PB81-209595
Microcosms as Test Systems for jthft Ecological
Effects of Toxic Substances
An Appraisal with Cadmium
Georgia Univ.
Athens
Prepared for
Environmental Research Lab
Athens, GA
Jun 81
U.S. DEPARTMENT OF COMMERCE
National Technical Information Service
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EPA 600/3-81-036
June 1981
MICROCOSMS AS TEST SYSTEMS FOR THE ECOLOGICAL EFFECTS
OF TOXIC SUBSTANCES: AN APPRAISAL WITH CADMIUM
by
Paul F. Hendrix, Christine L. Langner,
Eugene P. Odum, and Carolyn L. Thomas
Institute of Ecology
University of Georgia
Athens, Georgia 30602
Grant No. R805860010
Project Officer
Donald Brockway
Environmental Systems Branch
Environmental Research Laboratory
Athens, Georgia 30613
RESEARCH LABORATORY
OFFICE OF RESEARCH AND DEVELOPMENT
U.S. ENVIRONMENTAL PROTECTION AGENCY
ATHENS, GEORGIA 30613
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NOTICE
THIS DOCUMENT HAS BEEN REPRODUCED
FROM THE BEST COPY FURNISHED US BY
THE SPONSORING AGENCY. ALTHOUGH IT
IS RECOGNIZED THAT CERTAIN PORTIONS
ARE ILLEGIBLE, IT IS BEING RELEASED
IN THE INTEREST OF MAKING AVAILABLE
AS MUCH INFORMATION AS POSSIBLE.
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TECHNICAL REPORT DATA
(Please read Instructions on the reverse before completing)
1. REPORT NO.
EPA-6nO/3-81-Q36
2.
ORD Report
3. RECIPIENT'S ACCESSION>NO.
Pg^l 209595
4. TITLE AND SUBTITLE
Microcosms as Test Systems for the Ecological Effects
of Toxic Substances: An Appraisal with Cadmium
5. REPORT DATE
June 1981
6. PERFORMING ORGANIZATION CODE
7. AUTHOR(S)
Paul F. Hendrix, Christine L. Langner, Eugene P. Odum
and Carolyn L. Thomas
8. PERFORMING ORGANIZATION REPORT NO.
9. PERFORMING ORGANIZATION NAME AND ADDRESS
Institute of Ecology
University of Georgia
Athens GA 30602
10. PROGRAM ELEMENT NO.
AARB1A
11. CONTRACT/GRANT NO.
12. SPONSORING AGENCY NAME AND ADDRESS
U.S. Environmental Protection Agency-Athens GA
Environmental Research Laboratory
College Station Road
Athens GA 30613
13. TYPE OF REPORT AND PERIOD COVERED
Final. 5/78-9/80
14. SPONSORING AGENCY CODE
EPA/600/01
15. SUPPLEMENTARY NOTES
16. ABSTRACT
A two-phase set of experiments was conducted to address some of the problems
inherent in ecological screening of toxic substances in aquatic microcosms. Phase
I was a 4 x 4 factorial experiment (four levels of cadmium versus four levels of
nutrient enrichment) on the intereactive effects of cadmium and nutrients using
static microcosms. Phase II was a 2 x 4 factorial experiment (continuous and
pulsed cadmium inputs versus phosphorus limited and non-limited inputs) using
flowthrough microcosms to study temporal aspects of system behavior in response to
nutrient limitation and chronic versus acute cadmium perturbations. Generally, as
cadmium concentration increased, parameters changed to indicate more system stress,
except that high nutrient levels reduced somewhat the stress effect of cadmium.
Of the variables measured, community metabolism, community composition by
trophic groups, and output/input ratios for NQ.3-N, Mn, and Fe provided the best
indicators of system response to cadmium. Nutrient enrichment and phosphorus
limitation significantly influenced cadmium effects on most of the variables
studied. Pulsed cadmium inputs early in succession significantly affected system
response to cadmium pulses later in succession.
A bibliography of microcosm literature is included.
17.
KEY WORDS AND DOCUMENT ANALYSIS
DESCRIPTORS
b.lDENTIFIERS/OPEN ENDED TERMS C. COSATI Field/Group
13. DISTRIBUTION STATEMENT
RELEASE TO PUBLIC
19. SECURITY CLASS (ThisReport)
UNCLASSIFIED
21. NO. OF PAGES
186
20. SECURITY CLASS (Thispage)
UNCLASSIFIED
22. PRICE
EPA Form 2220-1 (9-73)
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DISCLAIMER
This report has been reviewed by the Environmental Research Laboratory,
EPA, Athens, Georgia, and approved for publication. Approval does not sig-
nify that the contents necessarily reflect the views and policies of the
Environmental Protection Agency, nor does mention of trade names or commer-
cial products constitute endorsement or recommendation for use.
ii
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FOREWORD
Environmental protection efforts are increasingly directed towards
preventing adverse health and ecological effects associated with specific
compounds of natural or .human origin. As part of this Laboratory's research
on the occurrence, movement, transformation, impact, and control of environ-
mental contaminants, the Environmental Systems Branch studies complexes of
environmental processes that control the transport, transformation, degrada-
tion, and impact of pollutants or other materials in soil and water and
assesses environmental factors that affect water quality.
Concern about environmental exposure to toxic substances has increased
the need for accurate information on the transport, fate, and effects of
trace contaminants in natural waters. In developing this information,
interest is currently being shown in the use of microcosms for toxicant
screening and predictive model validation. This report evaluates microcosms
as research tools for providing accurate and reliable data on ecological
effects of a toxic substance.
David W. Duttweiler
Director
Environmental Research Laboratory
Athens, Georgia
iii
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ABSTRACT
A two-phase set of experiments was conducted to address some of the prob-
lems inherent in ecological screening of toxic substances in aquatic micro-
cosms, and to test two hypotheses concerning the response of ecosystems to
perturbations. Phase I was a 4 X 4 factorial experiment (four levels of cad-
mium versus four levels of nutrient enrichment) with static microcosms designed
to test the "subsidy-stress" hypothesis (Odum et at. 1979), and focused on the
interactive effects of cadmiun and nutrients. Phase II was a 2 X 4 factorial
experiment (continuous and pulsed cadmium inputs versus phosphorus limited
and non-limited inputs) with flowthrough microcosms designed to test the
"biomass increment" hypothesis (Vitousek 1977), and focused on temporal as-
pects of system behavior (especially out/input for several elements) in response
to nutrient limitation and chronic versus acute cadmium perturbations.
Phase I results supported the subsidy-stress hypothesis with respect to
cadmium inputs: Increasing cadmium concentrations (0, 1, 10, 100 ppb) caused
a decrease in the P/R ratio, a decrease in grazing herbivores, increase in
nighttime respiration and fungi, all indicators of system stress. Since net
daytime production and nighttime respiration increased with nutrient enrichment,
there was no nutrient stress effect even at the highest level. There was a
significant interaction effect of cadmium and nutrients with high nutrient
levels reducing somewhat, stress effect of cadmium. Phase II results generally
supported the biomass increment hypothesis and suggested a retention pattern
for continuous, low concentration cadmium inputs similar to that of essential
elements. Cadmium may have accumulated to a toxic threshold in some of the .
microcosms. Pulsed, high concentration cadmium inputs had significant effects
on system behavior, depending on timing of inputs.
iv
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Conclusions relevant to toxicity screening in microcosms are: 1) Of the
variables measured, community metabolism, community composition by trophic
groups, and output/input ratios for NO,-N, Mi and Fe, provided the best in-
dicators of system response to cadmium. 2) Nutrient enrichment and phosphor-
ous limitation significantly influenced cadmium effects on most of the vari-
ables studied. 3) Pulsed cadmium inputs early in succession significantly
affected system response to cadmium pulses later in succession.
Recommendation: For screening a suspected toxic substance, we recommend
a hierarchy of microcosm experiments including: 1) static microcosms (with
and without sediments), 2) flowthrough microcosms (with and without sediments),
and 3) microcosm subsamples from specific natural ecosystems. Each step re-
sults in increased information about effects of a toxicant and each step more
closely approximates natural ecosystems.
A bibliography of microcosm literature is presented at the end of the
report.
This report was submitted in fulfillment of Grant No. R805860010 by the
University of Gerogia under the sponsorship of the U.S. Environmental Protec-
tion Agency. The report covers the period 22 May 1978 to 31 September 1980,
and work was completed as of 30 September 1980.
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CONTENTS
Foreword ill
Abstract iv
Figures vii
Tables xii
Acknowledgements xiii
1. Introduction 1
2. Materials and Methods 9
3. Results 18
4. Discussion 30
5. Comparison of Static and Flowthrough Microcosms 44
6. Considerations and Recommendations for Toxicity
Testing 54
7. Conclusions 63
Literature Cited 122
Microcosm Bibliography 127
Appendices 165
v-i
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FIGURES
Number Page
1 Hypothesized patterns of ecosystem response to usable
and toxic inputs 65
2 Hypothesized patterns of net ecosystem productivity
(A) and element retention (B) through ecosystem
succession 66
3 Experimental design for Phase I, with three repli-
cations of each treatment 67
4 Experimental design of Phase II, with four repli-
cations of each treatment 68
5 Influence of cadmium (A) and nutrient enrichment (B)
on average biomass concentration in static micro-
cosms ................. 69
6 Biomass concentrations through time in lowest nutrient
(Level 1) control static microcosms 70
7 Biomass concentrations through time in highest nu-
trient (Level 4) control static microcosms 71
8 Influence of cadmium (A) and nutrient enrichment (3)
on average chlorophyll concentrations in static
microcosms 72
9 Chlorophyll a concentrations through time in lowest
nutrient (Level 1) control static microcosms 73
10 Chlorophyll a concentration through time in highest
nutrient (Level 4) control static microcosms 74
11 Phaeo-pigment concentrations through time in lowest
nutrient (Level 1) control static microcosms 75
12 Phaeo-pigment concentrations through time in highest
nutrient (Level 4) control static microcosms 76
13 Net production nighttime respiration and P/R for the
four nutrient levels in static microcosms 77
14 Net production, nighttime respiration and P/R for the
four levels of cadmium in static microcosms 78
15 Community metabolic activity through time in lowest
nutrient (Level 1) control static microcosms 79
Vii
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Number
16 Community metabolic activity through time in highest
nutrient (Level 4) control static microcosms.
80
17 Influence of cadmium and nutrient enrichment on mean
fungal colony abundance in static microcosms 81
18 Influence of cadmium and nutrient enrichment on bac-
terial colony abundance in static microcosms 82
19 Influence of cadmium and nutrient enrichment on crus-
tacean abundance in static microcosms 83
20 Biomass concentrations through time in phosphorus
limited control flowthrough microcosms 84
21 Biomass concentrations through time in non-phosphorus-
limited control flowthrough microcosms 8 5
22 Chlorophyll a concentrations through time in N:P = 100
control flowthrough microcosms
23 Chlorophyll a concentrations through time in N:P = 10
control flowthrough microcosms
24 Phaeo-pigment concentrations through time in N:P = 100
control flowthrough microcosms 88
25 Phaeo-pigment concentrations through time in N:P = 10
control flowthrough microcosms 89
26 Net daytime production (A), nighttime respiration, (B),
and P/R (C) through time in flowthrough microcosms
with input N:P = 100 and no cadmium 90
27 Net daytime production (A), nighttime respiration (B),
and P/R (C) through time in flowthrough microcosms
with input N:P = 100 and continuous ppb Cd input. ... 91
28 Net daytime production (A), nighttime respiration (B),
and P/R (C) through time in flowthrough microcosms
with input N:P = 100 and cadmium pulses as indicated
in ppb Cd by arrows 92
29 Net daytime production (A), nighttime respiration (B),
and P/R (C) through time in flowthrough microcosms
with input N:P = 100 and cadmium pulse as indicated
in ppb Cd by arrow 93
viii
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Number Page
30 Net daytime production (A) , nighttime respiration (B) ,
and P/R (C) through time in flowthrough microcosms
with input N:P = 10 and no cadmium ..........
31 Net daytime production (A) , nighttime respiration (B) ,
and P/R (C) through time in flowthrough microcosms
with input N:P = 10 and continuing 10 ppb Cd inputs. .
32 Net daytime production (A) , nighttime respiration (B) ,
and P/R (C) through time in flowthrough microcosms
with input N:P = 10 and cadmium pulses as indicated
in ppb Cd by arrows .................. 96
33 Net daytime production (A) , nighttime respiration (B) ,
and P/R (C) through time in flowthrough microcosms
with input N:P = 10 and cadmium pulse as indicated
in ppb Cd by arrow .................. 97
34 Crustacean abundance through time in flowthrough micro-
cosms with input N:P = 10 and no cadmium ....... 98
35 Crustacean abundance through time in flowthrough micro-
cosms with input N:P = 10 and continuous 10 ppb Cd
inputs ........................ 99
36 Crustacean abundance through time in flowthrough micro-
cosms with input N:P = 10, and cadmium pulses as
indicated in ppb Cd by arrows ............. 1°0
37 Crustacean abundance through time in flowthrough micro-
cosms with input N:P = 10 and cadmium pulse as in-
dicated in ppb Cd by arrows .............. 101
38 Crustacean abundance through time in flowthrough micro-
cosms with input N:P = 100 and continuous 10 ppb Cd
inputs ........................ 102
39 Rotifer abundance through time in flowthrough microcosms
with input N:P = 100 and cadmium pulses as indicated
in ppb Cd by arrows .................. 103
40 Rotifer abundance through time in flowthrough microcosms
with input N:P = 100 and cadmium pulse as indicated
in ppb Cd by arrow .................. 104
41 Total nitrogen (A), ammonia nitrogen (B) and nitrate
nitrogen (C) output/input ratios through time in
flowthrough microcosms with input N:P = 100 and no
cadmium ........... . ...... ..... 105
ix
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Number Page
42 Total nitrogen (A), ammonia nitrogen (B), and nitrate
nitrogen (C) output/input ratios through time in
flowthrough microcosms with input N:P = 100 and
continuous 10 ppb Cd inputs 106
43 Total nitrogen (A), ammonia nitrogen (B), and nitrate
nitrogen (C) output/input ratios through time in
flowthrough microcosms with input N:P = 100 and cad-
mium pulses as indicated in ppb Cd by arrows 107
44 Total nitrogen (A), ammonia nitrogen (B), and nitrate
nitrogen (C) output/input ratios through time in
flowthrough microcosms with input N:P = 100 and
cadmium pulse as indicated in ppb Cd by arrow 108
45 Total nitrogen (A), ammonia nitrogen (B), and nitrate
nitrogen (C) output/input ratios through time in
flowthrough microcosms with input N:P = 10 and no
cadmium „ 109
46 Total nitrogen (A), ammonia nitrogen (B), and ni-
trate nitrogen (C) output/input ratios through time
in flowthrough microcosms with input N:P = 10 and
continuous 10 ppb Cd inputs 110
47 Total nitrogen (A), ammonia nitrogen (B), and nitrate
nitrogen (C) output/input ratios through time in
flowthrough microcosms with input N:P = 10 and cad-
mium pulses as indicated in ppb Cd by arrows HI
48 Total nitrogen (A), ammonia nitrogen (B), and ni-
trate nitrogen (C) output/input ratios through time
in flowthrough microcosms with input N:P «• 10 and
cadmium pulse as indicated in ppb Cd by arrow H2
49 Total phosphorus (A), manganese (B), and iron (C)
output/input ratios through time in flowthrough
microcosms with input N:P = 100 and no cadmium ....
50 Total phosphorus (A), manganese (B), and iron (C)
output/input ratios through time in flowthrough
microcosms with input N:P = 100 and continuous
10 ppb Cd inputs 114
51 Total phosphorus (A), manganese (B), and iron (C)
output/input ratios through time in flowthrough
microcosms with input N:P = 100 and cadmium pulses
as indicated in ppb Cd by arrows 115
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Number Page
52 Total phosphorus (A) , manganese (B) , and iron (C)
output /input ratios through time in flowthrough
microcosms with input N:P = 100 and cadmium pulse
as indicated in ppb Cd by arrow ............ ^ ^
53 Total phosphorus (A) , manganese (B) , and iron (C)
output/input ratios through time in flowthrough
microcosms with input N:P = 10 and no cadmium .....
54 Total phosphorus (A) , manganese (B) , and iron (C)
output/input ratios through time in flowthrough
microcosms with input N:P = 10 and continuous 10
ppb Cd inputs ..................... 118
55 Total phosphorus (A) , manganese (B) , and iron (C)
output/input ratios through time in flowthrough
microcosms with input N:P = 10 and cadmium pulses
as indicated in ppb Cd by arrows ...........
56 Total phosphorus (A) , manganese (B) , and iron (C)
output /input ratios through time in flowthrough
microcosms with input N:P = 10 and cadmium pulse
as indicated in ppb Cd by arrow ............ 12°
57 Cadmium output /input ratios through time in flow-
through microcosms with input N:P •» 10 (A), and
N:P = 100 (B) . Cadmium input concentration was
10 ppb- .......... .............. 121
-xi
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TABLES
Number Page
1 Comparison of nutrient effects on static and flow-
through microcosms 45
2 Comparison of cadmium effects on static and flow-
through microcosms 48
3 Qualitative comparison of microcosm responses to
cadmium 51
xii
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ACKNOWLEDGEMENTS
We are grateful to Ted Elliott and John Leffler for useful discussions
and suggestions throughout these experiments. We thank Julie Fortson and
Gladys Russell for their help in preparing and typing the manuscript.
Special thanks are due Mary Pitts, who provided a number of references
included in the Bibliography.
xiii
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SECTION 1
INTRODUCTION
The release of toxic substances into the environment has become a
serious problem, especially in industrialized nations. Toxic substances
/
amount to over 43,000 different compounds totaling 51 million tons
annually in the U.S. according to a report issued by the Council on
Environmental Quality (1979). These chemicals enter the environment
from all phases of industrial and commercial activity, including extrac-
tion, production, storage, transportation, utilization and disposal. The
"once-through" nature of the production-consumption process with little
waste removal at source imposes a heavy burden on natural systems, which
in the past have been called upon to absorb and assimilate the wastes of
civilization. As a result, many compounds remain in the environment for
long periods of time increasing the chances for exposure to humans and
other components of the biosphere. The human and ecological effects of
many of these compounds are unknown or have been discovered tragically
through accidental contamination.
In accordance with the Toxic Substances Control Act of 1976 (TSCA),
the U.S. Environmental Protection Agency is developing testing standards
for evaluating potential hazards of chemicals before they are manu-
factured and released into the environment. In 1979 methods were pro-
posed for human health-effects testing (oncogenicity, acute and sub-
chronic toxicity, and reproductive teratogenic and metabolic effects);
standards for evaluating ecological effects and environmental fate and
transport have not yet been developed (Council on Environmental Quality
1
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1979), but interest is currently being shown in the use of microcosms
for toxicant screening and predictive model validation (Haque et al.
1980).
The use of microcosms for these purposes is somewhat controversial
due to the uncertainty involved in extrapolating results to natural
conditions. However, when considered as generalized models of eco-
logical processes, small scale microcosms might provide a means for
evaluating gross effects of toxic substances on ecosystems because such
microcosms do mimic certain properties of ecosystems. For example, a
number of studies have demonstrated similarities between temporal pro-
cesses in natural systems and microcosms, including species succession
(Gorden et al. 1969, Kurihara 1978), biomass accumulation (Wilhm and
Long 1969, Odum 1971), net production and community respiration (Beyers
1962, Odum 1971), and radioisotope uptake and distribution (Whittaker
1961, Leffler 1977a). In addition, similar responses have been suggested
in natural and microcosm systems to various perturbations, including
radiation (Ferens and Beyers 1972), temperature (Leffler 1978), heavy
metals (Asmus et al. 1978, Giesy et al. 1979), arsenic (Giddings and
Eddlemon 1978), organic toxicants (Bryfogle and McDiffett 1979, Asmus et
al. 1979), and nutrient enrichment (Wilhm and Long 1969, Fraleigh 1971).
Thus, while quantitative extrapolation of microcosm results is not
currently possible (but see Shirazi 1979), qualitative behavior of
microcosms under controlled laboratory conditions may provide a prelim-
inary basis for evaluating the ecological effects of toxic substances.
The development of standardized testing procedures will require
answers to several important questions, including the following:
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1) Which ecosystem properties are most sensitive or best reflect
ecosystem response to toxicant perturbations?
2) What influence will other environmental variables (e.g., pH,
nutrient enrichment, light intensity, etc.) have on ecological
effects of a toxic substance?
Will ecosystem response be a function of the timing or fre-
quency of toxicant inputs with respect to stages of ecosystem
A ^TT« 1 /NT-»m*»T-» +• O
3)
development?
4) What 'degree of realism (biotic and abiotic complexity) should
be incorporated into microcosms for use in toxicity screening?
In an effort to address these questions and to further evaluate the
potential utility of microcosms as ecological screening tools, we have
conducted a series of experiments in which aquatic laboratory microcosms
were exposed to a toxic substance. Because most of these questions are
important, not only for screening protocol development but for ecosystem
analysis in general, we have designed the experiments to test two
hypotheses which have been developed to explain ecosystem behavior in
response to stress (toxic substances being a specific form of stress).
The experiments were conducted in two phases, each addressing a different
hypothesis.
PHASE I
Odum et al. (1979) have suggested that ecosystems respond to environ-
mental perturbations in a "subsidy-stress" fashion (Fig. 1). At low to
moderate levels of intensity system inputs often act to subsidize or
increase overall system function (e.g., the effects of nutrient enrich-
ment or increase in temperature on productivity). Conversely, high
levels of the same input can stress or decrease system function or
result in development of an entirely different system (replacement).
3
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The overall pattern is a unimodal, bell-shaped curve of system response
along a gradient of increasing perturbation intensity. It also is
hypothesized that relative variance of system response increases mono-
tonically along the perturbation gradient. The response of system
function to a toxic or lethal input is hypothesized to be a stress at
all levels of input. Complicating these general response patterns are
the influences of environmental and developmental gradients, such that
system response to a given level of perturbation might vary with environ-
mental conditions or successional stages. These interactive effects are
especially important considerations for toxicity screening, since test
results will be unavoidably biased by standard testing conditions. An
alternative to single factor experiments (i.e., varying levels only of a
toxicant) might be a multifactor or factorial experimental design which
would allow for consideration of the interaction of several factors
simultaneously.
Phase I of our experiments was designed to test the subsidy-stress
•»
hypothesis and to evaluate the influence of an environmental variable
(nutrient enrichment) on aquatic microcosm response to a toxic substance
(cadmium). The experiment was arranged in a 4 X 4 factorial design with
increasing levels of nutrient enrichment superimposed on increasing
cadmium levels. Of particular interest were the interactive effects of
nutrients and cadmium on several system level variables.
PHASE II
A number of ecosystem studies have suggested that nutrient
output/input ratios are sensitive system level measures of ecosystem
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behavior and stress response (e.g., Woodwell and Whittaker 1968, Borraann
et al. 1974, Jordan and Kline 1972, Rykiel 1977). These studies indi-
cate that the loss of essential elements from ecosystems often increases
significantly after disturbance. Vitousek and Reiners (1975) and Vitousek
(1977) have summarized information from the literature into a set of
hypothesized patterns of output/input behavior for essential and non-
essential elements (Fig. 2). This is called the "biomass increment"
hypothesis, since it suggests that nutrient output is an inverse func-
tion of the rate of biomass production within an ecosystem. Briefly,
the hypothesis is as follows for an essential nutrient: Prior to biotic
colonization of an area nutrient outputs are equal to inputs (barring
abiotic uptake or loss). As biota become established and ecosystem
development proceeds, nutrient output becomes less than inputs due to
biotic uptake and storage in growing tissues. At the time of peak net
ecosystem productivity the ratio of nutrient output/input is at a mini-
mum, thereafter gradually increasing to unity as net productivity ap-
proaches zero at ecosystem maturity (steady state). A pulsed pertur-
bation to the ecosystem (i.e., one time "destructive event") results in
an increase in nutrient output/input followed by secondary succession
and an abbreviated repeat of the initial patterns of productivity and
nutrient uptake. For non-essential elements output/input remains near
unity throughout the entire sequence of events; for limiting quantities
of essential elements deflection of the output/input curve is related to
the degree of limitation.
Efforts to empirically evaluate these patterns in natural eco-
systems have not been conclusive (e.g., Haines 1978, Martin 1979,
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Johnson and Edwards 1979) probably due to long successional time
scales, indistinct ecosystem boundaries and potentially large sampling
errors. Laboratory microcosms provide a partial solution to these
problems and a potential means for evaluating nominal and stressed
ecosystem nutrient flux patterns. For example, Confer (1972) found that
phosphorus output from continuous flow aquatic microcosms decreased
(relative to input) during early succession but increased to approxi-
mately equal input after prolonged operation. The introduction of
snails and ostracods after two months of succession resulted in a signi-
ficant increase in phosphorus output. Evans (1977) showed that elevated
phosphorus inputs into flowthrough marine reef-flat microcosms resulted
in increased ammonia-nitrogen uptake, whereas elevated ammonia-nitrogen
inputs caused increased output of phosphorus, suggesting that ammonia is
toxic to reef-flat communities.
Studies in terrestrial microcosms have shown that systems respond
to heavy metal perturbations with increased outputs of essential
elements (Asmus et al. 1978, Van Voris et al. 1980). However, Giesy et
al. (1979) found no significant changes in nitrate, phosphate and sul-
fate outputs from stream channel microcosms exposed to cadmium; they
suggested that future studies include measures of ammonia and potassium
dynamics as possible indicators of heavy metal stress in microcosms.
In addition to the input-output dynamics of essential elements, the
temporal patterns of uptake and release of toxic elements by ecosystems
is an important consideration for toxicity screening in microcosms and
for ecosystem analysis in general. Little is known of the long term
input-output behavior of toxic elements. Henderson (1975) suggested
6
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that ecosystems must have a finite capacity to accumulate toxic elements
and as that capacity is approached, increasingly greater proportions of
input should appear in system outputs. He proposed that temporal pat-
terns "should fall somewhere between the curves for non-essential, not
accumulated, and limiting elements" (Fig. 2). If this is true, then the
potential for an ecosystem to become a source of (rather than a sink
for) toxic elements increases as the system approaches maturity. Further,
if the accumulation capacity could be estimated a priori, then this
potential might be predictable.
Phase II of our experiments was designed to test Vitousek's (1977)
and Henderson's (1975) hypotheses and to evaluate the utility of
output/input ratios of several elements as indicators of microcosm
response to toxic element (cadmium) perturbations. Several other fac-
tors were incorporated into the experiment to determine: 1) the in-
fluence of pulsed versus continuous toxicant inputs on system response,
2) the effects of toxicant exposure early in succession on system res-
ponse to the same toxicant applied later in succession (i.e., the in-
fluence of system "history" on stress response), and 3) the influence of
nutrient limitation on system response to toxicant exposure. The experi-
ment was arranged in a 2 X 4 factorial design with phosphorus-limited
(N:P = 100) and non-limited (N:P = 10) input regimes superimposed on four
modes of cadmium input (zero input, continuous input, cadmium pulses
early and late in succession, and a cadmium pulse late in succession).
In addition to the objectives discussed above, both experimental
phases were coordinated to provide a comparison between the responses of
static and flow-through microcosms to a toxic substance. To accomplish
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this, both experiments incorporated the same inoculum, microcosm con-
tainers and laboratory conditions, and most of the same response
variables. Due to differences in experimental design, however, rigorous
statistical comparisons between Phase I and II were not possible.
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SECTION 2
MATERIALS AND METHODS
GENERAL
Experimental Design
Phase I and Phase II both consisted of factorial experimental
designs with various combinations of nutrient and cadmium treatments, as
shown in Figures 3 and 4. Phase I employed three replicates per treat-
ment combination (48 microcosms), all arranged in a completely ran-
domized design in the growth chamber. Supporting tables were rotated
every four weeks to minimize variability due to possible gradients of
temperature, light, etc. Phase II employed four replicates per treatment
combination (32 microcosms) arranged in two randomized complete blocks
(two replicates of each treatment combination in each block) in the
growth chamber. These systems remained in place throughout the experiment
because of attached input and output tubing. No significant differences
in light intensity or water temperature were detected between the two
blocks.
Experimental Containers
Polypropylene animal containers 26cm X 20cm X 15cm (with a
seven-liter capacity) were chosen for both experiments based on National
Bureau of Standards data (Struempler 1973) which indicate that this
material does not adsorb heavy metals, and on a preliminary adsorption
experiment which indicated no significant retention of the elements of
interest. Containers were filled to six liters with nutrient solution.
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Experimental Conditions
A 2.8m X 2.8m animal room at the Institute of Ecology, University
of Georgia, was modified for use with the installation of a bank of
40-watt Gro & Show lights with an average intensity of 79-86 (Jeinsteins
-2 -1
cm sec at the water surface, and a twenty-four hour timer set for a
twelve hour light - twelve hour dark cycle. Temperature and humidity
were under thermostatic control through the building system; air temper-
ature varied between 19°C and 30°C. Water temperature varied from 19°C
to 21°C (Phase I) and 19°C to 25°C (Phase II).
Nutrient Medium
The medium used in Phase I was a modified Taub and Dollar (1964)
#36 with the nutrient gradient (Appendix A) spanning a wide range of
concentrations intended to approximate levels found in natural systems,
ranging from oligotrophic to hypereutrophic (Wetzel 1975). Each level
had a nitrogen to phosphorus ratio of ten (N:P = 10). Phase II used two
levels of modified Taub #36 medium (Appendix A), one with a nitrogen to
phosphorus ratio of ten (N:P = 10) and the other with N:P = 100 to impose
phosphorus limitation. This level of Taub #36 was chosen on the basis of
results from Phase I.
Toxic Substance
Cadmium was selected as the toxic chemical for the following
reasons:
1) Cadmium is on the EPA's list of toxic substances of immediate
concern.
10
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2) Cadmium is toxic at some concentration to all organisms
(Bowen 1966).
3) Cadmium possesses physical properties which result in a cer-
tain degree of persistence in aquatic systems.
4) Cadmium concentrations can easily be measured with available
instrumentation.
Cadmium was added in the form of cadmium chloride because of its
solubility even at high concentrations (Giesy et al. 1977). The range
of cadmium concentrations in Phase I (0, 1, 10 and 100 ppb Cd) included
one level below and one level above that of the EPA (1971) recommended
allowable cadmium concentration of 10 ppb in drinking water, and was
chosen to cover the wide range of toxicity levels found for different
aquatic organisms (Warnick and Bell 1969, Patrick et al. 1968, Stapleton
1968).
In Phase II, 10 ppb cadmium was chosen for the continuous input
based on the drinking water standard and on a preliminary study which
indicated that higher concentrations (for example, 100 ppb) severely
depressed system metabolism after only a few weeks of continuous input.
Pulsed inputs were pipetted into appropriate systems to achieve total
concentrations of 100 ppb (day 28), 500 ppb (day 64), 750 ppb (day 100)
and 750 ppb (day 190).
Inoculum
Inoculation of both phases was 50 ml from stock microcosms
originally derived from a natural pond, and self-maintaining in the
laboratory. Cross inoculation among replicates was done during the
11
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first week of each experiment to reduce initial variability and,
thereafter periodic reinoculation from laboratory stock systems was
conducted to provide a continuous input of genetic material. The stocks
contained bacteria, fungi, blue-green algae, green algae, protozoa,
nematodes, annelids, rotifers, ostracods, cladocerans, and copepods.
Community Metabolism
Metabolic activity in both experimental phases was assessed through
net daytime production and nighttime community respiration based on diel
changes of dissolved oxygen concentrations, as measured by the three-point
oxygen method of McConnell (1962). This consisted of a dissolved oxygen
reading taken before the lights went on, a second reading just before the
lights went out and a third reading the next morning before the lights
went on. All measurements were made with a YSI model 54 A oxygen meter
equipped with a self-stirring probe. Net daytime production (Pn) is the
difference between the first and second reading, while nighttime community
respiration (RvJ is the difference between the second and third reading.
Gross production is the sum of P_ and R« and net community production the
difference between PD and R«. Results are presented in terms of net day-
time production and nighttime community respiration in mg CL/1/12 hr.
Corrections for oxygen diffusion were calculated several times
according to McConnell (1962). It was found that diffusion over any
given 12-hour period was generally less than 6% of corresponding P- and R.,
values. Therefore, diffusion corrections were not applied to the data.
This probably resulted in underestimation of both P- and R-,, since
dissolved oxygen concentrations were slightly above saturation during
12
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the day and below saturation at night.
Statistical Analyses
All data analyses were conducted on an IBM 360 computer using
methods from the Statistical Analysis System package (Barr et al. 1979).
Analyses included Means, GLM, and ANOVA (Duncan's Multiple Range option).
The Plot Procedure was used to plot means and 95% confidence bars against
time for most of the variables; overlapping confidence intervals indicated
no significant difference between two values, while non-overlapping
intervals indicated significant differences at p = 0.05. Results of
statistical analyses are presented in Appendix C.
PHASE I
The aquatic systems used in Phase I were static (non-flowing)
systems and ran for 119 days in 1978. Cadmium and nutrient solution
were applied at the time of the first inoculation (day zero).
Sample Collection and Analysis
In addition to net. daytime production and nighttime respiration,
measurements were made of: (1) total biomass (all particulate matter),
(2) plant pigments (chlorophyll a and phaeo-pigments), and (3) taxonomic
composition. All samples were collected as aliquots of suspended matter
following thorough mixing of the microcosms (very little attached growth
occurred). Biomass estimates were based on the change in filter weight
after a 20-ml sample of the microcosm was filtered through a glass fiber
filter. Presample and postsample weight was determined after drying in
13
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an oven (60°C) for 24 hours. Chlorophyll a and phaeo-pigment concentra-
tions were measured as 663 run wavelength absorbance of acetone-extracted
solutions of filtered matter, according to Strickland and Parsons (1968).
Samples for biomass, plant pigment analysis, and production and respira-
tion were taken twice weekly.
Taxonomic composition was quantified when qualitative examinations
of samples indicated a major shift in community structure. The fungal
population density was estimated by plating two dilutions (10 and 10 )
of each microcosm (2 replicates each) onto total fungal media (Shokes
1978) and counting the number of colonies after 60 hours. Bacterial
O /
population density was measured by plating three dilutions (10 ,10 ,
and 10 ) of each microcosm (2 replicates each) onto nutrient agar and
counting the number of colonies after 48 hours. The number of crus-
taceans was determined by counting the number of cladocerans, ostracods,
and copepods in a preserved 18-ml sample from each microcosm.
PHASE II
The aquatic systems in Phase II were flowthrough systems and ran
for 286 days, from April 1979 to January 1980.
Nutrient Flowthrough
Nutrient solution was added in a discontinuous flow: one liter of
solution was dripped in at a rate of one liter/2 hr every two days,
resulting in a turnover time of twelve days. The solution was poured
into a one-liter overhead beaker for gravity feed through tygon tubing,
with flows regulated by a screw clamp. Output from the system was
14
-------
defined as the solution overflowing from the opposite end of the tank
through another tubing into covered collection beakers. Diel variations
in nutrient concentrations were not measured but output samples were
always collected about three hours after dawn for consistency. Poly-
ethylene baffles were installed over the output ports after it was
noticed in preliminary experiments that large and highly variable
amounts of surface growth washed out of the systems with the output.
The baffles probably resulted in greater biomass accumulation than would
otherwise have occurred, and may have lengthened the time required for
the microcosms to achieve steady state conditions.
Sample Collection
Sampling was initially done every six days, with the series of
dissolved oxygen readings taken before each sampling. The sampling
schedule was cut back to every eight days when trends in the data indica-
ted that such an intensive sampling regime was unnecessary in order to
see system response.
Prior to sampling, all microcosms were topped up to 6 1 with
deionized water to correct for evaporative and sample withdrawal losses.
After suspended material had settled, samples of standing water and biota
were collected by scraping a 1-cm wide strip of water surface, side and
bottom material (2% of total surface area), and drawing it with suction
into a 125-ml Erlenmeyer flask. Flasks were then topped up to 75 ml with
water from the water column and stored on ice until analyzed. This
procedure was necessary because of considerable quantities of attached
growth which occurred in the Phase II microcosms. Samples of input and
15
-------
output solutions were collected in 20-ml polypropylene scintillation
vials, acidified with one drop of concentrated HC1, and refrigerated until
analyzed.
Sample Analyses
Standing stock samples were divided into three 15-ml subsamples.
The first 15 ml were filtered through a prewashed and preweighed 0.45 (Jm
membrane filter, which was then dried at 60°C to a constant weight and
used to determine dry weight biomass.
The second 15-ml subsample was filtered through a glass fiber
filter for pigment analysis. The filter was ground by hand in 10 ml of
90% acetone, mixed on a vortex mixer, and extracted overnight in a cold
room. After centrifugation at 2000 rpm for 20 minutes, the absorbance
of the extract was read on a spectrophotometer at 663 and 750 nm before
and after acidification (Strickland and Parsons 1968).
The third 15-ml subsample was preserved with Lugol's solution and
stored for microscopic examination. Microscopic counts were made in
Sedgwick-Rafter counting cells on an inverted microscope according to
standard methods (American Public Health Association 1976). Crustaceans
were counted on the biomass filters with a dissecting microscope.
Input and output solutions were analyzed for NH_-N and NO»-N on a
Technicon AutoAnalyzer according to standard methodologies (American
Public Health Association 1976). Samples for total phosphorus (TP) and
total nitrogen (TN) were digested with an alkaline potassium persulfate
solution according to D'Elia et al. (1977) with minor modifications:
4-ml samples were used due to sample size restriction, and no further
16
-------
dilutions or additions were made after digestion. These samples were
analyzed according to standard Cd reduction methods for NCL-N and the
ascorbic acid method for orthophosphate-phosphorus (PO,-P). Results are
reported in mg NCL-N/1 and mg PO,-P/1.
Cation analyses were run on a Jarrell-Ash Plasma Emission Spec-
trograph (Model No. 750). Standard dilutions of the elements of interest
were run on the instrument to determine the lower detection limits and
account for the matrix effect in the nutrient medium (Appendix B).
Cadmium analyses were conducted on a Perkin-Elmer Model 306 atomic
absorption spectrophotometer equipped with a graphite furnace. Analyses
were run according to procedures recommended in the instrument manual.
17
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SECTION 3
RESULTS
PHASE I
Biomass
Biomass (filterable particulate matter) accumulation over the
experimental period showed a significant increase in response to
nutrient enrichment (p = 0.0001). Values averaged over the entire
experiment indicated that only nutrient level 4 was significantly
different from the others, increasing sharply over level 3 (Fig. 5b).
Successional patterns of biomass accumulation reflect this effect. By
day 60, biomass began to increase rapidly at high nutrient levels (Fig.
7), but less rapidly at the lower levels (Fig. 6). All appeared to
approach a roughly defined upper limit by the end of the experiment
(day 119).
Cadmium, introduced as a single dose at the beginning of the exper-
iment, appeared to cause a slight increase in biomass accumulation (Fig.
5a), but the effect was not significant. There was no nutrient-cadmium
interaction effect on biomass.
Chlorophyll a and Phaeo-pigments
The chlorophyll a response to nutrient enrichment was similar
to that of biomass; a significant (p = 0.0001) increase occurred
only at nutrient level 4 (Fig. 8). In the highly enriched systems,
18
-------
chlorophyll a reached maximum values between days 60 and 90, and then
decreased to lower stable values by the end of the experiment (Fig. 10).
In the nutrient poor systems the pattern was similar but less distinct
(Fig. 9).
Cadmium at 100 ppb resulted in a significant (p = 0.05) increase in
chlorophyll a over systems with no cadmium (Fig. 8). One and 10 ppb Cd
had no effect. A significant (p = 0.01) nutrient-cadmium interaction
effect was indicated by the analysis of variance.
Phaeo-pigment concentrations showed a significant increase due to
nutrient enrichment, but no cadmium or nutrient-cadmium interaction
effect. Phaeo-pigments were present in low concentrations for most of
the experiment but increased toward the end of the experiment in most of
the systems (Figs. 11 and 12).
Community Metabolism
Mean net daytime production was significantly influenced by nutrient
enrichment (p = 0.001). At nutrient level 4, net production was signi-
ficantly elevated over the other nutrient levels (Fig. 13a). Cadmium
had no significant effect on net daytime production (Fig. I4a). A
significant (p = 0.0001) nutrient-cadmium interaction effect occurred
for net daytime production.
Nighttime respiration showed a significant (p = 0.001) increase in
response to nutrient enrichment; again, this effect was significant only
at nutrient level 4 (Fig. 13b). Cadmium treatments resulted in a signi-
ficant (p = 0.05) increase in nighttime respiration (Fig. I4b). The
interaction effect of nutrients and cadmium also was highly significant
19
-------
(p = 0.0001).
Temporal patterns of net daytime production and nighttime respira-
tion are shown for representative microcosms in Figures 15 and 16.
Both reached early peak values around day 30, remained high at nutrient
level 4, and gradually declined at lower nutrient levels.
The P/R ratio showed no response to nutrient enrichment due to the
nearly identical responses of both production and respiration (Fig. 13c).
Cadmium caused a significant (p = 0.05) decrease in P/R due to the signi-
ficant increase in respiration (Fig. I4c). No interaction effect of
nutrients and cadmium was observed for P/R.
Population Densities
Fungal, bacterial and crustacean population abundances all showed
positive correlations (p = 0.01) with nutrient enrichment (Figs. 17,
18 and 19). Cadmium also significantly influenced population densities.
Fungal abundance showed a positive correlation (p = 0.05) with cadmium
(Fig. 17), while bacterial abundance revealed no cadmium effect (Fig.
18). Crustacean abundance abundance was negatively correlated (p =
0.05) with cadmium (Fig. 19); grand means of crustacean density at 10
and 100 ppb Cd were significantly lower than means at 0 and 1 ppb Cd.
PHASE II
Biomass
Time averaged biomass (filterable particulate matter) was signi-
ficantly higher (p = 0.0001) in non-nutrient-limited (N:P = 10) micro-
20
-------
cosms than in phosphorus-limited (N:P = 100) systems. Neither pulsed
nor continuous cadmium inputs significantly influenced biomass accumu-
lation, nor was there a significant nutrient-cadmium interaction.
Temporal patterns of biomass accumulation are shown in Figures 20 and 21
for zero-cadmium controls under both nutrient regimes. The figures
indicate relatively little accumulation in the N:P = 100 systems (Fig.
20), but steady accumulation up to about day 200 in the N:P = 10 systems
(Fig. 21).
Chlorophyll a and Phaeo-pigments
Plant pigment concentrations were significantly greater (p =
0.0001) in the N:P = 1.0 systems than in the N:P = 100 systems and
neither pigment showed a detectable response to cadmium, based on values
averaged over the entire experiment. Chlorophyll a concentrations
increased steadily up to about day 60 in the N:P = 100 systems (Fig. 22)
and then declined to a relatively stable value by about day 130; phaeo-
pigments followed a similar but less distinct pattern (Fig. 24). In the
N:P = 10 microcosms, chlorophyll a values steadily increased to a stable
value around day 150 (Fig. 23), while phaeo-pigment concentrations
(Fig. 25) increased dramatically (but with high variance) around day
150, declining by the end of the experiment (day 286).
Community Metabolisms
Due to the strong interaction effect between nutrients and cadmium,
the two treatments showed no significant main effects on net daytime
production or nighttime respiration, according to our analysis of
21
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variance. Zero-cadmium controls of both N:P = 10 and N:P = 100 treat-
ments reached peak values around day 90 and then declined and oscillated
within a reasonably well-defined operating range for the remainder of the
experiment (Figs. 26a and 30a). Cadmium treatments did cause significant
deviation, depending on nutrient levels and mode of cadmium input.
In the N:P = 10 systems, continuous 10 ppb Cd input had no signi-
ficant effect on net daytime production (Fig. 31a). Pulses of Cd be-
tween days 28-100 caused a delay in peak net production to about day 150
(Fig. 32a). These pulses also lessened the immediate net production
response to the Cd pulse on day 190, as compared to systems not receiv-
ing early Cd pulses (Fig. 33a). However, after a delay of about 30 days
variance in net production increased markedly in the early and late
Cd-pulsed systems (Fig. 32a). Microcosms receiving Cd only at day 190
(Fig. 33a) showed a significant decrease in net daytime production
followed by a prompt (about 25 days) return to the former operating
range.
In the N:P = 100 systems, continuous 10 ppb Cd input resulted in
a dramatic increase in net production around day 110 in two of the
four replicates. This is reflected by the extremely high variance in
Figure 27. Since the responsive microcosms were in the same experi-
mental block, the increased net production may be a result of some
block effect which has not yet been identified. Cadmium pulses between
day 28 and 100 resulted in a highly significant increase in net produc-
tion around day 130 (Fig. 28a). The newly defined operating range was
maintained until the day 190 Cd pulse which resulted in a decrease in
net production followed by a prompt (about 25 days) rebound to the
22
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former level. Phosphorus-limited systems receiving the Cd pulse only
at day 190 (Fig. 29a) showed a time-delayed increase in net production
followed by a gradual (about 50 days) return to the former operating
range.
Patterns of nighttime respiration in response to both nutrient and
cadmium treatments were practically identical to those described above
for net daytime production (Figs. 26b-33b). Differences in magnitude
were reflected in the production/respiration ratio (P/R). In the
N:P = 100 systems P/R was significantly higher (p = 0.0002) than in the
N:P = 10 systems and remained greater than 1.0 more of the time (Figs.
26c-33c). P/R showed no direct cadmium or nutrient-cadmium interaction
effects.
Population Densities
Taxonomic data from Phase II were not analyzed statistically, but
graphical examination of the data revealed interesting trends. Crustaceans
(ostracods and copepods) were generally abundant in N:P = 10 microcosms
(Figs. 34-37), but appeared in the N:P = 100 systems only in the two
highly productive replicates receiving continuous 10 ppb Cd inputs
(Fig. 38). In all cases crustacean populations did not become established
until around day 130 or later.
Effects of cadmium are shown for N:P = 10 systems in Figures 35-37.
Continuous 10 ppb Cd inputs resulted in a delay in initiation of popula-
tion growth, wide oscillations in both ostracod and copepod numbers, and
in lower total numbers of individuals (Fig. 35). Cadmium pulses between
days 28 and 100 occurred before populations became established but
23
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nevertheless caused a delay and oscillations in population growth (Fig.
36). The cadmium pulse at day 190 had marked effects on crustacean
populations. In the previously pulsed systems (Fig. 36) copepod popula-
tions were destroyed just as they began to grow, while ostracod numbers
oscillated and then finally began to grow by day 286. In microcosms not
subject to earlier pulses of cadmium (Fig. 37), the pulse on day 190
brought about extinction of both populations after a few oscillations in
numbers.
Other heterotrophic organisms were enumerated and their population
numbers indicated responses to phosphorus limitation. Relative abun-
dances of rotifers, nematodes, and Paramecium sp. all were distinctly
greater in N:P = 10 than in N:P = 100 systems. Nematode and Paramecium
sp. numbers showed no response to cadmium treatments, but decreases in
rotifer numbers suggest responses to cadmium pulses, especially in the
N:P = 100 systems (Figs. 39 and 40).
Autotroph population numbers showed no response to cadmium, but
showed distinct differences in relative abundance as a result of phos-
phorus limitation. In general, following an early bloom of Chlamydomonas
sp., N:P = 10 systems were dominated by thick surface, side wall and
bottom mats of Ulothrix sp. followed in order of decreasing abundance
by Chlorella sp., Chlamydomonas sp., Lepocinclis sp. and Ankistrodesmus
sp. The N:P = 100 systems, also following an early bloom of Chlamydomonas
sp., were dominated by Chlorococcum sp. followed by Chlorella sp.,
Chlamydomonas sp., Ankistrodesmus sp., Lepocinclis sp. and Ulothrix sp.;
all occurred predominantly on the bottom and, to a lesser extent, on the
sides of the containers. Blue-green algae were rarely observed in any
24
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of the microcosms, probably because of the abundance of available
nitrogen (Schindler 1977).
Chemical Element Dynamics
Concentrations of chemical elements and compounds were measured in
inflowing and outflowing solutions of Phase II microcosms. For each
chemical species, ratios of output/input concentrations were calculated
and plotted against time. Values less than 1.0 indicate accumulation of
the chemical within the system, while values greater than 1.0 indicate
net loss from the system. Of the chemicals studied, boron, calcium,
copper, magnesium, sodium, and zinc had values not significantly dif-
ferent from 1.0 (p = 0.05) throughout the experimental period. Total
phosphorus (TP), total nitrogen (TN), NH--N, NCL-N, manganese, iron and
cadmium all fell significantly below 1.0 (p = 0.05) at some time during
the experiment.
Nitrogen, especially NCL-N, displayed the most interesting behavior
in response to nutrient and cadmium treatments. In the N:P = 100 con-
trol microcosms (Fig. 41) there was little significant retention of
nitrogen in any form, as compared with N:P = 10 controls (Fig. 45).
Continuous 10 ppb Cd inputs had no significant effect on nitrogen reten-
tion in the N:P = 10 systems (Fig. 46), but resulted in significant
uptake in the two highly productive replicates of the N:P = 100 systems
(Fig. 42), again causing a considerable increase in variance. This
increased variance is most apparent for NCL-N and, to a lesser extent,
for TN but is virtually undetectable for NH»-N which differed little
25
-------
from the controls.
Cadmium pulses between day 28 and 100 had little effect on nitro- .
gen retention in the N:P = 10 microcosms (Fig. 47), but resulted in
significant retention of NO -N after day 100 in the N:P = 100 systems
(Fig. 43c). The cadmium pulse on day 190 resulted in a significant but
transient increase in NCL-N output in the latter systems (Fig. 43c)
and an increase in variance in the former (Fig. 47c). Microcosms not
receiving early cadmium pulses responded to the day 190 pulse with a
significant increase in NCL-N output in the N:P = 10 systems (Fig. 48c)
and a significant decrease in NIL-N output in the phosphorus limited
systems (Fig. 44b). The apparent NCL-N response in the latter (Fig.
44c) was not significantly different from the controls (Fig. 4lc).
An analysis of variance of nitrogen outputs averaged over the
entire experiment indicated a highly significant nutrient-cadmium inter-
action effect for TN (p = 0.0001), NHg-N (p = 0.005), and NCyN
(p = 0.0001). As a result, no significant main effects of cadmium were
detected by the analysis. Averaging the data over time obliterated the
temporal dynamics which indicated significant short term cadmium- effects
(Figs. 41-48).
The output/input ratio for total phosphorus (TP) was less res-
ponsive to nutrient and cadmium treatments than were the nitrogen
ratios. In addition, TP showed much higher variability, especially in
the N:P = 100 systems, since output concentrations were often near
detection limits. Control microcosms with inputs of both N:P = 100
and N:P = 10 (Figs. 49a and 53a) showed initially rapid uptake of TP
followed by a gradual approach to output/input not significantly
26
-------
different from 1.0 around day 110. Phosphorus limited systems (Fig.
49a) then displayed roughly defined oscillations below and just equal
to 1.0 for the remainder of the experiment. The ratio remained below
1.0 for most of the experimental period in the N:P = 10 systems (Fig.
53a). Retention of TP showed no detectable response to cadmium treat-
ments in the N:P = 100 systems (Figs. 50a, 51a, and 52a). N:P = 10
systems displayed general trends in response to cadmium but few were
clearly significant. Continuous 10 ppb Cd inputs resulted in greater
overall TP retention (Fig. 54a) than was shown by the controls (Fig.
53a). Early cadmium pulses (Fig. 55a) appeared to cause an increase
in TP output, while the pulse at day 190 resulted in a slight decrease
in output in these, and in the systems not subjected to early cadmium
pulses (Fig. 56a). In g'eneral, cadmium may have resulted in slightly
greater TP retention but the effect was not significant at p = 0.05,
according to an analysis of variance. Also, no nutrient-cadmium inter-
action effect was indicated.
Somewhat surprisingly, output/input ratios for manganese showed
significant responses to cadmium treatments. Control microcosms under
both nutrient regimes showed no accumulation of Mn (Figs. 49b and 53b).
Continuous 10 ppb Cd inputs in the N:P = 100 systems (Fig. 50b) resul-
ted in an increase in variance among replicates, beginning around day
100 (again, apparently due to some block effect). Continuous cadmium
inputs had no measurable effect on Mn retention in the non-limited
systems (Fig. 54b). Cadmium pulses between days 28 and 100 resulted
in increased variance and significant Mn retention under both nutrient
regimes (Figs. 51b and 55b).. In the N:P = 10 systems the effect was
27
-------
transient, followed by a brief net system loss of Mn around day 170
and then a slight gain, in response to the cadmium pulse on day 190.
In the N:P = 100 systems (Fig. 51b) Mn continued to accumulate until
the day 190 cadmium pulse which resulted in a gradual (about 40 days)
increase in the output/input ratio to 1.0. N:P = 100 microcosms pulsed
with cadmium only at day 190 showed no response with respect to Mn
retention (Fig. 52b). Corresponding N:P = 10 systems (Fig. 56b) showed
a considerable increase in variance but no significant gain or loss
of Mn.
No detectable nutrient effect on iron output/input behavior was
indicated (Figs. 49c-56c) but there was an apparently significant res-
ponse to the cadmium pulse on day 100 in the N:P = 10 systems (Fig.
55c): After an initial period of accumulation similar to the control
microcosms (Fig. 53c), the cadmium-pulsed systems continued to retain Fe
until about day 150, followed by a brief period of net system loss. The
cadmium pulse on day 190 (Fig. 55c) seems to have caused an increase in
variance but little deviation from output/input = 1.0. Iron retention
showed no measurable response to cadmium treatment in the N:P = 100
systems.
Output/input ratios were calculated for cadmium in the microcosms
receiving continuous 10 ppb Cd inputs. Significant cadmium retention
occurred in both the N:P = 100 and N:P = 10 systems (Figs. 57a and 57b),
reaching greater total accumulation in the latter. Both displayed an
inverse bell-shaped retention curve, approaching output/input = 1.0
toward the end of the experiment (day 286), but accumulation continued
in the N:P = 10 systems (Fig. 57a). Cadmium output/input ratios were not
28
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calculated for systems receiving cadmium pulses, but in each case cad-
mium concentrations in the output followed an exponential decay curve
over time, related to the system turnover time of 12 days.
29
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SECTION 4
DISCUSSION
PHASE I
Nutrient Effects
One objective of Phase I was an empirical evaluation of the
"subsidy-stress" hypothesis (Odum et al. 1979). That hypothesis pre-
dicts that a gradient of increasing levels of a "usable" system input
(e.g., nutrient enrichment) will result in a bell-shaped curve of system
response defined in terms of energy flow (community metabolism). Thus,
high levels of enrichment should act as a stress, depressing system
performance. The nutrient gradient employed in Phase I (0.10/0.01,
0.5/0.05, l.O/.l and 10/1 ppm N/P) ranged from oligotrophic to hyper-
eutrophic (Wetzel 1975). As shown in Fig. 13a and b, only the highest
nutrient level caused a significant increase in net production and
community respiration, at best only approaching the left shoulder of a
subsidy stress curve. The P/R ratio showed no significant nutrient effect
because of the simultaneous increase in net production and community
respiration. Therefore, these results are inconclusive but suggest that
the highest level may have approached a level of maximum performance.
Extremely hyper-eutrophic conditions (more so than in this experiment)
have been shown to depress production and respiration in microcosms. For
example, Butler (1964) found that 88.0/35.0 ppm N03/P04 resulted in lower
2
net production and respiration values (0.61 and 0.56 g C0?/m /12 hr,
respectively) than did NO/PO = 44.0/18.0 ppm (P =1.22 and R = 1.25
D . N
2-
2-
g CO /m /12 hr) . Likewise, Wilhm and Long (1969) showed a slight depres-
2
sion in microcosm metabolism (P., = 1.09 and RN = 1-H g C0_/m /12 hr)
30
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at NCL/PO^ = 120/20 ppra as compared to NCL/PO^ = 12/2 ppm (P =1.12 and
2
TL, - 1.13 g CCL/m /12 hr). As in the present experiment, P/R showed no
notable response to nutrient enrichment in these studies.
Most of the other variables measured in Phase I showed positive
correlations with nutrient enrichment, none suggesting a stress response
at the highest nutrient level. Concentrations of chlorophyll a,
phaeo-pigments, and biomass, and the abundance of fungi, bacteria and
crustaceans all increased with increasing nutrient concentrations.
Cadmium Effects
Odum et al. (1979) also predicted that toxic or lethal system
inputs will have no subsidizing effect; such inputs are hypothesized to
depress system performance at all levels of input, although it is known
that low concentrations of some toxins have a stimulating effect on
organisms. The cadmium gradient in Phase I covered three orders of
magnitude (0, 1, 10 and 100 ppb), with the highest level well above
accepted standards for aquatic ecosystems. Net daytime production
showed no detectable response to cadmium, while nighttime respiration
showed a significant increase (p = 0.05). This translates into a de-
crease in P/R in response to cadmium (Fig. I4a) and indicates an in-
crease in energy flow through heterotrophic system components. Over
prolonged periods this would result in destruction of the system. Thus,
using P/R as a measure of ecosystem performance, our results support the
subsidy-stress hypothesis with respect to toxic substance (cadmium)
inputs. Furthermore, in Phase II, cadmium pulses often resulted in a
considerable increase in variance among replicates (e.g., Figs. 32, 47,
31
-------
55 and 56), also in accordance with the hypothesis.
The significant increase in chlorophyll a with increasing cadmium
concentration (Fig. 8a) can most likely be attributed to the decrease in
crustacean grazers. Cadmium at 100 ppb virtually eliminated the crus-
.taceans (Fig. 19), and resulted in the highest chlorophyll a concentra-
tions. The toxic effect of cadmium on crustaceans has been noted pre-
viously by Marshall and Mellinger (1980) and Eiseler et al. (1972).
One explanation for the increase in chlorophyll a concentration is that
reduced grazing allowed algal cells to remain in the water column
longer, thereby increasing the standing crop of chlorophyll. The fact
that chlorophyll and net daytime production were not-positively cor-
related indicates that, while cadmium may not be as lethal to the algae
as it is to the animals, it does reduce the rate of photosynthesis per
unit of chlorophyll. The assimilation ratio (net daytime production/
chlorophyll a) at 10 and 100 ppb Cd was roughly half the value at 0 and
1 ppb Cd. As uneaten algae cells died, they contributed to the detri-
tal food chain resulting in relatively large numbers of decomposers
(especially fungi) and an increase in community respiration.
Interaction of Cadmium and Nutrients
Significant interaction effects between cadmium and nutrient enrich-
ment were exhibited for net daytime production, nighttime respiration,
and chlorophyll a. The effect resulted in an increase in each variable.
No interaction was indicated for phaeo-pigments, biomass and population
densities.
A major interactive effect appeared to result from a synergistic
32
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augmentation of cadmium and nutrient effects at the highest extreme of
each treatment. Cadmium had a greater stress effect on the herbivore
trophic level than on the autotrophic or saprotrophic levels. Accordingly,
the main effect of cadmium on the ecosystem as a whole was an alteration
in trophic structure. A decrease in primary consumers or grazing
animals apparently resulted in an increase in the standing crop of
producers (algae) and decomposers (fungi), and this was reflected in
increased community respiration. In effect, the system responded to
cadmium perturbation by switching from a grazing to a detritus food
chain. The persistence of crustaceans in the highest nutrient-highest
cadmium levels suggests that nutrient enrichment may reduce the toxic
effects of cadmium.
Stress and Ecosystem Performance
Interpretation of the above results emphasizes the importance of
the definition of "stress" with respect to ecosystems. Barrett et al.
(1976) and Leffler (1977) consider ecosystem stress to be any externally
induced response which deviates from the system's normal pattern of
behavior. Odum et al. (1979) define "stress" as any negative deviation,
and "subsidy" as any positive deviation from the normal operating range
of system performance. System performance is defined in terms of energy
flow through the system (e.g., productivity), and the effect of a pertur-
bation is interpreted as a reduction (subsidy) or increase (stress) in
"maintenance cost or ... overall [system] function." Rather than pro-
ductivity or respiration alone, the relationship between the two (i.e.,
P/R) is probably the best measure of energetic maintenance cost to the
33
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ecosystem, and therefore, an indicator of subsidy or stress.
In terras of P/R, nutrients had no effect on system performance at
the levels of enrichment used in Phase I, or those used by Butler (1964)
and Wilhm and Long (1969). Much higher levels are apparently necessary
to evaluate the subsidy-stress hypothesis with respect to nutrients.
Cadmium, on the other hand, caused a significant decrease in P/R, as
predicted by the hypothesis. A similar effect was noted by Giddings and
Eddlemon (1978) for arsenic perturbations in aquatic microcosms; P/R
was negatively related to As concentration. Both studies suggest the
existence of toxicity thresholds for Cd and As, respectively, since the
lowest concentrations studied (1.0 ppb Cd and 66 ppb As) had no detect-
able effect on P/R.
PHASE II
Two distinct perspectives underlie biogeochemical studies of eco-
systems. The first focuses on the influence of ecosystem dynamics on
patterns of chemical element behavior, particularly input-output be-
havior as a function of ecological succession and perturbation response.
This is the context of several recent studies of large scale ecosystems
(e.g., Rykiel 1977, Woodmansee 1978, Borman and Likens 1979). The
second perspective focuses on the behavior of ecosystems in response to
chemical element perturbations, such as increased nutrient loading or
inputs of toxic substances. This view is the basis for studies of
eutrophication and environmental toxicology. Both perspectives are
essential for an understanding of the interactions between ecosystems
and their input and output .environments. The following discussion
34
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considers results from Phase II from both perspectives.
Element Dynamics as a Function of Ecosystem Behavior
Vitousek (1977) proposed a family of curves representing temporal
patterns of ecosystem output/input for essential (limiting and non-
limiting) and non-essential elements (Fig. 2). These curves are pro-
jected as the inverse of net ecosystem production, (or biomass increment
in the development or succession of the ecosystem). The magnitude
of deflection is viewed as being a function of the degree to which an
element is limiting. Any disturbance severe enough to reduce net produc-
tion is proposed to result in a corresponding reduction in element
retention, since there will be a reduction in rate of incorporating
elements into biomass, again depending on the degree of element limita-
tion. Our results generally confirm these trends.
Outputs of boron, calcium, copper, magnesium, sodium and zinc, all
essential but in excess of biotic demand, remained equal to inputs
throughout the experiment. Output curves for nitrate-nitrogen (Figs.
4lc-48c), also essential but more nearly limiting, were practically
mirror images of the corresponding net daytime production curves (Figs.
26a-33a), with the exception of the initial 60-day lag in NO--N uptake
in N:P = 10 systems (Figs. 45c-48c). Thus, nitrate was retained by the
system during periods of high productivity. Ammonia-nitrogen displayed
rapid uptake within these microcosms during the same period, suggesting
preferential utilization of NH,,-N by the early bloom of Chlamydomonas sp.,
followed by additional utilization of NO--N by the later bloom of Ulothrix
sp. Since NO -N output responded significantly to cadmium treatments in
35
-------
the absence of any NH_-N response, cadmium may have selectively inhibited
NCL-N metabolism (autotrophic and heterotrophic). In N:P = 100 systems
(Figs. 4lb-44b), NH,-N was accumulated in all cases, while NCL-N showed
significant retention only after a bloom of Chlorococcum sp. which followed
the cadmium pulses between days 28 and 100 (Fig. 43c). The cadmium pulse
on day 190 resulted in a significant increase in NCL-N output. These
results again suggest 1) preferential NEL-N utilization but with NCL-N
supporting population blooms, and 2) cadmium inhibition of NCL-N uptake.
Outputs of manganese and to a lesser extent, iron (Figs. 49b and c
to 56b and c) were roughly inverse to net production (Figs. 26a-33a),
especially in response to cadmium pulses. These patterns suggest that
both elements were present in excess of biotic demand much of the time
but approached limiting concentrations during population blooms.
Total phosphorus (in the form of PO/-P in the inputs) showed rapid
initial uptake in all microcosms (Figs. 49a-56a), preceding peak metabolic
activity by about 60 days. In the N:P = 100 control systems (Fig. 49a),
TP gradually increased in concentration in the output solutions to nearly
equal input concentration (0.06 ppm) by about day 100. Since very
little nitrogen was accumulated during this period (Fig. 41) phosphorus
may have been sequestered through luxury consumption (by autotrophic and
heterotrophic organisms) and utilized later during peak activity, thus
reducing the uptake of new phosphorus inputs. After day 110 TP outputs
again fell below input levels, but in the absence of any change in net
daytime production (Fig. 26a). This may have resulted from an exhaus-
tion of the phosphorus accumulated earlier. Interestingly, the large
changes in net daytime production which followed cadmium pulses (Fig.
36
-------
28a and 29a) caused only small deviations from the TP output patterns
just described. This suggests that the phosphorus accumulated early in
succession was sufficient to sustain a large amount of metabolic
activity. In addition, it indicates that phosphorus was strongly re-
tained within the systems even after major disturbances. The exact
mechanism of this retention has not been identified, but may be the
result of efficient recycling between heterotrophic and autotrophic
organisms which often occur in intimate contact in particulate
aggregates in microcosms (Kurihara 1978).
Retention patterns for all of the elements discussed above gener-
ally support Vitousek's (1977) proposal (Fig. 2) with two possible
exceptions. First, maximum uptake of all essential elements studied did
not coincide with maximum metabolic activity, as discussed above for
phosphorus. Luxury consumption may have been responsible for the early
occurrence of maximum phosphorus retention, and might be expected to
occur for other essential, limiting elements as well. Second, distur-
bances (i.e., cadmium pulses) which caused significant changes in meta-
bolic activity, were not reflected most strongly in the retention pat-
terns of the element most limiting in. system inputs (i.e., phosphorus).
Outputs of NCL-N, present in abundance relative to phosphorus, showed
the strongest disturbance response, possibly as a result of selective
cadmium effects on nitrogen metabolism. Since Vitousek's (1977) ideas
were developed for terrestrial watershed ecosystems subject to variable
nutrient inputs and other environmental conditions, and to rather dras-
tic "destructive events" (i.e., clearcutting or fire), our evaluations
may not be entirely valid. Also, it should be noted that our estimates
37
-------
of ecosystem productivity are based on calculations of net daytime
production of oxygen. Net ecosystem production (the difference between
net daytime production and nighttime respiration, or the slope of the
biomass accumulation curves) is currently being studied for a more
complete evaluation of the hypothesis.
Henderson (1975) proposed the existence of a finite capacity for
ecosystem accumulation of toxic substances. He suggested a temporal
output/input curve somewhere between non-essential and essential, limit-
ing elements in Vitousek's (1977) scheme (Fig. 2). Our data provide a
preliminary evaluation of this idea for cadmium. Figure 57 shows cad-
mium retention patterns for microcosms receiving continuous 10 ppb Cd
inputs under both phosphorus-limiting and non-limiting conditions. The
curves indeed support Henderson's hypothesis and suggest further that
overall cadmium accumulation is a function of productivity. In the less
productive systems (Fig. 57), cadmium outputs approached input levels by
the end of the experiment (286 days), while the more productive systems
continued to accumulate cadmium. Since inorganic sediments were not
present in the microcosms, cadmium must have been retained or stored in
the biomass but it is not possible to tell from these data whether the
mechanism was active biochemical uptake by living cells or sorption
onto detrital materials. Both processes have been shown to occur for
cadmium (Khalid et al. 1977,'Sarsfield and Mancy 1977).
Ecosystem Behavior as a Function of Element Dynamics
The observations discussed above reflect the influence of eco-
logical processes on the dynamics of essential elements. In general,
38
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outputs of essential elements in shortest supply relative to demand (N,
P, Mn, Fe) responded most strongly to successional and disturbance-
induced changes in ecosystem behavior. Ecosystem behavior, in turn, was
largely a function of alterations in the chemical nature of system
inputs. The effects of these alterations (phosphorus limitation and
cadmium inputs) are discussed below.
A further aspect of the problem of toxic substance accumulation in
ecosystems is the ultimate effect of the toxicants on ecological pro-
cesses. In Phases I and II of this work, we have indicated that cadmium
seems to most strongly affect grazing herbivores, thus altering trophic
structure and changing overall ecosystem behavior. These effects re-
sulted from relatively large concentrations of cadmium (100 ppb Cd in
Phase I and 750 ppb Cd in Phase II). However, small concentrations
accumulating over longer time periods might be expected to have similar
effects, particularly if some threshold toxic concentration is achieved.
Such an effect may have occurred in two of the four replicate N:P = 100.
An abrupt and highly significant increase in net production (Fig. 27a),
community respiration (Fig. 27b), and NO--N uptake (Fig. 42c) occurred
around day 100 in these systems after a total input of approximately
500 (Jg of cadmium By day 100 very little of the inflowing cadmium had
accumulated within the systems (Fig. 57.a); in fact this point marks the
beginning of significant cadmium accumulation. If a threshold response
did occur it resulted from relatively low concentrations of cadmium.
For reasons which are not clear, the other two replicates failed to
display this behavior and we thus are unable to make an evaluation.
Further research will be required to clarify the existence and quan-
39
-------
titative nature of toxicant accumulation thresholds. The N:P = 10
systems (Fig. 58) accumulated considerably more cadmium than the N:P =
100, but showed no detectable response, suggesting that cadmium was
immobilized within the systems.
Schindler (1977) suggested that phosphorus is the single most
important essential element directing the behavior of aquatic eco-
systems, since it is more often scarce, relative to biotic demand, than
other elements. This idea is substantiated by the success with which
biotic activity can be predicted from phosphorus loading models (e.g.,
Dillon and Rigler 1974). In the Phase II experiment, phosphorus limita-
tion significantly influenced all of the variables measured, causing
reductions in biomass, plant pigments, community metabolic activity and
nutrient retention, and alterations in community structure. Of perhaps
greater interest is the fact that these manifestations also influenced
system responses to cadmium perturbations (i.e., significant nutrient-
cadmium interaction effects). In general, N:P = 100 microcosms were
more sensitive (in terms of net daytime production, nighttime respir-
ation and nutrient accumulation) to cadmium treatments than the N:P = 10
systems. This observation agrees with Pomeroy's (1975) hypothesis that
ecosystem stability is a function of the availability of essential
elements. With respect to toxic substance perturbations, this could be
due to immobilization of toxicants in dead organic matter, which is
usually abundant in eutrophic systems, or to the dominance of generally
euryaceous organisms under nutrient rich conditions. Both mechanisms
are likely to contribute to ecosystem stability in any given situation.
The response of an ecosystem to any perturbation will be influenced
40
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by the developmental history of the system (Leffler 1978). Thus,
systems frequently exposed to a particular type of disturbance may
develop a degree of resistance to that disturbance through selection for
resistant organisms. Some ecosystems have actually become dependent on
environmental perturbations for maintenance of structural and functional
integrity (pulse-stability sensu Odum 1969). Examples include fire
maintained forests and tidal-pulse maintained salt marshes. We have
attempted to determine if developmental history (in terms of cadmium
exposure) might influence the resistance of an ecosystem to toxic sub-
stance perturbations.
In the N:P = 100 systems, early cadmium pulses resulted in signi-
ficant increases in net daytime production (Fig. 28a), nighttime res-
piration (Fig. 28b), and uptake of N03~N (Fig. 43c) and Mn (Fig. 51b).
Thus, by day 190 these systems were significantly different from those
not receiving the early cadmium pulse. The cadmium pulse on day 190
produced different responses in the two types, but the differences were
not as expected. The previously pulsed microcosms showed an immediate
but transient decrease in metabolic activity (Fig. 32), and an increase
in output of NCL-N (Fig. 43a'), and Mn, (Fig. 51b), while the previously
unpulsed systems responded with a gradual, but long-lived increase in
metabolic activity (Fig. 29) and NH»-N uptake (Figs. 44b). Interestingly,
the latter response was qualitatively similar to the initial cadmium res-
ponse of the early-pulsed systems, both showing an increase in net
daytime production and nighttime respiration. In Phase I, this effect
was attributed to the release of primary producers from grazing pressure
due to the decline in macroinvertebrate herbivores (crustaceans). In
41
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the present case, macroinvertebrate grazers were never abundant, but
microinvertebrates (primarily rotifers) may have served the same func-
tion. In fact, total rotifer numbers declined considerably following
early cadmium pulses (Fig. 39) and the single, day-190 pulse (Fig. 40).
Since the algal community in these systems consisted primarily of small
unicellular forms (e.g., Chlorococcum sp., Chlorella sp. and Chlamydomonas
sp.) potentially available to rotifers, the altered trophic structure
explanation of system-level cadmium response seems plausible. Marshall
and Mellinger (1980) report the same effect in toxicity studies in a
Canadian shield lake. However, altered trophic structure alone does not
account for the observed decrease in metabolic activity and increase in
nutrient output following the cadmium pulse on day 190 in the previously
exposed systems (Figs. 28 and 43). Rotifer numbers showed no response
(Fig. 39) suggesting selection for cadmium resistant strains after the
earlier pulses. Cadmium appears to have directly inhibited metabolic
activity of primary producers, and perhaps heterotrophs as well, but
with no detectable change in community structure. It is possible that
when cadmium was first added, removal of grazers was the dominant factor.
Later, after grazers had developed cadmium resistance, photosynthetic
inhibition may have been more important (Jeff Giddings, personal communi-
cation) . It is not clear from these data why phosphorus limited systems
were more sensitive to cadmium than non-limited systems.
In the N:P = 10 systems (Fig. 32a) early pulses of cadmium resulted
in a delay, but no significant increase, in peak metabolic activity over
controls (Fig. 30a). The cadmium pulse on day 190 caused a slight, but
not significant decrease in net daytime production and nighttime respira-
42
-------
tion followed by a large increase in variance among the replicates
approximately 20 days later (Fig. 32a). In the previously unpulsed
systems the day-190 cadmium pulse resulted in a significant but transient
decrease in community metabolism (Fig. 33) and increase in NCL-N output
(Fig. 48c). It is suggested that the large pulse of cadmium directly
affected primary production as well as heterotrophic activity, thus
depressing overall system metabolism.
In general, then, early cadmium pulses appeared to increase system
resistance to later pulses in the N:P = 10 systems, and decrease resis-
tance but increase resilience (sensu Waide et al. 1975) to later pulses
in the N:P = 100 systems. The fact that ostracod numbers (Figs. 36 and
37) eventually rebounded from, and rotifer numbers (Figs. 39 and 40) were
apparently unaffected by the day-190 cadmium pulse only after previous
exposure to cadmium, supports the idea of increased stability due to
selection for cadmium tolerant organisms.
43
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SECTION 5
COMPARISON OF STATIC AND FLOWTHROUGH MICROCOSMS
Nutrient Treatments
Data from the Phases I and II experiments are summarized in Table I
to provide a gross comparison between selected attributes of static and
flowthrough microcosms not subjected to cadmium treatment. Phase I
preceded Phase II and was run by different personnel, but both experi-
ments were conducted in the same growth chamber under similar environ-
mental conditions. In addition, all microcosms were established in
identical containers, in the same basic medium (quantitatively modified
for nutrient manipulations) and inoculated from the same laboratory
stock microcosms. In Phase II the containers were equipped with input
and output tubing to allow for flowthrough of the nutrient solution.
For comparision, data in Table 1 are from control microcosms (i.e., no
cadmium treatment) at nutrient levels two (N:P=0.5/0.05) and four
(N:P=10.0/1.0) in Phase I, and phosphorus-limited (N:P=6.2/0.06) and
non-limited (N:P=0.2/0.02) systems in Phase II. Values for biomass,
chlorophyll a, phaeo-pigments, net daytime production and nighttime
respiration were averaged over the last 1/3 of each experimental period
so that approximately steady state conditions could be compared. For
the static systems this represents days 77-119 and for the flowthrough
systems, days 198-286. All other variables were calculated from these
data, as indicated. Many of the values showed considerable variability
as reflected in large standard deviations. Because of this and
differences in experimental design, statistical comparisons were not
made. However, these data provide the closest possible comparison,
44
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T.ihlo I. Comparison of nutrient clt'rcls on slat it: ;intl f lowllirtmgh microcosms.
,„,;,
Sl.il. if Uicrorosiiis Klowlhroii)
ili: Low NiiLrifiil ' High NnLriuiil. 3 Low Phos|i|iorous J
{0.5/6.05) Ho/i) (6.2/0.065
Ilionuiss 4H(66) 2)'i(121)) 40(18)
Chlorophyll .1 (Chi) 0.01(0.03) 0.81(0.70) (1.13(0.06)
Ph.,o
-|iigmnnl s (I'h.i) 0.10(0.12) 0.60(1.53) 0.09(0.04)
Nel Diiytiuii! Pio,liu-li..u (P()) 0.92(0.76) 1.71(0.77) 0.65(0.28)
-,h Mi croroRms*"
lljf;h Phosjihoroi
867(327)
2.97(1.17)
2.23(2.61)
2.60(0.37)
NinhLI inn- Kcspir.itimi (K..) 0.66(0.38) l.57(0..r>8) 0.57(0.36) 2.42(0.45)
N
V"N
(Iross
Net C
1',/B
yci,
Chi /I)
1.39 1.09 1.14
d it ft
inuiiiiiiily Pro.hiclii.ii (I'.."!'..-!)..) 0.26 0.14 0.08
NUN
0.03 0.01 0.03
.10 .67 2.11 1 . 00
0 . 0006 0 . 0(13 0 . 003
Chl/Plia 0.30 1.35 1.44
i
1.07
5.02
0. 18
0.006
0.88
0.003
1.33
t\ II v.'ilurs nvor;*j>rhy 1 1 :i .mil |i|i;>no- pixmriit. s in mg/ 1 ; nrl. il;iyliinc |iro
-------
based on levels of phosphorus enrichment.
In general, the low phosphorus systems of both types behaved
similarly with respect to community metabolism (P_ and RW) and biomass
accumulation. This is surprising since by day 286 the flowthrough
systems had accumulated roughly 3 mg P, compared to 0.3 mg P which is
the total amount which could have been taken up in the static systems.
This suggests that the static systems operated at much higher efficiency
(ie., on 10 times less phosphorus) than the flowthrough systems.
Higher efficiency in the static systems is also indicated by higher
values for net community production and for Pn/Chl (the assimilation
ratio) which suggests greater oxygen production per unit chlorophyll.
These observations imply relatively greater recycling of phosphorus in
the static than flowthrough micocosms. The flowthrough systems appeared
to have higher chlorophyll a concentrations and consequently, higher
value for chlorophyll a/biomass and chlorophyll a/phaeo-pigments.
In the high phosphorus systems, most of the variables showed higher
values in the flowthrough than in the static systems. In this case,
roughly 60 mg P had accumulated in the flowthrough microcosms compared
to, at most, 6 mg P in the static systems. The higher assimilation
ratio in the static microcosms again indicates greater efficiency in
these systems.
It is interesting that a 10 to 20-fold increase in phosphorus
resulted in only a two to four-fold increase in net daytime production and
nighttime respiration in both static and flowthrough systems. It would
appear that some other factor was limiting to metabolic activity at the
high levels of enrichment, (perhaps some other nutrient, or light
46
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penetration through thick algal mats) or that phosphorus was immobilized.
Finally, a notable difference between the static and flowthrough
systems was in the timing of peak metabolic activity. Nutrient flow-
through resulted in peak net daytime production and nighttime respiration
around day 90 (Fig. 26 and 30), compared to around day 30 in the static
system (Figs. 15 and 16). This represents a difference of about 60 days
or roughly a three-fold expansion of time scales of activity. The
magnitude of expansion might be a function of system turnover time,
which in this case was 12 days.
To summarize, static microcosms appeared (1) to operate at higher
efficiency in terms of assimilation ratios and metabolic activity per
unit phosphorus, and (2) complete development over shorter time scales
than flowthrough microcosms. Phosphorus enrichment in both system
types increased net daytime production and nighttime respiration but not
in a linear fashion; at high levels of enrichment some other factor
appeared to be limiting to community metabolism. Phosphorus enrichment
also lowered net production efficiency, in terms of assimilation ratios,
in both static and flowthrough systems.
Cadmium Treatments
Table 2 presents a summary of cadmium effects on static versus flow-
through microcosms. The format is similar to that of Table 1 with
respect to nutrient treatments. Static systems represented are the 10
ppb Cd and 100 ppb Cd treatments at nutrient levels two (N:P=0.5/0.05)
and four (N:P=10.0/1.0). Flowthrough systems are the continuous 10 ppb
Cd input treatments under phosphorous-limited (N:P = 100) and non-limited
47
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Table 2. Comparison of cadmium effects on static and flnwllirough microcosms.
I
CD
Static Microcosms
Flowthrough Microcosms
Variable
Cadmium Accumulated
Hiomass (II)
Chlorophyll -a (Chi)
Phaeopigments (pha)
Net Daytime Production ((*)
Nighttime Respiration (Ru)
rl
VRN
Cross Production (P,,=P.,*RU)
O If N
Not Community Production (PU=I'-R«)
ft U tf
Chl/B
Chi /Mia
Low Nuti
(0.5/0
IQppliCd
60
67(41)
0.15(0.11)
0.04(0.06)
1.10(0.72)
0.82(0.32)
1.34
1.92
0.28
0.03
7.33
0.002
3.72
rient
.05}
""ToOnjdiCd
600
72(45)
0.15(0.14)
0.05(0.12)
0.82(0.46)
0.69(0.25)
1.19
1.51
0.13
0.02
5.47
0.002
3.00
High Nutrient
(10. O/
IQppbCd
60
246(156)
0.80(0.81)
0.14(0.26)
1.69(0.72)
1.58(0.59)
1.07
3.27
0.11
0.01
2.11
0.003
5.71
lOOppbCd
600
246(105)
1.61(1.25)
0.43(1.09)
1.79(0.75)
1.65(0.58)
1.08
3.44
0.14
0.01
1. 11
0.65
3.74
Low Phosphorous
(6.2/0.06)
IQppbCd
300
89(49)
0.29(0.29)
0.16(0.15)
2.10(1.02)
1.94(0.98)
1.08
4.04
0.16
0.05
7.24
0.003
I.BI
High I'hosphori
^llJf
600
835(369)
2.63(1.67)
3.92(3.80)
2.52(0.70)
2.29(0.57)
1.10
4.81
.23
0.006
0.96
0.003
0.67
-All values averaged over days 77-119.
All values averaged over day 198-286.
' mgN/mgP in nutrient medium.
Note: Cadmium accumulation in |ig Cd/61 microcosm; biomass, chlorophyll a and phaeo-pigments in mg/l;
net daytime production and nighttime respiration in mg 02/1/12 lirs.; standard deviations in parentheses.
-------
(N:P = 10) conditions. By the end of the experiment the N:P = 100
microcosms had accumulated roughly 300 |Jg Cd, while the N:P = 10 micro-
cosms had accumulated approximately 600 pg Cd. This compares with 60 (Jg
Cd and 600 |Jg Cd, the maxiumum which could have been taken up in the
10 ppb Cd and 100 ppb Cd treated static microcosms, respectively.
Values shown in Table 2 are averages over days 77-119 in the static
systems, and days 198-286 in the flowthrough systems (as in Table 1).
A comparison of data in Tables 1 and 2 reveals several general
trends. In the static microcosms the most notable cadmium response is
reflected in chlorophyll a concentrations and secondary variables which
include chlorophyll a (PD/Chl,Chl/B and Chl/Pha). This observation is
supported by data presented earlier (Fig.8). Chlorophyll a in the high
nutrient static systems showed the greatest response to 100 ppb Cd, while
the low nutrient static system responses to 10 ppb Cd and 100 ppb Cd were
indistinguishable for all variables. This reemphasizes the interactive
effects of high nutrient-high cadmium concentrations discussed in
Section 4. In contrast, only the low phosphorus flowthrough microcosms
showed a noticeable cadmium response and this was in terms of net day-
time production, nighttime respiration and the related secondary
variables. The high phosphorus flowthrough systems showed no
detectable response.
From these observations, we are unable to draw any firm conclusions
with respect to relative sensitivities of static and flowthrough micro-
cosms. It would appear (although tenuously) that low nutrient static
systems showed detectable responses to relatively less accumulated
cadmium than either low or high phosphorus systems. However, it is
49
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possible that the low phosphorus flowthrough systems responded to consid-
erably less accumulated cadmium than indicated in Table 2 (see Section 4).
Unfortunately, a block effect in our experiment precludes evaluation.
To more precisely address this problem, future experiments should include
exactly comparable levels of nutrient enrichment, equivalent pulsed
toxicant inputs into static and flowthrough system (early and late in
succession), and several low level continuous toxicant inputs into flow-
through systems.
Relative Sensitivity of Variables
Table 3 is a general, qualitative summary of responses to cadmium of
all variables measured in the static and flowthrough microcosms. This
comparison includes the effects of cadmium pulses in the flowthrough
systems. The purpose of Table 3 is to provide a gross evaluation of the
relative sensitivities of the variables. The presence of a response
("+" indicates an increase in value, "-"a decrease in value, and "0" no
response) is based on statistical analyses presented earlier in this
report, or on obvious response patterns (e.g., crustacean abundance in
flowthrough microcosms).
A comparison of variables in Table 3 suggests that community
metabolism (especially respiration) and population densities (especially
grazers) provide the best overall measures of cadmium effects. This
agrees with the conclusion of Odum et al. (1979) that ecosystem stress
evaluations should focus on variables at the ecosystem and population
levels of organization (energy flow and key population densities, res-
pectively) . The P/R ratio decreased in response to cadmium in the
50
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Table 3. Qualitative comparison of microcosm responses to cadmium.
Static Microcosms Flowthrough Microcosms
Low Nutrient High Nutrient . Low Phosphorus High Phosphorus
Biomass 0000
Chlorophyll a 0 + + 0
Phaeopigments 000 0
Net Daytime Production 00+-
Nighttime Respiration + + +-
P/R 0 0
Population densities
Algae -C + + 0
Grazers -
Bacteria 0 0 N.M. N.M.
Fungi . + + N.M. N.M.
Nutrient Output
TN N.M. N.M. -+ 0
NH -N N.M. N.M. - 0
NCK-N N.M. N.M. -+ +
TP N.M. N.M. 0 0
Mn N.M. N.M. -+
Fe N.M. N.M. 0
Note: + indicates increase in value; - indicates decrease in value; 0 indicates no
response; N.M. indicates that a variable was not measured.
51
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static microcosms due to an increase in community respiration. Giddings
and Eddlemon (1978) also observed a decrease in P/R in static microcosms
exposed to arsenic. In the present experiment, net production and
community respiration in the flowthrough systems responded identically
to cadmium, resulting in no measurable P/R response. We are unable to
tell at present whether this difference is due to the actual nutrient
flowthrough or to the pulsed nature of cadmium inputs in the flowthrough
microcosms.
Biomass and plant pigment concentrations were generally the poorest
indicators of cadmium effects. This is not surprising for biomass
since, as a cumulative system property, it would not be expected to
reflect short term system dynamics in response to chemical pertur-
bations. Biomass accumulation rates might be more revealing. As
measures of autotrophic mass and condition, plant pigments might be more
sensitive to toxicants which selectively affect primary producers.
In the flowthrough microcosms, output/input ratios of nitrogen
(especially NCL-N) proved to be quite sensitive to cadmium pulses,
responding as the inverse of net production. This may have been the
result of a direct cadmium influence on nitrogen metabolism. Giesy et
al. (1979) found no NCL-N output response to cadmium continuously intro-
duced into stream channel microcosms, possibly because of significantly
lower cadmium (5 and 10 ppb) and NCL-N concentrations (3.6-10.4 ppb), or
other properties of the stream systems (e.g., biotic composition). The
influence of toxic substances on nitrogen metabolism requires further
research.
Finally, manganese and iron outputs in response to cadmium pulses
52
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were suggestive of the pattern described above for NCL-N, but the trends
were not as clear. And, again, the mechanisms involved are not known.
Nonetheless, these results emphasize the potential utility of essential
element dynamics as an indication of ecosystem stress response.
Phosphorus outputs showed no significant response to cadmium treatments
at either level of enrichment, indicating that phosphorus is efficiently
retained within the systems even after disturbances. Evans (1977) found
similar results in flowthrough reef-flat microcosms exposed to copper
perturbations.
53
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SECTION 6
CONSIDERATIONS AND RECOMMENDATIONS FOR TOXICITY TESTING
Results of these experiments suggest some tentative answers to the
questions raised in the Introduction:
1) Which ecosystem properties are most sensitive or best reflect
ecosystem response to toxicant perturbations?
Of the ecological variables measured in this study, community
metabolism (net daytime production and especially nighttime respiration)
and densities of various taxonomic groups provided the most consistent
indicators of cadmium effects. The ratio of net production to community
respiration (P/R) has been suggested as a useful measure of toxicant
stress in microcosms (Giddings and Eddlemon 1978), but proved responsive
to cadmium only in the static systems in our study; in the flowthrough
system P_ and R,, both responded similarly, resulting in no net change in
P/R. Reasons for this difference are not clear, but it does seem clear
that P_ and R« expressed individually are important and easily measured
variables in microcosm studies. Biomass and plant pigment concen-
trations were the least sensitive to cadmium of the variables measured
in our study. Biomass accumulation rates and pigment ratios might prove
to be more useful. In the flowthrough systems, output/input ratios of
NO»-N, Mn and Fe showed significant responses to cadmium treatment.
This illustrates the potential utility of output/input ratios
(especially nitrogen) for toxicity screening and suggests further that
54
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some toxicants might selectively alter specific metabolic pathways.
Estimates of rates of metabolism of certain essential elements (e.g.,
N, P, S) should be considered for use in microcosm screening tests.
Thus, based on our results, the most useful ecological variables for eval-
uating toxicant effects in aquatic microcosms appear to be those that
reflect: 1) overall community metabolism (P-, R« and P/R), 2) changes in
community composition (relative abundances of key functional or trophic
groups), and 3) dynamics of essential elements (output/input ratios and
possibly activity of specific metabolic processes). Sampling frequency
in this study was approximately once per week for most of the variables.
The observed trends could have been detected from less frequent sampling
over most of the experimental periods but with more intense sampling
early in succession and immediately after perturbations.
2) What influence will other environmental variables (e.g., pH,
nutrient enrichment, light intensity) have on ecological effects .
of a toxic substance?
Nutrient enrichment and phosphorus limitation significantly in-
fluenced the cadmium response of most of the variables measured in this
study. In general, the poorly enriched microcosms were more sensitive
to cadmium than their highly enriched counterparts. The importance of
this finding for toxicity screening in microcosms is that standard
testing conditions, such as levels of nutrients and other factors, are
likely to influence test results. This unavoidable bias can be mini-
mized or at least accounted for by conducting screening tests in matrix
55
-------
or factorial experimental designs which include potentially interacting
factors. In particular, if tests are run in microcosms of site specific
derivation, then environmental factors important in a given geographic
area (e.g., salinity, pH, temperature extremes) could be incorporated
into the test, along with toxicant levels, for a more meaningful evalua-
tion. Any number of factors could be included in such a scheme
(including several toxicants), but experimental costs would increase with
each factor. Judicious choice of potentially important factors would be
required. An especially important environmental factor which this study
did not consider was the effect of inorganic sediments (and the asso-
ciated biotic community) on cadmium toxicity. Because soils and sediments
are important biogeochemical factors in all ecosystems, they might be
more appropriately included as a nominal" experimental condition rather
than a separate factor, unless the interactive ecological effects of
toxicants and sediments are of interest. Since this study focused on
biotic processes and was, therefore, ecologically incomplete, we would
suggest a complimentary follow-up experiment of similar design, which
incorporates sediments as an experimental condition applied equally over
all treatments. This would add more realistic conditions and- allow for
inferences as to the influence of sediments on cadmium toxicity.
3) Will ecosystem response be a function of the timing or frequency of
toxicant inputs with respect to stages of ecosystem development?
The mode of toxicant introduction into microcosms is an important
consideration for toxicity testing. Since toxic substance inputs into
56
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natural ecosystems occur over wide ranges of frequency and magnitude,
one-time additions of a toxicant to microcosms might not provide a
meaningful evaluation of ecological effects. In the present study,
cadmium was added to the static microcosms only at the beginning of the
experiment, precluding any consideration of toxicant input dynamics. We
attempted to address this problem in flowthrough microcosms by applying
cadmium in pulses at several stages in succession. Results showed that
cadmium pulses early in succession significantly affected system res-
ponse to later pulses, possibly due to selection for tolerant organisms.
We are unable, with these data, to evaluate relative sensitivities of
different successional stages. This could be easily done, however, in a
factorial experiment using time of pulse as one factor and magnitude of
pulse as another. We also compared flowthrough microcosm responses to
continuous chronic versus acute pulsed cadmium exposure. Continuous
10 ppb Cd inputs may have caused a toxic threshold response, but results
are inconclusive. Giesy et al. (1979) found no evidence for cadmium
threshold responses in stream microcosms exposed to continuous 5 and 10
ppb Cd inputs.
4) What degree of realism (biotic and abiotic complexity) should be
incorporated into microcosms for use in toxicity screening?
Generally, the microcosms used in this study (small volume [6 1]
with naturally derived communities) were sensitive to moderately low
concentrations of cadmium (100 ppb). The lowest concentrations, how-
ever, caused no response in the static systems (1 and 10 ppb Cd) and a
57
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possible but inconclusive response in the flowthrough systems (10 ppb
Cd). In contrast, others have found significant ecological responses to
low levels of cadmium (5 and 10 ppb Cd; Giesy et al-. 1979) and copper
(10 ppb Cu; Evans 1977) in relatively large, ecologically complex,
outdoor microcosms. This suggests a possible direct relationship
between microcosm size (or complexity) and toxicant sensitivity, but
the relationship is not clear. Conversely, a broad interpretation of
the results of Van Voris et al. (1980) would suggest that the most
sensitive systems (i.e., least resistant to perturbation) are relatively
low in "functional complexity." Until some empirical means is found to
evaluate functional complexity, however, this problem will be difficult
to resolve. It is also possible that physical or chemical properties
(e.g., pH or water hardness) of the various microcosms are related to
their various sensitivities. In any event, our results suggest that
small laboratory microcosms are potentially useful for estimating gross
ecological effects of toxic substances, perhaps as an early phase in
multiple-stage testing followed by later but more selective studies in
more complex systems (subsamples from specific ecosystems; eg., Giddings
and Eddlemon 1978).
We are unable to judge the relative sensitivities of static versus
flowthrough microcosms used in this study. We suggest, however, that
nutrient flowthrough provides a degree of realism lacking in static
microcosms and allows for consideration of chemical input-output dy-
namics, which proved to be sensitive to cadmium perturbations. In- ad-
dition, continuous low level input of toxicant provides a means for
evaluating chronic toxicity. It should be noted that continuous
58
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nutrient flowthrough appeared to result in a 60-day delay in peak meta-
bolic activity compared to static conditions. This suggests that screen-
ing tests in flowthrough microcosms might require longer periods of
observation if entire successional sequences are to be studied. However,
responses to cadmium pulses were relatively rapid and observable over
shorter time periods (approximately 30-60 days in most cases). The
behavior of flowthrough microcosms has been suggested to be related to
system turnover time (Leffler 1978) which, in the present experiment,
was 12 days. Turnover times which provide maximum toxicant sensitivity
will have to be determined for toxicity screening tests.
A Hierarchical Approach
As mentioned in the Introduction, testing standards have not yet
been developed for evaluating ecological effects of toxic substances
prior to their widespread release into the environment. We suggest that
a potentially useful screening protocol for aquatic ecosystems might
consist of a series of factorial experiments in aquatic microcosms of
increasing complexity: (1) Relatively simple, static microcosms (with
and without sediments), (2) flowthrough microcosms (with and without
sediments), and (3) detailed but selective studies in more complex
microcosm subsamples from specific ecosystems. Steps (1) and (2) are
based partly on results from the present experiment; although sediments
were not studied, they have been shown to influence the toxicity of a
number of compounds (e.g., Hongve et al. 1980). In addition, separate
consideration of natural sediments corresponds to previous conclusions
that toxicant effects on pelagic and sediment communities should be
59
-------
studied in separate screening experiments (Leffler 1980, personal communi-
cation) . We include sediments in the protocol as a point for further
research. Step (3) is based on results from Ausmus et al. (1980) which
suggest that laboratory microcosms can be constructed which reasonably
mimic specific natural ecosystems (ponds), and that such systems are most
useful for later stages of screening of toxic substances.
The protocol is tentative in that details of analysis and interpre-
tation have not been developed. A general outline is as follows (the
steps are similar in rationale to those described for terrestrial micro-
cosms in Gillett and Witt [1977], pp. 5-6):
1) Based on consideration of available information concerning a
toxicant (chemical properties, species bioassay data, simulation
model predictions, etc.), short-term factorial experiments are
conducted in simple static microcosms to elucidate gross ecological
effects. The factors to be included are indicated by available
information, but may be simply toxicant levels versus the presence
and absence of sediments. If other factors require evaluation,
then sediments might be considered in separate'but concurrent
experiments. The experiments might be designed to test a statis-
tical null hypothesis of no toxicant effect over some range of
concentrations (e.g., several orders of magnitude). In such a case,
a minimum set of response variables should include community meta-
bolism (productivity and respiration), toxicant and selected nutrient
concentrations (for evaluations of uptake/release of nitrogen and
phosphorus, for example), and abundances of key taxonomic groups
60
-------
(e.g., primary producers, grazers and microbial decomposers). Other
variables might be appropriate, especially in cases where specific
modes of toxicant activity are known or suspected (e.g., rates of
nitrogen fixation for chemicals that inhibit nitrogenase activity).
If, as a result of these experiments, a chemical proves to have
highly undesirable ecological effects, even at low concentrations,
no further testing may be required. If moderate or no effects are
detected, testing should be continued at the next level.
(2) Based on results from the static experiments, flowthrough microcosms
are employed to evaluate chronic or threshold effects of low level,
continuous toxicant inputs. In addition, the effects of toxicant
input dynamics (inputs of various intensity, duration or frequency)
can be studied if desired. As before, factors to be included
depend on available information. Effects of sediments might be
included as a factor or studied in separate experiments. In addition
to response variables considered in step (1), output/input relation-
ships for selected nutrients and for the toxicant should be measured.
Again, if dramatic ecological effects are discovered during
these experiments, further testing may be unnecessary. Otherwise,
tests are conducted at the next level.
(3) Results from steps (1) and (2), combined with existing information,
should provide a reasonable estimation of gross ecological effects
of a toxic substance. The purpose of the last step is to analyze
some of the details of toxicant activity in microcosms derived from
61
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specific ecosystems and to detect effects which might be site
specific. Ecosystems of interest might be those expected
to receive excessive exposure to a toxic substance. Details of
experimentation with this type of aquatic microcosm are described
in Ausmus et al. (1980). Appropriate analyses include toxicant
transport and degradation (via radioisotope-labeled compounds),
bioaccumulation ratios, nutrient concentrations in interstitial
water, and community metabolic -activity (productivity and respir-
ation). Other variables might be of interest in specific situations,
Information from such experiments should suggest mechanisms for
ecological effects which may have been observed, but less well
understood, in steps.(1) and (2).
Any suspected toxicant which fails to show adverse effects in all
three hierarchical steps might be expected to have little impact in
natural aquatic ecosystems, at least over the concentration ranges
studied. However, this statement cannot be confirmed from existing
information. Further research is needed to validate experimentally
derived results through studies in natural systems, and to assess the
feasibility of a hierarchical approach to toxicity screening. The
advantage of such an approach is that each step yields increasingly
greater information about the effects of a toxicant, and more closely
approximates natural ecosystems.
62
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SECTION 7
CONCLUSIONS
1) Of the variables measured in this study, the most useful for evalu-
ating the ecological effects of cadmium were: a) community meta-
bolism (net daytime production and nighttime respiration), b) changes
in community composition (relative abundances of trophic groups),
and c) output/input ratios for NO--N, Mn and Fe. Biomass and
plant pigment concentrations were the poorest indicators of cadmium
effects. The response of specific metabolic activities (e.g., for
N, P and S) to toxic substances requires further research and
should be considered for incorporation into toxicity screening
tests.
2) Nutrient enrichment and phosphorus limitation significantly in-
fluenced cadmium effects on most of the variables measured in this
study. The use of a factorial experimental design provides a
means of including potentially important interacting factors into
microcosm screening tests. The effects of inorganic sediments on
system response to cadmium should be investigated for comparison
with results of this study.
3) Pulsed cadmium inputs early in succession significantly affected
system responses to cadmium pulses later in succession (in flow-
through microcosms) possibly as a result of selection for cadmium
63
-------
tolerant organisms. Continuous 10 ppb Cd inputs may have resulted
in a threshold response due to cadmium accumulation, but results are
inconclusive.
4) A hierarchy of microcosm experiments, including 1) static micro-
cosms (with and without sediments), 2) flowthrough microcosms
(with and without sediments), and 3) microcosm subsamples from
natural ecosystems, appears potentially useful for screening
purposes. Each step provides increasingly greater information and
more closely approximates natural ecosystems.
64
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Ul
Sub
Sub: Subsidy Effect
N : Normal Operating Range
St : Stress Effect
R : Replacement
L •' Lethal
Relative Variance
Increasing Perturbation
FIGURE 1. Hypothesized patterns of ecosystem response to usable and toxic inputs (redrawn from Odum
et'al. 1979),
-------
NET
ECOSYSTEM
PRODUCTIVITY
(KG/HA/YR)
INPUT
RATE
ELEMENTAL
OUTPUTS
(EQ/HA/YR)
PRIMARY SUCCESSION
APPROACH TO
STEADY STATE SECONDARY SUCCESSION
NON-ESSENTIAL
ELEMENT ESSENTIAL
NOW-LIMITING
ELEMENT
ESSENTIAL
LIMITING
ELEMENT
SUCCESSIONAL TIME
FIGURE 2. Hypothesized patterns of net ecosystem productivity (A) and element retention (B) through
ecosystem succession (redrawn from Vitousek 1977).
-------
100
o
10
Q.
0.
LU
LU
Q
O
I
NITROGEN .10
PHOSPHORUS -01
.50
.05
1.00
.10
10.00 ppm
1.00 ppm
NUTRIENT LEVEL
FIGURE 3. Experimental design for Phase I, with three replications
of each treatment.
67
-------
LATE PULSE
Cd
EARLY 4-LATE
PULSE Cd
CONTINUOUS
(Oppb Cd
NO CADMIUM
NITROGEN 6.2
PHOSPHORUS 0,62
N:P=IO
6.2 ppm
0.062 ppm
N:P=IOO
FIGURE 4. Experimental design of Phase II, with four replications
of each treatment.
68
-------
80
60
CO
CO
'50
90
30
r
0 I 10 100
CADMIUM CONCENTRATION (ppb)
B
r_
Ix 5x !0x
NUTRIENT LEVEL
!00x
FIGURE 5. Influence of cadmium (A) and nutrient enrichment
(B) on average biomass concentration in static
microcosms. Each point represents the mean over
the entire experiment.
69
-------
IUU
E
co5O
CO
<
g
co
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-
-
•
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-
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>
<
(
)
g
60 90 120
DAY
FIGURE 6. Biomass concentrations through time in lowest nutrient (Level 1) control static microcosms.
Each point is the mean of three replicate systems with 95% confidence bars.
-------
ouu
e
0)
0)
^
o
GO
°c
-
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) 30
<
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<>
60 90 120
DAY
FIGURE 7. Biomass concentrations through time in highest nutrient (Level 4) control static microcosms.
Each point is the mean of three replicate systems with 95% confidence bars.
-------
0.4
- 0.2
o>
£
x
o.
§0.6
0.4
0.2
0 I 10 100
CADMIUM CONCENTRATION (ppb)
Ix 5x lOx JOOx
NUTRIENT LEVEL
FIGURE 8. Influence of cadmium (A) and nutrient enrichment (B) on average
chlorophyll concentrations in static microcosms. Each point
represents mean over the entire experiment.
72
-------
U.D
\ 0.4
e
o 0.3
_l
-J
x 0.2
Q_
O
CC
g o.i
X
0
o
•
-
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0 30
<
)
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)
<
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)
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)
<
i
Ml
60 90
DAY
<
>
Jl.
120
FIGURE 9. Chlorophyll a concentrations through time in lowest nutrient (Level 1) control static micro-
cosms. Each point is the mean of three replicate systems with 95% confidence bars.
-------
5
4
0>
E
o 3
_j
_j
> 2
X
Q_
0
01 I
0 8
i
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-
..
. <
1 i
ill*
o i o 10 Qi I i 1 t i
<
>
<
t
i
•
!
(
1
)
<
) 30 60 90
DAY
(
[]
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j
(
12
FIGURE 10. Chlorophyll a concentration through time in highest nutrient (Level 4) control static micro-
cosms. Each point is the mean of three replicate systems- with 95% confidence bars,
-------
-J
I/I
0.5r
*0.4
C/)
H
2
LU
0.3
CD
E0.2
i
o
LJ
X
Q_
0
0
i
O
<•» r>i i o
o 9
i
30
60
DAY
90
120
FIGURE 11, Phaeo-pigment concentrations through time in lowest nutrient (Level 1) control static micro^
cosms. Each point is the mean of three replicate systems with 95% confidence bars,
-------
D
£ 4
CO
z: 3
UJ
CD
ol 2
1
o
LU
< 1
X
0.
o
•
.
•
*
i.i A 4. „
o
\ ,190. .1 0. ^> A .
0 30 60 90 I2<
DAY
FIGURE 12, Phaeo-^plgment concentrations through time in highest nutrient (Level 4) control static
microcosms. Each point is the mean of three replicate systems with 95% confidence bars.
-------
cc
CL
L»J O
ZLU
(T
o:
a.
1.4
1.0
0.6
1.4
1.0
0.6
1.2
1.1
1.0
Ix
Ix
5x IOx !00x
B
5x IOx lOOx
Ix 5x. IOx ICOx
NUTRIENT LEVEL
FIGURE 13. Net production and nighttime respiration, in
mg 02/1/hr, and P/R for the four nutrient
levels in static microcosms. Each point
represents the mean over the entire experiment.
77
-------
2 1.0
o
O
cc
Q.
0.9
0.8
0.8
I.I
1.0
10 100
B
0
10 100
0 I
CADMIUM
10 100
LEVEL
FIGURE 14. Net production and nighttime respiration, in
rag 02/1/12 hr, and P/R for the four levels
of cadmium in static microcosms. Each point
represents the mean over the entire experiment.
78
-------
e
iP 2
M
o
o
NET PRODUCTION
NIGHTTIME RESPIRATION
0
30
60
DAY
90
120
FIGURE 15. Community metabolic activity through time in lowest nutrient (Level 1) control static
microcosms.
-------
09
O
- 2
CM
o
o
NET PRODUCTION
NIGHTTIME RESPIRATION
30
60
DAY
90
120
FIGURE 16. Community metabolic activity through time in highest nutrient (Level 4) control static
microcosms.
-------
1000 .
CO
CD
3
a.
GO
cu 100
a.
LU
z
o
o
o
z
ID
u.
z
<
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10
0 I 10 100 01 10 100 0 I 10 100 0 I 10 100
CADMIUM CONCENTRATION (ppb)
Ix
5x
NUTRIENT
lOx
LEVEL
lOOx
FIGURE 17. Influence of cadmium and nutrient enrichment on mean fungal
colony abundance in static microcosms. Each point represents
the mean over the entire experiment.
81
-------
0)
o
CL
CO
CO
UJ
3
O
o
cr
UJ
s
<
<
O
FIGURE 18.
10'
0 I 10 100 01 10 ICO 0 I 10 100 01 10 100
CADMIUM CONCENTRATION (ppb)
Ix
5x
NUTRIENT
lOx
LEVEL
100 x
Influence. of cadmium and nutrient enrichment on bacterial
colony abundance in static microcosms. Each point represents
the mean over the entire experiment.
82
-------
5000
-------
CO
550
wo
O
CD
IShP = IOO
CONTROL
300
FIGURE 20. Biomass concentrations through time in phosphorus limited control flowthrough microcosms.
Each point is the mean of four replicate systems with 95% confidence bars.
-------
00
1500
glOOO
O 500
CD
0
CONTROL
o
60
0
50
100
150
DAY
200 250 300
FIGURE 21. Biomass concentrations through time in non-phosphorus-limited control flowthrough micro-
cosms. Each point is the ujean of four replicate systems with 95% confidence bars.
-------
0.6
0.4
o
co
ON
9b0.2
o
X
o
o
o
i
Control
o
o
C
0
oo
o
J tJ 1 K I
f
•
*l
• ' « — I — I — I — I — I — I
0 50 100
150 200 250 300
DAY
FIGURE 22, Chlorophyll a concentrations through time in N:P = 1QQ control flowthrough microcosms.
Each point is the mean of four replicate systems with 95% confidence bars.
-------
oo
o
100 150 200 250 300
FIGURE 23, Chlorophyll a concentrations through time in N;P = 10 control flowthrough microcosms,
Each point is the mean of four replicate systems with 95% confidence bars.
-------
00
00
0.6
E
{20.4
0-
i
o
UJ
X
Q.
0
Conlro!
AAfyO
'.Tli «
j>—i
0
50
100 150
DAY
200
250
I
300
FIGURE 24, Phaeo^pigment concentrations through time in N;P - 1QO control flowthrough microcosms,
Each point is the mean of four replicate systems with 95% confidence bars.
-------
CO
3
^
E
CO
fe 3
UJ
E 2
i
a
UJ
x 1
Q_
(
N:P = IO
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50
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FIGURE 25. Phaeo-pigment concentrations through time in N:P = 10 control flowthrough microcosms.
Each point is the mean of four replicate systems with 95% confidence bars.
-------
w
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-------
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4
3
en 2
3
O
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CM
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™
-
i 9^
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E
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i
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3 <
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3.0
2.0
CC
CL 1.0
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-
:'
—
<
>
*
''•
ft
^
i i * i
» i
fiV
''i H
•Uft* n-
,.. ., r
i
i i i i i i i i i i i
»
1
i
i
r
I
'i+4.»»f
ti • r
> 1)
r t
1 1 1 1 ! 1 1 1 I I I 1 1 !
50 100 150 200 250 300
DAY
FIGURE 27. Net daytime production (A), nighttime respiration (B), and
P/R (C) through time in flowthrough microcosms with input
N:P = 100 and continuous 10 ppb Cd input. Each point is the
mean of four replicate systems with 95% confidence bars.
91
-------
5
4
3
en 2
O
CNJ
^ 0
&
~ 5
CVJ
O 4
O) *
3
2
750
500
100 |
750
i
0
3.0
2.0 h
cr
Q- i.o
o-
,}
.*
I
- 1 1 1 ! 1
B
*
~ W j
;(t"
i/jft
t i i I i I i i
1,
f fr ? * t
50 100 150 200
DAY
250 300
FIGURE 28.
Net daytime production (A), nighttime respiration (B), and
P/R (C) through time in flowthrough microcosms with input
N:P = 100 and cadmium pulses as indicated in ppb Cd by arrows.
Each point is the mean of four replicate systems with 95%
confidence bars.
92
-------
en
o
C\J
•= 5
CM
I*
3
2
750
\
i i i i i i i i i i i
B
- 1 I' 1 1 1 1 ! 1 1 1 1 1 1 1 | [ 1_J
1 1 1 1 1
3.0 r
2.0
Q- i.o
4
0 50 100 150 200 250 300
DAY
FIGURE 29. Net daytime production (A), nighttime respiration (B), and
P/R (C) through time in flowthrough microcosms with input
N:P = 100 and cadmium pulse as indicated in ppb Cd by arrow.
Each point is the mean of four replicate systems with 95%
confidence bars.
93
-------
O
CVJ
5
CM
O 4
-i i i i i i i i i i i i i i i i i i i i i i i i i i i i i i i
B
0 I— i i i i i i i i i i i i i i i i i i i i i i i i i i i i i i i
3.0 r
2.0
cr
Q-i.O
0.0
I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I
0 50 100 150 200 250 300
FIGURE 30.
DAY
Net daytime production (A), nighttime respiration (B), and
P/R (C) through time in flowthrough microcosms with input
N:P » 10 and no cadmium. Each point is the mean of four
replicate systems with 95% confidence bars.
-------
CVJ
£ 5
\
CVJ
I4
3
B
0 r- I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I
3.0 r
2.0
cr
0-1.0
I I I I ! I I I I I I I I I I I I I I I I I I I I I I I I I I
0 50 100 150 200 250 300
DAY
FIGURE 31. Net daytime production (A), nighttime respiration (B), and
P/R (C) through time in flowthrough microcosms with input
N:P = 10 and continuing 10 ppb Cd inputs. Each point is the
mean of four replicate systems with 95% confidence bars.
95
-------
co
5r
4
3
2
500
» *
100
9
i
..'
19
^ Q t-1 i i i i i i i i i i i i i i i i i i i i t i i 11 i i i i i i
1 5
OJ
O 4
3
2
1
Q\- i i i i i i i i i i i i i i i i i i i i i i i i il I i i i i i
B
3.0 r
2.0
cr
1.0
f
i i i i i i i i i i i i i i i i i i i i i i i i i i i i i i
50 100 150 200 250 300
FIGURE 32.
Net daytime production (A), nighttime respiration (B) , and
P/R (C) through time in flowthrough microcosms with input
N:P - 10 and cadmium pulses as indicated in ppb Cd by arrows.
Each point is the mean of four replicate systems with 95%
confidence bars.
96
-------
4
3
2
O
-c l
CVJ
w. oU i i i i i i i i i i
750
,1
0 O
I
— 5r
o>
B
Co
t.AAl
-1 i i i i i i i i i i i i i i i i i i i i i i i i i i i i i i
3.0 r
2.0
cr
Q- i.o
50 100 150 200 250 300
DAY
FIGURE 33. Net daytime production (A), nighttime respiration (B) , and
P/R (C) through time in flowthrough microcosms with input
N:P = 10 and cadmium pulse as indicated in ppb Cd by arrow.
Each point is the mean of four replicate systems with 95%
confidence bars.
97
-------
00
80'
a:
Id
CO
-------
H
CO
C9
a:
o
10
0
N:P=IO
Continuous lOppb Cd
-o-OSTRACODS
-0---COPEPODS
50
100
150
DAY
200
250
300
FIGURE 35. Crustacean abundance through time in flowthrqugh microcosms with input N;P = 1Q and continuous
10 ppb Cd inputs. Each point is the mean of four replicate systems.
-------
o
o
Id
h-
<3
o:
o
10
0
N'-P=IOO
Cd Pulses Early and Late
—a— OSTRACODS
--o-- COPEPODS
750
100
500 750
A
50
100
150
DAY
200 250
300
FIGURE 36. Crustacean abundance through time time in flowthrough microcosms with input N;P ^ 10, and
cadmium pulses as indicated in ppb Cd by arrows. Each point is the mean of four replicate
systems.
-------
o:
ui
h-
O)
S
CO
C9
CC
O
10s
10
0
N:P=IO
Cd Pulse Late
-o-OSTRACODS
--0--COPEPODS
50
100
150
DAY
200
250
300
FIGURE 37, Crustacean abundance through time in flowthrough microcosms with input N:P = 10 and cadmium
pulse as indicated in ppb Cd by arrows. EAch point is the mean of four replicate systems.
-------
o
N3
cc
UJ
CO
O
tr
o
I02
10
0
NP = IOO
Continuous SOppb Cd
OSTRACODS —o—
COPEPODS —o™
J—I—I—8—I—'«»"««
-I—I—I/ I I I » I t
50
100
150
DAY
200 250 300
FIGURE 38. Crustacean abundance through time in flowthrough microcosms with input N;P = 1QO and continuous
1Q ppb Cd inputs. Each point is the mean of four replicate systems.
-------
o
10
o
QC
o:
Id
CO
10
Cd Pulses Early and Late
0
50
100
150
DAY
200
250
300
FIGURE 39. Rotifer abundance through time in flowthrough microcosms with input N:P= 1QO and cadmium
pulses as indicated in pph Cd by arrows. Each point is based on a single microscopic count
of a composite from four replicate microcosms.
-------
gioo
U-
O
o:
UJ
CD
10
N'P=IOO
Cd Pulse Late
' «
0
50
100
150
DAY
200
250
300
FIGURE 40. Rotifer abundance through time in flowthrough microcosms with input N;P = 100 and cadmium
pulse as indicated in pph Cd by arrow. Each point is based on a single microscopic count
of a composite from four replicate microcosms.
-------
2.0
1.0
TN
1 lO
-
-------
2.0
FIN
—
o
Oi
f
ii
2.0
H
o,
S
*v
H 1.0
ID
a,
h-
o
o
Oh
NH3-N
1 1 1 1 1 1 1 1 1 ) 1 1 1 ! 1 1 1 t 1 1 1 1 1 1 I 1 1 | 1 |
2.0 r
ot
N03-N
50 100 150 200 250 300
DAY
FIGURE 42. Total nitrogen (A), ammonia nitrogen (B), and nitrate nitro-
gen (C) output/input ratios through time in flowthrough
microcosms with input N:P = 100 and continuous 10 ppb Cd
inputs. Each point is the mean of four replicate systems
with 95% confidence bars.
106
-------
•TN
.00
T
h-
ID
Q.
Z
H 1-0
13
Q_
h-
^
O
NH3-N
B
N03-N
>« 6°o° 0°6
o ~ i i i i i i i * i i i i i i * i i i i i i * i i i i * * i i *
0 50 100 150 200 250 300
DAY
FIGURE 43. Total nitrogen (A), ammonia nitrogen (B), and nitrate nitro-
gen (C) output/input ratios through time in flowthrough micro-
cosms with input N:P = 100 and cadmium pulses as indicated in
ppb Cd by arrows. Each point is the mean of four replicate
systems with 95% confidence bars.
107
-------
2.0
1.0
ot
TN
2.0
ID
CL
h-
^
O
NH3=N
B
2.0 r
1.0
^
A 1 A Tu
6
0 - i i i i i i i i i i i i i i i i i i i i i i i i i i ' i i i i
0 50 100 150 200 250 300
DAY
FIGURE 44. Total nitrogen (A), ammonia nitrogen (B), and nitrate nitro-
gen (C) output/input ratios through time in flowthrough
microcosms with input N:P = 100 and cadmium pulse as indi-
cated in ppb Cd by arrow. Each point is the mean of four
replicate systems with 95% confidence bars.
108
-------
2.0
1.0
0 -
TN
2.0 r
1.0
13
Q_
H
O
Ob
NH3-N
B
«°o o* oo
i ii i i i ii i iii rii i
2.0 r
1.0
N03-N
Obi
I I I I I I [II
I I I I I
50 100 150 200
DAY
250 300
FIGURE 45.
Total nitrogen (A), ammonia nitrogen (B) , and nitrate nitro-
gen (C) output/input ratios through time in flowthrough
microcosms with input N:P = 10 and no cadmium. Each point
is the mean of four replicate systems with 95% confidence
bars.
109
-------
1.0
TN
- A
Ot-i t i i i i i i i i i i i i i i i i i i i i i i i i i i i i i
2.0r KIU ,M B
h-
CL
h- 1-0
NH3-N
** I I I I I I \ I I I I I I I I M I I I Tl I I I I I I I I I Ol I
2.0r
1.0
N03-N
lilt
50 100
150
DAY
200 250 300
FIGURE 46.
Total nitrogen (A), ammonia nitrogen (B), and nitrate nitro-
gen (C) output/input ratios through time in flowthrough
microcosms with input N:P = 10 and continuous 10 ppb Cd
inputs. Each point is the mean of four replicate systems
with 95% confidence bars.
110
-------
0 " I L _l_ 1 _L I I I 1 i 1 L 1 _L I I I I I I I I I I I L 1 1 I I J
20 r
ID
Q_
I-
a.
NH3-N
B
2.0 r
1.0
N03-N
i »
00
I I I I I I Mill III II II I I I I
50 100 150 200 250 300
DAY
FIGURE 47. Total nitrogen (A), ammonia nitrogen (B) , and nitrate nitro-
gen (C) output /input ratios through time in flowthrough
microcosms with input N:P = 10 and cadmium pulses as indi-
cated in ppb Cd by arrows. Each point is the mean of four
replicate systems with 95% confidence bars.
Ill
-------
2.0
TN
ot
2.0
h-
r>
CL
h- 1-0
CL
NH3-N
r N03-N
o°o
B
i i i i i i i Qi i
50 100 150 200 250 300
Oh
FIGURE 48. Total nitrogen (A), ammonia nitrogen (B), and nitrate nitro-
gen (C) output/input ratios through time in flowthrough
microcosms with input N:P = 10 and cadmium pulse as indicated
in ppb Cd by arrow. Each point is the mean of four repli-
cate systems with 95% confidence bars.
112
-------
2.0
rTP
1.0
9SO
9 A9
11 I I I I
2.0rMn
ID
Q.
Q.
h-
O
1.0
B
-.66
^
0 ~ i i i i i i i i i i i i i i i i i i i i i i i i i i i i i i i
2.0 rFe
Oo
m
0 "till i_ i II I 1 t_ I II 1.1 I I t I I I 1 II 1 ( L I t I
0 50 100 150 200 250 300
DAY
FIGURE 49. Total phosphorus (A), manganese (B), and iron (C) output/
input ratios through time in flowthrough microcosms with
input N:P = 100 and no cadmium. Each point is the mean of
four replicate systems with 95% confidence bars.
113
-------
2.0
-TP
1.0
mi
t.
i i i
2.0r Mn
h-
CL
Z
5'.°
CL
H
O
B
Too
0<3>
2.0 r Fe
i.o
ob
0,
i i i i i i t i
0 50 100 150 200 250 300
DAY
FIGURE 50. Total phosphorus (A), manganese (B), and iron (C) output/
input ratios through time in flowthrough microcosms with
input N:P = 100 and continuous 10 ppb Cd inputs. Each point
is the mean of four replicate systems with 95% confidence
bars.
114
-------
2.0
1.0
-TP
100
f 500
O nO
f
- , ,11, 9 .
Or 9
2.0
rMn
h-
Z5
0.
1.0
13
O.
O
0
2.0
B
*}•
1.0
Ob
-Fe
O 9
50 100 150 200 250 300
DAY
FIGURE 51. Total phosphorus (A), managanese (B ), and iron (C) output/
input ratios through time in flowthrough microcosms with in-
put N:P = 100 and cadmium pulses as indicated in ppb Cd by
arrows. Each point is the mean of four replicate systems
with 95% confidence bars.
115
-------
Ob
2.0r Mn
H-
CL
1.0
O
B
-j*
AT
}•
i i i i i i i i i i i i i i i i i i i i i i i i i i i i i i i
2.0
rFe
1.0
0 * i
I
50 ' 100 150 200
DAY
250 300
FIGURE 52. Total phosphorus (A) , managanese (B) , and iron (C) output/
input ratios through time in flowthrough microcosms with
input N:P = 100 and cadmium pulse as indicated in ppb Cd
by arrow. Each point is the mean of four replicate systems
with 95% confidence bars.
116
-------
2.0
rTP
1.0
2.0 r Mn
\
B
2.0 rFe
i.o
0 50 100 150 200 250 300
DAY
FIGURE 53. Total phosphorus (A), managanese (B), and iron (C) output/
input ratios through time in flowthrough microcosms with
input N:P = 10 and no cadmium. Each point is the mean of
four replicate systems with 95% confidence bars.
117
-------
Ob
2.0 r Mn
0.
h-
CL
h-
O
i.o
B
L
0 • ii i i t i i i i __i i [_
2.0 r Fe
I.O
- OY 6
0 "Li I I III t t t rO| I |. II II it I I I L I I 111 1 \
50 100 150 200 250 300
DAY
FIGURE 54. Total phosphorus (A), manganese (B), and iron (C) output/
input ratios through time in flowthrough microcosms with
input N:P = 10 and continuous 10 ppb Cd inputs. Each point
is the mean of four replicate systems with 95% confidence
bars.
118
-------
2.0
rTP
1.0
100
750.
750
I
0 • i t i i t i i i i t i t i i i i i i i i i i i i
2.0r Mn
£1.0
Z>
CL
2.0
rFe
i.o
t
'0
B
- i I i i i i i i i i i i .-i—l_I—I I I—I—I—I—I—I—L_l—I—I—I—I—I—I
0 50 100 150 200 250 300
DAY
FIGURE 55. Total phosphorus (A), manganese (B), and iron (C) output/
input ratios through time in flowthrough microcosms with
input N:P = 10 and cadmium pulses as indicated in ppb Cd
by arrows. Each point is the mean of four replicate systems
with 95% confidence bars.
119
-------
2.0
rTP
i.o
A
o
T
2.0
r Mn
H
CL
Z)
CL
O
1.0
0
2.0
B
i! .
#9 ^
4ft
00
rFe
i.o
0 50 100 150 200 250 300
DAY
FIGURE 56. Total phosphorus (A), manganese (B), and iron (C) output/
input ratios through time in flowthrough microcosms with
input N:P = 10 and cadmium pulse as indicated in ppb Cd by
arrow. Each point is the mean of four replicate systems
with 95% confidence bars.
120
-------
2.0-
OUTPUT/ INPUT
,,?,,,
s •
n-
<
> i
1
1
i
\\
\
I
i
i
N:P=10 A
i
I
•
> 11°
t **}**f||M*
o
5O 100
15O 2OO
DAY
25O 300
zcH
5 to
CL
\—
Z)
O
s
o
N:P = 100
B
±
o
-i—i—i—i—r—p
5O
10O 15O 2OO 25O 30O
DAY
FIGURE 57. Cadmium output/input ratios through time in flowthrough
microcosms with input N:P = 10 (A), and N:P = 100 (B).
Cadmium input concentration was 10 ppb.
121
-------
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164
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APPENDIX A
Nutrient medium composition. Modified Taub and Dollar (1964) #36 medium.
All values are in mg/1.
Compound
CaCl
MgSOit • 7 H 0
KH2POi,
NaOH
EDTA
FeSOit • 7 H20
MnCl2 • 4 H20
H3B03
Co(N03)2 • 6 H20
ZnSOtt • 7 H20
CuSO(+ • 5 H20
NaMoOit • 2 H20
KOH
NH^NOa
NaCl
Phase I (Level I)1
0.367
1.233
0.046
0.077
0.162
0.156
0.050
0.046
0.007
0.007
0.001
0.006
0.026
0.304
Phase II (N:P=100)2
1.952
4.944
0.276 (2.724)
0.734 (1.309)
1.631
1.556
0.990
0.927
0.145
0.143
0.025
0.121
0
17.770
4.380 (43.338)
LLevel 2 = 5 X Level 1; Level 3 = 10 X Level 1; Level 4 = 100 X Level 1.
2N:P = 10 same as N:P = 100 except as indicated by values in parentheses.
165
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APPENDIX B
Detection limits of elements analyzed on the Jarrell-Ash plasma emission
spectrograph. Limits were determined as the lower point of linearity on
standard curves containing the entire nutrient complex. All values are
in ug/1.
Element
Boron
*Cadmium
Calcium
Cobalt
Copper
Iron
Potassium
Magnesium
Manganese
Sodium
Zinc
Lower Detection Limit
100
10
100
10
100
100
1000
10
10
100
10
Nutrient Medium Input
Concentrations (Phase II)
200
10
500
35
6
300
80
480
350
1700
40
*Cadmium concentrations were determined independently by flameless atomic
adsorption spectrophometry.
166
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APPENDIX C
Results of Analysis of Variance. Where interactions were significant, F values
for main effects were calculated using mean square of interaction as the
denominator.
PHASE I:
Variable - Net Daytime Production
Model - P =
Source
Model
NLEV
CDLEV
CDLEV * NLEV
Error
NLEV + CDLEV +
df
32
3
3
9
1495
NLEV *
SS
263.61
111.29
3.02
21.46
352.20
CDLEV + Wk
MS
8.24
37.10
1.01
2.39
.24
F
34.33
15.52
.423
9.96
a
.0001
.001
NS
.0001
Variable - Nighttime Respiration
Model - R^ =
Source
Model
NLEV
CDLEV
CDLEV * NLEV
Error
NLEV + CDLEV +
df
32
3
3
9
1494
NLEV *
SS
241.95
123.42
33.38
23.77
270.86
CDLEV + Wk
MS
7.56
41.14
11.17
2.64
.18
F
42.00
15.58
4.21
14.67
a
.0001
.001
.05
.0001
Variable - Production/Respiration
Model - P/R =
Source
Model
NLEV
CDLEV
CDLEV * NLEV
Error
NLEV + CDLEV + NLEV *
df
32
3
3
9
1459
SS
321.67
3.91
6.58
1.86
795.42
CDLEV + Wk
MS
10.05
1.30
2.19
.21
.55
F
18.27
2.36
3.98
.38
a
.0001
NS
.05
NS
167
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Variable - Chlorophyll a
Model - Chi = NLEV
Source
Model
NLEV
CDLEV
CDLEV * NLEV
Error
+ CDLEV + NLEV *
df SS
30 114.91
3 70.71
3 19.31
9 14.74
730 203.37
CDLEV + Wk
MS
3.83
23.57
6.44
1.64
.28
F
13.68
14.37
3.92
5.86
a
.0025
.001
.05
.01
Variable - Phaeo-pigments
Model - Pha = NLEV
Source
Model
NLEV
CDLEV
CDLEV & NLEV
Error
Variable - Biomass
+ CDLEV + NLEV *
df SS
30 23.88
3 13.05
3 1.03
9 4.08
730 143.16
CDLEV + Wk
MS
.80
4.35
.34
.45
.20
F
4.00
21.75
1.70
2.25
a
.0001
.0001
NS
.10
Model - B = NLEV + CDLEV + NLEV * CDLEV + Wk
Source
Model
NLEV
CDLEV
CDLEV * NLEV
Error
df SS
30 348,315,998
3 140,496,382
3 2,868,906
9 3,796,917
734 398.569,829
MS
.12 11,610,533
.06 46,832,127
.34 956,302
.61 421,879
.97 543,010
F
.27 21.38
.00 86.25
.11 1.76
.73 0.78
.67
a
.0001
.0001
NS
NS
168
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PHASE II:
Variable - Net Daytime Production
Model - Pn = NUT + CD + NUT * CD
Source
df
SS
Model
NUT
CD
NUT *
Error
Variable -
Model - R^
Source
Model
NUT
CD
NUT *
Error
Variable -
7
1
3
CD 3
1240
Nighttime Respiration
= NUT + CD + NUT * CD
df
7
1
3
CD 3
1224
Production/Respiration
351.66
133.38
129.66
88.61
1011.18
SS
351.48
146.47
114.85
90.15
981.12
61.60
4.52
1.46
36.22
F
62.64
4.87
1.61
37.49
.0001
NS
NS
.0001
a
.0001
NS
NS
.0001
Model - P/R = NUT + CD -f- NUT * CD
Source
Model
NUT
CD
NUT *
Error
Variable -
df
7
1
3
CD 3
1224
Chlorophyll a
SS
0.84
0.53
0.06
0.25
46.83
F
3.13
13.93
0.50
2.16
a
.0029
.0002
.6831
.0891
Model - Chi = NUT + CD + NUT * CD
Source
Model
NUT
CD
NUT *
Error
df
7
1
3
CD 3
1230
SS
904.65
900.52
0.76
3.38
1098.91
F
144.65
1007.94
0.28
1.26
a
.0001
.0001
.8397
.2863
.169
-------
Variable - Phaeo-pigments
Model - Pha = NUT + CD + NUT * CD
Source
df
SS
Model
NUT
CD
NUT *
Error
Variable -
Model - B
Source
Model
NUT
CD
NUT *
Error
Variable -
Model - TP
Source
Model
NUT
CD
NUT *
Error
Variable -
Model - TN
Source
Model
NUT
CD
NUT *
Error
7
1
3
CD 3
527.95
503.56
10.88
13.52
29.13
194.48
1.40
1.74
.0001
.0001
.2399
.1551
1230 3184.72
Biomass
= NUT + CD + NUT * CD
df SS
7 53,277,
1 53,065,
3 78,
CD 3 132 ,
1235 86,364,
Total Phosphorus Output
= NUT + CD + NUT * CD
df
7
1
3
CD 3
1238
Total Nitrogen Output
= NUT + CD + NUT * CD
df •
7 3,
1 3,
3
CD 3
1238 1,
320.91
507.29
974.66
838.96
454.86
SS
18.68
18.64
0.02
0.02
13.20
SS
124.24
059.94
18.02
46.28
631.11
F
108.84
758.83
0.38
0.63
F
250.38
1,749.11
0.59
0.61
*
F
338.75
198.35
0.39
11.71
a
.0001
.0001
.7731
.5977
a
.0001
.0001
.6288
.6149
a
.0001
.001
NS
.0001
,170
-------
Variable - Ammonia Nitrogen Output
Model - NH N = NUT + CD + NUT * CD
Source df SS
Model
NUT
CD
NUT * CD
Error
7
1
3
3
1173
1,413.09
1,409.93
0.72
2.44
1,633.15
1,076.03
1,733.52
0.89
4.33
.0001
.001
NS
.005
Variable - Nitrate Nitrogen Output
Model - N03N = NUT + CD + NUT * CD
Source df SS
Model
NUT
CD
NUT * CD
Error
7
1
3
3
1173
1,020.31
918.23
45.51
56.56
1,011.72
168.99
48.70
0.08
21.86
.0001
.01
NS
.0001
171
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