cores, and then by 10 to convert from 1 to 10 square centi- 
meters of surface. The sum of taxon abundances at a given coring 
station was taken as the abundance of total meiofauna at that 
station. 

Geometric mean abundance per station and 95% confidence 
limits were then calculated for each taxon and site, using log (X) or 
(X + 1) transformations as appropriate. The resulting values were cor- 
related with a provisional three-parameter index of the physical- 
chemical environment. Of the three pgirameters in the index — 
noncarbonate conductivity tempered by high oxygen saturation and 
stream flow — the first two represent faunally weighted means of 
stream- water and interstitial-water values. For the faunal weighting 
factor, the fauna in the upper centimeter of sediment was thought to 
be most responsive to stream-water values and the fauna of the re- 
maining depths to be most responsive to interstitial- water values. 
Hence, for a given site, stream- water values were multiplied by the 
decimal fraction of abundance occurring in the upper centimeter of 



194 HUMMON et al. 

sediment, and the interstitial-water values were multiplied by the 
decimal fraction of remaining abundance. Noncarbonate conduc- 
tivity is given in micro mhos per centimeter, and oxygen saturation is 
given as a decimal fraction, rather than as percent. The third 
parameter is the cube root of cubic decimeters of stresim flow per 
second, or decimeters per second. 

In an alternate way of viewing meiofaunal relationships between 
sites, the H' (Lloyd, Zar, and Karr, 1968) taxon diversity was 
calculated for the arithmetic aggregate of station abundances at each 
site. It is proper to use the H' diversity measure with respect to taxa 
so long as (1) the results are compared with those of other studies 
using the same taxa and sampling— analytic scheme and (2) no 
inferences are made with respect to H' generic or species diversity. 
Faunal abundances from all 14 sites were then subjected to an Sh' 
similarity analysis (Hummon, 1974), based on shared taxon diversity, 
and the results were assembled in a dendrogram using the unweighted 
mean, pair— group method. 



RESULTS 

Values for pH were lowest at Raccoon Creek and Sandy Run, the 
two streams most heavily polluted by acid mine effluents (Table 2). 
In both streams the lower site showed slightly moderated effects of 
mine acid. Minkers Run was the only other stream having pH values 
consistently below 7.0, with the lower site in this case showing 
slightly increased effects of mine acid, probably associated with the 
nearby tipple zone. Interstitial waters generally showed slightly 
lower pH values than the adjacent stream waters, the major 
exception being Sandy Run (upper site) where interstitial water was 
higher than stream water. 

Total conductivity was greatest at Raccoon Creek and least at 
Tick Ridge, which lay just below the recently stripped and reclaimed 
area (Table 2). Intermediate values, in descending order, were Minkers 
Run, Sandy Run (upper site). Long Run, Strouds Run, Sandy Run 
(lower site), and Margaret Creek. Total conductivity of interstitial 
waters was similar to or lower than that of stream waters, the trend 
being most accentuated at Sandy Run (lower site), but with major 
reversals at Minkers Run cind Margaret Creek (south site). Carbonate 
conductivity was absent or minimal at Raccoon Creek, Sandy Run, 
and Minkers Run (lower site), low at Tick Ridge and in the stream 
water at Minkers Run (upper site), and high in the interstitial water 
at Margaret Creek (south site). Other stream sites had intermediate 



MEIOFAUNAL ABUNDANCE 



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values. Subtracting carbonate from total conductivity and applying 
the faunal v^^eighting factors (which show, incidentally, that only at 
Sandy Run and Long Run were the majority of animals in the upper 
layer of sediment) gives the numerator values (Table 2, column A) 
of the preliminary physical— chemical index. 

Dissolved oxygen treated as decimal saturation showed the 
expected constancy in stream water (x= 0.97, SD = 0.08, n = 14) 
but a wide variability in interstitial water (x=0.51, SD = 0.24, 
n = 14) (Table 2). Application of faunal weighting factors resulted in 
one of two parts (Table 2, column B) of the index's denominator. 
The BOD showed wide variability both in stream water (x=2.8, 
SD = 1.1, n = 14) and in interstitial water (x= 3.2, SD = 1.8, n = 14). 
Little pattern was visible from the standpoint of faunal weighting 
factors or faunal abundance. 

Stream flow showed more than a 100-fold difference between 
sites, though no site carried a large volume of water (Table 2). 
Minkers Run had the largest flow, more than doubling its volume 
between the upper and lower sites; Tick Ridge had the smallest flow. 
Raccoon Creek showed the largest difference in flow between sites, 
and, relative to the amount of flow, Long Run and Sandy Run 
showed the least. Taking the cube root of flow rate resulted in the 
second part (Table 2, column C) of the index's denominator. Light 
transmission in stream waters was high at the time of most 
collections; this indicated stable conditions and a lack of erosional 
runoff due to rainfall. Only Minkers Run (upper site, 60%; lower site, 
77%) showed less than 100% transmission. 

Iron ranged from trace amounts at Tick Ridge, Strouds Run, 
and Margaret Creek to 2.2 ±0.5 ppm at Raccoon Creek; manganese 
ranged from trace amounts at Strouds Run to 19.6 ±2.1 ppm at 
Raccoon Creek; and sulfate ranged from 72 ± 7 ppm at Tick Ridge, 
Strouds Run, and Margaret Creek to 1055 ± 375 ppm at Raccoon 
Creek (Table 2). Calcium and total hardness were lowest at Tick 
Ridge (51 ± 7 and 85 ± 7 ppm) and highest at Raccoon Creek 
(327 ± 46 and 650 ± 57 ppm). Little pattern was noted among the 
streams having intermediate values. Only at Raccoon Creek was there 
a consistent relationship between stream and interstitial waters with 
respect to these five chemical parameters, the values of interstitial 
waters being 0.67 ± 0.08 times those observed in stream waters. 

The compensated noncarbonate conductivity, A/(B x C), values 
for each site are shown in Table 3 in decreasing order of magnitude 
together with the faunistic data with which they were correlated. 
The number of taxa encountered, ranging from 3 at Raccoon Creek 



MEIOFAUNAL ABUNDANCE 197 

(upper site) to 10 to 11 at Strouds Run and Margaret Creek, 
showed a significant negative correlation with compensated non- 
carbonate conductivity (P < 0.01). Geometric mean abundance per 
station of total meiofauna and Diptera likewise showed significant 
negative correlations (P < 0.01 and P < 0.05), but for no other taxon 
was this the case. 

The fauna was dominated by Nematoda, Rotifera, and Diptera, 
with occasionally high counts of Oligochaeta (Margaret Creek, south 
site; Strouds Run, west site), Gastrotricha (Tick Ridge, lower site; 
Strouds Run, west site), and Cyclopoida copepods (Strouds Run, 
north site). There was a total of 16 taxa (listed in Table 3 in 
decreasing order of Gx abundance per station, summed over all sites), 
of which six (Turbellaria, Harpacticoida copepods, Pelecypoda, 
Ostracoda, Collembola, and Ephemeroptera) were observed at but 
three or four sites each and three (Cladocera, Gastropoda, and 
Plecoptera) were found at but one site each. 

The two Long Run sites showed greatest taxon similarity, with 
86% shared diversity (Fig. 1). The following sites joined at about the 
same level (53 to 54%): Minkers upper with the two Long Run sites, 
Margaret Creek west with south, Strouds west with Tick lower, and 
Raccoon upper with Sandy lower. At a slightly lower level (49%), the 
latter two pairs were joined, respectively, by Strouds north and 
Sandy upper. Already, at 49% similarity, four of the seven stream 
pairs have joined one another. At 46% similarity, Margaret Creek 
joined the Minkers uppei^-Long Run group, and it in turn was joined 
at 40% similarity by the Strouds Run— Tick lower group to form 
one major complex of predominantly unpolluted streams. Also, at 
46% similarity. Raccoon lower and Minkers lower joined. This group 
joined the central complex at 35%, just 1% less than the point at 
which Tick upper joined the Raccoon upper— Sandy Run group. 
Finally, the latter group joined the enlarged complex at the 30% 
similarity level to complete the series. 

Sites were arranged along the top of the figure, within the 
confines of the axes provided by their sequential joining, in such a 
manner as to maximize the Sh' values between adjacent members. A 
pattern emerges v^dth two interesting features. One is that the H' 
values for sites as arranged along the figure form a sine wave, with 
but two reversals, increasing from a minimum on the left to a 
maximum just right of center to a minimum again on the right. The 
second feature is that this arrangement portrays a bipolarity of 
faunal dominance, from rotifer-dominated faunae on the left to 
nematode-dominated faunae on the right, with the high diversity- 
low dominance faunae in the center. 



198 



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01 

•M 

a 


U 
H 

*■ 

X 


U* 


*C« 


-o 


^ 


Q H 



MEIOFAUNAL ABUNDANCE 201 

DISCUSSION 

It was important to collect all sites during stable, fair weather 
undisturbed by temporary rains, winter runoff, or spring floods. The 
three parameters in the physical— chemical index are easily changed 
by an influx or spate of water, which would also change the observed 
abundance of meiofaunal taxa since the sampling scheme is closely 
tied to the water level. 

Total conductivity is a blackbox-like measure that in no way 
specifies which ions are present, in what proportions, or involving 
what sorts and amounts of chemical complexing. What we have done 
in proposing the compensated noncarbonate conductivity index is to 
exclude from consideration those ions which are measured in 
titrating alkalinity. It can be said at present that, in the autumn 
season under relatively stable weather conditions, the index provides 
a relationship between certain physical— chemical parameters of the 
streams surveyed and the number of meiofaunal taxa and geometric 
mean abundance per station of total meiofauna and Diptera within 
those same streams. 

Based on levels of compensated noncarbonate conductivity. Long 
Run is more closely associated with Strouds Run and Margaret 
Creek, the two unpolluted streams, than with Raccoon Creek and 
Sandy Run upper, the two polluted streams. On the other hand, both 
sites on Long Run have fewer than the expected number of taxa, and 
the lower site has greater than expected abundance of total 
meiofauna. Tick Ridge upper is most closely associated with the 
polluted streams, although it has a greater than expected number of 
taxa and total meiofaunal abundance and no observed Diptera. 
Minkers Run, Tick Ridge lower, and Sandy Run lower occupy 
intermediate positions, with the Sandy Run site having fewer than 
the expected number of taxa and both the lower sites at Minkers and 
Sandy Runs having greater than expected abundances of total 
meiofauna. 

Results of the similarity analysis form a pattern, not greatly at 
variance with results of the correlation analysis. Long Run again is 
more closely associated with the unpolluted than with the polluted 
streams, with Minkers upper and Tick lower occupying comparable 
positions. Raccoon Creek and Sandy upper, along with Tick upper, 
are located at the ends of the array, but joining them in this case are 
Sandy lower and Minkers lower. 

On balance, considering Strouds Run and Margaret Creek to be 
unpolluted and Raccoon Creek and Sandy upper to be polluted, the 
following comments on the other seven sites can be made. The Long 



202 HUMMON et al. 

Run sites appear to have undergone the greatest amount of recovery, 
although they lack the number of taxa one would expect of an 
unpolluted stream. Tick lower and Minkers upper would be next in 
order from unpolluted to polluted, both having a moderate load of 
compensated noncarbonate conductivity and lacking the abundance 
of meiofauna expected of an unpolluted stream but both showing 
greatest simileirity of the meiofaunal taxa present with the meiofauna 
of unpolluted streams or those sites well along in the recovery 
process. Next in order would be Minkers lower and Sandy lower, 
both of which have abundant meiofauna, an intermediate to 
depressed number of taxa, and a moderate to less than moderate load 
of compensated noncarbonate conductivity. The meiofauna of each 
of these two sites is most similar, each in its own way, to one of the 
Raccoon Creek sites. Finally, and most anomalous, is the Tick upper 
site which, aside from the low measured total conductivity, gives 
some indications that it may have been adversely affected by the 
recently stripped and reclaimed area at its headwaters. 



ACKNOWLEDGMENTS 

This research was supported by a grant from the Office of Water 
Research and Technology, U. S. Department of Interior, through the 
Ohio Water Resources Center. We wish to thank George Billy, Ohio 
Department of Natural Resources, Athens; Roger Jewell, Wayne 
National Forest, Athens; and James Tong, Department of Chemistry, 
Ohio University, Athens, for consultations regarding the nature and 
extent of acid mine pollution in southeastern Ohio. We are 
particularly indebted to Roger Jewell for suggesting the Raccoon 
Creek and Tick Ridge collecting sites. Our thanks go to Deborah 
Zmarzly, Lynn Sarles, and Stuart Arkett for aiding in various of the 
field collections. 



REFERENCES 

Bailey, N. T. J., 1959, Statistical Methods in Biology, The English Universities 

Press, Ltd., London. 
Bennett, H. D., 1969, Algae in Relation to Mine Water, Castanea, 34: 306-328. 
Dills, G., and D. T. Rogers, 1974, Macroinvertebrate Community Structure as an 

Indicator of Acid Mine Pollution, Environ. Pollut. (London), 6: 239-262. 
Faucon, A., and W. D. Hummon, 1976, Effects of Mine Acid on Longevity and 

Reproductive Rate of the Gastrotricha Lepidodermella squammata (Du- 

jardm), flydrobiologia, 50: 265-269. 
Feldner, M. E., and W. S. Stanley, 1976, Macrofaunal Survey of Long Run, 

unpublished. 



MEIOFAUNAL ABUNDANCE 203 

Hill, R. D., 1968, Mine Drainage Treatment: State of the Art and Research 

Needs, U. S. Department of the Interior, Federal Water Pollution Control 

Administration, Cincinnati, Ohio. 
Hummon, W. D., 1974, Sh': A Similarity Index Based on Shared Species 

Diversity, Used to Assess Temporal and Spatial Relations Among Intertidal 

Marine Gastrotricha, Oecologia (Berlin), 17: 203-220. 
,1977, Meiobenthos of the Mississippi Headwaters, Am. Zool., 17: 869 

(abstract). 
Koryak, M., M. A. Shapiro, and J. L. Sykora, 1972, Riffle Zoobenthos in 

Streams Receiving Acid Mine Drainage, Water Res., 6: 1239-1247. 
Lackey, J. B., 1939, Aquatic Life in Waters Polluted by Acid Mine Waste, U. S. 

Public Health Rep., 54: 740-746. 
Lloyd, M., J. H. Zar, and J. R. Karr, 1968, On the Calculation of Information — 

Theoretical Measures of Diversity, Am. Midi. Natur., 79: 257-272. 
Massey, H. F., and R. I. Barnhisel, 1972, Copper, Nickel and Zinc Release from 

Acid Coal Spoil Material of Eastern Kentucky, Soil ScL, 13: 207-212. 
Napier, S., Jr., and W. D. Hummon, 1976, Survival of Mayfly Larvae Under Mine 

Acid Conditions, Int. Rev. Gesam. HydrobioL, 61: 677-682. 
Nichols, L. E., and F. J. Bulovv^, 1973, Effects of Acid Mine Drainage on the 

Stream Ecosystem of the East Fork of the Obey River, Tennessee, J. Tenn. 

Acad. ScL, 48: 30-39. 
Parsons, J. D., 1956, The Effects of Acid Strip Mine Pollution on the Ecology of 

a Central Missouri Stream, Diss. Abstr., 16: 1301-1302. 
, 1968, The Effects of Acid Strip-Mine Effluents on the Ecology of a Stream, 

Arch. HydrobioL, 65: 25-50. 
Roback, S. S., and J. W. Richardson, 1969, The Effects of Acid Mine Drainage 

on Aquatic Insects, Proc. Acad. Nat. ScL Philadelphia, 12: 81-107. 
Warner, R. W., 1971, Distribution of Biota in a Stream Polluted by Acid-Mine 

Drainage, Ohio J. ScL, 71: 202-215. 



CYTOTOXICITY OF UNTREATED 
COAL-CONVERSION GASIFIER CONDENSATE 



T. WAYNE SCHULTZ,*t JAMES N. DUMONT4 and LOLA M. KYTE4: 
*University of Tennessee, Knoxville, Tennessee, and Oak Ridge Graduate 
School of Biomedical Sciences, Oak Ridge, Tennessee; 
:|:Biology Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 



ABSTRACT 

The possible environmental effects of an untreated gasifier condensate (filtered 
product water from the Synthane gasification process) are examined. Popula- 
tions of the ciliate Tetrahymena pyriformis w^ere exposed to varying concentra- 
tions of condensate, and their behavior, respiration, cytology, and growth rates 
were investigated. Concentrations of 1% and less cause little if any behavioral 
(shape and motility) changes, but concentrations of 2% and greater decrease 
motility and increase cell lysis. The condensate causes a nonlinear, dose- 
dependent reduction in oxygen consumption. At concentrations of less than 2%, 
no alteration in respiration is noted over a 300-min exposure. At all 
concentrations tested, the most striking cytological alterations are in the 
mitochondrial matrixes, which become more electron dense. Cell membranes are 
also disrupted, and mucocysts are discharged. Population growth is reduced by 
concentrations of product water as low as 0.2% and is completely inhibited by 
1% concentration. The density of test populations plateaus at values inversely 
related to concentration. Pure phenolic compounds elicit similar responses. 



For many years gas and oil have been the major energy sources in the 
United States, but, with the depletion of domestic reserves and 
increasing dependence on foreign sources for these fuels, coal, which 
accounts for 75% of the U. S. fossil-fuel resources, will be relied on 
more and more as a source of energy. To be of greater industrial and 
commercial value, however, coal must be converted into gas and oil. 



tCurrent address: Department of Biology, Pan American University, 
Edinburg, Texas. 

204 



COAL-CONVERSION GASIFIER CONDENSATE 205 

One of the more promising coal-to-gas schemes is the Synthane 
gasification process, which encompasses basically four steps: (1) pre- 
treatment; (2) gasification; (3) purification; and (4) methanation to 
produce a medium-Btu gas (for a review of this process, see Forney 
et al., 1974). A potential effluent is the contaminated condensate 
from the gasifier (Forney et al., 1974). Chemical analyses of this 
aqueous effluent (Forney et al., 1974; Schmidt, Sharkey, and 
Friedel, 1974; Ho, Clark, and Guerin, 1976) show it to be a potential 
environmental and health hazard since it contains large quantities of 
phenolic compounds. 

The ciliate Tetrahymena pyriformis has been used as a test 
organism and model to study the effects of trace elements (Carter 
and Cameron, 1973; Tingle, Paulet, and Cameron, 1973) and organic 
compounds (Gray and Kennedy, 1974; Schultz and Dumont, 1977). 
It provides a rapid and inexpensive means of analyzing several 
parameters of cellular effects of potential pollutants. This paper 
reports some lethal and sublethal effects of untreated laboratory- 
scale Synthane gasifier condensate on Tetrahymena. 

MATERIALS AND METHODS 

General 

Tetrahymena pyriformis, strain GL-C, were grown in axenic 
cultures in a semidefined proteose peptone medium (Schultz and 
Dumont, 1977). Cultures were grown without shaking in 500-ml 
Erlenmeyer flasks containing 100 ml of medium in a 28° C water 
bath. Stationary-grovvi:h-phase cultures (3 to 4 days old, with 90,000 
cells/ ml) were used throughout the investigation. The Synthane 
process condensate was provided by the Pittsburgh Energy Research 
Center, Pittsburgh, Pa. 

Behavior 

The behavior of test cells was observed with a phase-contrast 
microscope immediately after the test solutions were added, and the 
general reactions and appearance of the cells were recorded. 
Particular attention was paid to changes in shape and motility, and 
the percent of cells altered was estimated at various times. 

Oxygen Consumption 

The effect of the gasifier condensate on the respiratory rate of 
Tetrahymena was examined in a respirometer (Gilson Medical 
Electronics), with the temperature stabilized at 28° C. Reaction flasks 



206 SCHULTZ, DUMONT, AND KYTE 

with a capacity of 15 ml, each containing 4.5 ml of cell suspension, 
were used. A paper wick saturated with 15% KOH solution was 
placed in the center well to absorb free CO2, and 0.5 ml of 
condensate at a concentration 10 times that desired for final testing 
was placed in the sidearm of the reaction vessel and later was mixed 
with the sample. Experiments were performed with final concentra- 
tions of 1 through 5%. Experimental and control samples were 
monitored at 15-min intervals for a total of 300 min, and total 
oxygen consumed (/i liter) was recorded for each time point. The 
immediate effect of gasifier condensate on respiration was deter- 
mined with a biological oxygen monitor (Yellow Springs Instrument 
Company, Inc.) equipped with a platinum— oxygen electrode. The 
temperature was stabilized at 28° C, and the rate of oxygen 
consumption (%/min) was recorded. For each test a 3-ml aliquot of 
cells was aerated for 3 min in the sample chamber before recording 
the data. The 0.3-ml aliquots of lOx condensate or sterile medium 
were added directly to the sample chambers, which contained either 
the cell suspension or sterile medium, and the samples were 
continuously stirred. Oxygen consumption was recorded before, 
during, and immediately after the test solutions were added to the 
chambers. 

Electron Microscopy 

The test animals were removed from the condensate solution at 
intervals of 15, 30, 60, 120, and 360 min for electron microscopy 
and were fixed according to the technique of Kennedy and 
Richardson (1969). Fixed cells were dehydrated in ethanol and 
propylene oxide and then infiltrated with and embedded in Epon 
(Shell Chemical Company). Thin sections stained with uranyl acetate 
and lead citrate were viewed with an electron microscope (Hitachi) 
operated at 75 kV. 

Population Growth and Density 

The effects of gasifier condensate on growth rates and population 
densities of Tetrahymena were measured spectrophotometrically. 
Optically matched 18- by 150-mm glass culture tubes were used, and 
experiments were performed with final concentrations of 0.1, 0.2, 
0.4, 0.6, 0.8, and 1% condensate. Each tube, containing 10 ml of 
medium, was inoculated with 0,2 ml of log-growth-phase culture 
and maintained in a water bath at 28° C. Absorbance at 540 nm was 
used to estimate population density. The period of exponential 
growth was determined for each test concentration, and the best line 



COAL-CONVERSION GASIFIER CONDENSATE 207 

for the data (Y is absorbance, and X is time) was fitted by the 
least-squares method of linear regression. The slopes were tested for 
homogeneity using analysis of covariance at the 5% level (P = 0.05). 

Pure Compounds 

Pure phenolic components known to be present in gasifier 
condensate (3 methyl; 2,6-dimethyl; 3,5-dimethyl; and 4-ethyl) were 
also examined for their effects on the behavior, respiration, and 
cytology of Tetrahymena. 

RESULTS 

Behavior 

Little, if any, behavioral alteration was caused by 1% toxicant. 
Reduction of motility and increased incidence of alteration in cell 
shape and lysing was directly related to concentrations of from 2 to 
5%. 

The general scheme of morphological alteration, although a 
continuum, can be subdivided into three phases: (l)the normal 
pear-shaped cells become rounded posteriorly; (2) the rounded cells 
become completely spherical; (3) the spherical cells become swollen. 
Concomitant with shape changes are alterations in the contractile 
vacuole. For example, the rate of discharge decreased and the volume 
of the vacuole increased with increased concentrations and/or 
increased exposure to condensate. Table 1 summarizes morphological 
and motility changes in test populations. 

Oxygen Uptake 

Gasifier condensate caused a nonlinear, dose-dependent reduc- 
tion in oxygen consumption (Fig. 1). Oxygen uptake by Tetra- 
hymena exposed to 2% or less product water was not different from 
controls. Respiration of cells exposed to 3% toxicant continued at a 
normal rate for the initial 90 min of exposure but then decreased 
with time and plateaued after 300 min. Respiration of cells treated 
with 5% condensate fell quickly and then leveled off after 120 min. 
Uptake of oxygen by ciliates exposed to 4% toxicant was inter- 
mediate to that for those exposed to 3 and 5%. The reduction of 
culture respiratory rates was correlated with the number of viable 
cells in the culture at any given time. For example, we can see from 
Table 1 that, at 180 min in 5% condensate, ~75% of the individuals 
in the population had lysed. Figure 1 indicates that, at the same 
concentration and time, the respiratory rate was reduced to about 



208 



SCHULTZ, DUMONT, AND KYTE 



TABLE 1 

SUMMARY OF MORPHOLOGICAL AND MOTILITY CHANGES 
IN Tetrahymena EXPOSED TO SYNTHANE PRODUCT WATER 



Synthane 


Exposure, 






concentration, % 


min 


General appearance* 


Motilityt 


2 


30 


Slight alterations 
in shape 


1 00% normal 




60 


<5% lysed; 
60% phase I and II 


50% reduced 




120 


10% lysed; 


15% reduced 






15% phase II and III 


(many feeding 
on detritus) 




180 


10% lysed; 
<10% phase III 


100% normal 


3 


30 


Occasional lysing; 
<10% phase I and II 


100% normal 




60 


10% lysed; 
25% phase I to III 


90% reduced 




120 


15-20% lysed; 


5% immobile; 






50% phase I to III 


90% reduced 




180 


< 25% lysed; 


10% immobile; 






70% phase I to III 


85% reduced 


5 


30 


25% phase I and II 


99% reduced 




60 


10% lysed; 


50% reduced; 






85% phase II and III 


50% immobile 




120 


50% lysed; 


25% reduced; 






50% phase III 


75% immobile 




180 


75% lysed; 
25% phase III 


100% immobile 



♦Percent of initial population expressing trait; remainder have normal shape. 
tPercent of existing population expressing trait; remainder have normal 
motility. 



35% of that of the controL Thus, at least with this toxicant, 
respiratory rates undoubtedly reflected changes in population densi- 
ties rather than alterations in the respiration of individuals. We 
should note that the slow, continued uptake of oxygen, even up to 
240 min in 5% condensate, was probably caused by respiratory 
activity of detritus (mitochondria) from lysed cells. 

The following results were obtained in tests designed to monitor 
changes in oxygen utilization and/or saturation levels immediately 
after addition of toxicant to the oxygen monitor (during the first 
3 min). Introducing 0.3 ml of full-strength gasifier condensate into 
the sample chamber containing the cell suspension caused an 



COAL-CONVERSION GASIFIER CONDENSATE 



209 



DUVJ 


1 


1 1 ' 


1 








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, 






Control / 










/ / 


3% 








/ / 






400 




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1 300 


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100 


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60 120 180 240 

LENGTH OF EXPOSURE, min 



300 



Fig. 1 Effect of gasifier condensate on respiration of Tetrahymena 
at 28°C. 



immediate 5- to 7-unit decrease in the percent-saturation reading 
(Fig. 2, curve A). The total time elapsed from the addition of 
toxicant to reestabhshment of a linear decrease in percent saturation 
(which we refer to as reaction time) was ~30 sec. In this case 
introducing half-strength condensate caused an immediate 1-unit 
decrease in the percent saturation (Fig. 2, curve B); the reaction time 
was less than 15 sec. The concentration of test solution added 
affected the slope (rate of respiration) of the reestablished oxygen- 
consumption line, as well as the reaction time and percent saturation. 
Adding 0.3 ml of sterile medium to the cell suspension caused a very 
slight decrease in the rate of oxygen uptake, less than 0.5%/ min 
(Fig. 2, curve C). Sterile medium injected into sterile medium had no 
effect (Fig. 2, curve F). FuU-strength condensate introduced into 
sterile medium caused a decrease in saturation of about 6 to 8 units, 
udth a reaction time of less than 15 sec (Fig. 2, curve D). Half- 
strength condensate added to sterile medium caused only a 3% 
decrease wdthin 9 sec (Fig. 2, curve E). These tests showed that, 
Eilthough the addition of gasifier condensate initially reduced the 
oxygen content of the medium, respiration was £ilso reduced. 



210 



SCHULTZ, DUMONT, AND KYTE 




Fig. 2 Immediate effects on respiration of adding gasifier product 
water at 28°C, measured with an oxygen electrode with constant 
stirring. A, Undiluted Synthane product water added to cell suspen- 
sion (final concentration, 10%). B, 50% Synthane product water 
added to cell suspension (final concentration, 5%). C, Sterile medium 
added to cell suspension. D, Undiluted Synthane product water 
added to sterile medium (final concentration, 10%). E, 50% Synthane 
product water added to sterile medium (final concentration, 5%). 
F, Sterile medium added to sterile medium. 



Cytology 

Elliott and Kennedy (1973) reviewed the fine structure of 
Tetrahymena. A series of three unit membranes enclose each cell; the 
innermost is the plasma membrane, and the outer two form the 
pellicle (Fig. 3a). Located immediately underneath the plasma 
membrane are numerous small mucocysts. The matrix of mature 
mucocysts displays a crystalline lattice pattern (Fig, 3b). The circular 
mitochondrial matrix varies with different fixation techniques; 
EUiott and Kennedy (1973) stated "... with good preservation the 
matrix is densely granular." 

The most prominent cytological alterations of Tetrahymena 
exposed to gasifier condensate occurred in the mitochondria and the 



COAL-CONVERSiON GASIFIER CONDENSATE 



211 



pellicular and plasma membranes. For all concentrations tested, the 
first cytological indication of alteration was observed in the first 
15 min, during which time there was a marked increase in the 
electron density of the mitochondrial matrixes (Fig. 4). The in- 
creased matrix density remained unaltered over the 6-hr test period 
in toxicant concentrations as low as 1% (Fig. 4a). 

Disruption of the cellular membranes occurred concomitantly 
with mitochondrial alteration. Initially the pellicular membrane split 
or separated (Fig. 4b), and the disruption of the plasma membrane 
and cell lysis, which followed, were directly related to the concentra- 
tion of the toxicant and the length of exposure, at least up to 
~240 min. An indirect indication of lysis was the presence of cellular 




















fe 






(b) 



Fig. 3 Electron micrographs of Tetrahymena pyriformis, strain 
GL-C (3- to 4-day-old cultures), (a) Section of a portion of a control 
cell showing cilium (C); pellicle (P); mitochondria (M), with tubular 
cristae and granular matrices; electron-dense glycogen stores (GS); 
and a segment of the macronucleus (N) (16,000X ). (b) Higher 
magnification of the periphery of a control cell revealing pellicular 
membrane organization, a mitochondrion, and mature mucocysts 
(MC) with internal crystalline lattice (16,400X ). 



212 



SCHULTZ, DUMONT, AND KYTE 







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COAL-CONVERSION GASIFIER CONDENSATE 213 

detritus in the food vacuoles of ciliates remaining after exposure to 
the toxicant. 

Test cells also discharged mucocysts (Fig. 4a) within the first 
15 min for all concentrations tested. All mucocysts appeared to be 
affected since no crystalline lattice was seen in mucocysts of any 
cells exposed to concentrations greater than 1%. Cells exposed to 1% 
toxicant or less retained a few mucocysts with a crystalline matrix, 
however, even after 6 hr of exposure. The apparent decrease in 
glycogen content with increased length of exposure suggested for 
Tetrahymena exposed to phenol (Schultz and Dumont, 1977) was 
not as apparent for cells exposed to gasifier condensate. 

Population Growth 

Population growth of axenic cultures of Tetrahymena grown at 
28° C was measured spectrophotometrically as absorbance at 540 nm. 
Growth of cultures exposed to condensate concentrations of 0.2 to 
1% for 72 hr showed an inverse relationship to concentration, with 
the mean rate during exponential growth being significantly affected 
(P < 0.05) by concentration (Fig. 5). In the presence of 0.2% 
toxicant, cells grew at a somewhat slower rate than controls, but in 
0.4% they grew at about half the rate of controls. These cultures 
plateaued at 48 hr at about 66% of the final control value. In 0.6% 
toxicant, populations grew at an even slower rate and plateaued 
within 36 hr at ~33% of the final control value. Growth of cultures 
exposed to 0.8% condensate plateaued in ~30 hr at an absorbance 
less than 25% of that of 72-hr controls. Gasifier condensate at 1% 
concentration inhibited population growth during the 72 hr tested. 

Pure Compounds 

The behavioral, respiratory, and cytological results for the four 
pure phenolic derivatives paralleled results described by Schultz and 
Dumont (1977) for pure phenol and those given here for gasifier 
condensate. We should note, hov/ever, that, although Tetrahymena 
detoxified or otherwise altered phenol (as indicated by return to 
normal shape and motility within 8 hr), cells exposed to methyl- and 
ethyl-substituted phenols did not recover as rapidly, exhibiting shape 
and motility alterations for as long as 24 hr after exposure. 



DISCUSSIOIM 

Although the gasifier condensate water used in this investigation 
is not a final effluent, there is a real need for biomedical and 



214 



COAL-CONVERSION GASIFIER CONDENSATE 




Fig. 5 Effect of gasifier product water on population growth of 
Tetrahymena at 28 C. Slopes of the mean log-phase growth lines 
(based on three replicate determinations) for control populations 
and for populations exposed to 0.2, 0.4, 0.6, and 0.8% condensate 
are 0.013, 0.013, 0.006, 0.004 and 0.002, respectively. Analyses of 
covariance were performed to test these slopes. Control and 0.2% 
populations are not significantly different, but control and 0.2% 
populations and the slopes for 0.4, 0.6, and 0.8% populations differ 
significantly (P < 0.05). 



environmental screening of such untreated product streams to ensure 
water quality and to avoid potential health hazards since the 
coal-conversion process is advancing from bench-scale and pilot-plant 
facilities to demonstration plants using 5000 tons/day and eventually 
to commercial-level plants using 25,000 tons/day. 

The major organic components of the Synthane process gasifier 
condensate are phenol, which alone accounts for 35% by weight of 
the total organics present (Ho, Clark, and Guerin, 1976), and its 
methyl-substituted derivatives. 

The most obvious effects of gasifier condensate on Tetrahymena 
were changes in shape and discharge of its mucocysts. Similar shape 
alterations and mucocyst discharge have been observed in ciliates 



SCHULTZ, DUMONT, AND KYTE 215 

exposed to a variety of compounds, including mercuric chloride 
(Tingle, Paulet, and Cameron, 1973), nontobacco cigarette-smoke 
residue (Gray and Kennedy, 1974), and phenol (Schultz and 
Dumont, 1977). These responses undoubtedly represent generalized 
reactions to a wide variety of adverse environmental conditions. 
Concomitant wdth these events was the cessation of contractile 
vacuole function; the contractile vacuole filled but ceased to 
discharge and became severely enlarged. We interpreted this response 
as indicative of the action of the phenolic components since pure 
phenol (Schultz and Dumont, 1977) and the alkane-substituted 
phenols examined in this study all elicit a similar response. 

The cytological effect of the toxicant on mitochondria is similar 
to mitochondrial matrix changes noted in animals exposed to as Uttle 
as 10 mg/liter of phenol (Schultz and Dumont, 1977). Unlike the 
phenol-treated animals, however, in which the matrix density 
returned to normal after 240 min, the matrix density of mitochon- 
dria of Tetrahymena treated with 1% gasifier condensate did not 
return to normal, possibly because methyl-substituted phenols, 
which have been shown to elicit the same mitochondrial response, 
were present in the sample. Changes in the configuration of 
mitochondria have also been observed in media-grown exponential- 
growth-phase Tetrahymena transferred to inorganic salts (Nilsson, 
1970) or exposed to higher temperatures (Nilsson. 1976) or to 
dimethyl sulfoxide (Nilsson, 1974). Hamburger and Zeuthen (1957; 
1960) and Skriver and Nilsson (1974) reported a reduction in the 
rate of respiration after these treatments. Schwab-Stey, Schwab, and 
Krebs (1971) described three configurations of mitochondria isolated 
from Tetrahymena (orthodox, intermediate, and condensed) but 
were unable to correlate the configurational states with specific 
energy stages or physiological conditions of the animal. The 
orthodox configuration corresponds to the normal or control type 
(see Fig. 3), and the condensed form is similar to mitochondria in 
cells exposed to gasifier condensate (see Fig. 4). In our study the 
configurational change corresponds to reduced respiratory activity, 
but other physiological parameters that may also contribute to such 
mitochondrial transformations are unknown at this time. 

A discussion of the significance of the effects on respiratory rates 
of Tetrahymena cultures of longer exposure (up to 240 min) to 
gasifier condensate must be tempered wdth the knowledge that 
during these experiments the density of the population was reduced 
because of cell lysis. Thus the respiratory rates correlated with the 
number of viable cells in the culture at any given time. The 
immediate decrease in oxygen saturation after addition of toxicant 



216 SCHULTZ, DUMONT, AND KYTE 

to the cultures probably represents an interaction of the toxicant and 
the medium rather than a respiratory effect (see Fig. 2). After the 
sharp initial decline of oxygen saturation, however, the oxygen 
consumption rate declined again; this indicated a reduction in 
respiration of the population. 

Population growth rates and final stationary-phase population 
densities were sensitive to lower concentrations of product water 
than were either cytological changes or respiration rates. The 
exponential growth rates (slopes) for cultures exposed to as little as 
0.2% toxicant were significantly reduced from those of controls. 
That this was not observed for cells grown in the presence of 5 to 25 
mg/liter of pure phenol (Schultz and Dumont, 1977) suggests that 
some component of the gasifier condensate other than phenol 
affected the rate of population growth (cell division). On the other 
hand, the lengthened lag phase and the premature onset of stationary 
growth at higher concentrations is consistent with data obtained 
from the growth rates of phenol- treated cells (Schultz and Dumont, 
1977). Since the cessation of population growth atsuboptimum levels 
is characteristic of Tetrahymena cultures exposed to a variety of 
compounds (Blum, Kirshner, and Utley, 1966; Satir, 1967; Meyer 
et al., 1972; Schultz and Dumont, 1977), it is difficult to determine 
precise modes of action that bring about this effect. 

Finally, attempts to relate the observed effects of gasifier 
condensate to one or a group of its specific identified components 
focus attention immediately on the fact that very high concentra- 
tions of phenol (2100 mg/hter) and methylated phenols (3120 
mg/liter) were present in the sample (Ho, Clark, and Guerin, 1976). 
Although effects were almost certainly elicited by many of the other 
components present, it is interesting to compare the data presented 
here with data previously obtained for pure phenol or some methyl 
phenols. For example, the point at which respiration plateaued in 
populations exposed to 5% condensate (263 mg/Uter total phenols) 
was comparable to that in populations exposed to 100 mg/liter 
phenol (Schultz and Dumont, 1977), 400 mg/liter 3-methyl phenol, 
300 mg/liter 2,6- and 3,5-dimethyl phenol, and 200 mg/liter 4-ethyl 
phenol. There is no assurance that phenol per se and/or the other 
phenolic compounds present were primarily responsible for this 
effect. Nonetheless, they were the major organic components, and 
we can be reasonably confident that they had the greatest influence 
on the parameters measured. Although correlation of toxicity with n 
and o of selected phenolic compounds has been successful (Kopper- 
man, Carlson, and Caple, 1974), the compounds that the investi- 
gators chose for testing had no ortho substitution; the Hammett 



COAL-CONVERSION GASIFIER CONDENSATE 217 

equation is valid only for meta and para substitution (Jaffe, 1953). 
Partition coefficients per se may be of value for indicating relative 
toxicities, however. We have found, for example, that, within certain 
groups of related compounds, there is a direct correlation between 
the partition coefficient and the toxicity of a compound, but 
elaboration of this concept must await further investigations. 

ACKNOWLEDGMENTS 

We acknowledge the excellent technical assistance provided by 
Patricia Miller and Carole Richter. We are also indebted to the 
Pittsburgh Energy Research Center and especially P. M. Yavorsky for 
the Synthane condensate samples used in this investigation. 

When this work was done, T. W. Schultz was a postdoctoral 
investigator supported by subcontract No. 3322 from the Biology 
Division, Oak Ridge National Laboratory, to the University of 
Tennessee. 

REFERENCES 

Blum, J. J., N. Kirshner, and J. Utley, 1966, The Effect of Reserpine on Growth 

and Catecholamine Content of Tetrahymena, Mol. Pharmacol., 2: 606-613. 
Carter, J. W., and I. L. Cameron, 1973, Toxicity Bioassay of Heavy Metals in 

Water Using Tetrahymena pyriformis. Water Res., 7: 951-961. 
Elliott, A. M., and J. R. Kennedy, 1973, Morphology of Tetrahymena, in The 

Biology of Tetrahymena, A.M. Elliott (Ed.), pp. 58-87, Dowden, 

Hutchinson and Ross, Inc., Stroudsburg, Pa. 
Forney, A. J., W. P. Haynes, S. J. Gasior, G. E. Johnson, and J. P. Strokey, 

1974, Analyses of Tars, Chars, Gases and Waters Found in Effluents from 

the Synthane Process, Technical Progress Report No. 76, U. S. Bureau of 

Mines, Department of the Interior. 
Gray, J. P., and J. R. Kennedy, Jr., 1974, Ultrastructure and Physiological 

Effects of Non-Tobacco Cigarettes on Tetrahymena, Arch. Environ. Health, 

28: 283-291. 
Hamburger, K., and E. Zeuthen, 1957, Synchronous Division in Tetrahymena 

pyriformis as Studied in an Inorganic Medium. The Effect of 2,4-dinitrophe- 

nol, Exp. Cell Res., 13: 443-4 53. 
, and E. Zeuthen, 1960, Some Characteristics of Growth in Normal and 

Synchronized Populations of Tetrahymena pyriformis, C. R. Trau. Lab. 

Carlsberg, 32: 1-18. 
Ho, C. H., B. R. Clark, and M. R. Guerin, 1976, Direct Analysis of Organic 

Compounds in Aqueous By-Products from Fossil Fuel Conversion Processes: 

Oil Shale Retorting, Synthane and Gasification and COED Coal Liquefac- 
tion, J. Environ. Sci. Health, Part A, 11: 481-489. 
Jaffe, H. H., 1953, A Reexamination of the Hammett Equation, Chem. Rev., 53: 

191-261. 
Kennedy, J. R., and S. H. Richardson, 1969, Fine Structure of Vibrio cholerae 

During Toxin Production, J. Bacteriol., 100: 1393-1401. 



218 SCHULTZ, DUMONT, AND KYTE 

Kopperman, H. L., R. M. Carlson, and R. Caple, 1974, Aqueous Chlorination 

and Ozonation Studies. I. Structure— Toxicity Correlations of Phenolic 

Compounds to Daphnia magna, Chem.-Biol. Interact., 9: 245-251. 
Meyer, R. R., C. R. Boyd, D. C. Rein, and S. J. Keller, 1972, Effects of 

Ethidium Bromide on Growth and Morphology oi Tetrahymena pyriformis, 

Exp. Cell Res., 70: 233-237. 
Nilsson, J. R., 1970, Cytolysomes in Tetrahymena pyriformis GL. II. Reversible 

Degeneration, C. R. Trau. Lab. Carlsberg, 38: 107-121. 
, 1974, Effects of DMSO on Vacuole Formation, Contractile Vacuole 

Function, and Nuclear Division in Tetrahymena pyriformis GL, J. Cell Sci., 

16: 36-47. 
, 1976, Physiological and Structural Studies on Tetrahymena pyriformis GL, 

C. R. Trau. Lab. Carlsberg, 40: 215-355. 
Satir, B., 1967, Effect of Actinomycin D on Cultural Growth Phases and on the 

Pattern of Total RNA Synthesis in Tetrahymena, Exp. Cell Res., 48: 

253-262. 
Schmidt, C. E., A. G. Sharkey, Jr., and R. A. Friedel, 1974, Mass Spectrometric 

Analysis of Product Water from Coal Gasification, Technical Progress Report 

No. 86, U. S. Bureau of Mines, Department of the Interior. 
Schultz, T. W., and J. N. Dumont, 1977, Cytotoxicity of Synthetic Fuel 

Products on Tetrahymena pyriformis. I. Phenol, J. Protozoal., 24: 164-172. 
Schwab-Stey, H., D. Schwab, and W. Krebs, 1971, Electron Microscopic 

Examination of Isolated Mitochondria of Tetrahymena pyriformis, J. 

Ultrastruct. Res., 37: 82-93. 
Skriver, L., and J. R. Nilsson, 1974, Oxygen Uptake and Food Vacuole 

Formation in Tetrahymena, J. ProtozooL, 21: 462. 
Tingle, L. E., W. A. Paulet, and I. L. Cameron, 1973, Sublethal Cytotoxic 

Effects of Mercuric Chloride on the Ciliate Tetrahymena pyriformis, J. 

ProtozooL, 20: 301-304. 



AQUATIC TOXICOLOGY OF TRACE ELEMENTS 
OF COAL AND FLY ASH 



WESLEY J. BIRGE 

T. H. Morgan School of Biological Sciences, University of Kentucky, 

Lexington, Kentucky 



ABSTRACT 

Aquatic bioassays were performed on 22 coal elements, with developmental and 
juvenile stages of fish and amphibians used as test organisms. For more sensitive 
test species, LC50 values of 0.1 ppm or less were observed for 15 trace elements, 
and LCi values ranged down to 0.1 to 0.2 ppb for mercury and silver. Studies 
also were performed on the aqueous leaching characteristics and toxicological 
properties of coal-produced fly ash. A 52-kg sample of precipitator-collected fly 
ash was subjected to continuous flow-through washing for 2000 consecutive 
hours in a bench-scale ash-settling pond. Chemical characteristics of the 
simulated effluent compared closely with those recorded for actual ash-settling 
ponds. During the first 500 hr of operation, conductivity averaged 690 
/Umhos/cm, and a mean of 0.56 g/liter was observed for total dissolved solids. 
Gradual decreases were observed thereafter. Effluent pH averaged 4.3 during the 
first 500 hr but approached the level of influent water (7.1 to 7.9) by 2000 hr. 
Maximum effluent concentrations detected for seven selected metals were 126 
ppm Al, 766 ppb Zn, 518 ppb Cu, 500 ppb Cd, 370 ppb Ni, 87 ppb Hg, and 8 
ppb Ag. Mean concentrations for the first 500 hr of elution were 32.6 ppm Al, 
350 ppb Zn, 156 ppb Cd, 155 ppb Ni, 110 ppb Cu, 2.1 ppb Ag, and 1.8 ppb Hg. 
All metals except mercui-y reached maximum levels within 500 hr, and 
concentrations declined thereafter. Mean mercury levels increased to 27 and 15 
ppb for the second and third 500-hr elution intervals. After 522 and 1033 hr of 
elution time, continuous-flow treatment with undiluted ash effluent produced 
100% mortality of frog and sunfish eggs. A 0.1 dilution at 1033 hr resulted in 
42% hatchability of sunfish eggs. After 1775 hr of continuous leaching, 
undiluted ash effluent and 0.1 and 0.01 dilutions gave survival frequencies of 57, 
76, and 88% for goldfish eggs, compared with 92% for controls. Metals analyzed 
for undiluted effluent administered to goldfish were well below LCj determina- 
tions, except aluminum, which was present at the LC50 level. 

219 



220 BIRGE 

With the increasing dependence on coal as a national energy source, 
there is a serious need to investigate further the effects of coal 
production and use on environmental health. Numerous recent 
studies emphasize the extent to which coal utilization has grov^n 
beyond our ability to identify fully the hazardous trace elements in 
coal, quantify their release rates into the environment, and define 
their biological and health-related effects (Ayer, 1974; Yavorsky and 
Akhtar, 1974; Babu, 1975; Vaughan et al., 1975). Approximately 
two-thirds of the over 60 elements that occur in coal have been 
detected as environmental pollutants (Vitez, 1976). Although toxico- 
logical data are largely incomplete, most of the elements found in 
coal and other fossil fuels are known to have at least some toxic 
effects on animal species (National Academy of Sciences— National 
Academy of Engineering, Committee, 1973; Smith, Ferguson, and 
Carlson, 1975; Vitez, 1976). 

The annual combustion of 600 million tons of coal constitutes 
the major source of environmental contamination v^th coal trace 
elements (Abel and Rancitelli, 1975; Bolton et al., 1975; Sheibley, 
1975). The main sources of water pollution are power plants, which 
dispose of more than 50 million tons/year of bottom ash and 
precipitated fly ash (Rubin and McMichael, 1974; Chu, Nicholas, and 
Ruane, 1975). Large quantities of water are used in sluicing ash 
residues to settling ponds, and pond effluents contain toxic metals 
that affect the quality of receiving waters (Theis, 1975; Hildebrand, 
Cushman, and Carter, 1976). For each 1000-MW capacity, sluicing- 
water requirements for Tennessee Valley Authority (TVA) power 
stations average 11.5 million gal/day or 4.2 billion gal/year (Environ- 
mental Protection Agency, 1974; Chu, Nicholas, and Ruane, 1975). 
Current projections indicate that the rate of coal combustion will 
double by the mid 1980s (Vaughan et al., 1975). Therefore, a better 
understanding of the aquatic toxicology of coal-derived contami- 
nants is essential if we are to maximize coal use and also institute 
safeguards necessary to maintain reasonable and proper environ- 
mental health. 

In this study, aquatic bioassays were performed to establish a 
comparative toxicological ranking for 22 coal elements, identify 
those which may be particularly hazardous to aquatic ecosystems, 
and provide quantitative data for use in further evaluations of 
environmental standards and pollution-abatement technology. In 
addition, a bench-scale settling pond was developed to simulate 
fly-ash effluents and to investigate the aqueous leaching of toxic 
elements. Continuous flow embryo— larval bioassays were used for in 
situ monitoring of ash effluents to provide direct toxicological 
evaluations on complex suites of trace elements. 



AQUATIC TOXICOLOGY OF TRACE ELEMENTS 221 

MATERIALS AND METHODS 

Aquatic Bioassays 

Semistatic embryo— larval bioassays were performed on the 
goldfish (Carassius auratus), the rainbow trout (Salmo gairdneri), and 
the narrow-mouthed toad (Gastrophryne carolinensis) with rapid- 
scan procedures previously described (Birge and Just, 1975). Eggs 
were exposed to coal elements from fertilization through 4 days 
posthatching, giving treatment periods of 7 days for toads and 
goldfish and 28 days for trout. Test water and toxicant were 
renewed at regular 12-hr intervals. Mean water hardness, with 
standard error, was 195 ± 5.4 ppm CaCOj for goldfish and toad 
stages and 104 ± 2.0 for trout. Test water pH averaged 7.4 ± 0.1. 
Dissolved oxygen was maintained near saturation by continuous, 
moderate aeration. Other chemical and physical characteristics of the 
reconstituted test water were described by Birge and Black (1977). 
Water temperature was 13.0 ± 0.5°C for trout eggs and 22.0 ± 1.0°C 
for other species. 

Test organisms were examined daily to tabulate frequencies of 
mortality and teratogenesis. Control adjusted LCj and LCjq values 
were calculated for combined test responses by log probit analysis 
(Daum, 1969). Anomalous survivors were counted as lethals. Control 
eggs were cultured simultaneously with experimentals and under 
identical conditions, except for omission of toxic coal elements. 
Minimum sample size was set at 150 eggs per culture. 

The 22 coal elements and test compounds selected for bioassay 
analysis are given in Table 1. Depending on the degree of anticipated 
toxicity, exposure concentrations were initiated at 10 to 100 ppm 
and continued at two- to tenfold dilutions until survival of 
experimental animals equaled or approached that observed for 
controls. Each coal element was administered at 10 to 14 exposure 
levels. Elemental concentrations of test water were monitored by 
atomic absorption spectrophotometry with a model 503 Perkin— 
Elmer unit equipped vAth an HGA-2100 graphite furnace and a 
mercury analyzer (Perkin— Elmer Corp., 1973). 

Aqueous Leaching of Fly Ash 

A bench-scale Plexiglas settling pond was designed to investigate 
the aqueous leaching characteristics of precipitator-collected fly ash 
obtained from a local 1000-MW coal-fired power plant. A 52-kg 
sample of dry ash was deposited in an 88.2-liter settling chamber. A 
Gilson Minipuls II peristaltic pump (Gilson Medical Electronics, Inc.) 
provided a continuous flow of water over the ash bed at a rate of 1 



222 



BIRGE 



TABLE 1 

COAL TRACE ELEMENTS SELECTED 
FOR BIO ASSAY EVALUATIONS 



Trace 


Bio assay 


Concentration* 


element 


test compound 


in coal, ppm 


Aluminum 


AICI3 


10,440-12,900 


Antimony 


SbCl3 


0.50-1.26 


Arsenic 


NaAs02 


4.45-14.02 


Cadmium 


CdCl2 


0.47-2.52 


Cobalt 


CO(N03)2 


2.90-9.57 


Chromium 


CrOa 


13.75-18.00 


Copper 


CUSO4 


8.30-15.16 


Germanium 


Ge02 


1.00-6.59 


Lanthanum 


LaCla 


3.80-10.00 


Lead 


PbCl2 


4.90-34.78 


Manganese 


MnCl2 


33.80-49.40 


Mercury 


HgCl2 


0.12-0.20 


Molybdenum 


Na2Mo04 


5.00-7.54 


Nickel 


NiCl2 


16.00-21.07 


Silver 


AgNOa 


0.03-0.12 


Selenium 


Na2Se04 


2.08-2.20 


Strontium 


SrCl2 


10.00-23.00 


Thallium 


TICI3 


0.29-2.00 


Tin 


SnCl2 


0.03-4.79 


Tungsten 


Na.W04 


0.10-3.00 


Vanadium 


V2O5 


28.50-32.71 


Zinc 


ZnCl2 


46-272 



*The majority of values are from Ruch, 
Gluskoter, and Shimp (1974), Fulkerson et al. 
(1975), and Carter (1975) and represent means for 
multiple coal samples taken largely from western 
Kentucky and southern Illinois. Lower means for 
Ag, Tl, Sn, and W are from Lloyd (1976), and the 
upper mean for Ag is from Vaughan et al, (1975). 



liter/hr, giving a detention time of 42 hr. Water was discharged from 
the settling chamber into an overflow-equipped effluent reservoir. 
The ash-to-water ratio and the detention time were calculated to 
approach conditions observed for a local ash-settling pond (Freeman 
and Birge, 1978). Also, the detention time was in good agreement 
with times reported for a number of TVA ash ponds (Chu, Ruane, 
and Steiner, 1976). Influent and effluent water samples were taken 
at 1- to 2-day intervals for 2000 hr of continuous operation to 
observe changes in water-quality parameters. Determinations were 
made on pH, conductivity, alkalinity, and total dissolved solids, and 



AQUATIC TOXICOLOGY OF TRACE ELEMENTS 223 

analyses were performed for seven selected metals (Ag, Al, Cd, Cu, 
Hg, Ni, and Zn). Alkalinity and total dissolved solids were deter- 
mined according to standard methods (American Public Health 
Association, 1975), and metals were analyzed by atomic absorption 
spectrophotometry. Fly ash displayed good settling characteristics, 
and effluent water was essentially free of ash particulates. The fly-ash 
bed compacted sufficiently to impede interstitial percolation, limit- 
ing water movement primarily to surface flow. Through the first 770 
hr of operation, influent water was distilled and deionized and had a 
conductivity less than 0.25 jumhos/cm and a pH of 6.8.' Total 
dissolved solids and trace metals were not detectable. During the 
remainder of the leaching period, the settling chamber was supplied 
with carbon-filtered tap water, which had a pH of 7.1 to 7.9, 
conductivity of 141 to 252 jumhos/cm, alkalinity of 54 to 70 ppm 
CaC03, and total dissolved solids of 0.19 to 0.24 g/hter. Water 
temperatures ranged from 24.4 to 26.0°C. 

Bioassay Monitoring of Fly-Ash Effluent 

Continuous-flow bioassays were performed on the simulated ash 
effluent to evaluate toxicological properties of the aqueous leachates. 
Eggs of the goldfish (Carassius auratus), redear sunfish (Lepomis 
microlophus), leopard frog (Rana pipiens), and Fowler's toad (Bufo 
fowleri) were used as test organisms. Full-strength effluent and serial 
dilutions thereof were perfused continuously through 300-ml egg 
chambers at flow rates of 200 to 300 ml/hr. Effluent dilutions of 
0.1, 0.01, 0.001, and 0.0001 were achieved with a proportional 
diluter (Freeman and Birge, 1978). Exposure was maintained from 
fertilization through hatching, and results were expressed as percent 
survival (hatchability). Hatching times averaged 1.5 days for Fowler's 
toad, 2.5 days for the leopard frog, and 3 days for sunfish and 
goldfish. Minimum sample size was set at 100 eggs. Control egg 
chambers received the same influent water as that supplied to the 
simulated ash-settling pond. Bioassays were initiated after 522, 1033, 
and 1775 hr of continuous aqueous leaching of the original 52-kg 
fly-ash sample. 

RESULTS 

Embryo-Larval Bioassays 

Fish and amphibian eggs were exposed to each of 22 selected 
coal elements (Table 1) from fertilization through 4 days post- 
hatching, giving treatment periods of 28 days for trout and 7 days 
for the narrow-mouthed toad and goldfish. Probit-derived LC50 and 



224 BIRGE 

LCi values expressed in parts per million and parts per billion, 
respectively, are summarized in Table 2. In order of decreasing 
toxicity, on the basis of LC50 determinations, the 12 elements most 
lethal to trout were Hg, Ag, La, Ge, Ni, Cu, Cd, V, Tl, Pb, Cr, and Sr. 
The LC50 values were 0.005, 0.01, and 0.02 for Hg, Ag, and La, 
respectively; 0.05 for Ge and Ni; 0.09 for Cu; 0.13 for Cd; and 0.16 
to 0.20 for V, Tl, Pb, Cr, and Sr. The calculated LCj 's for the 
more toxic elements were 0.2 for Hg and Ag, 0.4 for Ge, 0.6 for Ni, 
0.8 for La, 1.8 for Cu, 2.5 for Pb, and 6.0 to 6.1 for Sr and Cd 
(Table 2). 

The goldfish was the least sensitive of the three test species. The 
12 elements most toxic to goldfish eggs were Ag, Hg, Al, Cd, As, Cr, 
Co, Pb, Ni, Sn, Zn, and V. The LC50 values were 0.03, 0.12, 0.15, 
0.17, 0.49, 0.66, 0.81, and 1.66 for the first eight, respectively; 2.14 
for Ni and Sn; 2.54 for Zn; and 4.60 for V. The LCj values obtained 
for these metals ranged from as low as 0.4 and 0.6 ppb for Al and Ag 
to 400 ppb for Zn. Certain coal elements (e.g., Ag and Hg) were 
more toxic to fish embryos; others (e.g., Al, Cd, Ge, and Pb) 
exhibited considerable toxicity to posthatched juveniles. 

In bioassays with the narrow-mouthed toad, the 12 most lethal 
elements v/ere Hg, Ag, Zn, Cr, Pb, Cd, Cu, As, Ge, Co, Ni, and Al. 
The LC50 values were 0.001, 0.01, 0.01, and 0.03 ppm for the first 
four elements, respectively; 0.04 ppm for Pb, Cd, Cu, and As; and 
0.05 ppm for Ge, Co, Ni, and Al. The calculated LCi 's ranged 
only from 0.1 and 0.6 ppb for Hg and Ag to 1.6 and 3.2 ppb for Cd 
and Pb. 

The LC5 values were averaged for all animal species (Table 3) to 
provide a simplified toxicological index for the 22 elements. This 
mean toxicity index provided a convenient ranking, consisting of 
three general toxicity groups. Group 1 included ten highly toxic 
elements vidth mean LC50 values below 1 ppm; group 2 included 
nine elements with LC5 values of 1 to 5 ppm; and group 3 included 
three elements with an LC5 range of 20 to 47 ppm. 

The selected coal elements were also ranked according to a most 
sensitive species index (Table 3) based on median lethal concentra- 
tions determined for the animal species exhibiting highest sensitivity 
to each of the 22 elements. The LC5 values ranged from 0.001 ppm 
Hg to 2.90 ppm W. Elements with approximately the same LC^o 
concentration were further differentiated on the basis of LCj values. 

Aqueous Leaching of Fly Ash 

A 52-kg sample of precipitator-coUected fly ash was subjected to 
continuous washing for 2000 hr at a flow rate of 1 liter/hr. 



AQUATIC TOXICOLOGY OF TRACE ELEMENTS 



225 







TABLE 2 










COAL-ELEMENT LC, 


AND LC 


5 VALUES 






WITH 95% CONFIDENCE LIMITS 






Element 
and 


LC50 , 
s ppm 


Confidence limit 


LC,, 
ppb 


Confidence limit 


animal specie 


Lower 


Upper 


Lower 


Upper 


Aluminum 














Trout 


0.56 


0.40 


0.70 


256 


52.7 


371 


Goldfish 


0.15 


0.02 


0.82 


0.4 


0.0 


5.6 


Toad 


0.05 


0.04 


0.08 


2.3 


0.7 


4.8 


Antimony 














Trout 


0.58 


0.34 


0.92 


28.6 


4.6 


72.2 


Goldfish 


11.3 


3.99 


55.0 


111 


0.1 


663 


Toad 


0.30 


0.18 


0.51 


3.8 


0.7 


10.7 


Arsenic 














Trout 


0.54 


0.42 


0.67 


39.7 


15.5 


71.6 


Goldfish 


0.49 


0.39 


0.61 


15.5 


7.5 


26.6 


Toad 


0.04 


0.02 


0.07 


1.6 


0.2 


4.4 


Cadmium 














Trout 


0.13 


0.10 


0.18 


6.1 


1.8 


12.9 


Goldfish 


0.17 


0.13 


0.21 


15.0 


4.4 


19.2 


Toad 


0.04 


0.03 


0.05 


1.6 


0.9 


2.5 


Chromium 














Trout 


0.18 


0.07 


0.31 


19.1 


0.4 


56.5 


Goldfish 


0.66 


0.40 


1.10 


8.1 


1.5 


22.1 


Toad 


0.03 


0.03 


0.04 


1.0 


0.6 


1.5 


Cobalt 














Trout 


0.47 


0.38 


0.58 


34.2 


13.8 


60.8 


Goldfish 


0.81 


0.27 


2.27 


6.8 


0.0 


42.6 


Toad 


0.05 


0.02 


0.08 


0.9 


0.3 


2.0 


Copper 














Trout 


0.09 


0.05 


0.15 


1.8 


1.0 


4.5 


Goldfish 


5.20 


4.13 


6.41 


299 


101 


571 


Toad 


0.04 


0.03 


0.05 


1.0 


0.3 


1.3 


Germanium 














Trout 


0.05 


0.03 


0.07 


0.4 


0.1 


0.7 


Goldfish 


5.60 


1.76 


7.84 


143 


2.7 


567 


Toad 


0.05 


0.03 


0.08 


1.2 


0.1 


3.8 


Lanthanum 














Trout 


0.02 


0.01 


0.04 


0.8 


0.0 


2.7 


Goldfish 


60.4 


30.3 


105 


1987 


136 


6503 


Toad 


0.29 


0.19 


0.43 


7.5 


2.3 


16.2 


Lead 














Trout 


0.18 


0.10 


0.32 


2.5 


0.2 


8.1 


Goldfish 


1.66 


0.85 


3.05 


14.6 


1.4 


53.0 


Toad 


0.04 


0.02 


0.07 


3.2 


0.1 


9.0 


Manganese 














Trout 


2.91 


1.85 


4.37 


388 


66.2 


800 


Goldfish 


8.22 


2.39 


24.6 


21.5 


0.1 


182 


Toad 


1.42 


0.84 


2.40 


3.0 


0.5 


9.8 



(Table continues on following page.) 



226 



BIRGE 



TABLE 2 (Continued) 



Element 


















Confid( 


ence limit 




Confidei 


nee limit 


and 


LjC-i^ 1 






LC, , 






animal species 


ppm 


Lower 


Upper 


1 ' 

ppb 


Lower 


Upper 


Mercury 














Trout 


0.005 


0.004 


0.005 


0.2 


0.1 


0.3 


Goldfish 


0.12 


0.10 


0.14 


14.3 


8.2 


21.2 


Toad 


0.001 


0.001 


0.002 


0.1 


0.0 


0.3 


Molybdenum 














Trout 


0.73 


0.30 


1.40 


22.3 


1.2 


83.4 


Goldfish 


60.0 


7.94 


92.2 


39.3 


0.9 


261 


Toad 


0.96 


0.58 


1.60 


3.1 


0.6 


9.5 


Nickel 














Trout 


0.05 


0.04 


0.06 


0.6 


0.2 


1.2 


Goldfish 


2.14 


1.19 


3.63 


55.8 


7.9 


160 


Toad 


0.05 


0.03 


0.09 


0.4 


0.0 


1.5 


Selenium 














Trout 


4.18 


2.82 


5.82 


79.5 


17.5 


202 


Goldfish 


8.78 


7.23 


10.6 


506 


267 


805 


Toad 


0.09 


0.08 


0.15 


5.0 


0.7 


7.3 


Silver 














Trout 


0.01 


0.01 


0.02 


0.2 


0.1 


0.4 


Goldfish 


0.03 


0.02 


0.03 


0.6 


0.4 


0.9 


Toad 


0.01 


0.01 


0.03 


0.6 


0.0 


2.0 


Strontium 














Trout 


0.20 


0.10 


0.38 


6.0 


0.3 


19.9 


Goldfish 


8.58 


2.11 


21.2 


45.3 


0.0 


396 


Toad 


0.16 


0.12 


0.21 


2.4 


1.0 


4.6 


Thallium 














Trout 


0.17 


0.09 


0.30 


8.4 


0.7 


24.8 


Goldfish 


7.00 


1.94 


9.96 


52.5 


1.1 


266 


Toad 


0.11 


0.09 


0.14 


2.4 


1.1 


4.5 


Tin 














Trout 


0.40 


0.23 


0.67 


15.5 


2.1 


42.5 


Goldfish 


2.14 


0.36 


3.45 


68.8 


0.0 


390 


Toad 


0.09 


0.08 


0.13 


1.7 


0.3 


4.5 


Tungsten 














Trout 


15.61 


6.71 


31.98 


828 


14.2 


2810 


Goldfish 


120 


92.3 


156 


345 


4.7 


2139 


Toad 


2.90 


2.44 


3.50 


10.7 


4.5 


21.2 


Vanadium 














Trout 


0.16 


0.07 


0.30 


6.9 


0.3 


22.8 


Goldfish 


4.60 


0.51 


9.10 


55.2 


0.0 


116 


Toad 


0.25 


0.13 


0.44 


7.4 


0.6 


23.0 


Zinc 














Trout 


1.06 


0.75 


1.39 


20.0 


5.7 


33.2 


Goldfish 


2.54 


1.59 


4.18 


400 


26.5 


500 


Toad 


0.01 


0.01 


0.04 


0.6 


0.0 


2.2 



AQUATIC TOXICOLOGY OF TRACE ELEMENTS 



227 



TABLE 3 

COMPARATIVE TOXICITY OF COAL 

ELEMENTS TO FISH AND AMPHIBIAN 

EMBRYO-LARVAL STAGES 



Mean toxicity index* 



Most sensitive species index 



Element 



LC50 , 
ppm 



Element 



Species 



LC50, 
ppm 



LCi, 
ppb 



Toxicity group 1 




Mercury 


Toad 


0.001 


0.1 


Silver 


0.02 


Silver 


Trout 


0.01 


0.2 


Mercury 


0.04 


Zinc 


Toad 


0.01 


0.6 


Cadmium 


0.11 


Lanthanum 


Trout 


0.02 


0.8 


Aluminum 


0.25 


Chromium 


Toad 


0.03 


1.0 


Cobalt 


0.29 


Copper 


Toad 


0.04 


1.0 


Arsenic 


0.36 


Cadmium 


Toad 


0.04 


1.6 


Chromium 


0.45 


Arsenic 


Toad 


0.04 


1.6 


Lead 


0.62 


Lead 


Toad 


0.04 


3.2 


Nickel 


0.75 


Nickel 


Trout 


0.05 


0.6 


Tin 


0.88 


Cobalt 


Toad 


0.05 


0.9 


Toxicity group 2 




Germanium 


Toad 


0.05 


1.2 


Zinc 


1.20 


Aluminum 


Toad 


0.05 


2.3 


Vanadium 


1.67 


Tin 


Toad 


0.09 


1.7 


Copper 


1.78 


Selenium 


Toad 


0.09 


5.0 


Germanium 


1.90 


Thallium 


Toad 


0.11 


2.4 


Thallium 


2.43 


Strontium 


Toad 


0.16 


2.4 


Strontium 


2.98 


Vanadium 


Trout 


0.16 


6.9 


Antimony 


4.07 


Antimony 


Toad 


0.30 


3.8 


Manganese 


4.18 


Molybdenum 


Trout 


0.73 


22.3 


Selenium 


4.35 


Manganese 


Toad 


1.42 


3.0 


Toxicity group 3 




Tungsten 


Toad 


2.90 


10.7 


Lanthanum 


20.25 










Molybdenum 


20.56 










Tungsten 


47.17 











*LC5o values at 4 days posthatching averaged for three species, 
narrow-mouthed toad, goldfish, and rainbov^ trout. 



Detention time was 42 hr, and water-quality parameters were plotted 
and averaged for each of four 500-hr elution intervals. Total 
dissolved solids, conductivity, and pH showed marked decreases 
during the first 100 hr of elution time (Fig. 1). Total dissolved 
solids decreased from 2.2 g/liter at 18 hr to 0.5 g/liter at 94 hr, 
averaging 0.56 g/liter for the first 500 hr. Conductivity (jumhos) 
decreased from 2400 at 20 hr to 900 at 94 hr and continued to drop 
slowly to 200 at 500 hr. The sharpest decHne was observed for pH, 
which decreased from 7.7 at 1 hr to about 4.0 at 18 hr, averaging 4.3 



228 



BIRGE 



8.0 



• ,pH 

A , Total dissolved solids 
 , Conductivity 




3.0 



1.0 



200 300 400 

FLY ASH LEACHING TIME, hr 



500 



E ^ 

<J 0) 



E Q 



2.0 ^,9 

> -I 
HO 



QO 

U-< 



U 



CO 



0.0 



Fig. 1 Changes in fly-ash effluent with leaching time. 



for the first elution interval. As seen in Fig. 1, changes in these 
effluent parameters were most pronounced during the initial 4 days 
of ash-leaching time, presumably correlating with the period during 
which leachable components were most rapidly removed from the fly 
ash. Mean values for the first 500 hr are given in Table 4. 

Midway in the second elution interval, at 770 hr, the influent 
source was changed to carbon-filtered tap water. This action was 
taken to determine whether influent water of higher pH and greater 
buffering capacity would alter the leaching process. Initially, 
conductivity and total dissolved solids of the effluent rose propor- 
tionately with increases observed for the new influent water, but 
values for these parameters declined steadily over the third and 
fourth elution intervals, closely approaching those obtained for 
influent water by 2000 hr (see Materials and Methods section). After 
the change to influent tap water, effluent pH for the second elution 
interval increased steadily from 4.5 to 7.1. A gradual increase 
continued thereafter, and, during the last two elution intervals, pH 
ranges of 7.1 to 7.9 and 7.0 to 7.7 were recorded for influent and 
effluent water, respectively. Although total alkalinity was not 
determined during the first 1000 hr, ranges for the third and fourth 
elution intervals were 32 to 55 and 46 to 62 ppm CaCOj, compared 
with 54 to 69 ppm for influent tap water. After 2000 hr of 
continuous washing of the original fly-ash sample, influent and 



AQUATIC TOXICOLOGY OF TRACE ELEMENTS 229 

TABLE 4 
CHARACTERISTICS OF SIMULATED ASH-POND EFFLUENT 



Characteristic 




Simulated effluent* 


TVA ranget 


Total dissolved solids, 


g/liter 


0.56 ± 0.17 


0.14-0.52 


pH 




4.3 ±0.1 


4.4-11.3 


Conductivity, limhosj 


cm 


690 ±80 


242-855 


Alkalinity,! mg/liter i 


CaCOa 


43 ±3 


40-154 


Ag, iUg/liter 




2.1 ± 0.9 




Al, mg/liter 




32.6 ±6.1 


1.4-7.2 


Cd,iUg/liter 




156 ± 35 


1-37 


Cu, /Jg/liter 




110 ± 26 


10-310 


Hg, Atg/liter 




1.8 ±0.5 


0.2-38 


Ni, /ig/liter 




155 ±16 


31-1100 


Zn, ^g/liter 




350 ± 33 


30-1510 


Input, ml/hr 




969 ± 10 




Output, ml/hr 




897 ± 18 




% evaporation 




8 ± 2 





*Mean ± standard error for initial 500 hr of continuous operation. 
tRange of mean values for 14 TVA ash ponds (Chu, Ruane, and Steiner, 

1976). 

t Alkalinity determined for the third 500-hr elution interval. 



effluent water did not differ substantially in pH, alkalinity, conduc- 
tivity, or total dissolved solids. 

Effluent concentrations for the seven selected metals monitored 
through 1500 hr are summarized in Table 5. Maximum concentra- 
tions, which in most instances were observed during the first 100 hr 
of elution time, were 126 ppm Al, 766 ppb Zn, 518 ppb Cu, 500 ppb 
Cd, 370 ppb Ni, 87 ppb Hg, and 8 ppb Ag. Mean concentrations for 
the first 500 hours were 32.6 ppm Al, 350 ppb Zn, 156 ppb Cd, 155 
ppb Ni, 110 ppb Cu, 2.1 ppb Ag, and 1.8 ppb Hg. The 500-hr elution 
patterns for Al, Cu, Ni, and Zn are illustrated in Fig. 2. Elevated 
concentrations observed at about 300 hr correlated with mechanical 
disturbances that temporarily facilitated water filtration through the 
fly-ash bed. Concentrations for all metals except mercury continued 
to decline progressively with further leaching time, resulting in mean 
values for the third elution interval of 540 ppb Al, 61.4 ppb Zn, 33.6 
ppb Ni, 25.7 ppb Cd, 4.1 ppb Cu, and 0.2 ppb Ag (Table 5). Mercury 
fluctuated from 0.3 to 7.4 ppb during the first 500 hr but increased 
substantially thereafter, with mean values of 27.4 and 14.9 ppb for 
the second and third elution intervals. However, the mercury level 
dropped markedly toward the end of the third elution period, 
averaging 2.6 ± 0.7 ppb after 1360 hr. Metals were not detected in 



230 



BIRGE 



TABLE 5 
METAL CONCENTRATIONS FOR FLY-ASH EFFLUENT 





Maximum 


Mean concentration for th 


ree elution intervals, ppb* 


Infl 


uent 




concen- 














cor cen- 


Element 


tration, ppb 


0—500 hr 


500-1000 hr 


1000- 


-1500 hr 


tratio 


n, ppb 


Ag 


8 


2.1 


± 0.9 


0.2 


± 0.2 


0.2 


±0.2 


0.0 




Al 


126,000 


32,600 


±6,100 


1,570 


± 260 


540 


±80 


230 


± 29  


Cd 


500 


156 


± 35 


93.8 


± 24.8 


25.7 


± 11.3 


1.7 


± 0.8 


Cu 


518 


110 


± 26 


14 


± 1.8 


4.1 


± 0.8 


3.5 


± 0.9 


Hg 


87 


1.8 


± 0.5 


27.4 


± 11.7 


14.9 


±5.3 


0.0 




Ni 


370 


155 


± 16 


58 


± 10 


33.6 


± 2.3 


3.3 


± 1.4 


Zn 


766 


350 


± 33 


106 


± 20 


61.4 


±4.1 


4.9 


± 3.1 



*Mean values with standard errors were based on analyses taken at 1- to 3-day intervals. 




100 200 300 

FLY ASH LEACHING TIME, hr 



400 



500 



Fig. 2 Leaching patterns for fly-ash metals. 



the distilled— deionized influent water used for the first 770 hr, and 
background values for the carbon-filtered tap water are given in 
Table 5. 

Bioassay Analysis of Fly-Ash Effluent 

Four sets of embryo— larval bioassays were performed on fly-ash 
effluent by use of a continuous-flow system. Tests were initiated 



AQUATIC TOXICOLOGY OF TRACE ELEMENTS 



231 



after 522, 1033, and 1775 hr of continuous aqueous leaching of the 
original 52-kg sample of precipitator-collected fly ash. At 522 hr 
tests were conducted on eggs of the leopard frog and Fowler's toad 
with undiluted ash effluent. Frog eggs suffered rapid and complete 
mortality, and a hatching frequency of 46% was observed for 
Fowler's toad. Survival was 97 to 99% for control populations 
treated with the same influent water source used to supply the fly- 
ash leaching chamber (Table 6). Bioassays were initiated at 1033 hr 
on eggs of the redear sunfish. Undiluted effluent produced complete 
mortality, and 0.1 and 0.01 dilutions gave survival frequencies of 42 
and 90%, which closely approached control survival. In tests with 
goldfish eggs conducted at 1775 hr, survival averaged 57, 76, and 
88% for undiluted effluent and 0.1 and 0.01 dilutions, respectively. 
Control survival was 92%. 

Effluent metal concentrations observed for the amphibian 
bioassays approximated mean values given for the second elution 
interval (Table 5). Although ash toxicants produced a near-LCgo 
response for toad eggs, the exposure period was limited to only 1.5 
days. In addition, developmental stages of Fowler's toad are highly 
resistant to trace metals, compared with other amphibian and piscine 
species (Birge, 1976). Animal species used for the initial toxicological 



TABLE 6 
EMBRYO-LARVAL BIOASSAYS ON FLY-ASH EFFLUENT 





Elution 


Exposure 




Percent 




interval, 


time, 


Bioassay 


survival 


Species 


hr 


days 


solution 


at hatching 


, Leopard frog 


522-582 


2.5 


Ash effluent 





(Rana pipiens) 






Control 


97 


Fowler's toad 


522-558 


1.5 


Ash effluent 


46 


(Bufo fowleri) 






Control 


99 


Redear sunfish 


1033-1105 


3.0 


Ash effluent 





(Lepomis 






Diluted effluent 




microlophus) 






0.1 
0.01 
0.001 
0.0001 
Control 


42 
90 
93 
95 
89 


Goldfish 


1775-1847 


3.0 


Ash effluent 


57 


(Carassius 






Diluted effluent 




auratus) 






0.1 
0.01 
Control 


76 

88 
92 



232 BIRGE 

characterization of coal elements were not available for the first two 
sets of effluent bioassays. Sunfish eggs, however, have the same 
hatching time (exposure period) as goldfish and generally exhibit 
similar sensitivity when used in aquatic bioassays (Birge, Black, 
and Westerman, 1978). During the exposure period for sunfish eggs, 
mean effluent metal concentrations, with standard errors, were 
0.4 ± 0.2 ppb Ag, 1070 ± 230 ppb Al, 72.0 ± 43.0 ppb Cd, 5.5 ± 1.8 
ppb Cu, 20.6 ± 4.8 ppb Hg, 31.5 ± 1.4 ppb Ni, and 70.0 ± 6.7 ppb 
Zn. At the 0.1 dilution, which gave 42% survival for sunfish eggs 
(Table 6), all analyzed metals except aluminum were well below 
goldfish LCi values. Aluminum was present at approximately 
two-thirds of the LC50 value. Although the effluent was not 
analyzed for all possible toxicants, this correlation tends to support 
application of the toxicological index given for coal elements 
(Tables 2 and 3). Before the goldfish bioassays were initiated, 
effluent metal concentrations had dropped to ppb Ag, 160 ± 10 
ppb Al, 1.5 ±1.5 ppb Cd, 4.5 ± 1.8 ppb Cu, 3.8 ± 0.7 ppb Hg, 
23.0 ± 3.0 ppb Ni, and 44.5 ± 8.0 ppb Zn. These values were all 
below LCi 's calculated for goldfish, except aluminum, which was 
present at about the LC50 level (Table 2). The undiluted effluent 
gave 57% survival. 



DISCUSSION 

The embryo— larval bioassays reported in Table 2 demonstrate 
the high toxicity of numerous inorganic coal elements to aquatic 
biota. Depending on the animal species, LC50 values of 0.1 ppm or 
less were observed for 15 coal elements, and calculated LCj 's 
ranged down to 0.1 to 0.2 ppb for mercury and silver. Tungsten was 
the least toxic element in all cases, with LC50 values ranging from 
2.90 ppm for the toad to 120 ppm for the goldfish. When the test 
data were averaged, the increasing order of sensitivity of animal 
species was goldfish, trout, and toad. 

The order of toxicity of the 22 elements, as determined by LCg 
values, varied somewhat for embryo— larval stages of the three 
species. Only Ag, Cd, Cr, Hg, Ni, and Pb occurred among the 12 most 
toxic elements for all three, but Al, As, Co, Cu, Ge, V, and Zn were 
included in this group for two species (Table 2). Of particular 
interest were the consistent extreme toxicity of mercury and silver to 
developmental stages of all species and certain selective responses, 
such as the high relative toxicity of aluminum to goldfish, germa- 
nium and lanthanum to trout, and selenium and zinc to the toad. 



AQUATIC TOXICOLOGY OF TRACE ELEMENTS 233 



100 



80 



< 60 



> 

Z) 
00 

>? 40 



20 




 , Goldfish 
• , Trout 
▲ , Toad 



OU L_J L_^ I t ^•^f 



0.0001 0.001 0.01 0.1 1.0 

SILVER CONCENTRATION, ppm 

Fig. 3 Effects of silver on embryo — larval stages. 



Several patterns of response were discernible concerning the 
differential sensitivity of the three test organisms. Highest uniformity 
was obtained for silver, which gave an exceptionally narrow range of 
LC50 values (0.01 to 0.03 ppm). As seen in Fig. 3, this relationship 
held for the full range of exposure concentrations. Germanium 
produced similar effects on the two most sensitive test animals, trout 
and toads, but was substantially less toxic to the goldfish (Fig. 4). 
This same pattern was given by Cu, Mo, Ni, Sb, Sr, Tl, and V. A still 
more heterogeneous response occurred for Pb (Fig. 5), Hg, and 
certain other elements (e.g.. La, Sn, and W). Considering the response 
patterns summarized in Figs. 3 to 5, it is probable that the diversity of 
aquatic species affected by pollution would increase in the order of 
Pb, Ge, and Ag. Although elements such as Pb and Ge hkely 
would affect fewer species, these toxicants probably would con- 
tribute to an ecological imbalance of aquatic biota. As noted, Se, 
Zn, and certain other elements (e.g.. As and Co) were more selective 
for the toad, and, on the basis of LCg o values, the toad was the most 
sensitive species for 17 of the 22 elements. This suggests that 
amphibians may constitute particularly sensitive target sites for coal 
contaminants. For example, goldfish LCj o determinations for 
selenium and zinc exceeded those for the toad about 100 and 250 
times, respectively. 



234 



BIRGE 



100 



80 



<60|— 
> 

> 

cr 

5? 40 — 



20 




 , Goldfish 
• , Trout 
A , Toad 



0.001 



0.01 0.1 1 

GERMANIUM CONCENTRATION, ppm 

Fig. 4 Effects of germanium on embryo— larval stages. 



100 



100 



> 

ca 

C/3 




0.001 



0.01 



0.1 1 

LEAD CONCENTRATION, ppm 



100 



Fig. 5 Effects of lead on embryo— larval stages. 



AQUATIC TOXICOLOGY OF TRACE ELEMENTS 235 

The heterogeneity of response observed for the three animal 
species somewhat comphcates application of the bioassay data on 
coal elements to impact assessment and pollution-abatement tech- 
nology. Therefore, the mean LC50 and sensitive species indexes 
(Table 3) w^ere developed to provide a simplified data base for energy 
and environmental engineers. The sensitive-species ranking for coal 
elements was used to delineate upper limits of toxicity observed for 
the 66 independent bioassays, and the mean index summarized 
average test responses. Despite some notable exceptions (e.g., Al and 
La), the toxicological orders given in the two indexes were generally 
similar. Principal differences in relative order were attributed to 
elements exhibiting disproportionate selective toxicity for a particu- 
lar animal species. The only extreme disparity involved lanthanum, 
for which mean and sensitive species LC50 values differed by three 
orders of magnitude. We should note that several recent publications 
review additional bioassay data for some of the trace metals found in 
coal (National Academy of Sciences— National Academy of Engineer- 
ing, Committee, 1973; Vaughan et al., 1975; Environmental Protec- 
tion Agency, 1976). 

In the fly-ash leaching study, characteristics of the simulated 
effluent were compared with those recorded for 14 TVA ash ponds. 
As seen in Table 4, good agreement was obtained for all test 
parameters except aluminum and cadmium, but concentrations for 
these metals were within TVA ranges early in the third elution 
interval. The high initial values for aluminum and cadmium may have 
resulted from use of distilled influent water, which contributed to 
low pH in the simulated ash pond. These and other results indicate 
that the quality of effluent water may be improved somewhat by 
regulating certain parameters (e.g., pH and alkalinity) of influent 
water used for ash sluicing. 

Appreciable metal leaching continued, however, even after 770 
hr, when the change was made in influent water (Table 5). The 
resulting suite of toxic metals produced lethality of test organisms 
through 1775 to 1847 hr of continuous elution time (Table 6). 
Effluent metal concentrations (Table 5) were compared to fresh- 
water guidelines (National Academy of Sciences— National Academy 
of Engineering, Committee, 1973; Environmental Protection Agency, 
1976) to further evaluate potential effects of fly-ash leaching on 
aquatic biota. Through 1775 hr, mercury remained well above the 
limit of 0.05 ppb, and aluminum exceeded the 100-ppb level 
considered deleterious to growth and survival of fish. Cadmium was 
over the trout standard of 0.4 to 1.2 ppb for 1775 hr and exceeded 
the maximum limit for other aquatic species (4 to 12 ppb) for 1050 



236 BIRGE 

to 1435 hr. On the basis of the Environmental Protection Agency's 
(EPA) application factor (0.01) and the trout, toad, and goldfish 
embryo— larval LCg o values, nickel and zinc concentrations exceeded 
recommended levels for all test species through 1775 hr, and silver 
was above acceptable limits for 1050 to 1266 hr. Copper, with an 
application factor of 0.1, exceeded calculated concentrations for 
trout and toad through 1000 to 1500 hr but was over the goldfish 
limit for only 22 hr. Using embryo— larval rather than adult LCj o 
values resulted in more stringent limits for Ag, Cu, Ni, and Zn. 
However, freshwater standards should permit adequate protection 
for sensitive life-cycle stages. Except for copper, the suggested EPA 
application factors appeared acceptable for embryo— larval stages. On 
the basis of data in Table 2, 0.01 to 0.05 of LC50 determinations 
gave values that generally fell within or near 95% confidence limits 
for LCi 's. In comparison with the EPA value of 0.1, a more suitable 
application factor for copper was found to be 0.05 for goldfish and 
trout and 0.01 for the toad. 

Since combined toxicological effects of complex suites of trace 
metals are difficult to quantify by existing hazard-assessment criteria, 
direct bioassay monitoring was used to provide further characteriza- 
tion of ash effluent. As noted, after 1033 hr of continuous elution, 
undiluted ash effluent produced 100% mortality of sunfish eggs, and 
survival of goldfish eggs was reduced to 57% when exposure was 
initiated at 1775 hr. A 0.1 dilution produced an approximate LC50 
for sunfish, and 0.01 gave essentially control-level survival for both 
species. When median survival was obtained, concentrations of all 
monitored metals except aluminum were at or below goldfish LCi 
values, and aluminum was present at about the LC50 level (Table 2). 
Effluent dilutions that gave control-level survival did not contain any 
monitored metals at concentrations exceeding goldfish LCj values. 
Although ash effluent was not analyzed for all possible toxicants, 
results obtained by direct effluent monitoring were in good 
agreement with the independent embryo— larval bioassays for coal 
elements. Also, trace metals present at or below the probit LCj 's did 
not exert any overt synergistic effects. In addition, results indicate 
that continuous-flow embryo— larval test systems are highly suitable 
for in situ toxicological monitoring of complex coal effluents. 

Although not intended to serve in lieu of actual field studies, 
simulated ash ponds can be used to characterize aqueous leaching 
processes and to evaluate ash effluents for potential environmental 
hazards. Test parameters can be manipulated individually to deter- 
mine effects on metal elution rates, and such model systems can be 
particularly useful in comparing ash residues of coal from different 



AQUATIC TOXICOLOGY OF TRACE ELEMENTS 237 

formations. The chemical composition of bottom and fly ash is 
highly variable, depending on the source of the coal used, combus- 
tion conditions, and such factors as the efficiency of emission- 
control equipment (Moulton, 1973; Chu, Nicholas, and Ruane, 1975; 
Cooper, 1975). In addition to differences in ash composition, 
numerous physical and chemical factors may affect the leaching of 
trace elements and the final composition of ash-pond water. These 
factors include the quantity of water used for sluicing; its tempera- 
ture, pH, and hardness; and various performance characteristics of 
the setthng pond. As noted by Chu, Nicholas, and Ruane (1975), the 
effects of such variables on the quality of ash-pond effluents are not 
sufficiently understood. It is knovm, however, that a number of 
coal-derived inorganic elements reach appreciable concentrations in 
ash-pond waters. Since 1973, TVA has analyzed for 17 trace 
elements in quarterly grab samples from bottom ash, fly ash, and 
combined ash ponds, and the results have been summarized by Chu 
and co-workers (Chu, Nicholas, and Ruane, 1975; Chu, Krenkel, and 
Ruane, 1976). Discharges from fly-ash ponds were reported to 
contain up to 7.3 ppm Al, 0.3 ppm Ba, 0.04 ppm Cd, 0.1 ppm Cr, 
0.3 ppm Cu, 0.08 ppm Pb, 13.4 ppm Mn, 1.1 ppm Ni, and 1.5 ppm 
Zn. Ranges for a number of these metals are summarized in Table 4. 
Other investigators also have considered various problems 
associated with fly-ash disposal (Guthrie, Cherry, and Rodgers, 1974; 
Theis, 1975; Holland et al., 1975). Theis (1975) indicated that the 
production of metal leachates and alterations of pH and dissolved 
oxygen may affect receiving waters. He also demonstrated significant 
release rates for trace metals when fly ash was dispersed in distilled 
water. Holland et al. (1975) investigated the environmental effects of 
trace elements in the pond disposal of ash and flue-gas desulfuriza- 
tion sludge. Samples of ash and sludge from five generating stations 
were studied by simulated ponding. In general, concentrations of 
aqueous leachates were low, but Ba, B, Cr, Hg, and Se exceeded EPA 
guidelines for public water suppHes. However, these investigators did 
not compare their findings with EPA standards for freshwater biota, 
which generally are more stringent, and they did not consider the 
combined toxic effects of the resulting metal mixtures. Guthrie, 
Cherry, and Rodgers (1974) evaluated the impact on biota in 
waters receiving ash-basin effluent from a coal-fired power plant. 
Bacterial, plant, and animal diversities were reduced at sites affected 
by ash effluents. Abiotic water parameters affected by ash-basin 
effluents included temperature, turbidity, dissolved oxygen, and pH. 
Concentrations of coal-ash leachates (e.g., Cd, Cr, Cu, Hg, and Zn) 
were lowest in effluent water, somewhat greater in aquatic biota, and 



238 BIRGE 

highest in benthos. This indicated accumulation of these toxicants in 
biomass and bottom sediment. 

The results given here show clearly that a substantial number of 
minor and trace elements of coal and fly ash are highly toxic to 
aquatic organisms. Many are leachable from ash residues at concen- 
trations that prove lethal to fish and amphibian embryo— larval stages 
and other organisms. Since annual coal utilization in the United 
States may reach 1 billion tons or more in the near future (Vaughan 
et al., 1975), it remains essential to characterize more fully the toxic 
properties of coal-derived contaminants, ascertain their release rates, 
and determine their pathways of exchange wdthin and ultimate 
effects upon aquatic ecosystems. 

ACKIMOWLEDGMEIMTS 

I should like to acknowledge efforts devoted to bioassay 
evaluation by A. G. Westerman and J. A. Black and contributions by 
R. A. Freeman and J. E. Hudson to the fly-ash-leaching studies. I am 
most grateful to B. A. Ramey for preparation of the manuscript and 
figures. The research reported here was supported by the Institute 
for Mining and Minerals Research, Lexington, Kentucky (grant 
number 7576-EZ). 

REFERENCES 

Abel, K. H., and L. A. Rancitelli, 1975, Major, Minor and Trace Element 
Composition of Coal and Fly Ash as Determined by Instrumental Neutron 
Activation Analysis, in Trace Elements in Fuel, S. P. Babu (Ed.), Advances in 
Chemistry Series, No. 141, pp. 118-138, American Chemical Society, Wash- 
ington, D. C. 

American Public Health Association, 1975, Standard Methods for the Examina- 
tion of Water and Wastewater, 14th ed., Washington, D. C. 

Ayer, F. A. (Comp.), 1974, Environmental Aspects of Fuel Conversion 
Technology, Symposium Proceedings, St. Louis, Mo., May 13—15, 1974, 
Report EPA-650/2-74-118, Environmental Protection Agency, NTIS. 

Babu, S. P. (Ed.), 1975, Trace Elements in Fuel, Advances in Chemistry Series, 
No. 141, American Chemical Society, Washington, D. C. 

Birge, W. J., 1976, Effects of Metals on Embryogenesis and Use of Vertebrate 
Embryos as Sensitive Indicators of Environmental Quality, NSF(RANN) 
Technical Report, Grant No. AEN 74-08768 AOl, National Science Founda- 
tion, Washington, D. C. 

, and J. A. Black, 1977, A Continuous Flow System Using Fish and 

Amphibian Eggs for Bioassay Determinations on Embryonic Mortality and 
Teratogenesis, Report EPA-560/5-77-002, Environmental Protection 
Agency. 



AQUATIC TOXICOLOGY OF TRACE ELEMENTS 239 

, J. A. Black, and A. G. Westerman, 1978, Embryo— Larval Bioassays with 

Goldfish and Redear Sunfish, unpublished data. 

, and J. J. Just, 1975, Bioassay Procedures Using Developmental Stages as 

Test Organisms, Research Report No. 84, U. S. Department of the Interior, 
Washington, D. C. 

Bolton, N. E., et al., 1975, Trace Element Mass Balance Around a Coal-Fired 
Steam Plant, in Trace Elements in Fuel, S. P. Babu (Ed.), Advances in 
Chemistry Series, No. 141, pp. 175-187, American Chemical Society, Wash- 
ington, D. C. 

Carter, J. A., 1975, Trace Element Composition of Coal-Derived Materials 
(NSF— RANN), in Coal Technology Program Quarterly Progress Report 
No. 1 for the Period Ending December 31, 1974, pp. 66-69, ERDA Report 
ORNL-5026, Oak Ridge National Laboratory, NTIS. 

Chu, T. J., P. A. Krenkel, and R. J. Ruane, 1976, Characterization and Reuse of 
Ash Pond Effluents in Coal-Fired Power Plants, paper presented at 49th 
Annual Water Pollution Control Federation Conference, Minneapolis, Minn., 
Oct. 3-8, 1976. 

, W. R. Nicholas, and R. J. Ruane, 1975, Complete Reuse of Ash Pond 

Effluents in Fossil-Fueled Power Plants, paper presented at 68th Annual 
Meeting of the American Institute of Chemical Engineers, Los Angeles, 
Calif., Nov. 16-20, 1975. 

, R. J. Ruane, and G. R. Steiner, 1976, Characteristics of Wastewater 

Discharges from Coal-Fired Power Plants, paper presented at the 31st Annual 
Purdue Industrial Waste Conference, Purdue University, West Lafayette, 
Ind.,May 4-6, 1976. 

Cooper, H. B., Jr., 1975, The Ultimate Disposal of Ash and Other Solids from 
Electric Power Generation, in Water Management by the Electric Power 
Industry, E. F. Gloyna, H. H. Woodson, and H. R. Drew (Eds.), pp. 183-195, 
Water Resources Symposium No. 8, Center for Research in Water Resources, 
The University of Texas, Austin. 

Daum, R. J., 1969, A Revision of Two Computer Programs for Probit Analysis, 
Bull. Entomol. Soc. Am., 16: 10-15. 

Environmental Protection Agency, 1974, Steam Electric Power Generating Point 
Source Category, Report EPA-440/1-74 029-a, group 1, Environmental 
Protection Agency, GPO. 

, 1976, Quality Criteria for Water, Washington, D. C. 

Freeman, R. A., and W. J. Birge, 1978, Aqueous Leaching of Toxic Metals from 
Coal-Produced Fly Ash, unpublished data. 

Fulkerson, W., et al., 1975, Allen Steam Plant Study, in Energy Division Annual 
Progress Report for Period Ending December 31, 1974, pp. 77-82, ERDA 
Report ORNL-5030, Oak Ridge National Laboratory, NTIS. 

Guthrie, R. K., D. S. Cherry, and J. H. Rodgers, 1974, The Impact of Ash Basin 
Effluent on Biota in the Drainage System, in Mid-Atlantic Industrial Waste 
Conference, Vol. 7, pp. 17-43, Drexel University, Philadelphia, Pa. 

Hildebrand, S. G., R. M. Cushman, and J. A. Carter, 1976, The Potential 
Toxicity and Bioaccumulation in Aquatic Systems of Trace Elements Present 
in Aqueous Coal Conversion Effluents, in Trace Substances in Environmental 
Health— X, D. D. Hemphill (Ed.), pp. 305-313, University of Missouri Press, 
Columbia, Mo. 

Holland, W. F., K. A. Wilde, J. L. Parr, P. S. Lowell, and R. F. Pohler, 1975, The 
Environmental Effects of Trace Elements in the Pond Disposal of Ash and 



240 BIRGE 

Flue Gas Desulfurization Sludge, prepared by Radian Corporation, Austin, 
Tex., for the Electric Power Research Institute, Palo Alto, Calif. 

Lloyd, W. G., 1976, Mercury in Texas Coal Samples, unpublished report, 
Institute for Mining and Minerals Research, University of Kentucky, 
Lexington. 

Moulton, L. K., 1973, Bottom Ash and Boiler Slag, m Information Circular No. 
8640, U. S. Bureau of Mines, Pittsburgh, Pa. 

National Academy of Sciences— National Academy of Engineering Committee on 
Water Quality Criteria, 1973, Water Quality Criteria 1972, GPO. 

Perkin— Elmer Corp., 1973, Analytical Methods for Atomic Absorption 
Spectrophotometry, Norwalk, Conn. 

Rubin, E. S., and A. McMichael, 1974, Some Implications of Environmental 
Regulatory Activities on Coal Conversion Processes, in Environmental 
Aspects of Fuel Conversion Technology, Symposium Proceedings, St. Louis, 
Mo., May 13-15, 1974, pp. 69-90, Report EPA-650/2-74-118, Environ- 
mental Protection Agency, NTIS. 

Ruch, R. R., H. J. Gluskoter, and N. F. Shimp, 1974, Distribution of Trace 
Elements in Coal, in Environmental Aspects of Fuel Conversion Technology, 
Symposium Proceedings, St. Louis, Mo., May 13—15, 1974, Report 
650/2-74-118, Environmental Protection Agency, NTIS. 

Sheibley, D. W., 1975, Trace Elements by Instrumental Neutron Activation 
Analysis for Pollution Monitoring, in Trace Elements in Fuel, S. P. Babu 
(Ed.), Advances in Chemistry Series, No. 141, pp. 98-117, American 
Chemical Society, Washington, D. C. 

Smith, I. C, T. L. Ferguson, and B. L. Carson, 1975, Metals in New and Used 

Petroleum Products and By-Products Quantities and Sequences, in The 

Role of Trace Metals in Petroleum, T. F. Yen (Ed.), pp. 123-148, Ann Arbor 
Science Pubs., Inc., Ann Arbor, Mich. 

Theis, T. L., 1975, The Potential Trace Metal Contamination of Water Resources 
Through the Disposal of Fly Ash, paper presented at 2nd National 
Conference on Complete Water Reuse, American Institute of Chemical 
Engineers and Environmental Protection Agency, Chicago, 111., May 4—8, 
1975. 

Vaughan, B. E., et al., 1975, Review of Potential Impact on Health and 
Environmental Quality from Metals Entering the Environment as a Result of 
Coal Utilization, ERDA file No. NP-20585, Battelle Pacific Northwest Labs., 
Richland, Wash. 

Vitez, B., 1976, Trace Elements in Flue Gases and Air Quality Criteria, Power 
Eng., January: 56-60. 

Yavorsky, P. M., and S. Akhtar, 1974, Environmental Aspects of Coal 
Liquefaction, in Environmental Aspects of Fuel Conversion Technology, 
Symposium Proceedings, St. Louis, Mo., May 13—15, 1974, pp. 325-330, 
Report EPA-650/2-74-118, Environmental Protection Agency, NTIS. 



MERCURY CONTAMINATION STANDARDS 
FOR MARINE ENVIRONMENTS 



RONALD EISLER 

Environmental Protection Agency, Environmental Research Laboratory, 

Narragansett, Rhode Island 



ABSTRACT 

Selected technical literature on biological and ecological effects of mercury 
compounds on marine and estuarine biota is reviewed. Potential and actual 
hazards to public health through marine vectors are considered. Within this 
framework, approaches for establishing mercury contamination standards in 
saline environments are presented. 



Toxicological aspects of mercury and mercury compounds in coastal 
and offshore environments as a result of anthropogenic or natural 
processes have been extensively reviev^ed elsew^here (D'ltri, 1972; 
Friberg and Vostal, 1972; Gavis and Ferguson, 1972; Harriss, 1971; 
Holden, 1973; Jemelov, Landner, and Larsson, 1975; Keckes and 
Miettinen, 1972; Newberne, 1974). Most of these authorities agree 
on five points. First, forms of mercury v^ith relatively low toxicity 
can be transformed into forms v^^ith very high toxicity through 
biological and other processes. Second, uptake of mercury directly 
from seawater or through biomagnification in marine food chains 
returns mercury to man in concentrated form. Third, mercury 
uptake may result in genetic changes. Fourth, elevated levels of 
mercury in some marine fishes, such as tuna or swordfish, emphasize 
the complexity of both natural mercury cycles and man's impact on 
those cycles. Finally, man's use of mercury should be curtailed 
because, in contrast to some other pollutants, the difference between 
tolerable natural background levels of mercury and harmful levels in 
the environment is exceptionally small. 

241 



242 EISLER 

This paper considers recent material on mercury effects in saline 
waters and recommends useful criteria and promising research 
approaches for incorporating mercury contamination standards that 
will protect marine products of commerce, their food organisms, and 
their predators, including man. 

HISTORICAL REVIEW 
Laboratory Studies 

Comparative Toxicity, Survival, and Biotic and Abiotic Modifiers 

In general, salts of mercury and its organic compounds have been 
shown in short-term bioassays to be more toxic to marine organisms 
than are salts of other heavy metals. To oyster embryos, for example, 
mercury salts were more toxic than were Ag, Cu, Zn, Ni, Pb, Cd, As, 
Cr"^*", Mn, or Al (Calabrese et al., 1973); to clam embryos, mercury 
was the most toxic metal tested, followed by Ag, Zn, Ni, and Pb, in 
that order (Calabrese and Nelson, 1974). Toxicity bioassays of 168 hr 
duration with salts of Hg, Cd, Cr"^^, Ni, and Zn on adults of 
representative marine fishes, crustaceans, bivalve and gastropod 
molluscs, annelids, and echinoderms confirmed that mercury was 
consistently the most toxic metal in this series (Eisler and Hennekey, 
1977). Similar results are reported for marine algae (Berland et al., 
1976); marine fungi (Schneider, 1972); sea urchin eggs (Kobayashi, 
1971); larvae of marine molluscs and crustaceans (Connor, 1972); 
some species of marine polychaete worms (Reish et al., 1976); 
freshwater annelids, insects, and gastropods (Rehwoldt et al., 1972); 
crustaceans (Cabejszek and Stasiak, 1960); and fish (Weir and Hine, 
1970). 

Acute toxicity values of mercury compounds for various marine 
species are summarized in Table 1. These values are similar to those 
reported for freshwater groups (McKim, 1977). Differences in species 
resistance to mercury compounds (Hendrick and Everett, 1965; 
Schweiger, 1957; Wisely and Blick, 1967) may account for some of 
the variability in test results shown in Table 1, but many additional 
factors are known to affect or modify the survival time of 
mercury -stressed marine biota, sometimes by one order of magnitude 
or more. Abiotic modifiers include the chemical form of mercury 
administered (Boetius, 1960; Boney, 1971; Boney and Corner, 1959; 
Boney, Corner, and Sparrow, 1959; Corner and Sparrow, 1957; Ellis, 
1947; Fang, 1973; MacLeod and Pessali, 1973; Middaugh and Rose, 
1974); cations other than mercury present in the medium (Barnes 



MERCURY CONTAMINATION STANDARDS 



243 



TABLE 1 

ACUTE TOXICITY OF MERCURY COMPOUNDS TO VARIOUS 
SPECIES OF MARINE BIOTA* 



Species 



Concentration 



Effect 



Reference 



Algae 
18 spp. 

8 spp. 



10-25 
12-8,000 



5 spp. 


60 


Laminaria hyperboria 


2,500 


Coelenterata 




Eirene viridula 


300 


Echinodermata 




Acanthocidaris 


18-46 


crassispina eggs 




Asterias forbesi 


10 


Asterias forbesi 


20 


Asterias forbesi 


125 


Annelida 




Neanthes arenaceodentata 


22-100 


Neanthes arenaceodentata 


17—90 


Capitella capitata 


14-<100 


Capitella capitata 


100 


Nereis uirens 


25 


Nereis virens 


60 


Nereis uirens 


125 


Ophryotrocha labronica 


1,000 


Mollusca 




My a arenaria 


1 


Mya arenaria 


4 


Mya arenaria 


30 


Mercenaria mercenaria 


2.5 


embryos 




Mercenaria mercenaria 


4.8 


embryos 




Mercenaria mercenaria 


7.5 


embryos 




Crassostrea virginica 


1.0 


embryos 




Crassostrea virginica 


5.6 


embryos 




Crassostrea virginica 


8.0 


embryos 





LCioo (17 days) Berland et al., 

1976 
Boney, 1971; 
Boney and 
Corner, 
1959 
Ukeles, 1962 
Hopkins and 
Kain, 1971 



LCso (0.5-iir 
exposure plus 
168-iir 
postexposure 

LCi 

LCioo (24 hr) 



LCioo (3hr) 

LCioo (48 hr) 

LCo (168 hr) 
LCso (168 hr) 
LCioo (168 hr)^ 

LCso (96 hr) ] 
LCso (28 days) I 
LC5o(96hr) r 
LCso (28 days) J 
LCo (168 hr) 
LCso (168 hr) 
LCioo (168 hr) 
LCso (0.5 hr) 



LCo (168 hr) 
LCso (168 hr) 
LCioo (168 hr) 
LCo (48 hr) 

LCso (48 hr) 

LCioo (48 hr) 

LCo (48 hr) 

LCso (48 hr) 



Karbe, 1972 

Kobayshi, 

1971 
Eisler and 

Hennekey, 

1977 



Reish et al., 
1976 

Eisler and 

Hennekey, 

1977 
Brown and 

AhsanuUah, 

1971 

Eisler and 
Hennekey, 
1977 

Calabrese 
and Nelson, 
1974 



Calabrese 
etal., 1973 



LC.oo (48 hr) 

(Table continues on following page.) 



244 



EISLER 



Table 1 (Continued) 



Species 


Concentration 


Effect 


Reference 


Mollusca (continued) 








Crassostrea virginica 


50 


LCso (19 days) 


Kopfler, 1974 


Argopecten irradians 


89 


LCso (96 hr) 


Nelson et al., 
1976 


Nassarius obsoletus 


100 


LCo (168 hr) ^ 


Eisler and 


Nassarius obsoletus 


700 


LCso (168 hr) 


> Hennekey, 


Nassarius obsoletus 


5,000 


LCioo (168 hr) 


1977 


Congeria leucophaeta 


1,000 


LC20 (48 hr) ^ 
LC.oo (48hr)i 


Dorn, 1974 


Congeria leucophaeta 


10,000 


Cardium edule 


10,000 


LC50 (48 hr) 


Portmann, 
1968 


Rangia cuneata 


6,300- 


LC50 (48 hr) 


Olson and 




40,000 




Harrel, 1973 


Crustacea 








Tigriopus japonicus 


6 


LCioo (72 hr) 


D'Agostino 
and Finney, 
1974 


Paneus setiferus 


17 


LCso (96 hr) 


Green et al., 


postlarvae 






1976 


Pagurus longicarpus 


10 


LCo (168 hr) 


Eisler and 


Pagurus longicarpus 


50 


LCso (168 hr) 


^ Hennekey, 


Pagurus longicarpus 


125 


LCioo (168 hr). 


1977 


Petrolisthes armatus 


50-64 


LCso (96 hr) 


Roesijadi 
etal., 1974 


Sesarma sp. 


60 


LCso (24 hr) 


Okubo and 
Okubo, 1962 


Pandalus montague 


100 


LC50 (48 hr) 


Portmann, 
1968 


Uca pugilator larvae 


180 


LC,oo (24 hr) 


DeCoursey and 
Vernberg, 
1972 


Uca pugilator 


1,000 


LCeo (28 days) 


Weis, 1976 


Nitocra spinopes 


600 


LCso (24 hr) 


Barnes and 
Stanbury, 








1948 


Carcinus maenus 


1,000 


LCso (48 hr) 


Portmann, 
1968 


Balanus balanoides 


1,000 


LC90 (48 hr) 


Clarke, 1947 


Crangon crangon 


6,000 


LCso (48 hr) 


Portmann, 
1968 


Artemia salina 


1,000 


LCso (25 hr) 


Brown and 

Ahsanullah, 
1971 


Artemia salina 


21,000- 


LCso (24 hr) 


Okubo and 




50,000 




Okubo, 1962 



(Table continues on following page.) 



MERCURY CONTAMINATION STANDARDS 



245 



Table 1 (Continued) 



Species 


Concentration 


Effect 


Reference 


Teleosts 








Mugil cephalus 


500 


LCss (3hr)' 


Middaugh 


Mugil cephalus 


50 


LCo (3hr) > 


and Rose, 
1974 


Fundulus heteroclitus 


100 


LCo (168 hr) " 


Eisler and 


Fundulus heteroclitus 


800 


LCso (168 hr) > 


Hennekey, 


Fundulus heteroclitus 


1,000 


LCioo (168 hr) 


1977 


Fundulus heteroclitus 


1,000 


LCioo (168 hr)^ 
LCioo (264 hr)/ 


Weis and 


Fundulus heteroclitus 


100 


Weis, 1976 


Fundulus heteroclitus 


860 


LCo (96 hr) ^ 


Klaunig, Koepp, 


Fundulus heteroclitus 


2,000 


LCso (96 hr) ^ 


and McCormick, 


Fundulus heteroclitus 


4,600 


LCioo (96 hr) 


1975 



*Concentrations are in micrograms per liter (ppb) of total mercury added at 
start of the experiment which were lethal to specified percentage within the 
indicated time frame. 



and Stanbury, 1948; Corner and Sparrow, 1956; Gray, 1974; Gray 
and Ventilla, 1973; Hunter, 1949; Lask et al., 1971); anion concen- 
tration in the medium (Amend, Yasutake, and Morgan, 1969; Lask 
et al., 1971); complexing agents in solution (Boney and Corner, 
1959; Eisler et al., 1972; Nishikawa and Tabata, 1969; Tabata and 
Nishikawa, 1969); presence of surface active agents (Calamari and 
Marchetti, 1973; Eisler et al., 1972); rate at which mercury was 
administered (Corner and Rigler, 1957; Gillespie, 1972; Horn and 
Katz, 1946); temperature of the water (Amend, Yasutake, and 
Morgan, 1969; Ballard and Oliff, 1969; Boney and Corner, 1959; 
Clemens and Sneed, 1958; Jones, 1973; Lask et al., 1971; MacLeod 
and Pessah, 1973; Portmann, 1968; Rodgers et al., 1951; Vernberg, 
DeCoursey, and O'Hara, 1974; Vernberg and O'Hara, 1972; Vernberg 
and Vernberg, 1972); seasonal differences, as distinct from tempera- 
ture (Vernberg, DeCoursey, and O'Hara, 1974); dissolved oxygen 
content (Amend, Yasutake, and Morgan, 1969); pH (Lask et al., 
1971); and salinity of the medium (Binet and Nicolle, 1940; Boetius, 
1960; Hunter, 1949; Jones, 1973; 1975; Olson and Harrel, 1973; 
Pyefinch and Mott, 1948; Roesijadi et al., 1974; Schneider, 1972; 
Vernberg, DeCoursey, and O'Hara, 1974; Vernberg and Vernberg, 
1972). Biological factors modifying the mercury survival response of 
marine organisms include: age of test organisms (Connor, 1972; 
Green et al., 1976; Okubo and Okubo, 1962; Portmann, 1968; Reish 
et al., 1976; Vernberg, DeCoursey, and O'Hara, 1974; Wilson and 



246 EISLER 

Connor, 1971); sex (Vernberg, DeCoursey, and O'Hara, 1974; 
Vernberg and Vernberg, 1972); general health of animal (Portmann, 
1968; Shealy and Sandifer, 1975); previous exposure to organic 
compounds (Boney and Corner, 1959); or to mercury (Corner and 
Sparrow, 1956; Foster and Olson, 1951; Gillespie, 1972; Green et al., 
1976); moulting stage of crustaceans (Wilson and Connor, 1971); and 
presence of parasites (Clemens and Sneed, 1958). 

It was not possible to document a specific trend for any 
individual modifier. Some studies showed relatively short survival 
times at comparatively high temperatures, and others demonstrated 
unchanged survival times for some species at a At of 10° C or more. 
Most studies, however, showed that previous exposure to mercury 
salts was in some way associated with increased sensitivity to 
mercury and other stressors; shrimp were an exception. Pre-exposure 
of shrimp for 57 days to 1.0 /jg Hg/liter did not affect LC^o values 
(Green et al., 1976). There was general agreement that organo- 
mercury compounds were more toxic than inorganic compounds; 
that chelating agents in combination with mercury salts produced 
less-than-additive toxicity but other compounds, especially salts of 
copper, lead, or zinc act synergistically to increase toxicity; and 
that salinity stress, especially abnormally low salinities, reduced 
significantly the survival time of mercury-exposed organisms. The 
evidence suggests that species adapted to a fluctuating estuarine 
environment could be more vulnerable to the added stresses of heavy 
metal pollution, including mercury, than species inhabiting more 
uniformly stable environments (Jones, 1973). 

Sublethal and Latent Effects 

Mercury adversely affects various metabolic processes essential to 
normal growth, development, reproduction, and general well-being of 
marine and estuarine biota. Typically, metabolic effects are mani- 
fested at mercury concentrations that are orders of magnitude below 
those producing death. Morphological variations, for example, occur 
in dinoflagellates at 1.0 /ig Hg/liter (Kayser, 1976), and teratogenic 
effects, such as the abnormal growth of multiple eyes and tentacles, 
are found in marine gastropods exposed only as embryos for 3 to 24 
days to 10.0 /ug Hg/liter (Reinhart and Myers, 1975). Exposure of 
shrimp larvae for 48 hr to high sublethal mercury levels is associated 
with reduced survival at post larval stage, delayed molting, extended 
development time, and morphological deformities (Shealy and 
Sandifer, 1975). At 1/lOOth of the lethal concentration, mercury 
disrupts avoidance-learning responses in fish (Weir and Hine, 1970), 
and, in fact, mercury is more effective in reducing these conditioned 



MERCURY CONTAMINATION STANDARDS 247 

responses than are salts of arsenic, lead, or selenium (Weir and Hine, 
1970). Altered feeding behavior and appetite reduction during and 
after exposure to mercury salts are documented for teleosts (Klaunig, 
Koepp, and McCormick, 1975; Rodgers et al., 1951; Salzinger et al., 
1973) and mussels (Dorn, 1976). 

Mercury-induced growth inhibition is reported for several marine 
species. The sediment-living, ciliate protozoan Cristigera exhibited 
reduction in growth during immersion in 2.5 to 5.0 )Ug Hg/liter 
(Gray, 1974; Gray and Ventilla, 1973); synergistic effects of Hg— Cu 
and Hg— Pb mixtures on Cristigera growth were also recorded (Gray 
and Ventilla, 1971). Growth of the colonial, marine hydro id 
Campanularia flexuosa was depressed during immersion for 11 days 
in 1.6 to 1.7 iUg Hg/liter; however, growth stimulation occurred in 
1.0 /ig Hg/liter between days 3 and 7 (Stebbing, 1976). Kelps and 
other species of algae exhibited growth inhibition during immersion 
in <5.0 to 350.0 jug Hg/liter (Berland et al., 1976; Boney, 1971; 
Clendenning and North, 1959; Kayser, 1976; Sick and Windom, 
1975); similar results were observed for various bacteria (Ben-Bassat 
et al., 1972). Photosynthesis was reduced in several species of marine 
alga during immersion in 0.06 to 10.0 jUg Hg/liter; pronounced 
effects were consistently induced by organomercury compounds at 
concentrations of 1.0 /ug/liter (Harriss, White, and MacFarlane, 1970; 
Hopkins and Kain, 1971; Nuzzi, 1972). Recovery of algae to control 
growth levels after initial mercury -induced inhibition was also 
reported (Davies, 1974). 

Mercury disrupts various reproductive processes of aquatic 
organisms, including fecundity, egg deposition, and hatching fre- 
quency. Concentrations between 32 and 92 jug Hg/liter seriously 
impair development of sea urchin embryos (Okubo and Okubo, 
1962; Waterman, 1937); higher concentrations (1,000 /Jg/liter) were 
necessary to produce a similar effect on marine protozoa (Persoone 
and Uyttersprot, 1975). Flagellar contractility of sea urchin sperm 
was inhibited during immersion in 20 to 200 jug Hg/liter (Young and 
Nelson, 1974); however, mercury was exceeded in this effect by Cd, 
Cu, Zn, and Fe (Morisawa and Mohri, 1974). Teleost zygotes 
fertilized and incubated in water containing at least 0.2 /ug Hg/liter 
exhibit a reduced hatching rate (Kihlstrom, Lundberg, and Hulth, 
1971). The number of teleost eggs deposited decreases when the 
concentration of organomercury compounds is 1.0 ^ig Hg/liter or 
greater (Kihlstrom, Lundberg, and Hulth, 1971). Eggs fertilized in 
mercury-free water and then allowed to develop under various 
mercury regimes exhibited increased hatch at 10.0 jug Hg/liter but 
reduced or negligible hatch at 50.0 jug Hg/liter (Kihlstrom and Hulth, 



248 EISLER 

1972). Mercury also inhibits zoospore activity and subsequent 
development of sporangia in marine fungi (Schneider, 1972). 

Mercury interferes w^ith enzyme production or activity in marine 
teleosts, including brain cholinesterase (Abou-Donia and Menzel, 
1967), blood transaminases and dehydrogenases (Christensen, 1971), 
hemopoietic Na—K—ATPase activities (Renfro et al., 1974), and liver 
aminolevulinate dehydrases and other enzymes (Jackim, 1973; 
Jackim, Hamlin, and Sonis, 1970). Low levels, 5.0 Mg Hg/liter, 
increased allantoise formation in marine annelids, but higher levels 
prevent formation (May and Brown, 1973). Enzyme activities may 
have potential as an early warning system of mercury -induced stress. 
For example, a concentration of 0.17 fig Hg/liter, one-tenth the level 
causing growth inhibition of marine hydroids, inhibited the lyso- 
somal hydrolase staining reaction in that group (Moore and Stebbing, 
1976). 

Histopathological damage was observed among marine teleosts 
subjected to 500 [ig Hg/liter; damage was most severe in olfactory 
organs and in the lateral line system (Gardner, 1975). An observed 
dose-related increase in mantle tentacle epithelial cells of mercury- 
treated clams (Fowler, Wolfe, and Hettler, 1975) suggests that 
histological studies might also make it possible to predict impending 
mercury stress. 

Mercury affects oxygen consumption and ventilation rates of 
aquatic animals. Increased respiration of the mollusc Congeria 
leucophaeta was observed during immersion in 10.0 /ig Hg/liter for 
48 hr (Dom, 1974). Concentrations of 3.0 /ig Hg/liter caused a 
significant increase in "cough frequency" of trout, and this may 
alter oxygen consumption in that species (Drummond, Olson, and 
Batterman, 1974). Larvae of the fiddler crab Uca pugilator exposed 
to 1.8 fig Hg/liter for 24 hr showed a marked reduction in swimming 
ability and reduction in general metabolic processes, including 
oxygen consumption (DeCoursey and Vernberg, 1972). Marine 
teleosts exposed for 60 days to 10.0 /ug Hg/liter exhibited elevated 
respiration rates, and, at 5.0 jug/liter, there were increases in plasma 
proteins and decreases in plasma osmolality (Calabrese et al., 1975). 

Studies with antifouling compounds suggest that mercury is 
relatively ineffective in preventing metamorphosis of barnacles 
attached to glass plates (Clarke, 1947). Some mariculture studies 
have indicated that low concentrations of mercury salts for short 
periods have either no measurable effect or beneficial, therapeutic, or 
prophylactic applications (Green et al., 1976; Rodgers et al., 1951; 
Rucker and Amend, 1969). The preponderance of studies, however, 
seems to demonstrate that mercury adversely affects several vital life 



MERCURY CONTAMINATION STANDARDS 249 

processes of marine organisms at concentrations as low as 0.2 and 
1.0 )Ug/liter. In addition to the deleterious effects previously listed on 
behavior, growth, reproduction, histology, respiration, and enzyme 
production, there are a variety of mercury -related effects that are 
imperfectly understood. These include increased mucous production 
in fish (Gardner, 1975; Lask et al., 1971); initiation of diuresis in 
amphipods (Lockwood and Inman, 1975); a rise in urine nitrogen 
levels of mercury-poisoned crabs (Corner, 1959); altered osmoregula- 
tory ability of estuarine isopods (Jones, 1975); and negative 
phototaxy and increased operculate movements of teleosts (Klaunig, 
Koepp, and McCormick, 1975). Increased efficiency of mercury 
transport mechanisms has also been noted in crabs exposed at 
comparatively high temperatures (Vernberg and O'Hara, 1972). 

Uptake, Retention, and Translocation 

Rapid accumulation of mercury, especially organomercury com- 
pounds, by various species of marine biota, primarily teleosts and 
molluscs, is well documented (Bligh, 1972; Boulton and Hetling, 
1972; Cunningham and Tripp, 1975a; 1975b; Davies, 1974; Fang, 
1973; Fowler, Wolfe, and Hettler, 1975; Hannerz, 1968; Hasselrot, 
1968; Hibiya and Oguri, 1961; Johnels et al., 1967; Kramer and 
Neidhart, 1975; Lask et al., 1971; Laumond et al., 1973; MacLeod 
and Pessah, 1973; McKone et al., 1971; Middaugh and Rose, 1974; 
Nelson et al., 1976; Olson, Bergman, and Fromm, 1973; Pentreath, 
1976a; 1976b; Rucker and Amend, 1969). Bioaccumulation of 
mercury and its compounds from seawater can be modified by many 
factors. These include chemical form of mercury administered 
(Cunningham and Tripp, 1975a; Hannerz, 1968; Kramer and 
Neidhart, 1975; Pentreath, 1976a; 1976b); mode of administration 
(Jarvenpaa, Tillander, and Miettinen, 1970); presence of complexing 
agents in medium (Kramer and Neidhart, 1975); initial concentration 
(Kramer and Neidhart, 1975; Sick and Windom, 1975); exposure 
time (Sick and Windom, 1975); presence of selenium (Fowler and 
Benayoun, 1976); salinity of medium (Vernberg, DeCoursey, and 
O'Hara, 1974); water temperature (Cunningham and Tripp, 1975b; 
Vernberg, DeCoursey, and O'Hara, 1974); age of organism (Beckett 
and Freeman, 1974; Cunningham and Tripp, 1975b; Glooschenko, 
1969; Hannerz, 1968); biological surface area (Sick and Windom, 
1975); variability in detoxication mechanisms (Davies, 1976); sexual 
condition (Cunningham and Tripp, 1975b); tissue specificity (Cun- 
ningham and Tripp, 1975a; Fowler, Wolfe, and Hettler, 1975; 
Hannerz, 1968; Pentreath, 1976a; 1976b; Vernberg, DeCoursey, and 
O'Hara, 1974); presence of mercury -resistant strains of bacteria 



250 EISLER 

(Colwell and Nelson, 1975; Colwell et al., 1976); and accumulation 
after death (Glooschenko, 1969). Two studies, both on adult 
American oysters, Crassostrea virginica, are worth emphasizing. 
Cunningham and Tripp (1973) held oysters in seawater containing 
10 [ig Hg/liter as mercuric acetate. After 45 days the whole-body 
mercury concentration of exposed animals was 28,000 Mg/kg wet 
weight. The mercury concentration in control oysters was always less 
than 20 Mg/kg wet weight. The mercury concentration in exposed 
oysters dropped to 18,000 Mg/kg by day 60, probably because of 
spawning. At day 60, oysters were transferred to mercury-free 
seawater for 160 days. During the first 18 days, levels declined to 
15,000 /ig Hg/kg, but thereafter no further decline occurred. It was 
concluded that oysters can concentrate 10 jug Hg/liter by a factor of 
2800 and that total self-purification was not achieved over a 6-month 
cleansing period. Kopfler (1974) found that continuous exposure to 
1 jUg Hg/liter in any of the three mercury compounds tested caused 
oysters to concentrate mercury rapidly in their tissues far in excess 
of 0.5 mg/kg wet weight, i.e., at levels potentially hazardous to 
humans ingesting these oysters, according to the action guideline 
established by the Food and Drug Administration. Details of 
Kopfler's study follow: 

Accumulation of mercury compounds by oysters was determined in two 
experiments, each utilizing three groups of 100 adult oysters. In the first 
experiment, conducted between and 10 C, mercury levels were main- 
tained at 50 /ig/1 with flow rate adjusted to one liter per oyster per hour. 
In the second experiment, mercury levels were reduced to one^<g/l, the 
water temperature varied between 25 and 35 C, and flow rates maintained 
at 2 1/oyster/hr because of the increased temperature. Controls were 
maintained for each study. In the first experiment, the administration of 
organic mercury compounds was terminated after 19 days because many 
of the oysters in the groups receiving salts of either methylmercury or 
phenylmercury were dead or moribund. Oysters classified as moribund 
exhibited slow, incomplete valve closure when disturbed. When oysters 
which survived 19 days of exposure to methylmercury and phenylmercury 
were placed in flowing seawater, about half in each group died within a 
week with all oysters in both groups dead within 14 days. Oysters exposed 
to inorganic mercuric chloride exhibited no apparent ill effects over a 
42-day period of exposure to 50 ;Ug/l of Hg. Mean mercury levels in 
experimentals after one week was lOOOX over controls. Mercury values in 
experimental oysters at 7 days, in mg Hg/kg wet wt, ranged between 15 
and 25; for controls this was 0.02. Copper and zinc levels were depressed 
in flesh from all three groups of oysters after one week exposure to 
mercury; in the two groups exposed to organomercury, Cu and Zn 
declined over the 19-day exposure. Copper and zinc levels in the oysters 
exposed to mercuric chloride began to increase during the third week and 
continued to do so until they were essentially the same as control values. 
In the second experiment methyl- and phenylmercury were concentrated 



MERCURY CONTAMINATION STANDARDS 251 

to essentially the same degree, while inorganic mercury was concentrated 
about 4 times less over a 74-day exposure. For organomercury com- 
pounds, values in mg Hg/kg wet weight were about 10 at 20 days and 30 at 
60 days (a final concentration factor of about 30,000). For inorganic 
mercuric chloride, values were about 2 at 20 days and about 10 at 60 days. 

Mercury is also accumulated from seawater by other marine 
organisms. In radiotracer studies, clams {Tapes decussatus) contained 
10 times more ^^ ^Hg per unit weight than the medium within 24 hr 
(Unlu, Heyraud, and Keckes, 1972). Two species of marine alga, 
Chaetoceros galvestonensis and Phaeodactylum tricornutum, con- 
tained 7.4 and 2.4 g/kg of mercury, respectively, when cultured in 
media containing 100 /ig Hg/liter (Chaetoceros) or 50 jug Hg/liter 
(Phaeodactylum) (Hannan et al., 1973). 

Mercury can also be accumulated through food webs. Bacteria 
have a demonstrable effect on mercury accumulation in food chains 
that include filter feeders. Thus whole oyster accumulation of 
mercury more than doubled in the presence of mercury-resistant 
strains of Pseudomonas spp. (Colwell and Nelson, 1975; Colwell 
et al. 1976; Sayler, Nelson, and Colwell, 1975). Sarcophagous flies 
feeding on mercury-contaminated fish muscle accumulated 3 times 
more mercury than their food; this was especially pronounced when 
the fish flesh contained > 0.5 mg Hg/kg wet weight (Nuorteva and 
Hasanen, 1972). A similar pattern was noted among wild fish feeding 
on mercury-contaminated fingerlings (Rucker and Amend, 1969). In 
the food chain algae-detritus— worm— fish (prey)— fish (predator), 
mercury had a long biological half-life, > 1000 days in predatory fish 
compared with about 55 days in prey fish (Huckabee and Blaylock, 
1972). The transfer efficiency of inorganic mercury from prey to 
predator fish was about 40% but from worm to prey fish, only 12%; 
worms assimilated 60% of the inorganic mercury contained in the 
algae-detritus. Huckabee and Blaylock concluded that food-chain 
uptake can account for a significant percentage of the mercury body 
burden in fish. In an algae-to-copepod food link, however, the 
Crustacea showed no impairment of egg laying or egg development 
and no retention of mercury in tissues, eggs, or feces (Parrish and 
Carr, 1976). No progressive mercury concentration was observed in a 
clam-to-eel transfer (Tsuruga, 1963). When dogfish meal containing 
up to 2.3 mg total Hg/kg, of which 1.9 mg/kg was methyl mercury, 
replaced low-mercury fish rations used in salmon culture, the flesh of 
the salmon contained > 0.5 mg/kg within 240 days (Spinelli and 
Mahnken, 1976). When dogfish meal comprised less than half the 
diet, however, mercury levels in salmon flesh were < 0.5 mg/kg. 
Similar results were observed among sablefish fed dogfish meal 
(Kennedy and Smith, 1972). 



252 EISLER 

Skeletal muscle of teleosts appears to function as a reservoir for 
methyl mercury (Giblin and Massaro, 1973; Johnels et al., 1967; 
MacLeod and Pessah, 1973; Middaugh and Rose, 1974; Pentreath, 
1976b; Weisbart, 1973). Maximum concentration factors of radio- 
mercury were reached in skeletal muscle, brain, and lens after 34, 56, 
and >90 days, respectively; maximum values were reached in most 
other tissues and organs in about 7 days (Giblin and Massaro, 1973). 
One pathway by which anadromous fishes accumulate mercury from 
a medium is through the gills; up to 90% of the mercury taken up on 
the gills is subsequently bound to erythrocytes within 40 min (Olson, 
Bergman, and Fromm, 1973; Olson and Fromm, 1973). 

The retention time of mercury in marine organisms depends on 
several factors. Weisbart (1973) found that the gill, heart, and 
swim-bladder tissues of fish lost mercury at rates faster than the 
whole organism, but some tissues, including brain, liver, muscle, and 
kidney, showed no significant decrease with time. In clams radio- 
mercury seems to have a biological half-life of 10 days if accumu- 
lated via the food chain but only 5 days if taken up from the water 
(Unlu, Heyraud, and Keckes, 1972). Retention times of ^°^Hg in 
most marine species were comparatively lengthy, ranging from 267 
days for the fish Serranus scriba to 1000 days for mussels, Mytilus 
galloprouincialis (Miettinen, Heyraud, and Keckes, 1972; Miettinen 
etal., 1969; 1972). Miettinen and coworkers found that phylogenet- 
ically related species follow a similar pattern of methyl mercury 
excretion, with biological half-life depending on water temperature 
and mode of entry into organisms; it is longer after intramuscular 
injection than after peroral administration. There is some evidence 
that mercury excretion rates follow a biphasic or polyphasic pattern 
(Burrows and Krenkel, 1973; Giblin and Massaro, 1973; Tillander, 
Miettinen, and Koivisto, 1972; Weisbart, 1973). Tillander, Miettinen, 
and Koivisto found that, in seals, Pusa hispada, the fastest excreted 
component took 20 days for 50% elimination and the slowest 
excreted mercury fraction, which comprised 45% of all mercury, 500 
days for 50% elimination. 

Field Investigations 

Residues in Water and Sediments 

Mercury levels in coastal seawater from various locations ranged 
from 0.021 to 0.078 Mg/liter (Dehlinger et al., 1973); concentrations 
were lower in continental slope water, ranging from 0.010 to 
0.041 jug/liter. Mercury levels in water were several orders of 



MERCURY CONTAMINATION STANDARDS 253 

magnitude higher in the vicinity of chlor^-alkali plants and similar 
industrial operations (Kazantzis, 1971). Mercury levels in sediments 
varied widely and tended to be elevated in the neighborhood of 
sewer outfalls (Klein and Goldberg, 1970), sludge disposal areas, and 
especially areas impacted by mercury wastes from industrial opera- 
tions, such as Minamata Bay, Japan (Irukayama, 1967). Vucetic, 
Vernberg, and Anderson (1974) reported values ranging from 130 to 
1500 /ig/kg of mercury in sediments in the Adriatic Sea, and Williams 
and Weiss (1973) found 390 ^ig/kg in pelagic clays collected 430 km 
southeast of San Diego, Calif. It is reported that mercury in seawater 
exists almost entirely bound to suspended particles (Jemelov et al., 
1972), that the surface area of sediment granules is instrumental in 
determining final mercury content (Renzoni, Bacci, and Falciai, 
1974), that conversion and transformations occur in the surface layer 
of the sediment or on suspended organic particles in the water (Dean, 
1972; Fagerstrom and Jernelov, 1972; Jernelov et al., 1972), and, 
finally, that mercury-containing sediments would require many 
decades to purge themselves naturally to background levels (Langley, 
1973). 

Mercury— sediment— water interactions affect uptake by marine 
life. Bivalves can accumulate mercury directly from seawater, and 
molluscs had higher concentrations of the metal in turbulent waters 
than in clear waters (Raymont, 1972). Further, marine organisms 
feeding in direct contact w.ith sediment have higher overall mercury 
levels than those feeding above the sediment— water interface 
(Klemmer, Unninayer, and Ukubo, 1976). 

Residues in Biota 

Table 2 summarizes the ranges of concentrations of mercury in 
field collections of marine flora and fauna. These data support the 
findings of other investigators (Cocoros, Cahn, and Siler, 1973; 
Huckabee and Blaylock, 1972; Jernelov and Lann, 1971; Knauer and 
Martin, 1972; Skei, Saunders, and Price, 1976; Stickney et al., 1975), 
who demonstrated that the efficiency of mercury transfer through 
natural marine food chains among lower trophic levels is compara- 
tively low. Higher trophic levels, such as fishes, fish-eating birds, and 
mammals, however, exhibit marked mercury amplification. The 
variability of concentrations is partly explainable in terms of 
collection locale; some field collections were taken from areas where 
human activities have raised the mercury content in the aquatic 
environment above natural levels, thus producing a significant 
increase in the mercury content of endemic fauna (Hearnden, 1970; 
Johnels et al., 1967; Kazantzis, 1971; Kleinert and Degurse, 1972; 



254 



EISLER 



TABLE 2 

RANGE IN CONCENTRATIONS OF MERCURY (Mg/kg wet weight) 

REPORTED FROM FIELD COLLECTIONS OF 

MARINE BIOTA 



Sample 



Concentration 



Reference 



Algae 



Higher aquatic 
plants 

Porifera 

Coelenterata 

Tunicata 

Echinodermata 

Annelida 

MoUusca 



Crustacea 



Insecta 



40—2,000 Greig, Wenzloff, and Shelpuk, 1975; Haug, 

Melsom, and Omang, 1974; Leatherland and 
Burton, 1974; Lulic and Strohal, 1974 
10—8,700 Gardner et al., 1975; Johnson and Braman, 

1975; Lindberg and Harriss, 1974; Windom, 
1973 
330—1,580 Leatherland and Burton, 1974; Williams and 

Weiss, 1973 
70—860 Leatherland and Burton, 1974; Leatherland 

etal., 1973 
60—570 Leatherland and Burton, 1974; Leatherland 

etal., 1973 
280-400 Williams and Weiss, 1973 

350 Leatherland and Burton, 1974 

1—4,440 Anderlini, 1974; Burton and Leatherland, 

1971; Craig, 1967; Greig, Wenzloff, and 
Shelpuk, 1975; Hussain and Bleiler, 1973; 
Irukayama et al., 1962a; 1962b; Laumond 
et al., 1973; Leatherland and Burton, 1974; 
Lulic and Strohal, 1974; Stenner and Nick- 
less, 1975; Thibaud, 1973; Vucetic, Vern- 
berg, and Anderson, 1974; Williams and 
Weiss, 1973; Young, 1974 
5—2,520 DeClerk, Vanderstoppen, and Vyncke, 1974; 

Eftekhari, 1975; Evans, Bails, and D'ltri, 
1972; Greig, Wenzloff, and Shelpuk, 1975; 
Holden and Topping, 1972; Johnson and 
Braman, 1975; Leatherland et al., 1973; 
Raeder and Snekvik, 1949b; Skei, Saunders, 
and Price, 1976; Somayajulu and Rama, 
1972; Stenner and Nickless, 1975; Vucetic, 
Vernberg, and Anderson, 1974; Williams 
and Weiss, 1973 
221—630 Kim, Chu, and Barron, 1974 

(Table continues on following page.) 



Renzoni, Bacci, and Falciai, 1974; Windom, Taylor, and Stickney, 
1973; Wobeser et al., 1970; Zitko et al., 1971). 

Inshore marine biota often contain higher mercury concentra- 
tions than the same or similar species collected offshore (Dehlinger 
etal., 1973; Jones, Jones, and Stewart, 1972; Westoo, 1969). In 



MERCURY CONTAMINATION STANDARDS 
Table 2 (Continued) 



255 



Sample 



Concentration 



Reference 



Elasmobranchs 24—2,080 



Teleosts 



10-6,300 



Birds 
Mammals 



50—65,000 



40-387,000 



Childs and Gaffke, 1973; Childs, Gaffke, and 
Crawford, 1973; Forrester, Ketchen, and 
Wong, 1972; Gardner et al., 1975; Leather- 
land et al., 1973; Peterson, Kalwe, and 
Sharp, 1973; Windom et al., 1973 

Alexander et al., 1973; Arima and Umemoto, 
1976; Barber, Vijayakumar, and Cross, 
1972; Beasley, 1971; Beckett and Freeman, 
1974; Benson et al., 1976; Childs and 
Gaffke, 1973; Cocoros, Cahn, and Siler, 
1973; Cugurraand Maura, 1976; DeGoeij 
and Zegers, 1971; Establier, 1975a; Freeman 
and Home, 1973; Gardner et al., 1975; 
Greig, Wenzloff, and Pearce, 1976; Greig, 
Wenzloff, and Shelpuk, 1975; Greve and 
Wit, 1971; Johnson and Braman, 1975; 
Kamps, Carr, and Miller, 1972; Leatherland 
and Burton, 1974; Lulic and Strohal, 1974; 
Peterson, Kalwe, and Sharp, 1973;Port- 
mann, 1972; Raeder and Snekvik, 1949a; 
1949b; Renzoni, Bacci, and Falciai, 1974; 
Shultz et al., 1976; Stenner and Nickless, 
1975; Stickney et al., 1975; Suzuki, 
Miyama, and Toyama, 1973; Ui and 
Kitamura, 1971; Vucetic, Vernberg, and 
Anderson, 1974; Williams and Weiss, 
1973 ; Windom etal., 1973 

Benson et al., 1976; Berg et al., 1966; 
Koivusaari et al., 1976 

Anas, 1971; 1974; Buhler, Claeys, and Mate, 
1975; Gaskin et al., 1972; 1973; 1974; 
Holden, 1975; Jones et al., 1976; Kim, Chu, 
and Barron, 1974;Koeman et al., 1973; 
Roberts, Heppleston, and Roberts, 1976; 
Robertson et al., 1972; Sergeant and 
Armstrong, 1973; Tillander, Miettinen, 
and Koivisto, 1972 



Sweden, marine fish caught near shore often showed comparatively 
high methyl mercury levels, with many values in the range from 
5,000 to 10,000 [ig/kg wet weight (Ackefors, Lofroth, and Rosen, 
1970; Westoo, 1969); however, levels above 1,000 /Lig/kg in Swedish 
fish are usually caused by industrial discharges of mercury com- 
pounds (Westoo, 1969). 



256 EISLER 

Several observations can be made regarding mercury residues in 
teleosts collected in the field. First, mercury tends to concentrate in 
the edible flesh of finfish, with older fish containing more mercury 
per unit weight than young fish (Alexander et al., 1973; Barber, 
Vijayakumar, and Cross, 1972; Cross et al., 1973; Cumont et al., 
1972; DeClerk, Vanderstoppen, and Vyncke, 1974; Evans, Bails, and 
D'ltri, 1972; Forrester, Ketchen, and Wong, 1972; Giblin and 
Massaro, 1973; Greichus, Greichus, and Emerick, 1973; Hannerz, 
1968; Johnels and Westermark, 1969; Johnels etal., 1967; Kleinert 
and Degurse, 1972; Knight and Herring, 1972; Nuorteva and 
Hasanen, 1971; 1975; Peterson, Kalwe, and Sharp, 1973; Scott and 
Armstrong, 1972; Svansson, 1975; Taylor and Bright, 1973; 
Vermeer, 1972). Second, most of the mercury in fish flesh was in the 
organic form, primarily methyl mercury (Fukui et al., 1973; Kamps, 
Carr, and Miller, 1972; Koeman etal., 1973; Peterson, Kalwe, and 
Sharp, 1973; Rissanen, Erkama, and Miettinen, 1972;Westoo, 1966; 
1969; 1973; Zitko etal., 1971). Third, levels of mercury in muscle 
from adult tunas, billfishes, sharks, and other carnivores were higher 
than those in young fishes with a shorter food chain; this indicates 
associations among predatory behavior, longevity, and mercury 
accumulation (Forrester, Ketchen, and Wong, 1972; Jernelov, 1972; 
Peakall and Lovett, 1972; Peterson, Kalwe, and Sharp, 1973; 
Ratkowsky, Dix, and Wilson, 1975; Saila, 1971; Ui, 1972; Walter, 
June, and Brown, 1973). Finally, elevated levels of mercury in 
wide-ranging oceanic fish are not solely the consequence of anthro- 
pogenic activities but also result from natural concentrations as well 
(Greig, Wenzloff, and Pearce, 1976; Miller et al., 1972; Schultz et al., 
1976). 

Birds that feed on aquatic animals exhibit markedly increased 
concentrations of mercury in comparison with terrestrial raptorial 
species (Johnels and Westermark, 1969; Karppanen and Henriksson, 
1970). Top trophic-level predators, such as cormorants and pelicans, 
demonstrated mercury concentration factors in their flesh of 14- and 
6-fold, respectively, over prey fish (Greichus, Greichus, and Emerick, 
1973). Mercury levels in aquatic and fish-eating birds were elevated 
in the vicinity of chlor— alkali plants where mercury is used as a 
catalyst (Fimreite, 1974; Fimreite etal., 1971); these differences 
were detectable up to 300 km from the chlor— alkali plant (Fimreite 
and Reynolds, 1973). Eggs of fish-eating birds, including herons and 
grebes, collected near mercury point-source discharges contained 
abnormally high levels of mercury; 29% of eggs contained more than 
0.5 mg/kg wet weight, and 9% contained more than 1.0 mg/kg 
(Faber and Hickey, 1973). Seasonal variations in mercury levels 



MERCURY CONTAMINATION STANDARDS 257 

occur in livers of aquatic birds. Higher levels were observed in winter, 
when birds were exclusively estuarine, and drastically lower levels 
were observed in summer when birds migrate to inland Arctic and 
sub-Arctic breeding grounds (Parslow, 1973). 

Diet is an important concentrating mechanism in marine mam- 
mals. Gray seals and harbor seals, which feed on large fish and 
cephalopods, contained 10 times more mercury than harp seals, 
which feed on small pelagic fish and crustacea (Sergeant and 
Armstrong, 1973). Age and tissue specificity also influence mercury 
residue levels. Liver from older sea lions contained more mercury per 
unit weight than that from younger specimens (Anas, 1974; Holden, 
1975; Jones et al., 1976; Sergeant and Armstrong, 1973). Some adult 
seals found dead had high levels of mercury in the brain in 
comparison with levels in various species poisoned by exposure to 
mercury compounds (Koeman et al., 1973). Mercury and selenium 
concentration in livers of marine mammals seem to be positively 
correlated (Koeman et al., 1973; 1975; Martin et al., 1976). Koeman 
and co-workers (1973) suggested that selenium protects these species 
against mercury poisoning by completely binding to subcellular S 
sites, the presumed location of mercury's toxic action. 

Three points are worth emphasizing at this juncture. First, 
mercury discharged into rivers, bays, or estuaries as metallic mercury, 
inorganic divalent mercury, phenyl mercury, or alkoxyalkylmercury 
can all be converted to methyl mercury compounds by natural 
processes (Jernelov, 1969). Second, organomercury complexes are 
rapidly accumulated in tissues with high lipid content (Wood, 1973). 
Finally, mercury -resistant strains of bacteria which have been 
developed or discovered may have application in mercury mobiliza- 
tion or fixation from mercury-contaminated waters to the extent 
that polluted areas become innocuous (Colwell and Nelson, 1975; 
Nelson et al., 1973; Vosjan and Van der Hoek, 1972). 

Minamata 

Any review of mercury hazards in the marine environment 
should include the Minamata Bay incident in southwestern Kyushu, 
Japan. This extensively documented case (Fujiki, 1963; Irukayama, 
1967; Irukayama et al., 1961; 1962a; 1962b; Kiyoura, 1963; 
Kurland, Faro, and Siedler, 1960; Matida and Kumada, 1969; Matida 
etal., 1972; Takevchi, 1972; Tsubaki et al., 1967) reveals effects 
upon man of chronic discharges of low-level methyl mercury wastes 
into coastal waters. The source of mercury was waste discharged 
from an acetaldehyde plant into Minamata Bay beginning in 1952. 



258 EISLER 

Several years later, the mercury levels in sediments near the plant 
outfall were about 2010 mg/kg w^et weight; this decreased sharply 
with distance from the plant. Sediments in the bay contained 
between 0.4 and 3.4 mg Hg/kg wet weight. Concentrations of 
mercury in fish, shellfish, and other food decreased with increasing 
distance from the point of effluence and appeared to reflect 
sediment mercury levels. Late in 1953, a severe neurological disorder 
was recognized among inhabitants of the Minamata Bay region. By 
1956, the outbreak had reached epidemic proportions; 111 cases of 
poisoning were found by the end of 1960; and 41 deaths were 
reported as of August 1965. The poisoning was caused by eating fish 
and shellfish from Minamata Bay and the neighboring sea, except for 
19 congenital cases in children bom of mothers who had eaten the 
same diet. In addition to humans, cats and water fowl living near the 
bay succumbed to the disease. Experimental cats and rats fed fish 
and shellfish collected from the bay developed the same symptoms as 
animals spontaneously affected. Symptoms included cerebellar 
ataxia, constriction of visual fields, dysarthria, and, in congenital 
cases, disturbance of physical and mental development. Pathological 
findings included regressive changes in the cerebellum and the 
cerebral cortexes. The clinico-pathological features resembled alkyl 
mercury poisoning. Abnormal mercury content (i.e., > 30.0 mg 
Hg/kg wet weight) was measured in fish, shellfish, and muds from the 
bay and in organs of necropsied humans and cats that had 
succumbed to the disease. Years after the waste-discharge situation 
was corrected, fish and shellfish still contained levels of mercury 
hazardous to human health. Mercury levels in Minamata fish and 
shellfish were significantly higher than levels shown in Table 2 for 
teleosts and molluscs; note also that the high levels shown for 
mammals in Table 2 are from liver. 

Potential Health Hazards 

The dangerous mercury level in human blood is about 2000 ng/g; 
the normal background level in about 80% of people without 
occupational exposure to mercury is < 5 ng/g (Saha, 1972). Since 
methyl mercury has a biological half-life of 70 to 200 days in man 
(Lofroth, 1970), it is not unexpected that mutagenic and teratogenic 
effects of mercury have been reported at levels well below those 
associated with acute poisoning (Kazan tzis, 1971; Keckes and 
Miettinen, 1972). 

The findings of elevated blood mercury levels, increased human 
chromosome breakage, and easy passage of mercury through 
placental membranes among people who regularly eat fish containing 



MERCURY CONTAMINATION STANDARDS 259 

1 to 17 mg Hg/kg wet weight suggest to some health authorities that 
the currently accepted level in the United States [0.5 mg Hg/kg wet 
weight (500 /ng/kg)] does not have an appreciable level of safety for 
pregnant women (Establier, 1975b; Peakall and Lovett, 1972; 
Skerfving, Hansson, and Lindstem, 1970). In Sweden, the official 
limit for mercury in fish is 1.0 mg/kg wet flesh. Human risk in 
consumption of mercury-contaminated fish within this guideline is 
considered negligible in that country (Berglund and Berlin, 1969); 
however, some Scandinavian scientists recommend that fish con- 
sumption should be limited to one meal a week (Lofroth, 1970). 

Selected Studies 

Mercury retention by teleost species is variable. In one study, 
when northern pike from a lake that was heavily contaminated with 
mercury were transplanted to waters relatively free of mercury, only 
30% of the mercury in their muscle was eliminated in 1 year 
(Lockhart et al., 1972). A study by Amend (1970) of juvenile sockeye 
salmon indicated that fish treated repeatedly with mercurials during 
their freshwater phase accumulated and retained high levels of 
mercury for several months, but, after 4 years at sea, the returning 
salmon contained normal levels of mercury in all tissues examined. 

A number of investigators report that mercury from point-source 
discharges, including sewer outfalls and chloi^alkali plants, was 
taken up by sediments; sediment levels were eventually reflected by 
an increased mercury content of epibenthic fauna (Dehlinger et al., 
1973; Hoggins and Brooks, 1973; Klein and Goldberg, 1970; 
Klemmer, Luoma, and Lau, 1973; Parsons, Bawden, and Heath, 
1973; Takevchi, 1972). Analysis of the effluent from the Hyperion 
sewer outfall in Los Angeles showed a mercury content slightly 
below 1 /jg/liter (Klein and Goldberg, 1970). Concentrations of 
mercury in sediments near this outfall were as high as 820 jug/kg but 
decreased with increasing distance from the outfall; mercury levels in 
epibenthic fauna, including crabs, whelks, and scallops, were also 
highest near the discharge and lowest tens of kilometers away. 

A mercury budget for estuaries along the Georgia coast indicates 
that the dominant salt-marsh plant, Spartina alterniflora, exerts a 
strong control on mercury migration (Gardner et al., 1975;Windom 
et al., 1976; Windom, 1973). Mercury entered the estuary primarily 
in solution, delivering ~1.5 mg annually to each square meter of salt 
marsh. Annual uptake of mercury by S. alterniflora alone was about 
0.7 mg/m^ salt marsh. Mangrove vegetation plays a similarly im- 
portant role in mercury cycling in the Florida everglades (Lindberg 
and Harriss, 1974; Tripp and Harriss, 1976). 



260 EISLER 

RECOMMENDATIONS 

On the basis of these studies, it appears that establishing marine 
mercury-contamination standards requires abatement of existing 
discharges, development of technologies to decontaminate polluted 
waterways, monitoring criteria for protecting human health, and 
research to modify existing standards, as well as to predict impending 
mercury stress in marine ecosystems. Specific recommendations are 
listed. 

1. Prohibit the sale, manufacture, and use of methyl mercury 
compounds. All evidence presented to date implicates methyl 
mercury as the most toxic chemical form of mercury. Its demon- 
strated deleterious effects to mcirine biota and human health 
mandate passage of legislation banning all environmental uses of 
methyl mercury compounds. In the decade since Sweden prohibited 
agricultural use of methyl mercury for seed coatings and pesticides, 
bird populations have begun to recover and the amounts of mercury 
in many types of food have decreased (Johnels and Westermark, 
1969). 

2. Restrict use of other mercurials. Investigations are presently in 
progress in several countries on the geochemistry and biogeo- 
chemistry of mercury, but much remains to be learned about its 
distribution, its conversion from one form to another, and its 
transport on a global basis. It is well known, however, that inorganic 
mercury compounds can be converted in nature to organomercury 
compounds, which are more readily transported and accumulated in 
tissues. Accordingly, legislation is needed which will curtail environ- 
mental use of all mercury compounds, especially organomercurials. 

3. Develop alternative technologies. About 90% of the mercury 
consumed annuEilly is used for industrial purposes. Mercury is used as 
a catalyst in chlor— alkali plants, as a slimicide in pulp and paper 
mills, as a chemical reagent in the plastics industry, in pharma- 
ceuticals and paints, in power plants in special heat engines, in 
metal-refinement operations by amalgamation, and in the manufac- 
ture of electric switches, batteries, and lamps. Chlor— alkali plants 
probably represent the greatest point-source hazard at this time; 
typical plants contain more than 500,000 kg of liquid mercury and 
discharge several kilograms daily to the environment. In the absence 
of better controls, this loss could be averted by developing a new 
technology that precludes mercury compounds. This technology is 
urgently required and should be awarded the highest priority. 

4. Remove mercury from contaminated waterways. Thousands of 
kilometers of our inland waterways and some coastal areas are 



MERCURY CONTAMINATION STANDARDS 261 

contaminated with mercury to the extent that fish and other 
organisms taken from these waters are unsafe to eat (Anonymous, 
1971). This process shows httle sign of abatement. Accordingly, high 
priority should be given to research and development technology to 
remove mercury from existing contaminated areas. These could 
include bacterial strains and other methods to solubilize mercury 
from sediments, with subsequent removal and reclamation from 
waterways via biological or abiotic vectors. One interim alternative 
would be to feed mercury-contaminated scrapfish and seafoods as 
partial diet supplements to migratory anadromous fishes. Removal 
by dredging of mercury-contaminated sediments and storage at 
designated locations is another alternative, but numerous problems 
are associated with this approach as currently practiced. 

5. Develop monitoring criteria. Preventing mercury feedback into 
human diets is of paramount importance. To achieve this goal, we 
must refine existing mercury-residue standards for waste waters, 
sediments, and biota, with due consideration for geographical 
location and economic aspects of the resource. 

It is emphasized at this time that mercury in marine waters is 
usually bound to bottom materials, proteinaceous matter, plankton, 
and higher organisms. Even in water heavily polluted by mercury 
discharges, only a fraction is found free in solution, except near the 
point of discharge. The best available evidence indicates that total 
mercury in waste waters, dissolved plus particulate, emanating from 
the pipe terminus should not exceed 1.0 /ag/liter; however, I believe 
two additional restrictions on pipe terminus concentrations are 
warranted to achieve a reasonable margin of safety. First, outfall 
volume should not exceed one-fiftieth of the mean daily waterflow 
of the receiving water. Second, the receiving waters upstream of the 
terminus (or in direction of positive tidal flow, if applicable) should 
contain less than 0.02 /ug/liter total mercury, dissolved plus particu- 
late. The final recommended value of 0.0392 /ug total Hg/liter after 
mixing is about 2.5 times lower than the currently recommended 
value of less than or equal to 0.10 /ig/liter proposed by the National 
Academy of Sciences (1973); however, the 0.10 yug/liter does not 
consider mixing processes. 

Because benthic animals sometimes reflect the mercury levels of 
their sediment substrate, it is recommended that sediments in outfall 
environs should not exceed 500 jUg total Hg/kg. This value is less than 
the 750 )ug/kg set by the Environmental Protection Agency (1977) 
for solid wastes disposed offshore. 

For biological monitoring, two groups of indicator organisms are 
recommended, filter-feeding bivalve molluscs and piscivorous fishes. 



262 EISLER 

Total mercury levels in soft tissues from bivalves or fish axial 
musculature should not exceed 500 /Lig/kg wet weight (0.5 ppm). 
This is the current limit in comestibles set by the Food and Drug 
Administration. Until additional evidence becomes available it is also 
suggested that expectant mothers limit to 200 g/week their dietary 
intake of seafood items containing total mercury concentrations in 
the 0.3- to 0.5-ppm range. 

6. Conduct research. One of the highest priorities should be 
assigned to refining the current analytical chemistry methods for 
detecting mercury. Specifically, procedures must be developed for 
accurate, precise, and inexpensive determination of mercury at 
concentrations as low as 0.02 ^ig/liter. 

An equally high priority could be assigned to laboratory studies 
on lethal, sublethal, and latent effects of mercurials on selected 
marine indicator species during lifetime exposure. These data do not 
exist at present. Tests must be conducted in flowing seawater and 
should, at a minimum, accurately assess mercury effects on survival, 
growth, behavior, reproduction, accumulation, and histopathology. 
Results of these studies would provide a basis for a more reasonable 
assessment of safe levels of mercury in water and would probably 
result in some modification of the proposed 0.0392 //g/liter value 
recommended here. 

Field and laboratory investigations of interaction effects of 
mercury with other constituents in the environment should be 
conducted. The significance of the apparent protective effect of 
selenium in marine mammals is a case in point. At present, data on 
field studies of mercury cycling and effects of mixed wastes 
containing mercury on community structure are scarce or absent. 
These studies should be conducted, with a major effort being 
assigned to roles played by aquatic mammals, fish-eating birds, 
predatory fishes, higher plants, and mercury-resistant strains of 
bacteria. Establishment of a nation-wide monitoring program on 
mercury levels in coastal sediments appears to be a necessary 
prerequisite for identifying heavily contaminated cireas and selecting 
appropriate sites for field investigations. 

One of the most important research needs is to develop an early 
warning system in selected indicator organisms that will forecast 
generalized stress among marine communities, with emphasis on 
response parameters peculiar to mercury-induced stress. Within the 
past decade, multiparametric approaches have been used extensively 
by industrial toxicologists and others who work with poisonous 
substances; however, application of these approaches to marine 
communities is rare and difficult. Typically, mercury-induced stress 



MERCURY CONTAMINATION STANDARDS 263 

would be evident long before physiological or morphological damage 
occurs, would be manifested at the cellular or subcellular level, and, 
if allowed to remain unabated, would ultimately cause death or 
large-scale changes in community structure. Biochemical responses 
are probably most sensitive at present, but behavioral and histologi- 
cal responses should not be discounted as possible early indicators. 

7. Apply recommendations to other contaminants. With minor 
modifications, the preceding recommendations could become 
protocols for other heavy metals in coastal ecosystems and, with 
additional modifications, could be useful in abatement, decontamina- 
tion, and research programs now in progress on many groups of 
synthetic chemicals routinely discharged into the marine environ- 
ment. 

ACKNOWLEDGMENT 

I am obligated to fellow staff members of the Environmental 
Research Laboratory, Narragansett, for their many constructive 
comments on this manuscript, especially Gerald Pesch, Frank 
Lowman, Daniel O'Neill, Glen Thompson, Earl Davey, Gerald 
Zaroogian, John Gentile, Sandra Marburg, and Brian Melzian. All 
opinions and data interpretations expressed herein are mine and do 
not necessarily reflect those of the Environmental Protection Agency 
or any other regulatory agency. 

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A RADIOISOTOPIC STUDY OF MERCURY 
UPTAKE BY HUDSON RIVER BIOTA 



LOIS S. ZUBARIK and JOSEPH M. O'CONNOR 

New York University Medical Center, Institute of Environmental Medicine, 

A. J. Lanza Research Laboratories, Tuxedo, New York 



ABSTRACT 

Planktonic organisms from the Hudson River were exposed to various forms of 
mercury (^°^Hg) to evaluate the role of estuarine forage organisms in the 
kinetics of toxic metal transport in aquatic systems. Mercury accumulation was 
expressed as concentration per unit time. Concentration factors ranged from 10 
to 10 times that in the filtered river water. Mercury-203 uptake was greater in 
microzooplankton and algae than in macrozooplankton and fish larvae. The 
amphipod Gammarus sp. was tested to determine if differences in mercury 
uptake could be related to the form of mercury or to changes in environmental 
conditions. Exposure to two inorganic forms of mercury (mercuric nitrate and 
mercuric chloride) and two organic forms of mercury (methyl mercury chloride 
and phenyl mercuric acetate) showed no differences in concentrations of the 
four forms of mercury after a 1-day exposure. Concentration of the organic 
forms by Gammarus sp. was three times greater than that of inorganic mercury 
compounds after exposure for 1 week. Studies of mercury uptake throughout 
the year showed that uptake of all the mercury compounds tested increased 
during the summer months, but uptake of organic compounds increased to a 
greater extent than that of inorganic compounds. Temperature change was 
shown to be an important variable for determining the degree of uptake; 
however, no single environmental parameter adequately explained the seasonal 
fluctuations in mercury uptake. 



Levels of mercury in excess of 0.5 mg/liter in freshwater fish have 
been reported in Japan (Fujiki and Fujima, 1973), Sweden (Johnels 
and Westermark, 1969; Berglund et al., 1971), Norway (Underdal 
and Hastein, 1971), Finland (Miettinen, 1969), the United States 
(Wallace et al., 1971), and Canada (Bligh, 1970). Marine plankton 
may show concentrations of mercury from 0.2 to 25 ppm dry weight 

273 



274 ZUBARIK AND O'CONNOR 

(Skei, Saunders, and Price, 1976; Williams and Weiss, 1973), and 
estuarine organisms in the southeastern United States, including blue 
crabs and many species of fish, have average mercury levels above 0.5 
ppm. Larger predators, such as lemon and bull sharks, exhibited 
mercury levels of 4 to 10 ppm (Gardner et al., 1975). 

Despite abundant data on mercury levels in aquatic systems, it is 
the consensus that insufficient data exist on the mechanisms of 
mercury accumulation and cycling (Gavis and Ferguson, 1972; D'ltri, 
1973; Gardner et al., 1975; Lindberg, Andrew, and Harriss, 1975; 
Matsunaga, 1975; Tsai, 1975; Stickney et al., 1975; Wallace et al., 
1971; Friberg and Vostal, 1972). Measuring mercury levels in 
organisms is important in assessing the degree of an environmental 
problem, but survey and monitoring data frequently cannot be used 
for msiking predictions about mercury cycling because the conditions 
under which uptake and accumulation occurred are not known. 

Most uptake and accumulation studies performed to date have 
been on fish, marine mammals, and larger invertebrates (D'ltri, 1973; 
Miettinen, 1969; Olson, Bergman, and Fromm, 1973; MacLeod and 
Pessah, 1972; Guarino and Anderson, 1976; Hannerz, 1968). Often 
there seems to be no clear reason for the high mercury levels 
frequently found in fish. Confusion still exists over the relative 
importance of mercury availability for direct uptake from water vs. 
biomagnification through food chains. To understand aquatic cycling 
of mercury, we must determine uptake and accumulation of mercury 
by forage organisms as well as commercially important fish and 
shellfish. 

There are few investigations of bioaccumulation by smaller 
invertebrates, few studies on mercury uptake by any estuarine biota, 
and no studies on mercury uptake by Hudson River biota. Our study 
was carried out to evaluate the role of estuarine organisms in 
mercury dynamics and to determine the accumulation of mercury 
compounds by Hudson River biota. A broad spectrum of planktonic 
organisms, from algae to fish larvae, were selected for study of 
bioconcentration under natural conditions. The organisms were 
chosen on the basis of their abundance in the river and their 
importance as forage. The amphipod Gammarus sp. was studied in 
detail, to acertain if there was a difference in uptake of four mercury 
compounds (mercury chloride, mercury nitrate, methyl mercury 
chloride, and phenyl mercuric acetate) and to determine if 
fluctuations in selected environmental parameters might relate to 
changes in mercury uptake. 



RADIOISOTOPIC STUDY OF MERCURY UPTAKE 275 

MATERIALS AND METHODS 

Collection and Maintenance of Organisms 

Zooplankton and algae were collected from midchannel and 
shore locations in the Hudson River 66 km north of New York City. 
Zooplankton (see Table 2) were collected on the day preceding or on 
the morning of an experiment with a 0.5-m-diameter nylon net 
having a mesh size of either 76 or 500 ju. River water and algae were 
collected by filling 4-liter plastic buckets with surface water. Algae 
were subsequently concentrated with a nannoplankton net (18-jU 
mesh). Gammarus sp. collected from Myriophyllum spicatum 
gathered from the Hudson River were placed in aquariums containing 
Hudson River water together with M. spicatum and maintained in 
culture at ambient river temperature. 

Before use in an experiment, the larger zooplankton (Crangon, 
Gammarus, Amnicola, Neomysis, and Chiridotea) were maintained in 
380-liter aquariums filled with Hudson River water, and small 
zooplankton {Eurytemora, Acartia, Daphnia, Leptodora, Cypris, 
Mesocyclops, Monoculoides, Chaoborus nauplii and cyclopoid 
copepodids) were kept in 800-ml battery jars filled with Hudson 
River water. All holding vessels were placed in water troughs filled 
with flowing river water and were illuminated on a 12 : 12 light— dark 
cycle. Organisms were fed ad libitum before the experiment. 

Striped bass (Morone saxatilis) larvae from Hudson River stock 
were obtained from the Consolidated Edison Hudson River fish 
hatchery at Verplanck, N. Y. Larvae were maintained in holding 
facilities at the hatchery before the experiment and were brought to 
the New York University laboratory at Indian Point for acclimation 
over a 2-day period to Hudson River water. This was accomplished 
by serial dilution of hatchery water with Hudson River water. 
Striped bass larvae v/ere maintained at ambient Hudson River 
temperatures and fed brine shrimp nauplii. 

Accumulation Studies 

Organisms were taken from holding facilities and placed in 
individual culture bowls. The numbers of organisms added to each 
bowl varied according to species. Generally 150 to 300 microzoo- 
plankton, 30 to 50 macrozooplankton, or 6 to 10 fish larvae were 
placed in the experimental containers. Each bowl contained 100 ml, 
or 300 ml in the case of fish larvae, of Hudson River water. One 
milliliter of radioisotope carrier (~0.1 fiCi) was injected with an 



276 ZUBARIK AND O'CONNOR 

Eppendorf pipettor directly into Hudson River water containing the 
test organisms. The four mercury compounds used [mercuric nitrate, 
^^•^Hg(N03 )2 ; mercuric chloride, ■^°^HgCl2; methyl mercury 
chloride, ^^^HgCHaCl; and phenyl mercuric acetate, 
^ ^^HgCOOCH3 ] were purchased from New England Nuclear, 
Dilutions to appropriate radioactive concentrations (0.1 to 1 /iCi) 
were made in deionized water. The final concentrations of stable 
mercury added with the radioisotope was always less than mercury 
concentrations reported for Hudson River water (0.1 ppb). 

At predetermined intervals organisms were removed from the 
water by collection in netted cages, killed in hot water, and rinsed 
with clean Hudson River water. There was no evidence that the 
technique caused breakage of cells of the organisms used. They were 
then air dried overnight and placed in scintillation vials filled with 

15 ml of phase combining system solubilizer (PCS) (Amersham/ 
Searle Corp.) and 5 ml of water. 

The test water was filtered immediately through 0.45-/J Millipore 
filters when an experiment was terminated. Five milliliters of the 
filtered river water and the filter paper containing the suspended 
particulate matter from the test water were placed in separate liquid 
scintillation vials containing 15 ml of PCS. The filter paper was air 
dried overnight and then weighed. To avoid yellowing of the sample, 
we added the cocktail to the filter paper just before counting. The 
samples were counted on Nuclear Chicago Mark I or Isocap/300 
liquid scintillation counters. Both instruments were calibrated with a 
primary standard from Amersham /Searle Corp. (126 mCi/g ± 2.9%). 
Quenching was corrected for by the channels ratio technique on the 
Mark I and by an external standard on the Isocap (Wang and Willis, 
1965; Chase and Rabinowitz, 1967). Samples were counted for 10 
min or longer (if necessary) to give a counting error of less than 3%. 
Experiments generally consisted of three replicates. 

All counts were corrected for decay and background, and the 
counts were converted to disintegrations per minute. Concentration 
factors were obtained by dividing the disintegrations per minute per 
gram of organism by the disintegrations per minute per gram of 
filtered test water. 

Food organisms were labeled as if they were being tested for 
uptake from water except that, instead of being killed at the end of 
the experiment, they were washed in filtered Hudson River water, 
recollected, and added to the test culture. Food organisms were 
always supplied to test cultures in excess amounts. 

During each experiment, salinity, dissolved oxygen, conductivity, 
alkalinity, and temperature were measured according to procedures 



RADIOISOTOPIC STUDY OF MERCURY UPTAKE 277 

in Standard Methods (American Public Health Association, 1971). 
Algal cell counts and carbon values were obtained from ongoing 
ecological studies of the Hudson River at Indian Point (New York 
University Medical Center, 1976; P. Storm, New York University, 
unpublished data). Turbidity, phosphate, and nitrogen levels were 
obtained from Lawler, Matusky, and Skelly Engineers (1976). 

Statistical Analysis 

All experimental data were converted to natural logarithms 
before analysis. Bartlett's test for homogeneity of variance and the 
Kolmogorov— Smirnov test for normality were run to ensure that 
assumptions of the analysis of variance (ANOVA) were met. Once 
differences were shown, the Scheffe test compared each experiment 
for significant differences. Multiple regression analysis (Nie et al., 
1975) was used as an inferential tool for evaluating the relationship 
between mercury uptake and fluctuations in the chemical and 
physical parameters of Hudson River water. 



RESULTS 

Both fish larvae and zooplankton took up mercury directly from 
water and from food. In most cases mercury uptake from filtered 
river water was similar in degree to uptake from whole river water 
and from labeled algae, detritus, and bacteria. Presence of sediment 
reduced the level of mercury in organisms (Table 1). 

Comparing the concentration factors for several Hudson River 
species shows that each species is able to concentrate all four forms 
of mercury to a considerable extent over the water phase. After a 
1-day exposure, mercury concentration in organisms was 10^ to 10^ 
times that in the filtered river water (Tables 2 and 3). In general, 
Hudson River algae and microzooplankton showed much higher 
concentration factors (50,000 to 1,000,000) than macrozooplankton 
(1,000 to 30,000) and fish (1,000 to 10,000). Of the Crustacea, the 
filter feeders (e.g., Eurytemora affinis, Acartia tonsa, and Daphnia 
pulex) show greater concentrations of mercury taken up from river 
water than carnivorous copepods (e.g., cyclopoid copepods) or 
detrital feeders (e.g., Gammarus sp.). 

Gammarus sp. was extensively studied to determine if there was 
greater uptake of organic mercury than of inorganic mercury. 
One-way ANOVA comparing uptake of four mercury compounds 
[Hg(N03 )2 , HgCU , HgCHj CI, 0HgCOOCH3 ] showed no differences 
after 1 day (68 df, P > 0.05), but there were differences at 1 week 



278 



ZUBARIK AND O'CONNOR 



TABLE 1 

INORGANIC MERCURY UPTAKE IN HUDSON RIVER WATER 
FOR DIFFERENT LABELING CONDITIONS* 



Mean 



Experiment 



Organism 



dismin-' g^^ X 10^ ± SE 



1. Labeled river water 
Labeled filtered 

river water 

2. Labeled river water 
Labeled filtered 

river water 

3. Labeled river water 
Labeled filtered 

river water 

4. Labeled river water 
Labeled leaves 

5. Labeled filtered 

river water 
Labeled algae, 

detritus, and 

bacteria 
Labeled algae 

6. Labeled river water 
Labeled algae, 

detritus, and 
bacteria 

7. Labeled river water 
Labeled algae, 

detritus, and 
bacteria 

8. Labeled river water 
Labeled Gammarus 

9. Labeled river water 
1-in. mud layer 

10. Labeled river water 
Labeled river water 

(1 day), then 
nonlabeled river 
water (1 day) 

11. Labeled river water 
Labeled copepods 
Labeled copepods, then 

1 day in nonlabeled 
river water 



Gammarus sp. 

(G. daiberi 

and G. tigrinus) 
Neomysis 

americana 

Morone saxatilis 



Gammarus sp. 
Gammarus sp. 



Gammarus sp. 

Gammarus sp. 

Gammarus sp. 
Gammarus sp. 
Gammarus sp. 



Morone saxatilis 



1,130 ± 560 (3) 
880 ± 110 (3) 

510 ± 220 (4) 
680 ± 130 (2) 

8,040 + 230 (4) 
8,200 ±4,400 (2) 

4,500 ± 2,000 (3) 
1,090 ± 240 (3) 
620 ± 160 (3) 

710 ± 110 (3) 



270 ±47 (3) 
2,190 ±390 (3) 
2,200 ±990 (3) 



510 ± 270 (3) 
700 ±600 (3) 



150,000 ± 30,000 (10) 
12,000 ± 2,100 (10) 
13,220 ± 670 (3) 

99 ± 14 (3) 
87,000 ± 13,000 (3) 

126,000 ± 27,000 (3) 



8,040 ± 200 (4) 
10,300 ± 5,000 (2) 
4,400 ± 2,000 (2) 



*Numbers in parentheses are numbers of replicates. 



RADIOISOTOPIC STUDY OF MERCURY UPTAKE 279 

TABLE 2 

MERCURY CONCENTRATION FACTORS FOR SELECTED 

AQUATIC BIOTA AFTER 1-DAY EXPOSURE TO 

INORGANIC MERCURY COMPOUNDS* 

Biota Hg(N03 )2 HgCl2 

Phytoplankton 
Bacillariophyta 
Melosira sp. 1,100,000 ± 170,000 (2) 

Synedra sp. 220,000 ± 33,000 (2) 

Chrysophyta 

Scenedesmus sp. 93,000 ± 36,000 (2) 

Hudson River algae, 49,000(1) 92,000(1) 

detritus, and bacteria 
Crustacea 
Cladocera 
Daphnia pulex 62,000 ± 11,000 (3) 200,000 ± 130,000 (6) 

Leptodora kindti 200,000(1) 

Ostracoda 

Cypns sp.t 58,000(1) 

Copepoda 
Nauplii 9,800 ± 1,200 (2) 

Copepods (cyclopoid 3,700 ±920 (2) 2,830 ± 310 (2) 

copepodids) 
Mesocy clops edax 194,000 ± 14,000 (2) 

Eurytemora affinis 104,000 ± 32,000 (7) 230,000 ± 160,000 (7) 

Acartia tonsa 61,000 ± 23,000 (2) 14,000 ± 13,000 (2) 

Isopoda 

Chiridotea almyraf 2,336 ± 30 (2) 

Amphipoda 
Gammarus sp. (G. daiberi 1,440 ± 400 (14) 1,490 ± 520 (23) 

and G. tigrinus) 
Monoculodes edwardsi 1,330 ± 780 (2) 

Mysidacea 

Neomysis americana 133(1) 95(1) 

Decapoda 
Crangon septemspinosaf 18,000 (1) 

MoUusca 
Gastropoda 
Amnicola limosa 412 ± 40 (3) 

Ichthyoplankton 
Percichthyidae 
Morone saxatilis 
Eggs 58 ±25 (2) 

Larvae 1,300 ± 770 (4) 7,600 ± 5,900 (5) 

♦Numbers in parentheses are numbers of experiments. 

fConcentration factors are based on uptake after exposure of 5 to 9 days. 



280 



TABLE 3 



MERCURY CONCENTRATION FACTORS FOR SELECTED 
AQUATIC BIOTA AFTER 1-DAY EXPOSURE TO ORGANIC 

MERCURY COMPOUNDS* 



Biota 



203 



HgCHaCl 



(^^^^HgCOOCHg 



Phytoplankton 
Bacillariophyta 
Melosira sp. 
Synedra sp. 
Chrysophyta 

Scenedesmus sp. 
Hudson River algae, 
detritus, and bacteria 
Crustacea 
Cladocera 
Daphnia pulex 
Leptodora kindti 
Ostracoda 

Cypris sp.f 
Copepoda 
Nauplii 
Copepods (cyclopoid 

copepodids) 
Mesocyclops edax 
Eurytemora af finis 
Acartia tonsa 
Isopoda 

Chiridotea almyraif 
Amphipoda 
Gammarus sp. 
(G. daiberi and 
G. tigrinus) 
Monoculodes edwardsi 
Mysidacea 

Neomysis americana 
Decapoda 
Crangon septemspinosa'f 
Insecta 
Diptera 
Chaoborus sp. 
Mollusca 
Gastropoda 
Amnicola limosa 
Ichthyoplankton 
Perciciitiiyidae 
Morone saxatilis 
Eggs 
Larvae 



201,600 ±1,200 (2) 
390,000 ±72,000 (2) 



12,000 ±(1) 



240,000 ± 220,000 (3) 
140,000 (1) 



15,000 ±4,300 (2) 
9,800 ±7,000 (2) 

360,000 ±200,000 (2) 
250,000 ±190,000 (6) 
540,000 ±220,000 (2) 



4,900 ±2,600 (22) 



2,800 ±700 (2) 
53,000 ± 15,000 (2) 

14,200 ± 1,000 (2) 



12,000 (1) 



63,000 (1) 



15,000 ±4,500 (2) 



105,000 ±46,000 (6) 
180,000 ± 170,000 (2) 



2,660 ±950 (13) 



1,700 ±(1) 

4,039 (1) 



620 ± 220 (10) 
5,200 ±410 (3) 



10,000 ± 29,000 (2) 



*Numbers in parentheses are numbers of experiments. 

fConcentration factors are based on uptake after exposure of 5 to 9 days. 



RADIOISOTOPIC STUDY OF MERCURY UPTAKE 



281 



(28 df, P < 0.05). Uptake of methyl mercury was greater than 
uptake of mercuric nitrate. There were no uptake differences 
between mercuric nitrate and mercuric chloride or between methyl 
mercury and phenyl mercury. Combining uptake of the two 
inorganic forms and the two organic forms after a 1-day exposure 
showed that mean uptake of inorganic compounds was less than that 
of organic compounds, but this was not statistically significant. 
Organic mercury uptake was three times greater than inorganic 
uptake after 1 week (P < 0.007; Table 4). 

TABLE 4 

MEAN MERCURY CONCENTRATION FACTORS AND 95% 
CONFIDENCE LIMITS (Lj L2 ) FOR Gammarus sp. 









Mercury type 






Exposure 




Inorganic 






Organic 




time 


Mean 


Li 


L2 


Mean 


Li 


L2 


1 day 
1 week 


688 
2,562 


475 
1,540 


996 
4,260 


1,153 
8,196 


736 
4,065 


1,798 
16,526 



Rates of uptake over time were rapid for both methyl mercury 
and mercuric chloride (Figs. 1 and 2). Of the total mercury taken up 
by Gammarus after 1 week, almost one-half the radioactivity of 
organic mercury and one-third the radioactivity of inorganic mer- 
cury were taken up during the first day. Studies of mercury uptake 
over periods longer than a week show a decline in mercury per gram 
of organism between days 10 and 19 (Fig. 3). 

Further studies were undertaken with Gammarus sp. to deter- 
mine what changing conditions might explain the variations in 
concentration factors shown by one species. Studies of mercury 
uptake in conjunction with seasonally changing estuarine variables 
show that the difference between inorganic and organic uptake is 
increased during the summer months (Fig. 4). There was a strong 
positive correlation between uptake and temperature for both types 
of mercury compounds and an inverse correlation of mercury uptake 
with total organic carbon. Positive correlations existed with phos- 
phates and algal cell concentration, but there were peaks in these 
values when there were no peaks in mercury uptake. No single 
environmental parameter adequately explains the seasonal fluctua- 
tions in mercury uptake (Fig. 4). 



282 



ZUBARIK AND O'CONNOR 



14,000 




1 2 3 4 5 6 7 

TIME, days 

Fig. 1 Methyl mercury uptake by Gammarus sp. over a period of 1 
week. Each point represents the mean of three replicates. Activity 
ratio = dis min~ g~' organism per dis min~* g^' in the w^ater at 
the end of the experiment. 



4,000 



3,000 — 



< 

> 



CJ 

< 



2,000 



1,000 — 




3 4 5 6 7 8 

TIME, days 

Fig. 2 Mercuric chloride uptake by Gammarus sp. over a period of 
1 week. Each point represents the mean of three replicates. 



RADIOISOTOPIC STUDY OF MERCURY UPTAKE 



283 





lU 


1 1 1 1 1 1 1 1 1 


1 1 1 1 1 1 1 1 1 _ 


^ 


8 


— -| 


r — 


Ol 




— 


— 


I 

c 

'e 


6 


— ^^^..^"^ 


"^--.^ - 


'-0 


4 


r / ^ 


^^^^^ 


o 


2 


-J 


^^- 







1 1 1 1 1 1 1 1 1 1 


1 1 1 1 1 1 1 1 1 



10 
TIME, days 



15 



20 



Fig. 3 Long-term accumulation and loss of mercuric chloride by 
Gammarus sp. Each point represents the mean uptake of 15 to 20 
organisms. 




14 = 
ORGANIC 12 — 
CARBON lOE 
mq/liter C 

6 

PHOSPHORUS 008 = 
mg/liter P g g^ 

ORGANIC NITROGEN 0-8 
mg/liter N 

SALINITY, ppt 

ALGAE CELLS/liter |= 

AMBIENT RIVER 
TEMPERATURE, °C 

10,000 

MERCURY 
CONCENTRATION 5,000 
FACTOR 



Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. 

Fig. 4 Correlation between mercury concentration factors (inor- 
ganic and organic) for Gammarus sp. and seasonal fluctuations in 
physical and chemical parameters of Hudson River water during 
1975. Values of R are correlation coefficients for inorganic (first 
value given) and organic (second value) mercury concentration 
factors with the variable graphed. Coefficients underlined are 
significant (P < 0.005). 



A stepwise multiple regression was done to determine which 
parameters might best explain variability in mercury uptake. 
Ambient river temperature accounted for the largest percent of 



284 ZUBARIK AND O'CONNOR 

variability for both inorganic and organic mercury uptake. For 
organic uptake the variance contributed by changes in algal cell 
concentration and salinity was also significant. Inorganic uptake was 
apparently related to several factors other than temperature 
(Table 5). The significant concentration factors (CF) for inorganic 
and organic uptake produced the following predictive equations: 

CFinorganic = 2.3 + 0.07(T) - 2.2(ON) - 0.055(OC) 
+ 48(TB) + 0.0002(COND) 
R2 = 0.65 (1) 

CForganic = 2.4 + 0.07(T) + 0.024(SAL) 
- 0.06(AC/liter) - 0.02(OC) 
R2 = 0.75 (2) 

where T = temperature 

ON = organic nitrogen 
OC = organic carbon 
TB = turbidity 
COND = conductivity 
SAL = salinity 
AC /liter = algal cells per liter 

TABLE 5 

SIGNIFICANT VARIABLES USED IN 

PREDICTION EQUATIONS FOR INORGANIC 

AND ORGANIC MERCURY UPTAKE 



Concentration 




Probability 


factor 


Variables 


F value 


Inorganic 


Temperature (T) 


< 0.000 


66 cases 


Organic nitrogen (ON) 


0.027 




Organic carbon (OC) 


0.043 




Turbidity (TB) 


0.001 




Conductivity (COND) 


0.003 


Organic 


Temperature (T) 


<0.000 


66 cases 


Algal cells per liter 
(AC/liter) 


<0.000 




Salinity (SAL) 


< 0.000 




Organic carbon (OC) 


0.097 



RADIOISOTOPIC STUDY OF MERCURY UPTAKE 285 

DISCUSSION 

A variety of Hudson River forage organisms, ranging from algae 
to fish larvae, accumulated mercury compounds from the test 
environment. The concentrations in organisms ranged from 10^ to 
10^ times that in the test medium. In all cases tested, uptake of 
mercury occurred via food, as well as directly from water. The 
greatest relative concentrations (10^) over the external medium 
occurred among algae; the least (10-^) occurred among the larger 
planktonic Crustacea (e.g., Gammarus) and striped bass larvae. 
Mercury was transferred to striped bass lairvae from copepods labeled 
with mercury. Thus mercury concentrations in forage organisms and 
the conditions that affect their mercury uptake are relevant to 
predictions about mercury cycling. However, the concept of bio- 
magnification along a food chain is misleading in aquatic systems 
where bioaccumulation occurs from water as well as food. 

Mercury uptake in Hudson River organisms was found to vary on 
a seasonal basis within the same species or species group, showing a 
strong positive correlation with temperature. MacLeod and Pessah 
(1973), in their studies of Salmo gairdneri (rainbow trout), and Heit 
and Fingerman (1977), in their studies of Procambarus clarki and 
Faxonella clypeata (crayfishes), also found that mercury accumula- 
tion was strongly dependent on temperature. This suggests that 
several possible mechanisms are operating to cause a gradual increase 
in mercury content. First, since poikilothermic organisms generally 
show an increase in metabolic rate as temperature increases, the 
increased bioaccumulation during warm months may be due simply 
to a greater rate of uptake of mercury -contaminated food. Increased 
metabolism should also result in more rapid rates of mercury 
clearance, however, but this is not borne out by our results. 
Nonetheless, the potential for bioaccumulation of mercury com- 
pounds during warm months is greater than during cool months. 
Field studies should be carried out in mercury -contaminated environ- 
ments to verify this hypothesis and its several ramifications: (1) that 
the concentration of mercury compounds per gram of organism 
increases during warm periods, (2) that uptake and retention of 
mercury is greater during the summer, and (3) that an increase in the 
absolute quantity of mercury compounds available for direct uptake 
and food-chain transfer occurs in warm environments. 

The form of mercury available to organisms affects uptake 
rates and the environmental impact of mercury on aquatic systems. 
Experiments with Gammarus showed a greater uptake of organic 
over inorganic forms of mercury, but only after prolonged (1-week) 



286 ZUBARIK AND O'CONNOR 

exposures. Initigil uptake of both forms was extremely rapid, 
however; this indicates that perhaps the hypothesized "necessary" 
conversion of inorganic mercury to a methylated form before uptake 
by organisms is not required. Mercury methylation by natural 
bacterial assemblages could not convert mercuric nitrate or mercuric 
chloride to an organic form rapidly enough to generate the rates of 
uptake observed in these experiments (Langley, 1973). These results 
are confirmed by those of Olson, Bergman, and Fromm (1973), who 
studied the rainbow trout; Prabhu and Hamdy (1977), who studied 
Lebistes reticulatus (guppy); and Mellinger (1973), who studied 
Margaritifera margaretifera (freshwater mussel). Kramer and Neidhart 

(1975) found that mercury uptake by fish (Poecilia reticulata) in a 
methyl mercury chloride solution was about four times as fast as in a 
mercuric nitrate solution. 

Variations in concentration factors for the same species can be 
related to the conditions under which bioconcentration of mercury 
took place. The facts that the presence of sediments decreases uptake 
by Gammarus sp. and that there is an inverse correlation between 
mercury uptake and total organic carbon levels indicate that mercury 
concentration or type of mercury compound are not the only factors 
controlling mercury uptake by aquatic organisms. Environmental 
parameters may affect the availability of mercury for uptake and 
accumulation. Tsai, Boush, and Matsumura (1975) reported that the 
pH of the ambient water has a great effect on the translocation of 
inorganic mercury to fish. In the area of the Hudson River studied, 
pH varies annually by only 0.6 of a unit (7.2 to 7.8). Therefore, it 
was impossible to assess the effect of pH on mercury uptake in this 
study. Lindberg, Andrew, and Harriss (1975) reported that transport 
and deposition of mercury in the estuarine environment is largely 
controlled by interaction with natural organic matter. Cranston 

(1976) stated that the process controlling accumulation and distribu- 
tion of mercury in estuarine sediments is related to the amount of 
fine-grain sediments. 

The experiments reported here address only the effects of 
relationships among species, environmental parameters, and chemical 
form on the uptake of mercury from water and food. The impact 
related to the community and to seasonal differences in mercury 
uptake was not studied directly. The relationship between tempera- 
ture and mercury uptake identified in our study, however, justifies 
some speculation on the stress mercury compounds may cause on 
aquatic systems. First, since the toxicity of organic mercury 
compounds is greater than that of inorganic and since organic 
compounds can be accumulated to greater levels during periods of 



RADIOISOTOPIC STUDY OF MERCURY UPTAKE 287 

high temperature, we might propose that mercury contaminated 
environments are most stressed during the summer months. Even at 
sublethal concentrations, stress responses to mercury intoxication, if 
at all related to total body burden, must be greater if accumulated 
quantities are greater during periods of high temperature. 

The absence of intensive study on the physiological and 
biochemical effects of metals on planktonic organisms, vi^hich may 
act as the major vectors for mercury transport to organisms used as 
food by human populations, has led to the unfortunate circumstance 
wherein the environmental impact of mercury is based on surveys of 
concentrations in fish flesh and the results of relatively few 
laboratory bioassay experiments. Our experiments attest to the need 
for further study of the behavior of mercury compounds under 
conditions that simulate natural conditions to ascertain in a valid 
ecological context the true meaning of mercury-related stress on 
aquatic ecosystems. 

ACKNOWLEDGMENTS 

The research reported here was funded in part by grant No. 
ES-00260 from the National Institute of Environmental Health 
Sciences. 



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Stickney, R. R., H. L. Windom, D. B. White, and F. E. Taylor, 1975, 
Heavy-Metal Concentrations in Selected Georgia Estuarine Organisms with 
Comparative Food-Habit Data, in Mineral Cycling in Southeastern Ecosys- 
tems, ERDA Symposium Series, Augusta, Ga., May 1—3, 1974, F. G. 
Howell, J. B. Gentry, and M. H. Smith (Eds.), pp. 257-267, CONF-740513, 

NTIS. 
Tsai, Shan-Ching, G. M. Boush, and F. Matsumura, 1975, Importance of Water 

pH in Accumulation of Inorganic Mercury in Fish, Bull. Environ. Contam. 

To.xicol., 13(2): 188-193. 
Underdal, B., and T. Hastein, 1971, Mercury in Fish and Water from a River and 

a Fjord in the Krager Region, South Norway, Oikos, 22: 101-105. 
Wallace, R. A., W. Fulkerson, W. D. Schults, and W. S. Lyon, 1971, Mercury in 

the Environment: The Human Element, USAEC Report ORNL-NSF-EP-1, 

Oak Ridge National Laboratory, NTIS. 
Wang, C. H., and D. L. Willis, 1965, Radiotracer Methodology in Biological 

Science, Prentice-Hall, Inc., Englewood Cliffs, N. J. 
Williams, P. M., and H. V. Weiss, 1973, Mercury in the Marine Environment: 

Concentration in Sea Water and in a Pelagic Food Chain, J. Fish. Res. Board 

Can., 30(2): 293-295. 



IMPACT OF ARSENICALS ON NITRIFICATION 
IN AQUEOUS SYSTEMS 



HARVEY W. HOLM and MARILYN F. COX 

Environmental Research Laboratory, Environmental Protection Agency, 

College Station Road, Athens, Georgia 



ABSTRACT 

The impact of both arsenate and cacodylic acid (at arsenic concentrations of 0, 
0.1, 1, 10, 100, and 1000 mg/liter) on mixed populations of nitrifiers in model 
aqueous systems containing ammonia was determined by measuring levels of 
ammonia and nitrite over a 24-day incubation period. Ai'senate decreased the 
rate of oxidation of ammonia by Nitrosomonas only at high concentrations (100 
and 1000 mg/liter) of arsenic; low levels of arsenate (0.1, 1, and 10 mg As/liter) 
had no effect on the oxidation rate, in comparison with arsenic-free controls. 
The oxidation of nitrite to nitrate by Nitrobacter was affected by all 
concentrations of arsenic added as arsenate; low concentrations (0.1, 1, and 10 
mg/liter) delayed the oxidation of nitrite and high concentrations (100 and 1000 
mg/liter) inhibited the process. The only impact of cacodylic acid on 
nitrification occurred at 1000 mg As/liter. The oxidation of ammonia by 
Nitrosomonas was delayed by the arsenical, but the Nitrobacter population was 
not affected. Although cacodylic acid is not toxic to the nitrification process, its 
degradation product, arsenate, can inhibit nitrification if it is in an available 
form. This inhibition of the Nitrobacter population may promote the accumula- 
tion of nitrite in the environment. 



An understanding of the impact of pollutants on nutrient cycling in 
aquatic ecosystems is important to decision makers in industry and 
to surveillance and enforcement personnel in local, state, and federal 
government. These individuals need to know (l)how a pollutant 
affects an environment, (2) what the consequence of an altered 
environment might be, and (3) how the environment influences the 
fate of a pollutant. 

290 



IMPACT OF ARSENICALS ON NITRIFICATION 291 

Economic factors prevent the use of individual field studies to 
answer these questions for every pollutant. Instead, smaller 
laboratory-associated studies must be completed and the data 
ultimately extrapolated to a field situation. To meet this end, we 
have focused much of our laboratory's research on the fate and 
impact of pollutants in different environmental systems. Our 
environmental system studies largely involve mixed microbial popula- 
tions that are important in the nutrient cycling process. 

For this study, we investigated the impact of two arsenicals, 
cacodylic acid (hydroxydimethylarsine oxide) and sodium arsenate, 
on the nitrification process in aqueous systems. Cacodylic acid, 
which is representative of the organic arsenicals, is used in the 
cotton-growing states as a defoliant (Versar, Inc., 1976). Sodium 
arsenate was chosen because it is a common metabolic product of the 
organic arsenicals (Woolson and Kearney, 1973). 

Oxidation of nitrogen from a reduced state, such as ammonia, to 
a more oxidized state, such as nitrite and nitrate, is called 
nitrification (Hardy and Holsten, 1972). These nitrogen transforma- 
tions are usually mediated by two types of chemosynthetic, 
autotrophic bacteria. Ammonia oxidizers, typified by Nitrosomonas, 
get energy for growth by oxidizing ammonia to nitrite; nitrite 
oxidizers of the Nitrobacter type complete the process by oxidizing 
nitrite to nitrate. 

The objectives of this research were to develop simple systems to 
study the impact of pollutants on nitrification and to determine 
whether arsenicals, represented by sodium arsenate and cacodylic 
acid, signific£intly alter nitrification rates. These objectives were met 
by the following steps: (1) Mixed populations of nitrifiers were 
cultured in an aqueous medium; (2) the reproducibility and reli- 
ability of the system was determined; and (3) the impact of 
arsenicals on nitrification was determined by measuring the oxida- 
tion of ammonia and nitrite. 

MATERIALS AIMD METHODS 

Growth Medium 

Nitrification rates were determined in a chemically defined 
medium containing micronutrients and macronutrients. In a final 
volume of 1000 ml, the filter-sterilized micronutrient stock con- 
tained EDTA-Na2, 500 mg; FeS04 • 7H2O, 200 mg; ZnS04 • 7H2O, 
10 mg; MnCU • 4H2 O, 3 mg; H3 BO3 , 30 mg; C0CI2 * 6H2 O, 20 mg; 
CUCI2 • 2H2O, 1 mg; NiCl2 • 6H2O, 2 mg; and Na2Mo04 • 2H2O, 
3 mg. Each liter of the chemically defined medium contained NH4CI, 



292 HOLM AND COX 

38.2 mg; K2HPO4, 1.1 mg; MgClj , 5.7 mg; MgS04 • 7H2O, 1.9 mg; 
CaCl2 • 2H2O, 4.4 mg; NaHCOj, 150 mg; and micronutrient stock, 
10 ml. The medium was sterilized by filtration, and 100-ml ediquots 
were added to sterilized 250-ml Erlenmeyer flasks. 

Appropriate amounts of sodium arsenate or cacodylic acid were 
added to the medium before filter sterilization. Reagent grade 
chemicals were used to prepare the growth medium. Mixed nitrifying 
populations (containing both Nitrosomonas and Nitrobacter types) 
from local garden soil were used as inocula for the systems. Although 
the functional populations were not identified, oxidation of am- 
monia to nitrate indicated that both Nitrosomonas and Nitrobacter 
were present. 

Ammonia and nitrite concentrations in each flask were measured 
at selected intervals during the incubation period using a Technicon 
Autoanalyzer unit (AAII). Ammonia was measured using the auto- 
mated colorimetric phenate method (Technicon Corp., 1971). Nitrite 
concentrations were measured using the automated cadmium reduc- 
tion method (Environmental Protection Agency, 1974). 

Experimental Design 

Enrichment of nitrifying populations was completed by adding 
1 g of garden soil to 250-ml Erlenmeyer flasks containing 100 ml of 
the growth medium. The flasks were incubated in the dark at 25° C at 
a shaking rate of 125 rpm. At 2- to 3-day intervals, samples were 
taken, diluted, and analyzed for ammonia and nitrite. After 
populations had oxidized all the ammonia to nitrate, 1-ml inocula 
were transferred into fresh media, and the sampling cycle was 
repeated. Inocula from the second and third transfers were used for 
the arsenic studies. 

The reproducibility of the nitrification system was measured in 
seven replicate flasks, each receiving a 5-ml inoculum from a culture 
transferred twice previously. Biological activity was determined 
within each flask by measuring the oxidation of ammonia to nitrate 
over a 20-day incubation period. 

The impact of both sodium arsenate and cacodylic acid (at 
arsenic concentrations of 0, 0.1, 1, 10, 100, and 1000 mg/liter) was 
measured on mixed cultures of nitrifiers in aqueous systems 
containing 10 mg/liter nitrogen as ammonia. Duplicate flasks were 
set up for each treatment, and nitrification rates were determined in 
each flask by measuring levels of ammonia and nitrite over a 24-day 
period. 

The hours required for the oxidation of ammonia by Nitro- 
somonas and nitrite by Nitrobacter to a nitrogen concentration of 1 



IMPACT OF ARSENICALS ON NITRIFICATION 293 

mg/liter were the quantities chosen for statistical analysis. Data were 
analyzed using analysis of variance and Tukey's co procedure (Steel 
and Torrie, 1960). 

RESULTS 

Nitrifying populations were easily cultured from the garden-soil 
inoculum. For the initial enrichment, ammonia was oxidized to 
nitrite by Nitrosomonas organisms within 2 weeks, and the nitrite 
formed in the first step was oxidized to nitrate by Nitrohacter within 
3 weeks. In successive transfers of 1-ml inocula, however, the rate of 
oxidation of ammonia to nitrate was significantly increased. By the 
second transfer, all the ammonia was oxidized to nitrite within 1 
week. The entire nitrification process, involving the oxidation of 10 
mg/liter ammonia nitrogen to 10 mg/liter nitrate nitrogen, was 
shortened from 24 days to 10 days by the third transfer. 

No counts of nitrifiers were made as the ammonia was being 
oxidized to nitrate. Nitrosomonas probably outnumbered Nitro- 
hacter in each flask, however, because the oxidation of ammonia to 
nitrite provides more energy for growth of cells than does the 
oxidation of nitrite to nitrate (Tuffey, 1973; Curtis, Durrant, and 
Harmon, 1975). 

These nitrification systems provide reproducible results. Data in 
Table 1 were collected from seven replicate flasks, each receiving a 
5-ml inoculum from a culture transferred twice previously. These 
results demonstrate that aqueous systems in flasks can be used to 
study the impact of soluble pollutants on nitrification. An estimate 
of homogeneity of data, the coefficient of variation (CV), which is 
100(standard deviation/mean), calculated from the data in Table 1 
shows that these systems have CV values of 20% or less when the 
ammonia or nitrite nitrogen concentration is above 1 mg/liter. 

Using these test systems, we observed that Nitrosomonas 
organisms are not sensitive to arsenicals. At low levels of arsenate 
(10 mg As/liter), the rate of ammonia oxidation was identical to that 
of the arsenic-free controls (Fig. 1). The rate of ammonia oxidation 
was significantly different from the control only at 1000 mg As/liter 
added as arsenate, determined with Tukey's co procedure (a = 0.05). 
These results show that arsenate should not have an inhibiting action 
on Nitrosomonas in the natural environment because of the high 
concentrations necessary before any effects are seen. 

Likewise, cacodylic acid should not have a significant direct 
effect on Nitrosomonas. Nitrosomonas oxidized ammonia at normal 
rates in media containing as much as 100 mg As/liter as cacodylic 



294 HOLM AND COX 

TABLE 1 

CONCENTRATIONS OF NITROGEN 
IN AQUEOUS NITRIFICATION SYSTEMS* 



Incubation, 








days 


NH4- 


-N, mg/liter 


NO2 — N, mg/liter 




1 


9.35t(S = 0.38) 




3 


9.23 


(S = 0.38) 


0.04t (S= 0.01) 


6 


8.42 


(S = 0.36) 


0.71 (S = 0.13) 


8 


5.14 


(S= 0.97) 


4.35 (S = 0.78) 


10 


0.12 


(S= 0.22) 


8.93 (S = 0.51) 


13 






7.81 (S=0.46) 


15 






6.06 (S = 0.82) 


17 






4.79 (S=0.99) 


20 






0.43 (S = 0.49) 



*The growth medium containing 10 mg/liter NH4^N 
was inoculated with 5 ml of a mixed nitrifier population. 
Abbreviation S is standard deviation of seven flasks. 

tMean of seven observations. 



acid. There was a small decrease in the oxidation rate at concentra- 
tions of 1000 mg As/liter (Fig. 2). 

Nitrobacter-type organisms used in this study are sensitive to 
arsenate (Fig. 3). Apparently there is a progressively longer lag phase 
in the arsenic concentration range from 0.1 to 10 mg/liter, but the 
only treatment statistically different from the control (based on 
analysis of variance, a' = 0.05) is 10 mg/liter. Because only one point 
from each oxidation curve was used for the statistical analysis and 
only two replicate curves were obtained for each treatment, the 
analyses for differences are probably conservative. At very high levels 
of arsenate (100 and 1000 mg As/liter), Nitrobacter was inhibited, 
and nitrite accumulated. 

Cacodylic acid does not affect Nitrobacter. Arsenic concentra- 
tions as high as 1000 mg/liter as cacodylic acid did not alter the 
oxidation rate of nitrite (Fig. 4). 

DISCUSSIOIM 

The technique we adapted for this study is useful for studying 
the impact of pollutants on specific functional groups of bacteria. In 
this study we enriched the medium for chemosynthetic autotrophs 
important in the nitrification process. There are several advantages to 



IMPACT OF ARSENICALS ON NITRIFICATION 



295 




DAYS 



Fig. 1 Impact of arsenate on Nitrosomonas. •, no arsenic; o, 10 mg 
As/liter; A, 100 mg As/liter; and A, 1000 mg As/liter. 



this approach. First, mixed cultures growing in a selective medium 
provide a larger genetic pool than do pure cultures. This large genetic 
pool may allow the system to adapt to the toxicant much as 
populations do in nature. Second, enrichment of the mixed 
population assures the researcher uniform cultures to be used for a 
given set of toxicity tests (Table 1). This assurance usually is not 
present in studies of functional groups using natural samples or 
colonized slides. Third, monitoring ecosystem function is usually 
faster and easier than measuring specific bacterial populations. For 
example, the study by Fliermans, Bohlool, and Schmidt (1974), 
using fluorescent antibodies for counting nitrifiers, is very time and 
labor consuming. 



296 



HOLM AND COX 



X 




Fig. 2 Impact of the organic arsenical, cacodylic acid, on Nitro- 
somonas. •, no arsenic; A, 100 mg As/liter; and A, 1000 mg As/liter. 



Our approach also has some disadvantages. First, selection of new 
variants or species may occur, but this is not monitored. In fact, the 
selection process may have occurred during the enrichment phase of 
the study since the nitrification rate increased on successive transfer. 
This phenomenon may also have occurred when populations of 
Nitrobacter were exposed to arsenicals (Fig. 3). Second, interactions 
of populations from different segments of the nutrient cycle are not 
possible with enrichment techniques. This contrasts with work by 
Lavegha and Dahm (1974), who used soil systems to monitor the 
activity of several functional groups of bacteria after the test systems 
were dosed with pollutants. 

Inhibition of Nitrosomonas and, consequently, inhibition of the 
total nitrification process, can be economically and ecologically 



IMPACT OF ARSENICALS ON NITRIFICATION 



297 




DAYS 



Fig. 3 Impact of arsenate on Nitrobacter. •, no arsenic; O, 0.1 mg 
As/liter; D, 1 mg As/liter; ■,10 mg As/liter; A, 100 mg As/liter; and 
A, 1000 mg As /liter. 



desirable. The agricultural industry prolongs the availability of 
nitrogen fertilizer by applying N-SERVE [2-chloro, 6-(trichloro- 
methyl) pyridine], an inhibitor specific for Nitrosoinonas (Campbell 
and Aleem, 1965). When the oxidation of ammonia to nitrite is 
inhibited, the nitrogen remains in a relatively immobile form, 
ammonia, but it is still available for plants. Pesticides such as 
lindane, Malathion, and Baygon also inhibit nitrification at this first 
stage (Garretson and San Clemente, 1968). It may also be desirable 
to control nitrification in streams and lakes because it contributes a 
significcint oxygen demand in some waters. Theoretically, 4.57 mg of 



298 



HOLM AND COX 




Fig. 4 Impact of the organic arsenical, cacodylic acid, on Nitro- 
bacter. •, no arsenic; Z\ 100 mg As/liter; and A, 1000 mg As/liter. 



molecular oxygen are required to oxidize 1 mg of ammonia nitrogen 
to nitrate nitrogen (Young, 1969). 

Our results show that arsenate inhibits the second step of 
nitrification to a greater degree than it does the first stage. This was 
reflected in a delay in the oxidation of nitrite at low concentrations 
of arsenate; at high levels no nitrite was oxidized within 25 days. The 
mechanism of this inhibition was not studied. Button and Dunker 
(1971), however, showed that arsenate interrupts phosphate metabo- 
lism in some microorganisms. Torstensson (1974) reported that 
MCPA, 2,4, 5-T, and Linuron inhibit Nitrobacter and cause an 
accumulation of nitrite. 

Nitrite in the environment is undesirable because of its toxicity 
to biota (National Academy of Sciences, 1973) and its possible 
implication in the formation of carcinogenic nitrosamines (Lijinsky 



IMPACT OF ARSENICALS ON NITRIFICATION 299 

aiid Epstein, 1970; Elespuru and Lijinsky, 1973; Eisenbrand, 
Ungerer, and Preussmann, 1975). 

Generally organic arsenicals are reported to be between 10 and 
100 times less toxic to biota than inorganic arsenicals (Versar, Inc., 
1976). Our results showed this to be the case. Although arsenic in the 
form of arsenate increased the lag phase of Nitrobacter at concentra- 
tions as low as 0.1 and 1 mg/liter, cacodylic acid affected the 
nitrifiers only at arsenic concentrations of 100 mg/liter and above. 
Bollen, Norris, and Stowers (1977), studying forest floors and forest 
soils treated with either cacodylic acid or MSMA, concluded that 
these organic arsenicals should not have a significant adverse effect 
on nitrogen metabolism of forest-floor and soil microorganisms. 

In aerobic systems, cacodylic acid is readily degraded to arsenate 
(Woolson and Kearney, 1973). This fact, coupled with our observa- 
tion of arsenate toxicity towards nitrifiers, points toward a potential 
temporary buildup of nitrite in environments receiving high levels of 
the nontoxic arsenical. 

In summary, our study showed (1) that these nitrification 
systems provide reproducible results, (2) that Nitrobacter-type 
organisms used in these systems are sensitive to arsenate, and (3) that 
cacodylic acid is not directly toxic to nitrifiers. Field investigations 
should be completed to test whether arsenicals inhibit Nitrobacter in 
field situations. 

DISCLAIMER 

Mention of tradenames of commercial products does not 
constitute endorsement or recommendation for use. 

REFERENCES 

Bollen, W. B., L. A. Norris, and K. L. Stowers, 1977, Effect of Cacodylic Acid 

and MSMA on Nitrogen Transformations in Forest Floor and Soil, J. 

Environ. Qual., 6: 1-3. 
Button, D. K., and S. S. Dunker, 1971, Biological Effects of Copper and Arsenic 

Pollution, Report No. R71-8, Institute of Marine Science, University of 

Alaska, College. 
Campbell, N. E. R., and M. I. H. Aleem, 1965, The Effect of 2-Chloro, 

6-(Trichloromethyl) Pyridine on the Chemoautotrophic Metabolism of 

Nitrifying Bacteria, Anionic van Leeuwenhoek J. Microbiol. SeroL, 31: 

137-144. 
Curtis, E. J. C, K. Durrant, and M. M. Harmon, 1975, Nitrification in Rivers in 

the Trent Basin, Water Res., 9: 255-268. 
Ksenbrand, G., O. Ungerer, and R. Preussmann, 1975, The Reaction of Nitrite 

vidth Pesticides. II. Formation, Chemical Properties and Carcinogenic 



300 HOLM AND COX 

Activity of the N-Nitroso Derivative of N-Methyl-1-Naphthyl Carbomate 

(Carbaryl), Food Cosmet. Toxicol., 13: 365-367. 
Elespuru, R. K., and W. Lijinsky, 1973, The Formation of Carcinogenic Nitroso 

Compounds from Nitrite and Some Types of Agricultural Chemicals, Food 

Cosmet. Toxicol., 11: 807-817. 
Environmental Protection Agency, 1974, Methods for Chemical Aiialysis of 

Water and Wastes, Publication No. EPA-625/6-74-003, Washington, D.C. 
FUermans, C. B., B. B. Bohlool, and E. L. Schmidt, 1974, Autecological Study 

of the Chemoautotroph Nitrobacter by Immunofluorescence, Appl. 

Microbiol., 27: 124-129. 
Garretson, S. L., and C. L. San Clemente, 1968, Inhibition of Nitrifying 

Chemolithotrophic Bacteria by Several Insecticides, J. Econ. Entomol., 61: 

285-288. 
Hardy, R. W. F., and R. D. Holsten, 1972, Global Nitrogen Cycling: Pools, 

Evolution, Transformations, Ti'ansfers, Quantitation and Research Needs, in 

The Aquatic Environment: Microbial Transformations and Water 

Management Implications, symposium sponsored by EPA Office of Water 

Programs Operations, October 197 2, pp. 87-132, U.S. Government Printing 

Office, Washington, D.C, Stock No. 5501-00615. 
Laveglia, J., and P. A. Dahm, 1974, Influence of AC92,100 (Counter) on 

Microbial Activities in Three low^a Surface Soils, Environ. Entomol., 3: 

528-533. 
Lijinsky, W., and S. S. Epstein, 1970, Nitrosamines as Environmental Car- 
cinogens, A^a^wre, 225: 21-23. 
National Academy of Sciences, 1973, Water Quality Criteria 1972, Washington, 

D.C, Publication No. EPA-R3-7 3-003, prepared for Environmental Protec- 
tion Agency, Washington, D.C. 
Steel, R. G. D., and J. H. Torrie, 1960, Principles and Procedures of Statistics, 

1st ed., pp. 109-110, McGraw-Hill Book Company, Inc., New York. 
Technicon Corp., 1971, Industrial Method, AAII, Report No. 98-70W, Tarry- 
town, N.Y. 
Torstensson, L., 1974, Effects of MCPA, 2,4, 5-T, Linuron and Simazine on 

Some Functional Groups of Soil Microorganisms, Swedish J. Agric. Res., 4: 

151-160. 
Tuffey, T., 1973, The Detection and Study of Nitiification in Streams and 

Estuaries, Ph.D. Thesis, Rutgers University, New Brunswick, N.J. 
Versar, Inc., 1976, Technical and Microeconomic Analysis, Task III— Arsenic and 

Its Compounds, Publication No. 560/6-76-016, prepared for Environmental 

Protection Agency, Washington, D.C. 
Woolson, E. A., and P. C. Kearney, 1973, Persistence and Reactions of 

^"^C-Cacodylic Acid in Soils, Environ. Sci. TechnoL, 7: 47-50. 
Young, J. C, 1969, Chemical Methods for Nitrification Control, in Proceedings 

of the 24th Industrial Waste Conference, Purdue University, Lafayette, Ind., 

May 6-8, 1969, pp. 1090-1102. 



COPPER SENSITIVITY OF ADULT 
PACIFIC OYSTERS 



F. L. HARRISON and D. W. RICE, JR. 

Environmental Sciences Division, Lawrence Livermore Laboratory, 

University of California, Livermore, California 



ABSTRACT 

Sensitivity of the Pacific oyster, Crassostrea gigas, to copper w^as evaluated in 
experiments of about 2-w^eeks duration. Groups of 8 to 10 animals were exposed 
to copper concentrations ranging from 100 to 1300 /ig/liter in a high-volume 
flow-through bioassay system. Copper concentrations in the oysters and the 
major chemical form of copper in the water were determined. In addition, 
experiments were performed with Cu to determine accumulation rates and 
distribution. The family of mortality curves of time vs. concentration for oysters 
was unlike that for other organisms in that the greatest mortality at 96 hr 
occurred in animals at intermediate rather than high copper concentrations. 
However, typical mortality curves were obtained by correcting the duration of 
copper exposure of each oyster by a factor related to the amount of time the 
shells were open. Significant mortalities occurred at copper concentrations of 
200 /ig/liter and higher. Analysis of the data yields an LC50 at 48 hr of 
650 /ig/liter, an LC50 at 96 hr of 430 jug/liter, and an incipient LC50 of 
230 /ig/liter. Distributions of ^"^Cu in oysters after a 24-hr exposure differed in 
animals maintained in water containing high and low concentrations of copper. 
The flux of copper into tissues was related to copper concentrations in the 
water; this indicated that there was little metabolic regulation. 



Shellfish resources of estuarine and marine ecosystems can be 
harmed by increased levels of heavy metals in water. Of the heavy 
metals commonly released as a result of man's activities, copper is of 
special interest because of the known sensitivity of aquatic organisms 
to it (Becker and Thatcher, 1973). Oysters accumulate copper 
(Galtsoff, 1964; Pringle et al., 1968; Shuster and Pringle, 1969; 

301 



302 HARRISON AND RICE 

Drifmeyer, 1974; Okazaki, 1976) and are harvested commercially in 
large numbers as an important shellfish consumed by man. 

Although a considerable amount of information exists on 
quantities of copper in oysters from pristine and polluted waters 
(Brooks and Rumsby, 1965; Establier, 1972; Windom and Smith, 
1972; Thrower and Eustace, 1973; Estabher and Pascual, 1974; 
Ayling, 1974; Boyden and Romeril, 1974; Cronin et al., 1974; 
Ratkowsky et al., 1974; Huggett, Cross, and Bender, 1975; Mackay 
et al., 1975; Frazier, 1975; 1976), very little data are available on the 
sensitivity or accumulation rates of copper in the adult oyster. 
Previously reported LC5 values at 96 hr range from 500 to 1900 ng 
Cu/liter (Galtsoff, 1932; Fujiya, 1960; Okazaki, 1976). Neither 
Galtsoff nor Fujiya determined the concentrations and chemical 
forms of copper to which the oysters were exposed; Okazaki 
analyzed the bioassay water for total copper in his experiments. 

Our studies were initiated to determine the effects on oysters of 
increased levels of copper in water. Under controlled laboratory 
conditions we determined the effects on mortality rates, on copper 
levels in the soft tissues, and on accumulation rates and tissue 
distributions of ^"^Cu. Amounts and major chemical forms of copper 
in the bioassay waters and amounts of copper in the oysters were 
measured. 



MATERIAL AND METHODS 

Experimental Population 

Oysters, Crassostrea gigas, were obtained from the Coast Oyster 
Company beds in Areata Bay, the shallow north arm of Humboldt 
Bay, Calif. They were shipped by air to San Francisco, transported 
immediately by truck to Lawrence Livermore Laboratory, and then 
maintained for 7 to 10 days in a 10,000-gal recirculating seawater 
system before testing. Water in this system was continuously 
refiltered and was kept between 10 and 12°C by refrigeration. The 
water for the bioassay system was collected before the experiment 
and stored in a 10,000-gal underground tank. Water in the circulating 
system and in the storage tank was obtained from the University of 
California Marine Station at Bodega Bay, Calif. This water is pumped 
from the sea off the open coast in an area that receives little 
anthropogenic input. The water contains low levels of trace metals, 
dissolved organics, and particulate material. Although the oysters 
were reported to be 3 years old, they varied considerably in size. Soft 



COPPER SENSITIVITY OF ADULT PACIFIC OYSTERS 303 

body masses were typically between 30 and 60 g. Oysters were 
scrubbed before random selection for placement in the bioassay 
system. 

Toxicity Experiments 

Bioassay System 

Animals were exposed to copper in a flow-through bioassay 
system. The exposure solutions were introduced by gravity from a 
mixing chamber into 10-liter 5- by 40- by 48-cm plastic trays 
containing 10 oysters placed hinge side up at known locations. 
Filtered seawater and CuCh solutions were pumped into the mixing 
chambers at predetermined rates to provide the desired copper 
concentrations. The volume of water in the exposure tray was 
maintained constant with an outflow siphon. The flow of seawater 
from the trays was 6.6 liters/hr. Replacement of 90% of the seawater 
in the tray required approximately 3.4 hr. 

Gentle streams of bubbles from outlets arranged in a 5- by 15-cm 
grid at the bottom of the trays aerated and mixed the seawater in the 
exposure trays. All exposure trays were immersed in a water bath 
whose temperature was monitored and maintained at 12.8 ± 1°C. 
Continuous illumination was provided because we observed that 
some oysters responded to abrupt changes in light intensity by 
closing the valves of their shells. The salinity and pH of the bioassay 
water were 31.1% o and 8.08 ± 0.05, respectively. 

During the 10- to 12-day experiments, observations were made at 
4-hr intervals from 8:00 a.m. to 12:00 p.m. (no observations were 
made at 4:00 a.m.). At each observation the amount of valve 
separation of the shell was recorded. Gaping oysters (having a 
separation of ~1 cm between the v£ilves) were gently tickled with a 
blunt, soft, plastic probe to check for muscular responses. Animals 
that did not respond were considered dead and were removed from 
the bioassay system. At the termination of the experiment, oysters 
alive in the 230 idg Cu/liter and control trays were sacrificed. 

Copper Analyses of Oysters 

Oysters were weighed intact; the bodies were removed from the 
shells; and the soft tissues were weighed before freezing for later 
dissection. To prepare for copper analyses, we dissected the animals 
while they were still partially frozen into gills, digestive glands and 
stomachs, and remaining tissues. Tissues were dried at 100°C, ashed 
at 450°C, and wet ashed in a mixture of HCl and HNO3 for copper 
analysis on an atomic absorption spectrometer. 



304 HARRISON AND RICE 

Copper Analyses of Bioassay Water 

Total and ionic copper concentrations in the bioassay water were 
measured at 1- to 3-day intervals during the test period. Water was 
collected either by siphoning directly from the trays over a 5-min 
interval (grab sample) or by continuously pumping from the tray at a 
low rate over a 2- to 3-day interval (integrated sample). Both tot£il 
and ionic copper concentrations generally were measured in grab 
samples, but only total copper was measured in integrated samples 
since they were acidified to pH 1 during collection. 

Total copper in samples containing copper concentrations 
>400 jUg/liter was determined by direct aspiration of seawater into 
the flame of the atomic absorption spectrometer and in samples with 
copper concentrations >10 yug/liter by direct injection into a graphite 
furnace. 

Ionic copper, operationally defined as the fraction retained by 
Chelex 100 resin (Bio-Rad Laboratories), was determined by the 
method of RUey and Taylor (1968). Eluants from the columns were 
analyzed directly in the flame or in the graphite furnace. 

Accumulation of ^'*Cu 

Groups of oysters were exposed in refrigerated aquariums to 
^ "* Cu-labeled seawater containing concentrations of approximately 
1.0, 800, or 2400 /ig Cu/liter. Sixteen oysters were maintained at 
each concentration, and four animals were sampled from each system 
after 1, 5, 10, and 24 hr of exposure. 

The initial amount of ^"^Cu in the water at all three copper 
concentrations was 300 pCi/liter. Standards of ^^Cu were made 
when the isotope was added to the aquarium water. At regular 
intervals concentrations of ^"^Cu in aquarium waters were compared 
with the standards. Additions of ^"^Cu were made to aquarium 
waters when the ^'*Cu level was lower than expected from decay 
alone so that changes in the water reflected only radioactive decay. 

To prepare for ^^Cu analysis, we weighed oysters whole, 
removed the soft tissues from the shells, and dissected them into 
mantles, gills and labial palps, digestive glands and stomachs, gonads 
and intestines, adductor muscles, body fluids, and remains. Each 
tissue was weighed and counted in a gamma well counter. 

All counts of water and tissues were corrected for background 
and counting efficiency and then for decay to the time the 
experiment began. 



COPPER SENSITIVITY OF ADULT PACIFIC OYSTERS 305 

RESULTS 

Toxicity Experiments 

The family of mortality curves from our first two experiments 
with oysters was difficult to interpret because increased copper 
concentrations in the water did not consistently result in increased 
mortality rates; 100% mortality of the oysters occurred first in the 
water containing 500 rather than 900 or 1500 jUg Cu/liter. Since 
oysters can prevent the entrance of water into their mantle cavities 
by tight closure of the valves of the shell, they might have reduced 
their exposure to copper in this way. In experiments 3 and 4, oysters 
were observed at 4-hr intervals from 8:00 a.m. to 12:00 p.m. so that 
the exposure of each oyster could be corrected for the difference 
between the time the animal was first observed with its shell open 
and the time it was introduced into the water and also by the ratio of 
the number of times the shell was seen opened to the number it was 
seen closed (Table 1). Typical mortality curves were generated with 
adjusted exposure times (Fig. 1), and, in all further measures of 
toxicity, we used adjusted exposure time. A logit instead of a probit 
analysis was performed on the time-vs. -mortality data (American 
Public Health Association, 1975). Differences between the slopes of 
the lines fitted to the curves and the intercepts of the lines were 
tested using a t statistic (Snedecor and Cochran, 1967). The slopes 
were significantly different from the controls (P < 0.01), but the 
intercepts were not. 

Sensitivity to copper sometimes differed between the two groups 
of oysters in experiments 3 and 4. Such differences are expected 
when oysters are collected at different times, the number of animals 
tested at each concentration is small, and the exposure conditions 
and concentrations are not exactly identical (Table 1). 

The concentration-vs.-time-to-50%-mortality data from experi- 
ments 3 and 4 were used to generate a toxicity curve (American 
Public Health Association, 1975). Acute lethality stopped at con- 
centrations below about 230 ng Cu/liter (Fig. 2). In this group of 
oysters, the LC5 value (lethal concentration for 50% of the test 
population) ±95% confidence interval at 48 hr was 650 ± 100 idg 
Cu/liter; at 96 hr, 430 ± 60 /ug Cu/liter; and at 168 hr, 30 ± 100 )Ug 
Cu/liter. The incipient lethal or threshold concentration is defined as 
the concentration that kills 50% of the population during an 
exposure sufficiently long for acute lethal action to cease (Sprague, 
1969). In this group of oysters, the estimated incipient lethal 
concentration (incipient LC5 ) was 230 ± 100 /ig Cu/liter. 



306 



HARRISON AND RICE 



TABLE 1 

CONDITIONS OF TOXICITY TESTS OF COPPER TO ADULT OYSTERS 











Bioassay 


test system 








Condition 


1 


2 


1 


3 




4 


C 


i 


6 


Experiment 3 




















Copper 




















Total,* Mg/liter 


3 (control) 


180 




310 




580 


680 




1050 


Range, Mg/liter 




160- 


-190 


270- 


-360 


480—620 


640- 


-700 


1000-1100 


Ionic, % 




84 ± 


5 


94 ± 


3 


86 ±6 


89 ± 


6 


76 ± 8 


Oysters 




















Number 


10 


10 




9 




8 


8 




8 


Ratio of opened 




















to closed 


0.59 


0.66 




0.72 




0.64 


0.43 




0.32 


LTso 




















X 




164 




163 




59 


49 




12 


95% CIt 




±47 




±59 




±12 


±15 




±6 


Experiment 4 




















Copper 




















Total,* Mg/liter 


1 (control) 


230 




440 




510 


760 




1300 


Range, jUg/liter 




210- 


-270 


400- 


-600 


410-570 


750- 


-760 


1100-1400 


Ionic, % 




76 ± 


5 


74 ± 


10 


86 ± 6 


83 ± 


2 


78 + 2 


Oysters 




















Number 


10 


10 




10 




10 


10 




9 


Ratio of opened 




















to closed 


0.60 


0.74 




0.79 




0.82 


0.56 




0.48 


LTso 




















X 








95 




64 


24 




18 


95% CIt 








±7 




±6 


±10 




±5 



*Mean values of six to eight determinations. 

"t"In calculating the 95% confidence intervals, we assumed the error mean square to be 1. 



At each test concentration an LT5 value (time required for 50% 
mortality of the test population) was determined. The LT5 values 
ranged from 164 hr at the lowest concentration to 18 hr at the 
highest concentration (Table 1). 

Concentrations of total and ionic copper in the water were 
relatively constant during the test period. Deviations from the 
average concentrations (Table 1) can be attributed to (1) small 
changes in inflow rates resulting from conformational changes in the 
tubing of the pumping system, (2) changes in rates of accumulation 
of copper from the water by the oysters, and (3) analytical errors. 
The ionic fraction was generally greater than 75% of the total 
amount of copper present (Table 1). 

Copper Concentrations in Oysters 

Oysters maintained at increased levels of copper in the water 
contained more copper than those in control groups (Table 2). The 



COPPER SENSITIVITY OF ADULT PACIFIC OYSTERS 



307 



100 


Aooo / 


^ 


1 "^ — 


a) 


s? 


/ 68o/y 


y 580 






> 80 








— 


1- 


h. QhU 








_i 


1 11 






C 


< 
1— „„ 


L // 




P^"""" 


c 


£ 60 


— / / / 




^^5 


— 


O 


/ / / 




X 310,180 




S 


lA An 




/JO 




LU 


1 / / 


/ 






> 40 


^ / /] 


o /^ 




— 


H 


1 / / 


/ 






< 


1 / / 


n/ 






_l 


LI ^ / 


f</ 






D { 


rl 1 r^ 


y 






S 20 


111 


d 






3 


i 1 J 


f 






n 


IL^^ 


] 


1 1 






50 100 150 200 50 

ADJUSTED EXPOSURE TIME, hr 



100 



150 



200 



Fig. 1 Cumulative mortality of adult oysters continuously exposed 
to copper, (a) Experiment 3. (b) Experiment 4. Exposure time was 
adjusted by the ratio of amount of time the shells were opened to 
the time closed. Numbers on the curves are copper concentrations in 
micrograms per liter. 



>- 



DC 

o 



55 
O 
ID 




0.2 



0.3 0.4 0.5 0.6 
COPPER, A(g/ml 



0.8 



1.5 



Fig. 2 Toxicity curve for adult oysters continuously exposed to 
copper based on data from experiments 3 and 4 with adjusted 
exposure times. The least square equations for this line are Y = 
6.3595- 1.6619X and r^ = 0.9645. The dashed lines (= = = =) 
indicate ±95% confidence limits around the x value. 



308 . HARRISON AND RICE 



TABLE 2 



AVERAGE COPPER CONCENTRATIONS* IN WATER 
AND OYSTERS FROM EXPERIMENT 4 



Copper in 










bioassay water, 






Digestive gland 


Remainder 


A^g/liter 


Whole body 


Gills 


and stomach 


of body 


1 (control) 










/^g/g 


19.4 


65.0 


42.0 


15.3 


total iJg 


1,790 


426 


131 


1,230 


230 










A^g/g 


221 


368 


382 


195 


total /ig 


11,400 


1,530 


1,250 


8,650 


440 










/^g/g 


73.8 


95.2 


90.9 


70.8 


total Idg 


3,380 


404 


237 


2,740 


510 










/^g/g 


68.4 


99.9 


85.7 


63.3 


total Idg 


3,510 


515 


251 


2,750 


760 










t^glg 


57.6 


111 


50.8 


53.3 


total /ig 


2,310 


404 


126 


1,870 


1300 










Mg/g 


49.6 


112.0 


66.2 


42.4 


total Idg 


2,770 


592 


164 


1,990 



♦Fractional standard deviation (SD/mean) generally ranged from 
0.2 to 0.4 for the concentrations expressed in micrograms per gram 
and from 0.4 to 0.6 for the total amounts. 



increases were not linear with concentrations in the water, however; 
the highest levels were found in the oysters in water containing 
230 [Jig Cu/liter. The quantities of copper contained in oysters held in 
seawater with copper concentrations greater than 230 jUg/liter did 
not differ significantly from each other. 

The quantities of ^"^Cu (decay corrected) in the total soft tissues 
at the end of the 24-hr exposure were different from oysters in each 
of the three copper concentrations. The highest concentrations of 
^^Cu were detected in animals held in water with the lowest copper 
concentrations (Table 3). Some regulation of copper accumulation is 
suggested; the '''^Cu concentrations would have been similar in the 
animals from the three test systems if the amount of copper 
accumulated per unit time was directly proportional to the copper 
concentration in the water (no homeostasis). 

The ^"^Cu in the tissues of oysters placed in each of the three 
copper concentrations increased with time, except in the digestive 



COPPER SENSITIVITY OF ADULT PACIFIC OYSTERS 



309 






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CQ 



310 HARRISON AND RICE 

glands and stomachs of control animals (Table 3). The highest ^"^Cu 
concentrations in tissue were in the digestive glands and stomachs of 
control oysters and in the gills of oysters at 800 and 2400 jug 
Cu/liter. Although ^'^Cu concentrations in the gills of control 
animals and of those at 800 /jg Cu/liter were similar after the first 
hour, concentrations in the digestive glands were more than 20 times 
higher in the controls than in oysters at 800 /ig Cu/liter. These results 
indicate that a much greater fraction of the ^ '^ Cu-labeled copper 
reaching the gills is transported to the digestive glands and stomachs 
of animals at low rather than high copper concentrations. However, 
even though the influx of '''^Cu into digestive glands and stomachs is 
greater in controls, the influx of stable copper is less. The specific 
activity was 800 times greater in controls than in oysters at 800 fig 
Cu/liter, whereas the ^"^Cu in digestive glands and stomachs was only 
20 times greater in control animals than in those at 800 [dg Cu/liter. 
The accumulation rates of *''*Cu in the soft tissues of oysters 
decreased with increasing concentrations of copper in the water 
(Table 3). The average and the maximum amounts of ^'^Cu increased 
linearly for the first 10 hr at all three exposure concentrations. The 
average rates of accumulation in the oysters in 1.0 (control), 800, 
and 2400 ng Cu/liter were 390, 260, and 60 pCi g^' wet weight 
hr~^, respectively. The maximum rates at all three con- 
centrations were about 1.7 times the average rates. Since the initial 
specific activity of the water was known, calculation of the 
accumulation rates of stable copper was possible. The rates of 
accumulation (jug Cu/hr) of a hypothetical oyster whose wet weight 
was 50 g were 0.25 for the control, 32 at 800 jug Cu/Uter, and 23 at 
2400 Mg Cu/liter. 



DISCUSSION 

The LCj that we obtained for C. gigas at 96 hr (430 jug Cu/liter) 
is higher than that obtained for many other aquatic species (Becker 
and Thatcher, 1973) and considerably lower than the 1900 ^g 
Cu/liter for oysters reported by Fujiya (1960), but it is in the same 
range as the 500 /^g/liter obtained by Okazaki (1976). Fujiya used a 
static system and did not determine the final copper concentration in 
the bioassay water. We found in our preliminary experiments that 
oysters could remove a significant fraction of the copper from test 
waters. When the flow rate was 1.5 liters/hr and the copper 
concentration was <500 /jg/liter, the outflow concentration was 
about half that of the inflow. When the copper concentration was 
between 500 and 1200 /ig/liter, the outflow concentration was about 



COPPER SENSITIVITY OF ADULT PACIFIC OYSTERS 311 

three-fourths that of the inflow. The actual copper concentrations to 
which the animals were exposed in Fujiya's experiments were 
probably lower than he reported. 

The greatest mortality at 96 hr in our experiments and in those 
of Okazaki (1976) occurred at intermediate rather than at high 
copper concentrations. Our observations indicate that this response 
resulted from the oysters' remaining open for shorter periods in the 
water containing high concentrations of copper. In an early 
experiment one oyster maintained at 1200 /ig Cu/liter was closed 
during each observation period for 14 days. When sacrificed at the 
end of the experiment, the oyster appeared normal, and its heart was 
beating regularly. We observed during preliminary experiments that 
oysters will stop circulating seawater when copper is added to it at 
levels >1000 Mg/hter. Establier and Pascual (1974) noted increased 
incidence of shell closure in C. angulata at high copper concentra- 
tions. This response of oysters may serve as protection from episodic 
releases of copper. Moreover, it suggests that oysters may not be the 
best biological indicators of copper pollution even though they have 
been used as such in the past (Huggett, Bender, and Stone, 1973). 
They may accumulate copper only when the concentration in the 
water is at low and intermediate levels. Since accumulation may not 
be continuous, the copper content of oysters may not reflect the 
total amount of copper in their environment. 

Mussels, like oysters, can detect copper in their environment. 
Mytilus edulis avoids the detrimental consequences of exposure to 
copper by closing its shell valves (Davenport, 1977). Davenport 
suggested that mussels and other animals possessing similar closure 
mechanisms are of doubtful use as a biological pollutant-monitoring 
system. 

The toxic response in some 6inimals is attributed to the 
concentration of ionic copper in the water (Sunda and Guillard, 
1976). In our experiments the ionic fraction (as operationally 
defined) was greater than 75% of the total in all test systems. If 
oysters are sensitive to only the ionic form, however, the LC50 
values for the toxic copper form should be lower than that reported. 

The impact of past releases on oyster populations can be 
approximated by comparing the concentrations of copper in past 
releases to concentrations known to elicit a toxic response in oysters. 
Two important sources of copper in marine systems are municipal 
wastes and power-plant effluents. A survey of 108 municipal waste 
discharges along the Atlantic coast reported concentrations of 20 to 
5900 Mg Cu/hter; 50% of the effluents contained more than 100 jug 
Cu/liter (Mytelka et al., 1973). These represent the total copper 



312 HARRISON AND RICE 

concentrations in the waste at the point of discharge (before 
dilution) and do not indicate the fraction that might have been in a 
toxic form. A year-long survey at a single Pacific coastal power plant 
showed copper values in the intake and discharge waters to vary from 
0.1 to 5.8 jug Cu/Uter (Dorband et al., 1976). These values are in 
contrast to the 1800 /.ig Cu/liter (before dilution) discharged in the 
initial surge of water from the cooling system during startup at 
another power plant (Warrick, Sharp, and Friedrich, 1975). Until 
recently the California State Water Resources Control Board per- 
mitted concentrations in discharges of 200 jug Cu/liter for half a 
month and 300 /jg/liter for 10% of a month (California State Water 
Resources Control Board, 1972). Based on an analysis of acute 
toxicity, chronic toxicity, and reported seawater concentrations, the 
board has proposed amendments to the water quality control plan 
for ocean waters of California which have a water-quality objective 
of 5 jug Cu/liter in the receiving water (Klapow, 1978). This objective 
should adequately protect adult oysters because the estimated 
incipient lethal concentration for adults is 230 /ig Cu/liter. 

Organism mortalities resulting from heavy metals may be caused 
by (1) excessive amounts of a metal in tissues, (2) excessive rates of 
influx into tissues, or (3) inhibition of a vital metabolic process. In 
the first case, if the influx of copper into an organism is greater than 
its efflux, increased levels result; lethal amounts may accumulate in 
all tissues or in a special storage depot. We tested for the first 
possibility by copper analyses on the experimental animals and for 
the second possibility with ^"^Cu-uptake experiments. 

The results of copper analyses on test oysters show that the 
highest concentrations of copper were in oysters at 230 idg Cu/liter 
rather than at the higher concentrations in seawater. Also, levels of 
copper in oysters held in water containing more than 230 [dg Cu/liter 
did not increase with increasing concentrations in the water but were 
relatively constant. The duration of exposure was not always the 
same for oysters held at the same and at different concentrations, 
however. For example, exposure for oysters in water containing 
440 iUg Cu/liter ranged from 3.9 to 8.3 days. The concentrations in 
this group of animals did not increase consistently with increased 
exposure. The durations of exposure and the tissue concentrations 
(Cu/g wet weight) were: 3.9 days, 37.4 /ig; 4.2 days, 48.8 jUg; 5.2 
days, 92.1 and 86.5 Mg; 5.9 days, 82.5 Mg; 6.0 days, 77.6, 90.4, and 
107 fxg; 6.5 days, 48 jug; and 8.3 days, 68.2 fig. At 230 fig Cu/liter, 
the two animals that died at 8.8 and 9.4 days contained 60.0 and 
96.0 /ig Cu/g wet weight, respectively. Copper may be lost from 
animals near death as a result of permeability changes. The hearts of 



COPPER SENSITIVITY OF ADULT PACIFIC OYSTERS 313 

many oysters held in water containing high concentrations of copper 
were observed beating when they were removed from the shell; no 
significant difference in copper content was found in animals with 
and without a firm heartbeat. Permeability changes may occur 
before the heart is affected, however. Consequently, the results of 
the copper analysis do not demonstrate conclusively that morteility 
was caused by an excessive amount of copper in the tissues. 

Results of the ^ "^ Cu experiment indicate that the flux of copper 
is much greater in oysters maintained at 800 and 2400 /ig Cu/liter 
than in the controls in seawater. If the concentration of copper in 
oyster tissues were regulated, the flux should remain constant with 
changes in copper concentration in seawater. Since this did not 
occur, strict homeostatic control probably does not take place. The 
decreased rate of ^"^Cu accumulation with increased copper concen- 
tration does suggest a small amount of regulation of copper intake, 
however. Whether this is the result of changes in transport across 
membranes or changes in the circulation of seawater by the oyster is 
not known. 

Coombs (1974) reported that copper in oyster tissues occurs in 
at least two different forms, one a readily solubilized component and 
the second firmly bound to tissues. No information is available on 
which fraction is related to mortality. 



ACKNOWLEDGMENTS 

The research reported here was performed under the auspices of 
the U.S. Nuclear Regulatory Commission, research order 
No. 60-76-144, and the U. S. Department of Energy, contract 
No. W-7405-ENG-48. 

We thank Jack Dawson, Rose Carrillo, and James Alexander for 
their assistance in this investigation and the Coast Oyster Company, 
Eureka, Calif., for supplying the oysters. 

Reference to a company or product name does not imply 
approval or recommendation of the product to the exclusion of 
others that may be suitable. 

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the Pacific Oyster, Crassostrea gigas. Grown in the Tamar River, Tasmania, 
Water Res., 8: 729-738. 



314 HARRISON AND RICE 

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Boyden, C. R., and M. G. Romeril, 1974, A Trace Metal Problem in Pond Oyster 
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Coombs, T. L., 1974, The Nature of Zinc and Copper Complexes in the Oyster 
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Drifmeyer, J. E., 1974, Zn and Cu Levels in the Eastern Oyster, Crassostrea 
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Galtsoff, P. S., 1932, The Life in the Ocean from a Biochemical Point of View, 

J. Wash. Acad. Sci., 22: 246-257. 
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Bulletin 64, U. S. Fish and Wildlife Service, GPO. 

Huggett, R. J., M. E. Bender, and H. D. Stone, 1973, Utilizing Metal 
Concentration Relationships in the Eastern Oyster {Crassostrea virginica) to 
Detect Heavy Metal Pollution, Water Res., 7: 451-460. 

, F. A. Cross, and M. E. Bender, 1975, Distribution of Copper and Zinc in 

Oysters and Sediments from Three Coastal-Plain Estuaries, in Mineral 
Cycling in Southeastern Ecosystems, ERDA Symposium Series, Augusta, 
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pp. 224-238, CONF-740513, NTIS. 

Klapow, L. A., 1978, California State Water Resources Control Board, 
Sacramento, personal communication. 

Mackay, N. J., R. J. Williams, J. L. Kacprzac, M. N. Kazacos, A. J. Collins, and 
E. H. Auty, 1975, Heavy Metals in Cultivated Oysters {Crassostrea com- 



COPPER SENSITIVITY OF ADULT PACIFIC OYSTERS 315 

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Aust. J. Mar. Freshwater Res., 26: 31-46. 
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in Wastewater and Treatment Plant Effluents, J. Water Pollid. Control Fed., 

45: 1859-1864. 
Okazaki, R. K., 1976, Copper Toxicity in the Pacific Oyster Crassostrea gigas. 

Bull. Environ. Contam. Toxicol., 16: 658-664. 
Pringle, B. H., D. E. Hissong, E. L. Katz, and S. T. Mulawka, 1968, Trace Metal 

Accumulation by Estuarine Mollusks, J. Sanit. Eng. Diu., Am. Soc. Civ. Eng., 

94: 455-475. 
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Study of the Concentration of Some Heavy Metals in Tasmanian Oysters, J. 

Fish. Res. Board Can., 31: 1165-1171. 
Riley, J. P., and D. Taylor, 1968, Chelating Resins for the Concentration of 

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Shuster, C. N., Jr., and B. H. Pringle, 1969, Trace Metal Accumulation by the 

American Eastern Oyster, Crassostrea virginica, Proc. Nat. Shellfish Assoc, 

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State University Press, Ames. 
Sprague, J. B., 1969, Measurement of Pollution Toxicity to Fish. I. Bioassay 

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Activity and the Toxicity of Copper to Phytoplankton, J. Mar. Res., 34: 

311-329. 
Thrower, S. J., and I. J. Eustace, 1973, Heavy Metal Accumulation in Oysters 

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Corrosion Investigations Related to the Testing of the Diablo Canyon Unit 1 

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Board Can., 29: 450-452. 



AN IN SITU STUDY OF CADMIUM STRESS 
IN A NATURAL ZOOPLANKTON COMMUNITY 



J. S. MARSHALL and D. L. MELLINGER 

Ecological Sciences Section, Radiological and Environmental Research 

Division, Argonne National Laboratory, Argonne, Illinois 



ABSTRACT 

The effects of elevated cadmium concentrations on a natural zooplankton 
community were studied in situ in Green Bay, Lake Michigan, during the 
summer of 1976, with polyethylene carboys as enclosures. The results of five 
experiments showed that cadmium concentrations as low as 5 /Jg/liter, the 
lowest concentration tested, caused large and highly significant effects 
(P < 0.001) on both functional and structural attributes of the zooplankton 
community within 9 days. The effects of enclosure up to 15 days were mostly 
insignificant. Functional responses, as indicated by changes in the different 
species' rates of increase, showed highly significant differences (P < 0.001) 
among total Cladocera, Calanoida, and Cyclopoida, but no differences among 
species in each of these major groups. Structural responses included reduced 
total abundance, species diversity (3 indexes), and community similarity 
(2 indexes). The results indicate that added cadmium concentrations much lower 
than 5 /Jg/liter probably would cause detectable effects within 9 days and that 
incubations up to 15 days are feasible. 



The need for experimental studies of pollutant stress in whole 
communities and ecosystems, as opposed to lower levels of organiza- 
tion, has been emphasized recently by several ecologists (Barrett, 
Van Dyne, and Odum, 1976; Jernelov and Rosenberg, 1976; Fisher 
and Wurster, 1974). The usefulness of in situ experiments in studies 
of toxic stress in a marine ecosystem was shown by Reeve et al. 
(1976), who concluded that the zooplankton community was 
probably the component most affected. Although it has been 
possible to maintain nearly normal zooplankton communities in 

316 



AN IN SITU STUDY OF CADMIUM STRESS 317 

enormous enclosures (18,000 m-^) up to 22 months in a small lake 
(Smyly, 1976), the use of large enclosures in the Great Lakes has 
been limited by their high unit cost and susceptibility to storm 
damage (Schelske and Stoermer, 1972). 

Cadmium has long been recognized as a highly toxic element, but 
only recently has concern been expressed over the impact of 
anthropogenic emissions of cadmium into the environment. Man's 
activities now appear to be contributing more cadmium to streams 
than is contributed by natural processes (Fleischer et al., 1974). 
Unfortunately, the concentrations and distribution of cadmium in 
the Great Lakes remain poorly knovm. The average concentration of 
cadmium in Lake Ontario is 0.09 /jg/liter (Chau et al., 1970). In the 
heavily polluted, extreme southern portion of Green Bay, Lake 
Michigan, cadmium concentrations ranged from 1.0 to 1.4 ^ig/liter 
during 1973 (Wiersma et al., 1974). Recent analyses at Argonne 
National Laboratory indicate, however, that the concentration of 
cadmium in the main body of Lake Michigan is less than 0.1 )Ug/liter 
(Tisue, 1976). 

The purpose of our study was to determine the short-term effects 
of increased cadmium concentrations on the zooplankton compo- 
nent of the Lake Michigan ecosystem. We used an in situ method 
designed to overcome some of the limitations of large enclosures for 
experiments in large lakes. Following guidelines recommended by 
Barrett, Veqi Dyne, and Odum (1976) for ecosystem stress studies, 
we studied both functional and structural attributes of the zooplank- 
ton component under seminatural conditions and evaluated the 
relative sensitivities of different indexes of stress. 



MATERIALS AND METHODS 

Field Methods 

During the summer of 1976, five in situ cadmium-enrichment 
experiments were conducted in northern Green Bay, Lake Michigan. 
Two sampling and incubation stations were located where the 
bottom depth is approximately 30 m, 1 km northwest of the larger 
of the Sister Islands off Sister Bay, Wisconsin. Water was collected 
from different depths in the lower half of the epilimnion (6 to 12 m) 
with a nonmetaillic, 16-liter Kemmerer bottle and composited in a 
large mixing tub. In each experiment, two to four opaque polyethyl- 
ene carboys (8- or 20-liter capacity) for each of five levels of added 
CdCl2 were filled gradually with water from the mixing tub by 



318 MARSHALL AND MELLINGER 

adding small portions in turn to each carboy. Two to four additional 
carboys, which were not to be incubated, were filled at the same 
time. When all the carboys were nearly filled, those to be incubated 
were assigned prescribed cadmium additions at random. The concen- 
trations of added cadmium in the five experiments were 0, 50, 100, 
150, and 200 jug/liter in experiments 1 to 3; 0, 25, 50, 75, and 
100 Mg/liter in experiment 4; and 0, 5, 10, 20, and 40 /ig/liter in 
experiment 5. After the cadmium was added, each carboy was 
capped, thoroughly shaken, and finally filled completely through a 
small plughole in the cap to exclude all air bubbles. This last step is 
very important because of the propensity of small cladocerans, such 
as Bosmina, to become trapped at air— water interfaces. 

For in situ incubations the carboys were suspended in the 
epilimnion at depths of 2 to 12 m in the sampling area. Inclusive 
dates of the incubation periods for the five experiments were 1, 
July 22—26; 2, July 27- August 1: 3, August 20-27; 4, August 27— 
September 11; and 5, September 11—20. At the end of each incuba- 
tion, the zooplankton in each carboy were removed by filtering 
through a nylon net with apertures of either 153 jum (experiments 1 
to 3) or 85 /im (experiments 4 and 5), narcotized with "club soda" 
(Gannon and Gannon, 1975), and preserved in 4% Formalin. 

Laboratory Methods 

The zooplankton were identified vidth the aid of keys, illustra- 
tions, and descriptions in Edmondson (1959) and Torke (1974) by 
use of binocular compound and dissecting microscopes. The identifi- 
cation categories in each entire sample were enumerated in an 
open-top, chambered counting cell (Gannon, 1971) with a binocular 
dissecting microscope. Special care was taken to count only 
specimens that showed no signs of decomposition. 

Calculations and Definitions of Symbols 

As in the work of Edmondson (1968), rates of increase, r, were 
calculated from the equation 

In Nt - In Ni 

where Nt is the terminal number of individjaals of a given 
identification category in an incubated sample, Nj is the average 
initial number in the unincubated samples, and At is the duration of 
incubation in days. 



AN IN SITU STUDY OF CADMIUM STRESS 319 

Three indexes of species diversity were calculated according to 
HUl (1973): 

Nq = total number of identification categories (2) 

Ni =exp(-i: Pi In Pi) (3) 

'^? (4) 



N 

1 



where Pi is the proportional abundance of the different identification 
categories in a given sample. 

Two indexes of community similarity, S and S , were calculated 
according to Whittaker (1972): 



2C 



A + B 



(5) 



where A is the number of identification categories in the control 
samples, B is the number of categories in any single sample, and C is 
the number common to both; and 

S' = l-0.5 2:|APi| (6) 

where APi is the difference between the proportional abundance of a 
given identification category in any single sample and its average 
proportional abundance in the controls. 

RESULTS 

The effects of cadmium on functional attributes of the com- 
munity, as indicated by the relationships among average rates of 
increase (r) and added cadmium (micrograms per liter) for the 
predominant zooplankton groups and component species, were more 
consistent and much more pronounced than the effects of enclosure, 
which are discussed later. The linear regression coefficients (slopes) 
for relationships among average rates of increase and added cadmium 
(0 to 50 /ig/liter) for the three major groups of crustacean zoo- 
plankton in each of the five experiments are shown in Table 1. 
Friedman's analysis of variance by ranks (Siegel, 1956) indicates that 
the differences between slopes for cladocerans, calanoid copepods, 
and cyclopoid copepods are highly significant (P < 0.001). The mean 
regression coefficients for the Cladocera, Calanoida, and Cyclopoida 



320 



MARSHALL AND MELLINGER 



TABLE 1 

INCUBATION (EXPOSURE TIME) AND LINEAR REGRESSION 

COEFFICIENTS FOR RELATIONSHIPS AMONG RATES 

OF INCREASE AND ADDED CADMIUM FOR MAJOR GROUPS 

OF CRUSTACEANS FOR IN SITU EXPERIMENTS IN 

LAKE MICHIGAN* 



Experiment 



Exposure time, 
days 



Cladocera 



Calanoida 



Cyclopoida 



1 


4 


-0.0212 


-0.0049 


-0.0004 


2 


5 


—0.0202 


-0.0057 


-0.0005 


3 


7 


-0.0190 


-0.0084 


-0.0006 


4 


15 


-0.0059 


-0.0031 


-0.0018 


5 


9 


-0.0075 


-0.0071 


-0.0015 



*Added cadmium ranged from to 50 Idg/Mter. 



are -0.0131 ± 0.0032, -0.0058 ± 0.0009, and -0.0010 ± 0.0003, 
respectively (mean ± standard errors). 

The effects of cadmium on different species or other categories 
within each major crustacean group in experiment 5 are represented 
by the linear regression equations and corresponding lines fitted to 
the mean values, r (Fig. 1). The data from v^hich these values w^ere 
calculated are summarized in Table 2; summaries of the data from 
experiments 1 to 4 are available (Marshall and Van Reken, 1977). 
Differences in apparent sensitivity among species or other categories 
v^^ithin each major crustacean group, as indicated by the differences 
in the slopes (steepness) of the lines in Fig. 1, are quite small in 
comparison v^ith the differences among the major groups. The 
immature copepodites of both calanoid and cyclopoid copepods 
appear to be no more sensitive to cadmium than the adults are. 
Furthermore, the mean number of copepod nauplii in samples at 
each added cadmium level (Table 2) w^as not significantly different 
(P > 0.1) from that of the controls. 

At higher ranges of added cadmium (> 50 jug/liter) in experi- 
ments 3 and 4, the relationships between r and cadmium are better 
represented by curves (not shown) whose slopes decrease with 
increasing cadmium. This is most pronounced in Cladocera and is 
noticeable even for the to 20 ng Cd /liter range in the data for 
Bosminidae plus Daphnidae in Fig. 1. Even in this range the data are 
fitted better by an exponential function. In other words, the 
sensitivity of Cladocera in the range of to 5 fig Cd /liter is probably 
greater than that indicated by the slope of the line in Fig. 1. 



AN IN SITU STUDY OF CADMIUM STRESS 



321 



> 




10 20 30 40 10 20 30 40 10 20 30 40 

CADMIUM, Aig/iiter 

Fig. 1 Effects of cadmium on rate of increase, r, of (a) cyclopoid 
copepods, (b) calanoid copepods, (c) cladocerans, and (d) large 
rotifers. 



The mean numbers of nauplii, several rotifer species, and one 
large protozoan in the samples for experiment 5 are shown in 
Table 2. The effect of added cadmium on the large rotifers is shown 
in Fig. 1(d) by the linear regression equation and the corresponding 
line fitted through the average rates of increase, r, for the large 
rotifers in experiment 5. The apparent cadmium sensitivity of these 
rotifers, as indicated by the slope of the line, is comparable to that 
of calanoid copepods. Differences among mean numbers of Cera- 
tium hirundinella in incubated controls and unincubated samples 
indicated a pronounced effect of enclosure on this protozoan. The 
mean numbers remaining in incubated samples containing different 
levels of added cadmium were not significantly different from the 
controls (Table 2). 

The effects of cadmium on structural attributes of the crustacean 
zooplankton community are exemplified by decreases in total 
abundance, relative abundance of the major groups, species diversity, 



322 



MARSHALL AND MELLINGER 



TABLE 2 

NUMBER OF ZOOPLANKTON PER LITER (x 10) IN A 

CADMIUM-ENRICHMENT EXPERIMENT WITH IN SITU 

INCUBATION IN LAKE MICHIGAN* 





Unincubated 
samples 


Incubated samples 


with added cadmium, 


/Jg/liter 


Zooplankton 





5 


10 


20 


40 


Cladocera 














Leptodora kindtii 


0.4 ± 0.4 


0.4 ± 0.4 











1 ± 1 


Holopedium gibberum 


49 ±6 


1 ± 1 


0.4 ± 0.4 











Bosmina longtrostris 


37 ± 3 


39 ±3 


22 ± 8 


18 ± 1 


5 ± 1 


5 + 1 


Eubosmina coregoni 


144 ± 13 


125 ± 9 


3± 1 


4 ± 1 


2 ± 1 


1 ± 1 


Daphiiia retrocurua 


87 ± 10 


42±4 


22 ±6 


1 ± 1 


1 ± 1 


4 ± 2 


D. galeata mendotae 


13 ± 1 


10 ± 5 


7 ± 2 


5 ± 2 


3 + 1 


0.3 ± 0.3 


D. longiremis 


2 ± 2 


3 ± 3 


0.4 ± 0.4 











Cenodaphnia lacustris 


15± 1 


11 ±4 


3 ± 1 


1 + 1 





0.3 ± 0.3 


Chydorus sphaericus 


50 ± 1 


94 ± 5 


35 ± 7 


26 ± 10 


4 + 2 


8 ± 2 


Copepoda: Cyclopoida 














Cyclops vernalis 


2 ± 1 


3 ± 1 


5 ±2 


5±3 


3 ± 1 


7± 1 


C. bicuspidatus Ihomasi 


37 ± 9 


41 ± 5 


47 ± 11 


45 ±6 


36 ± 4 


32 ± 4 


Mesocyclops edax 


6 ± 1 


15 ± 2 


14 ± 2 


9 ± 1 


9 + 2 


11 ±2 


Tropocyclops prasinus 


47 ± 1 


40 ± 5 


38 + 5 


43 + 2 


31 ± 2 


17 ± 1 


Copepodites I — V 


231 ± 14 


169 ± 2 


146 ± 14 


144 + 8 


128 ±6 


95 ± 13 


Copepoda: Calanoida 














Eurytemora affinis 


2 + 1 


2 ± 1 


3 ± 2 


1 ± 


1 + 1 


1 + 1 


Diaptomus sppt 


9 ± 1 


12 ± 1 


6 ± 1 


9 ± 3 


5 ± 2 


0.4 ±0.4 


Copepodites I— V 


14 ± 1 


15 ± 3 


8 ± 3 


9±4 


5 ± 1 


1 ± 1 


Copepoda 














Nauplii 


244 ± 10 


115 ± 21 


138 ± 34 


150 ± 26 


120 ± 4 


80 + 10 


Rotifera 














Keratelta cochlearis 


172± 11 


31 ± 8 


35 ± 3 


22 + 1 


9 ± 3 


4 ± 1 


Asplanchna pnodonta 


54 ±4 


5 ± 3 


5 ± 3 


4 ± 2 


0.4 ± 0.4 


Ploesoma spp. 


15± 1 


18 ±3 


11 ± 3 


11 ± 3 


12 ± 3 


2 ± 1 


Polyarihra spp. 


25 ± 1 


5±3 


2 ± 1 


1 + 1 


1 ± 1 


1 ± 1 


Trichocerca spp. 


16 ± 4 

















Protozoa 














Ceratium hirundinella 


1183 ± 104 


7 ± 2 


1 ± 1 


2 ± 2 


10 ±3 


11 ± 3 



♦The experiment was conducted Sept. 11—12, 1976; values are mean ± standard error. 
fD. oregonensis. D. minutus. and D. ashlandi. 



and community similarity. The results for experiment 5 are illus- 
trated in Fig. 2. 

Changes in total abundance of crustacean zooplankton (minus 
copepod nauplii) and relative abundances of the major crustacean 
groups are shown in Fig. 2(a). The relationship between total 
abundance and added cadmium is represented by the uppermost line, 
the slope of which decreases with increasing cadmium. Thus total 
abundance is most sensitive to cadmium in the lowest segment of the 
range (0 to 5 jug/liter). Total abundance at 5 )Ug Cd/Hter was reduced 
by 42% from that in the controls, and the difference is highly 
significant (P < 0.002); whereas, from 5 to 10 ^tg/liter, it was 
reduced only 11% further. 



AN IN SITU STUDY OF CADMIUM STRESS 



323 




10 



20 



30 40 10 

CADMIUM, Mg/liter 



Fig. 2 Effects of cadmium on (a) abundance of major zooplankton 
groups, (b) species diversity, and (c) community similarity. (See text 
for definitions of symbols.) 



Changes in relative abundance of the major crustacean groups 
were primarily an increase in the percentage of cyclopoid copepods 
and a decrease in that of the cladocerans. Again, these changes were 
greatest in the lowest portion of the overall range. From to 5 /ig 
Cd/liter, the relative abundance of cyclopoid copepods increased 
from 43 to 70%, cladocerans decreased from 52 to 25%, and calanoid 
copepods remained at 4 to 5%. 

The effects of cadmium on species diversity, as indicated by the 
mean values of Hill's (1973) diversity numbers in the range of to 
40 [Jig Cd/liter, are shown in Fig. 2(b). The mean number of 
identification categories, Nq, decreased with increasing cadmium 
although the means at 5 and 10 /ig/liter are not significantly different 
from the controls. The mean diversity numbers Nj and N2 also 
decreased with increasing cadmium but were more^ sensitive than Nq 
in the range of to 5 )Ug Cd/liter. The values of Nj and N2 at 5 /xg 
Cd/liter are both significantly different (P < 0.05) from the controls. 

Changes in community similarity, as measured by indexes S and 
S', are shown in Fig. 2(c). Both S and S' decreased with increasing 



324 MARSHALL AND MELLINGER 

cadmium, but S' was by far the more sensitive index, especially in 
the range of to 5 fig/liter. The mean value of S' at 5 jUg/liter is 
reduced to 73% of that for the controls, and the difference is highly 
significant (P < 0.001); whereas the mean value of S at 5 jUg/liter is 
not significantly different. 

The effects of enclosure, in contrast to the effects of cadmium, 
were mostly insignificant. This is shown by the results of t-tests of 
the significance of differences between mean numbers in the 
incubated controls and those in unincubated samples taken either at 
the end of experiments 1, 3, and 5 (48 tests) or at the beginning of 
each experiment (80 tests). These results are summarized in Table 3. 
Both sets of tests indicated that most of the differences (58 to 62%) 
were not significant (P > 0.05). The two sets of tests also indicated 
that 35 to 37% of the significant differences were caused by larger 
populations in the incubated controls as compared with the 
unincubated samples. Most of the significant differences, further- 
more, are accounted for by relatively few species. Holopedium 
gibberum, Eubosmina coregoni, and immature copepods account for 
54 to 68% of the significant decreases, and Chydorus sphaericiis and 
Cyclops bicuspidatus thomasi account for 57% of the significant 
increases (Table 3). 



DISCUSSION 

The results of this study showed that added cadmium concentra- 
tions as low as 5 jUg/liter caused pronounced effects on both 
functional and structural attributes of a Lake Michigan zooplankton 
community in 9 days, but the effects of enclosure were relatively 
minor up to 15 days. The results indicate further that added 
cadmium concentrations less than 5 ^tg/liter probably would cause 
detectable effects within 9 days and that incubations up to 15 days 
are feasible. 

The responses of species' r to environmental changes are, 
collectively, a fundamental functional attribute of a plankton 
community because these responses affect mineral-cycling and 
energy-flow pathways by determining the absolute and relative 
abundances of the different species. In this study the observed 
effects of cadmium on values of r for the different species were 
probably caused mostly by direct toxicity because the effect in all 
cases was a reduction of r. Furthermore, the duration of the 
experiments was probably too short for secondary effects to 
manifest themselves. Hurlbert (1975) defined secondary effects as 
those which take place in an ecosystem followdng and as a result of 



AN IN SITU STUDY OF CADMIUM STRESS 



325 



TABLE 3 

RESULTS OF T-TESTS OF DIFFERENCES BETWEEN 

MEAN NUMBERS OF VARIOUS CRUSTACEANS IN 

INCUBATED CONTROL SAMPLES AND UNINCUBATED 

SAMPLES TAKEN AT INITIATION AND TERMINATION 

OF IN SITU INCUBATION* 





Incubated controls 


Inci 


abated controls 




T 


re. unincubated 




vs 


. unincubated 






initial samples 




terminal samples 






(80 tests) 






(48 tests) 


Crustacean 





— 


+ 





— + 


Cladocera 












Holopedium gibberum 


1 


4 





1 


2 


Bosmina longirostris 


3 


2 





2 


1 


Eubosmina coregoni 


2 


3 





1 


2 


Daphnia longiremis 


4 


1 





3 





D. galeata mendotae 


5 








3 





D. retrocurva 


2 


3 





2 


1 


Ceriodaphnia lacustris 


4 





1 


3 





Chydorus sphaericus 


2 





3 


1 


2 


Copepoda: Cyclopoida 












Cyclops uernalis 


3 





2 


2 


1 


C. bicuspidatus thomasi 


4 





1 


1 


2 


Mesocyclops edax 


3 





2 


2 


1 


Tropocyclops prasinus 


5 











2 1 


Copepodites I— V 





4 


1 


1 


2 


Copepoda: Calanoida 












Eurytemora affinis 


4 





1 


2 


1 


Diaptotnus spp.f 


5 








2 


1 


Copepodites I— V 


3 


2 





2 


1 



*The number of tests with no significant differences are shown as 0; those 
with a significant difference (P < 0.05) are shown as — for decrease or + for 
increase of the incubated control populations. 

fD. oregonensis, D. minutus, D. ashlandi, and D. siciloides. 



direct effects on growth, survival, or reproduction of the sensitive 
species. He also stated that toxicity is the parsimonious explanation 
for any population decline that is demonstrated to result from 
exposure. 

The observed differences in apparent cadmium toxicity to the 
different major groups of zooplankton and the similar sensitivities of 
species within each major group are in agreement with the results of 
previous studies of heavy-metal toxicity to zooplankton. Mcintosh 
and Kevem (1974) found that in copper- treated ponds both 



326 MARSHALL AND MELLINGER 

cladoceran and rotifer populations were more sensitive to copper 
than the cyclopoid copepods. In a laboratory study of the acute 
toxicity of cadmium and other heavy metals to three species of 
crustacean zooplankton, Baudouin and Scoppa (1974) found that 
the cladoceran Daphnia hyalina was considerably more sensitive than 
the two copepod species and that the calanoid Eudiaptomus padanus 
was more sensitive than the cyclopoid Cyclops abyssorum. They 
found only minor differences in the rank orders of the metals' 
toxicities to these species, and their results for D. hyalina were in 
good agreement with those reported for D. magna by Biesinger and 
Christensen (1972). The observed similarity of cadmium effects on 
different species of Cladocera agrees with the findings of Winner and 
Farrell (1976) that four species of Daphnia did not differ in their 
sensitivity to copper. 

The observed effects of cadmium on structural attributes of a 
Lake Michigan zooplankton community are qualitatively similar to 
those found in studies of long-term effects of other stresses in natural 
communities (Woodwell, 1970). The long-term effects of cadmium 
on the Lake Michigan zooplankton community would probably be 
more pronounced than the effects observed in this study, however, 
because heavy-metal toxicity tends to increase with chronic expo- 
sure. For example, chronic cadmium toxicity to laboratory popula- 
tions of Daphnia galeata mendotae increases with time, and 23 weeks 
are required to establish equilibrium relationships (Marshall, 1978). 

The various indexes of community structure differed consider- 
ably in their sensitivity to cadmium. Total zooplankton abundance, 
the most sensitive index, was reduced by 42% in 9 days at 5 jug 
Cd /liter, whereas the most sensitive indexes of species diversity and 
community similarity, N2 and S', were reduced by only 29 and 
27%, respectively. The diversity number N2 was the most sensitive 
index of species diversity because it is the one most heavily weighted 
by the more abundant species (Hill, 1973). This also explains the 
different sensitivities of the two indexes of similarity, S and S'. The 
indexes of similarity account for changes in relative proportions of 
each species, whereas the diversity number accounts only for 
presence or absence of species. Although total abundance was the 
most sensitive index of community structure in our study, species 
diversity or community similarity would probably be more sensitive 
to long-term effects of chronic, low-level cadmium stress because 
total zooplankton abundance would probably be partially restored, 
given time, by more tolerant species. 

There are few previous studies of heavy-metal effects on aquatic 
ecosystems with which to compare our results, and none dealing with 



AN IN SITU STUDY OF CADMIUM STRESS 327 

the effects of cadmium. The most relevant study of heavy metal 
stress is that of Reeve et al. (1976) on the short-term effects of 
copper on a marine zooplankton community in enclosed v/ater 
columns. Reduced abundance of total zooplankton was apparently 
the most sensitive index of copper stress, just as it was for cadmium 
in our study. Reeve and co-workers were not able to detect a 
statistically significant reduction of either Shannon's index (H) or 
percentage similarity (S') caused by copper concentrations up to 
50 )Ug/liter because of pronounced enclosure effects. Total phyto- 
plankton, as measured by chlorophyll a, increased in the copper- 
treated enclosures because of reduced zooplankton grazing (Reeve et 
al., 1976). The effects of various heavy metals and other pollutants 
on functional and structural changes in freshwater algae and 
protozoan communities include reduced total abundance and in- 
creased relative abundance of tolerant species (Cairns, Lanza, and 
Parker, 1972). The effects of copper have probably been studied 
more than those of any other heavy metal because it is frequently 
used as an aquatic herbicide, but there are few studies even of copper 
effects on zooplankton (Mcintosh and Kevern, 1974). Heavy metals 
associated with acid precipitation have been implicated in the 
reduction of biomass and species diversity of phytoplankton, 
zooplankton, and fish communities in lakes chronically exposed to 
these inputs (Gorham, 1976). The well-documented reductions of 
abundance and species diversity of zooplankton and fish communi- 
ties in the LaCloche Mountain lakes near the mining and smelting 
region of Sudbury, Ontario, appear to be caused primarily by acid 
stress rather than by the associated heavy metals (Beamish, 1976; 
Sprules, 1975). 

Reduced biomass and diversity appear to be common symptoms 
of stress caused by many kinds of disturbances, at least in terrestrial 
ecosystems (Woodwell, 1970). Not all stresses have the same effects, 
however. Eutrophication is frequently referred to as a stress, yet its 
effects are just the opposite of those of oligotrophication (Hutchin- 
son, 1973), a process that is claimed to occur in lakes subjected to 
excessive acid loading (Gralin, Hultberg, and Lander, 1974). Thus 
different stress syndromes are more likely to be found for different 
classes of stressors, e.g., toxic substances. Universally toxic sub- 
stances, such as cadmium or strong acids, are even more likely to 
have similar and predictable effects than are more-selective toxicants, 
such as pesticides (Hurlbert, 1975). 

The effects of heavy metals and other toxic substances on 
aquatic communities in the Great Lakes have been rated low in 
importance relative to other stresses, including uncontrolled commer- 



328 MARSHALL AND MELLINGER 

cial fishing, erosion and nutrient loading, invading species, and 
stream destruction and shoreline restructuring (Regier and Hartman, 
1973). Certainly any reduction of plankton abundance which may 
have been caused by toxic substances in recent decades has been 
masked by dramatic effects of eutrophication and fish predation. In 
Lake Michigan, alewife predation has had a dominant influence on 
changes in the zooplankton community (Wells, 1970) although 
eutrophication may have been responsible for counteracting the 
effects of alewife predation in Green Bay (Gannon, 1972). 
Eutrophication has not only increased the total abundance of Lake 
Michigan phytoplankton (Beeton, 1965) but has also changed the 
species composition (Schelske and Stoermer, 1972). As long as such 
dramatic changes are taking place in the Great Lakes, there seems to 
be little chance of detecting the effects of toxic substances by direct 
observation (monitoring), except in the vicinity of strong local 
sources. 

The results of this study indicate that the use of relatively small 
enclosures overcomes some of the limitations of large enclosures for 
short-term experiments in large lakes. For studies of pollutant effects 
on zooplankton, at least for short-term effects, the in situ method 
used in this study has several advantages over other methods. Recent 
work indicates that effects of enclosure in opaque polyethylene 
carboys in longer experiments become excessive, but effects of 
enclosure in translucent carboys incubated for 3 weeks at optimal 
depths are not much greater than effects of large enclosures of 
various kinds (Marshall and Mellinger, 1978a). Longer in situ 
experiments still do not appear to be feasible in the Great Lakes, 
however. Therefore, future determinations of relationships between 
short- and long-term stress effects in laboratory populations of 
species that live in these lakes (Marshall, 1978) and the same 
relationships in zooplankton communities of small, experimental 
lakes (Marshall and Mellinger, 1978b) wOl be useful in assessing the 
long-term significance of the results of in situ experiments in large 
lakes. 

ACKNOWLEDGMENTS 

The research reported here was performed under the auspices of 
the U. S. Department of Energy. 

We thank J. A. Zischke and R. Van Reken for assistance in 
various phases of the laboratory and field work. Helpful reviews of 
an earlier version of this paper were provided by A. L. Buikema and 
W. T. Edmondson. 



AN IN SITU STUDY OF CADMIUM STRESS 329 

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Zooplankton, Crustaceana (Leiden), 28: 220-224. 
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Modified by Chronic Cadmium Stress, J. Fish. Res. Board Can., 35: 461-469. 



330 MARSHALL AND MELLINGER 



, and D. L. Mellinger, 1978a, Effects of Cadmium Enrichment on a Lake 

Michigan Plankton Community, in Radiological and Environmental Research 
Division Annual Report, Part 3, January— December 1977, ANL- 
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Smyly, W. J. P., 1976, Some Effects of Enclosure on the Zooplankton in a Small 
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Tisue, G. T., 1976, Argonne National Laboratory, personal communication. 

Torke, B. G., 1974, An Illustrated Guide to the Identification of Planktonic 
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No. 17, Center for Great Lakes Studies, The University of Wisconsin, 
Milwaukee. 

Wells, L., 1970, Effects of Alewife Predation on Zooplankton Populations in 
Lake Michigan, Limnol. Oceanogr. , 15: 556-565. 

Whittaker, R. A., 1972, Evolution and Measurement of Species Diversity, Taxon, 
21: 223-251. 

Wiersma, J. H., I. K. Iskandar, L. J. Schwartz, R. W. Lanz, and C. C. Weber, 
1974, The Effect of a Fossil Fuel Power Plant's Cooling System on the Water 
Quality of Green Bay, Wisconsin, Proc, Conf Great Lakes Res., 17: 535-543. 

Winner, R. W., and M. P. Farrell, 1976, Acute and Chronic Toxicity of Copper 
to Four Species oi Daphnia, J. Fish. Res. Board Can., 33: 1685-1691. 

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Ecosystems, Science, 168: 429-433. 



THERMAL ECOLOGY AND STRESS: 

A CASE HISTORY FOR RED-SORE DISEASE 

IN LARGEMOUTH BASS 



GERALD W. ESCH and TERRY C. HAZEN 

Department of Biology, Wake Forest University, Winston— Salem, 
North Carolina; and Savannah River Ecology Laboratory, Aiken, 
South Carolina 



ABSTRACT 

The stress concept is analyzed and related to individual, population, and 
ecosystem levels of biological organization. Red-sore disease, produced by the 
gram-negative bacterium Aeromonas hydrophila, is discussed in terms of its 
relationship to stress. An effort is made to relate seasonal changes in red-sore 
disease to environmentally induced alterations in the physiology and behavior of 
largemouth bass. A hypothesis is proposed to explain these interactions in terms 
of stress. 



ANALYSIS OF THE STRESS CONCEPT 

The operative word in the title of this symposium is stress, yet we 
question whether many investigators have anything more than an 
intuitive notion of what it means. To estabhsh a common ground and 
to set the stage for a discussion of our own work in this area, we feel 
we should first briefly discuss the concept of stress and consider its 
application at various levels of biological organization. We hope that 
the discussion of stress at individual and ecosystem levels of 
organization is not misconstrued as an effort to rediscover the wheel. 
The following conceptualization of stress represents our amalgama- 
tion of the ideas and notions presented by Selye (1950; 1956), Brett 
(1958), Slobodkin (1967), Odum (1969), Cairns (1976), and 
Gibbons (1976). 

331 



332 ESCH AND HAZEN 

Traditional Perspective 

Historically the word stress has been used by biomedical 
scientists to describe a somewhat vague array of physiological, 
morphological, and biochemical responses by an individual organism 
to an even more vague and less defined group of etiologies. Thus 
there is more certainty about how an individual organism manifests 
stress than there is about what causes the response to occur. 

Selye (1950) described the response of an individual organism to 
stressor input as a succession of physiological and biochemical 
reactions to which he collectively referred as the general adaptation 
syndrome (or GAS). Selye separated the GAS into three parts, the 
alarm stage, the resistance stage, and the exhaustion stage. 

The alarm stage begins with stressor input, which promotes the 
release of epinephrine into the blood vascular system from the 
adrenal glands and increases the activity of the sympathetic portion 
of the autonomic nervous system (Fig. 1). The combined action of 
epinephrine and the autonomic nervous system then produces a wide 
range of physiological and biochemical changes in the respondent 



STRESSOR 



RECEPTOR 



NERVOUS °SYSTEM ADRENAL MEDULLA 



RESPONSE RESPONSE 




PHYSIOLOGICAL, BIOCHEMICAL, 
AND MORPHOLOGICAL CHANGES 

INCREASE IN LEVELS OF CIRCULATING 
BLOOD GLUCOSE 

DILATION OF PUPILS OF THE EYE 

STIMULATION IN FREQUENCY, FORCE, 
AND AMPLITUDE OF HEART CONTRACTIONS 

INCREASE IN VASCULAR FLOW TO 
SKELETAL MUSCLES 

DECREASE IN BLOOD-CLOTTING TIME 

EFFECT ON PIGMENT CELLS, e.g., 
AMONG TELEOST FISHES 

Fig. 1 Alarm stage of the general adaptation syndrome. 



THERMAL ECOLOGY AND STRESS 333 

organism, including increasing the levels of circulating blood glucose, 
dilating the pupils of the eye, stimulating the frequency and force of 
heart contractions, etc. These kinds of responses are clearly effective 
in preparing an individual to respond defensively or offensively to 
the threat of external attack or provocation. It is appropriate that 
the alarm stage is sometimes called the fright— flight— fight response. 
The second phase of the GAS is the resistance stage. Very soon 
£ifter the alarm stage has run its course, the activity of the autonomic 
nervous system is diminished, and the release of epinephrine from 
the adrenal medulla also slows down. If the stressor persists in time, 
however, there is a substantial rise in the level of circulating 
corticosteroids produced by cells in the adrenal cortex (Fig. 2). The 
cortical cells are stimulated by adrenocorticotrophic hormone 
(ACTH), which, in turn, is produced by the pituitary gland. The 
stimuli for discharge of ACTH are releasing factors produced in the 
hypothalamus; presumably higher centers in the central nervous 
system are responsive to external and internal stimuli that promote 
the liberation of the so-called releasing factors from the hypothala- 
mus. The function of corticosteroids is to mitigate cellular damage. 



STRESSOR 



RECEPTOR 



PITUITARY GLAND 



ACTH 



ADRENAL GLAND 



ADRENOCORTICOSTEROIDS 



PHYSIOLOGICAL, MORPHOLOGICAL, 
AND BIOCHEMICAL CHANGES 

DEPRESSED CARBOHYDRATE METABOLISM 

PROMOTION OF G LUCONEOGENESIS FROM 
TISSUE PROTEIN 

PROMOTION OF GLYCOGENESIS IN LIVER 

SUPPRESSION OF INFLAMMATORY RESPONSE 

Fig. 2 Resistance stage of the general adaptation syndrome. 



334 ESCH AND HAZEN 

which could be induced as a consequence of long-term stressor input. 
It is also known that some corticosteroids cause significant changes 
in carbohydrate metabolism and suppress inflammatory reactions. 
According to Selye, these responses collectively provide protection 
against the stressor. We should note, however, that the action of 
corticosteroids in suppressing inflammation may actually be counter- 
productive since the organism simultaneously becomes more vulner- 
able to infection by pathogenic organisms. A significant body of 
literature exists which details the impact of increased corticosteroid 
output in terms of reducing both natural and acquired resistance (for 
details of the relationship between stress and parasitism, see Esch, 
Gibbons, and Bourque, 1975). 

The third stage of the GAS, exhaustion, occurs when, after long 
and persistent stressor input, the cells of the adrenal cortex become 
exhausted. At this time there is functional and structural deteriora- 
tion of the cortical cells, resulting in cessation of corticosteroid 
production. If this occurs, death of the stressed organism rapidly 
follows. 

Thus, if stressor input continues over a long period of time or if 
it is of sufficient magnitude, there is a potential for mortality either 
from exhaustion of the adrenals or from side effects such as stroke, 
hypertension, bleeding ulcers, arthritis, and infection with patho- 
genic agents. We should emphasize that, although the concept of 
stress is accepted by most biomedical scientists, there is discussion 
about whether stress is necessarily related to some of the diseases 
mentioned. 

Definitions of Stress 

Stress as a process can be more or less adequately described at 
the individual level, but most definitions of stress appear to be less 
than acceptable. This is especially true since most of the definitions 
were developed to apply only at the individual level and only for 
animals. We know, however, that the stress concept can be extended 
to plants (Harper, 1967; Vadas et al., 1976) and to the population 
(George, 1977) and ecosystem (Cairns, 1976) levels of organization. 

Let us consider, for example, the definition of stress offered by 
Selye (1956): the "sum of all physiological responses by which an 
animal attempts to maintain or re-establish a normal metabolism in 
the face of a chemical or physical force." In some ways this 
definition is acceptable, but we feel it is too restrictive because it 
excludes plants and it is not applicable at the ecosystem level. 
Homeostatic processes operating at the individual level and forces 
that tend to maintain stability or equilibrium at the ecosystem level 



THERMAL ECOLOGY AND STRESS 335 

are, we believe, analogous. Such an assertion is more meaningful if 
ecosystem stability is viewed as the capacity to maintain equilibrium 
or to return to equilibrium after the system has been perturbed. 
Certainly a perturbed system can be considered in terms of stress if 
ecosystem stability is perceived in this way. 

Brett (1958) proposed a more acceptable definition of stress: "a 
state produced by any environmental or other factor which extends 
the adaptive response of an animal beyond normal range, or which 
disturbs the normal functioning process to such an extent that, in 
either case, the chances for survival are significantly reduced." The 
obvious utility of this definition rests with the implication that stress 
can be viewed in terms of chance or probability, which indicates an 
implicit assumption that stress can be quantified. Although this is 
clearly a positive aspect of Brett's definition, there are several 
objections similar to those raised for Selye's definition. Brett does 
not consider plants nor ecosystems, and, in addition, he implies that 
the outcome of stress must be viewed in negative terms. This is not 
always the case; although it is clearly negative for an individual 
organism if it dies as a result of exhaustion caused by stress, it is not 
necessarily negative for the success or survival of a population. For 
example, mortality of some individuals in a crowded population may 
actually serve to ensure species survival if space and/or nutrient 
resources are limiting. It is interesting to note that a similar 
mechanism may operate among some host— parasite systems, enhanc- 
ing survival potential of both host and parasite species in an 
evolutionary sense. Pimentel (1961) and Pimentel and Bellotti 
(1976) noted that "co-evolution in a host and/or parasite toward a 
balanced supply— demand economy and regulation of parasite num- 
bers is possible" through operation of a genetic feedback mechanism. 
Thus, if virulent parasites are eliminated by parasite-induced host 
mortality, the probability of propagating less-virulent parasites is 
enhanced, and survival and reproduction of more-resistant hosts may 
also be concomitantly increased. Another positive aspect of stress 
was suggested by Gibbons (1976) when he indicated that a process 
which may ultimately be negative at the population level can actually 
be preceded by an enhancement of the same process. Reviewing 
available literature, he noted, for example, that increases in tempera- 
ture caused by release of thermal effluent in aquatic systems were 
shown initially to increase both primary and secondary productivity 
(Gibbons, 1970) and to alter a variety of species interactions (Saks 
etal., 1974). 

All these objections to Selye's and Brett's definitions of stress 
were also discussed by Esch, Gibbons, and Bourque (1975), who, in 



336 ESCH AND HAZEN 

an attempt to obviate the objections, suggested that stress be defined 
as "the effect of any force which tends to extend any homeostatic or 
stabihzing process beyond its normal limit, at any level of biological 
organization" such that the result will be either an enhancement or a 
diminishment in the probability of mortality, natality, or permanent 
change. This definition is broad enough in scope to permit 
application at individual, population, or ecosystem levels of organiza- 
tion but is explicit enough that the possibilities for quantification of 
stress are still maintained. 

Model for Response to Stressor Input at the Individual Level 

Possible response of an individual organism to stressor input is 
shown in Fig. 3. A resting or undisturbed individual operates within 
the constraints of a normal homeostatic range. In addition, there are 
wider limits within which the organism may continue to function, 
although not optimally. The dimension of these ranges varies in both 
sDace and time among individuals within a single population and 
among individuals in different populations. 

If the organism is subjected to a stressor input of the proper kind 
and with an appropriate magnitude, the alarm stage of the GAS will 
be initiated. Generally, the duration of the alarm stage is brief, and 
the direction of the response is dictated by the nature of the specific 
biochemical or physiological process being measured. If the stressor 
input is withdrawn, the original steady state of the organism will 
return. 

If the stressor input persists in time or grows in magnitude, then 
the respondent organism enters the resistance stage. The length of 
time an individual is able to resist stressor input and maintain itself 
within maximum homeostatic limits is variable. It depends to some 
extent, of course, on the inherent (or genotypic) potential of the 
individual, in combination with such intrinsic factors as its state of 
well-being, age, etc. Other extrinsic factors that modify the length of 
time the organism is able to operate within homeostatic limits 
include the season of the year and the nature, magnitude, and 
duration of the stressor input. As the model suggests, if the stressor is 
withdrawn during the resistance stage, then the original steady state 
returns. 

If the stressor input continues long enough or if the magnitude of 
input increases beyond a critical point, the individual organism will 
no longer be able to cope homeostatically. The final stage, 
exhaustion, then ensues. If this end point is reached, the probability 
of an individual organism's surviving, reproducing, or returning to its 
original steady state is permanently altered. 



THERMAL ECOLOGY AND STRESS 



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338 ESCH AND HAZEN 

This concept of stress was developed for vertebrate animals with 
autonomic nervous systems and endocrine glands capable of produc- 
ing epinephrine and adrenocorticosteroids. Obviously many organ- 
isms, both plant and animal, have neither. The question that then 
occurs is, Can these organisms be considered within the framework 
of Fig. 3? The answer to the question is a tentative yes. We believe 
the schematic is general enough in scope to permit us to view the 
response of any organism, plant or animal, vertebrate or invertebrate, 
to the force of stressor input. 

Model for Response to Stressor Input at the Ecosystem Level 

Figure 3 represents what may occur when an individual organism 
is subjected to stressor input. But what happens when an ecosystem 
is perturbed? Clearly an ecosystem response to perturbation is far 
too complex to model or represent by a series of solid or dashed 
lines, especially if the perturbation is subtle. If, however, as 
previously noted, the forces operating to maintain homeostatic 
steady state in an individual are analogous to those maintaining 
equilibrium at the ecosystem level, models for stress at these two 
levels should be somewhat similar and, for the sake of this discussion, 
simple. 

Before dealing with a conceptualization of stress at the ecosys- 
tem level, we should emphasize that ecosystem stability and 
complexity do not necessarily go hand-in-hand. Thus increased 
stability does not necessarily follow from increased complexity 
(May, 1976). Stability at the ecosystem level, as used here, refers 
only to the ability of an ecosystem to return to equilibrium 
following perturbation. 

We have assumed that there is a clear parallel between stress at 
individual and ecosystem levels (Fig. 4). Initially, we perceive an 
equilibrium, or steady state, operating at more or less a constant 
level. If the ecosystem is perturbed, a new steady state, or 
equilibrium, will be established. If the stressor input is withdrawn, 
then either the original or the new equilibrium will be established, 
depending on an array of factors, including the nature, magnitude, 
and duration of the perturbing force and the initial fragility of the 
system. These factors will also be of importance in determining the 
length of time it would take the ecosystem to reach a stage of 
exhaustion. Cairns (1976) referred to the capacity of an ecosystem 
to resist insult in terms of inertia. 

Exhaustion at the individual level is manifested as a permanent 
change in either mortality or natality probability. At the ecosystem 
level exhaustion leads to death (rarely) or an irreversible change in a 



THERMAL ECOLOGY AND STRESS 



339 



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340 ESCH AND HAZEN 

given functional attribute (more commonly). In the latter course, the 
new steady state may be a close facsimile of the original, but again 
this depends on the nature, magnitude, and duration of the 
perturbing force. For example, let us consider the consequences of 
cultural eutrophication and its reversal. It is well known that 
enrichment causes an oligotrophic ecosystem to undergo eutrophica- 
tion and that this process can be reversed if the source of enrichment 
is diverted or stopped, in which case the original "pristine" character 
of the system will be restored. Many of the functional characteristics 
of the original system may be restored, but the system still will not 
be the same. The explanation is simple when we consider that some 
species in the system will be unable to withstand conditions of stress 
associated with eutrophication and will become locally extinct. If 
this occurs, many of the species interactions that were characteristic 
of the original ecosystem are not reestablished in the new one. The 
result is a new steady state, or equilibrium, even though functionally 
the two oligotrophic systems are similar in many ways. 

Thermal Ecology and Stress 

Temperature is a universal influence on the normal physiological, 
metabolic, and behavioral processes of individual plants and animals, 
especially those living as heterotherms in aquatic systems. Most 
species of plants and animals have evolved a strategy not only of 
coping with normal environmental temperatures but also of exploit- 
ing temperature variations to such an extent that they are either 
partially or totally dependent on annual, seasonal, or diel fluctua- 
tions. With the construction of electricity-generating facilities pro- 
ducing heated effluent, many species of plants and animals that have 
evolved successful strategies for dealing with normal temperature 
cycles are now faced with levels of temperature that can be 
considered excessive. In responding to these elevated temperatures, 
each species has several alternative courses of action: (1) It can 
migrate away from or toward the high temperatures; (2) it can 
become locally extinct or flourish; or (3) it can cope until forced to 
follow one of the first two courses of action or until such time as it 
can evolve a new strategy to permit it to survive. Under any of these 
situations, the individual is subjected to stress and will behave in a 
manner consistent with Fig. 3. 

Stress may be manifested in a number of insidious ways, none 
more so perhaps than increased susceptibility to disease of both 
organic and external origin. Our own specific interest over the years 
has been the relation between thermal effluent and parasitism and 
the various ways in which host— parasite relationships can be 



THERMAL ECOLOGY AND STRESS 341 

affected. Recently we have begun to deal with a disease in fish which 
we know to be related not only to thermal effluent but also to 
organic loading. Indeed, we now believe it to be basically a problem 
of stress, induced by a series of etiologies with which we can 
associate a number of environmental variables. 

RED-SORE DISEASE, TEMPERATURE, AND STRESS 

Description of Problem 

Epistylis, a stalked, colonial ciliate, has been identified as the 
causative agent for red-sore disease, which affects several fish species 
in various aquatic systems throughout the southeastern United States 
(Rogers, 1971). The protozoan has a motile telotroch stage that 
attaches to a substrate, forms a stalk, and produces feeding bodies 
called zooids. When attached to the surface of a fish, it is said to 
cause scale erosion, producing pit-like lesions. The gram-negative 
bacterium Aeromonas hydrophila enters the tissues via these lesions 
and in time produces hemorrhagic septicemia and death. 

Because of the heavy mortality from the disease, it has drawn 
considerable attention over the past few years. For example, more 
than 37,500 fish were killed in a few weeks in 1973 in Badin Lake, 
on the Yadkin River in North Carolina (Dean, 1974). During the fall 
of 1976, approximately 95% of the white perch population in 
Albemarle Sound, North Carolina, was killed by an epizootic of 
red-sore disease (Cook, 1976). During the same outbreak, 50% of the 
commercial catch of all species was discarded because of the presence 
of unsightly surface lesions associated with red-sore. 

Despite the widespread nature of red-sore disease in the 
southeast, its epizootiology has not been extensively studied. Indeed, 
some literature on the problem is confusing, if not actually 
contradictory. For example, Rogers (1971) stated that Epistylis is 
the primary invader, with A. hydrophila then producing the second- 
ary infection. On the other hand, Lom (1973) emphatically stated 
that Epistylis is incapable of producing lesions and that, as a 
bacterivore, it only secondarily associates with fish. Earlier Lom 
(1966) reported that heavy infections of fish with Epistylis were 
seasonal (occurring mostly in winter) and were independent of the 
amount of organic solids and the density of bacteria in the water. 
Bullock and McLaughlin (1970) and Meyer (1970) reported the most 
severe outbresiks to occur during summer when temperature is high 
and dissolved oxygen is low. During winter of 1973, Esch and 
Gibbons (unpublished observations), noting the presence of red-sore 
disease among several species of centrarchids in a South Carolina 



342 ESCH AND HAZEN 

cooling reservoir, tentatively concluded that it could be related to 
thermal effluent from a nuclear production reactor. 

From this brief overview^, we see clearly that red-sore disease is a 
serious problem, that its epizootiology is not well understood, and 
that, because of its impact on both commercial and sport fisheries, it 
deserves rigorous study. An investigation of the problem was begun 
in the fall of 1974. The initial objectives were (1) to ascertain the 
identity of the causative agent, (e.g., is it Epistylis or Aeromonas)-, 
(2) to follow the course of the disease seasonally and relate it, if 
possible, to one or more water-quality parameters; (3) to determine 
whether thermal effluent affects the course of the disease; and (4) to 
develop a model for possible use in predicting when, where, and 
under what circumstances an epizootic may occur in a given body of 
water. During the first 2.5 years of the study, it became apparent 
that the disease could be related to the stress phenomenon. This 
notion has since been incorporated into the second and third 
objectives listed. 

Description of the Study Site 

Par Pond, an 1120-ha reservoir located at the Savannah River 
Plant near Aiken, South Carolina, serves as a cooling pond for a 
nuclear production reactor. Extensive descriptions of the tempera- 
ture and biotic characteristics have been given by Holland et al. 
(1974), Lewis (1974), and Parker, Hirshfield, and Gibbons (1973). 
Figure 5 shows the primary collecting sites. Most of the fish from the 
thermally altered area were taken within 1 km of the point of entry 
of thermal effluent from Pond C. Temperatures in this area varied 
because of variability in reactor activity and season but generally 
averaged between 5 and 10°C above ambient, depending on season 
and distance from point of entry of thermal effluent into Par Pond. 

From the fall of 1974 through the present time, temperature, 
dissolved oxygen, pH, redox potential, and conductivity have been 
measured weekly, in profile, at several selected sites in the reservoir. 
A depth profile for these parameters, measured in midwinter and 
midsummer at representative ambient and thermal locations (Fig. 6), 
clearly shows the monomictic nature of the impoundment. This is 
characteristic of most impoundments in the southeastern United 
States. Hazen (1978) provided a complete description of the 
water-quality parameters in Par Pond during the course of this study. 

Identifying the Causative Agent for Red-Sore Disease 

As previously indicated, the literature is contradictory as to 
whether Epistylis or Aeromonas is the etiological agent for red-sore 



THERMAL ECOLOGY AND STRESS 



343 



HEATED EFFLUENT 




1 km 



Fig. 5 Map of Par Pond showing entry of thermal effluent. Shading 
represents the area with elevated temperature; all other locations in 
reservoir have ambient temperatures. Bass in thermal areas were 
mostly taken within 1 km of the point of entry of thermal effluent. 
Bass in ambient locations were mostly taken from sites marked 1,2, 
and 3. 



disease. Rogers (1971) stated that Epistylis induces scale erosion, 
permitting secondary infection by A. hydrophila, but Lorn (1973) 
indicated that there was no evidence to suggest that Epistylis could 
produce the histolytic enzymes required to cause scale erosion. In 
our study of the problem, we found three lines of evidence to suggest 
that A. hydrophila is the etiological agent for red-sore disease. 

First, examination by scanning electron microscopy (Fig. 7) of 
the site of attachment by Epistylis to a lesion on the surface of a 
largemouth bass {Microptems salmoides) does not suggest that the 



344 



ESCH AND HAZEN 




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THERMAL ECOLOGY AND STRESS 



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ESCH AND HAZEN 




CO 



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Fig. 7 Site of attachment by stalk of Epistylis sp. to surface of bass 
scale (S = stalk). 2000 X. 



THERMAL ECOLOGY AND STRESS 347 

protozoan produces erosion of the mucous-epithelium layer of the 
scale (Hazen et al., in press; Hazen, Raker, and Esch, 1977). Bacteria 
(presumably A. hydrophila) were observed adhering to the stalk of 
Epistylis but not in association with the zooids, or feeding bodies 
(Fig. 8). Histological sections of the surface lesions suggest a very 
loose association of the colonial ciliate with the scale surfaces and 
intensive inflammation in muscles beneath the scales. Within the 



B. 



\ 



Fig. 8 Cross section of Epistylis sp. zooid and stalk viewed by 
transmission electron microscopy. Note presence of bacteria closely 
adhering to stalk, but not to the zooid (S = stalk, Z = zooid, B = 
bacteria). 4600 X. 



348 ESCH AND HAZEN 

muscle, there is also substantial infiltration of bacterial cells, 
presumably A. hydrophila (Huizinga, Esch, and Hazen, manuscript in 
preparation; Hazen, Raker, and Esch, 1977). 

A second line of evidence is provided by collaborative studies 
conducted by Robert Gorden and colleagues at the Savannali River 
Laboratory, Savannali River Ecology Laboratory, University of 
South Carolina Medical School, South Carolina Wildlife and Marine 
Resources Department, and Wake Forest University. During the 
spring and summer of 1975, a series of unexpected alligator 
mortalities occurred in Par Pond. In virtually all cases, A. hydrophila 
was cultured from lungs and other internal organs at the time of 
necropsy. This suggests that, in some manner, mortality may have 
been related to the presence of the bacteria. A review of available 
literature indicated that in 1971 red-sore disease induced by A. 
hydrophila was responsible for mortality of approximately 120,000 
fish of several species in Lake Apopka, Florida (Shotts et al., 1972). 
In addition, 16 alligators died suddenly during the same period of 
time, all with symptoms of red-sore disease. During the fall and 
winter of 1976—1977, Gorden and his colleagues were able to 
generate substantial experimental evidence to show that A. hydroph- 
ila was capable of producing skin lesions on the surface of 
alligators aiid that A. hydrophila could be isolated from the tissues of 
dead and/or dying alligators. Furthermore, it was shown that surface 
lesions and mortality in alligators could be induced without a 
primary infection by Epistylis. Indeed, Epistylis was not present in 
50 alligators with experimentally induced red-sore disease. 

Finally, for A. hydrophila to be the primary invader, it is 
essential that the bacteria be capable of producing an extracellular 
toxin. Liu (1961) and others reported that A. hydrophila produces a 
number of potent exotoxins capable of inducing lesions such as those 
typically associated with red-sore disease. 

On the basis of these observations, we feel confident in stating 
that the etiological agent for red-sore disease is A. hydrophila. 
Therefore, our further discussion is directed toward understanding 
the biology of the bacterium and its relation to the disease in fish. 

Seasonal and Other Factors Associated with Red-Sore Disease 

Previous studies have shown that red-sore disease differentially 
affects five species of centrarchid fish in Par Pond (Esch et al., 1976); 
infection percentages were consistently highest for largemouth bass 
(Micropterus salmoides). Since this trend has been the same since 
1974, efforts have focused on this species of fish. 



THERMAL ECOLOGY AND STRESS 



349 



Red-sore disease among bass in Par Pond shows a very striking 
seasonal periodicity. The highest incidence of infection occurs during 
the spring months (March, April, and May), followed by lower levels 
in summer, a decline in fall, and the lowest incidence in winter 
(Fig. 9). Although there are differences in amplitude from year to 
year, these seasonal variations were consistent for 36 months, 
beginning in the fall of 1974. 




SEASON 

Fig. 9 Seasonal changes (composite for 36 consecutive months) in 
infection percentages among large mouth bass in Par Pond. 



Since August 1975, the density of A. hydrophila has been 
determined in vertical profile at various locations within Par Pond. 
Temperature, dissolved oxygen, pH, redox potential, and conduc- 
tivity were also recorded simultaneously (Hazen, manuscript in 
preparation). As might be expected, there were seasonal changes in 
each water-quality parameter, and A. hydrophila densities also varied 
seasonally. The seasonal changes in A. hydrophila densities showed a 
strong relation to the incidence of red-sore disease (Fig. 10); many of 
the significant increases and decreases in disease among bass were 
preceded by corresponding modulations in the density of A. 
hydrophila in water. 

Meyer (1970) suggested that seasonal outbreaks of red-sore 
disease may be related to depressed levels of dissolved oxygen during 
summer months, which would lead to stress in certain fish species 
and then to increased vulnerability to infection. Since increased 



350 



ESCH AND HA2EN 



110 — 



100 — 



o 




1 — I — I — I — I — I — I — I — I — I — I — I — I — I — I — I — \ — \ — I — I — I — r 

ASONDJ FMAMJJASONDJ F MAM 



1975 



1976 



1977 



Fig. 10 Monthly changes in mean number of A. hydrophila cells per 
milliliter and in infection percentage of largemouth bass 
from Par Pond. Note that a rise in bacterial cell density (solid arrow) 
frequently precedes a rise in infection percentage among bass 
(dashed arrow). (CV <35%.) 



organic loading may lead to seasonal depression of dissolved oxygen 
in hypolimnetic water, efforts were made to measure total organic 
carbon at several sites in Par Pond during each of four consecutive 
seasons. These measurements were made simultaneously with the 
other five water-quality parameters and the density of ^. hydrophila. 
As shown in Table 1, there was some seasonal variabiUty, as might be 
expected. There was not, however, a relation between total organic 
carbon and the other water-quality parameters nor A. hydrophila 
density. 



THERMAL ECOLOGY AND STRESS 351 

TABLE 1 

SEASONAL DEPTH PROFILES FOR TOTAL 
ORGANIC CARBON* (mg/liter) 



Depth, 


Summer 


• 1976 


Fall 1976 


Winter 1976 


Spring 
H 


1977 


m 


H 


A 


H 


A 


H 


A 


A 





353.3 


12.3 


4.9 


2.3 


24.1 


6.6 


2.7 


0.5 


1 


169.9 


263.2 


143.3 


72.1 


216.5 


340.8 


322.2 


192.6 


3 


3.9 


101.0 


3.2 


27.6 


59.8 


48.2 


33.8 


91.5 


5 


5.6 


8.9 


11.0 


5.8 


34.0 


28.1 


11.3 


12.1 


7 


2.1 


2.5 


4.4 


7.1 


22.8 


15.8 


2.9 


1.1 


9 




4.9 




2.1 




4.9 




0.4 


11 




8.7 




3.3 




8.7 




0.5 


13 




2.2 




4.4 




2.2 




1.3 


15 




1.1 




5.4 




1.1 




2.4 












SR water 


= 0.71 


SR water = 1.0 



* Abbreviations are H, thermally altered location; A, ambient location; and 
SR, Savannah River. 



Red-Sore Disease and Temperature 

If the mean seasonal surface temperatures are compared with 
changes in incidence of red-sore disease among bass in Par Pond, then 
a parallel pattern emerges (Fig. 11). The lowest infection percentages 
are in winter, followed by peak infections in spring, and subsequent 
declines in summer and fall. The seasonal changes in infection 
percentages parallel seasonal temperature changes, except during 
summer. 

The overall incidence of red-sore disease was only slightly higher 
among bass from thermal areas (N, 2956; infected, 19%) as compared 
with bass from ambient locations (N, 2431; infected, 16%). This 
pattern does not provide a realistic view of the differences in 
infection percentages among bass in ambient and thermally altered 
locations, however, because of other variables impacting on the 
bacteria and the bass. If, for example, the incidence of disease among 
bass in thermal and ambient locations is compared on a seasonal basis 
(Fig. 12), the influence of temperature can be seen more clearly. 
Thus the levels of infection were significantly higher in bass from 
thermal locations during the fall of 1974, the spring of 1975, and the 
winter months of all 3 years of study. 

Since it appears that temperature is a highly significant variable, 
the question that must be considered is, In what way does 
temperature influence red-sore disease in Par Pond? At the present 



352 



ESCH AND HAZEN 




1975 



1976 



SEASON 



Fig. 11 Mean seasonal surface temperatures (composite for reser- 
voir) and infection percentages among bass. 



35 



30 — 



Q 

L^ 25 
u 

LU 

yr 20 



u 15 



^10 



• , Thermal 
O, Ambient 




F W SP S F W SP S 

1974 1975 1976 

SEASON 



W SP 
1977 



Fig. 12 Seasonal changes in infection percentages of bass from 
ambient and thermal locations. 



THERMAL ECOLOGY AND STRESS 353 

time, two explanations appear to be plausible. First, it is conceivable 
that elevated temperature in thermally altered locations may act as a 
selection force for a more virulent strain of A. hydrophila. Although 
it is indirect and not unequivocal, there is some evidence to support 
this hypothesis. Hazen, Fliermans, and Esch (manuscript in prepara- 
tion) have shown serological and immunological differences in 
certain strains of A. hydrophila isolated from fish, alligators, and Par 
Pond water. This line of study has promise and is being pursued. 
There appears to be a more sound explanation, however, for the 
relation between temperature and red-sore disease in the reservoir. 

Since 1967, more than 10,000 bass have been captured in Par 
Pond (Gibbons et al., in press). The weight— length relationships of 
each of these fish were recorded, and the body condition, or 
K-factor, of each individual was determined. Body condition is a 
measure of individual fitness, or physical well-being (Carlander, 
1969). Parenthetically, it is important to note that mark-recapture 
studies of many of the same 10,000 bass indicate that the vast 
majority (>98%) appear to remain locally within discrete home 
ranges of the reservoir and, consequently, do not move long distances 
(Gibbons and Bennett, 1971; Quinn et. al., 1978; Hazen and Esch, 
1978. When K-factors for all bass are shown seasonally (Fig. 13), 
a distinct pattern emerges. Generally, maximum body condition 
occurs in winter, with lowest conditions in summer. The exceptions 
during the fall of 1975 and in the fall of 1976 are due either to 
variations in reactor activity or to differences in sample sizes in 
thermally altered and ambient locations. 

When body conditions of bass from ambient and thermally 
altered locations are compared (Fig. 14), individuals from thermally 
altered areas are, in general, less fit than those from ambient 
locations. Exceptions to this trend occur in the fall of 1975 and 
again in the winter of 1977. Even when these data are included with 
those from all other seasons, there are significant differences in body 
conditions of bass taken in thermally altered and ambient locations. 

Because of the within-season variability in body condition and 
infection percentage, it was surmised that there could be a 
relationship between body condition and the probability of a bass 
being infected with A. hydrophila. Comparing the infection percent- 
ages for each 0.2-unit K-factor subclass between 1.0 and 3.0 
(Fig. 15), we can see clearly that bass with the lowest body 
conditions are most likely to be infected. The decline in infection 
percentages begins between K-factors of 1,8 and 2.0 and continues to 
decrease as body conditions improve. It is interesting to note that 
virtually all bass with body conditions below 2.0 are without any 



354 



ESCH AND HAZEN 



2.50 



2.40 — 



2.30 



I 



2.20 — 



2.10 



< 



2.00 — 



1.90 — 



1.80 — 



1.70 




1975 



1976 



1977 



SEASON 



Fig. 13 Seasonal changes in body condition (K-factor) of bass in 
relation to changes in mean surface temperature. 



dissectable body fat and that as the percent of body fat increases, 
body condition improves (Gibbons et al., in press). 

Infection percentages were compared in each 0.2-unit K-factor 
subclass for bass from ambient and thermal locations (Fig. 16). For 
bass from thermally altered areas, infection percentages were high 
when body conditions were 1.8 or less. When body conditions were 
> 1.8, infection percentages were lower, but variably so. The pattern 
for bass from ambient locations was clear; infection percentage 
declined beginning at 1.8 and continued to decrease as body 
conditions improved (the zero infection at 3.0 is believed to be 
artifact of the small sample size). Attempts to show these kinds of 
relationships seasonally are ineffective because of relatively small 
sample sizes in certain seasons in all 3 years. If bass are separated into 
two groups, however (> 1.8 and < 1.8), and the data for each season 
for all 3 years are pooled (e.g., spring, 1975—1977), the patterns 
show the impact of temperature on both infection percentage and 
body condition (Fig. 17). 

Several conclusions can be drawn from these observations. First, 
among bass in both thermally altered and ambient locations in Par 
Pond, there is a clear relationship between body condition and the 



THERMAL ECOLOGY AND STRESS 



355 



2.60 



2.50 — 



<u 

c 



.E 2.30 



2.20 



5 2.10 



< 
^2.00 

O 

h- 

^ 1.90 



1.80 



1.70 



• , Thermal 
O, Ambient 




I I I 



W SP 



w 



SP 



1974 



1975 



1976 



W SP 
1977 



SEASON 



Fig. 14 Comparison of seasonal changes in body condition of bass 
from ambient and thermal locations. 




Fig. 15 Comparison of infection percentages among 0.2 unit body 
condition subclasses beginning at 1.0 and extending through 3.0. 



356 



ESCH AND HAZEN 



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THERMAL ECOLOGY AND STRESS 



357 



40 



30 



I- 
o 



20 






10 



• , Thermal 
O, Ambient 




1.0 1.2 1.4 1.6 



1.8 2.0 2.2 
K-FACTOR 



Fig. 17 Seasonal changes at ambient and thermally altered locations 
in infection percentages among bass with body conditions <1.8 and 
>1.8. Thermal samples at K-factors of 2.8 and 3.0 were pooled 
because of small sample sizes. 



probability of a fish's being infected with red-sore disease. Second, 
body condition and infection probability appear to be dependent 
variables, except that the relationship is muted among bass in 
thermally altered locations. It is suggested that the muted effect is 
produced by the higher mean annual temperature in the heated areas 
of Par Pond and that the effect may operate via an immediate and 
direct stress on bass in these locations, which increases susceptibility 
to infection without necessarily having to induce an initial reduction 
in body condition. 



Red-Sore Disease and Stress: A Hypothesis 

On the basis of the evidence presented thus far, there seem to be 
relations among red-sore disease, bass body condition, and water 
temperature. Since these relationships are consistent from year to 
year, can a hypothesis be generated to provide an explanation? The 
answer to this question appears to be yes, and, furthermore, the 
hypothesis will incorporate the stress concept into our thinking on 
the epizootiology of red-sore disease. Indeed, since red-sore disease is 
known to occur in aquatic systems that are not affected by thermal 
effluent (e.g., Albemarle Sound and Badin Lake, North Carolina), it 
is conceivable that stress may be of greatest overall significance. 



358 ESCH AND HAZEN 

As water temperature increases in an aquatic system, the 
metabolic rates of bass will also increase (Fig. 18). With an increase 
in metabolism, there is a concomitant rise in catabolic processes, 
initially involving body fat but ultimately involving body protein as 
well (Gibbons et al., in press). The body condition, or K-factor, of 
bass affected by elevated temperature will, accordingly, decline in 
time (assuming, of course, that caloric intake is exceeded by 
metabolic demand). The exceedingly rapid and extensive growth of 
luxuriant stands of the submergent, rooted, vascular macrophyte, 
Myriophyllum spicatum, contributes to a fall in body condition in 
summer (aside from a normal post-spawn decline). Large masses of 
this plant provide excellent refuge for some species of forage fish. 
Reduced foraging success among bass, coupled with increased energy 
expenditure would exacerbate metabolic processes already conducive 
to reducing body condition. Lowered body conditions increase the 
probability of infection with red-sore disease. This explanation 
certainly describes the situation that occurs during part of the spring, 
throughout the summer, and into the fall months, before Myrio- 
phyllum dies back and disappears. It does not explain the high 
infection percentages that develop early in spring, however. During 
early spring, sexually mature bass are involved with activities 
associated with spawning and levels of circulating sex hormones (all 
steroids) are highest. These hormones function primarily to promote 
sexual behavior and develop secondary sexual characteristics, but 
they are also known to enhance the establishment, maintenance, 
and/or growth of numerous species of parasitic organisms (see Esch, 
Gibbons, and Bourque, 1975, for review). It is, thus, conceivable that 
elevated levels of circulating sex hormones also increase vulnerability 
to infection with A. hydrophila. 

We believe that persistent, elevated temperature in thermally 
altered areas of the reservoir during most seasons of the year and 
during summer in ambient locations also promotes stress in bass. 
Stress, in the classical sense (Selye, 1950), necessarily implies the 
production and release of excess levels of adrenocorticosteroids, 
some of which have a striking anti-inflammatory action that 
promotes increased susceptibility to invasion by pathogenic organ- 
isms. We must point out that we have no evidence for increased 
production of corticosteroids during periods when there are high 
levels of red-sore disease among Par Pond bass, but this line of study 
is being pursued. We do know, however, that thyroxine levels are 
highest in bass during the summer months (Hazen et al., 1978) and 
that an increased level of circulating thyroxine is an indication of 
stress among mammals. 



THERMAL ECOLOGY AND STRESS 



359 



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360 ESCH AND HAZEN 

As previously noted, red-sore disease also occurs among fish 
species in aquatic systems that are not affected by thermal effluent. 
In these systems the disease is associated with such conditions as 
lowered dissolved oxygen and increased organic loading (Meyer, 
1970; Rogers, 1971; Dean, 1974). Under these circumstances, it is 
quite possible that bass are stressed, and this leads to increased 
circulation of corticosteroids and then to increased susceptibility to 
infection with red-sore disease. 

This scenario, which describes the relationships among red-sore 
disease, body condition, and temperature in Par Pond (see Fig. 18), 
includes the possibility that stress may be of significance in reducing 
innate or acquired resistance of bass to infection with A. hydrophila. 
As indicated, we have not yet generated data indicating that 
corticosteroids are higher in bass from thermally altered areas, but 
there is evidence in other fish species that epinephrine and 
corticosteroids vary iii direct proportion to various types of stressors 
(Nakano and Tomlinson, 1967; Hill and Fromm, 1968). 

CONCLUSIONS 

The aim of this discourse has been twofold. First, an effort was 
made to describe the stress phenomenon in physiological terms and 
to illustrate how it has application at the individual and ecosystem 
levels of organization. Second, we attempted to represent these 
relationships by describing the case history of red-sore disease among 
largemouth bass in the southeastern United States. 

Hazen (manuscript in preparation) has isolated Aeromonas 
hydrophila from lakes and streams in 34 states, from Maine in the 
northeast, to Montana in the west, to Texas in the southwest, and to 
Florida in the southeast. The largemouth bass, Micropterus sal- 
moides, is present in virtually all the localities from which A. 
hydrophila has been isolated, yet red-sore disease has been reported 
only in the southeastern United States. On the basis of these 
observations and of our studies in Par Pond, it seems reasonable to 
conclude that only a unique assortment of physicochemical proper- 
ties in a given aquatic system, an assemblage of variably susceptible 
hosts, and the presence of virulent A. hydrophila will promote an 
epizootic outbreak of disease. Stress and its impact at individual, 
population, and ecosystem levels of organization would, of course, 
temper the potential for outbreak. Thus, for red-sore disease to reach 
epizootic proportions, a wide range of interacting biotic and abiotic 
variables are clearly necessary. Perhaps, with additional effort, 
conditions conducive to such outbreaks can be identified. If so, we 



THERMAL ECOLOGY AND STRESS 361 

will have the means for predicting and perhaps minimizing the 
impact of the disease. 

ACKNOWLEDGMENTS 

We especially want to thank James Mathews, Mark Raker, and 
Melanie Trogdon for their excellent technical assistance and thank 
Jean Coleman for her usual excellence in preparing all the figures. 
The research reported here was supported by contract EY-76-S- 
09-0900 between the Energy Research and Development Administra- 
tion (ERDA) and Wake Forest University and contract EY-76- 
C-09-0819 between ERDA and the University of Georgia. The work 
was also supported in part by grants from the North Carolina Board 
of Science and Technology and from the North Carolina Water 
Resources Research Institute. 



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362 ESCH AND HAZEN 



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, G. W. Esch, A. B. Glassman, and J. W. Gibbons, 1978, Relationship of 

Season, Thermal Loading and Red-Sore Disease with Various Hematological 

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, M. L. Raker, and G. W. Esch, 1977, Light and Electron Microscope Studies 

on Lesions Associated with Red-Sore Disease in Largemouth Bass, Bull. 
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, M. L. Raker, G. W. Esch, and C. B. Fliermans, in press, Ultrastructure of 

Red-Sore Lesions on Largemouth Bass; Association of the Peritrich Epistylis 
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Hill, C. W., and P. O. Fromm, 1968, Response of the Interrenal Gland of 

Rainbow Trout (Salmo gairdneri) to Stress, Gen. Comp. Endocrinol, 11: 

69-77. 
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Nuclear Reactor, Physiol Zool, 47: 110-118. 

Lewis, W. M., Jr., 1974, Evaluation of Heat Distribution in a South Carolina 
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Liu, P. v., 1961, Observations on the Specificities of Extracellular Antigens of 
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Lom, J., 1966, Sessiline Peritrichs from the Surface of Some Freshwater Fishes, 
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, 1973, The Mode of Attachment and the Relation to the Host in Apiosoma 

Pissicola (Blanchard) and Epistylis Iwoffi (Faure-Fremiet), Ectocommensals 
of Freshwater Fish, Folia Parasitol (Prague), 20: 105-112. 

May, R. M., 1976, Models for Two Interacting Populations, in Theoretical 
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THERMAL ECOLOGY AND STRESS 363 

Meyer, F. P., 1970, Seasonal Fluctuations in the Incidence of Disease on Fish 

Farms, in A Sy?7iposium on Diseases of Fishes and Shellfishes, S. L. Snieszko 

(Ed.), pp. 21-29, Special Publication No. 5, American Fisheries Society, 

Washington, D.C. 
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of Thermally Affected Aquatic Habitats, J. Water Pollut. Control Fed., 45: 

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Mechanism, Am. Nat., 95: 65-79. 
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Stability, A An. Nat, 110: 877-888. 
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Movement and Homing by Largemouth Bass (Micropterus salmoides) in a 

Thermally Altered Reservoir, Copeia, 1978(3): 542-545. 
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Peritricha) in the Southeastern U. S., Proc, Anna. Conf. Southeast. Assoc. 

Game Fish Comm., 25: 493-496. 
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Marsh Microcosms Subjected to Thermal Stress, in Thermal Ecology, AEC 

Symposium Series, Augusta, Ga., May 3—5, 1973, J. W. Gibbons and R. R. 

Sharitz (Eds.), pp. 391-398, CONF-730505, NTIS. 
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1383-1392. 

, 1956, The Stress of Life, McGraw-Hill Book Company, Inc., New York. 

Shotts, E. B., J. L. Gaines, C. Martin, and A. K. Prestwood, 1972, Aeromonas- 

Induced Deaths Among Fish and Reptiles in an Eutrophic Inland Lake, J. 

Am. Vet. Med. Assoc, 161: 603-607. 
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Biology and Evolution, R. C. Lewontin (Ed.), pp. 187-205, Syracuse 

University Press, Syracuse, N.Y. 
Vadas, R. L., M. Keser, P. C. Rusanowski, and B. R. Larson, 1976, The Effects 

of Thermal Loading on the Growth and Ecology of a Northern Population of 

Spartina alterniflora, in Thermal Ecology II, ERDA Symposium Series, 

Augusta, Ga., Apr. 2-5, 1975, G. W. Esch and R. W. McFarlane (Eds.), pp. 

54-63, CONF-750425, NTIS. 



SIZE-FRACTIONATED PRIMARY PRODUCTIVITY 
IN LAKE MICHIGAN NEAR THE KEWAUNEE 
NUCLEAR POWER PLANT 



STEPHAN I. ZEEMAN* and RALPH GRUNEWALD 
Department of Botany and the Center for Great Lakes Studies, 
The University of Wisconsin, Milwaukee, Wisconsin 



ABSTRACT 

Primary productivity rates were measured at the site of the Kewaunee Nuclear 
Power Plant from Aug. 26, 1975, to July 23, 1976. Productivity was determined 
for three size fractions by sequential filtration through 64-, 10-, and 0.45-jUm 
porosity filters. Total unfractionated productivity was also measured. Univariate 
analysis of variance showed no difference (P > 0.05) between pre- and 
postcondenser productivity rates of the unfractionated samples. Multivariate 
analysis of variance applied to size-fractionated samples detected lower rates 
only when there was a AT across the condenser. These differences were caused 
by changes in the <10- and >64-/jm fractions. Average productivity rates for the 
year at the postcondenser station were within 13% of those at the precondenser 
station. Chlorophyll a values were within 4% of precondenser values. It was 
concluded that, although individual phytoplankton may be killed by passage 
through the cooling system, populations suffer no permanent damage. Both 
productivity rates and chlorophyll a concentrations for the net plankton 
(>64 ixm) averaged over 55% of the sum of the three fractions. The 10- to 64-^<m 
fraction averaged about 12% for productivity and 24% for chlorophyll, but the 
values for the <10-jUm fraction were about 30 and 20% of the sum of the 
fractions for productivity and chlorophyll, respectively. Assimilation numbers 
(milligrams of carbon per milligram of chlorophyll a per cubic meter per hour) 
were generally low (<3) for the unfractionated plankton. For the size- 
fractionated samples, the two larger fractions were most often low, and the 
<10-jUm fraction had numbers >3 on 44% of the sampling dates. 



*Present address: Marine Science Program, University of South Carolina, 
Columbia, S. C. 

364 



SIZE-FRACTIONATED PRIMARY PRODUCTIVITY 365 

This study assesses the effect on the rate of phytoplankton 
productivity of passage through the cooUng system at the Kewaunee 
Nuclear Power Plant. An important facet of this research was the 
determination of photosynthetic rates for three size classes of 
phytoplankton, as well as for the total community. 

Passing through the cooling system of a steam electric-power 
station subjects phytoplankton to a variety of stresses, including: 
(1) mechanical stress from physical abrasion, pressure changes, and 
turbulence; (2) thermal stress; and (3) chemical effects of antifouling 
agents, corrosion products, and concentrations of dissolved gases 
(Lauer, Walter, and Beck, 1972). The effects of these stresses are not 
at all certain. The severity of a stress depends on its intensity and 
duration and on the physiological condition of the organisms. 

The effects of temperature on microalgae were reviewed by 
Hoogenhout £ind Amesz (1965). Patrick (1969) gave temperature 
tolerance ranges for freshwater algae and stated that diatoms 
preferred temperatures below 30°C and that condenser passage 
causes little or no harm to algae if the temperature remains below 
34.5°C. Furthermore, if the volume of the entrained water is small 
relative to the volume of the receiving water body, any effect on the 
phytoplankton population as a whole will likely be negligible 
(Patrick, 1974). 

Many studies have shown that photosynthetic rates may be 
affected by temperature changes and condenser passage. Warinner 
and Brehmer (1966) showed that enhancement or suppression of 
photosynthesis depends on initial temperature as well as the 
temperature increase. Similar results were reported by other investi- 
gators (e.g., Morgan and Stross, 1969; Brooks, 1972; Fox and Moyer, 
1973). 

In a preoperational study at the Kewaunee Nuclear Power Plant, 
Bremer and Redmond (1974) found that, in nine of ten sampling 
periods, analyses detected a significant difference between the 
precondenser and discharge productivity rates at Kewaunee. They 
showed that mechanical effects could reduce productivity rates from 
1 to 34%. Operational studies on immediate effects (7 hr after 
sample collection) showed that chlorophyll was significantly lower in 
the discharge on only one occasion (Jones, Brown, and Redmond, 
1975). Significant difference in productivity between the precon- 
denser and discharge sites was not detected. Furthermore, mechani- 
cal effects were responsible for mean annual decreases of only 8% for 
productivity and 5% for chlorophyll. Delayed effects (after 24 and 
48 hr), although more variable, were still minimal. These studies 
suggest that normal plant operations might have only limited effects 
on phytoplankton assemblages entrained in the cooling water. 



366 ZEEMAN AND GRUNEWALD 

Differential injury and recovery of specific size classes of 
entrained phytoplankton could be important to community struc- 
ture in the receiving waters. The small nannoplankton are thought to 
be more important to primary production than the larger net 
plankton (Pomeroy, 1974). Rodhe, Vollenweider, and Nauwerck 
(1958) found that nannoplankton were responsible for more than 
90% of production in spring and early summer and that net plankton 
became more important in summer and fall. Similar results were 
presented by Goldman and Wetzel (1963). 

As far as we know, the application of multivariate analysis of 
variance (MANOVA) to a data set of this type is novel, but 
multivariate analyses in general have been successfully applied to 
algal communities (Allen and Skagen, 1973). 

Since there were multiple measures for each sample (i.e., 
size-fractionated productivities), the chances for correlation among 
the variables was high (Van de Geer, 1971). Thus a separate analysis 
for each variable would not constitute independent tests. The 
MANOVA technique then provides an important analytical tool, and 
separate analyses should be avoided unless the MANOVA null 
hypothesis has been rejected (Cooley and Lohnes, 1971). The 
MANOVA procedure assumes a multivariate normal distribution for 
variables with equality of dispersions. 

MATERIALS AND METHODS 

Site Description 

The Kewaunee Nuclear Power Plant is located on the shore of 
Lake Michigan, ~43.5 km east— southeast of Green Bay, Wise. The 
facility has once-through cooling and can produce a net output of 
540 MW(e). Ambient temperatures ranged from 0.5 to 18.3°C and 
AT's, from to 14.5°C. The maximum discharge temperature 
recorded during this study was 28.8°C. 

Sampling 

Sampling was initiated on Aug. 26, 1975, and concluded on 
July 23, 1976. Samples were collected from a precondenser station 
in the forebay (FRB) and a postcondenser station in the discharge 
flume (KD) on eighteen dates. Two other stations were sampled on 
six dates from August to November, one at the intake structure 
(KWI) and one at a reference station (REF) about 4 km north of the 
plant. Figure 1 shows the location of the plant and the sampling 
sites. 



SIZE-FRACTIONATED PRIMARY PRODUCTIVITY 



367 




Fig. 1 Location of study area and sampling stations. 



Water samples were obtained with an opaque, 2-liter, PVC 
Van Doni sampler at a depth of 3 m at all sites except KD, where the 
depth of the samples varied because the current was too fast. Five 
separate casts were made at each site, and the water was stored in 
opaque, 2-liter plastic jars. Three samples were used for the carbon 
uptake experiments and two for chlorophyll extraction. At each site 
a 1-liter polyethylene bottle was also filled with lake water for 
inorganic carbon determination. 



368 ZEEMAN AND GRUNEWALD 

Carbon Uptake 

Photosynthetic rates of phytoplankton were estimated by the 
radiocarbon method described by Steeman-Nielsen (1952). Individ- 
ual samples were mixed well, and subsamples were siphoned into sets 
of two light and one dark bottle (125-ml glass-stoppered bottles). 
For each site, three sets were used in the size-fractionated procedure, 
one set from each of three different samples. In addition, one or two 
other sets were filled to measure the total unfractionated carbon 
uptake. 

Each bottle was inoculated with 5 [jlCi of Na2H''*C03 and 
incubated for 4 hr in a constant temperature (ambient) and light 
incubator. All incubations were started between 1000 and 1100 hr 
local time to minimize any effects of diurnal rhythms (Doty and 
Oguri, 1957). 

Light was provided by 40-W cool-white fluorescent tubes. 
Intensities were checked before each experiment and adjusted to give 
not less than 150 microeinsteins m~^ sec"' (~900 ft-c). 

Samples were filtered immediately after the incubation period, at 
a vacuum of /^ atm. 

The radiocarbon and chlorophyll samples were fractionated 
sequentially. Bothwell (1975) showed that this was superior to 
estimating from differential titrations. The apparatus, based on a 
design by Schubel and Schiemer (1969), used filters of 10- and 
64-jum pore size Nitex netting (Tetko, Inc.) and 0.45-jum HA 
Millipore filters. 

After filtration, all filters were fumed with concentrated HCl and 
placed in vials containing 15 ml of Aquasol (New England Nuclear). 
Samples were later counted in a liquid scintillation counter. 

Total inorganic carbon in the water samples was determined 
potentiometrically as described by Golterman and Clymo (1969). 

Chlorophyll 

Chlorophyll a and phaeopigments were measured fluorometrically 
(Strickland and Parsons, 1972). After filtration, the filters were 
placed in screw-cap vials containing 10 ml of 90% acetone, and the 
vials were wrapped in aluminum foil and kept refrigerated for 24 hr. 
No grinding was attempted since it was impractical with the Nitex 
filters. Thus there was a possibility of incomplete extraction 
(Yentsch and Menzel, 1963), but Bothwell (1975) indicated that this 
was not a serious problem. 



SIZE-FRACTIONATED PRIMARY PRODUCTIVITY 369 

Statistics 

Univariate analysis of variance (ANOVA) computations were 
made with the program NWAYl of the STAT JOB series (Academic 
Computing Center, University of Wisconsin, Madison). The 
M ANOVA computations were made with program BMD12V of the 
BMD series (Dixon, 1968). 

RESULTS 

Primary Productivity 

The unfractionated productivity measurements ranged from < 1 
to about 30 mg C m~^ hr~ ' , with the highest values occurring in late 
October. Interestingly, the < 10- and the 10- to 64-iUm fractions 
remained relatively low and constant throughout the year, usually 
contributing less than 5 mg C m~^ hr~' . The > 64-^m fraction, on 
the other hand, was responsible for the large seasonal variations 
observed in the unfractionated productivity measurements, reaching 
peak values of about 20 mg C m~^ hr~ ^ in the fall. 

The results of the productivity measurements were tested by the 
MANOVA technique. The model used as a first step was a three-way 
partial hierarchical design. The three factors were date, station, and 
sample nested within station. The dependent variables were the three 
size fractions (the unfractionated totals and the sums of the fractions 
were tested separately). With the experimental design used, we hoped 
to estimate adequately the within-station variance and factor it out 
from the true between-station variance. Each sample was replicated 
(the two light bottles) to account for technique errors. The three 
samples taken at each station should estimate within-station variance. 

The MANOVA results are shown in Table 1. The first analysis, 
which was for the six dates when all four stations were sampled, 
indicates that all main effects and their interactions were significant. 
When the analysis was repeated for the 18 dates with only samples 
from stations FRB (precondenser) and KD (postcondenser), again all 
effects were significant (Table 1). 

The MANOVA was also applied to the results for the four dates 
when there was a AT of zero. The only significant factor at a = 0.05 
was date (Table 1). A test on the remaining dates with a AT again 
showed all effects to be significant. This indicates that productivity 
rates at KD were different from FRB because of plant operations. To 
make the tests more comparable, since only four dates had no AT, 
we selected four dates randomly (June 25, Sept. 20, July 12, and 
Jan. 15). The MANOVA test on these four dates again showed all 
effects to be significant. Mean productivity rates were slightly lower 



370 ZEEMAN AND GRUNEWALD 



TABLE 1 



MANOVA RESULTS FOR PRIMARY PRODUCTIVITY 

MEASUREMENTS, WITH THE RATES OF THREE SIZE 

FRACTIONS AS DEPENDENT VARIABLES 



Source 


df 


F 


Sign 


All Four Stations (6 dates) 






Dates 


15, 193.64 


113.0055 


* 


Stations 


9, 170.51 


40.8262 


* 


Samples within (stations) 


24, 203.62 


2.8252 


* 


Date X station 


45, 208.73 


7.6476 


* 


Date X sample (station) 


120, 210.63 


1.6923 


* 


Stations 


FRB and KD (18 dates) 




Dates 


51, 316.38 


62.3049 


* 


Stations 


3, 106.0 


9.4821 


* 


Samples (station) 


12, 280.74 


2.9821 


* 


Date X station 


51, 316.38 


2.8676 


* 


Date X sample (station) 


204, 318.80 


1.7987 


* 


Stations 


1 FRB and KD (AT = 


0) 




Dates 


9, 53.63 


76.0505 


* 


Stations 


3, 22 


1.5719 




Samples (station) 


12, 58.5 


0.9330 




Date X station 


9, 53.69 


0.6656 




Date X sample (station) 


36, 65.73 


1.0489 




Stations FRB and KB (AT 9^ 0, 4 ram 


dom dates) 




Dates 


9,53.69 


96.9242 


* 


Stations 


3,22 


14.5135 


* 


Samples (station) 


12, 58.5 


4.3724 


* 


Date X station 


9,53.69 


10.7098 


* 


Date X sample (station) 


36, 65.73 


4.0723 


* 



*Significant at a = 0.05. 

for all three fractions at station KD when a AT was present across 
the condenser. The difference is more noticeable for the < 10- and 
> 64-jum fractions. We should note that, on three of the four dates 
with no AT, only one pump was in operation. (Flow rates were 
1.086 X 10-^ and 1.56 x 10^ m^/min with one and two pumps 
operating, respectively.) Thus mechanical effects may play an 
important role. 

The results of a two-way MANOVA run on data from stations 
KD and FRB for individual dates, with station and sample as 
independent variables, are shown in Table 2. On 8 of the 18 dates. 



SIZE-FRACTIONATED PRIMARY PRODUCTIVITY 371 

the stations were sigiiificaiitly different. Samples also differed 
significantly on 8 dates, but not always the same dates as those for 
station effects. The four dates with no AT showed no significant 
differences between stations or samples at o: = 0.05. 

In an attempt to see which variables were contributing most to 
the observed MANOVA results, we carried out univariate three-way 
mixed-model ANOVA tests on each size fraction separately. The 
results of these tests, shown in Table 3, indicate that the 10- to 
64-jum fraction is consistent over all stations and samples. The <10- 
and > 64-/um fractions, however, form the basis of distinctions 
between stations. This is not wholly unexpected in view of the fact 
that the medium fraction, on the average, contributed only about 
12% to the sum or productivity rates. Note also that sample variances 
are significant for the < 10-^m fraction but not for the other 
fractions. 

Univariate ANOVA tests were also run on the sums of the 
fractions and the unfractionated totals of the productivity measure- 
ments. A three-way mixed-model ANOVA was again used for the 
sums of the fractions, but a two-way mixed model was required for 
the unfractionated totals because of unequal cell numbers. The 
results are shown in Table 4. Only the sample factor was not 
significant for the sums of the fractions. The ANOVA results for the 
unfractionated totals showed that stations were not significantly 
different, however. 

To estimate relative variations within a station, we determined the 
coefficients of variation. These values ranged from 0.118 to 224.2%, 
with one exceptional value at 1217%. This considerable variability is 
not totally unexpected since patchiness of plankton is well docu- 
mented (e.g., Piatt, Dickie, and Trites, 1970; McAlice, 1970). 
Furthermore, methodological problems are indicated by the fact that 
the sums of the fractions and the unfractionated total are not equal 
for any given experiment. This disparity has been documented in 
other studies (e.g., Rodhe, Vollenweider, and Nauwerck, 1958; 
McCarthy, Taylor, and Loftus, 1974). 

Chlorophyll a 

The unfractionated chlorophyll a concentrations ranged from ~2 
to 13 mg/m^ . Little difference could be seen among the stations for 
either unfractionated or fractionated concentrations. As with the 
productivity measurements, the < 10-/jm fraction was relatively low 
and constant throughout the year (ranging between 0.5 and 
3.5mg/m'^). The > 64-/im fraction was responsible for the large 
seasonal fluctuations observed (ranging between 1 and 11 mg/m'^). 



372 



ZEEMAN AND GRUNEWALD 



TABLE 2 

MANOVA RESULTS FOR PRIMARY PRODUCTIVITY 

MEASUREMENTS AT STATIONS FRB AND KD, WITH 

THE RATES OF THE THREE SIZE FRACTIONS AS 

DEPENDENT VARIABLES 







Number 






Date 


AT 


of pumps 


Sourcet 


Sign 


8/26/75 


9.5 


2 


A 
B 


* 


9/6/75 


6.1 


2 


A 
B 


* 
* 


9/20/75 


3.0 


2 


A 
B 




10/4/75 


9.5 


2 


A 
B 


* 


10/24/75 


9.5 


2 


A 
B 




11/1/75 





1 


A 
B 




11/15/75 


6.0 


2 


A 
B 




12/17/75 


14.5 


1 


A 
B 




1/15/76 


6.3 


1 


A 
B 


* 
* 


2/14/76 





1 


A 
B 




3/27/76 





1 


A 
B 




4/14/76 


3.5 


2 


A 
B 


* 


5/1/76 


8.0 


2 


A 
B 


* 


5/19/76 





2 


A 
B 




6/9/76 


9.5 


2 


A 
B 


* 
* 


6/25/76 


9.5 


2 


A 
B 


* 


7/12/76 


9.7 


2 


A 
B 


* 
* 


7/23/76 


10.0 


2 


A 
B 


* 
* 


♦Significant at 


a = 0.05 








tA, station; B, 


sample. 









TABLE 3 373 

ANOVA RESULTS FOR PRIMARY 

PRODUCTIVITY MEASUREMENTS ANALYZING 

EACH FRACTION INDIVIDUALLY 



Sourcet 



df 



MS 



Sign 



Three-Way ANOVA for All Stations (6 dates) 
0.45- to 10-^m Fraction 



A 


5, 72 


17.90529 


217.88 


* 


B 


3, 72 


18.07965 


220.00 


* 


C(B) 


8, 72 


0.49502 


6.02 


* 


AX B 


15, 72 


3.15367 


38.37 


* 


A X C (B) 


40, 72 


0.20671 
10- to 64-iJm Fraction 


2.52 


* 


A 


5, 72 


20.77367 


163.24 


* 


B 


3, 72 


0.18209 


1.43 




C(B) 


8, 72 


0.14739 


1.16 




A X B 


15, 72 


0.23573 


1.85 


* 


A X C (B) 


40, 72 


0.19897 
>64-^fm Fraction 


1.56 


* 


A 


5, 72 


430.87411 


316.38 


* 


B 


3, 72 


11.16415 


8.20 


* 


C(B) 


8, 72 


1.50015 


1.10 




A X B 


15, 72 


7.57823 


5.56 


* 


A X C (B) 


40, 72 


2.21260 


1.62 


* 



Three-Way ANOVA for Stations FRB and KD (all dates) 



0.45- to 10-/jm Fraction 



A 


17, 108 


9.86904 


60.86 


* 


B 


1, 108 


1.37600 


8.49 


* 


C(B) 


4, 108 


0.45492 


5.11 


* 


AX B 


17, 108 


0.96713 


5.96 


* 


AX C (B) 


68, 108 
IC 


0.16214 
>- to 64-/jm Fraction 


2.81 


* 


A 


17, 107 


15.38948 


105.38 


* 


B 


1, 107 


0.16729 


1.15 




C(B) 


4, 107 


0.12321 


1.84 




A X B 


17, 107 


0.24905 


1.71 




A X C (B) 


68, 107 


0.17070 
>64-/./m Fraction 


1.17 




A 


17, 108 


332.05368 


261.38 


* 


B 


1, 108 


24.05937 


18.94 


* 


C(B) 


4, 108 


3.51762 


2.77 




A X B 


17, 108 


2.04306 


1.61 


* 


AX C (B) 


68, 108 


2.31443 


1.82 


* 



*Significant at a = 0.05. 

tA, date; B, station; and C (B), sample (station). 



374 ZEEMAN AND GRUNEWALD 



TABLE 4 



ANOVA RESULTS FOR PRIMARY PRODUCTIVITY 

MEASUREMENTS ANALYZING THE SUMS OF FRACTIONS 

AND UNFRACTIONATED TOTALS 



Source 


df 


MS 


F Sign 


Three-Way ANOVA on 


Sums of Fract 


ions for All Stations (6 dates) 


Date' 


5, 72 


759.55246 


387.69 * 


Station 


3,72 


26.03235 


13.29 * 


Sample (station) 


8,72 


2.46270 


1.26 


Date X station 


15,72 


21.20638 


10.82 * 


Date X sample (station) 


40,72 


1.95916 


1.85 * 



Three-Way ANOVA on Sums of Fractions for Stations 
FRB and KD (all dates) 



Date 


17,108 575.05704 298.14 


* 


Station 


1, 108 32.13914 16.66 


* 


Sample (station) 


4, 108 3.89665 2.02 




Date X station 


17,108 3.68309 1.91 


* 


Date X sample (station) 


68,108 1.92879 2.06 


* 


Two-Way ANOVA on Unfractionated Totals for All Stations (6 dc 


ites) 


Date 


5,24 289.55586 182.17 


* 


Station 


3,24 1.47682 0.93 




Date X station 


15,24 9.25700 5.82 


* 



Two-Way ANOVA on Unfractionated Totals for Stations 
FRB and KD (all dates) 



Date 


17, 76 


345.29883 


305.87 


* 


Station 


1, 76 


0.81450 


0.72 




Date X station 


17, 76 


3.19544 


2.83 


* 



*Significant at a = 0.05. 



Evidence of patchiness was found on several occasions. For 
example, on Aug. 26 there was a relatively high concentration for the 

> 64-/am fraction at station KWI which was not observed at any of 
the other stations. Similarly, high values were recorded for the 

> 64-iim fraction on Sept. 20 at all stations except REF. 

On the average, pre- and postcondenser chlorophyll a concentra- 
tions were comparable. The relative concentrations were 104, 98.5, 
102, 99, and 101% of those found at FRB for the < 10-, 10- to 64-, 
and > 64-/im fractions, the unfractionated total, and the sum of the 
fractions, respectively. 



SIZE-FRACTIONATED PRIMARY PRODUCTIVITY 375 

Assimilation Ratios 

The relationship of productivity per unit of chlorophyll a is 
known as the assimilation ratio. Current usage of assimilation ratio 
implies that carbon uptake should be measured at light saturation 
(Tailing, 1974). During this study light intensity was kept constant, 
and no provision was made to determine saturating intensities, which 
are species dependent. For most of the year, the small fractions have 
the highest assimilation numbers. This is to be expected since small 
organisms have higher surface-to-volume ratios and, thus, are able to 
absorb nutrients more readily (Dugdale, 1967). The assimilation ratio 
has also been said to be a measure of physiological status (Thomas, 
1970; Eppley, 1972). High ratios tend to indicate that factors such as 
temperature or nutrients are not limiting. 

The medium fraction consistently had the lowest assimilation 
ratios. On the basis of size alone, the ratios in this fraction would be 
expected to be higher than the large fraction. Therefore, they may 
consist largely of detrital material, damaged cells, or broken 
filaments from the large fraction, or, alternatively, they may require 
different temperatures or light intensities. 

The large fraction, although usually intermediate in terms of 
assimilation numbers, did reach a significant peak in spring (between 
5.5 and 9.5). 

The size-fractionated assimilation ratios showed some differences 
among the stations. Stations KWI and REF generally had higher 
ratios for the small fraction than did stations KD and FRB. There 
was also a spike in the small fraction at FRB on Sept. 20 which was 
not apparent at the other stations. The peaks in assimilation numbers 
were generally higher for station FRB than the corresponding peaks 
for KD. This could indicate lowered photosynthetic capacity after 
passage through the plant, 

DISCUSSION 

In this report we address power-plant operation only in relation 
to the physiological status of entrained phytoplankton. More general 
discussions on the ecology of the nearshore phytoplankton are given 
elsewhere (Zeeman, 1977). 

Entrainment Effects 

In this study, we attempted to distinguish between variances 
caused by sampling methods and true differences in primary 
productivity among stations by means of both multivariate and 



376 ZEEMAIM AND GRUNEWALD 

univciriate analysis of variance. The models were designed to factor 
out effects of repetitive sampling to estimate true differences. The 
statistical results seem contradictory, however. When the three size 
fractions were analyzed simultaneously, power-plant operations 
appeared to be having an effect, however small. Differences among 
samples from the same station were also found to be significant when 
the plant was in operation. This indicates patchy distribution of 
phytoplankton. When the sums of the size fractions were subjected 
to ANOVA techniques, station differences were once again seen, but 
sample effects were not observed. The unfractionated productivity 
measurements, on the other hand, showed no differences among 
stations. Sample effects in the last analysis could not be tested. 

One explanation for the observed results is that perhaps the 
size-fractionation method produces artifacts. The sums of the 
fractions and the unfractionated totals are not the same in any given 
experiment. It is, therefore, not unreasonable to assume that this 
could influence the outcome of statistical tests. Holmes and 
Anderson (1963) and Lasker and Holmes (1957) showed how 
variable retention can be on different filters. Evidence that size 
fractionation is responsible for much of the variance in productivity 
among stations comes from the ANOVA results. Analysis on the 
unfractionated totals showed no significant differences among 
stations, yet the ANOVA on the sums of the fractions showed that 
differences did exist. If the methodology were as precise as desired, 
the results would agree. 

According to Strickland and Parsons (1972), the precision of the 
radiocairbon technique is ~7% for two replicates at the 
1.5 mg C m~^ hr~' level and ~8% at the 25 mg C m~^ hr~^ level. 
For six replicates the precision is increased to about 5 and 4% for the 
two levels, respectively. From the coefficients of variation in this 
study, it was evident that any attempt to characterize differences in 
productivities among the sites was going to be complicated by large 
variations, possibly caused by patchiness and analytical error. 

Differences in productivity rates between the precondenser 
(FRB) and the postcondenser stations (KD) were small when 
averaged over the entire year. Percent differences (in comparison to 
FRB) were -9.08, +5.32, -12.12, -2.62, and -9.27% for the 
small-, medium-, and large-size fractions, the unfractionated total, 
and the sum of the fractions, respectively. Even though these values 
showed a general decrease at KD, we do not feel they are biologically 
significant in view of the methodologies involved in their determina- 
tion. The slight increase observed for the medium-size fraction, if 
real, was possibly caused by breakage of filamentous or colonial algae 



SIZE-FRACTIONATED PRIMARY PRODUCTIVITY 377 

into smaller fragments, which are apparently undamaged. The 
chlorophyll concentration was unaffected (98.5% of FRB), however. 
Therefore either the power plant stimulated photosynthesis in this 
fraction or the results are related to the method of fractionation. 

Rousar (1973) reported a mean productivity rate of 
9.6 mg C m~^ hr~^ at an inshore Wisconsin station. Our estimates 
were 9.3 and 8.6mgCm~^ hr~^ at stations FRB and KD, 
respectively. This indicates that power-plant operation has not 
radically altered productivity rates in the surrounding region. Rather, 
deaths of individual phytoplankton caused by entrainment were 
balanced by natural processes of population growth. We also 
calculated that, at most, only 0.41% of the nearshore water (0 to 
30 m in depth) could pass through the plant annually. 

Natural variability poses a significant obstacle to determining 
small changes in productivity or chlorophyll a. Carpenter, Anderson, 
and Peck (1974) stated that inabihty to detect changes in photo- 
synthetic rates could be caused by sampling error or patchiness or 
could be because there was no actual difference. They also concluded 
that for chlorophyll a 88 rephcates would have to be taken to detect 
a ±5% change. Similarly, 22 replicates were required for a ±10% 
change and 6 replicates for a ±20% change. 

The fact that the unfractionated productivities at the pre- and 
postcondenser stations were virtually identical and were not signifi- 
cantly different statistically was a very strong indication that the 
power plant was not affecting the phytoplankton. Any differences 
observed between the stations were probably negligible when the 
precision of sampling techniques and analytical procedures is taken 
into account. Statistical tests indicate that if certain components of 
the phytoplankton were affected, whether by stimulatory or 
inhibitory action, it would be those having dimensions < 10 and 
> 64 [ira. 

This discussion presents the pertinent facts regarding the effects 
of power-plant operation on primary productivity at the Kewaunee 
Power Plant. Some of the statistical results suggest that plant 
operation may be injurious to individual phytoplankton passing 
through the cooling system, but the effect on populations is 
negligible. Furthermore, any observed changes could be artifacts of 
the methods used in the study. If they are real, the effects are small 
and detectable only by statistical techniques. Indeed, they may not 
even be as significant as such natural perturbations as wave action 
during storms. 

The lack of any obvious effects on the phytoplankton is 
probably a result of several factors. The ambient temperatures of 



378 ZEEMAN AND GRUNEWALD 

Lake Michigan are relatively low, and temperature rises caused by the 
power plant are not sufficiently great to exceed the thermal 
tolerance limits of the organisms, even during the summer. Also 
important is that this power plant does not have to use chlorine or 
other biocide to maintain efficient heat exchange in the condenser 
tubes. 

Estimates of size-fractionated productivity are important to our 
understanding of aquatic ecosystems. Their utility will increase 
further when our knowledge of size-selective grazing is improved. 
Entrainment does not seem significant to phytoplankton population 
changes at the Kewaunee Nuclear Power Plant, but conditions may 
be different elsewhere. Changes in productivity of certain size classes 
could have far-reaching implications to trophic structure. 

Multivariant analysis of variance, as demonstrated here, could 
prove to be a useful tool in analyzing structural changes in 
phytoplankton communities. The ability to analyze several variables 
simultaneously adds new dimensions to ecological investigations 
which have been neglected previously. These variables need not be 
limited to productivity rates. Indeed, it might prove enlightening to 
use other measurements (e.g., of adenosine triphosphate or chloro- 
phyll a) in combination with productivity estimates. 

ACKNOWLEDGMENTS 

This research was supported in part by a grant to The University 
of Wisconsin, Milwaukee, Department of Botany, from the Wisconsin 
Public Service Corporation and by a research assistantship to Stephan 
Zeeman from the Center for Great Lakes Studies, UWM. This study 
was part of an M.S. thesis in botany by Zeeman. 

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Brooks, A. S., 1972, The Influence of a Thermal Effluent on the Phytoplankton 
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SIZE-FRACTIONATED PRIMARY PRODUCTIVITY 379 

Carpenter, E. J., S. J. Anderson, and B. B. Peck, 1974, Copepod and Chlorophyll 

a Concentrations in Receiving Waters of a Nuclear Power Station and 

Pi-oblems Associated with Their Measurement, Estuarine Coastal Mar. Sci., 2: 

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Golterman, H. L., and R. S. Clymo (Eds.), 1969, Methods for Chemical 
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Holmes, R. W., and G. C. Anderson, 1963, Size Fractionation of C' "^-labeled 
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Jones, P. A., C. L. Brown, and D. G. Redmond, 1975, Phytoplankton 
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Patrick, R., 1969, Some Effects of Temperature on Freshwater, in Biological 
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380 ZEEMAN AND GRUNEWALD 



, 1974, Effects of Abnormal Temperatures on Algal Communities, in 

Thermal Ecology, AEC Symposium Series, Augusta, Ga., May 3—5, 1973, 

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Wisconsin, Milwaukee. 



PRIMARY PRODUCTIVITY: ANALYSIS 
OF VARIANCE IN A THERMALLY 
ENRICHED AQUATIC SYSTEM 



MARGARET O. WELCH and C. H. WARD 

Departments of Biology and Environmental Science and Engineering, 

Rice University, Houston, Texas 



ABSTRACT 

Primary production experiments were performed in a 400-ha cooling reservoir 
for a 530-MW electric generating plant in eastern Texas over a 15-month period. 
Annual primary productivity of the heated and ambient surface waters and the 
nutrient enrichment response were investigated in situ by ' C methods. On the 
basis of analysis of variance techniques, primary productivity was significantly 
higher at the heated station on 18 of 26 sampling dates, but the magnitude of 
the difference was not correlated with the difference in water temperature at the 
stations. Nutrient enrichment had no effect on primary productivity, but 
temperature did. Regression analysis indicated that the temperature optimum 
for the natural population of phytoplankton was ~25 C. The temperature 
tolerance range for the phytoplankton community subjected to higher tempera- 
tures was higher than for the community at ambient temperatures. 



An understanding of the biology of high-temperature aquatic systems 
is necessary for predicting and managing the effects of man-induced 
thermal additions. The extensive literature (e.g., Patrick, 1969; Fogg, 
1975) documenting the thermal tolerance range and the thermal 
optimum of many species of freshwater algae enables us to generalize 
that more species of the Cyanophyta are thermsil tolerant and grow 
well above 35°C, that the Chlorophyta tend to grow best up to 35°C, 
and that the diatoms, the Bacillariophyta, succeed best below 30°C. 
Most investigators agree that the thermal optimum for all species in 
the laboratory is generally higher than that in natural aquatic 
systems. Castenholz and Wickstrom (1975) and Patrick (1969) 
pointed out that most studies deal with the effects of thermal 

381 



382 WELCH AND WARD 

additions on species or on populations, but not a great deal is known 
about the effects at the community, level. When the thermal 
optimum for existing species is exceeded in natural waters, the 
species are unable to compete for the available resources, and the 
community structure of the system changes. The seasonal variation 
of resources superimposes more complicating factors. The question 
is, Will system function, energy flow, and productivity also be 
altered? 

The objectives of this study were to measure and evaluate the 
effect of increased temperature on a phytoplankton community as 
indicated by primary productivity. Annual primary productivity of 
the heated and unheated surface waters of a cooling reservoir were 
investigated in situ by ' '^C methods. 

LITERATURE 

Warinner and Brehmer (1966), studying the effects of thermal 
effluents on a community of marine organisms in a riverine estuary, 
found an increase in primary production during the winter months 
and a decrease during the summer months. Patrick (1969) noted 
that, as long as nutrients and light are sufficient, productivity may 
increase with increases of temperature within the thermal tolerance 
range of the existing algae. Simmons and Armitage (1974) deter- 
mined that heated power-plant effluent had no effect on algal 
blooms in the Potomac River. Foerster, Trainor, and Buck (1974), 
on finding that blooms correlated well with increased temperature, 
thought that the mechanism might be an increase in the rate of 
diffusion across the depletion zone surrounding the algal cell. Tilly 
(1973; 1974; 1975) and Marshall and Tilly (1971) reported on 
investigations of phytoplankton and periphyton in Par Pond in South 
Carolina. Maximum productivity and integral productivity were 
strongly correlated with temperature increases, but primary produc- 
tivity per unit of chlorophyll was not. Tilly theorized that elevated 
temperatures enabled phytoplankton to use higher light intensities 
without photoinhibition, a phenomenon well documented in labora- 
tory studies (Sorokin and Myers, 1953). 



DESCRIPTIOIM OF THE STUDY AREA 

Lewis Creek Reservoir (Fig. 1) is a 404-ha reservoir constructed 
in 1970 by Gulf States Utilities as a semiclosed system to cool the 
condensers of a 530-MW electric generating plant. The reservoir, 



PRIMARY PRODUCTIVITY 



383 




INTAKE 



Fig. 1 Approximate bathometry of Lewis Creek Reservoir. Contour 
lines show depth. 

formed by constructing an earthen dam over Lewis Creek, an 
intermittent stream, has a maximum depth of 5.34 m, and its 
elevation is 83 m. It is located in Montgomery County, Texas, at 
latitude 30°26' and longitude 95° 32'. The climate is subtropical, 
with mild winters, hot, humid summers, and a rainfall average of 120 
cm/year. The drainage basin is ^^1000 ha, and the land is used 
principally as pine timberland and livestock range. The area is 
sparsely populated. 

Station 1 was located at the outfall of the canal, which discharges 
into a small preliminary cooling pond ~1 km from the generating 
plant. The temperature at Station 1 approximated the temperature 
of the effluent as it left the plant. Station 2 was in a cove of the lake 
~2.5 km by water from Station 1. Because of the construction of a 
dike, these two stations were separated by land by about 15 m. This 
permitted almost simultaneous sampling and incubation. The 
temperature of Station 2 approximated the temperature of the water 
at the intake screen. 



METHODS 

Sampling 

Sample collections were made from September 1976 to August 
1977. To minimize the errors inherent in sampling the heteroge- 
neously distributed phytoplankton, we took one large water sample 
from the surface to a depth of 30 cm at each station. Portions of the 
large sample were used for chemical analysis, primary productivity 
measurements, and phytoplankton cell counts. 



384 WELCH AND WARD 

Physicochemical Measurements 

Measurements of temperature, pH, water transparency, solar 
radiation, and alkalinity were made at each station on each sampling 
date. Nitrate nitrogen, orthophosphate, and dissolved oxygen mea- 
surements were made monthly. Water temperature at the incubation 
depth (0.5 m) was measured with a mercury centigrade thermometer; 
hydrogen ion concentration was measured with a pH meter in the 
laboratory; water transparency was measured with a Secchi disk; and 
instantaneous solar radiation in foot-candles was measured with a 
portable light meter. The instantaneous light readings were converted 
to total langleys for the sampling date by correlating the data with 
data from the Texas A & M University Meteorological Center. 
Phenolphthalein and methyl orange alkalinity were measured by 
titration with 0.02N sulfuric acid (American Public Health Associa- 
tion, 1971). Duplicate dissolved oxygen samples were fixed by the 
azide modification of the Winkler method (American Public Health 
Association, 1971). Nitrate nitrogen was measured by the ultraviolet 
spectrophotometric method, and orthophosphate was measured by 
the stannous chloride method using a benzene— isobutanol extraction 
(American Public Health Association, 1971). 

Biological Measurements 

Carbon-14 techniques were used to estimate primary produc- 
tivity, following the procedures of Goldman et al. (1974) and the 
liquid scintillation techniques of Schindler, Moore, and Vollenweider 
(1974). An ampul of 1 ml of NaHCOj with an activity of 5 fiCi was 
added to each 125-ml bottle, and the bottles were incubated for 2 hr 
between 10:00 a.m. and 2:00 p.m. Twelve hters of the large initial 
sample were poured through a plankton net of No. 20 nylon-mesh 
bolting cloth with 68 threads to the centimeter. The concentrate was 
centrifuged at 1500 x ^ in the laboratory, resuspended in a known 
volume, and counted according to the methods of Edmondson 
(1974). 

Ten nutrient-enrichment experiments were conducted to deter- 
mine the effect of two levels of nitrogen (NaNOg ) and phosphorus 
(K2HPO4) at the two temperature levels by use of a factorial design 
(Ramm and Karn, 1976; Jordan and Bender, 1973). Levels of 
nitrogen were and 0.025 mg/liter and of phosphorus, and 0.005 
mg/liter. 

Eight temperature -effects experiments were conducted by re- 
versing four bottles from each station and incubating the hot-water 
sample at Station 2 and the cool-water sample at Station 1. 



PRIMARY PRODUCTIVITY 385 

Statistical Measurements 

The data from each sampHng date were treated with analysis 
of vari£ince (ANOVA) to determine if there was a statistically signifi- 
cant effect of temperature or treatment (Snedecor £ind Cochran, 
1967). The data for the year were graphed as a regression of primary 
productivity on temperature. The graphs of data from both stations 
exhibited a curvilinear relationship. Two hnear components could be 
analyzed; however, by separating the data at 25°C and performing a 
least-squares hnear regression on each component. In the equation 
for the regression hne (Y = o: + j3X), a is height, where X = X, and j3 
is slope (Cohen and Cohen, 1975; Snedecor and Cochran, 1967). 

RESULTS 

Physicochemical Measurements 

The temperature range at Station 1 was 17 to 39°C, and the 
average temperature for the year was 27°C. At Station 2 the range 
was 10 to 34°C, and the average was 21.5°C. 

The difference in temperature (AT) between Stations 1 and 2 
was greater in the winter months. The largest AT (8°C) occuiTed in 
January, and the smallest (2°C) occurred three times, in October and 
November 1976 and June 1977. 

The pH ranged from 6.5 to 7.0 at Station 1 and 6.4 to 7.0 at 
Station 2 and was frequently the same at both stations. The seasonal 
variation was shght. 

The transparency of the water decreased during the fall and 
winter months and increased during the spring and summer, with the 
maximum occurring in August and the minimum in January. The 
range of the Secchi disk depth was 1.13 to 2.20 m. Although we 
attempted to sample on clear, cloudless days, daily variation in solar 
radiation was considerable, ranging from 530 to 120 langleys/day. 

Alkalinity, as CaCOs, varied from 89 to 120 mg/liter and was 
generally the same at both stations. Alkalinity was caused by 
bicarbonate since phenolphthalein alkahnity was never detected. 
Seasonal variation was slight. 

Nitrate nitrogen ranged from undetectable to 0.45 mg/liter. 
Orthophosphate was never detected by the method used. Dissolved 
oxygen was always over 90% saturation and often over 100% 
saturation at both stations. 



386 



WELCH AND WARD 



200 



150 



I 100 



O 
ca 
az 
< 



50 




V b & 



Sept. Oct. Nov. Dec. Jan. Feb. March April May June July Aug. 

MONTH 

Fig. 2 Seasonal variation of the surface-water primary produc- 
tivity. 



Biological Measurements 

On the basis of aneilysis of variaiice techniques, primary 
productivity was significantly higher at the discharge station on 18 of 
26 samphng dates (Fig.2). On five samphng dates there were no 
significant differences between stations in the amount of carbon 
fixed. On three sampling dates productivity was significantly higher 
at the unheated station. There was no apparent relationship between 
higher productivity and biomass or community composition between 
the two stations. At all times, dark-bottle fixation was ~10% of 
light-bottle fixation at both stations. 

The difference between the two stations in the amount of carbon 
fixed could be considered the difference in photosynthesis (AP). 
There was no correlation between the difference in temperature, AT, 
and the difference in carbon fixation, AP. 

Analysis of variance showed nutrient enrichment had no effect 
on primary productivity in any of the experiments. Experiments 
incubating hot-water samples at the ambient station and ambient- 
water samples at the heated station showed statistically significant 
effects of temperature in five of eight experiments (Fig. 3). Ambient- 
water samples incubated at increased temperatures showed increased 
productivity rates, and, conversely, samples from the discharge 



PRIMARY PRODUCTIVITY 



387 



100 



en 

E 



O 

< 




112 76 11-10-76 1-25-77 2-27-77 3-23-77 

SAMPLE DATE 



4-11-77 5-19-77 6-20-77 



Fig. 3 Carbon-14 fixation rates during temperature effect ex- 
periments. H — H, hot samples incubated at Station 1. H — C, hot 
samples at Station 2. C — C, cold samples at Station 2. C — H, cold 
samples at station l.t, 2 standard deviation. 



stations incubated at cooler temperatures showed lower rates of 
productivity. On Nov. 10, Feb. 27, and May 19, there was no 
significant difference between the primary productivity at Stations 1 
and 2 and no temperature effect when samples were reversed. 

Figures 4 and 5 are plots of the productivity as a function of 
temperature for Stations 1 and 2, respectively. Regression lines and 
equations are given for each component; r^ is a measure of variance 
in the data, and r is the Pearson product-moment correlation 
coefficient, a measure of how well the data fit the regression line or 
of the "scatter" in the data. On both figures the values at 25°C were 
included in the calculations for both components. 



DISCUSSION 

The rate of carbon fixation is affected by increased temperature, 
as evidenced by the ANOVA for 69% of the sampling dates. The 
maximum values in September and October for primary production 
rates could be associated with lake turnover and vertical mixing of 
nutrients into the epilimnion after disintegration of the thermocline, 
but this was not reflected in the chemistry of the water. This 
hypothesis is further supported by the concurrent decrease in 
transparency of the water during the fall of 1976. Texas lakes are 
generally monomictic, with mixing occurring during the cool months 
and stratification occurring during the warmer months. 



388 



WELCH AND WARD 



200 



150 



Y = 257.72 + (-6.08)25 
r2= 0.21 
r = 0.46 




25 30 

TEMPERATURE, °C 



Fig. 4 Carbon fixation as a function of temperature at Station 1. 



120 



100 — 



E 60 — 



194.92 + (-4.97)25 

0.45 

0.67 




20 25 

TEMPERATURE, °C 



Fig. 5 Carbon fixation as a function of temperature at Station 2. 



That temperature stimulates the rate of carbon fixation in Lewis 
Creek Reservoir is supported by the temperature-effect experiments. 
On dates when the data showed a significant effect of temperature 
on the rate of carbon fixation, it was significant to the 99% level, 
except on Nov. 2, when sampling error was such that the level of 
significance was only 90%. 

The results of the nutrient experiments could be caused by an 
insufficient nutrient spike or could be associated with nutrient 



PRIMARY PRODUCTIVITY 389 

uptake lag time. It is possible that a 2-hr incubation time is not 
sufficient to detect the effects of additions of a limiting nutrient. 

Biological processes are not often linear, and relationships are not 
generally continuous. Regression analysis assumes that the under- 
lying relationships between variables are linear and additive. In 
attempting to analyze the data, however, we found it more expedient 
to divide the data from each station at 25°C and compute the linear 
regression equation and measures of correlation before using more 
compHcated methods. The objectives were, not to develop a model 
for phytoplankton productivity, but to explain and predict the 
functioning of the phytoplankton community as it relates to 
temperature. 

The rate of carbon fixation tends to increase jS units with every 
degree of increase in temperature up to 25° C and to decrease —(i 
units with every degree of increase in temperature above 25°C; i.e., it 
appears that the temperature optimum for the natural 
phytoplankton community in Lewis Creek Reservoir lies in the 
vicinity of 25°C, and temperatures in excess of that tend to suppress 
the rate of carbon fixation. 

By setting Y equal to 0, we can estimate a temperature tolerance 
range below and above which productivity is suppressed entirely. For 
Station 1 the estimated temperature tolerance range is 10 to 42°C 
and for Station 2, 5 to 39° C. This assumption excludes the 
possibility of a complete change in community structure. It is 
interesting to note that the estimated temperature tolerance ranges 
are not the same and that the estimate for the community subjected 
to consistently higher temperatures at Station 1 is higher. This 
suggests that organisms at Station 1 are adapted to higher tempera- 
tures. 

The proportion of variance explained by temperature, r^ , is 
larger at Station 2; i.e., 51% of the variance at Station 2 between 10 
and 25°C is explained by temperature and only 13% is explained at 
Station 1. Thus other factors at Station 1 contribute to the 
variability of rates of carbon fixation. One possibility is stress to the 
organism caused by passage through the condensers (Lanza and 
Cairns, 1972; Gurtz and Weiss, 1974). 

Our work centered only on the phytoplankton of Lewis Creek 
Reservoir. It became obvious soon after this study commenced that, 
throughout much of the year, the system is dominated by a large 
population of benthic algae. Detailed studies on the effects of 
temperature on benthic productivity and biomass accumulation 
would be of considerable interest. 



390 WELCH AND WARD 

ACKNOWLEDGMENT 

We want to express our appreciation to the Gulf States Utilities 
Company for its cooperation and support in the conduct of this 
study. 

REFERENCES 



American Public Health Association, 1971, Standard Methods for the Examina- 
tion of Water and Wastewater, 13th ed., Washington, D. C. 

Castenholz, R. W., and C. E. Wickstrom, 197 5, Thermal Streams, in River 
Ecology, B. A. Whitton (Ed.), University of California Press, Berkeley. 

Cohen, J., and P. Cohen, 1975, Applied Multiple Regression: Correlation 
Analysis for the Behavioral Sciences, John Wiley & Sons, Inc., New York. 

Edmondson, W. T., 1974, A Simplified Method for Counting Phytoplankton, in 
A Manual on Methods for Measuring Primary Production in Aquatic 
Environments, R. A. Vollenweider (Ed.), International Biological Program 
Handbook 12, Blackwell Scientific Publications, Oxford. 

Foerster, J. W., F. R. Trainor, and J. D. Buck, 1974, Thermal Effects on 
Connecticut River: Phycology and Chemistry, J. Water Pollut. Control Fed., 
46: 2138-2152. 

Fogg, G. E., 1975, Algal Cultures and Phytoplankton Ecology, 2nd ed., 
University of Wisconsin Press, Madison. 

Goldman, C. R., E. Steeman-Nielson, R. A. Vollenweider, and R. G. Wetzel, 
1974, in A Manual on Methods for Measuring Primary Production in Aquatic 
Environments, R. A. Vollenweider (Ed.), International Biological Program 
Handbook 12, Blackwell Scientific Publications, Oxford. 

Gurtz, M. E., and C. M. Weiss, 1974, Effect of Thermal Stress on Phytoplankton 
Productivity in Condenser Cooling Water, in Thermal Ecology, AEC 
Symposium Series, Augusta, Ga., May 3—5, 1973, J. W. Gibbons and R. R. 
Sharitz (Eds.), pp. 490-507, CONF-730505, NTIS. 

Jordan, R. A., and M. E. Bender, 1973, An In Situ Evaluation of Nutrient 
Effects in Lakes, Report EPA-Re-73-018, Environmental Protection Agency, 
Washington, D. C. 

Lanza, G. R., and J. Cairns, Jr., 1972, Physio-Morphological Effects of Abrupt 
Thermal Stress on Diatoms, Trans. Am. Microsc. Soc, 91: 276-298. 

Marshall, J. S., and L. J. Tilly, 1971, Temperature Effects on Phytoplankton 
Productivity in a Reactor Cooling Pond, in Radionuclides in Ecosystems, 
Proceedings of the Third National Symposium on Radioecology, Oak Ridge, 
Tenn., May 10-12, 1971, D. J. Nelson (Ed.), USAEC Report CONF- 
710501-Pl, pp. 645-651, Oak Ridge National Laboratory, NTIS. 

Patrick, R., 1969, Some Effects of Temperature in Freshwater Algae, in 
Biological Aspects of Thermal Pollution, P. A. Krenkel and F. L. Parker 
(Eds.), Proceedings of National Symposium on Thermal Pollution, Vander- 
bilt University Press, Nashville, Tenn. 

Ramm, A. E., and B. P. Karn, 1976, A Note on the Design of Nutrient 
Enrichment Studies, J. Water Pollut. Control Fed., 48: 2211-2212. 

Schindler, D. W., J. Moore, and R. A. Vollenweider, 1974, Liquid Scintillation 
Techniques, in A Manual on Methods for Measuring Primary Production in 



PRIMARY PRODUCTIVITY 39I 

Aquatic Environments. R. A. Vollenweider (Ed.), International Biological 

Program Handbook 12, Blackwell Scientific Publications, Oxford. 
Simmons, G. M., and B. J. Armitage, 1974, Evaluation of Heated Water 

Discharge on Phytoplankton Blooms in the Potomac River, Hydrohiologia, 

45: 441-465. 
Snedecor, G. W., and W. G. Cochran, 1967, Statistical Methods, 6th ed., Iowa 

State University Press, Ames. 
Sorokin, C, and J. Myers, 1953, A High Temperature Strain of Chlorella, 

Science, 117: 330-331. 
Tilly, L|. J., 1973, Comparative Productivity of Four Carolina Lakes, Am. Midi. 

Nat., 90: 356-365. 
, 1974, Periphyton Colonization and Productivity in the Reactor Cooling 

Reservoir — Par Pond, paper presented at the 35th Annual Meeting of the 

Association of Southeastern Biologists, Savannah, Ga., April 18—20, 1974. 
, 1975, Periphyton Crops and Productivity in a Reactor Thermal Effluent, 

paper presented at the 38th Annual Meeting of the American Society of 

Limnology' and Oceanography, Halifax, Nova Scotia, June 23 — 26, 1975. 
Warinner, J. E., and M. L. Brehmer, 1966, The Effects of Thermal Effluents on 

Marine Organisms, /n^ J. Air Water Pollut., 10: 277-289. 



NITRATE REDUCTASE ACTIVITY 
AND PRIMARY PRODUCTIVITY 
OF PHYTOPLANKTON ENTRAINED 
THROUGH A NUCLEAR POWER STATION 
ON NORTHEASTERN LONG ISLAND SOUND 



BRADFORD B. PECK* and R. SCOTT WARREN 

Department of Botany, Connecticut College, New London, Connecticut 



ABSTRACT 

The effects of temperature and various concentrations of chlorine on nitrate 
reductase activity and primary productivity of phytoplankton were studied at 
the Millstone Nuclear Power Station on northeastern Long Island Sound. During 
August the ambient temperature at the cooling water intake ranged from 19.5 to 
20 C. Power generation during this period resulted in temperature increases of 
11 and 14 C at the discharge and depressed phytoplanktonic nitrate reductase 
activity by 88 to 89% and phytoplanktonic primary productivity by 42 to 52%. 
The decrease occurred during the 6- to 9-hr transit through the cooling pond. 
Nitrate reductase activity, maximally depressed after exposure to a mean 
increase of 13 C above ambient temperature on seven days in August, did not 
recover to intake control levels after 24 hr of incubation at ambient intake 
temperature. In March and April, when the ambient temperature of Long Island 
Sound water was 4.3 to 9.9 C, phytoplanktonic nitrate reductase activity was 
stimulated 25% above that of controls after 6 to 9 hr of exposure at 11.5 to 
18.1 C above ambient temperature. The productivity results are similar to 
previous unpublished findings on temperature influence at this site. The nitrate 
reductase activity findings support the hypothesis that nitrate reductase is a 
heat-labile enzyme. Chlorine concentrations below and above those required to 
eliminate fouling organisms (0.50 ppm) produced large decreases in the 
photosynthetic rate of entrained phytoplankton. Previous work at this site 
reported similar findings. Nitrate reductase activity decreased 15% at 1.0 ppm 
and 1.2 ppm, the two highest chlorine dosages applied. 



♦Present address: Peaks Island, Maine. 

392 



NITRATE REDUCTASE ACTIVITY 393 

The effects of various levels of temperature and chlorine in the 
cooling water entrained through the Millstone Nuclear Power Plant 
on nitrate reductase activity and primary productivity of the natural 
phytoplankton population were tested. 

Nitrate reductase catalyzes the reduction of nitrate to nitrite: 

NO7 + 2H^ + 2e~ ^ NO7 + H2O 

The initial reduction of nitrate is the rate-limiting step in the 
assimilation of nitrate (Beevers and Hageman, 1969). The nitrite 
produced is further reduced to ammonia by nitrite reductase and is 
assimilated by glutamic dehydrogenase to produce glutamic acid, the 
nitrogen source for other amino acids. 

Nitrate reductase is light and heat labile and is relatively unstable 
in vivo and in vitro (Beevers and Hageman, 1969; Schrader et al., 
1968). Eppley, Packard, and Maclsaac (1970) and Packard et al. 
(1971) reported an optimum temperature of around 15°C for the 
nitrate reductase activity of a natural population of marine phyto- 
plankton in the Peru current. There is evidence that a large and 
sudden rise in temperature lowers nitrate reductase activity of 
Hordeum vulgare L. (barley) (Travis, Jordan, and Huffaker, 1969). 

Electric-power generating plants usually entrain large volumes of 
water for cooling purposes and discharge heated effluents that 
exceed maximum ambient temperatures. The nitrate reductase 
activity of entrained phytoplankton may be affected by thermal or 
chlorination stresses during passage through power-plant condensers. 

Briand (1975) attributed large reductions in phytoplankton 
bio mass to the magnitude of increases above ambient temperature at 
two southern California coastal power plants. Carpenter, Peck, and 
Anderson (1972), reported substantial phytoplankton productivity 
losses at the Millstone plant at all levels of continuous and 
intermittent chlorination, but the effects of temperature shock on 
nitrate reductase activity and productivity were not studied. If the 
level of phytoplanktonic nitrate reductase is influenced by photo- 
synthetic rate, then chlorination could mask any temperature effects 
on this enzyme. To determine the effects of temperature increase 
resulting from power-station generation, we measured nitrate reduc- 
tase activity and primary productivity over an annual cycle of 
temperature fluctuations from January 1973 through January 1974. 
Coordinating sampling wdth plant operations allowed us to monitor 
nitrate reductase and primary productivity over a range of tempera- 
tures and at chlorination levels of 0.0 to 1.2 ppm [the highest dosage 
studied by Carpenter, Peck, and Anderson (1972)] . 



394 



PECK AND WARREN 



41 "20' 



72"10' 




INTAKE 

DISCHARGE 




CUT- 



1 2 3 
_J I I 

Nautical miles 



2 4 

I \ I  I 

km 



72 10' 

Fig. 1 Map of study area, Long Island Sound, showing nuclear 
power plant. 



MATERIALS AND METHODS 



Study Area 

The Millstone Nuclear Power Station, Unit I, located on 
northeastern Long Island Sound (Fig. 1), entrains 9.5 x 10"^ m'Vhr 
(3.2 X 10^ ftVhr) of seawater (salinity 28 to 30%o) for cooling 
from Niantic Bay at a depth of ^3 m. The AT from intake to 
discharge is 13°C when the plant is operating at a capacity of 650 
MW(e). The water passes through the plant in about 2 min, is 
discharged into an effluent pond, and then enters Long Island Sound 
via a cut. 

The fjord-shaped effluent pond, which was formerly a granite 
quarry, has a volume of 850,000 m^, a maximum depth of ^30 m, 
and a minimum depth at the shallow sill, the cut where entrained 
water enters Long Island Sound, of ~3 m. When the plant is 
operating, water in the effluent pond is both isothermal and 
isohaline. Mean residence time of water in the pond is 6 to 9 hr. 
Measurements with a surface float show that surface flow from 
discharge to cut through the effluent pond occurs in ~1.5 hr to a 
depth of 1 m. The surface-to-volume ratio of the pond is small, and 



NITRATE REDUCTASE ACTIVITY 395 

water cools by only about 0.5 to 1.0° C in passage through the pond 
to the end of the cut. 

Sampling 

Sampling was conducted to assure, as much as possible, that the 
same water masses (intake, discharge, and cut) were sampled from 
each station. All samples were collected around noon because 
maximum solar radiation occurred near noon, and maximum nitrate 
reductase activities have been reported about noon. Commencement 
of sampling deviated by a maximum of 30 min before or after noon 
during the entire study period. Twelve casts were made to a depth of 
1 m with a 1-liter Kemmerer sampler at the intake, discharge, and cut 
(Fig. 1). Intake samples were the controls. Discharge samples were 
collected within 15 min after collection of intake samples. Cut 
samples were collected no more than 1.5 hr after collection of 
discharge samples. 

All treatments, with and without temperature and chlorine 
additions, were randomized and replicated throughout the 1-year 
study, and samples discussed here represent trends observed. Samples 
were collected five times monthly from April through September 
1973, three times in October 1973, twice monthly in February, 
March, and November 1973, once monthly in January and December 
1973, and once in January 1974. On several occasions samples were 
collected from three depths in the middle of the effluent pond (1, 
15, and 30 m) to determine nitrate reductase activity and primary 
productivity in the water column of the pond. Also at each station 
(intake, discharge, and cut) salinity and temperature were measured 
with an induction salinometer. Percent surface illumination at each 
depth was calculated according to Holmes (1970) from Secchi disk 
lowerings and was validated by a submarine photometer. 

Chlorine 

Chlorine was added at the plant intake at rates of 95 to 1100 
g/hr to give 0.1 to 1.2 ppm chlorine. Free residual chlorine was 
measured with an orf/io-tolidine chlorometric method at a 1-m depth 
at intake, discharge, and cut. This method is not sensitive enough to 
measure residual chlorine below 0.05 ppm. 

Nitrate reductase activity and primary productivity were mea- 
sured at various levels of continuous chlorine applications ranging 
from 0.0 to 1.2 ppm. Continuous chlorination was begun at least 12 
hr before measurements were made. Samples without chlorination 
were taken no less than 12 hr after chlorine applications ceased. This 



396 PECK AND WARREN 

assured flushing of the effluent pond so that only the chlorine 
concentration to be tested for a particular treatment was present. 

Nitrate Reductase 

Nitrate reductase was measured by a biochemical assay modified 
from that of Eppley, Coats worth, and Solorzano (1969). Ten liters 
of seawater from each station were placed in a 5-gal green Nalgene 
(Nalge Co.) bottle and kept at ambient temperature in a seawater 
bath until the enzyme assay could be run, usually within 3 hr of 
sample collection. Nitrate reductase activity is expressed as micro- 
gram atoms of NO2 formed per hter per hour and per cell per 
hour. Nitrite produced was determined on a colorimeter by the 
absorption at 550 nm after addition of sulfanilamide and 
Ar-(l-naphthyl)ethylenediamine dihydrochloride solutions (Strickland 

and Parsons, 1968). Nitrite standards ranging from 1 to 8 )Ug 
atoms /liter were determined in the same way. 

Total Protein 

Protein was determined by the method of Lowry et al. (1951). 

Primary Productivity 

Primary productivity was measured with the light— dark bottle 
'"^C method of Steeman-Nielson (1952). For each sample station 
500 ml of the 12 liters of water collected was used to fill four (three 
light and one dark) 125-ml Pyrex bottles. To each bottle was added 
0.7 juCi of NaH' '^C03. At each station the four bottles were shaken, 
separately attached to curtain hooks, and lowered into the water to a 
depth of 1 m for 4 hr of incubation in situ. After incubation the 
contents of each bottle were filtered with suction onto glass-fiber 
filters, which were then suspended in 20-ml vials containing Bray's 
fluor and counted for 20 min on a liquid scintillation counter (Bray, 
1960). Total carbon per cubic meter was determined from tempera- 
ture—salinity data and the tables of Strickland and Parsons (1968). 
Percent productivity for discharge and cut, relative to intake 
productivity, was calculated from milligrams of carbon fixed per 
cubic meter per hour. 

Phytoplankton Cell Concentration 

Subsamples of phytoplankton (100 ml) from the pooled 12 liters 
of water collected at each station were preserved in Lugol's solution 
in 100-ml bottles (Lund, Kipling, and Lecren, 1958). After concen- 



NITRATE REDUCTASE ACTIVITY 397 

tration by centrifugation, cells were counted by the Sedgewick— 
Rafter strip-count method (Jackson and Williams, 1962). Usually 
about 500 cells/ml were counted. 

Wutrient Concentration in Seawater 

Subsamples (100 ml) from the pooled 12 liters of water collected 
at each station were frozen for later nutrient analysis. The nitrite 
concentration of the water was determined by the diazotization— 
couphng reaction; the nitrate was reduced to nitrite and determined 
by passage through a copperized cadmium column (Strickland and 
Parsons, 1968); and ammonium was determined by the alkaline 
hypochlorite method of Solorzano (1969). 

RESULTS 

Phytoplankton Population 

Phytoplankton cell concentrations did not vary greatly from 
intake to cut over the 1-year sampling period. Two blooms occurred, 
one in the spring, peaking at about 2 x 10^ cells/liter, and one in 
midsummer, peaking at about 3.8 x 10^ cells/liter (Fig. 2). 

Of the fifteen different genera identified, the majority are 
diatoms, Skeletonema costatum, Thalassiosim nordenskioldii, Asteri- 
onella japonica, Chaetoceros sp., Thalassionema nitzschoides, and 
Rhizosolenia fragillissima. Other dominants include the flagellates 
Rhodomonas minuta and Rhodomonas amphioxeia and the dino- 
flagellates Dinophysis sp., Peridinium sp., and Prorocentrum sp. 
These genera were entrained through the plant from January 1973 to 
January 1974. The same species were found to be abundant in Long 
Island Sound by Conover (1956), in Block Island Sound by Riley 
(1952), and in the Niantic Bay estuary by Marshall and Wheeler 
(1965). 

Chlorination, Primary Productivity, and Nitrate Reductase Activity 

When there was no chlorine application during a study period, 
primary productivity was unaffected by entrainment (Table 1). 
Chlorination at every concentration used in this study reduced 
primary productivity. Continuous chlorine application at the highest 
dosage (1.2 ppm) reduced productivity by 89% at the discharge and 
84% at the cut, as compared with intake water productivity. Free 
residual chlorine concentrations at the discharge ranged from 0.4 
ppm at the highest chlorine application (1.2 ppm) to below 
measurable amounts at addition rates of 0.4 ppm and less. No 



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PECK AND WARREN 




JAN. FEB. MAR. APR. MAY JUNE JULY AUG. SEPT. OCT. NOV. DEC. 

1973 



JAN. 
1974 



Fig. 2 Intake and cut phytoplankton cell concentrations from 
January 1973 to January 1974. 



measurable residual chlorine was detected at the cut for any of the 
chlorine doses tested. At the lowest dosage (0.1 ppm), the 
productivity dechned 65% at discharge and 84% at the cut. Thus a 
chlorine dosage smaller by over an order of magnitude yielded 
essentially the same effect as the highest dosage. 

Nitrate reductase activity declined only at the two highest 
chlorine dosages. A 1.2-ppm chlorine application reduced nitrate 
reductase activity 47% in the discharge effluent and 14% at the cut, 



NITRATE REDUCTASE ACTIVITY 401 

as compared with intake levels. A 1.0-ppm chlorine application 
reduced nitrate reductase activity 26% at the discharge and 15% at 
the cut. 



Temperature, Ammonium, Primary Productivity, 
and Nitrate Reductase Activity 

Generally, temperature increases above 9°C resulting from 
power-station generation depressed productivity at the discharge and 
cut relative to that at the intake (Table 2). Percent nitrate reductase 
activity per cell per hour at the cut was stimulated after 6 to 9 hr of 
exposure to temperatures increasing to 17° C through the pond and 
to the cut, but, when temperatures exceeded 25° C, activity was 
greatly depressed. The power plant was not chlorinating on any of 
these sampling dates. Ambient nitrate, nitrite, and ammonium 
concentrations remained essentially the same after passage through 
the power plant. 

Figure 3 compares nitrate reductase activity at the plant intake 
with that at the cut for random sampling dates from January 1973 to 
January 1974. Figures 4 and 5 show changes in temperature and 
ammonium concentrations during this time. During March and April 
activity at the cut was stimulated above ambient nitrate reductase 
activity at the intake. Intake temperatures ranged from 4.3 to 9.9°C 
during this time, and cut temperatures were 11.5 to 18.1°C. From 
August through January 1974, nitrate reductase activity at the cut 
dropped sharply below that at the intake. Intake temperatures during 
this interval ranged from 22 to 6.4° C, and cut temperatures ranged 
from 34 to 17.9°C. From September through January 1974, 
ammonium concentrations at the cut were highest, ranging from 8 to 
14 /ig atoms/liter. Therefore, the depression of nitrate reductase 
activity at the cut in August 1973 appears to be caused by 
temperature increases resulting from station generation, and that 
from September through January 1974 is caused by increases in 
ammonium concentration. 

On seven dates in August 1973, the recovery of nitrate reductase 
activity after heating was tested by use of 10 liters of seawater, 
sampled from a depth of 1 m at each station (intake, discharge, and 
cut), at the ambient intake temperature. The water was held in 
dialysis tubing for periods of 1, 4, and 24 hr, and a nitrate reductase 
assay was run after each incubation period. The nitrate reductase 
activity of these samples, depressed at the cut after transit through 
the quarry at a temperature range of 30 to 34°C, did not recover to 
intake levels after 24 hr of incubation at ambient intake temperature. 



402 



PECK AND WARREN 



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1973 1974 

Fig. 3 Nitrate reductase activity at power-plant intake and at the 
cut on various sampling dates from January 1973 to January 1974. 
The power plant was not generating from the end of April to the 
beginning of August 1973. 



DISCUSSIOIM 



Our data suggest that there is no immediate decrease in 
phytoplankton population as a result of mechanical stresses of 
entrainment through the power plant. There are indications that 
phytoplankton are destroyed during passage through power-plant 
cooling systems, however. Briand (1975) reported large reductions in 
phytoplankton numbers and volumes at two southern California 
coastal power plants. Morgan and Stross (1969) and Hamilton et al. 
(1970) noted large decreases in the chlorophyll a content of cells 
concomitant v^th decreased primary productivity after entrainment 
with chlorination. Residual chlorine concentrations of 1.5 to 2.3 
ppm killed Skeletonema costatum in laboratory cultures, and 
sublethal chlorine concentrations adversely affected growth (Hira- 
yama and Hirano, 1970). 



NITRATE REDUCTASE ACTIVITY 



405 




JAN. FEB. MAR. APR. MAY JUNE JULY AUG. SEPT, OCT. NOV. DEC. 

1973 



JAN. 
1974 



Fig. 4 Temperatxire at power-plant intake and at the cut on various 
sampling dates from January 1973 to January 1974. When the 
curves are the same, the plant was not operating. 



406 



PECK AND WARREN 



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JAN. FEB. MAR. APR. MAY JUNE JULY AUG. SEPT. OCT. NOV. DEC. 

1973 



JAN. 
1974 



Fig. 5 Ammonium concentrations at power-plant intake and at the 
cut on various sampling dates from January 1973 to January 1974. 



Our results indicate that photosynthesis is more sensitive to 
chlorination than is nitrate reductase activity. Either a real difference 
between photosynthesis and nitrogen assimilation occurs, or nitrate 
reductase activity measures an effect on the level of an enzyme, 
whereas productivity measures an activity. Recovery of the nitrate 
reductase enzyme at the cut after depression at the discharge by the 
two highest chlorine dosages is consistent with a fairly rapid turnover 
rate for the enzyme and may indicate that chlorine does not have 
any long-term effects on the ability of phytoplankton to synthesize 
nitrate reductase. Further recovery of nitrate reductase activity may 
taJ^e place after exposure to ocean water with no added chlorine. 

It appears that nitrate reductase activity is stimulated in transit 
through the pond during 6 to 9 hr of exposure to temperatures 
increasing to ~18°C, such as occurred in March and April. At some 
temperature between 18°C, occurring at the cut in the spring, and 
27° C, occurring at the cut in the fall, there is a shift from stimulation 
to inhibition of nitrate reductase. For example, on Mar. 30, when the 
temperature at the cut was 17.4° C, nitrate reductase activity at the 
cut increased 25.9% above intake activity, but on Aug. 2, when the 
temperature was 31. 3° C, activity decreased 88%. Nitrate reductase 
activity never decreased after a 2-min exposure to temperature 
increases during passage through the plant but was affected after 
transit through the pond and exposure for 6 to 9 hr to a change in 



NITRATE REDUCTASE ACTIVITY 407 

temperature. The assay used measures the amount of enzyme present 
not its in vivo activity. The temperature shock of August through 
October is, therefore, either inactivating the enzyme already present 
or slowing or stopping the synthesis of the enzyme. This could be 
either a generalized effect on all protein or a specific effect for 
nitrate reductase. 

Nitrate reductase is an inducible enzyme, and, in an inducible 
enzyme system, temperature can influence enzyme synthesis (Lang- 
ridge and McWilliam, 1967). In some instances this effect may be 
the result of a progressive loss of the response of the control system 
to the inducer. Thus the temperature-related decrease in phytoplank- 
ton nitrate reductase activity observed at the cut in August could be 
the result of high-temperature impairment of the system controlling 
production of the enzyme. 

In December 1973 and January 1974, ammonium concentrations 
were high and nitrate reductase activities were undetectable at the 
cut (Figs. 3 and 5). Also, as can be seen in Figs. 3 to 5, high 
ammonium concentrations at the cut during two sampling dates in 
the middle of September were accompanied by low nitrate reductase 
activities (0 [ig atoms NOT" cell"' hr~' ) even though the intake and 
cut temperatures were the same (18°C) because the plant was not 
operating. Eppley, Coatsworth, and Solorzano (1969) found that 
ammonium concentrations in the range of 5 to 15 ^Lig atoms /liter 
inhibited nitrate reductase activity in sainples of tropical Pacific 
phytoplankton. Therefore, from September through January, 
ammonium concentration appears to be responsible for nitrate 
reductase depression at the cut, whereas in August depression is 
probably caused by temperature. 

To determine the correlation among nitrate reductase activity, 
temperature, and ammonium statistically, we used a stepwise 
regression analysis (the May 2, 1966, version of the Health Sciences 
Computing Facility, UCLA at Connecticut College). Temperature 
and nitrate reductase activity and ammonium and nitrate reductase 
activity are significantly correlated. 

Ammonium concentrations exceeding 8 /^g atoms/liter observed 
at the cut from September through January could be the result of 
increased copepod excretion or decay in the depths of the effluent 
pond. Carpenter, Peck, and Anderson (1974), working at this same 
site, reported that live copepods sink relatively rapidly after passing 
through the power plant. They found a large number (54 to 63%) 
of dead copepods in the deep water of the effluent pond, in contrast 
to a few dead (6 to 13%) at the surface. Conditions in the effluent 
pond itself are not responsible for copepod mortality. Mortality is 



408 PECK AND WARREN 

apparently related to the mechanical effects of passage through the 
power plant. 

The failure of the heat-depressed cut samples to recover any 
nitrate reductase activity after 24 hr of incubation suggests that the 
ability of this phytoplankton population to synthesize nitrate 
reductase after heat shock was seriously altered. During incubation at 
intake temperatures, cells were contained within dialysis tubing, and 
it is possible that this containment influenced the nitrate reductase 
activity of the cells. Ammonium concentrations in August did not 
exceed 5 [ig atoms/liter. However, the complicating effect of 
ammonium on changes in the nitrate reductase activity of contained 
cells must be recognized when interpreting any failure of nitrate 
reductase activity to recover. Vargo, Hargraves, and Johnson (1975) 
reported that detrital deposition and epiphytic growth on dialysis 
membranes at summer temperatures may decrease the membrane 
area available for nutrient flux in less than 3 days. This would tend 
to decrease the nitrate reductase present by limiting the nitrate 
entering the dialysis membrane. In our study this was not the case. 
Intake controls held at ambient intake temperature for 24 hr show 
no change in nitrate reductase activity. 

ACKNOWLEDGMENTS 

We thank E. J. Carpenter of the Marine Sciences Research 
Center, State University of New York, Stony Brook, Long Island, 
and Ian Morris and T. T. Packard of the Bigelow Laboratory for 
Ocean Sciences, West Boothbay Harbor, Me., for their comments on 
the original manuscript. Gratitude is also expressed to Jerry Lamb of 
the Naval Underwater Systems Center, New London, Conn., for 
statistical advice. 

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Annu. Rev. Plant Physiol., 20: 495-522. 
Bray, G. A., 1960, A Simple Efficient Liquid Scintillator for Counting Aqueous 

Solutions in a Liquid Scintillation Counter, Ana/. Biochem., 1: 279-285. 
Briand, F. J. -P., 1975, Effects of Power Plant Cooling Systems on Marine 

Phytoplankton, Mar. Biol, 33: 135-146. 
Carpenter, E. J., B. B. Peck, and S. J. Anderson, 1972, Cooling Water 

Chlorination and Productivity of Entrained Phytoplankton, Mar. Biol., 16: 

37-40. 
, B. B. Peck, and S. J. Anderson, 1974, Survival of Copepods Passing 

Through a Nuclear Power Station on Northeastern Long Island Sound, USA, 

Mar. Biol., 24: 49-55. 



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Conover, S. A. M., 1956, Oceanography of Long Island Sound, 1952—1954. 

IV. Phytoplankton, Bu//. Bingham Oceanogr. Collect., 15: 62-111. 
Eppley, R. W., J. L. Coatsworth, and L. Solorzano, 1969, Studies of Nitrate 

Reductase in Marine Phytoplankton, Limnol. Oceanogr., 14(1): 194-205. 
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Phytoplankton, Mar. Biol, 6(3): 195-199. 
Hamilton, D. H., Jr., D. A. Flemer, C. W. Keefe, and J. A. Mihursky, 1970, 

Power Plants: Effects of Chlorination on Estuarine Primary Production, 

Science, 169: 197-198. 
Hirayama, K., and R. Hirano, 1970, Influences of High Temperature and 

Residual Chlorine on Marine Phytoplankton, Mar. Biol., 7: 205-213. 
Holmes, R. W., 1970, The Secchi Disk in Turbid Coastal Waters, Limnol. 

Oceanogr., 15(2): 688-694. 
Jackson, H. W., and L. G. Williams, 1962, Calibration and Use of Certain 

Plankton Counting Equipment, Trans. Am. Microsc. Soc, 81(1): 96-103. 
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Lowry, H. O., N. J. Rosebrough, A. L. Farr, and R. J. Randall, 1951, Protein 

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Method of Estimating Algal Numbers and the Statistical Basis of Estimations 

by Counting, Hydro b/o/ogy, 11: 143-170. 
Marshall, N., and B. M. Wheeler, 1965, Role of the Coastal and Upper Estuarine 

Waters Contributing Phytoplankton to the Shoals of the Niantic Estuary, 

Ecology, 46: 665-673. 
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Cooling Water Supply of a Steam Electric Station, Chesapeake Sci., 10: 

165-171. 
Packard, T. T., D. Blasco, J. J. Maclsaac, and R. C. Dugdale, 1971, Variations of 

Nitrate Reductase Activity in Marine Phytoplankton, Invest. Pesq., 35(1): 

209-219. 
Riley, G. A., 1952, Phytoplankton of Block Island Sound, 1949, Bull. Bingham 

Oceanogr. Collect., 13: 40-64. 
Schrader, L. E., G. L. Ritenour, G. L. Eilrich, and R. H. Hageman, 1968, Some 

Characteristics of Nitrate Reductase from Higher Plants, Plant Physiol., 43: 

930-940. 
Solorzano, L., 1969, Determination of Ammonia in Natural Waters by the 

Phenolhypochlorite Method, L/mno/. Oceanogr., 14(5): 799-801. 
Steeman-Nielson, E., 1952, Use of Radioactive (C*^) for Measuring Organic 

Production in the Sea, J. Cons. Int. Explor. Mer, 23: 178-198. 
Strickland, J. D. A., and T. R. Parsons, 1968, A Manual of Seawater Analysis, 

Bulletin 167, Fisheries Research Board of Canada, Ottawa, Ont. 
Travis, R. L., W. R. Jordan, and R. C. Huffaker, 1969, Evidence for an 

Inactivating System of Nitrate Reductase in Hordeum uulgare L. During 

Darkness That Requires Protein Synthesis, P/an^ Physiol., 44: 1150-1156. 
Vargo, G. A., P. E. Hargraves, and P. Johnson, 1975, Scanning Electron 

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113-120. 



GROWTH OF DUCKWEED 

UNDER CONSTANT AND VARIABLE 

TEMPERATURES 



REBECCA R. SHARITZ and JEFFREY C. LUVALL 
Savannah River Ecology Laboratory, Aiken, South Carolina 



ABSTRACT 

Effects of variable temperatures on the growth and vegetative reproduction of an 
aquatic plant were examined by exposing populations of Spirodela oligorrhiza to 
cyclic, acyclic, and constant temperature regimes. Growth rates under the cyclic 
and acyclic regimes (each of which ranged from 10 to 25 C) were not 
significantly different from those at a constant temperature equal to the mean of 
the range (17.5 C). Population growth was directly related to temperature in 
both constant and variable thermal regimes. 



Laboratory studies of effects on organisms of increases in tempera- 
ture have commonly been based on exposure to constant tempera- 
ture regimes. Such studies do not reflect conditions generally existing 
in nature, and data on life-history phenomena of organisms at 
constant temperatures may be misleading if extrapolated to field 
conditions (Hagstrum and Hagstrum, 1970). Many freshwater organ- 
isms are confined to shallow-water habitats and exposed to both 
diurnal and seasonal fluctuations in temperature. 

The significance of cyclic and recurring temperatures on growth 
and development in a variety of organisms has been demonstrated. 
For example, a diurnal thermoperiodicity with night temperatures 4 
to 8°C lower than day temperatures enhances the growth of 
sporelings and fronds of Porphyra (Shimo, 1977). Insects frequently 
have been shown to develop more rapidly under fluctuating 
temperatures than constant temperatures if the range of fluctuation 
falls within the optimal range for the organisms' development 
(Hagstrum and Hagstrum, 1970). Heath (1963) reported that 
maximum tolerance to temperature extremes in the sea-run cutthroat 

410 



GROWTH OF DUCKWEED 411 

trout (Salmo clarki clarki) occurred under a 24-hr temperature cycle 
rather than shorter or longer cycles. He suggested that most fish 
respond to the extremes rather than the mean of the temperature 
cycle. Heath also summarized several studies indicating that certain 
organisms have higher thermal tolerances under cyclic than under 
continuous exposure to high temperatures. Such other processes as 
larval development in the mud crab, Rhithropanopeus harrisii 
(Costlow and Bookhout, 1971; Christiansen and Costlow, 1975), and 
byssal thread formation by Modiolus demissus (Van Winkle, 1969) 
apparently respond to cyclic temperatures in a mainner similar to that 
of a constant temperature equal to the mean of the cycle. 

In addition to constant temperatures and cyclic fluctuations, 
many organisms must contend with randomly varying temperatures 
or with thermal regimes in which the temperature change is 
much less predictable. This circumstance is becoming more 
common as many industrial facilities and power plants release heated 
water into streams and lakes. Even though effluent temperatures may 
not exceed the tolerance levels of the organisms, the thermal regimes 
may change frequently in unpredictable ways. 

A few studies of growth and development in aquatic animals 
under fluctuating temperatures are available (e.g., Grainger, 1959; 
Thorp and Wineriter, 1978) but the effects of irregularly changing 
temperatures have received little attention. This study compares the 
effects of three types of thermal regimes (constant, cyclic, and 
acyclic or randomly fluctuating) on survivorship and growth of an 
aquatic plant. 

METHODS 

A common species of duckweed, Spirodela oligorrhiza (Kurz) 
Hegelm, was chosen for study because of its abundance in south- 
eastern aquatic habitats, because of its ease of manipulation in 
experimental systems (Clatworthy and Harper, 1962; Hodgson, 
1970), and because of the large body of literature on growth, 
metabolism, and flowering in the Lemnaceae, as summarized by 
Hodgson (1970) and Hillman (1976). Populations of S. oligorrhiza 
were collected from five separate locations at the U. S. Department 
of Energy's Savannah River Plant in South Carolina. These were (1) a 
beaver pond along a creek that had received cooling water from 
nuclear reactor operations 9 years previously, (2) a sewage-effluent 
pond, (3) a roadside ditch, (4) a pond receiving chemical effluent, 
and (5) a ponded area along a natural stream. Spirodela oligorrhiza 
plants from each of these sites were grown under similar conditions 
in the laboratory (at a temperature range of 15 to 20° C) for 8 weeks 



412 SHARITZ AND LUVALL 

before the initiation of the temperature study. Only fronds from 
actively growing clones were used in the experiments. 

From each population one adult frond with a juvenile attached 
was placed in culture solution in each of 24 4.3- by 5.1-cm 
compEirtments in uncovered clear plastic trays. Each sample tray was 
treated to one of five thermal regimes in controlled environment 
chambers. This design provided 24 replicates of each temperature 
and population treatment. Frond division and growth of the clones 
were examined under constant temperatures of 10, 17.5, and 25° C; a 
daily square-wave cyclic regime of 10 to 25°C; and a daily square- 
wave acyclic regime varying within 10 to 25°C limits, with a mean 
temperature of 17.8°C. Cyclic temperatures changed every 12 hr, 
with the maximum (25°C) occurring in the day. Acyclic tempera- 
tures changed every 12 hr, with the maximum occurring either in the 
day or night so that the next temperature was unpredictable within 
the specified range. Temperatures within 0.5° C and 12-hr light— dark 
photoperiods with light intensities of approximately 800 ft-c 
(cool-white fluorescent light) were maintained in all chambers. These 
light conditions are within the range for optimal growth of the 
Lemnaceae (Ashby and Oxley, 1935). Each tray compartment 
contained 50 ml of half -strength Hoagland's culture medium (Hoag- 
land and Arnon, 1950) plus 5 ppm ferric citrate. The pH was 
adjusted to 6.8 with 300 ml O.IM KOH per 35 liters of solution. To 
reduce algal infection, all fronds were washed initially in distilled 
water, and the plants in each treatment were transferred to fresh 
culture solutions weekly to remove waste products and replenish 
nutrients. 

Growth of S. oligorrhiza clones was determined at weekly 
intervals by adult frond count. The number of adult fronds was used 
as a measure of population growth because high correlations have 
been demonstrated between the rate of increase in frond number and 
the net assimilation rate, frond area, protein content, and depth of 
frond color in Lemna sp. (White, 1939). Frond weight was not used 
since Hicks (1934) demonstrated that in L. minor frond weight 
depends on the amount of stored starch and may not accurately 
reflect population growth. The experiment was continued for 4 
weeks until the surface area in the culture chambers was covered by 
plants in the more rapidly growing populations. 



RESULTS 

The mean number of adult fronds of S. oligorrhiza at the end of 
the 4-week growing period under each set of experimental conditions 



GROWTH OF DUCKWEED 413 



TABLE 1 



NUMBER OF ADULT FRONDS OF Spirodela oligorrhiza GROWN 

IN 4 WEEKS FROM ONE ADULT FROND IN EACH OF FIVE 

TEMPERATURE REGIMES* 









Temperature regimef 




Population 


Constant, 
10°C 


Cyclic, 
10— 25°C 


Constant, 

17.5°C 


Acyclic, 
10-25°C 


Constant, 
25°C 


1 
2 
3 
4 

5 


3.0 ± 0.2 
2.4 ± 0.5*" 

3.2 ± 0.2 

3.1 ± 0.2*^ 

3.3 ± 0.4 


44.2 ± 6.6* 

17.3 ± 2.7*-'' 
72.8 ± 7.8* 
40.5 ± 4.8* 
61.8 ± 7.6* 


62.5 ± 5.7*-^ 
38.4 15.1* 
63.3 110.4* 
46.2 1 5.7* 
59.0 1 9.1* 


79.8 1 7.0*" 
53.0 18.6* 
66.9+ 10.1* 
33.2 1 7.3*-'' 
76.7 1 16.6* 


235.1 1 28.3 
57.9 1 9.5* 

236.6 1 23.6 

145.7 1 24.2 
216.3 1 41.8 



♦Population 1, beaver pond; 2, sewage-effluent pond; 3, roadside ditch; 4, 
chemical-effluent pond; and 5, natural stream. Values are X + standard error for N = 24 
replicates for each temperature and population treatment. 

tValues in each row with like superscripts do not differ significantly (a = 0.05) 
(Tukey's HSD test; Kirk, 1968). 



is given in Table 1. Significant differences (multiple significant 
difference; Morrison, 1967) {a = 0.05) in population (clone) growth 
occurred at the extremes of the temperature treatments. The greatest 
number of fronds was produced by each population at a constant 
temperature of 25° C. Except in the sewage-effluent population, 
which showed reduced growth under all treatments (Table 1), the 
increased growth at high temperatures was significant and repre- 
sented the production of a daughter frond by each adult every 4 
days. There was a significant reduction in growth at 10°C constant 
temperature in three of the S. oligorrhiza populations, and all 
populations produced fewer fronds at the low temperature than 
under the other temperature regimes. Only one new generation was 
produced at this temperature. Cyclic and acyclic thermal regimes 
generally affected the growth rate of S. oligorrhiza in the same way 
as exposure to a constant temperature equal to the mean of the 
variable temperatures. In all populations, growth under cyclic and 
acyclic conditions was not statistically different (o: = 0.05) from that 
at 17.5°C, and in only one population did the two fluctuating 
thermal regimes produce growth responses that differed from each 
other (Table 1). A new frond was produced every 5 to 6 days under 
these three treatments. 

In all populations rate of growth was highest at 25° C during the 
first 3 weeks (Fig. 1). Four populations showed a decline in the 
growth rate at this temperature during the final week of the study. 
Occasional differences in growth rates under the fluctuating and 



414 



SHARITZ AND LUVALL 



o 



75 

25 
20 
15 
10 

5 



120 
115 
110. 

80 
70 



*=74 



25 



11 



23 



25 



18 



en 
Q 

O 

tr 



O 60 

(X. 



50 — 



40 — 



CO 

< 

LU 

ir 30 



20 — 



10 



T 




m^ 



T 



12 3 4 
Population 1 



12 3 4 
Population 2 



I 

12 3 4 

Population 3 

WEEKS 



12 3 4 

Population 4 



12 3 4 
Population 5 



Fig. 1 Rate of frond increase in five populations of Spirodela 
oligorrhiza under five temperature regimes: constant exposures to 
10°C (A— A), 17.5°C (C^O), and 25°C (•-•); cyclic exposure at 10 
to 25°C (n— n); and acyclic exposure at 10 to 25°C (A— A) over a 
4-week period. Differences between temperature treatments greater 
than the bars at the top are significant (a = 0.05) (multiple 
significant difference; Morrison, 1967). N = 24. Populations are 
described in Table 1. 



constant 17.5°C regimes during the early weeks disappeared in the 
later part of the study as growth rates were reduced. 

Growth differences among the local populations of S. oligorrhiza 
were seen under the high-temperature treatments. Plants from the 
sewage-effluent pond grew less under all regimes, and those from the 
roadside ditch generally showed the highest rate of population 



GROWTH OF DUCKWEED 415 

growth. The significance of these differences cannot be determined 
without further investigation. 

DISCUSSION 

Differences in growth rates among populations of S. oligorrhiza 
were expected. Several investigators suggested that variations in 
grow^th rates of L. minor populations may be related to genetic or 
environmental differences (Wangermann and Ashby, 1951), age of 
the original parent plant (Claus, 1972), annual cycles (White, 1936), 
or other cyclic variations (Dickson, 1938). Because of the observed 
differences among the five S. oligorrhiza populations in this study, 
discussion is restricted to within-population comparisons across 
temperature treatments. 

Only limited frond mortality was observed in the S. oligorrhiza 
plants grown during the study. Although little information is 
available on longevity in this species, Rejmankova (1973a) indicated 
that fronds of Lemna species in Czechoslovakian lakes usually live 
about 4 weeks. Frond length of life is related to environmental 
conditions, especially temperature (Ashby, Wangermann, and Winter, 
1949; Ashby and Wangermcinn, 1951). This study was designed to be 
completed within the projected lifetime of a single plant. 

Spirodela oligorrhiza demonstrated highest population growth 
rates at a constant temperature of 25° C. Only during the final week, 
as crowding in the culture chambers became apparent, was growth at 
this temperature reduced. Similar curves consisting of an exponential 
growth phase, a linear growth phase, and a later steady-state stage of 
population maintenance were described by Clatworthy and Harper 
(1962) in laboratory populations of Lemna species. At the lower 
extreme, the 10°C constant-temperature regime severely restricted S. 
oligorrhiza frond multiplication. This pattern is consistent with the 
report by Jacobs (1947) that optimum growth of S. polyrhiza 
occurred at 25° C and the population deteriorated at 7°C. 

The relationship between temperature and growth in other 
members of the Lemnaceae has been well established. In an early 
study of L. minor. Hicks (1934) reported an exponential increase in 
frond number at temperatures between 15 and 30°C. Above 35° C, 
the growth rate declined rapidly. Similarly, Ashby and Oxley (1935) 
reported that the relative multiplication rate of L. minor fronds 
increased linearly with temperature up to 20° C and confirmed that 
temperatures above 35° C were deleterious to frond increase. At a 
light intensity of 500 ft-c, frond production in L. minor was twice as 
fast at 30° C as at 20° C (Ashby and Wangermann, 1951). More 



416 SHARITZ AND LUVALL 

recently Hodgson (1970), after observing the growth of L. minor at 
constant temperatures of 12.5, 17.5, 22.5, and 27.5°C, reported that 
the population leaf area was highest at the 27. 5° C exposure but the 
maximum net assimilation rate was achieved at 17. 5° C, with a 
marked decline at higher temperatures. These results disagree with 
those of Ashby and Oxley (1935), who indicated that the assimila- 
tion rate in L. minor was independent of temperature between 18 
and 29° C. Hodgson attributes the discrepancy to differences in 
experimental conditions, especially illumination. There appears to be 
general agreement, however, that population growrth (frond multipli- 
cation) in the Lemnaceae under constant-temperature regimes 
increases with temperature to a maximum at approximately 30° C. 

Combining the data from populations 1 through 5 in Table 1 
yields mean frond densities of 3, 47, 54, 62, and 178 for the 10°C, 
cyclic, 17.5°C, acyclic, and 25°C regimes, respectively. Because the 
individual populations demonstrated different responses, these com- 
bined means cannot be taken as predictions of response for any given 
population, but they can be used to evaluate the relative importance 
of constant and cyclic regimes. According to Tukey's HSD test (Kirk, 
1968), two of the combined means must differ by at least 12 to be 
significantly different at the 5% level. Thus the densities at constant 
temperatures of 10, 17.5, and 25°C are significantly different, but 
the densities under cyclic, 17.5°C, and acyclic regimes are not. The 
interval of 12 required for significance was computed from a 
mean-square error term that may have been inflated by inclusion of 
the highly variable replicates from the 25°C regime. An interval 
computed from a mean-square error term involving only the cyclic, 
17.5°C, and acyclic populations would be smaller and might indicate 
significant differences among means. This would not alter the 
conclusion that cyclic and acyclic regimes had relatively little effect 
on the growth response of duckweed, however. 

Although few efforts have been made to examine effects of 
fluctuating temperatures on growth in the Lemnaceae, Rejmankova 
(1973a; 1973b) demonstrated seasonal changes in growth of field 
populations of L. minor and L. gihha and suggested that frond 
multiplication is regulated by temperature during early and late 
periods of the growing season. 

The effects of cyclic temperatures on growth of other organisms 
have been much more carefully examined. Shimo (1977) demon- 
strated the influence of diurnal thermoperiodicity on the growth of 
sporelings and fronds of Porphyra and reported greater elongation of 
plantlets grown at temperatures of 18 to 22° C when night 
temperatures were lowered 4 to 8°C below day temperatures. Heath 



GROWTH OF DUCKWEED 417 

(1963) referred to a number of experimental studies demonstrating 
that organisms generally have higher thermal tolerance when tem- 
perature exposure is cyclic rather than continuous. His work 
demonstrated that certain species of fish respond to the upper 
extremes of the thermoperiod and have maximum thermal tolerance 
under a 24-hr temperature cycle. Van Winkle's (1969) study of 
Modiolus demissus showed that the net effect of a cyclic temperature 
regime (26 to 34° C) on byssal thread formation was similar to that 
of a constant 30° C exposure. Likewise, survival of the mud crab, 
Rhithropanopeus harrisii, exposed to 10°C cycles is similar to that at 
constant exposure to the mean temperature of the cycle (Costlow 
and Bookhout, 1971). Insects have frequently been shown to 
develop more rapidly under fluctuating temperatures than under 
constant temperature exposures (Hagstrum and Hagstrum, 1970). In 
a study paralleling this one. Thorp and Wineriter (1978) observed 
higher mortality in juvenile crayfish, Procambarus acutus acutus, 
under the cyclic regime (10 to 25°C) than under acyclic or constant 
17.5°C exposures. This organism apparently suffered negative effects 
at 25° C, even for short periods of exposure. 

Within the 10 to 25° C temperature range studied, frond 
multiplication of S. oligorrhiza appears to respond to the total 
temperature exposure. Cyclic and randomly fluctuating temperatures 
yielded the same growth response as constant-temperature treat- 
ments at the same mean temperature (17.5°C). The adaptability of 
duckweed species to a wide range of environmental conditions has 
been noted by other investigators (Hicks, 1934; Ashby and Oxley, 
1935; Hodgson, 1970; Hillman, 1976). One explanation for duck- 
weed's adaptability to a wide thermal range, even in natural 
populations, is that surface-dwelling aquatic species are more likely 
to be selected for tolerance to extreme temperatures than are 
bottom-dwelling forms, such as crayfish, which inhabit sites where 
temperatures normally remain more constant. This explanation is 
also applicable to the apparent selection for high thermal tolerance in 
bluegill, Lepomis macrochirus, living in a heated reservoir (Holland et 
al., 1974); whereas populations of the surface-dwelling mosquitofish, 
Gambusia af finis, from thermal and natural areas showed no 
differences in thermal tolerance (Smith, 1978). It is likely that this 
species, like the duckweeds, has a high thermal tolerance in the 
conditions of its natural habitat (Smoak, 1959). 

The ability of Spirodela to develop turions (specially resistant 
vegetative fronds produced under adverse environmental conditions) 
also contributes to its wide distribution and its effectiveness as a 
colonizing species in disturbed aquatic habitats. Since many man- 



418 SHARITZ AND LUVALL 

induced environmental disturbances occur intermittently, plant and 
animal species that have already undergone natural selection to 
withstand fluctuating conditions with low predictability may be of 
major importance in maintaining ecosystem structure. 



ACKNOWLEDGMENTS 

We thank J. H. Thorp and D. H. Nelson for their ideas and 
development of related studies, S. A. Wineriter for aid in maintaining 
the temperature chambers, K. A. VandenBosch for assistance in 
counting the plants, J. E. Pinder III for statistical advice and analysis, 
and J. B. Coleman for drafting the figure. The manuscript was 
reviewed by E. H. Liu and J. W. Gibbons. Research was performed 
under contract EY-76-C-09-0819 between the U. S. Department of 
Energy and the University of Georgia. 



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Gambusia affinis holbrooki (Girard) in the Savannah River Plant Area, S. C. 
Acad. Sci., 1959: 44-53. 

Thorp, J. H., and S. A. Wineriter, 1978, Grovii;h in a Stochastic Environment: 
Acyclic Temperature Regime, in preparation. 

Van Winkle, W., Jr., 1969, Physiological Effects of Short-Term, Cyclic 
Environmental Changes, Am. ZooL, 9: 1100. 

Wangermann, E., and E. Ashby, 1951, Studies in the Morphogenesis of Leaves. 
VII. Part I. Effects of Light Intensity and Temperature on the Cycle of 
Ageing and Rejuvenation in the Vegetative Life History of Lemna minor, 
NewPhytol, 50: 186-199. 

White, H. L., 1936, The Interaction of Factors in the Growth of Lemna. IX. 
Further Observations on the Effect of Light Intensity on Growth and 
Multiplication, Ann. Bot. (London), L: 827-848. 

, 1939, The Interaction of Factors in the Growth of Lemna. XIV. The 

Interaction of Potassium and Light Intensity in Relation to Growth and 
Assimilation, Ann. Bot. (London), III: 619-648. 



GROWTH AND ECOLOGY 

OF Spartina alterniflora IN MAINE 

AFTER A REDUCTION IN THERMAL STRESS 



M. KESER,* B. R. LARSON,* R. L. VADAS,t and W. McCARTHY* 
*Department of Botany and Plant Pathology, and fDepartment of Botany and 
Plant Pathology and Oceanography and Zoology, University of Maine, 
Orono, Maine 



ABSTRACT 

When a surface thermal discharge was relocated through a diffuser system in May 
1975, the thermal impact on a previously stressed and moribund population of 
Spartina alterniflora in Montsweag Bay, Maine, was terminated. Post-stress 
growth and recovery were examined over three growing seasons. Plant biomass 
and density were lowest in 1975 because of continued surface discharge into 
Bailey Cove during the winter and early growing season of 1975. In 1976 and 
1977, however, biomass and density increased slightly and shoot grovirth 
returned to prestress levels, as indicated by size-frequency distributions. The 
partial recovery of Spartina resulted from viable patches of plants and rhizomes 
in ~40% of the study area. In relation to previous values, biomass declined in the 
control marsh during this 3-year period. The decline was attributed to increased 
salinity, greater tidal amplitude, and decreased summer temperatures resulting 
from the removal of a causeway between the mainland and Westport Island in 
the fall of 1974. 



Spartina alterniflora, which dominates extensive coastal areas of 
eastern North America (Teal, 1962; Redfield, 1972), is generally 
considered eurytopic and relatively insensitive to aquatic stresses 
(Young, 1974; Adams, 1963; Anderson, 1969). Populations near 
their northern limit of distribution are not as tolerant as others, 
however, and, when they were exposed to thermal stress in Maine, 
they were affected adversely and collapsed within 2.5 years (Vadas, 
Keser, Rusanowski, and Larson, 1976). The disappearance of plants 

420 



GROWTH AND ECOLOGY OF Spartina alterniflora 421 

in 60% of the marsh was related to the destruction of the rhizome 
system, which had metabohzed its reserves and was unable to 
produce viable shoots in the spring of 1974 and 1975. 

In May 1975 the thermal discharge into Bailey Cove from the 
Maine Yankee Atomic Power Company (MYAPCO) was discon- 
tinued, and 2 months later the discharge was diverted into a 
multiport diffuser system in the main channel of Montsweag Bay. 
This paper analyzes the growth and potential recovery of this 
previously stressed population of Spartina. 

SITE AND METHODS 

We studied two populations of Spartina in Montsweag Bay from 
spring 1975 to August 1977. Populations were located in Bailey 
Cove, which was previously stressed by a surface thermal discharge, 
and in Causeway Marsh, a control area located 3 km north of the 
power plant (Fig. 1). Detailed descriptions of Bailey and Causeway 
marshes are available elsewhere (Vadas et al., 1976). 

Ten randomly selected quadrats ('/i^m^) at each site were 
sampled for aboveground biomass in July and August 1975 and 1977 
and monthly from May to October 1976. Because of the disruptive 
nature of biomass collections, limited sampling was performed in 
1975 and 1977 to minimize damage to previously stressed plants. In 
1975 and 1977 samples were taken during previously established 
peak biomass periods (Vadas et al., 1976). Sampling in Bailey Marsh 
was stratified since only 40% of the marsh contained Spartina. Four 
samples were taken at random in areas containing plants, and six 
were taken in cireas devoid of plants. Plants were cut v^th shears at 
the surface of the mud and were transported to the laboratory, 
where they were washed, counted, measured, and dried to a constant 
weight at 70° C. Salinities and temperatures were measured monthly 
over mud flats adjacent to each marsh during high tide at depths of 
0.15 m (surface) and 3.0 m (bottom) with a salinomete]^ 
thermometer. Light extinction coefficients were determined with a 
Secchi disc (Holmes, 1970). Incident solar radiation was measured 
with a pyreheliometer at MYAPCO. 

After removal of the causeway in the fall of 1974, the average 
tidal range increased by 0.34 m, reflecting greater water flow in and 
out of Montsweag Bay. The average high tide was 0.06 m higher, and 
the average low tide 0.27 m lower. The resultant average tidal range, 
2.88 m, exposed an additional 109 to 158 ha of mud flat during each 
tide (Anonymous, 1975). 



422 



KESER, LARSON, VADAS, AND McCARTHY 




CAUSEWAY MARSH 



0.5 1 

NAUTICAL MILES 




Fig. 1 Maine Yankee Atomic Power Company (MYAPCO) at 
Wiscasset, Me., showing the stressed (Bailey) and control (Causeway) 
marshes; Cowseagan Narrows causeway, C; and diffuser discharge, 
D. Water intake and former surface discharge are indicated by 
arrows. 



RESULTS AIMD DISCUSSION 



Hydrographic Data 

Average salinities at Causeway Marsh during 1975 to 1977 
increased by 4.2%o at the surface and by 3.4%o at a depth of 3 m 
(Fig, 2) compared with values from 1972 to 1974 (Vadas et al., 
1976). Variabilities among monthly measurements declined, how- 
ever. In contrast, salinity patterns at Bailey Marsh from 1975 to 
1977 were similar to those from 1972 to 1974. 

Lower temperatures at Causeway Marsh during the early growing 
seasons of 1975 to 1977 (April— July) resulted in lower yearly 



GROWTH AND ECOLOGY OF Spartina alterniflora 



423 



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424 KESER, LARSON, VADAS, AND McCARTHY 

average temperatures (1.3°C at 0.15 m and 2.1°C at 3 m) than in 
1972 to 1974. These were caused by increased exchange with the 
colder waters when the causeway was removed. Temperatures at Bailey 
Marsh declined significantly after relocation of the thermal discharge. 
Surface and bottom temperatures were higher at Bailey Marsh (2.7°C 
and 3.6° C, respectively) in spring and early summer (April— July) 
than at Causeway Marsh during this post-stress phase. The differen- 
tial was caused by increased insolation and heat conduction to the 
water column from newly exposed mud flats (Dean and Officer, 
1977). Average yearly temperatures were lower in Bailey Marsh, 
however, because of the entrapment of freshwater and the presence 
of ice. Turbidity decreased slightly after completion of the diffuser. 
Incoming solar radiation patterns were similar throughout stress and 
post-stress phases. 

Plant Density 

The density of Spartina at Causeway Marsh exhibited two 
distinct peaks, one in late spring and one in early fall (Fig. 3). 
Densities were highest from 1972 to 1974, averaging 704 and 1118 
shoots/m^ in July and August, respectively (Vadas etal., 1976). 
Mean densities from 1975 to 1977 averaged 434 and 686 shoots/m^ 
in July and August, respectively. The decline in density during this 
period was attributed to removal of the causeway, which allowed a 
greater influx of colder and more saline water. 

At Bailey Marsh the late spring peak did not develop in 1974, 
and its absence was attributed to the thermal discharge. This peak 
was reestablished in 1976, however, 1 year after the discharge into 
Bailey Cove was discontinued (Fig. 3). The density of Spartina in 
July and August 1972 was 560 and 900 shoots/m' , respectively, 
whereas in stressed years (1973 and 1974), densities in July and 
August averaged 625 and 750 shoots/m^ , respectively. Average shoot 
density for the marsh was lowest in 1975 but increased in 1976 and 
1977 to 222 and 476 shoots/m^ for July and August, respectively. In 
40% of the marsh, however, where healthy plants and rhizomes were 
present, plant densities in poststressed years (1976, 1977) averaged 
672 and 1188 shoots/m^ in July and August. These values were 
higher than those in 1972 and higher than densities at Causeway 
Marsh for the same periods. The plants at Bailey Marsh had thin 
shoots and leaves, however, and were not as robust as those at 
Causeway Marsh. These data suggest that recovery in the overall 
marsh is sparse and that, where plants survived, they recovered only 
partially. 



425 



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Fig. 3 Density of Spartina alterniflora during the last year of direct 
thermal discharge (1974) and since relocation of the thermal 
discharge through a diffuser (1975—1977) at (a) Causeway Marsh 
(control) and (b) Bailey Marsh (stressed). 



426 KESER, LARSON, VADAS, AND McCARTHY 

Growth 

At Bailey Marsh the number of new shoots increased in August, 
forming the typical bimodal pattern that was evident before 1972 
but was lacking during the second year of thermal stress. The size 
and numbers of Spartina continued to decline in 1975 because the 
surface discharge continued until May of that year. The bimodal 
growth pattern was reestablished in 1976 and 1977, however. The 
recovery of Spartina was limited to 40% of the marsh, where 
rhizomes had survived, and the remaining portion has not been 
recolonized by seeds or rhizomes. Growth patterns for Spartina at 
Causeway Marsh have not changed over the course of these studies 
(Fig. 4). Shoot growth began in early May, and by July the majority 
of plants were in the larger size ranges (50 to 125 cm in length). 

These results suggest that rhizome systems of northern popula- 
tions of Spartina are intolerant of thermal stress and that revegeta- 
tion of a marsh is a slow process in northern areas. The sensitivity of 
rhizomes to stress is not unique. The destruction of marshes through 
compaction and damage to rhizome systems by walking was 
described by Teal and Teal (1969). Similarly, Thomas (1973) 
reported that the mortality of S. alterniflora was most severe the 
second year after an oil spill because of the demise of the rhizome 
system. 



Flowering 

Flowering in Spartina at Bailey Marsh during stressed years began 
in July and continued through September (Vadas et al., 1976). When 
the stress was ameliorated (in 1975 to 1977), flowering was initiated 
later and lasted through October (Table 1). The onset of flowering in 
Causeway Marsh (control) occurred in August throughout both 
phases of these studies. Plants in the 75- to 100- and 100- to 200-cm 
size classes flowered at Bailey Marsh, but only plants taller than 100 
cm flowered at Causeway Marsh. The average height of reproductive 
plants in the Control Marsh during 1975 to 1977 ranged from 135 to 
149 cm, whereas average shoot heights at Bailey Marsh ranged from 
98 to 116 cm. These size ranges were similar to those recorded in 
1973 and 1974 (Vadas et al., 1976). Plants in the 50- to 75-cm range 
at Causeway Marsh did not flower in 1975 to 1977 although that size 
class had flowered previously. Since marsh plants are less fertile at 
high salinities (Adams, 1963), it is possible that the reduction in 
flowering at this site was caused by increased salinities. 



GROWTH AND ECOLOGY OF Spartina alterniflora 



427 



Biomass 

The increase in biomass of Spartina in Maine follows an 
exponential growth curve that usually peaks in August. Biomass 
estimates at Causeway Marsh for 1972 to 1974 averaged 1.04 kg/m'^ 
for July and August (Vadas et al., 1976). Average biomass values for 
July and August 1975 to 1977 decHned by 42% over the average of 
the previous three summers. These changes resulted from natural 
variability (Vadas et al., 1976) and likely from physical changes 
(especially sEilinity) in Montsweag Bay. Negative correlations between 
biomass and salinity were observed for other marsh grasses, e.g., S. 
alterniflora (Adams, 1963) and S. foliose (Phleger, 1971). However, 




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the last full year of surface discharge (1974) and after diversion of 
effluent through the diffuser (197 5—1977). 

(Figure continues on following page.) 



428 



KESER, LARSON, VADAS, AND McCARTHY 




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GROWTH AND ECOLOGY OF Spartina alterniflora 



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GROWTH AND ECOLOGY OF Spartina alterniflora 431 

similar findings by Nixon and Oviatt (1973) in Rhode Island were 
confounded additionally by negative correlations between salinity 
and nutrient levels which masked the causes of variability. High 
soil— sediment salinities have also been implicated in reduced growth 
in Spartina (Mooring, Cooper, and Seneca, 1971; Broome, Wood- 
house, and Seneca, 1973). 

The idea that the decrease in biomass at Causeway was caused by 
increased salinity is supported by the lack of correlation between 
biomass and temperature. Despite the apparent correlation between 
increasing temperatures and biomass from 1972 to 1974 (Vadas 
et al., 1976), warmer temperatures in 1976 did not result in higher 
than normal biomass estimates. This suggests that the growth of 
Spartina in Maine is not wholly temperature dependent, but rather 
that temperature and salinity, and perhaps other factors, act in 
concert to control growth. 

The decline in biomass at Bailey Marsh during the thermal- 
discharge phase, however, was attributed directly to increased 
temperatures. Direct surface discharge continued until May 2, 1975, 
and resulted in the lowest recorded biomass estimates for August 
(Fig. 5). Biomass increased slightly in 1976 and 1977, suggesting that 
the thermal stress and apparent shock has been alleviated and that 
the marsh may be returning to more stable (prestress) conditions. 



SUMMARY 

During the first year of diffuser operation, the biomass and shoot 
density of Spartina at Bailey Marsh continued to decline. In 1976 
and 1977 the decline, which was associated with the previous 
thermal stress on the rhizome system, was arrested, and recovery was 
evident. 

The biomass, plant density, and flowering of Sparf ma at Causeway 
Marsh (control) decreased after the Cowseagan Narrows causeway 
was removed in the fall of 1974. These declines were attributed to 
increased tidal amplitude and salinities and decreased temperatures 
during the growing season. Light was not considered important since 
changes in incoming solar radiation were not evident and since 
turbidity had decreased from 1975 to 1977. 

The most noticeable effect of the thermal effluent was the 
reduction in coverage of Spartina in Bailey Marsh. Approximately 
60% of the study area was devoid of plants. Colonization by seeds or 
rhizomes had not occurred as of 1977. Examination of rhizomes in 
the area showed them to be badly decomposed. Redfield (1972) 



432 



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1975 



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1977 



Fig. 5 Biomass of Spartina alterniflora at (a) Causeway Marsh 
(control) and (b) Bailey Marsh (stressed) during the last full year of 
surface thermal discharge (1974) and after diversion of the effluent 
through the diffuser (1975—1977). 



GROWTH AND ECOLOGY OF Spartina alterniflora 433 

found that lateral extension ol Spartina by rhizomes and colonization 
via seeds was a slow process in Massachusetts marshes. If plants in 
Bailey Marsh respond similarly, it will be several years before 
complete recovery occurs. 

REFERENCES 

Adams, D. A., 1963, Factors Influencing Vascular Plant Zonation in North 

Carolina Salt Marshes, Ecology, 44: 445-456. 
Anderson, R. R., 1969, Temperature and Rooted Aquatic Plants, Chesapeake 

ScL, 10: 157-164. 
Anonymous, 1975, Hydrography, Semi- Annual Report No. 6, pp. 1.7-3—1.7-11, 

Maine Yankee Atomic Power Company, Wiscasset. 
Broome, S. W., W. W. Woodhouse, and E. D. Seneca, 1973, An Investigation of 

Propagation and Mineral Nutrition of Spartina alterniflora, Sea Grant 

Publication UNC-SG-73-14, University of North Carolina, Chapel Hill. 
Dean, D., and C. B. Officer, 1977, Development Document in Support of 

Alternative Effluent Limitations Pursuant to Section 316(a) of the Federal 

Water Pollution Control Act for Maine Yankee Nuclear Generating Station, 

Maine Yankee Atomic Power Company, Wiscasset. 
Holmes, R. W., 1970, The Secchi Disk in Turbid Coastal Waters, Limnol. 

Oceanogr, 15: 688-694. 
Mooring, M. T., A. W. Cooper, and E. D. Seneca, 1971, Seed Germination 

Response and Evidence for Height Ecophenes in Spartina alterniflora from 

North Carolina, Am. J. BoL, 58: 48-55. 
Nixon, S. W., and C. A. Oviatt, 1973, Analysis of Local Variation in the 

Standing Crop oi Spartina alterniflora, Bot. Mar., 16: 103-109. 
Phleger, C. F., 1971, Effect of Salinity on Growth of Salt Marsh Grass, Ecology, 

52: 908-911. 
Redfield, A. C, 1972, Development of a New England Salt Marsh, Ecol. 

Monogr., 42: 201-237. 
Teal, J. M., 1962, Energy Flow in the Salt Marsh Ecosystem of Georgia, 

Ecology, 43: 614-624. 
, and M. Teal, 1969, Life and Death of the Salt Marsh, Atlantic Monthly 

Press, Boston. 
Thomas, M. L. H., 1973, Effects of Bunker C Oil on Intertidal and Lagoonal 

Biota in Chedabucto Bay, Nova Scotia, J. Fish. Res. Board Can., 30: 83-90. 
Vadas, R. L., M. Keser, P. C. Rusanowski, and B. R. Larson, 1976, The Effects 

of Thermal Loading on the Growth and Ecology of a Northern Population 

of Spartina alterniflora, in Thermal Ecology II, ERDA Symposium Series, 

Augusta, Ga., Apr. 2-5, 1975, G. W. Esch and R. W. McFarlane (Eds.), pp. 

54-63, CONF-750425, NTIS. 
Young, D. L., 1974, Studies of Florida Gulf Coast Salt Marshes Receiving 

Thermal Discharges, in Thermal Ecology, AEC Symposium Series, Augusta, 

Ga., May 3—5, 1973, J. W. Gibbons and R. R. Sharitz (Eds.), pp. 532-550, 

CONF-730505, NTIS. 



EFFECTS OF REDUCED TEMPERATURES 
ON PREVIOUSLY STRESSED POPULATIONS 
OF AN INTERTIDAL ALGA 



R. L. VADAS,* M. KESER,t and B. LARSONf 

*Departments of Botany and Plant Pathology and Oceanography and Zoology, 
and tDepartment of Botany and Plant Pathology, University of Maine, 
Orono, Maine 



ABSTRACT 

Relocation of a surface thermal discharge through a multiport diffuser and 
removal of a causevi^ay substantially reduced temperatures in an estuary 
surrounding a nuclear power plant. Although stressed and moribund during 
thermal discharge, basal portions of adult thalli of Ascgphyllum nodosum 
showed considerable resilience to thermal stress and potential competition from 
other species and survived. Previously stressed populations recovered fully; all 
measures of vigor being indistinguishable from prestress years. Growth in apical 
tips was sensitive to small shifts in ambient water temperature, suggesting that 
Ascophyllum might be a good indicator for thermal and perhaps other stresses in 
marine ecosystems. Growth data indicate that thermal enhancement occurs in 
Ascophyllum, artificially from thermal effluent and naturally from increased 
insolation to newly exposed mud flats. 



Altering physical, chemical, or biological components of ecological 
systems often provides insight into the structure and role of 
individual components. Manipulative experiments, for example, are 
powerful tools in analyzing causal relationships in marine com- 
munities (Connell,