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and airshed; 2) nutrient cycling includes all processes within the system
whereby nutrients are exchanged among biotic and abiotic components. The
"overall structure and function of an aquatic ecosystem are determined by
external fluxes and internal cycles." Effects of environmental disturbances
on nutrient cycling have not been well documented primarily because processes
are not well understood and analytical measurements require the use of radio-
isotope tracer techniques. A few investigations have been conducted in natural
systems (e.g., Hutchinson and Bowen 1950; Rigler 1956), but more detailed
studies have utilized simplified aquatic microcosms (e.g., Gushing and Rose
1970; Confer 1972; Sebetich 1975; Howarth and Fisher 1976; Witkamp 1976;
Leffler 1977).
The flux of nutrients through aquatic systems has received considerable
attention in recent years in the form of mathematical models and input-output
budgets. Although modelling is treated in depth in Chapter 6, a few high-
lights of recent modelling efforts are presented here
The development of mathematical models used for predicting effects of
organic and inorganic pollution in lakes and streams has been reviewed
(O'Melia 1972). Stream models have been predominantly based on engineering
models of the "Streeter-Phelps-01Conner" type and predict dissolved oxygen
and BOD responses to inputs of organic matter. The most commonly used models
for lakes are based on the empirical model of Vollenweider (1968, 1969b, 1976)
and focus on "critical" inorganic nutrient loading, particularly of nitrogen
and phosphorus as related to trophic state. The first model (Vollenweider
1968) predicted critical loading of phosphorus based on mean lake depth but
was later improved (Vollenweider 1969b) by the incorporation of coefficients
of sedimentation rate and hydraulic residence time. This model was modified
by including a coefficient of phosphorus retention used to predict phosphorus
concentrations at spring turnover in a number of Canadian lakes (Dillon and
Rigler 1974a). The utility of empirical models for predicting the trophic
state of lakes was discussed by Dillon and Rigler (1974b) who showed a high
correlation between spring total phosphorus and summer chlorophyll a_ concen-
trations in several temperate lakes. They suggested that phosphorus loading
models combined with the phosphorus/chlorophyll a_ regression model should be
useful for predicting the trophic response of lakes to nutrient enrichment.
This idea has been further discussed by Ahl (1975), Jones and Bachman (1975,
1976), Serruya (1975), Chapra and Tarapchak (1976) and Vollenweider (1976),
and in general has been supported.
Changes in phosphorus loading models have been proposed which would
account for epilimnetic loading of various forms of phosphorus rather than
the commonly used values for total lake area or volume and total phosphorus
(Schaffner and Oglesby 1978). Such a model (Oglesby and Schaffner 1978) was
used to predict the response of phytoplankton standing crop and water trans-
parency in 16 New York lakes to phosphorus loading, and significant correla-
tions with field data were found. The importance of epilimnetic versus total
lake volume in phosphorus loading models has been discussed, but it was con-
cluded that the effect of stratification on phosphorus concentration is
insignificant compared to the external sources of the element (Schindler 1978).
Analytical simulation models also have been used to predict the response
104
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of aquatic systems to nutrient enrichment (e.g., Park et al. 1974; Lehman
et al. 1975; Thomann et al. 1975). An ecosystem model of Lake Ontario was
compared with two empirical loading models and found to be consistent in pre-
dicting annual mean phosphorus and chlorophyll a_ concentrations (Scavia and
Chapra 1977). It was suggested that neither the empirical nor the mechanistic
approach is superior to the other; empirical models yield rapid, inexpensive
predictions of mean phosphorus or chlorophyll levels from phosphorus loading
data, but the mechanistic models provide insight into seasonal dynamics of
system components in response to nutrient enrichment.
Construction of input-output budgets of biologically-essential elements
represents an integrative approach to the analysis of nutrient impacts on
aquatic ecosystems. Budgets for entire drainage basins have shown that dis-
turbances in a watershed (e.g., forest clear-cutting and herbicide treatment)
can release large quantities of nutrients, resulting in eutrophication of
freshwater streams within the basin (Likens and Borman 1972; also see Likens
et al. 1977 for a review of the nutrient budget approach). Expected trends
in input-output relationships for essential and non-essential elements, during
succession and following perturbation in forested watersheds are shown in
Fig. 6.1 (Vitousek 1977). Estimates of nutrient budgets before and after
disturbance in a watershed could provide a measure of overall ecosystem
response and rate of recovery.
NET ECOSYSTEM PRODUCTIVITY (kg/ho/yr)
INPUT
RATE
PRIMARY SUCCESSION
I
ELEMENTAL OUTPUTS ( eq / ha / yr)
I I
APPROACH TO
STEADY STATE SECONDARY SUCCESSION
1-ESSENTIAL
ELEMENT
ESSENTIAL
.NON-LIMITING.
\ ELEMENT/
V
.ESSENTIAL LIMITING
ELEMENT
Fig. 6.1. Changes in net ecosystem productivity and elemental losses through
time. (From Vitousek 1977.)
105
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Input-output budgets also have been constructed for watersheds containing
lakes and impoundments. Johnson and Owen (1971) calculated annual nitrogen
and phosphorus budgets for the Bay of Quinte, Lake Ontario and found that 31
percent of the nitrogen and 44 percent of the phosphorus (from industrial,
municipal, and tributary stream sources) were retained in the sediments of the
bay, reflecting "well-advanced" cultural eutrophication. Studies in Slapy
Reservoir, Czechoslovakia, showed significant retention of total phosphorus
(as high as 33 percent) but little or no retention of total nitrogen (Prochaz-
kova 1975). N:P ratios in the water column increased from 68 to 137 over ten
years, indicating a nitrogen surplus over optimum algal requirements. Budgets
were constructed for several elements in the Rawson Lake watershed (Environ-
ment Canada, Experimental Lakes Area)(Schindler et al. 1976). Inputs of
nitrogen and phosphorus to the lake were rather small (1.0 - 1.5 and 0.05 -
0.10 g/m2, respectively) and were equally divided between terrestrial and
atmospheric sources, while cation inputs were predominantly from tributary
streams. The budgets indicated net gains of nitrogen, phosphorus, and chloride,
and net losses of seven other ions. The N:P ratio increased from 19.5:1 in the
input to 29:1 in the output, giving a retention ratio of 16:1, "very near the
expected ratio for phytoplankton." It was suggested that phosphorus limita-
tion is indicated if biological processes predominate over chemical processes
in the lake.
Short-term (7 months) and long-term (5 years) budgets for iron and phos-
phorus were developed in Sedlice Reservoir, Czechoslovakia (Chalupa 1975).
Long-term random sampling indicated net accumulations of the elements, but
intensive short-term sampling reflected net losses through storm discharges
and scouring; the need for proper sampling, statistical analysis, and inter-
pretations of nutrient budgets was emphasized. Others also have suggested the
need for constructing budgets over several years to avoid misinterpretations
(Schindler et al. 1976; Likens et al. 1977).
At present, the nutrient budget approach to ecosystem analysis probably
holds more promise for long-term management than for short-term impact assess-
ment. However, in watersheds where such information is available, effects of
proposed activities on nutrient loading and the consequent impacts in fresh-
water ecosystems might be predictable.
Stability
The concept of ecosystem stability has been a subject of controversy
among ecologists for a number of years (see Goodman 1975) and has been demon-
strated more as a property of mathematical models than of natural systems.
Odum (1969) included stability (resistance to external perturbations) as an
attribute of ecosystems, but actual measurements of this property in aquatic
systems have been rare. Measurements of stability in terrestrial ecosystems
have been discussed by Webster et al. 1975.
A ranking of lakes, rivers, estuaries, and oceans based on their relative
"elasticity," inertia," and "environmental stability" has been proposed for
environmental impact assessment (Cairns 1977). Ranking orders are as follows:
elasticity~rivers>lakes>estuaries>oceans; inertia—estuaries>rivers>lakes>
oceans; environmental stability—oceans>lakes>rivers>estuaries. Cairns also
106
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proposed a "recovery index" for predicting "the probability of relatively rapid
recovery" of a perturbed aquatic ecosystem. The index is based on the follow-
ing criteria: 1) existence of nearby epicenters for re-invading organisms;
2) transportability or mobility of disseminules; 3) general present condition
of habitat following pollutional stress; 4) presence of residual toxicants
following pollutional stress; 5) chemical-physical water quality following
pollutional stress; 6) management or organizational capabilities for immediate
and direct control of damaged area. Recovery implies re-establishment of
species originally inhabiting the disturbed area and Cairns reports that the
recovery index has been useful in studies of accidental spills and in acid
mine drainage.
Ecosystem stability may be quantified based on observations of previously
disturbed systems (Westman 1978). Inertia is defined as the ability of a
system to resist displacement in structure or function where subjected to a
disturbing force, and resilience as the ability of a natural ecosystem to
restore its structure following acute or chronic disturbance. Four components
of resilience are recognized: 1) elasticity - time required for an ecosystem
to return to steady state after disturbance; 2) amplitude - maximum disturbance
an ecosystem can sustain and still return to steady state; 3) hysteresis -
degree to which pattern of return to steady state is a reversal of pattern of
response to disturbance; and 4) malleability - degree to which recovered steady
state differs from original steady state. Westman suggests that each of these
ecosystem characteristics is measurable and proposes the following criteria.
Inertia might be measured as an ecological 1050 using a similarity index (i.e.,
the degree of disturbance resulting in a 50 percent similarity between the
before and after disturbance ecosystem). Likewise, elasticity might be measured
as the amount of time necessary for 85 percent similarity to be attained between
the disturbed ecosystem and "regional climax vegetation" (or perhaps nearby
undisturbed lakes or streams in the case of freshwater ecosystems). Where
long successional times are involved, computer models might be useful. Ampli-
tude is directly measurable in field experiments, but in practice (i.e., impact
analysis) Westman proposes the use of historical data (e.g., aerial photographs)
and/or computer models of ecosystems to estimate the frequency of disturbance
which "might prevent restoration of the regional climax " Hysteresis can
be measured using non-parametric statistical comparisons of patterns of species
disappearance in response to disturbance, and subsequent patterns of recoloni-
zation. Malleability might be measured simply as percent similarity between
pre-disturbance and post-disturbance stable states of the same ecosystem.
Westman suggested that stable state be defined as "a state in which the mean
(percent similarity) from each year to the next is no greater than 5 percent
over x years and the mean (percent similarity) between the first and the last
year in the sequence is no greater than 10 percent."
Values for inertia, elasticity, hysteresis, and malleability appear to be
readily calculable from data normally collected in impact analysis of fresh-
water ecosystems (i.e., species abundance data). At present these measures
are descriptive rather than predictive. Westman urges impact assessment
investigators to publish results in terms of the above parameters for use in
the development of predictive models.
Another view of aquatic ecosystem stability has been stated by Pomeroy
107
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(1975). He compared four types of aquatic systems (two estuarine grass commu-
nities, a coral reef, and oceanic plankton) in terms of their relative stabil-
ity, and concluded that resistance and resilience are a function of the avail-
ability of nutrients. Of the systems considered, the intertidal salt marsh is
the most resistant and resilient to perturbation due to a large reserve of
nutrients in the sediment and a tidal energy subsidy to circulate them. Con-
versely, planktonic communities, with limited nutrient reserves and no substra-
tum to support and conserve biomass, are the most unstable. Coral reefs
appear to have intermediate stability. Of particular relevance to nutrient
impact assessment in freshwaters is the idea that naturally enriched systems,
which contain species adapted to high nutrient concentrations and abiotic
sinks for excess nutrients, are relatively stable with respect to nutrient
enrichment. Nutrient-poor systems, on the other hand, have a limited capacity
to process excess nutrients and thus, "their only recourse in the presence of
[nutrient] pollution is succession, sometimes to an almost entirely different
kind of community..." (Pomeroy 1975). Stability in relation to available
nutrients is a qualitative and comparative system property but might be
estimable in quantitative terms through simulation models of aquatic ecosystems.
The concept deserves further research.
6.4 SELECTION OF APPROPRIATE VARIABLES
In conducting an environmental impact analysis or implementing an environ-
mental management scheme, one is confronted with the task of selecting a set
of variables which best reflect the response of an ecosystem to disturbance or
to various managerial alternatives. Most of the variables reviewed in this
chapter are potential candidates for this set in various situations. Thus,
given the current state of our understanding of freshwater ecosystems, it
appears that a universally applicable set of variables (and response criteria)
for nutrient and sediment impact analysis is not attainable and perhaps not
even desirable (Verneaux 1976). Spatial heterogeneity across the United States
(climatic, geologic, hydrologic, biotic, etc.) creates a wide range of con-
ditions which influence the nature and stress response of freshwater ecosystems,
and in a quantitative sense each system is unique. This view, of course,
precludes any feasible management strategy. However, a number of features
(components and processes) are common to many freshwater ecosystems and have
been the basis for classification schemes which aggregate lakes (e.g., Brink-
hurst 1974) and streams (e.g., Cummins 1975) into distinct types. Such typol-
ogies appear to be necessary for effective management and should be useful in
identifying biotic and abiotic variables which are important in certain kinds
of ecosystems.
The premise of this report is that the regional scheme integrates many of
the factors which account for spatial and temporal variability of freshwater
ecosystems, leaving remaining factors to be considered at lower hierarchical
levels. The remainder of this chapter 1) examines the biotic and abiotic
variables which appear to be most appropriate to the analysis of nutrient and
sediment impacts in lotic and lentic ecosystems, and 2) develops a scheme for
a hierarchical approach to the analysis of nutrient and sediment impacts. The
purpose is not to define a standard set of parameters, but to provide a
rational basis for deciding which variables are most likely to be important in
particular situations.
108
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6.4.1 Individual and Population Level
At the population and individual levels of organization, nutrient and
sediment impacts are best assessed with in situ and laboratory bioassays.
Species tolerance and algal nutrient-bioassay procedures are well developed
for evaluating direct effects of nutrients and sediment on biota (see section
6.3.1). However, methods for assessing indirect effects are lacking. It is
likely that these effects must be considered at higher levels of organization
possibly through microcosm or whole system studies.
6.4.2 Community Level
As mentioned earlier, freshwater communities are frequently studied as
aggregates of organisms with similar life modes or habitat preferences (Odum's
[1971] minor communities). Figure 6.2 (Hellawell 1977) shows the relative
emphasis which has been placed on various freshwater communities in river
pollution studies, and Table 6.6 (Hellawell 1977) indicates the relative advan-
tages and disadvantages associated with each. Macroinvertebrates and algae
have obviously received the most attention, probably because sampling metho-
dologies and taxonomies for these groups are fairly well developed. However,
it is important that all of the relevant groups in Figure 6.2 be considered,
not as isolated entities, but within the context of the system of which they
are a part.
Viruses
Bacteria
Fungi
Yeasts
Algae
Macrophytes
Protozoa
Macroi nvertebrates
Fish
0
10 20
Percent
30
Fig. 6.2. Percentage distribution of taxa recommended for use as indicators
based on a literature survey. (From Hell awe!1 1977.)
109
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Table 6.6. Advantages and disadvantages of different taxa as indicators.
(From Hellawell 1977.)
Taxon
Bacteria
Advantages
Disadvantages
Indicators of faecal pollution.
Rapid response to environmental
changes, including organic and
heavy metal pollution. Samples
relatively easy to obtain.
ROUTINE METHODOLOGY WELL DEVEL-
OPED. Automatic methods for total
counts.
Drifting cells—origin not clear,
maximum numbers probably down-
stream of origin of organic
pollution. Rapid recovery after
intermittent pollution. Need
for facilities for steriliz-
ing equipment, plating, incu-
bating, etc. Delay in obtain-
ing results from cultures.
Problem of distinguishing dead
and living cells in direct
counts without special tech-
niques. Is bacteriology of
"clean" waters well known?
Variability of counts.
Protoza
Supposed rapid response to changes.
SAPROBIC VALENCIES WELL DOCUMENTED
(e.g., Bick 1968) even within gen-
era, e.g. Vorticella (Sladecek,
1971). Gross collection of sam-
ples easy.
Taxomonic ability required and
good facilities for examination.
Some dispute over indicator
values since present in "normal"
environments. Studies must be
quantitative. Drift problems.
Variability of microhabitats.
Algae
Macroi nvertebrates
Useful for eutrophication estimates
and sensitivity to turbidity effects
(attached forms). POLLUTION TOLER-
ANCES WELL DOCUMENTED, e.g.,
Fjerdingstad (1964, 1965), Palmer
(1969) and several papers by
Patrick (e.g., 1954). Automa-
tion of counting total numbers.
Many sedentary forms—localized
effects of pollution detectable.
Good keys for several groups. Use-
ful for integration of pollution
effects, especially where life
history is long. Periodic sampling
may therefore be more valid. Qual-
itative sampling easy. WIDE RANGE
OF FORMS AND HABITS—COMMUNITY AS
A WHOLE LIKELY TO BE SENSITIVE
INDICATOR AND APPLICATION OF NU-
MERICAL METHODS (SPECIES DIVER-
SITY INDICES) PROBABLY VALID.
Elaborate equipment not required.
Not directly useful for heavy
organic pollution, nor as indi-
cators of faecal contamination.
Not as sensitive to pesticides
and heavy metals as other groups.
Taxonomic expertise needed.
Drift problems with unattached
forms. Quantitative sampling
difficult for epilithic/epiphy-
tic forms. Counting tedious.
Possible rapid recovery of
flora. Difficulty in distin-
guishing living and dead cells
in some cases.
Many species drift and may be
found in regions where they
cannot maintain themselves in-
definitely. Groups expected in
"poor," and especially lowland,
conditions (Chironomids and
Oligochaetes) not easily iden-
tified. Some groups without
adequate keys, e.g., Trichoptera.
Absence may be normal part of
life cycle—results must be
interpreted with care. QUANTI-
TATIVE SAMPLING DIFFICULT. IM-
PORTANT TO CHOOSE SIMILAR SUB-
STRATES WHEN SAMPLING.
Macrophytes
Fixed and relatively easily seen
and identified. Good indicators
of suspended solid loads. Good
indicators of enrichment of soft
water.
RESPONSE TO POLLUTION NOT WELL
DOCUMENTED (but see Besch and
Roberts-Pichette, 1970). Seas-
onal. Tolerant of intermittent
pollution. Poor indicators of
enrichment of chalk streams.
no
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Table 6.6. Continued.
Taxon Advantages Disadvantages
Fish INTEGRATORS OF RESPONSES OF FOOD MOBILE—AVOIDENCE BEHAVIOUR.
CHAINS AS WELL AS IMMEDIATE EFFECTS COLLECTION OF SAMPLES NEEDS
ON PHYSIOLOGY. METHODOLOGY WELL MANPOWER.
DEVELOPED. IDENTIFICATION EASY.
Monitored to some extent by anglers.
These community groups also represent functional components of freshwater
systems which often are employed, with greater or lesser degrees of aggrega-
tions, in ecosystem models. Specification of the couplings (material/energetic)
between these components places them in a system context and elucidates biotic
variables which require consideration at the community level. The existence
of standardized sampling methods and taxonomic keys for several of these groups
(e.g., American Public Health Association) simplifies their study and quanti-
fication. For the more-poorly studied groups (e.g., bacteria, fungi, yeasts,
protozoa), quantitative procedures need further development.
In Chapter 10 a conceptual framework has been developed for the incorpor-
ation of community groups into models of standing and flowing water ecosystems.
These models recognize spatial heterogeneity of freshwater systems and place
communities in appropriate vertical and horizontal strata. Important abiotic
factors are also included. Flows and component standing stocks of nutrients
(e.g., nitrogen or phosphorus) are used in the models to predict community
level effects of nutrient enrichment. Measurements of elemental composition
of communities, certain community metabolic activities (e.g., photosynthesis
and nitrogen fixation), and feeding transfer rates are necessary for model
simulation and impact predictions. While sediments are not explicitly
modelled as conservative flows, their impact on communities can be simulated
as influences on nutrient dynamics within the model.
6.4.3 Watershed Level
In studies of the effects of stress on ecosystems, Barrett et al. (1976)
suggest the study of both structural and functional ecosystem properties.
They recommend a "state variable approach" which balances and integrates these
properties. In this approach "rate processes" (those involved in energy and
matter transfers) are coupled with "state variables" (system components) to
form simulation models which predict system behavior through time under the
influence of "driving variables" (factors external to the system which are
unaffected by system behavior). Odum and Cooley (1976) suggest the study of
integrative and interactive system properties in addition to a few "red flag"
components which are of special concern in the local situation (e.g., game
organisms, endangered species, heavy metals, or organic poisons). Table 6.7
gives their comparison of "standing state" measures, which are often used in
freshwater impact assessments, with "dynamic state" measures which might be
more appropriate.
Ill
-------
A number of watershed level properties are pertinent to nutrient and
sediment impact assessments. Since nutrient loading usually has a direct
effect on aquatic plants, measurement of variables which reflect primary pro-
duction should be a first consideration in nutrient impact assessments. The
set of variables which defines trophic state (see Table 6.1) includes struc-
tural and functional biotic properties as well as relevant abiotic parameters.
Several models have been developed for predicting the impact of nutrient
enrichment on aquatic primary production (Chapter 7). Indirect Impacts of
nutrient enrichment are primarily associated with transfers of the excess
organic matter produced within the system. Trophic state variables as well as
measures of respiration and detrital characteristics reflect these processes.
Table 6.7. Comparison of the structural and functional approaches to the
assessment of a body of water. (From Odum and Cooley 1976.)
Standing State Dynamic State
Measurements Measurements
Dissolved Oxygen (D.O.) Diurnal Oxygen Metabolism
Dissolved Phosphate Phosphate Turnover Rate
Phytoplankton Biomass Chlorophyll Concentration
(as index to primary production)
List of Species Indexes of Species Diversity
Density of Fish Fish Production
Suspended sediment can influence a number of processes and components in
freshwater systems, depending on its concentration. These effects are studied
at lower levels of organization (organism or population levels). At lower
concentrations sediment impacts are usually indirect and are measurable at
the system level. Reduced light penetration into the water column inhibits
primary production, which in turn reduces overall biotic activity. This is
reflected in measures of production and respiration.
6.5 HIERARCHICAL APPROACH TO IMPACT ASSESSMENT
It is implicit in this literature review that freshwater biota can be
studied not only at several levels of organization but also at several levels
of magnitude as well (e.g., laboratory bioassays, in situ enclosures, whole
system studies). In terms of impact assessment, this is consistent with the
suggestion of Barrett et al. (1976) that "stress-effect evaluations should
112
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include . . . microcosm, seminatural, and natural" systems. These levels are
complimentary and observations at one level help to explain phenomena at the
other levels. More precisely, these levels of magnitude represent models of
the real system of interest and may be physical or abstract (diagrammatic or
mathematical) in form. In Figure 6.3 levels of magnitude have been combined
with the classification of quantifiable biotic properties from Table 6.1 to
form a three-dimensional figure. Each sub-block within the figure represents
a set of structural or functional biotic properties at some level of magni-
tude and organization. Thus, the left, lower, rear sub-block might include
an in situ bioassay for studying respiratory activity of a fish exposed to
sediment loading, or a dose-response regression model. The right, lower,
front sub-block might contain a stability analysis study of a lake system or
a nutrient input/output model for the lake.
<*h
°r *%,, *
°^ V,
Fig. 6.3. Classification scheme for quantifiable biotic properties.
This scheme provides an integrative framework for structuring impact
assessment problems. After initial development of a conceptual model,
Fig. 6.3 is entered at the watershed-ecosystem level. Important structural
and functional variables are studied in situ to establish "base-line" condi-
tions followed by perturbation studies conducted in enclosures and/or simpli-
fied microcosms. Enclosure studies might help identify key species and
important variables at the community level. The conceptual model is a guide
to selection of community components which should be examined in the field to
determine undisturbed conditions (e.g., diversity, biomass, P/R) before per-
turbation studies are conducted at lower levels of magnitude. "Red flag"
113
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species or "species of interest" are studied at the population and organism
levels of organization. Abundance and distribution information is gathered
in the field and in situ and/or laboratory bioassays establish population and
organism tolerances to perturbation. Although the procedure is described as
a sequence of events, in practice some of these investigations are conducted
simultaneously and not necessarily in the given order. The integrative nature
of this scheme lies in the use of information at one level as a guide to
further study at the same or other levels. This constant feedback of infor-
mation is necessary for refinement of conceptual models and keeps teams of
investigators in close contact with one another.
This approach recognizes that the nature and stress response of each level
of organization is to a large degree dependent on the structure and function
of the next higher as well as the next lower level. Thus, impact assessment
must be an integrative process to derive a meaningful evaluation of the
response of natural systems to human activity. A complete picture can emerge
only from studies of structural and functional variables at several levels of
organization and magnitude.
6.6 LITERATURE CITED
Aberg, B., and P.P. Hungate, eds. 1967. Radioecological concentration
processes. Pergamon Press, Oxford, Eng. 1040 p. (cited in Odum 1971).
Ahl, T. 1975. Effects of man-induced and natural loading of phosphorus and
nitrogen on the large Swedish lakes. Verh. Internat. Verein. Limnol.
19:1125-1132.
Alabaster, J.S. 1977. Classification of European rivers using biological
methods. Pages 1-8 in U.S. Alabaster, ed. Biological monitoring of
inland fisheries. Applied Science Pub!., London.
Allen, H.L. 1972. Phytoplankton photosynthesis, micronutrient interactions,
and inorganic carbon availability in soft-water Vermont lake. Pages
63-83 jjx G.E.-Likens, ed. Nutrients and eutrophication: The limiting
nutrient controversy. Special Symposia, Vol. 1, Amer. Soc. Limnol.
Oceanogr., Lawrence, Kan.
All urn, M.O., R.E. Glessner, and J.H. Gakstatter. 1977. An evaluation of the
National Eutrophication Survey Data. USEPA, Nat. Env. Res. Ctr.,
Corvallis, Ore. Working paper No. 900.
American Public Health Association. 1976. Standard methods for the
examination of water and v^astewater. 14th ed. Amer. Publ. Health
Assoc., Washington, D.C. 1193 p.
Andelman, J.B. 1973. Incidence, variability and controlling factors for
trace elements in natural, fresh waters. Pages 57-88 jji P.C. Singer,
ed. Trace metals and metal-organic interactions in natural waters.
Ann Arbor Science Publ., Ann Arbor, Mich.
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Archibald, R.E.M. 1972. Diversity and some South African diatom associations
and its relation to water quality. Water Res. 6:1229-1238.
Armitage, P.O. 1977. Invertebrate drift in the regulated River Tees, and
an unregulated tributary, Maize Beck, below Cow Green dam. Freshwater
Biol. 7:167-183.
Armstrong, F.A.J., and A.L. Hamilton. 1973. Pathways of mercury in a
polluted northwestern Ontario lake. Pages 131-156 TJX P.C. Singer, ed.
Trace metals and metal-organic interactions in natural waters. Ann
Arbor Science Publ., Ann Arbor, Mich
Atkinson, D.E. 1969. Regulation of enzyme function. Ann. Rev. Microbiol.
23:47-68.
Ball, R.C., N.R. Kevern, and T.A. Haines. 1973. An ecological evaluation of
stream eutrophication. Inst. Water Res., Mich. State Univ., East
Lansing, Mich. Tech. Rept. No. 36.
Barrett, G.W., G.M. Van Dyne, and E.P. Odum. 1976. Stress ecology.
BioScience 26:192-194.
Barton, B.A. 1977. Short term effects of highway construction on the
limnology of a small stream in southern Ontario. Freshwater Biol.
7:99-108,
Baudouin, M.F., and P. Scoppa. 1975. The determination of nucleic acids
in freshwater plankton and its ecological implications. Freshwater
Biol. 5:115-120.
Beak, T.W., C. deCourval, and N.E. Cooke. 1959. Pollution monitoring and
prevention by use of bivan*ate control charts. Sewage Ind. Wastes
31:1383-1394.
Beck, W.M., Jr. 1955. Suggested method for reporting biotic data. Sewage
Ind. Wastes 27:1193-1197.
Berman, M.S., and D.R. Heinle. 1978. The effect of low level hydrocarbon
pollution on copepod feeding. Abstract Paper presented 41st Annual
Meeting, Amer. Soc. Limnol. Oceanogr., Victoria, B.C. Can.
Berman, T., and R.W. Eppley. 1974. The measurement of phytoplankton
parameters in nature. Sci. Prog., Oxford 61:219-239.
Besch, W.K. 1973. Cartographic ecologique des eaux courantes de Bades-
Wurtemberg. Ann. Hydrobiol. 4:1-9. (cited in Hawkes 1977).
Besch, W.K. and Roberts-Pichette, P. 1970. Effects of mining pollution on
vascular plants in Northwest Miramichi River system. Can. J. Bot.
48:1647-1656. (cited in Hellawell 1977).
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CHAPTER 7
A SURVEY OF AQUATIC ECOSYSTEM MODELLING
7.1 INTRODUCTION
As the interrelations between man and his environment become more
intimately related to his survival, there is increasing need to understand
ecosystem phenomena in a precise way. The need for mathematical models to
predict impact due to nutrient and sediment inputs has become more apparent
in the last decade and has resulted in a flurry of activity in ecosystem
analysis. Impetus was provided by the International Biological Program, which
sponsored numerous modelling programs, and the U.S. Environmental Protection
Agency, which endorsed the use of mathematical modelling for impact assessment.
A diversity of models of aquatic systems appears in the literature. Many
are aimed at understanding the complexities of ecological systems especially
with regard to man's impact. There is a need to initiate discussion about
modelling techniques. Such a discussion should promote communication among
environmental modellers and provide assessments so managers can evaluate the
usefulness of models for particular problems.
A number of conferences and symposia have been held to compare modelling
theories and techniques and their application to ecology (Patten 1971, 1972b,
1975b, 1976; Middlebrooks et al. 1973; Innis 1976; Ott 1976). Several
journals such as Simulation, Ecological Modelling, and The International
Journal of General Systems provide forums for models and modelling techniques.
Traditional ecological, limnological, and pollution control journals are more
interested in water quality models which more easily fit into traditional
scientific format than larger models.
This survey is an attempt to assess aquatic ecosystem models in the
literature. Information has been taken from the Survey of Aquatic Ecosystem
Models of The Institute of Ecology (Parker and Roop 1974~J7 Only freshwater
ecosystem models have been examined; the extensive work on marine coastal
ecosystems has not been included. An evaluation of models in terms of useful-
ness in environmental impact studies will be the primary concern. Particular
attention will be given to nitrogen, phosphorus, carbon, and sediment inputs.
7.2 EVALUATION PROCEDURE
Ecosystem modelling is in a state of infancy although it has become
increasingly sophisticated; few comprehensive ecological models of aquatic
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ecosystems have been built. These models are rarely described in the open
literature because of their complexity but are found instead in the internal
literature of organizations. Many models are incomplete because they take so
long to build and are constantly evolving. The modelling and simulation of
aquatic ecosystems is a complicated undertaking with many considerations
involved. Criteria used to evaluate models and modelling philosophy are
discussed below.
7.2.1 Objectives and Philosophy
The major purpose of ecosystem models is to account for and explain
observed behavior of ecosystem properties. The variability accounted for by
a model is related to the precision of the model; a model which describes
more observed system variability is more precise. Coarse resolution models
use a small set of parameters which account for most of the observed variation.
Fine resolution models use a larger set of variables which potentially account
for more observed variation and predict with greater precision or explain in
greater detail. The number of variables used in a model is usually limited
by bounds set by economy and practicality. It is advantageous to use a small
set which can be obtained with a minimum of effort and expense yet still meet
the required standards of precision or explanation. Explanatory models are
sometimes neither the simplest nor the most efficient models.
Ultimately a model can be judged only as to whether it meets a priori
objectives. A primary objective considered in models discussed here is to
predict the effects of nutrient and sediment perturbations in aquatic eco-
systems. The ability to predict system response can be assessed either in
qualitative or quantitative terms. A second goal of ecosystem modelling
important to impact assessment is to communicate a holistic or macroscopic
ecosystem perspective. Ecological, political, and social managers often must
be made to think in terms of ecosystems rather than in terms of isolated
components and events. A third objective of many aquatic ecosystem models
is to provide and evaluate hypotheses about ecosystem structure and behavior.
Models, being hypotheses concerned with the nature of ecosystems and ecosystem
behavior, need to be tested and contrasted with opposing ecosystem hypotheses.
An evolving course will gradually emerge representing a compromise among
different theories.
7.2.2 Generality
Several models are meant to be general ecosystem paradigms which are
potentially applicable to a wide vareity of ecosystems. Although much
information used in ecological models is obtained from general ecological
literature (Overton 1977), site specific data are often required to calibrate
a model. The best way to evaluate the generality of a model is to enumerate
the systems where the model has been applied.
7.2.3 Level of Resolution
Models of aquatic ecosystems can be classified at several levels of
resolution. Coarse resolution water quality models deal with macroscopic
properties of systems (e.g., mean depth, volume, flow rate, retention time)
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and predict variables such as dissolved oxygen, dissolved phosphorus, and/or
chlorophyll concentrations. At the other end of the spectrum are fine reso-
lution models which involve and predict properties of ecological components
and their interactions. Fine resolution models are potentially capable of
predicting dynamic ecosystem properties with greater precision than coarse
resolution models (Scavia and Chapra 1977). The required level of resolution
depends on questions being asked of the system and the needed precision of
the answers.
7.2.4 Model Structure
Components and interactions demonstrate the dependency network of systems
by describing the paths over which cause and effect travel (Hutchinson 1948;
Caswell et al. 1972; Patten et al. 1976). Biotic, chemical, and physical
components can be regarded as propagators of cause. In fine resolution models
the internal cause and effect structure may be identified in great detail.
Compartments and State Variables
Compartments often represent stores of conservative materials such as
energy, biomass, numbers of organisms, nitrogen, phosphorus, or carbon. State
variables describe properties of physical, chemical, and biological compart-
ments. Usually only a few properties are simulated in a single model because
of the complexity introduced by modelling large numbers of properties
(Bierman et al. 1973). As indicated in Chapter 5, some biotic compartments
have been used in a majority of nutrient and sediment impact studies and in
ecological models. These compartments have been selected on the basis of
usefulness for field research and their ability to assess impact.
Interactions
Prevailing ecosystem paradigms indicate that many processes are basic to
ecosystems: nutrient cycling, primary production, herbivory, carnivory,
decomposition, detritivory, etc. (E. P. Odum 1971). Mathematical formulations
and coefficient values which describe interactions vary between models, such
as in the nutrient limitation of phytoplankton (Park et al. 1978). The
mathematical form may not be as important as the existence of the ecological
relationship, especially in a system near steady state. Model behavior is
largely determined by network structure and coefficient formulations which
describe the dependency structure in an ecosystem (Hill and Durham 1978;
Hill 1979).
Several mathematical formats have been used for modelling aquatic eco-
systems. When differential or difference equations are used to describe
behavior of ecosystems, relationships among components are assumed to be
deterministic. Stochastic models of ecosystems have also been constructed
(Parker 1974; Abendt 1975; Barber 1978a, 1978b). Discussions of stochastic
versus deterministic models can be found in Wiegert (1975a), and Parker (1974),
Many models are modular, having been built in terms of submodels which
are then brought together. The usefulness of the modular approach for con-
structing systems is pointed out in the watchmaker's parable of Simon (1973).
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The watchmaker's work Is facilitated by building 10 subcomponents consisting
of 10 parts each and then putting these subcomponents together, rather than
building the whole directly from 100 parts. Modularity allows flexibility in
adding or modifying components when components are built to fit together.
Inflows and Terrestrial-Aquatic Coupling
Aquatic ecosystems are open to their environments and are driven by
allochthonous carbon and nutrient inputs (Hynes 1970; Boling et al. 1975;
Cummins 1975; Wetzel 1975). The importance of the watershed in determining
the behavior of aquatic ecosystems has been the focus of contemporary eco-
logical research (Likens and Borman 1972; Schindler et al. 1976). Although
ecologists have studied nutrient relationships between watersheds and aquatic
systems, no comprehensive ecological model has been built which unites a
watershed model with an aquatic ecosystem model. Establishing the terrestrial-
aquatic link is an important direction that modelling must take.
Outflows
Outflows are as important in determining the properties of aquatic
ecosystems as inflows. Tributary outflow, harvesting, evapotranspiration,
sedimentation, and groundwater seepage are important to ecosystem behavior.
Rivers and streams are flow-through systems by definition; lakes are impound-
ments for drainage systems but generally have outflows.
Controls
Various physical and chemical factors constrain and often drive the
behavior of aquatic ecosystems and their components. Temperature, circulation,
turbidity, and pH are some of the controls which are simulated in aquatic
ecosystem models.
Spatial Considerations
The spatial structure of aquatic ecosystems is important in determining
ecosystem behavior. Reaches of a stream vary with flow rates, substrate type,
watershed type, etc. (Hynes 1970). Spatial diversity in lakes and reservoirs
can influence system behavior (Vollenweider 1968; O'Melia 1972; Vollenweider
and Dillon 1974; Oglesby and Schaffner 1978). The spatial structure of
streams and rivers is different from lakes and reservoirs and helps to account
for their different behaviors.
Systems Analysis and Simulation
Systems analysis techniques provide a basis for assessing model behavior
and generating new hypotheses about ecosystem structure and behavior. Simu-
lation and perturbation trials, sensitivity analyses, network analyses, flow
analyses, and model aggregation or condensation, are techniques which have
management implications. Model validation or verification also must be
considered with systems analysis techniques. As statements about real eco-
systems, models should be assessed in terms of real world behavior, that is,
they need to be validated. Formal statistical techniques often are not useful
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for validating ecosystem models (Wiegert 1975a; Innis 1976; Mankin et al. 1977),
Less formal qualitative techniques, such as comparison or corroboration of
calculated results with observed results, often are used to validate models
(Caswell 1976).
7.3 MODEL EVALUATIONS
A summary of models in the literature detailing the points discussed above
is presented in Table 7.1. Detailed evaluation of eight major aquatic eco- .
system modelling approaches follows this. These approaches include coarse
resolution water quality models which are assessed first (section 7.3.1).
Then several models which involve a fine level of resolution are examined:
the Eastern Deciduous Forest Biome lake models, the Manhattan College models
of the Great Lakes, the ecological model, Coniferous Forest Biome stream
models, the energy circuit language, and the linear modelling approach used
in Lake Texoma Cove (sections 7,.3.2 - 7.3.7).
7.3.1 Coarse Resolution Water Quality Models
Coarse resolution water quality models are used to rapidly assess
ecosystem productivity and impact of nutrient loading with a few easily
measured parameters. Several major references on the coarse resolution water
quality models exist (O'Connor 1961; Vollenweider 1968, 1972, 1975; O'Connor
and Mueller 1970; O'Melia 1972; Vollenweider and Dillon 1974; Abendt 1975;
Oglesby and Schaffner 1978; Schaffner and Oglesby 1978; Schindler 1978).
Objectives and Philosophy
The primary objective of these models is to predict or explain water
quality changes resulting from pollution or nutrient loading (Vollenweider
and Dillon 1974). Another objective is to establish criteria for tolerable
and critical loadings based on easily measured parameters. Water quality
models provide a framework for comparing nutrient loading and water quality
relationships in a large number of aquatic ecosystems. Some models predict
recovery time of a lake after nutrient diversion (Dingman and Johnson 1971;
Cooke et al. 1973; Emery et al. 1973).
Generality
Water quality models are relatively simple and applicable to a wide range
of lakes and streams. Vollenweider-type lake models have been applied to a
number of situations in North America and Europe but have been restricted to
well-mixed bodies of water studied in classic limnology (Sonzogni and Lee
1972). Spatially diverse systems such as marshes, swamps, and shallow littoral
lakes are not handled well. Models which predict biological oxygen demand
(BOD) have been applied to a number of streams and rivers throughout the
United States (O'Melia 1972).
Although coarse resolution models are theoretically useful for any
nutrient, they usually have been used for oxygen in streams and phosphorus in
lakes. Carbon and chlorides also have been modelled using this approach
139
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Table 7.1. A survey of aquatic ecosystem models with characteristics related to ability to predict impact,
MODEL REFERENCE
Abendt 1975
81 cornfield et al. 1973
Park 1974
Boling 1974
Brandes et al. 1973
Brylinski and Mann 1973
Chapra 1979
Chen 1971
Chen and Orlob 1972
Chen and Orlob 1972
Chen and Orlob 1975
Cooke et al. 1973
SYSTEM
Stream
Lake George
August
Creek
Tell i co
Reservoir
IBP Lakes
Saginaw Bay
Reservoirs
Lake
Koocanusa
Puget Sound
Lake
Washington
Twin Lakes
REGION
General
New York
Division 21
Michigan
Division 22
Tennessee
Division 22
Michigan
Division 22
California
Montana
Division 31
Washington
Division 24
Washington
Division 24
Ohio
Division 22
SPATIAL
PARTITIONS
None
Pelagic Regions/
Sediments
None
Interconnected
Spatial Sections
None
None
Interconnected
Spatial Sections
Interconnected
Spatial Sections
Interconnected
Spatial Sections
Interconnected
Spatial Sections
Littoral, Epi-,
Meta-, Hypo-
limnion, Sediments
AQUATIC
TERRESTRIAL
INTERACTIONS
Nutrient Load-
ing Data
Time Varying
Inputs
Hydrology and
Waste Input
None
Nutrient Loadings
Hydrology and
Waste Input
Hydrology and
Waste Input
Hydrology and
Waste Input
Hydrology and
Waste Input
Watershed Input
TYPE
R
G
R
E
S
S
0
N
X
S
M
U
L
A
T
I
0
N
X
X
X
X
X
X
X
X
X
X
WATERSHED
INPUTS
N
X
X
X
p
X
X
X
c
s
E
D
I
M
E
N
T
X
x • x
X X
i :
i X! !
X
X
X
X
X
X
X
X
X
X ' X
X: X
X
X
y
x
CHEMICAL
COMPONENTS
P
0
M
X
X
X
X
X
X
X
D
0
M
X
X
X
X
X
X
X
X
0
X
Y
G
E
N
X
c
H
0
R
0
P
H
Y
L
X !
i
x
X
i
X:
X
X
X
BIOTIC
COMPONENTS
C
R
P
T
E
X
X
A
L
G
A
E
X
X
M
R
0
F
A
U
N
A
X
X
X
X. X
X' X
X
X
X
X
X
X
M
C
R
0
5
N
A
X
X
X
X
X
X
X
F
I
S
H
X
X
X
X
X
X
c
0
I
E
R
s
X
X
X
X
X
X
X
M
I
S
C
E
L.
-------
Table 7.1. (Continued)
MODEL REFERENCE
Correll 1974
Dettmann 1974
Dillon and Rigler 1974
Gayle 1975
Gi 111 land 1975
Glanz 1972
Glanz et al. 1972
Glanz and Orlob 1973
Hall 1974
Huff et al. 1973
Kadlec 1978
SYSTEM
Ihode River
Lake Wingra
Lakes
Lake
Okeechobee
Peninsular
Florida
Peace River
Blue Marsh
Reservoir
Tock Island
Dam
Lincoln
Lake
Flax Pond
Estuary
Lake Wingra
Houghton
Lake Marsh
REGION
*
Maryland
Division 23
Wisconsin
Division 22
Northern
U.S.
Florida
Division 23
Florida
Division 23
Pennsyl-
vania
New Jersey
Illinois
Division 25
New York
Division 22
Wisconsin
Division 22
Michigan
Division 21
SPATIAL
PARTITIONS
Pelagial
None
Marsh, Pelagic
Regions, Sediment
Peninsular Florida
Peace River
Interconnected
Spatial Sections
Interconnected
Spatial Sections
Interconnected
Spatial Sections
Pelagic Region
Interconnected
Spatial Sections
AQUATIC
TERRESTRIAL
INTERACTIONS
Watershed-
Estuary
Constant F
Loading
Waste Input
P mining, wastes
from watershed
Hydrology and
Waste Input
Hydrology and
Waste Input
Hydrology and
Waste Input
Hydrologic
Transport Model ,
Nutrient Loading
Sewage Input
TYPE
R
r
G
R
t
S
I
0
N
X
S
I
M
u
1
A
T
0
N
X
X
X
X
X
X
X
X
X
X
WATERSHED
INPUTS
N
X
X
X
X
X
X
X
X
X
p
X
X
X
X
X
X
X
X
X
X
X
c
X
X
X
X
X
X
s
E
D
I
M
E
N
T
X
X
X
X
X
CHEMICAL
COMPONENTS
P
0
M
X
X
X
X
X
X
X
X
D
0
M
X
X
X
X
X
X
X
X
0
X
Y
G
E
N
X
X
X
X
X
u
L
0
8
p
H
Y
L
1
X
X
BIOTIC
COMPONENTS
M
A
P
H
v
X
X
X
A
L
U
A
E
X
X
X
X
X
X
X
X
X
X
A1
fl
p
0
ft
X
X
X
X
X
X
X
M
r
R
o
A
I
X
X
X
X
X
X
X
F
I
b
H
X
X
X
X
X
X
X
D
t
X
M
P
0
R
X
X
X
X
X
X
X
M
I
b
C
b
L.
-------
Table 7.1. (Continued)
MODEL REFERENCE
King 1973
MacCormick et al. 1972
Marshall et al. 1976
Mclntyre and Colby 1978
O'Connor and Dobbins 1958
Odum 1978
Oglesby and Schaffner 1978
Schaffner and Oglesby 1978
O'Melia 1972
Parker 1974
Patten et al. 1975
Rich 1974
SYSTEM
Trinity
River
Lake Wingra
Beaver
River Basin
Oregon
Streams
Stream
Cypress
Swamp
Lakes
Lakes
Libby Lake
Lake Texoma
Cove
Dunham Pond
REGION
Wisconsin
Division 22
Ohio, Penn-
sylvania
Di vision ?2
Oregon
Florida
Division 23
New York
Division 21
Europe
Wyoming
Division 21
Oklahoma-
Texas
Division 25
Connecticut
SPATIAL
PARTITIONS
Pelagic Region
River Junctions,
Stretches, Head-
watpr Rparhpt;
None
None
Watershed,
Cypress Dome
Epi-, Hypolimnion
Sediment
None
Watershed Model
AQUATIC
TERRESTRIAL
INTERACTIONS
Watershed Input
Watershed Input
Pollutant Input
Sewage Input
Constant P
Loadings
Constant P and
C Loading
Time Varying
Inputs
(WATERSHED
INPUTS
R
ei
R
S
I
8
X
s
1
p
A
I
0
N
X
X
X
X
X
X
N
X
X
X
p
X
X
X
X
c
X
X
X
X
X
X
s
t
M
N
X
CHEMICAL
COMPONENTS
P
0
M
X
X
X
n
0
M
X
X
X
n
X
Y
G
E
N
X
X
X
X
C
1
R1
0
p
H
I!
X
BIOTIC
COMPONENTS
M
r.
8
H
Y
1
E
S
X
X
A
L
b
A
E
X
X
X
X
X
M
C
8
i-
A
U
N
A
X
X
X
X
M
R
0
1-
A
U
N
A
X
X
X
X
F
1
H
X
X
X
U
c
0
M
P
0
S
E
X
X
X
X
X
M
S
C
L.
X
ro
-------
Table 7.1. (Continued)
MODEL REFERENCE
Scavla et al. 1976a, 1976b
Schindler 1978
Shannon and Brezonlk 1972
Streeter and Phelps 1925
Vollenweider 1968, 1969
Vollenweider 1972, 1975
Walters 1974
Waring 1974
Whitehead and Young 1974
Wloslnski 1974
SYSTEM
Lake Ontario
Great Lakes
IBP Lakes
Lakes
Ohio River
Lakes
Lakes
IBP Lakes
and
Watersheds
Streams
in
Watershed
Stream
Stream
REGION
Division 22
Florida
Division 23
Division 22
Northern
U.S.,
Eurooe
Northern
U.S.,
Europe
Oregon
Europe
Utah
Division 31
SPATIAL
PARTITIONS
Epi-, Hypo-
limnion
None
None
None
None
None
AQUATIC
TERRESTRIAL
INTERACTIONS
Constant P
Loading
None
Watershed
Characteristics
Pollutant Input
Constant P
Input
Constant P
Loading
TYPE
R
G
1
X
X
I
u
A
j
X
X :
X
X
X
X
WATERSHED
INPUTS
N
X
X
X
p
X
X
X
X
X
X
X
c
X
s
1
M
N
T
1
j
X
X
CHEMICAL
COMPONENTS
P
0
M
X
D
0
M
X
X
0
X
Y
G
E
N
1
. x
C
H
|j
R
9
H
I
X
X
1
1
]
X
BIOTIC
COMPONENTS
M
A
C
R
0
P
H
Y
T
X
X
X
A
L
G
A
E
X
X
X
X
X
M
A
C
R
U
N
A
X
X
X
X
X
M
I
R
0
A
U
N
A
X
X
X
X
X
F
I
S
H
X
X
X
D
E
R
X
X
X
M
I
S
C
E
L.
CO
-------
(O'Connor and Mueller 1970; O'Melia 1972).
Level of Resolution
Water quality models use and predict whole ecosystem properties such as
total phosphorus and will not answer dynamic or detailed questions about
ecological components or interactions. Most lake models are calibrated on an
annual time scale, predict annual system properties, and require measurements
one or two times a year. The most useful time scale for prediction and
measurement may not be a year; instead a "limnological year," having a length
which varies with meteorological, hydrological, and geological conditions may
be defined (Cooke et al. 1973). River models often are calibrated on a shorter
time scale and predict properties at points in space and time, downstream from
point of pollution loading.
Model Structure
Three basic types of coarse resolution models exist: regression,
correlation, and simulation models. Regression models of streams predict
biological oxygen demand or dissolved oxygen using pollution loading and
stream flow, width, depth, and cross-sectional area. Regression models of
lakes predict trophic state and nutrient concentrations using nutrient loadings
and system parameters such as depth, retention time, and area. Correlative
models examine the relationships between several variables such as nutrient
concentrations and chlorophyll concentrations (Brylinsky and Mann 1973; Dillon
and Rigler 1974; Oglesby and Schaffner 1978; Schindler 1978). Correlative
models theoretically should not be used for prediction. Simulation models
include differential, difference, or stochastic equation models which predict
nutrient concentrations or trophic state on the basis of system inputs, out-
puts, and processes affecting concentrations (O'Melia 1972; Vollenweider 1972,
1975; Vollenweider and Dillon 1974; Whitehead and Young 1974). Inputs are
from the watershed, the atmosphere, and the sediments; outputs are to outflow,
the atmosphere, and the sediments. Refinements include loss to sediments,
atmospheric invasion, chemical reactions, internal recycling by biota and
sediments, and time-varying inputs.
Consideration of spatial heterogeneity in coarse resolution models can
account for some of the variation in observed ecosystem behavior. Variation
in lake behavior can be explained by considering the littoral zone and shore-
line (Vollenweider 1968). Vertical stratification is important in many lakes
and can be included in water quality models (O'Melia 1972; Huff et al. 1973;
Dillon 1974; Oglesby and Schaffner 1978).
The ability of models to predict impact depends on the quality of nutrient
loading measurement. Measurement of nutrient loading is often difficult
because of numerous and diffuse sources, and time-varying input data may be
required to make valid predictions (O'Melia 1972; Sonzogni and Lee 1972;
Cooke et al. 1973) making necessary more data and larger sampling programs.
Phosphorus loading can be estimated on the basis of watershed characteristics
(Ratal as 1972; Shannon and Brezonik 1972; Cooke et al. 1973; Ratal as and
Salki 1973; Vollenweider and Dillon 1974), and drainage area, geology, land
use, and population have been suggested as influencing characteristics
144
-------
(Cooke et al. 1973; Vollenweider and Dillon 1974; Dillon and Kirchner 1975).
Systems Analysis and Simulation
Because of their simplicity and small data requirements, coarse resolution
water quality models can be easily validated. Correlations between model
parameters and ecosystem properties such as chlorophyll, trophic state, and
phosphorus concentrations are often high (Brylinski and Mann 1973; Vollenweider
and Dillon 1974; Schindler 1978). Simple input-output water quality models
are compatible with statistical validation procedures (Abendt 1975).
Assessment
Coarse resolution water quality models provide a quick and useful way of
assessing pollution in streams and eutrophication in lakes; however, these
models are not as inherently precise as fine resolution models, and they
generally do not predict dynamic properties. Only well-mixed systems can be
adequately described by the simpler models. Structurally complex systems can
be modelled by adding terms representing spatial heterogeneity. Nutrient
loadings (especially nitrogen) need to be better characterized in terms of
watershed properties, variation with time, and sediment and biotic regener-
ation. Phosphorus-chlorophyll correlation models are indirectly related to
phosphorus loading and their usefulness in predicting impact should be
evaluated.
7.3.2 Eastern Deciduous Forest Biome (EDFB) Aquatic Ecosystem Models
The initial Eastern Deciduous Forest Biome model was the Comprehensive
Lake Ecosystem Analyzer (CLEAN) which was intended to be a model framework
for incorporation of other work done in the Eastern Deciduous Forest Biome.
CLEAN has evolved into the more recent models CLEANER AND MS. CLEANER. Com-
prehensive modelling and field research was done at two sites within the
Eastern Deciduous Forest: Lake George, New York and Lake Wingra, Wisconsin.
Coordination between the two sites was accomplished by a multidisciplinary
research team, which established close relationships between modellers and
field researchers. Documentation for CLEAN can be found in Park and
Wilkinson (1970, 1971), Park et al. (1972), and Park et al. (1974); for
CLEANER in Scavia (1974), Blcornfield et al. (1975), Park et al. (1975),
Scavia and Park (1976), and Clesceri et al. (1977); and for MS. CLEANER in
Groden (1977), Desormeau (1978), Park et al. (1978, 1979).
Objectives and Philosophy
The central objective of the modelling program has been to understand
better ecosystem dynamics. An effort was made to include as much biological
and ecological realism as possible. A second objective was to predict the
consequences of man-induced perturbations. Thirdly, the modelling program
was to couple all generalized aquatic process models developed in the Biome.
Generality
CLEAN, CLEANER, AND MS. CLEANER were built to be used at either
145
-------
Lake George or Lake Wingra which represent "different ends of the environmental
continua." The models were intended to be flexible enough to model other
ecosystems as well. A number of European lakes have been modelled with
MS. CLEANER (Park et al.1978). Many ecological formulations used in these
models are general; a terrestrial ecosystem energy model described by O'Neill
et al. (1972) was the source of many formulations used in the models
(Blcornfield et al. 1973).
Level of Resolution
Models and submodels were constructed at several levels of resolution.
CLEAN, CLEANER, and MS. CLEANER compromise generalized process submodels
which represent basic ecological interactions occurring within aquatic eco-
systems. A number of fine resolution submodels were built to simulate
detailed processes, which are used when precise results are needed. CLEAN
consists of 28 compartments and operates for a year with time steps of one
day or less. MS. CLEANER consists of up to 20 biotic state variables and 20
abiotic state variables in each of 10 spatial segments; it is rarely run in
its entirety because of its complexity. Because simulations are expensive and
time consuming, it is advantageous to use as little of the model as possible
to adequately answer questions. As few as two state variables have been used
in a simulation (Park et al. 1978).
Model Structure
Components in MS. CLEANER potentially include phytoplankton (4 types),
submersed aquatic macrophytes (4 types), zooplankton (5 types), fish (2 or
more types), bottom animals (2 types), bacteria and fungi (3 types), DOM (7
types), POM (4 types), inorganic nutrients (5 types), dissolved oxygen, and
inorganic carbon (3 types). Mass or biomass is used to describe most compart-
ments. However, because age structure affects the behavior of some biotic
components, numbers of organisms can be used simultaneously with mass. Other
components can be added as needed.
Coefficients for equations were determined by experimental research.
Most interactions between components are nonlinear. The basic models have
evolved as various subsystems were created, tested, calibrated, and coupled
with the central model framework. The modular framework facilitates model
evolution.
Nutrient interactions were not included in the initial formulations of
CLEAN (Bloomfield et al. 1973); instead, nitrogen and phosphorus were used as
forcing functions rather than state variables. During evolution of the models,
nutrients were included and nutrient interactions with biota, organic materials
and decomposers became increasingly sophisticated. Development of nutrient
interactions hinged on a decomposition submodel .(Clesceri et al. 1977).
Arguments for various nutrient limitation formulations are expressed in
Bloomfield et al. (1973)., Scavia and Park (1976), and Park et al. (1978).
Internal pools of nutrients in phytoplankton are used to give realistic
simulations (Park et al. 1978). Adaptive characteristics of multispecies-
phytoplankton communities are included in the nutrient limitation character-
istics (Scavia and Park 1976; Groden 1977; Park et al. 1978). Incident solar
146
-------
radiation, water temperature, wind or barometric pressure, allochthonous
dissolved and particulate organic matter, water circulation, and nutrient
loadings are driving variables.
CLEAN is a point model which describes average conditions for a square
meter of lake surface. In order to describe processes which occur in
different parts of a lake, the point model is calibrated to conditions at
each part of the lake. MS. CLEANER can describe spatial heterogeneity with
10 spatial segments which are interconnected via mass flows. These segments
simulate horizontal and vertical diversity within an aquatic ecosystem.
Inclusion of all 10 spatial segments is expensive and unwieldy.
No explicit attempt has been made to couple a watershed model with the
basic aquatic ecosystem models. A Hydrologic Transport Model (HTM) was
developed at the Lake Wingra site (Huff 1968) which predicts nutrient runoff
with various land use practices. Potentially this and other watershed models
can be coupled with the basic aquatic ecosystem models but would greatly add
to computer time and expense.
Systems Analysis and Simulation
Verification of model behavior has been done by comparing calculated
values with observed values. Perturbation and sensitivity analyses have been
done with MS. CLEANER in order to better assess model behavior. Interactive
programming allows one to perturb coefficients, loadings, and state variables.
Sensitivity analyses can be done with a submodel, which introduces random
perturbations of varying magnitudes.
Assessment
The CLEAN, CLEANER, and MS. CLEANER series is the most elaborate aquatic
ecosystem modelling program attempted. The models contain a large degree of
ecological realism; the most recent versions of MS. CLEANER contain provisions
for evaluating "nutrient enrichment, thermal pollution, siltation, impoundment,
and fish removal" (Park et al. 1978). These models are expensive and time
consuming to run because of their complexity; however, modular construction
allows researchers to solve only portions of each model to answer specific
questions.
7.3.3 Phytoplankton-Zooplankton-Nutrient Interaction Models of Manhattan
College
A modelling approach which has been applied to the Great Lakes and
various estuaries is that developed by DiToro, Thomann, O'Connor, and Mancini
of Manhattan College and Hydroscience, Inc. Models derived from this approach
simulate the dynamics of phytoplankton chlorophyll, zooplankton carbon, and
various forms of nitrogen and phosphorus. Documentation can be found in
DiToro et al. (1971), Thomann et al. (1974), and DiToro et al. (1975).
Objectives and Philosophy
This modelling approach uses chemical kinetic laws and mass transport
147
-------
processes. Detailed chemical and physical descriptions of this philosophy
can be found in DiToro (1974, 1976). Objectives include determination of
important interactions in lake eutrophication, analysis of lake water quality,
and biological response to natural and man-made inputs, and estimation of the
direction of change expected with environmental control actions.
Level of Resolution
The models described in Thomann et al. (1974) and DiToro et al. (1975)
are at an intermediate level of resolution. Spatial and temporal distribution
of water quality parameters is predicted on a seasonal basis. Models are run
for at least a year and for up to 10 years.
Generality
The interactions between biotic and chemical compartments are represented
in general form and should be applicable to many lakes. Values of model
variables often are taken from the general literature (Thomann et al. 1974)
and then are adjusted to fine tune the models to data sets. The models have
been applied to Lake Ontario, Lake Erie, and Lake Huron. Similar models have
been applied to the Sacramento-San Joaquin Delta and Potomac estuaries
(O'Connor et al. 1972; DiToro et al. 1977). Phytoplankton and zooplankton
behaviors are simulated but fish, macrophyte, and benthic invertebrate
behaviors are not. Organic nitrogen, ammonia, nitrate, organic phosphorus,
and orthophosphate are chemical forms which have been simulated. Silica and
oxygen are included in the estuary models (DiToro et al. 1977) and can be
incorporated into the lake models.
Model Structure
Each model is a set of nonlinear differential equations which describe
the chemical kinetic relations among biotic and chemical compartments.
Nutrient limitations of phytoplankton are formulated as Michaelis-Menten
interactions. Spatial segments, which are assumed to be well-mixed, simulate
horizontal and vertical heterogeneity within lakes. Although 60-100 segments
potentially can be used in a model, the number and properties of horizontal
segments vary according to the lake and the model objectives; the Lake Ontario
model (Thomann et al. 1974) included only vertical segments, whereas the
Lake Erie model (DiToro et al. 1975) included 4 horizontal and 3 vertical
segments. Arrangement of spatial segments depends on circulation patterns,
basin topography, and inputs from the watershed. Movement of nutrients,
phytoplankton, and zooplankton through a lake are described as physical,
advective, and dispersive processes between the spatial segments.
Simulation and Systems Analysis
Validation of the models has been done by comparing calculated values
with observed values. Qualitative judgements were used for validation;
calculated values were described as being in reasonable agreement with
observations.
148
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Assessment
Good prediction of phytoplankton chlorophyll, zooplankton carbon, phos-
phorus, and nitrogen values have been obtained for several of the Great Lakes
and estuaries. Phytoplankton chlorophyll, as predicted by these models, lags
behind observed values, perhaps because internal phytoplankton pools of
nutrients were not incorporated (Park et al. 1978). These models will not
predict behavior of poorly mixed systems such as marshes and littoral zones.
They do not include fish, macrophytes, and benthic animals, which are important
to nutrient dynamics in many lakes.
7.3.4 Chen and Orlob's Ecological Model
The ecological model of Chen and Orlob has been used for a number of
systems across the country and has been shown to predict successfully. The
most comprehensive application of the model was done for Lake Washington,
Washington, for which Edmondson's (1961, 1969, 1972) extensive data set was
available. Documentation of the modelling approach can be found in Chen
(1970) and Chen and Orlob (1968, 1975).
Objectives and Philosophy
The modelling approach integrates fundamental physical, chemical, and
biological principles in aquatic ecosystems so all pertinent parameters and
processes are coupled. One objective is to simulate ecological processes in
water resources systems and to enable engineers and planners to use ecological
information in management of water projects. The model should allow realistic
assignment of priorities for pollution control, guide design of water quality
sampling programs, and identify problem areas for research.
Generality
Separate models have been built for a number of lakes, reservoirs, and
estuaries in the United States (Parker and Roop 1974). Much of the informa-
tion required to calibrate this model is site specific and includes: system
geometry, physical and chemical water characteristics, weather conditions,
hydrology, waste loads, historic water qualities, fish stock, and fish harvest.
Ecological information used in the model is general and can be obtained from
the literature.
Level o_f Resolution
The model represents a fine resolution approach which can address specific
questions about biota, and spatial and temporal distribution of chemical
parameters. Output of system parameters can either be a synopsis at a point
in time or trajectories of properties through time. Time steps vary from
3-4 hours to 15 day periods, and the model may be run for up to a year.
Model Structure
Components, inputs, and outputs are described by mass, mass balance
equations, and mass transference equations. The basic processes modelled are
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chemical reactions, inflow, outflow, advection, diffusion, sedimentation, and
exchange. Life forms used in the model are fish, bacteria, phytoplankton,
zooplankton, fish, and benthic animals. Carbon, phosphorus, and various forms
of nitrogen are among the water quality parameters predicted. Other physico-
chemical components used in the model are alkalinity, pH, benthic detritus,
temperature, and toxicity.
Various portions of a lake, reservoir, or estuary are simulated by inter-
connected cells which represent well-mixed portions of space. Cells are
connected by equations which describe transfer of mass. Vertical stratifica-
tion is represented by layers of horizontal cells, and lake circulation due to
thermal conditions and meteorological input is stimulated
Real data are used to drive the model. Nutrient loadings to the system
are dealt with as time varying point sources in the same manner as tributaries.
Watershed characteristics are not used in the model. In aquatic ecosystems
where major inputs are diffuse, such as from ground water or direct surface
runoff, the model as presented in Chen and Orlob (1975) may not work well.
Simulation and Systems Analysis
Validation has been done by comparing calculated values to observed values.
In the case of Lake Washington, the data sets are extensive and the models
predict the effects of nutrient diversion.
Assessment
The Chen and Orlob ecologic model deals with both spatial and temporal
heterogeneity in chemical and biotic components. The model can address
specific and general questions about impacts of nitrogen, phosphorus, carbon,
and sediments. The ecologic model may be unable to simulate structurally
complex systems with marshes, littoral zones, important sediment interactions,
and diffuse inputs from the watershed, ground water, and the atmosphere,
7.3.5 Coniferous Forest Biome Stream Model
The stream model of Mclntyre and Colby (1978) uses a modelling approach
developed for the Coniferous Forest Biome. This model is a product of a
number of years of research within the Coniferous Forest Biome and collabora-
tion with researchers in other parts of the country. A hierarchical approach
has been used to describe different aspects of general lotic ecosystems.
References can be found in Mclntyre et al. (1975), Overton (1975), and
Mclntyre and Colby (1978). A similar stream modelling program has been
documented by Boling et al. (1975).
Objectives and Philosophy
The major purpose of the modelling program has been to develop and
examine a general lotic ecosystem paradigm compatible with current concepts
about lotic structure and behavior. A purpose of the modelling approach is
to "increase understanding of behavior of fundamental biological processes in
lotic ecosystems and to generate meaningful hypotheses related to lotic
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dynamics at relatively coarse resolution" (Mclntyre and Colby 1978). Specific
objectives include determining which levels of resolution are "necessary for
adequate representation of environmental problems and management strategies"
and establishing whether "stream processes are controlled by physical environ-
ment, food resources, predation, or behavioral adaptations of organisms."
Generality
Although this model has been calibrated for streams in the Pacific
Northwest, it is thought to be applicable for any stream of orders 1 - 4
(defined by Cummins 1975). Benthic processes are represented in the model but
water column processes important in large streams and rivers are not. Much of
the information used in the model is obtained from the general literature.
Levels of Resolution
The theoretical aspects of the hierarchical paradigm (FLEX) and the
modelling program have been developed and discussed in Overton (1972, 1975,
1977). Computer implementations of the FLEX paradigm are called FLEX2 and
FLEX3 (White and Overton 1974).
The stream model has been characterized as having relatively coarse
resolution, although several levels of resolution are developed within the
model. Seven basic processes occur at the lowest or mechanistic level:
periphyton dynamics, grazing, shredding, collecting, vertebrate predation,
invertebrate predation, and detrital collection. These processes are
aggregated into intermediate level processes: detritivory, herbivory, pri-
mary consumption, and predation. At the upper level are ecosystem processes,
such as total production, which are aggregates of lower and intermediate level
processes.
Model Structure
Stream processes are described by 14 state variables which represent
biomass involved in the processes. Biomass is related to the processes by
the "unit of capacity," defined as the rate of consumption per gram of biomass,
State variables have been selected on the basis of functional groupings of
organisms important in energy transfer within the streams (Cummins 1975).
These functional groupings are not related closely to taxonomic categories
and are called "quasispecies." These groupings are different from the
"paraspecies" approach of Boling et al. (1975) which includes taxonomic
considerations.
Nutrient interactions are not included in the model (Mclntyre and Colby
1978) but are used as inputs from the environment as part of aquatic-
terrestrial couplings. Detrital processes form an important submodel, which
is consistent with the view of small streams as heterotrophic systems. Five
categories of organic material with varying size, decomposability, and diges-
tibility characteristics are used. There are fewer organic categories than
in the Boling et al. (1975) model which has 32 categories.
Field data for stream discharge, channel depth, width, cross-sectional
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area, slope, current velocity, and suspended load are required for running the
model. These hydrologic variables constrain the basic biotic, chemical, and
physical processes. Temperature, photoperiod, and input of allochthonous
inputs are important controls simulated by the model.
The model is hierarchically modular and allows for flexibility in modify-
ing simulated processes. Conceptualization of the model is in discrete time
with a basic time step of one day. One to six or more years are simulated
during each run.
Systems Analysis and Simulation
A number of standard simulations have used data from the literature, from
Oregon streams, and from laboratory and simulated stream experiments. Model
validation was done by comparing calculated values with observed values.
Various program modifications assessed model behavior. The model was run
after one or more basic processes had been eliminated in order to examine the
effects of process removal. Light inputs were changed to simulate stream
behavior within different geographical regions or with different canopy covers.
A perturbation analysis was done which simulated the effects of canopy removal
from a forested stream. Results from these modified runs helped to generate
new hypotheses about system behavior.
Assessment
The stream model of Mclntire and Colby (1978) realistically simulates
stream behavior and has served to give insight into ecological processes. The
hierarchical approach for modelling aquatic ecosystems is unique and provides
a valuable tool for ecosystem modelling and understanding ecosystem properties;
the approach allows questions to be formulated and addressed at several levels
of resolution. Effects of nutrient loading cannot be adequately simulated
until a nutrient submodel is included. Water column processes need to be
better developed before the model can simulate processes in large rivers and
streams. This model should not be as capable of fine resolution prediction
of detrital processes as the Boling et al. (1975) model which includes more
detrital compartments.
7.3.6 Energy Circuit Language
The principle feature of a modelling approach developed by H. T. Odum is
the energy circuit language which incorporates basic physical and chemical
laws. This approach has been used for a number of models prepared at the
Center for Wetlands at the University of Florida (Littlejohn 1973; Gayle 1975;
Gilliland 1975; Lugo et al. 1976; Odum 1978). The fundamentals of the energy
circuit language can be found in several places (H. T. Odum 1968, 1971, 1972,
1976).
Objectives and Philosophy
The philosophy behind the energy circuit language rests on several tenets:
energy can be used as a common denominator for expressing ecosystem behavior,
ecosystem dynamics can be expressed by simple physical and chemical laws, and
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it is possible to realistically and usefully simulate complex ecological
systems using holistic or macroscopic properties. One major purpose is to
have a comprehensive language which expresses the behavior of complex ecologi-
cal or social systems.
Two sets of models will be examined here. Models for the evaluation of
cypress domes in treatment of sewage have been developed by the Center for
Wetlands (Odum 1978). The major objective of the cypress dome project is to
determine the feasibility of using cypress domes or cypress swamps for manage-
ment of wastewater. More specific objectives include simulation of possible
effects of sewage application, fire, and harvest in cypress domes, and simu-
lation of regional interactions with cypress domes. A second set of models
deals with phosphorus management in Florida and more specifically with
phosphorus management in the Peace River/Charlotte Harbor estuarine system
(Gilliland 1975). The objectives were to evaluate phosphorus flows in Florida
and to test effects of population growth and alternative effects of water and
wastewater management on the estuarine system.
Generality
The modelling theory of H. T. Odum is general and capable of simulating
a wide range of phenomena in ecological, economic, and social systems. Among
systems modelled using the energy circuit language are wars (Odum 1968, 1972),
marine ecosystems (Odum 1972), and tropical rain forests (Odum and Pigeon 1971)
Because of their holistic and general nature, models built for one system can
be applied to similar systems.
Levels of Resolution
When simulating an ecosystem using the energy circuit language, models at
different levels of resolution are constructed. The cypress dome project uses
a fine resolution phosphorus model which describes the role of aquatic vegeta-
tion, particularly duckweed, in phosphorus and nitrogen uptake and conceptu-
alizes the effect of harvest and fire on cypress domes. Another model shows
interrelationships of the cypress domes with the surrounding watershed. A
third model describes competition of plants for nutrients within cypress
domes. The Peace River/Charlotte harbor estuary project includes models at
three levels of resolution. The coarsest resolution model examines phosphorus
dynamics and storages for peninsular Florida. A second model describes the
nutrient dynamics within the Peace River/Charlotte Harbor estuarine system.
At fine resolution are process models describing nitrogen, phosphorus, and
productivity relations in the mouth of Peace River.
Model Structure
Components of the energy circuit language can be translated directly to
a differential equation which describes their behavior. Some components are
modules consisting of several simpler components hooked together. Simple
components behave linearly while modular components are nonlinear.
Interactions among nutrients are modelled with mass action laws which
state that rates of reaction are determined by the product of concentrations.
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involved. Converting nutrients to energy flows and measuring the interrela-
tions between nutrients and energy flows can be difficult.
Many models are point models which describe properties and dynamics for
an average area. Although energy circuit diagrams depict spatial relations
within an ecosystem, as in the Peace River model, it is difficult to mathe-
matically simulate spatial diversity on an analog computer.
Systems Analysis and Simulation
Simulations using energy circuit language are centered on the analog
computer, because of the language's close relationship to electrical network
diagrams. Use is made also of digital computers and CSMP, DYNAMO, and FORTRAN.
Simulation on the analog computer is useful for displaying the behavior
of small ecosystem models. Dynamics can be expressed visually, and there is
immediate feedback between observer manipulation and resulting behavior. A
problem with the analog computer is determining easily the realism of value
combinations because of the need to scale values (Wiegert 1975a).
Usefulness of the energy circuit language is restricted to models of
small size. As Odum points out, the intuitive value gained is greatest for
small models. The diagrams have inherent limitations in size; information
gained by examining a diagram of a system decreases after a threshold of
complexity is exceeded. The usefulness of the analog computer decreases as
models become large because computer capacity is exceeded. The mathematical
formulations become unmanageable because of the combination of nonlinearities;
certain energy circuit models have five to eight state variables multiplied
together (Odum et al. 1974; Gayle 1975).
Assessment
One of the energy circuit language's useful features is its ability to
communicate a macroscopic perspective to ecosystem and social managers. The
models are relatively quick to develop and run, in contrast to other models
which often require many man-years to build and calibrate. Ecologists and
modellers need to evaluate whether or not macroscopic ecosystem behavior
obeys closely laws which describe simple, ideal physico-chemical systems.
Another point which should be evaluated is the usefulness of looking at an
ecosystem completely from an energy point of view. Although ecosystems and
their processes can be described in terms of energy, it may not be the most
appropriate means for addressing many questions. Ecosystems are multivariate
systems, and their behavior can be described by various forms of matter and
energy simultaneously.
7.3.7 Lake Texoma Cove Model
The Lake Texoma Cove model is a mathematical description of ecological
relationships occurring within a cove of a Texas-Oklahoma reservoir. The
model was developed as a teaching exercise for a group of postdoctoral
researchers under the direction of B. C. Patten. A detailed description of
the model and simulations is presented in Patten et al. (1975).
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Objectives and Philosophy
Several objectives were identified by modellers at Lake Texoma: to
characterize the unperturbed biomass dynamics of the cove ecosystem, to under-
stand the cove as an ecological unit, to examine the response to small,
realistic perturbations, and to explore the usefulness of linear systems
analysis. The model was intended to demonstrate the usefulness of linear-
donor controlled modelling for ecosystem analysis. Discussion in the Lake
Texoma paper outlines basic features of the linear-donor controlled modelling
philosophy which also is discussed in Waide et al. 1974; Patten 1975b; Patten
et al. 1975; and Webster et al. 1975. However, at least 35 percent of the
interactions in the model as described in Patten et al. (1975) are nonlinear
and a significant number are recipient or donor-recipient controlled. This
discrepancy compromises the model and makes it difficult to evaluate with
respect to the last objective. Recently, the nonlinearities have been linear-
ized and simulations run at the University of Georgia (C. I. Liff, personal
communication); however, these corrections do not yet appear in the literature.
Generality
The Lake Texoma Cove model simulates the behavior of a cove in a south-
western reservoir, but the holistic linear philosophy makes it possible to
simulate other aquatic ecosystems with a minimum of recalibration and
restructuring. Much of the model is general, representing basic processes
occurring in all aquatic ecosystems. Many interactions and coefficient values
were taken from the general ecological literature and are not specific to
Lake Texoma.
Level of Resolution
The Lake Texoma Cove model is a fine resolution model with 33 storage
compartments representing biotic and chemical components. The model is run
for periods of one to five years, using a time step of half-a-day, and output
is printed at weekly intervals.
Model Structure
The 33 compartments are aggregates of more than 200 compartments initially
identified in workshops. There are not special compartments which reflect
regional considerations. The compartments were divided into primary producer,
zooplankton, decomposer, and vertebrate submodels. Compartments and their
dynamics are described by mass relations. Carbon, hydrogen, oxygen, phosphorus,
and nitrogen are related to compartment mass by stoichiometric ratios. Poten-
tial nitrogen, phosphorus, and carbon limitations are included in the formu-
lation of nutrient dynamics. Nitrogen and phosphorus are considered to be
limiting in the cove, but it is assumed that carbon is never limiting.
Seasonal dynamics of compartments are expressed by making some coefficients
depend on time varying functions (sine waves) which represent temperature and
light. Real data can be substituted for these simple functions. Many inter-
actions are dependent on the initial state of the compartments and are inde-
pendent of them thereafter.
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Nonlinearities occur in the descriptions of vertebrate feeding, nutrient
uptake by plants, zooplankton feeding, and phosphorus relations with organic
matter. As noted earlier, these nonlinearities have recently been removed
from the model, although this correction does not yet appear in the litera-
ture.
Driving functions include wind, atmospheric invasion of gases, precipi-
tation, light, temperature, and turbidity. Physical processes such as
circulation, turbidity changes, light extinction, and water level fluctuations
are also modelled. The effect of water level change on biota was modelled by
a subroutine which simulated habitat changes. The cove is regarded to be a
well-mixed system, and vertical stratification is not included. Because of
the shallow depth, sediment relations are important but are inadequately
modelled as explained in the documentation of the model.
No attempt was made to model the watershed surrounding the Texoma Cove.
Simple time-varying inputs from the land are used. These inputs are based on
precipitation and vegetation cover and represent dissolved and particulate
organic matter, phosphorus, nitrogen, and carbon.
Systems Analysis and Simulation
Because little dynamic information about the cove was available, no
formal validation procedure was used for the simulated behavior. The validity
of model behavior was assessed in terms of reasonableness of expected behavior.
Several perturbation trials were done, and the results were judged to be
reasonable by the authors. Recently the behavior of the linearized model was
compared with the behavior of the nonlinear model described in Patten et al.
1975. Unperturbed behavior of the linear model was similar to the unperturbed
behavior of the nonlinear model.
Assessment
Linear modelling provides a quick way to describe and organize the infor-
mation about ecosystems. Useful insight can be gained by examining the
structure and behavior of linear ecosystem models (Patten 1972b; Waide et al.
1974; Webster et al. 1975). The use of linear models has been defended
because of the well-developed engineering techniques which can be applied to
them; however, the restrictions and assumptions behind linear formulations
must be well understood before results from these techniques can be inter-
preted. Given the success of nonlinear models (Wiegert 1975b; Chen and Orlob
1975; Park et al. 1978), there appears to be no reason to restrict modelling
efforts to linear formulations. Linear models will probably not predict
accurately quantitative results of large perturbations to ecosystems but will
describe qualitative ecological behavior. Many ecologists do not regard
linear-donor controlled formulations as being realistic for describing many
ecological processes (Wiegert 1975a; Bledsoe 1976). Large linear models can
be constructed, calibrated, and solved efficiently.
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7.4 SYSTEMS ANALYSIS TECHNIQUES
A number of systems analysis techniques have been presented in the litera-
ture for examining ecosystem models. Systems analysis techniques can be used
to generate hypotheses about ecosystem structure and behavior and can help
validate or invalidate a model as a statement about ecosystem structure and
behavior. Among systems analysis techniques applied to ecosystem models are
model aggregation or condensation, simulation, perturbation analysis, sensi-
tivity analysis, flow analysis, stability analysis, and network analysis.
7.4.1 Aggregation
Aggregation involves combining components and processes which have certain
taxonomic, structural, or functional characteristics in common; disaggregation
involves breaking components up into constituent subcomponents. In mathe-
matics "decomposition" is used to describe the partitioning of a set into
subsets (Simon 1973). Because "decomposition" already has a well defined
meaning in ecology, use of this word is confusing and inhibits communication
between theoreticians and ecologists. Disaggregation has been used equiva-
lently to decomposition in the sense of partitioning a set into subsets
(Park et al. 1978). Model condensation has been used equivalently to aggre-
gation (Wiegert 1975b; Halfon and Reggiani 1978).
Aggregation is a useful modelling tool and one that can be used to impart
a feeling about ecosystem structure and behavior (Odum 1972; Zeigler 1974,
1976; Wiegert 1975b; Overton 1977; Halfon and Reggiani 1978; Mclntyre and
Colby 1978). In the modelling approaches of Patten (1975a) and Odum (1972,
1976), the initial model may be a conceptual model comprising a large number
of components and interactions known to be important in the ecosystem of
interest. This large set of components and interactions then is aggregated
into smaller sets which are mathematically and conceptually manageable. The
exercise of deciding which components, interactions, and processes are aggre-
gated is important in imparting the macroscopic perspective discussed by
Odum (1976).
There may be no best way to aggregate a large set of components which
make up the conceptual description of an aquatic ecosystem. Although taxo-
nomic considerations have been used to define components, they are not always
useful. Different development stages of a species may have different functions
or spatial distributions (Cummins 1973), making it difficult to aggregate
some components along taxonomic lines. Components may be aggregated according
to both functional and taxonomic characteristics (Boling et al. 1975; Mclntyre
and Colgy 1978). A good strategy for defining components is to aggregate or
disaggregate them in a manner consistent with operational techniques; it is
often easier to measure composite properties of a large group of organisms
rather than properties of individual organisms or populations. Another use-
ful way to aggregate components is according to their spatial distribution in
aquatic ecosystems. Operational techniques often are compatible with spatial
distribution of ecosystem properties.
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7.4.2 Simulation and Perturbation Analyses
The most basic systems analysis technique is simulation which involves
solving the equations which describe behavior of the system being modelled.
Solution of the simple water quality models results in the state of an eco-
system at a particular point in time, usually at the end of a year. Solution
of comprehensive ecological models results in trajectories of ecosystem
properties through time.
A simple modification of simulation is to change the values of coefficients
and variables of the model and to examine resultant behavior. The analog com-
puter is ideal for examining the behavior of a simple differential equation
model (Patten 1972a). Although solutions to equations can be displayed
visually immediately, the analog computer is restricted to fairly small models.
Digital simulation is useful for large models and can be used with both differ-
ential, difference, and stochastic equations.
Perturbation analysis is. a simple sensitivity technique in which coeffi-
cient or state variable values are changed. Perturbations are relevant to
impact analyses because they can represent nutrient or sediment inputs.
Although some perturbations have no real meaning, they may be used to analyze
model behavior. Engineering techniques make use of standard perturbations
which can be analyzed formally; the use of the pulse function and the unit
step input function are described in Zadeh and Desoer (1963) and Waide and
Webster (1976).
7.4.3 Sensitivity Analyses
Because components of a model are constrained by one another in both
direct and indirect fashion, it often is difficult to ascribe a model's
behavior to a particular coefficient. Sensitivity analyses examine model
behavior in terms of changes in coefficient values. The simplest is a per-
turbation analysis which involves separate modification of each coefficient
and subsequent solving of the modified model. A more sophisticated technique
has been used by the Eastern Deciduous Forest Biome modelling program; pertur-
bations of various magnitudes are generated randomly in each of a number of
runs and the resulting runs are evaluated. This type of sensitivity analysis
is time consuming and expensive but works on a broad range of models. More
sophisticated techniques examine all coefficient and state variables simul-
taneously (Tomovic 1963; Tomovic and Vukobratovic 1972). Sensitivity
coefficients for a variable describe the relative and absolute effects of
small changes in coefficient values. This technique can identify the most
sensitive parts of a model; i.e., the variables which most influence model
behavior. The analysis demonstrates the effect of measurement error on model
variables and assesses parts of a model which require most attention. Extrapo-
lations from sensitivity analyses to real ecosystems should be done with
reservation and need to be tested. Discussions of sensitivity analyses and
their relationship to ecology are found in Patten /(1969), Gallopin (1971)
Kowal (1971), Brylinsky (1972), Parker (1975a), Waide and Webster (1976),
Astor et al. (1976), and Park et al. (1978).
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7.4.4 Network Analysis
Some of the simplest and most straightforward of the systems analysis
techniques are network analyses. These analyses are based on the idea that
components in an ecosystem dependency network are related both directly and
indirectly (Levins 1975; Patten et al. 1976; and Land and Levins 1977). The
dependency structure of a system can be described by graphical and matrix
techniques. Graphic techniques are pictorial and make use of compartments
which represent storages and arrows between compartments which represent
interactions.
A simple compartment model is shown in graphical form in Fig. 7.1. A
graph can be simply transformed to matrix notation. A matrix representation
of the graph in Fig. 7.1 is shown in Fig. 7.2. Each row and column represents
a compartment in the graph. Entries in the matrix represent interactions
(arrows) between compartments. Entry (i,j) represents the interaction from
compartment j_to compartment j_ in the graph. Matrix A is called the adjacency
matrix of the rnode^ and shows the position of all direct paths in the graph.
When matrix A_ is multiplied by itself, the resulting product shows the position
of all two length paths in the graph; A3 represents all the three length paths
and so on. Symbols can be used in place of numbers in the matrix and can trace
impacts through an ecosystem network. An asterisk has been used in matrix A_
to indicate the direct impact of organic pollution on bacteria. In A^ the
position of asterisks shows components (Protozoa, Diapatomus) influenced by
two length paths which have relayed the direct impact on bacteria. In A3, A4,
and A_5 one can see by the position of the asterisks which components (Cyclops,
Asplanchna, fish, organic material, and outflow) are affected indirectly by
direct impact on bacteria. Dissipation of impact occurs further from direct
impact; the impact becomes diluted by the dependency network (Hill 1979).
These techniques can be used to show the positions of direct and indirect
impact in ecosystems and to trace through an .ecosystem network to see what
components will be affected by an impact.
This network analysis is related to several techniques. Network analyses
have been done by Levins (1975) and Lane and Levins (1977) and indicate
whether or not interactions have a positive or negative influence on ecosystem
processes. Network analyses have been used to quantify structural character-
istics of network (Hill and Durham 1978; Hill 1979). Relationships between
flow analyses (Hannon 1973; Finn 1976a, 1977) and network analyses are discussed
in Patten et al. 1976; Barber et al. 1978. Markov chain analyses of Barber
(1978a, 1978b) also are related to network and flow analyses.
7.4.5 Stability Analyses
Stability has received a great deal of attention in ecosystem ecology and
modelling. Stability is related to the persistence of ecosystems and eco-
system models through time (Margalef 1968; Lewontin 1969; May 1971, 1974,
1976). Implicit in ecosystem stability is the existence of a normal range of
variability within which characteristic properties of an unperturbed ecosystem
remain for an extended period of time. Perturbations to ecosystems tend to
drive the observed values of these properties outside their normal range.
Stability implies the tendency of the perturbed properties to remain within
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Phytoplankton
(Compartment 1)
Allochthonous Organic
Matter
(Compartment 8)
Dead Fish of Streams
(Compartment 9)
Protozoa
(Compartment 2)
Planktonic
Bacteria
(Compartment 6)
Diapatomus
(Compartment 5)
Cyclops
(Compartment 3)
Asplanchna
(Compartment 4)
I
Fish
(Compartment 7)
Non-Predatory Organic Matter
(Compartment 10)
Sedimentation and
Outf1ow
(Compartment 11)
Fig. 7.1. Energy model of pelagic region of cove. (From Sorokin and Paveljeva 1972.)
-------
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1
1 1
Fig. 7.2. Products of adjacency matrices with asterisks to show position of
direct and indirect impact.
161
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their normal range or to return to it if moved outside. Resistance is the
component of stability related to the magnitude of the perturbation required
to drive properties outside their unperturbed range. Resilience is the com-
ponent of stability related to the time required for perturbed properties to
return to the unperturbed range.
Stability in mathematical models is analogous to stability in ecosystems.
In a stable model properties return to their normal trajectories after pertur-
bation. Model resistance and resilience have analogous definitions to ecosystem
resistance and resilience (Long 1974; Waide and Webster 1976; Webster et al.
1975). Techniques for assessing the stability of models include qualitative
assessment of model behavior, quantitative deviation from normal behavior,
existence of negative eigenvalues, and frequency response analyses. Deviation
from normal trajectories can be determined and assessed visually and mathe-
matically. Techniques such as existence of negative eigenvalues and frequency
response analyses have been restricted to small, linearized ecosystem models
(Bledsoe 1976). Further discussion of stability analyses are found in
MacArthur (1955); Tomavic (1963); Patten and Witkamp (1967); Odum (1969);
Watt (1969); Thorn (1972); Parker (1973, 1975a, 1975b); and Zalucki (1978),
Stability analysis of models has implications for impact assessment in
aquatic ecosystems. Formal stability analysis has been applied to a model of
Lake Kootenay, British Columbia, in order to assess ecosystem stability at
various points in time (Parker 1975a, 1975b). The model, documented in
Parker (1973, 1974), describes the dynamics of algae, crustacean zooplankton,
phosphate, nitrate, and ammonium in an ecosystem receiving effluent from a
fertilizer plant. Using negative eigenvalue techniques (Parker 1975a) and
sensitivity analyses (Parker 1975b), the model was shown to be "extremely"
stable.
7.4.6 Frequency Response Analyses
Many natural inputs to ecosystems are periodic. Some, such as light and
temperature, are approximately sinusoidal and can be characterized by fre-
quency and amplitude of their oscillations. Periodic inputs are transmitted
through the dependency network of an ecosystem model, and because of cons-
traints arising from the coupling between components, the model will modify
the amplitude and frequency of inputs. The degree to which periodic inputs
are modified and reflected in model output can be examined by linear engineer-
ing analysis. Amplitude and frequency that have been altered by a model
reflect the structure and time constants of the model (DiStefano et al. 1967;
Child and Shugart 1972; Waide and Webster 1976).
The damping factor and natural frequency are two parameters derived from
frequency response analysis. According to Child and Shugart (1972), Waide
et al. (1974), Waide and Webster (1976), and Harwell et al. (1977), the
damping factor and natural frequency are related to the resilience and resis-
tance of mathematical models. It would be useful for impact analysis to be
able to quantify the resistance and resilience of an ecosystem to perturbation
of phosphorus, nitrogen, carbon, and sediments.
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7.4.7 Flow Analyses
In material and energy models compartments represent storage, and the
interactions represent movement of materials or energy between compartments.
In order to assess the magnitude of indirect flows of a model, flow analysis
techniques have been developed. Flow analysis can examine how much an outflow
is influenced by each of the compartments and inputs in the model. Flow
analyses used in ecology are derived from input/output analyses for economic
systems derived by Leontief 1966 (Hannon 1973; Finn 1976a; Patten et al. 1976).
Input/output analyses indicate which inputs or compartments can be adjusted
to give a particular output or set of outputs. Theoretically, flow analyses
tell researchers how to modify inputs to real systems in order to adjust
storages and outputs in real systems. This ability would be useful for
pollution management of aquatic ecosystems. With flow analyses and a good
model, the effect of a change of phosphorus input on phosphorus storage and
phosphorus output can be determined.
Indices which weflect the degree of material cycling can be determined
for ecosystem models (Finn 1976a, 1976b, 1977). These indices have been used
recently to compare structural differences among four lake models (Richey
et al. 1978). Flow analyses can be interpreted easily only for relatively
simple systems which are at or near steady state. A related analysis is the
Markov chain analysis used to trace the paths of material or energy through
a model network (Barber 1978a, 1978b; Barber et al. 1978). This analysis is
compatible with statistical techniques,and confidence intervals can be placed
on a number of derived quantities.
7.4.8 Validation
Validation is the process by which model behavior is related to the real
world. According to Webster's Collegiate Dictionary (1976), "to validate"
means "to make valid; substantiate; confirm." Hypothesis testing in terms of
the scientific method may be regarded as a specific category of validation.
The process of validating ecosystem models has been discussed in a number of
papers (Innis 1975; Wiegert 1975a; Caswell 1976; Levins 1966; Mankin et al.
1977).
The validity of a model can be assessed in several ways depending on the
objectives of the model, accuracy and precision of model output, reasonable-
ness of model output in terms of observations and experimentation, and
reasonableness of interaction patterns and mathematical formulations in terms
of ecological theory. These three ways of validation are not related
necessarily to one another, as pointed out by Levins (1966). For example,
an unreasonable model may give accurate predictions and a reasonable model
may give inaccurate predictions (Caswell 1976). The iterative operation of
the scientific method should draw the above features of validation together
(Becht 1974), i.e., realistic models should become increasingly more reasonable,
precise, and accurate.
Caswell (1976) has argued that validation of ecosystem models be done by
disproving hypotheses derived from models rather than testing the model itself.
Levins (1966) asserts that ecosystem models cannot be hypotheses because
163
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experiments with ecosystems cannot be done. However, both terrestrial and
aquatic ecosystem experiments have been done (Likens and Bormann 1972; Swank
and Douglas 1975). Examining a large population of lakes and rivers subject
to a variety of natural and man-made inputs can be equivalent in some respects
to laboratory experimentation. Model structure is addressable as scientific
hypotheses in terms of such experimental results. Identification of the
relationships occurring in real ecosystems is a problem at the basis of eco-
system modelling and one that is addressable by formal statistical techniques
(Halfon 1975a, 1975b).
Because an infinite number of models will fit any particular data set
equally well (Bunge 1959; Popper 1959), most ecological modellers have used
qualitative "goodness-of-fit" criteria for validating models. Models are
judged as to whether they behave reasonably well or similar to behavior
expected in ecological systems. A model often is calibrated and compared to
a data set that was not used to construct the model. Another technique is to
use the data from one year to construct the model and another year's data to
validate it.
Caswell (1976) suggested that model validation proceed through testing
submodels via rigorous experimentation. Attention also must be paid to the
manner in which the submodels are connected together; i.e., to the upper level
hypotheses which constrain the interconnected submodels. Formulating and
testing whole system constraints and behavior is as important as testing
submodel and component behaviors.
7.5 SUMMARY
Mathematical models which describe observed variation in aquatic eco-
systems have become increasingly sophisticated in the last few years. Each
model describes a response surface and is capable of predicting response due
to changes in system inputs and controls. Because many components, processes,
and mechanisms are basic to all lakes and rivers, ecosystem models are rela-
tively general but require specific information on inputs and chemical and
physical parameters which control individual ecosystem behavior. Coarse
resolution models generally do not deal with dynamic properties and predict
only gross effects of nutrient loading. Although they have been used for
both lakes and rivers, coarse resolution models do not work well in spatially
diverse systems. Fine resolution models describe the dynamic variation of
several observed properties. Most fine resolution ecological models have been
built for lakes rather than for streams, marshes, or swamps. The MS. CLEANER
model of the Eastern Deciduous Forest Biome program represents the state-of-
the-art in fine resolution lake modelling and can answer questions about
nutrient enrichment, thermal pollution, siltation, impoundment, and fish
removal (Park et al. 1978). MS. CLEANER is complex and expensive to run in
its entirety; however, because MS. CLEANER is modular, only parts of the model
are required to answer questions about aquatic ecosystems. Approaches such as
Odum's (1972, 1976) and Patten's (1975a) may be better able to deal with
behavior of complex ecosystems. Most fine resolution lake models are capable
of dealing with systems which are partitioned into a few well-mixed sections;
however, they will not describe slow-moving systems such as marshes, swamps,
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and littoral regions. Recent models of swamp and marsh systems (Odum 1978;
Kadlec 1978) have begun to deal with these poorly mixed aquatic ecosystems.
Fine resolution stream models (Boling et al. 1975; Mclntyre and Colby 1978)
predict behavior of stream components and processes when driven by allochtho-
nous carbon sources. These stream models do not yet include nutrients.
A major problem still facing aquatic ecosystem modelling is the inability
to adequately characterize inputs. Inputs from atmosphere, watershed, tribu-
taries, and ground water drive aquatic ecosystems through time, the dynamic
behavior of ecosystem conponents is entrained largely by the temporal variation
of inputs (Patten 1978). Many inputs are difficult to measure because they
initiate from nonpoint sources and vary with time. Watershed, land use, and
meteorological characteristics establish the input regime of aquatic ecosystems.
Systems analysis techniques can play important roles in impact assessment.
Perturbation analysis of models, for example, can be used to describe behavior
of ecosystems to which pollutants have been introduced. Sensitivity analyses
can identify parts df an ecosystem most sensitive to impact, indicate what
information should be sought, and assess the effect of measurement error.
Stability analyses can evaluate how much, and how quickly a system should
respond to impact and then return to normal behavior. Flow analyses can
suggest how nutrient and sediment inputs to ecosystems can be adjusted to give
desired behavior and how much internal cycling contributes to system behavior.
Certain systems analysis techniques are restricted to a small set of simple
models. Simulation and perturbation trials can be used on most models and
probably can provide as much information as sophisticated sensitivity tech-
niques. However, it is possible to make models too complicated and unstable
to simulate. A number of sophisticated systems analysis techniques are
derived from engineering theory and are best suited for simple linear or
linearized models. The claim that they provide interesting and useful results
applicable to ecosystems should not be taken for granted, but the assumptions
behind them should be examined.
Mathematical models are statements about ecosystem behavior and demon-
strate properties analogous to ecosystem behavior. Models and systems analysis
techniques must be incorporated into the normal operation of the scientific
method; they must be validated, corroborated, and used to generate other state-
ments about ecosystems. Ultimately the best criteria for evaluating models
are success and acceptance by users. If a model predicts behavior well for a
number of systems under various conditions, then it will be considered a good
model. As ecosystem modelling evolves, "natural selection" of models will
occur, and many problems found in earlier models will be resolved.
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CHAPTER 8
SUMMARY OF ORGANIZING CONCEPTS
In the preceding chapters we have explored an organizational scheme to
evaluate the impact of nutrients and sediment on the biota of the nation's
waterways. To carry out this objective we utilized the ecosystem concept
which states that systems of biotic and abiotic units interact to form coher-
ent systems that have predictable properties. We next adopted the concept
that the great variety of ecosystems that are recognized at different scales
of complexity, over spatial scales, and at different times can be organized
into a hierarchy. The hierarchy we developed combines large geographic units
with more restricted biological units.
We find that the hierarchy is useful for organizing the work of the
study, since aquatic systems are immensely varied; to generalize to all lakes
or rivers within geographic regions results in loss of much of the biotic
character of the system. At the. upper levels of the hierarchy the physioco-
chemical factors, especially those related to the land, direct system
behavior; at lower levels biotic roles become more important.
Thus, we have identified a resolution problem related to water management.
Management of water quality, from a physico-chemical point of view, can be
carried out at coarse levels of resolution, if one is willing to accept
changes in biota. Management of biota, on the other hand, is carried out at
a fine level of resolution, and regulations must be geographically specific.
Quite clearly, regulations and programs directed to the same resource
(aquatic systems) can conflict by focusing on different levels of resolution.
Since the project objective specified biota as the target of interest,
we have explored in detail (in Chapter 6) those levels of the hierarchy where
the biotic component is dominant or very significant. These include communi-
ties, species populations, and individuals. We conclude that there are a
great variety of structural and functional attributes of biota which could be
used to predict responses of biota to nutrient and sediment impact. We are
not able to judge what are the best criteria, however. The best criteria
should reveal a great deal of information about the biotic unit, be general
in reference to many types of similar biotic units, be conservative, and be
responsive to the specific impact of concern. Various authors have argued
that many different criteria fit this standard.
We feel that the solution to this problem is the adoption of a dynamic
approach to system analysis and management. If we assume that aquatic systems
are not static, but rather are dynamically changing, then our concern is with
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the direction and rate of change. Our focus shifts from the structure to
the function of systems, recognizing that structure will shift to maintain
functional attributes within limits of stability. This point of view is not
congenial to those who wish to hold system structure (especially the species
structure) fixed in time. If that is the goal, then the management alterna-
tives are quite different. We believe that these two points of view are
contradictory, and if both points of view are pursued then conflict must
occur.
Nevertheless, the trend reflected in the literature stresses biota and
requires a structural view in part. Therefore, we seek vulnerable systems,
components, and populations. Vulnerability is expressed by a biotic response
to changes in nutrient or sediment levels, which often can be described by
response curves. These curves can provide information required to model
responses of biota under the complex interactions in ecosystems. Of course,
it is usually difficult to carry out experiments on biotic response in the
field. Not only are there mechanical problems, but the uncontrollable inter-
acting variables necessitate large sample sizes and complex statistical
procedures. Thus, response studies are usually carried out in the laboratory,
and it is difficult to determine if the data under controlled conditions can
be extrapolated to the field.
Because of the twin problems of scale resolution and a static-dynamic
analysis, we have constructed models of the freshwater systems at two levels
of resolution—a fine level and a coarse level. Coarse level modelling
approaches provide a relatively quick and inexpensive prediction of system
behavior, while fine level approaches incorporate biotic interactions and
temporal variations. Also, the problem of impact prediction depends upon
the accuracy or the confidence required in the prediction. Validation seems
not to be developed sufficiently to specify the predictive confidence
resulting from specified types of models. However, confidence increases as
the resolution increases. But the degree of resolution is clearly limited
both by the computing machinery and our ability to collect, reduce, and
analyze the data required for a fine resolution. Fine level models have been
developed for specific system types, but it is not apparent now how well any
of the coarse level models can be applied to many different systems. This
comparison would provide us with a way to judge which model to use in
assessment of impact. However, as far as we know, a comparative study of
this type has not been done.
Summarizing, the introductory sections of this report have utilized
concepts that allow integration of the physical, chemical, and biological
attributes of freshwater systems and that allow organization of the different
types of waters at all levels of the hierarchy. We have found a variety of
characteristics of biota and systems that could be used to describe biotic
response to nutrient and sediment impacts depending on the hierarchical
level considered. And, we have explored some modelling approaches for
studying system dynamics and response. We also have uncovered several
conceptual and methodological problems that mitigate against achieving the
goal of integrated water management across the nation.
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In the next section of the report we examine data on sediment and
nutrient impacts on biota and judge if these data are sufficient or adequate
for prediction. Chapters 9 and 10 analyze information at the lower levels
of the hierarchy since most research has been conducted using specific
organisms, communities, or water bodies. In the final chapter, Chapter 11,
we show how the hierarchical scheme may be utilized to evaluate the sediment
and nutrient impacts identified and we provide an analysis of our results in
this hierarchical context.
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CHAPTER 9
IMPACTS OF SEDIMENT ON BIOTA IN SURFACE WATERS
9.1 INTRODUCTION
The impact of sediment movement and deposition on aquatic biota in surface
waters of the United States is reviewed and evaluated in this chapter. The
review is primarily concerned with the effect of sediment on biota; the role
of sediment as a carrier of nutrients will be treated in Chapter 10. Heavy
metals and pesticides are also associated with sediments and may be detrimental
to organisms in certain aquatic systems. The effects of these compounds are
reviewed by the Environmental Protection Agency (EPA)(1976) and Kemp et al.
(1973) and are not considered in this study.
9.1.1 Sediment Characteristics
The term "sediment" refers to any particulate material, transported from
its site of origin by air, water, or ice, which is in suspension or has come
to rest on the earth's surface (Trowbridge 1962). In terms of biological
effects, sand, silt, and clay particles are of interest because they are
readily suspended and transported by water.
Most sediment may be assigned to one of two broad categories:
1. Organic material in varying states of decomposition, ranging
in size from colloidal particles to large detrital particles,
and
2. Inorganic material ranging in size from colloidal particles
through silts and sands to large boulders.
In practice it is difficult to completely separate organic and inorganic
fractions of natural sediments, due to the reactivity of organic and inorganic
colloids which results in the adsorption of organic colloidal compounds on
solid surfaces (Grim 1968; Jenne 1968; Malcolm and Kennedy 1970; Greenland
1971; Schnitzer and Kahn 1972).
Sediment also may be classified by particle size. The size of sediment
particles affects sediment transport and reactive surface area and influences
the distribution of biota (Cummins 1975). A suggested terminology for
particle size analysis of sediment was developed by the Subcommittee of Sedi-
ment Terminology of the American Geophysical Union and is widely used in the
United States (see Gottschalk 1964). This classification scheme is based on
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particle size only, with no reference to the composition of the material in
question.
Sediment is transported in the following two forms:
1. Suspended load - particles maintained in the water column
by turbulence and carried with the flow of water; and
2. Bed load particles resting on the streambed and pushed
or rolled along by the flow of water.
Suspended load and bed load are functional descriptions used to distinguish
two different modes of transport which follow different physical laws. Sus-
pended load, composed primarily of silts and clays, is usually limited by the
rate of supply from the watershed. Bed load is composed of larger particles,
such as sand and gravel, which are not as easily maintained in the water
column by turbulence. Movement of bed material is limited by the transporting
ability of the channel, that is, by the shear stress applied to the bed by
moving water. A given particle may move in either mode, depending upon the
conditions. Sand, for instance, may move as suspended material at high water
velocities associated with a steep gradient or high discharge. During periods
of low flow or slower water velocities associated with gentle gradients, sand
may move primarily as bed load (Chow 1964; Leopold et al. 1964; Gregory and
Walling 1973). Passega (1957, 1964) distinguishes several forms of sediment
movement representing a continuum between bed load and suspended load, includ-
ing rolling, bottom suspension, graded suspension, uniform suspension, and
pelagic suspension. Methods for distinguishing these sediment fractions are
available (Passega 1964; Friedman 1967; Royse 1968), but the ecological signif-
icance of the various fractions is unknown.
9.1.2 Measurement of Sediment Transport
Measurements of transported bed load and suspended load often show large
variations in time and space. These variations result from differences in
channel geometry, sediment supply, and discharge. As a result, estimates of
the total sediment yield are statistically accurate only if sampling is
sufficient to detect periods of fluctuation (Einstein 1964; Piest 1965).
Assessment of sediment yields rely either upon estimates of the total sediment
load deposited within a reservoir or upon measurement of suspended sediment
concentrations and estimates of bed load over a range of flow conditions.
Bed load often is assumed to be 5 to 10 percent of the suspended load by
weight (Mark and Keller 1963; Gregory and Walling 1973). For a detailed
treatment of sediment sampling see Chow (1964), Einstein (1964), Guy (1969,
1970), Guy and Norman (1970), Porterfield (1972), Riggs (1973), and Gregory
and Walling (1973).
The amount of sediment transported by a channel also may be estimated
from theoretical consideration of the properties of the sediment and the
potential of the channel to transport the imposed sediment load. These
methods of sediment load estimation are based on equilibrium conditions which
do not exist in an aggrading or degrading channel (Einstein 1964). Since the
ability of a channel to transport material as suspended load often exceeds
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the rate of supply, theoretical simulations also must consider conditions
within the watershed which affect the supply of sediment (Gregory and Walling
1973).
Biologically oriented studies often estimate suspended sediment concentra-
tions by measuring the turbidity produced by sediment. Turbidity is an optical
property of water causing light to be scattered and adsorbed rather than trans-
mitted in a straight line. The amount of light scattered is a function of
size, shape, and refractive index of the particles present, but has little
direct relationship to concentration and specific gravity of the suspended
material (American Public Health Association 1975). Turbidity is measured
using a turbidimeter or a nephelometer both of which measure the intensity of
light scattered at some angle to the incident light. An alternative method
measures the length of the light path through a suspension which causes the
image of a standard candle flame to disappear (Jackson candle turbidimeter).
There is no direct relationship between Jackson candle turbidity and the
intensity of light scattered at 90° (American Public Health Association 1975).
A number of turbidity standards and units are used, including:
1. Formazin - reported as Fprmazin Turbidity Units or FTU.
2. Si0 - reported as ppm
3. Manufactured standards may be reported as Nephelometer
Jurbidity Units; Jackson Turbidity Units (JTU); or any
of the preceding units.
The definitions of turbidity, units of measurement, and a comparison of the
results and principles of measurement of a variety of turbidity meters have
been reviewed by Duchrow and Everhart (1971) and McCluney (1975).
Suspended solids are determined by a gravimetric procedure. Generally,
tared filters are used to filter a known volume of water. The filters are
then dried to a constant weight and the amount of solids present reported in
milligrams per liter (American Public Health Association).
9.1.3 Modifiers of Sediment Impact
Evaluating the effect of sediment on aquatic biota is confounded by
variations in the physical and chemical environment, species response, and
community composition among different bodies of water. Physical and chemical
factors other than sediment regulate the presence and distribution of aquatic
organisms. Important factors are temperature, current velocity, substrate
light, pH, dissolved oxygen, carbon dioxide, nutrients, metals, and pesticides
Many of these parameters are interrelated and may be confounded by sediment
inputs, light penetration and nutrient levels, for example, are strongly
altered by sediment inputs, but nutrient levels are also a function of basin
geometry and flushing rate (e.g., Tilzer et al. 1976).
Biological relationships, including competition and herbivory, are other
factors which control the distribution and productivity of photosynthetic
organisms. In higher organisms food requirements, species interactions, and
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biogeography also influence the occurrence of organisms. Thus, in evaluating
the effect of sediment on aquatic biota, one must discriminate between effects
due to sediment and those due to differences in the physical, chemical, and
biological environment.
Water Velocity
One of the major difficulties in interpreting the impacts of sediment
movement in streams is the intimate relationship between water velocity and
sediment transport. Changes in water velocity alone are known to augment
photosynthesis, supposedly by increasing the availability of nutrients and
removing metabolic wastes (cf. Blum 1956; Whitford 1960; Mclntire 1966a, 1966b,
1968; Hynes 1970a). Laboratory streams have been used to study the influence
of a variety of factors on stream algae (Mclntire et al. 1964; Mclntire and
Phinney 1965; Mclntire 1966a, 1966b). The laboratory streams consisted of
wooden troughs with bottom material from a nearby stream. Water was taken
from a nearby stream and passed through the laboratory streams at a constant
rate of flow. Light intensity, light-dark cycle, water depth, current velocity,
flushing rate, and oxygen concentration could be regulated. This design
provides an ideal situation for examining the effect of siltation under
controlled conditions, as demonstrated by Mclntire and Phinney (1965). They
examined the effect of light intensity and carbon dioxide levels on periphyton
production, respiration, and export. Extremely turbid conditions occurred in
the laboratory streams with no change in water velocity during periods of high
runoff in the stream used as a water source. Introduced silt apparently
scoured the substrate, resulting in increased export of periphyton. The stream
with higher light intensity (550 ft. candles) developed large growths of fila-
mentous green algae (Oedogonium and Ulothrix) and showed the highest rate of
export, 2.65 g/day, upon the first influx of silt. The stream receiving low
light input, 225 ft. candles, developed a lower biomass of green algae and
lost less material during the first silty period, 0.782 g/day. The ratio of
production to respiration (P/R),which normally ranged between 1.3 and 2.5,
dropped below one in both streams. This decrease in P/R ratio resulted from
decreased rate of photosynthesis by the remaining algae and from greatly in-
creased community respiration. Unfortunately, determinations of the amount
of suspended material present were not made.
Flow Regime
Most rivers in the United States are regulated by impoundment and channel-
ization. These changes alter the flow regime, sediment load, water tempera-
ture, oxygen content, and water chemistry, which often adds lentic plankton
to downstream systems and alters the composition of aquatic biota in the
impounded stretch. The results of impoundment often depend upon the mode of
operation, particularly the flow pattern, depth from which water is released,
and limnological conditions within the reservoir. Effects on downstream
benthos have been reviewed recently by Ward (1967a). The diversity of benthos
is invariably reduced below dams, and the composition, often is altered greatly.
Relatively constant seasonal flow patterns often result in increased benthic
standing crops, while seasonal fluctuation in flows results in reduced benthic
biomass. Daily fluctuations in flow seem to be less important than the
seasonal regimes. Reduced benthic standing crops associated with variable
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flow may result from periodic exposure of the streambed or heavy silt deposition
due to low flows or both.
Changes in the flow regime often result in changes in bottom fauna compo-
sition. Trotsky and Gregory (1974), for instance, found that changes in flow
due to impoundment of the upper Kennebec River, Maine, modified the distribu-
tion of bottom fauna. Aquatic insects adapted for swift water were more
abundant in the river above the reservoir than below it and were absent from
those stations below the impoundment which had the lowest current velocity.
Sampling stations above the impoundment averaged 19 genera of aquatic insects,
while those below the dam averaged 11 genera.
The often noted increase in benthic standing crops below impoundments with
seasonally constant flow may be related to greater food resources supplied by
planktonic organism (Spence and Hynes 1971; Ward 1976a; Armitage 1978).
Similar increases in standing crops, over the normal levels found in streams,
are observed below outfalls from natural lakes (Hynes 1970b). A number of
changes associated with impoundment and channelization of the Missouri River
have been documented. Impoundment has increased the number of drifting
crustaceans, with the invertebrate drift now composed of 50 to 80 percent
Leptodora kindta (a limnetic cladoceran) by weight. Impounding also has
reduced maximum flow and turbidity (from 4500 ppm to 50 - 70 ppm) and has
resulted in higher dissolved oxygen concentrations. The increase in dissolved
oxygen may be due to decreased organic loading because of the trapping of
organic sediment in mainstream reservoirs and, hence, a lowered oxygen demand.
Channelization, in conjunction with impoundment, has reduced both the size and
variety of aquatic habitats by destroying key productive areas such as flood-
plain swamps, flood channels, and oxbows. The standing crop of benthos in
channelized and unchannelized reaches is similar, but channelization has
reduced the total benthic area by 67 percent. The construction of locks and
dams and subsequent impoundment of the Arkansas River has increased the pro-
duction and density of zooplankton (Short and Schmitz 1976). A decrease in
zooplankton was noted downstream from impoundments as a result of the decrease
in backwater areas and an increase in current velocity and silt load in the
lower channelized reaches of the river.
Temperature
Impoundment alters the temperature regime of downstream areas as well.
Storage reservoirs which release water from below the surface often result in
lower summer temperatures, higher winter temperatures, more constant temper-
atures diurnally and seasonally, and delayed seasonal maximums downstream
(Spence and Hynes 1971; Ward 1976a). Spence and Hynes report that impoundment
of the Grand River (Shand Dam, Wellington County, Ontario) results in a four-
week lag in summer rise in water temperature and a maximum temperature more
than 6° C lower than upstream. Such temperature alterations may have impor-
tant effects on stream biota. Hatching, growth, and emergence, for instance,
depend on thermal cues. As a result, changes in thermal signals below impound-
ments may prevent or alter the completion of the life cycle (Hynes 1970b;
Nebeher 1971; Lehmkuhl 1972; Ward 1976a, 1976b). Seasonal changes of as little
as 2 to 3° C may effectively eliminate species by affecting body size and
fecundity, and thus influence the geographic distribution of aquatic insects
Sweeney and Vannote 1978).
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Several other factors affect water temperature, hydrology, and sediment
transport. Removal of riparian vegetation often increases temperatures and
sediment loading. Mean monthly maximum temperatures increased up to 7° C
following clear cutting in the forested coast range of Oregon (Brown and
Krygier 1967). Similar results have been reported by Gray and Edington (1969)
and Krygier et al. (1971). Leopold (1968) reported that streams on Long Island,
most affected by man, exhibited temperatures 5° to 8° C above the control in
the summer and 3° to 5° below in the winter. Land-use practices also control
the amount of runoff and erosion. As a result, changes in fauna due to altered
hydrologic and sediment regimes may be confounded by subtle changes in temper-
ature.
9.1.4 Sampling Problems
The effect of sediment movement on macroinvertebrates, as with primary
producers, is complicated by concurrent changes in many other environmental
variables. Macroinvertebrates are mobile, resulting in difficulties in sampling
and in interpreting changes in composition and standing crop. Explanations
of variation in populations are further complicated by seasonal differences in
reproduction, growth, and emergence (Hynes 1970b).
Quantitative estimation of standing crop is difficult, particularly since
different sampling methods give different results (Gaufin et al. 1956; Cummins
1962; Hynes 1970a, 1970b; Chutter 1972; Dickson and Cairns 1972; Brinkhurst
1974; Hynes et al. 1974; Hughes 1975; Kinney et al. 1977). Macroinvertebrates
have been found as deep as 54 cm below the surface in gravel beds (Coleman and
Hynes 1970; Hynes 1974). Thus, conventional quantitative samples may under-
estimate standing stock and production, depending upon the type of substrate
sampled. Furthermore, the number of samples required must be considered.
For instance, it has been estimated that five surber samples, each one square
foot, would give an estimate of the population of insects with a variability
of ± 49 percent (Chutter 1972). Ten surber samples would reduce the variability
of the sample mean to ± 27 percent for a confidence interval of 95 percent.
The number of samples will, of course, vary with the distribution and abundance
of the organisms sampled.
Other problems result from temporal and spatial changes in environmental
conditions. Several authors point out that most available data are difficult
to interpret because of arbitrarily fixed temporal and spatial sampling and a
failure to account for temporal and spatial differences in hydrologic phenomena
(Brinkhurst 1974; Livingston 1976, 1977; Hines et al. 1977). More detailed
information regarding statistical methodology may be found in Edmondson and
Winberg (1971) and in Elliott (1971).
9.2 INFLUENCE OF SEDIMENT ON AQUATIC PRIMARY PRODUCERS
Sediment may have the following effects on primary producers:
1. Reduces production by decreasing light penetration and by
destroying photosynthetic organisms by abrasion, scour,
and burial.
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2. Changes species composition or relative abundances through
changes in sediment type or composition.
Many of these conclusions are based upon field observations with their
inherent difficulty in identifying causal relationships. As a result, quali-
tative statements regarding the effect of sediments on primary producers may
be made, but quantitative predictions are difficult due to the complexity oft
aquatic systems.
9.2.1 Production
Light Penetration
It seems intuitive that increased turbidity from suspended sediments will
decrease light penetration and result in lowered primary production. The
reduction in light intensity by suspended solids results from scattering and
absorption of light by the suspended particles. Several studies in the 1930s
examined the effect of suspended solids on light penetration in streams and
lakes.
Light penetration for over 700 stations in the Mississippi-Ohio-Missouri
River drainages was reported in terms of the depth at which light would be
reduced to one millionth of its surface intensity (millionth intensity depth
or m.i.d.)(Ellis 1936). Measurements ranged from 84 mm for the Missouri River
at Boonville, Missouri to 20,000 mm for the Tennessee River at Paducah,
Kentucky. Lower measurements were related to an increased silt loading result-
ing from rainfall.
The theory of light scattering in natural bodies of water was described
by Whitney (1938). Part of the light energy is absorbed by water, part is
absorbed by suspended solids, and part is scattered. Whitney determined the
total light extinction coefficient and the proportion of light scattered by
solids in 15 Wisconsin lakes. The total extinction coefficient is composed
of
Nt = Nw + Npc + Ss
where N^ is the extinction coefficient of pure water, NpC the coefficient for
absorption by dissolved and particulate matter in the water, and Ss the
coefficient for scattering. Since only half of the scattered light energy
will be directed toward a light detector, Ss is divided by 2. Little corre-
lation was found between the total extinction coefficient and the scattering
coefficient since the scattering coefficient varies both with the concentration
and type of particle. No studies were found relating concentrations and types
of particles to scattering and extinction coefficients in freshwater systems,
despite a theoretical basis for such measurements.
Variations in turbidity in western Lake Erie have been investigated,
as they influence light penetration and the quantity of phytoplankton
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(Chandler 1940, 1942a, 1942b, 1944; Chandler and Weeks 1945). In the spring,
runoff from the western shore contributed large amounts of sediment from agri-
cultural land. Comparison of weekly means for turbidity and discharge showed
that increased river flow was accompanied by increased lake turbidities during
the first six months of the year. During the remainder of the year, there
were few periods of high discharge, but turbidities often increased due to
high winds. Suspended inorganic material (clays, fine sand) varied from 1.0
to 28.5 mg per liter and composed from 50 to 95 percent of the total suspended
matter. The inorganic portion was greatest during stormy periods when runoff,
mixing, and turbidity were greatest; the organic portiqn was greatest during
calm periods with little mixing, low runoff, low turbidity, and abundant
plankton. Storms which mixed the water homogeneously to the bottom resulted
in high turbidities (greater than 20 ppm in this case) and uniform light
extinction with increasing depth. The suspended material settled during sub-
sequent calm periods, resulting in variations in turbidity and light extinction
with depth and time. Phytoplankton studies showed that plankton pulses
occurred when turbidity was low; small populations existed when turbidity was
high. Chandler suggested that variations in the composition, size, duration,
and time occurrence of phytoplankton pulses may be partially accounted for by
variation in turbidity. Verduin (1951, 1954) subsequently related turbidity,
light penetration, nutrient levels, and phytoplankton standing crops to
current patterns in western Lake Erie. Maps showing the horizontal distri-
bution of light penetration were related to established current patterns.
Most of the flow into Lake Erie (96 to 98 percent) is from the upper
Great Lakes through the St. Clair-Detroit River (see Chandler 1944; Chandler
and Weeks 1945). This water was low in suspended solids and nutrients. The
balance was provided by rivers entering along the west and south shore. These
rivers drain rich agricultural land and carry large loads of suspended sediment
and nutrients. Verduin suggested that plankton in the clearer water to the
northwest were limited by low nutrient levels. Maximal phytoplankton crops
occurred when northeast winds mixed this clear water with the turbid, fertile
water from the southwest, creating a water mass with increased fertility and
intermediate turbidity.
Several other studies have attempted to relate phytoplankton standing
crops to turbidity or light penetration. Conflicting results were reported
in studies of Texas reservoirs by Harris and Silvey (1940). In two of the
reservoirs studied, Worth and Bridgeport, maximum net plankton numbers
occurred at low turbidities. Lake Dallas and Eagle Mountain Lake, on the
other hand, had maximum net plankton numbers during high turbidities, but the
quantity of organisms did not account for the opacity of the water. No one
factor appeared to control the variability in plankton production, despite
the large amounts of physical and chemical data gathered.
Claffey (1955) compared plankton standing crops in a series of farm ponds
and reservoirs in Oklahoma. Twenty farm ponds were selected by matching a
clear (turbidity < 25 JTU) and turbid (turbidity > 25 JTU) pond by similarity
in surface area, watershed type, and locality. Twenty reservoirs, 10 clear
and 10 turbid, also were examined. When the reservoirs and ponds were grouped
according to their range in turbidities, the average number of plankters
decreased with increasing turbidity. The range in plankton numbers shows
little or no overlap among the turbidity categories. Similar results were
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reported by Buck (1956a, 1956b), with clear ponds (less than 25 ppm turbidity)
producing eight times as much plankton as ponds of intermediate turbidity
(25 - 100 ppm) and 12.8 times as much plankton as ponds with high turbidity
(over 100 ppm).
It is commonly accepted that decreased light penetration due to increased
levels of suspended solids will decrease primary production. This assumes
that primary production is light-limited, but it may, in fact, be inhibited
at high light intensities. Many algae have the ability to adapt to low light
intensity or even require "shaded" conditions (Mclntire and Phinney 1965;
Tilzer et al. 1976). Furthermore, the effect of decreasing light intensities
due to the presence of suspended solids may be modified by concomitant
increases in nutrient levels (Verduin 1954; Sherk 1972; Tilzer et al. 1976).
The effect of sediment inflow on primary production has been examined in
Lake Tahoe (Tilzer et al. 1976). Sediment inflow reduced underwater light
intensities and increased nutrient concentrations simultaneously. Phytoplank-
ton samples were incubated within and outside a sediment plume in order to
compare photosynthetic rates under different light conditions. Surface samples
incubated in clear water showed light inhibition throughout the day, but high
subsurface light intensities resulted in increased photosynthetic rates with
depth. Surface samples incubated within the plume exhibited light inhibition
only around noon and decreasing photosynthetic rates with depth due to rapid
light extinction. Integral photosynthesis was less within the sediment plume,
despite reduced light inhibition at the surface, because of the decreasing
photosynthetic rate with increasing depth. Bioassays also were conducted to
compare photosynthetic rates under constant light conditions but with different
nutrient levels resulting from sediment additions. These tests suggested that
iron added by the sediment plume stimulated both photosynthetic activity and
growth. The authors concluded that:
1. Increased turbidity alone reduces integral photosynthesis
although this effect is diminished by less surface light
inhibition.
2. Increased nutrient inputs alone lead to higher productiv-
ity.
3. The effect of combined sediment and nutrient inputs depends
on the increase of biomass relative to the increase of non-
living seston in influencing the portion of underwater light
which is absorbed and utilized by the photosynthetic pigments
of the algae.
A study of primary production in the Patuxent River Estuary illustrates
the effect of gradients in nutrient availability, salinity, and light penetra-
tion in a flowing system (Stress and Stottlemyer 1965). Rates of primary
production were measured along a 29 mile segment of the estuary and compared
with light penetration, which increased downstream. The highest rate of carbon
assimilation per unit volume occurred at the upstream end. The average rate
of primary production from 14 sampling periods was 58.3 mg C/nr/hr and ranged
from 2.8 to 148.5 mg C/ne/hr. The downstream, less turbid station was only
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one-third as productive on a unit volume basis, and also less variable. The
average rate of primary production was 17.5 mg C/m3/hr and ranged from 5.6 to
38.0 mg C/m3/hr. The rapid quenching of light by suspended inorganics limited
the depth of the eutrophic zone in the upstream reach so that it was least
productive per unit area. At the extreme upstream station, one percent of the
incident light reached one meter and the mean daily rate of primary production
for the year was 1.2 g C/m2. At the downstream station, one percent of the
incident light penetrated five meters, and mean daily primary production was
1.8 g C/m2.
The two previous studies address the interaction of nutrients and light
intensity on rates of energy fixation by phytoplankton. Several other studies
examine the effect of nutrients and suspended sediments on plankton composition.
Work on several reservoirs in northern Mississippi illustrates the complex
changes in plankton composition due to changes in turbidity and nutrients
(McGaha and Steen 1974; McGaha et al. 1976). Many plankton genera disappeared
during periods of increased runoff and resulting higher turbidities. However,
7 of 27 phytoplankton genera studied responded positively to increasing tur-
bidity, presumably due to some favorable change in nutrient or light levels.
Drastic reduction in green and blue-green algal populations were commonly
associated with high turbidity. As turbidity decreased, green and blue-green
populations tended to increase and were correlated with orthophosphate concen-
trations. Diatoms, especially Melosira sp., increased during and after periods
of high turbidity. Population increases by diatoms were correlated with
silica levels which increased with the influx of siliceous material causing
high turbidities. Some zooplankton, such as rotifers and microcrustaceans,
also appeared to be positively correlated with increasing turbidity. McGaha
and his co-workers concluded that no one factor was solely responsible for
the observed fluctuations in plankton numbers.
A study of the phytoplankton of the Arkansas River yielded slightly
different results, which may reflect differences between systems (McNutt and
Meyer 1976). Decreased phytoplankton abundance was associated with high
turbidities and attributed to decreased light penetration. Nutrients, grazing,
and the influence of impoundments and tributaries also may have affected the
phytoplankton assemblage. Contrary to the findings by McGaha and his co-
workers, the green algae did not appear to be affected by turbidity, while
several blue-greens and diatoms (including Melosira sp.) showed drastic
reductions associated with high turbidities. Factors influencing the phyto-
plankton assemblage may vary from system to system; therefore, comparisons
between systems must be made with caution (McNutt and Meyer 1976). Further
interpretation of the study of McNutt and Meyer is hampered by the lack of
nutrient data and information on the concentration, composition, and particle
size distribution of suspended solids.
Few studies have examined the effect of reduced light intensities caused
by suspended sediments on the photosynthetic rate of submersed macrophytes.
Meyer and Heritage (1941) reported that the apparent rate of photosynthesis
of Ceratophyllum demersum in western Lake Erie is reduced during periods of
maximum turbidity, even at depths less than one mater. The compensation point
was between eight and ten meters during a period of minimum turbidity and
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between one and two meters during a period of maximum turbidity. No inhibition
of photosynthesis was noted at surface light intensities.
Several studies demonstrate a close correlation between the daily varia-
tion in light intensity and daily variations in photosynthesis by aquatic
plants (Gessner 1938, 1955; Meyer 1939; Burr 1941; Verduin 1952; Westlake 1964,
1966a, 1966b). Many studies also relate the depth distribution of submerged
macrophytes to limiting light intensities (Rickett 1921, 1924; Juday 1934;
Wilson 1935). This suggests that photosynthesis by submerged aquatic macro-
phytes would be reduced by suspended sediment, but few data have been found
regarding the importance of the effect.
From the preceding discussion, one may conclude that suspended solids
have a great effect on primary production when they reduce light intensities.
The overall result of sediment suspension will depend upon the degree to which
light intensities are reduced and the length of time such conditions exist.
Other factors may act synergistically or antagonistically with regard to
reduced light levels. Under nutrient limited conditions, added nutrients may
ameliorate the shading effect of suspended solids. Under enriched conditions,
suspended soilds may influence nutrient availability and impose increased
shading. The impacts of suspended solids are strongly dependent upon other
factors, including temperature, current velocities and distribution, flow
regimes, and taxon specific response by the biota.
Scour, Burial, and Abrasion
Erosion and deposition of sediment may damage algae and macrophytes.
Erosion and deposition occur concurrently, so that separating their effects is
difficult, if not arbitrary. During erosion, the substrate may be removed,
carrying or detaching associated organisms. During deposition photosynthetic
organisms may be buried by accumulating sediments. Abrasion, in the course
of sediment movement also may be a significant cause of organism mortality.
Erosion of the substrate, or scour, often has a detrimental effect on
benthic algae. Spring floods in areas producing large amounts of runoff may
severely reduce algal populations and are probably a common annual pattern in
areas with heavy snow accumulations (Hynes 1970b). Several studies indicate
that the size of the bed material is extremely important in determing the
extent of damage to benthic algae by high discharges. This is to be expected
since bed load movement is partially a function of particle size, with smaller
particles moving at lower water velocities than larger particles (Einstein
1964; Gregory and Walling 1973).
Douglas (1958) found that numbers of Achnanthes (a pennate diatom) were
related to the stability of the substrate in Belle Grange Beck, England.
Populations of 10$ to 5 x 1(P cells/cm' were quite common on permanent rock,
and seldom fell below 5000 cells/cm* after high flows. Populations on stones
occasionally reached 105 cells/cm2, but were reduced to a few hundred cells/cm2
after floods. High populations did build upon on the stones during periods of
low flow. Similar results have been reported by Gumtow (1955) and Kobayasi
(1961).
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Tett et al. (1978) examined periphyton pigment densities in Meechums River,
a low-alkaline, third order, piedmont stream in Virginia. Measurements of
photosynthetic pigments (chlorophyll a^and pheophytin a) were used to estimate
the biomass of benthic algae on various substrates. The substrates included
fine sand, silts, and clays, collectively referred to as mud (particle diameters
less than 0.25 mm), sand (particle diameter of 0.25 mm to 4 mm), gravel (parti-
cle diameter of 2 mm to 75 mm), rock (from 4 cm upward), and muddy-sandy gravel,
a heterogeneous mixture of mud and gravel. Pigment densities were related to
substrate type and distribution, current velocity, and flow regime prior to
sampling. Substrate type varied laterally and longitudinally due to differ-
ences in water velocity. Mean pigment densities and variability differed with
substrate type. Chlorophyll a^ densities on mud, for example, appeared less
susceptible to varying flow than those on sand. As a consequence, pigment
densities on mud were less variable with time than pigment densities on sand.
This was attributed to differences in the depositional environment, with mud
being deposited along the edges of the channel in low velocity regions, and
sand towards the center of the channel in high velocity regions. When dis-
charge increased, chlorophyll a_densities on sand often showed drastic
decreases, while chlorophyll a_ densities on mud showed little change.
The authors made several important inferences based on the results of
their study. First, it may not be useful to construct deterministic models
to predict periphyton biomass in view of the stochastic fluctuation in biomass
attributed to random changes in discharge and duration of low flows. Second,
the response of periphyton biomass to changes in flow is a function of sub-
strate type. It is not known whether periphyton on artificial substrates such
as glass and plexiglass slides respond to flow, sedimentation, and bed load
movement in the same way as do algae on natural substrates. Furthermore, the
authors note that species composition and habit influence the relationship
between flow, substrate, and chlorophyll a_density. It also is evident that
the effects of sediment movement are not readily separated from those due to
changes in the flow regime.
Work by Tett and his co-workers adds to the understanding of the inter-
action of flow, substrate movement, and, indirectly, benthic algal biomass.
The influence of these factors on rates of primary production by benthic algae
is largely unknown. It has been suggested that scour reduces the epipelic
community (organisms inhabiting the sediment surface) in Meechum's River
(Virginia) and as a result decreases net community productivity (Kelly et al.
1974; Church, Kelly et al. 1978; Church, Shoop et al. 1978). As discharge and
sediment movement decrease, the epipelic community becomes re-established, and
net community productivity increases from day to day. No quantitative data
has been published to date, however.
A study of the energetics of the Red Cedar River in Michigan indicated
that autotrophic energy production and heterotrophic energy consumption
decline significantly following high flows and siltation (King and Ball 1967).
Energy budgets were constructed for five zones of the stream based on sampling
during the summer of 1961. The fraction of allochthonous energy required by
heterotrophic organisms varied from zero in the urban and reservoir zones to
91 percent in a reach below a sewage treatment plant. The amount of energy
required by heterotrophs appeared to decline by 58 percent following high
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flows and heavy silt loads in September. Autotrophic aufwuchs production
declined 68 percent during the same period. Macrophyte energy fixation, on
the other hand, appeared unaffected. Turbidity reached 378 JTU during this
period, compared to 20 to 30 JTU common for that time of year. The change in
autotrophic production and heterotrophic consumption was attributed to silta-
tion which might have resulted in reduced light penetration, scour, abrasion,
and burial of organisms. These results must be interpreted with care because
the Red Cedar River has been extensively modified by man and is influenced by
effluents from metal processing and sewage treatment plants, runoff from
agricultural and urban land, and an impoundment. Discharge also is quite
variable, ranging from 3 to 6000 cfs within any year (Ball and Kevern 1973).
9.2.2 Species Composition and Abundance
The impact of sediment deposition on primary producers varies with the
habitat requirements of the organisms, the type of material deposited, and the
rate of sedimentation. These factors are not independent in that species
requirements, sediment size and chemical composition, and rate of deposition
are interrelated (Round 1964; Hutchinson 1975).
Attached algae and rooted macrophytes often develop best on specific
substrates. Some require solid surfaces for attachment and may be affected
adversely by the deposition of fine, shifting sediment. Others appear well
suited for growth on beds of fine silt and clay. A third group, commonly
growing on macroscopic plants are influenced by any changes in the condition
of these plants (Blum 1956; Minckley 1963; Hynes 1970a; Nuttall and Bielby 1973).
Changes in the proportion of various substrates will modify species composition,
relative abundances, biomass, and productivity (Tett et al. 1978).
The response of primary producers to sediment type and changes in flow
are species specific. Differences in algal species response to sediments and
flow were reported in a study of Doe Run, Kentucky (Minckley 1963). Large mats
of Vaucheri'a were common in softer substrates in areas protected from currents.
They often were washed downstream during high flows and deposited on riparian
objects. These emergent masses frequently remained alive and usually were
able to fruit; fruiting did not occur in submerged mats. Dichostomosiphon
tuberosus also was abundant and formed thick mats in silty areas. Dichosto-
mosiphon was not affected as severely by floods as Vaucheria, presumably
because of strong attachment to the bottom by densely interwoven rhizoids.
The distribution of primary producers was discussed in terms of the
environmental gradient provided by Doe Run (Minckley 1963). Adjacent to the
main spring, at the head of Doe Run, flow was swift and turbulent, with the
moss, Fissi'dens jubianus dominating the rubble bottom. Next came an area with
swift, almost laminar, flow and a bottom of sand and gravel. This area was
dominated seasonally by Vaucheria, a rapidly growing alga which does not
require a deep substrate for "rooting." This was followed by a transition
area where deposition of larger sand and gravel size sediments occurred. This
reach was occupied by Potamogeton foliosus, which anchors in coarse, unstable
substrates by developing a substantial mass of subsurface rhizomes. A semi-
lentic condition followed, where a milldam formed a pool on the stream. The
substrate in this first pool graded from sand in the upper half to silt and
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muck near the dam and was colonized by Mi tell a flexilis.
Distribution and abundance of aquatic macrophytes in lakes is strongly
influenced by physical and chemical characteristics of the substrate (Pearsall
1917, 1918, 1920, 1921; Misra 1938). The most abundant and varied communities
occur on fine inorganic clays and silts and rich muds, especially in areas
with low turbulence. The absence of turbulence may be due to water depth or
dampening of water movement by the presence of macrophytes. In either case,
resuspension of fine sediment, which may limit light penetration, is reduced.
Several studies demonstrate that the composition of the sediment is an
important factor in the growth of macrophytes. Potamogeton perfoliatus and
El odea canadensis grew more rapidly in natural sediment than in sand (Pond 1907;
Snell 1907).Similar results were reported by Mulligan and Baranowski (1969)
for Myriophyllum exalbescens rooted in soil, as opposed to sand. Lobelia
dortmanna grew only in sand with low amounts of organic matter in Big Lake,
Minnesota (Moyle 1945). Organic sediment and sediment from alkaline, sulfate
rich lakes inhibited growth; but water from these lakes did not hinder growth.
Growth of Lemna, a free-floating, aquatic macrophyte, depended upon the amount
of clay suspended in the culture and the type of soil from which it came
(Healey and McColl 1974). Growth also was related to the amount of phosphorus
added with the clay.
The effect of sediment deposition depends upon the rate of burial and the
ability of the organisms to adjust to sedimentation. Pearsall's studies (1917,
1918) of English lakes indicate that some aquatic macrophytes do quite well in
disturbed areas. Littorella, for instance, is a shallow water plant capable
of colonizing wave-washed, sandy shores. Isoetes lacustris, on the other hand,
was more common on stones covered by thin layers of silt, especially in areas
with no erosion or deposition. Pearsall noted that Isoetes is readily
smothered by sediment deposition since it apparently is unable to alter its
root level. In cases where rapid silting was evident, Nitella and Juncus
often occurred instead of Isoetes. In some instances Potamogeton perifoliatus
replaced Isoetes in areas with increased silting. In those cases, the propor-
tion of clay and concentration of potassium were greater in areas growing
P_. perfoliates than in those growing Juncus.
Many epipelic algae were well adapted for living on soft substrates.
These include many diatoms, such as Nitzschia, Navicula, Caloneis, Gyrosigma,
Surirella, Closterium, and Cymatopleura and motile canophytes such as
Oscillatoria and Phormidium. These algae are capable of moving through sedi-
ment and often are found forming rich carpets on silt beds (Blum 1956; Hynes
1970a). Studies of tidal zone communities of pennate diatoms indicate that
these algae move through sand at velocities ranging from 15 to 25 microns
per second (Aleem 1950; Callome and Dekyser 1954; Wohlenberg 1954; Nultsch
1962). Motile unicellular algae may not be affected adversely when the
overall rate of deposition is slower than their rate of migration. The ener-
getic cost of movement, though, may reduce the potential for growth and repro-
duction.
Several sediment characteristics appear to regulate growth of aquatic
macrophytes. These include: proportion of organic matter, silt, clay, and
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sand; pH; C:N ratio; exchangeable cations; redox potential; oxygen concentra-
tion; and nutrient availability (Misra 1938; Sculthorpe 1967; Hynes 1970a).
These factors undoubtedly influence the type, amount, and productivity of
algae, but no studies have examined these relationships (Hynes 1970a).
Sedimentation often results from lowered water velocities associated with
plant structure. Large filamentous algae which grow attached to solid surfaces
(Cladophora, Oedogom'um, and Ulothrix) often accumulate silt as the water
velocity is slowed within the thai!us (Blum 1956; Minckley 1963). If enough
silt accumulates, the lower portions of the organisms become shaded from light
and subsequently may be killed or detached by the weight of the sediment. The
remaining basal portion often initiates new growth under more favorable condi-
tions.
The presence of macroscopic plants often causes local changes in water
velocity. In rivers, growing shoots often cause reduced currents downstream,
which lead to more deposition on the downstream side. The plant may continue
to spread on the deposited material, protecting it from the direct force of
the current and consolidating the material within a developing mass of roots
or rhizoids. Eventually, the accumulating sediment and plant biomass increase
turbulence and erosive force by diverting the flow around the growing bank
(Minckley 1963; Hynes 1970a). The importance of this effect varies according
to local conditions. In swift, deep rivers, plants will have little impact on
the rate of sedimentation. In slow, shallow rivers, stands of plants may
accelerate the building of silt beds, with silt-free channels forming between
the accumulating mounds (Sculthorpe 1967). In lakes, the presence of aquatic
macrophytes may reduce resuspension of bottom sediments by wave action
(Jackson and Starrett 1959).
9.3 INFLUENCE OF SEDIMENT ON MACROINVERTEBRATES
There is a large body of literature treating the effects of sediment
movement on macroinvertebrates. Aquatic insects receive the greatest atten-
tion, followed by crustaceans and molluscs. Other groups, including the
Porifera, Coelenterata, Platyhelminthes, Annelida, and Bryoxoa have received
less consideration. This may be due to difficulties in sampling and identifi-
cation, restricted distributions, or to the relative insignificance attributed
to some of these taxa.
Macroinvertebrates, particularly aquatic insects, have received much
attention in terms of the biological effects of water pollution. They often
are recommended as indicators of water quality (Hellawell 1972; Cairns and
Dickson 1975) because a) keys are available for most groups, b) their rela-
tively stationary habit allows spatial analysis of results, c) their relatively
long life cycle makes temporal analyses possible, and d) their heterogeneous
composition ensures that some groups will respond to a given environmental
change. As a result, a large amount of information is available regarding the
ecology of aquatic macroinvertebrates and their response to changes in water
quality.
Variables controlling the distribution and abundance of macroinvertebrates
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have been reviewed in detail by Hynes (1970b), Brinkhurst (1974), and Wetzel
(1975). However, interpreting changes in species composition, biomass, and
number of macroinvertebrates does present certain difficulties despite the
large amount of information available. Although aquatic macroinvertebrates
are less mobile than fish, they may actively migrate from areas with adverse
conditions. Invertebrates also have a variety of life cycles of varying
durations, which must be accounted for in comparing changes in -species compo-
sition, number of individuals, and biomass over time. The heterogeneous
composition of macroinvertebrate communities may ensure that some change will
be measured, but it may be difficult to ascertain the cause of a given response
unless gross changes in their environment are evident.
Sediment movement is thought to influence macroinvertebrates by a) causing
avoidance of adverse conditions by migration and drift; b) increasing mortality
from sedimentation due to physiological effects, burial, and physical destruc-
tion; c) reducing rates of reproduction resulting from physiological effects,
changes in suitable substrates, and loss of early life stages; and d) modifying
rates of growth or production caused by habitat modification and changes in
type and availability of food.
Few of these conclusions are based on controlled studies. As a result,
changes often are documented without identifying the causative agents or with-
out arriving at quantitative relationships between observed changes and
hypothesized controlling factors. This does not negate the utility of the
conclusions, but does point out a need for identifying the relative importance
of the effects noted, an analysis of the multivariate nature of controlling
factors, and, if possible, quantification of the observed relationships.
Factors which affect the distribution and biomass of macroinvertebrates and
which, consequently, may obscure the effects of sedimentation include: basin
or channel geometry, water velocity, flow regime, temperature, pH, oxygen,
carbon dioxide, salinity, interspecific competition, life history, predation,
and accessibility of food. These variables must be kept in mind when examining
the effects of sediments on macroinvertebrates.
9.3.1 Drift and Mortality
Numerous studies have shown that high rates of sedimentation often
drastically reduce the numbers of benthic organisms, although it often is
unclear whether the increased sedimentation increases mortality or increases
drift of organisms from the affected area. Periods of maximum accumulation
of sediment significantly reduced the standing crop of macroinvertebrates
below the mouth of a logged watershed at Coweeta Hydro!ogic Laboratory (Tebo
1955). A flood occurring, after the period of accumulation removed deposited
sand and silt below the mouth of the logged watershed and reduced the density
of bottom fauna to 7.3 organisms/ft2, compared to 30.3 organisms/ft^ at the
upper stations not subject to siltation. Prior to flooding, samples below
the logged waters had ranged from 22.8 to 27.3 organisms/ft2. High flows from
mid-February through May prevented reaccumulation of sand and silt at the
lower station. During this period there was no significant difference in the
bottom fauna of the upper and lower stations. Recolonization of the lower
station was thought to have resulted from drifting insects.
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A study by Gammon (1970) is particularly interesting since macroinverte-
brate and fish populations were monitored over a four-year period, and the
amount of sediment added to the stream was measured. Sediment was produced by
the operation of a crushed limestone quarry and the amount added to Deer Creek
(a small, low gradient stream in Putnam County, Indiana) was monitored using a
90° V-notched weir. No significant changes in chemical composition, oxygen
content, or temperature of the creek water resulted from the introduction of
sediment laden water. The sediment ranged from 5 to 125 microns in diameter
and consisted of 90 percent calcium carbonate and 8 percent magnesium carbonate.
Inputs which increased the suspended sediment concentrations less than 40 mg/
liter caused a 25 percent reduction in macroinvertebrate densities in riffles
below the quarry. Inputs that increased the concentrations to more than
120/mg/liter resulted in some deposition and caused a 60 percent decrease in
macroinvertebrate densities. When sediment settled out in riffles, populations
were reduced to 60 percent of normal levels regardless of the suspended solid
concentration. The actual macroinvertebrate density ranged from 8 ind/ft2 in
riffles below the quarry to nearly 1000 ind/ft2 in riffles above the quarry.
When sediment inputs ceased, accumulated sediments were washed out by high
discharge and macroinvertebrate populations increased to levels found in
unaltered riffles within a few days. Experimental increases in suspended
sediments increased the rate of invertebrate drift in direct proportion to the
concentration added (up to 160 mg/liter). Drift appeared to be the primary
cause of population decreases since no macroinvertebrate mortality was noted
during the entire study. All species, including those preferring fine sediment,
i.e., Chironomidae, Tricorythoides, decreased in numbers during sediment input.
As a result, diversity, as measured by the index of Wihlm and Dorris (1968),
remained fairly constant during changes in density.
Other studies show that macroinvertebrate populations and diversity are
affected severely by sedimentation. Reed (1977) examined the response of
macroinvertebrates and fish to siltation from highway construction in Virginia.
Four streams were sampled upstream and downstream from construction sites.
No other physical data were reported, but the streams appeared to be low
gradient piedmont and coastal plain streams. The data indicated that silta-
tion from highway construction decreased the number of species by 23 percent
and the number of organisms by 40 percent. Single comparisons often showed
significant differences in total numbers but not in diversity. Several
observations were often necessary to detect significant differences in diver-
sity. Although no quantitative measure of drift was made, the author suggested
that drift is a major response of macroinvertebrates to increased siltation.
Burial and subsequent mortality was not thought to be important. Recovery of
macroinvertebrate communities was quite rapid and was attributed to the
flushing action of high water and repopulation by drift.
Chisholm and Downs (1978) examined the effect of sediment movement on
aquatic organisms in Turtle Creek, West Virginia. Turtle Creek is a high
gradient stream in the southern Appalachians which was extensively altered by
the construction of a divided four-lane highway. Sediment yield of Turtle
Creek reached 34,000 T, or 1,400 T/mi2 as a result of construction. Samples
from Turtle Creek were compared with those collected on Lick Creek, an adjacent
undisturbed stream. Changes in macroinvertebrates were evaluated in terms of
diversity, total genera, and total organisms collected in a 45-minute period
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from three pools and three riffles at each site. Collections were made every
four to five months at four sites. The greatest decrease in numbers and
diversity was observed in the upper reaches of the stream where channel gra-
dient was greatest and tributary inputs of organisms the least. This effect
was attributed to high flow and erratic sediment movement. The number of
organisms increased downstream and the range in diversity values decreased.
The increase in macroinvertebrate numbers downstream appeared to be propor-
tional to increasing drainage area, suggesting that drift from undamaged tribu-
taries was important in repopulating damaged areas. A year after construction
was completed, the number and diversity of macroinvertebrates in Turtle Creek
were similar to those of Lick Creek.
Earlier studies have shown that increased sediment loading from mining
and dredging operations is damaging to macroinvertebrate populations. Taft
and Shapavalov (1935) found that macroinvertebrate populations were always
lower in streams where mining occurred than in clear streams. Similar results
were obtained by Sumner and Smith (1939) in their study of the effects of
hydraulic mining in tributaries of the Yuba and American Rivers in California.
Silted tributaries of the Yuba River had 63 percent of the standing crop found
in clean tributaries. Silted tributaries of the American River supported only
41 percent of the numbers found in unsilted streams. Reaches of the Rivers Fall
and Par (England) subject to heavy loads of china clay wastes supported 11 per-
cent of the normal number of macroinvertebrates (Herbert et al. 1961). Unaf-
fected reaches carried 60 mg/1 of suspended solids, while polluted reaches had
concentrations of suspended solids ranging from 1000 to 6000 mg/1. Solid
wastes from a glass manufacturing plant on the Potomac River resulted in almost
complete absence of organisms in areas with high rates of siltation (Bartsch
1959). .Depression of benthic numbers was detectable as far as 13 miles down-
stream. Reduced numbers of macroinvertebrates also were found in downstream
reaches of the Truckee River, California (Cordone and Pennoyer 1960). Silt
from a gravel washing plant on a tributary caused a 95 percent reduction in
benthic populations below the outfall. Populations were reduced to 25 percent'
of normal levels as far as 10 miles downstream. Numerous other references
document decreases in macroinvertebrate numbers and biomass in streams with
high rates of sedimentation [e.g., Cordone and Kelly 1961; European Inland
Fisheries Advisory Commission (EIFAC) 1964; Gammon 1970].
The effect of sedimentation on benthos in lakes and reservoirs appears
to be quite variable. High rates of deposition will occur where streams enter
the basin and deposit their sediment load in the form of a delta. The great-
est rate of sedimentation thus will be restricted to a few areas of inflow,
and low rates of deposition will occur throughout the remainder of the basin.
Complex spatial patterns often occur because of basin morphometry, currents,
and wave action (Brinkhurst 1974). Effects of erosion and sedimentation on
macrobenthos in northern Mississippi reservoirs were quite variable (Millican
and McGaha 1969; McGaha and Steen 1974; McGaha et al. 1976). The mud-muck
substrate produced by low levels of deposition on the profundal zone of the
reservoirs provided the most suitable substrate for habitation by benthos.
Deltas occurring where streams entered the reservoir were subject to increased
deposition and erosion. These areas had fewer species and fewer numbers of
organisms than the more stable profundal zone. Channelization of some streams
resulted in extreme water level and water velocity fluctuations. Only shelled
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molluscs persisted in these areas.
vLittle evidence of actual sediment induced mortality exists. Many changes
in macroinvertebrate communities have been attributed to mortality due to
sedimentation, but without supporting evidence.
/
Sedimentation destroyed large portions of the mussel populations on the
Mississippi, Tennessee, and Ohio Rivers (Ellis 1931). Populations were reduced
where thick deposits of mud buried the adults or smothered the smaller mussels
in areas where the adults could maintain themselves. Later work in experi-
mental streams (Ellis 1936, 1937) showed that a variety of freshwater mussels
could not tolerate the accumulation of one-quarter to one inch of silt on
otherwise suitable substrates. Other individuals of the species thrived in
the same water when they were suspended on lattice work a few inches or feet
above the bottom. The high mortality was attributed to the accumulation of
fine particles and not to low 03, pH, C0£» or other water conditions. Ellis
noted that mussels in silty water remained closed 80 to 90 percent of the time
and when opened produced excess mucus in order to remove silt which tended to
settle in the mantle cavity. Individuals of the same species were closed only
50 to 60 percent of the time when in clear water. One would also expect
changes in filtration rates of mussels exposed to suspended solids. This is
supported by Stone and Palmer (1975), who found that the relative filtration
rate of the bay scallop (Agropecten irradians) was related inversely to levels
of clay minerals suspended in sea water.They also concluded that long-term
exposure of bay scallops to sublethal levels of suspended solids may interfere
with normal growth and development.
Mortality induced by suspended sediment may be related to the composition
and size of the particles. Work reported by EIFAC (1964) showed that kaolinite
and montmorillonite clays were harmful to Daphnia magna at levels of 82 and
102 mg/1, respectively. Charcoal was harmful at 82 mg/1, but pond sediment
was not lethal up to concentrations of 1458 mg/1. The exact cause of mortality
remains unknown, but Sabaneeff (1956) and EIFAC (1964) suggest that suspended
solids may interfere with the feeding mechanisms of zooplankters. High suspen-
ded solid levels may result in silting out of zooplankton (Pennak 1946). This
is supported by Hanks' (1976) finding that indiscriminant feeding on sediment
particles by herbivorus zooplankton may increase organism density and result
in loss by sinking.
Macroinvertebrate bioassays are often used to test for mortality caused
by sediment. One must be careful to distinguish between chemical toxicity due
to contaminants and mechanical injury due to solids in interpreting the results,
Prater and Anderson (1977a, 1977b), for instance, exposed a number of organisms
to sediment from Otter Creek, Ohio, and Duluth and Superior Harbor Basins,
Minnesota, in a 96-hour bioassay. Test species included a burrowing mayfly
(Hexagem'a sp.), an isopod (Asellus commum's), and a cladoceran (Daphnia magna)
Sediment from several stations were found to be toxic, but the array of poten-
tially toxic metals and pesticides present precluded determination of the
cause of mortality. In several cases no mortality was noted, suggesting that
chemical toxicity was more important than mechanical injury in bioassays with
significant mortality. Oxberry et al. (1978) conducted long-term bioassays
using taconite tailings from Silver Bay, Minnesota. Experiments with
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Pontoporeia affinis, a benthic amphipod, and Mysis relicta, a freshwater
opposum shrimp,showed no adverse effects. The authors concluded that no
mechanical injury or chemical toxicity could be demonstrated for these inor-
ganic sediments, but that high rates of deposition could be inimical to benthic
populations near the waste outfall.
v
9.3.2 Reproduction
Few studies document the result of sedimentation on invertebrate repro-
duction. Various authors suggest that the loss of eggs and early instars
results in significant changes in benthic macroinvertebrate communities, but
it is difficult to collect, isolate, and identify eggs and early larval stages
(Cummins 1962; Brusven and Prather 1974; Hart and Brusven 1976).
Experimental studies have shown that suspended solids have a variable in
fluence on egg development in some invertebrates. Kaolin and illite suspen-
sions have been found to reduce reproduction in planorbid snails (Harrison
and Farina 1965). Of the three species used, Biomphalaria pfeifferi would not
lay eggs in turbid water, Bulinus globosus layed eggs which aborted in turbid
water but developed naturally in clear water, while reproduction by Lymnaea
natal ensis was unaffected by turbidity.
Aquatic insects may minimize loss of young due to high flows and sediment
movement in two ways (Hynes 1970b). Eggs may be attached very securely to the
substratum so that even if sediment movement occurs, some will survive. Many
insect eggs also hatch over a long period of time, ensuring that short-term
conditions which may decimate nymphs or larvae (e.g., floods) will not elimi-
nate the species. Aquatic insects also lay eggs on or in emergent vegetation
and in terrestrial habitats not subjected to extensive sediment movement or
deposition (Merritt and Cummins 1978).
9.3.3 Habitat Modification
Sediment movement often modifies available macroinvertebrate habitats and
alters the type, distribution, and availability of food. The preference of
invertebrate fauna for certain substrates is an important aspect of fauna!
distribution and influences the impact of sediment movement on benthic communi-
ties. Interpreting the results of substrate changes is difficult due to
problems in obtaining statistically accurate estimates of biomass and numbers,
concomitant changes in numerous variables, differences inherent in substrate
type, and the mosaic of substrate present (Hynes 1970a, 1970b; Harman 1972;
Brinkhurst 1974; Hart and Brusven 1976; Minshall and Minshall 1977).
The type of substratum often controls the species composition, numbers,
and weight of organisms present. Differences in number and species of inver-
tebrates on different types of substrates have been demonstrated (Percival and
Whitehead 1929). The largest number per unit area were found on thick moss;
progressively fewer numbers were observed on Potamogeton, loose moss, Cladoph-
ora on stones, and on embedded and loose stones^Species composition also
varied with the substrate. Similar results were obtained by Minckley (1963)
in his study of Doe Run, Kentucky. In this case, number, biomass, and species
composition were related to substrate. Changes in populations depended on
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the species as well as the substrate. High discharges, for instance, caused
decreases in total number of organisms in beds of Fissidens, a moss, presum-
ably due to wash-out of organisms and reduction in plant biomass. Amphipod
populations, mostly Gammarus minus, often were constant, even after high dis-
charge. Turbellaria, oligochaetes, and dipteran larvae increased in number in
Fissidens beds during periods of above normal discharge. Minckley attributed
this to movement of these organisms into the more stable habitat provided by
the moss. Increases in oligochaetes and dipterans may have been related to
increased deposition of sand and silt within Fissidens beds since ensuing low
flows resulted in gradual decreases in silt and sand and reduction in oligo-
chaete and dipteran numbers. Other substrates showed much greater fluctuations
in total numbers, species composition, and specific populations. Shifting sand
and marl riffles supported few organisms and were altered drastically by high
flows and bed load movement. The close proximity of different substrates often
influenced the distribution of organisms. The presence of isopods and amphipods
on shifting sand, for instance, was attributed to dispersal from their optimal
habitat, the Fissidens beds. In addition, some aquatic insects apparently
change substrate preference as they mature. Minckley noted that early instars
of Ephemerella and Baetis seemed to prefer the Fissidens, but then moved to
open riffles as mature nymphs.
Substrate preference of macroinvertebrates is related to a variety of
factors. The presence of vegetation often results in the greatest inverte-
brate biomass and may be related to increased surface area (Harrod 1964) or a
sheltered habitat (Minckley 1963). The colonization of inorganic substrates
may be a function of surface area (Sprules 1947; Barber and Kevern 1973),
current velocity, particle size (Cummins and Lauff 1969; MacKay 1977; Minshall
and Minshall 1977), degree of compaction (Hart and Brusven 1976), substrate
stability (Percival and Whitehead 1929; Chutter 1969), amount and type of
detritus, (Egglishaw 1964; Woodall and Wallace 1972; Minshall and Minshall
1977; Rabeni and Minshall 1977), and the amount of periphyton (Minshall and
Minshall 1977). In addition, organism preferences may change with different
stages in the life history (Minckley 1963; Harmon 1972; MacKay 1977). Un-
fortunately, the factors listed are not independent, resulting in difficulty
in experimental design and interpretation.
For example, benthic insect communities in six first- and one second-order
streams in the easily eroded Idaho batholith were compared to determine the
degree of natural variation within and between streams and seasons (Hart and
Brusven 1976). Higher flows during spring runoff of the second year of the
study decreased the standing crop, species diversity, and total numbers of
species present in all streams. High runoff resulted in larger surface
substrate particle size, greater cobble exposure, lower amounts of detritus,
and lower insect populations than found after the low spring runoff of the
previous year. Mayflies (Ephemeroptera) were the most adversely affected
group and stoneflies (Plecoptera) the least. Ordinal dominance of insects
changed to a great degree in some streams but little in others over the
summer; communities did not change in the same way in each stream. The authors
attributed these changes to differences in location, microhabitat, flow, sub-
strate, channel configuration, intra- and inter-specific competition, food
type and availability, and dissolved substances. This study illustrates the
variability in community responses found and the complex set of interactions
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which may cause these changes.
Several studies document changes in macroinvertebrate communities due to
substrate alteration by siltation. The elimination of aquatic plants by tur-
bidity may be the primary effect of sediment loading and the elimination of
insects only a secondary effect (Surber 1953). This is supported by Hamilton
(1961), who suggested that high turbidity produced by suspended inorganic
sediment may not, by itself, harm the bottom fauna in shallow lotic environ-
ments unless the bottom becomes covered with a thick layer of such material.
Settling out of suspended solids may alter or destroy the vegetation and
result in a change in the associated fauna before smothering of the "normal"
substrate can occur. Other studies, however, suggest that changes in the
bottom faunal community are quite evident at low levels of sediment input and
that drastic changes occur before smothering of the normal substrate (Chutter
1969; Gammon 1970).
Few studies have been detailed enough to show whether particular groups
of invertebrates were affected more by siltation than others (Chutter 1969).
Many studies have shown that faunal density may decrease considerably, but few
revealed whether fauna associated with fine sediment (e.g., Tubificidae and
Chironomidae) appeared. Chutter1s work on a South African river demonstrated
that the invertebrate fauna of sediment and cobble substrates changed with the
amount of silt and sand in the water course. In reaches with large amounts of
silt and sand, the variety of animals found in cobble substrates decreased,
but the total faunal density did not change. Some of the organisms which were
affected adversely by sedimentation appeared in large numbers below impound-
ments which trapped silt and sand. Seasonal changes in flow also were impor-
tant, with higher flows and large amounts of silt and sand causing summer
declines in surface dwelling organisms as a proportion of the entire sediment
fauna. Chutter concluded that there may be a considerable change in the
composition of cobble fauna due to silt and sand inputs without the substrate
being smothered. This increase in the amount of silt and sand results in
increased instability of the substrate and sealing of interstitial spaces.
9.3.4 Avoidance and Refugia
Macroinvertebrate responses to sediment loading must take into account
avoidance of adverse conditions and later recolonization from refugia. Changes
in faunal numbers and composition may result from migration to more protected
habitats or drift from the affected area during adverse conditions. Following
the resumption of "normal" conditions, altered areas may be recolonized by
drift from unaffected upstream areas and active migration from refugia.
The importance of drift often is emphasized in studies of sedimentation
in streams. A number of studies suggest that the observed decline in numbers
of invertebrates in response to suspended solids results from drift out of
affected areas (Gammon 1970; Rosenberg and Wiens 1975; Chisholm and Downs 1978).
Drift is increased during periods of increased flow. Anderson and
Lehmkuhl (1968) found a fourfold increase in numbers and five to eightfold
increase in biomass of drifting organisms with rainfalls of less than one inch.
The number of insects drifting per unit volume was thought to be similar before
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and during freshets, hence the observed increase may be attributed to increased
volume of flow (Elliott 1967). The authors suggested that drift may be bene-
ficial in dispersing aggregates of young larvae, but that the removal of leaf-
packs and detritus could be detrimental for the benthos. In addition, macro-
invertebrates may migrate to protected habitats during adverse conditions
(Minckley 1963).
The hyporheal habitat (below the sediment surface) may provide another
refugium from extreme conditions. Extremely high discharges in a Welch
mountain stream severely depleted the insect fauna (Hynes 1968). Following
resumption of normal flow, the fauna steadily increased with the same size
distribution as before the high flow. This suggests that recolonization
occurred by migration from within the gravel bed and not from reproduction.
Subsequent work (Coleman and Hynes 1970; Hynes 1974) confirms that inverte-
brates may occur down to at least 50 cm in gravel beds. In addition, Coleman
and Hynes (1970) found that only 20 percent of the total number of organisms
sampled occurred in the first 7.6 cm. Conventional samples, e.g., surber
sampler and standardized netting,may seriously underestimate standing crops
of macroinvertebrates in gravel substrates since only the upper few centi-
meters are sampled. The importance of the hyporheal zone as a refugium is
unknown, as is the result of surface sealing by the fine sediments (Chutter
1972; Hart and Brusven 1976).
Drift from unimpacted upstream areas is thought to be a major source for
recolonization by invertebrates. Downstream drift of Baetis (a mayfly) and
Gammarus (an amphipod) was sufficient to replenish reduced populations to
normal conditions within one or two days when drift rates were high (Waters
1964). Many studies suggest that recolonization by drift is quite rapid
following resumption of normal conditions (Gammon 1970; Reed 1977; Chisholm
and Downs 1978).
Upstream movement by invertebrates also has been noted. Upstream move-
ment of benthos in the Speed River, Ontario, was 6.5 percent of downstream
drift by numbers and 4 percent by weight (Bishop and Hynes 1969). Upstream
movement may account for recolonizatin of denuded areas but is not of the
same magnitude as downstream drift. The ability of invertebrates to move
upstream is related to the substrate type. Heavy sand accumulations impede
upstream movement of many common riffle insects, even at water velocities as
low as 12 cm/sec (Luedtke and Brusven 1976). As a result, sand deposition in
gravel and cobble beds may block this upstream movement by invertebrates.
Williams and Hynes (1976) and Williams (1977) evaluated the relative impor-
tance of four means of recolonization in permanent and temporary streams:
downstream drift, upstream migration, vertical migration from within the
substrate, and aerial sources, e.g., oviposition. In the permanent streams,
all four sources contributed substantially, with drift being the most impor-
tant. In temporary streams, vertical migration was most important, accounting
for as much as 95 percent of the increase in numbers. The relatively low
importance of oviposition by adults was related to seasonal aspects of repro-
duction. The authors noted that it is difficult to separate the effect of
vertical migration from subsequent upstream migration and downstream drift.
Colonization of disturbed areas in lakes also appears to be quite rapid
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Clean substrates placed in Lake Windermere were colonized by several species
in as little as six hours (Moon 1940). As the time allowed for colonization
increased, the number of species and number of individuals also increased.
9.4 INFLUENCE OF SEDIMENT ON FISH
Studies of the effect of sediment movement on aquatic biota often are
initiated because of concern for fisheries resources. Much of the work in
this area deals with salmonid fisheries, hence conclusions regarding the effect
of sedimentation on fish are largely oriented toward cold water fisheries
(cf. Cordone and Kelly 1961; EIFAC 1964). Recent work documents changes in
warmwater species, but less information is available for these organisms than
for salmonids. The general conclusion is that sediment loading may increase
adult mortality, decrease rates of reproduction, and modify growth rates of
fish.
9.4.1 Mortality
Increased mortality of adult fish may result from abrasion and smothering
of gill tissue by fine sediment. This conclusion is based on two lines of
evidence 1) exposure of fish to suspended sediment under laboratory conditions
and 2) examination of fish collected in field surveys. The most widely-cited
laboratory study is Wallen's (1951) investigation of the direct effect of
suspended soil on warmwater fishes. Wallen exposed 380 individuals of 14
genera and 16 species to varying concentrations of soil in aquaria. No esti-
mates of suspended sediment concentrations were made. The author found that
1) noticeable behavioral reactions did not begin until turbidities reached
20,000 JTU; 2) most of the experimental fish endured more than 100,000 JTU for
a week or longer, and 3) fish died at concentrations producing 175,000 -
225,000 JTU due to clogging of the opercular cavity and gill filaments with
sediment. No evidence of gill injury or unusual amounts of mucus was found
in the dead individuals. The tolerance of the fish to high levels of suspended
sediment in aquaria led Wallen to conclude that natural clay concentrations
were not likely to be lethal for juvenile and adult fishes. Wallen recognized
that turbidity is an optical property, and, hence, the actual concentrations
in the aquaria remain unknown. The concentrations and particle sizes (24 -
62 y) also varied with time because of the periodic stirring and subsequent
decrease in concentration and particle size as the solids settled. In addi-
tion, no food was added during the experiments because such additions decreased
both the turbidity and oxygen concentration. Thus, mortality may have been
induced by the poor condition of the fish after extended starvation.
Several researchers suggest that suspended soils adversely affect the
gills of adult fish. The effect depends upon the type of particle, its size,
shape, hardness (Ellis 1944), and the length of exposure (Herbert et al. 1961;
Herbert and Merkens 1961; Herbert and Richards 1963). Exposure to solids such
as rock powders, cinder particles, kaolin, diatomaceous earth, and coal wash-
ings may abraid gills, induce mucus secretion, cause thickening of the
epithelial cells, and reduce resistance to disease (Herbert et al. 1961).
Herbert and Merkens (1961) studied the impact of kaolin and diatomaceous earth
on rainbow trout survival in aquaria. No difference in effect was found
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between kaolin and diatomaceous earth. Mortality was extremely variable;
exposure to low concentrations had some adverse affect, but not nearly as
great a mortality as at higher concentrations. No significant difference was
found between either the weights or the lengths of the fish exposed to differ-
ent concentrations. Examination of gill tissue showed that some individuals
exposed to higher concentrations developed thickened epithelial cells; others
exposed to these suspensions for three to six months showed no thickening of
epithelial cells or other obvious changes in gill structure. The authors
noted that rainbow trout had increased incidences of fin rot when exposed to
suspended solids. They concluded that inert suspended solids may reduce sur-
vival in rainbow trout by potentiating other stresses such as disease or
changes in gill structure, which otherwise would have negligible effects on
the fish. This is supported by histological studies which demonstrate changes
in gill structure in other fish species affected by fine suspended soils
(brown trout, Herbert et al. 1961; white perch, O'Conner and Sherk 1975).
Thus, there is some evidence that suspended solids may have sublethal effects
on adult fish. Evidence for directly induced mortality is based on fish
exposed to extreme concentrations, where avoidance of adverse conditions is
impossible (e.g., aquaria). Documentation of sediment-caused mortality under
natural conditions is complicated by the avoidance of turbid conditions by
many fish (Gammon 1970), the possible presence of contaminants (Cordone and
Kelly 1961; Legore and Desvoigne 1973), and the ability of healthy, uninjured
fish to wash away sediment particles through the continuous secretion of mucus
(Ellis 1937). Several studies have found that salmon will migrate through
silty water from glacial streams (Smith 1939; Foskett 1958; Cooper 1965) and
mining activities (Ward 1938a, 1938b) to spawn in clear tributary streams. It
is more likely that fish populations will be reduced by destruction of their
food supply, alteration of their habitat, or reduction in reproductive success
before direct effects of suspended sediment will be detected.
t
9.4.2 Reproduction
One of the major impacts of sedimentation on fish populations appears to
be disruption of normal reproduction (Cordone and Kelly 1961). Sedimentation
may impair reproduction directly by increasing the mortality of eggs and fry
or indirectly by altering habitats so that reproductive behavior, such as nest
building, does not occur.
Early studies of the effect of sedimentation on fish reproduction were
concerned with the hatching of salmonid eggs in gravel. One of the earliest
experiments documenting the influence of sedimentation on fish egg survival
was by Harrison (1923). He found that the survival rate of salmon and trout
eggs placed in man-made redds (nests) declined as the particle size of the
substrate decreased. Later studies considered conditions necessary for natural
propagation of salmonids in gravel beds. These studies involved comparing the
survival of eggs incubated in gravel in a hatchery trough with those incubated
in a hatching basket. Experiments with steelhead trout, Salmo gairdnerri
(Shapavalov 1937), and coho salmon, Oncorhynchus kisutch (Shapavalov and
Berrin 1940), showed that silt produced by high flows was deposited in the
gravel, smothering the eggs and preventing the fry from emerging.
A subsequent study of Shaw and Maga (1943) demonstrated that the timing
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of silt addition is critical in terms of reproductive success. Coho salmon
eggs (0. kisutch) were placed in gravel nests in three standard hatchery
troughs. The control trough received only normal hatchery water during the
experiment. The experimental nests received mining silt for varying periods
and at different times during development. At the end of the experiment, the
controls yielded an average of 16.2 percent fry (total number of fry emerging
from each nest divided by the number of eggs introduced); the nests receiving
silt from the beginning of incubation averaged 1.16 percent emergence; and the
nests receiving silt after the incubation period yielded 13.4 percent fry with
yields declining with earlier initial dates of silt addition. Thus, silt
addition during incubation drastically reduces survival. Additions after
hatching may reduce emergence, but do not have as severe an effect on the
yield of fry. The authors also pointed out that flow conditions ar"e important.
During periods of high flows, most clay and silt size particles will be in
suspension. As a result, little deposition will occur and minimal damage to
eggs in the gravel would be expected. During periods of low flow, added sedi-
ment would be deposited in gravel beds and the survival of eggs and emergence
of fry would be reduced.
A number of factors influence the survival of salmon eggs and fry in
gravel. The uniformity of particle sizes and proportion of fine particles
(less than 300 y) affects the apparent rate of flow through the bed (Cooper
1965). The rate of flow through the gravel bed affects oxygen concentrations,
the level of metabolic wastes, and, as a result, the survival of eggs and fry
(Alderdice and Wickett 1958; Peters 1962, 1967; Cooper 1965). The occurrence
of high flows may result in scouring of the bottom, destroying eggs and young
fish (Allen 1951; Wickett 1958; Onodera and Ueno 1961; Elwood and Waters 1969;
Hoopes 1975). Low flows may prevent access to spawning areas, prevent flushing
of accumulated silt, and result in superimposition of redds (Wickett 1958).
Turbid conditions, resulting from mining or dredging, also may cause salmon to
crowd into clear areas to such an extent that spawning individuals destroy
previously constructed nests (Smith 1939; Cooper 1965).
Very little information has been found regarding the effects of sedimen-
tation on reproduction by warm water fishes. Several researchers have noted
that small headwater streams, which are the most susceptible to alteration and
sedimentation, are very important in maintaining fishable populations in larger
streams, rivers, and lakes. Headwater streams serve as important breeding
grounds and also provide habitat for growth and reproduction of smaller fish
and invertebrates used for food by game species (Hall 1972; Smith 1972; Karr
and Gorman 1975). Gammon (1970) found that longear sunfish (Lepomis megalotis)
spawned in clear water with a clean gravel substrate, but avoided areas with
deposits of a thin white layer of sediment from a limestone quarry. There was
no indication that spawning of other species, such as suckers, was inhibited
by introduced sediment.
Environmental factors regulating northern pike (Esox lucius) reproduction
were studied in two main-stem impoundments on the Missouri River (Hassler 1970).
Silt deposition of 1 mm/day due to bank slumping and wave action resulted in
egg mortalities in excess of 97 percent. Once hatching occurred, siltation
had less of an effect. Suitable spawning substrate also was necessary, with
large year classes occurring when abundant flooded vegetation was available
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for egg deposition. Small numbers in a given year class occurred when the only
available substrate was mud or rubble.
Much less research appears to have been done on the influence of siltation
on reproduction in groups other than the salmonids. Life history and ecologi-
cal requirements are known for most fish; thus, one may suggest that repro-
duction in certain groups will be impaired by siltation. This is true
especially for those groups requiring vegetation (e.g., Esocidae) or clean
gravel or rock substrates for reproduction. Others are tolerant of silt
turbidity and may replace clear water species (Ritchie 1972).
9.4.3 Fish Production
Sediment loading may regulate fish populations indirectly by modifying
available habitats and thus altering rates of fish production. This may result
from loss of habitat, decreases in the availability of prey, or from behavioral
changes in the fish. Several researchers suggest that fish populations often
are limited by the amount of production within a system, as opposed to limita-
tion of predator species by physical parameters (Herbert et al. 1961; Lotrich
1973). Good evidence exists, on the other hand, that reproduction is affected
by physical conditions, and that physical factors control the distribution of
fish in many cases (McCrimmon 1954). One must conclude that fish production
is controlled by a myriad of factors, with the most important factors depending
upon the site and species studied, as well as the time of study.
Siltation of riffles appears to be a critical factor in the survival of
some juvenile fish. A detailed study by McCrimmon (1954) considers several
factors affecting the survival of Atlantic salmon fry (Salmo salar). Fry were
planted in Duffin Creek, a stream flowing into Lake Ontario, and their survival
and distribution monitored over a five-year period. Factors affecting survival
included temperature, turbidity, predation, shelter, flood, sedimentation, and
food. Observation of the fish from the time of planting until their descent
from the stream showed that the population of salmon supported in a section of
the stream was dependent on the type of habitat, and that the required habitat
changed as the fish grew. Freshly planted fry had the greatest survival in
shallow gravel riffles, where shelter was available in spaces among gravel and
stones. Those fry planted in pools, or moving to pools from unsuitable riffles,
were subject to intensive predation by brook trout (Salvelinus fontinalis),
creek chub (Semotilus atromaculatus), and common shiner (Notrppis cornutus).
As the salmon increased in size, their habitat requirements changed from
shallow riffles to deeper pools with shelter offered by undercut banks, logs,
rubble, and vegetation. Some yearling salmon were forced to move out of the
tributary streams into the main stream, where more suitable habitats existed.
The amount of sedimentation in the riffles also influenced salmon survival.
Three types of bottom were considered: totally sedimented, with the original
gravel or rubble covered with sediment; heavily sedimented, with the spaces
around the gravel and rubble filled in with sediment; and unsedimented, with
the spaces around the gravel or rubble not filled in with sediment. As the
amount of sedimentation increased in the riffle areas, the protective cover
for the fry decreased and salmon survival showed a corresponding decline. The
inability of some sections to support yearling fish also was attributed to
sedimentation and resulting loss of cover in pools. Similar findings have
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been reported for juvenile steelhead trout (Salmo gairdnerri) and chinook
salmon (Oncorhynchus tshawytscha)(Stuehrenberg 1975), but neither McCrimmon
nor Stuehrenberg suggested that reductions in prey species were important.
Lotrich (1973), on the other hand, found that reduction in prey species
may be important. Lotrich studied the factors affecting the fish community in
first-, second-, and third-order reaches of Buckhorn Creek, in eastern Kentucky.
The species composition increased longitudinally with increasing stream order.
Species in the first-order stream fed primarily on terrestrial invertebrates
falling into the streams. Aquatic primary producers and aquatic invertebrates
became important energy sources in second-order streams. Fish, salamanders,
and invertebrate detritivores were utilized in the third-order stream. During
the study, silt from a strip mine entered the third-order stream and had an
adverse effect on the fish community. The number of fish declined by 50 per-
cent and biomass by 10 percent. This reduction appeared to be due to silta-
tion, as no changes in pH were found. The reduction in numbers occurred
primarily in those species utilizing aquatic invertebrates and in age group I
of all species. Age groups II and III of the larger species were not affected
as severely, but production in those groups was expected to decline as there
would be fewer age group II individuals from those few surviving in age group
I. No change occurred in the number of fish in the unaffected second-order
segment immediately above the polluted third-order reach. The reduced numbers
may be attributed to three factors: a reduction in available food for species
using aquatic invertebrates, avoidance of turbid conditions, and loss of refugia
necessary for the survival of smaller individuals.
Several studies suggest that floods may reduce the numbers of juvenile
fish (age class 0 +), but that reduced invertebrate fauna exert a longer last-
ing limit on fish production (Allen 1951). A more recent study by Elwood and
Waters (1969) demonstrated that reduced invertebrate populations, due to severe
flooding, caused an apparent decrease in growth rate for a population of brook
trout (Salvelinus fontinalis) in a Minnesota stream.
Fish respond to increased sediment inputs in several ways. Response
appears to be species specific and may include reduced feeding, increased
ventilation rates, and avoidance of adverse conditions.
Suspensions of iron hydroxide reduced the growth rate of juvenile brook
trout (Salvelinus fontinalis), presumably as a result of impaired visibility
which prevented the fish from feeding (Sykora et al. 1972). O'Brien (1977)
measured the reactive distance of bluegills (Lepomis macrochirus) to various
sizes of Daphm'a pulex under different light intensities and turbidities. The
reactive distance, the greatest distance at which a predator can locate its
prey, was greatly reduced by both reduced illuminance and increased turbidity
for all prey sizes. This factor may be very important since a 50 percent
reduction in reactive distance may reduce the actual volume searched by a
factor of 8 if the fish searches a hemisphere (O'Brien et al. 1976).
Increased turbidity results in other behavioral changes as well. General
movement by largemouth bass (Micropterus salmoides) and green sunfish (Lepomis
cyanel1 us) was reduced when turbidity was elevated for 30 days in aquaria
(Hemistra et al. 1969). The normal social hierarchy of the green sunfish was
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disturbed during periods of elevated turbidity. There were no significant
differences in the number of attacks or amount of food eaten by either species.
The absence of a change in feeding behavior may be due to the light intensity
used, which was not reported (Vinyard and O'Brien 1976). A field experiment
by Bachman (1958) demonstrated that cutthroat trout (Salmo clarki) ceased
feeding and moved to cover when turbidity was increased to 33 ppm. Horkel and
Pearson (1976) found that green sunfish (Lepomis cyanellus) responded to clay
suspensions by increasing their ventilation rates. HThe fish were examined at
four temperatures (5, 15, 25, and 35° C) and six bentonite clay concentrations
(0, 3.3, 6.7, 13.3, 17.8, and 26.7 g/1). At 15 and 25° C, ventilation rates
increased 50 to 70 percent for the three highest concentrations. Rates of
oxygen consumption were not affected by turbid suspensions at any of the four
temperatures. The authors suggest that increased ventilation rates are a means
of compensating for reduced respiratory efficiency under turbid conditions and
also may prevent clogging of the gills with clay. A decline in activity also
was noted following the introduction of the clay suspensions.
Several authors have noted that fish exposed to turbid suspensions often
show reduced activity (Bachman 1958; Heimstra et al. 1969; Horkel and Pearson
1976). This reaction has been noted only under controlled conditions. Sal-
monids, for instance, often migrate through stretches of turbid water (Cooper
1965). Other work suggests that fish actively avoid turbid conditions, a
response that is probably species specific (Gammon 1970). Juvenile Atlantic
salmon often seek out turbid water produced by disturbing the bottom
(McCrimmon 1954). McCrimmon suggested that poor visibility may protect the
juveniles from predation and noted that the smolts descend streams during
periods of high water and low visibility.
The distribution of fish has been related to sediment produced turbidity.
Young largemouth bass (Micropterus salmoides) were not found in waters with
turbidity greater than 84 ppm; redear sunfish (Lepomis macro!upus) were absent
where turbidity exceeded 174 ppm; and bluegill (Lepomis macrocnirus) were not
found in water with more than 184 ppm turbidity (Buck 1956a, 1956b). Fish
yield also was correlated with turbidity. Clear farm ponds produced 1.7 to
5.5 times the total weight of fish obtained from more turbid ponds. This may
be due to lower primary production in turbid ponds since clear ponds had
plankton standing crops 8 to 13 times greater than more turbid ponds. In
addition, a number of monographs document the preference of fish for clear
over turbid waters (Trautman 1957; Pflieger 1971; Buchanan 1976).
9.5 SUMMARY
Considerable effort has been directed toward determining the effect of
sediment inputs on aquatic biota. While a number of general conclusions can
be drawn from the literature, the number of interacting variables often pre-
cludes quantification of causal relationships. Figure 9.1 summarizes the
major interactions between biota and sediments. However, interpreting the
response of aquatic biota to sediment inputs is difficult since different
bodies of water vary in their physical, chemical, and biological characteris-
tics. These physical, chemical, and biological factors may act synergistically
or antagonistically with sediment in regulating the presence and abundance of
211
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BACTERIA
FUNGI
MOMENT TYPE
PARTICLE SIZE
*T TYPE\ A
LE SIZE \ A
*" >\)
OXYGEN / N
ATMOSPHERIC (
.WATERSHED INPUT
TRIBUTARY INFLOW* OUTFLOW
rtANO USE
SLOPE
SOS. TYPE
VeOCTATION
WATER FLOW
. PRECIPITATION
SEDIMENT
TYPE
PARTICLE
SIZE
OXYGEN
WATER
VELOCITY
SUSPENDED
SEDIMENT
INOftOANIC
ORGANIC
REPRODUCTION
GROWTH
D
SEDIMENTATION
FEEDING
DETRITIVQRV
BIOTA
/ T
A / H
K f A
\l I F
K \ S
\ N
S==;\
TOXIC EFFECTS
ggUmnarm
FEEOMB INHIBITION
SHADING
NUTRIENT
REPRODUCTION
GROWTH
WATER VELOCITY
CIRCULATION t STRATIFICATION
PARTICLE SIZE
RESUSPENSWN
FROM SEDIMENT
BED LOAD
PERMANENT
SEDIMENTS
Fig. 9.1. Sediment exchanges and interactions in aquatic systems. Major
biotic and sediment pools are shown in compartments. Lines indicate
material flows, with the controls on these flows also indicated.
Single-headed arrows are used when the opposite directions of flow
are labelled.
212
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organisms. Therefore, grouping of waters by generally similar physical, chem-
ical, and biological properties, as may be accomplished by a regionalization
scheme, may be useful for predicting impacts by sediments at the various
hierarchical levels.
9.5.1 Sediment Impact on Trophic Levels
Primary Producers
Sediment influences primary producers by altering light intensities,
nutrient levels, substrate types, and species composition. The response of
primary producers is often stochastic, depending upon random changes in flow
and, hence, sediment movement. Overall, increased levels of suspended sedi-
ment reduce light intensity and limit photosynthesis; however, the presence of
associated nutrients may ameliorate this effect to some extent. Species compo-
sition of primary producers also is influenced by suspended and deposited
sediment. Changes in species and biomass are related to changes in suspended
solid concentrations, rates of deposition, bed load movement, and substrate
type. Predictive information relating the response of primary producers to
sediment characteristics is lacking. Research using controlled experiments,
such as laboratory streams, appears promising. The development of better
techniques for estimating primary production in field situations and analyzing
the response of primary producers to the hydrologic regime is necessary.
Macroi nvertebrates
Sediment influences macroinvertebrates by modifying habitats and inducing
movement out of areas with high rates of deposition. High rates of deposition
often drastically reduce the number of benthic organisms by burial of sessile
organisms and alteration of the substrate. Increased suspended sediment levels
often result in increased insect drift in running water. Filter-feeding inver-
tebrates, especially certain molluscs and crustaceans, are adversely affected
by high levels of suspended solids for extended periods. There is little
evidence for sediment-induced mortality for groups other than the molluscs.
Recovery by mobile invertebrates is rapid,foil owing the resumption of normal
conditions. Recovery depends upon how the habitat was modified, the substrate
preference and life history of the organism, the types of refugia available,
and the mode of migration. Recolonization may involve downstream drift,
upstream migration, vertical migration from within the substrate, and repro-
duction. Little is known of the importance of the hyporheal habitat, the
result of surface sealing, and the effect of sediment loading on reproductive
success.
Fish
Sediment affects fish by indirectly, increasing mortality, altering rates
of reproduction, and modifying growth rates. Suspended sediment does not
appear to be lethal for juvenile and adult fish, but may reduce their resis-
tance to disease and damage gill tissue. Fish may avoid localized areas of
increased sediment concentrations. The deposition of clay- to sand-size par-
ticles adversely affects reproduction in some groups, particularly the salmon-
ids. This results from reducing the flow of water and, hence, the renewal of
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oxygen and removal of metabolic wastes from deposited eggs. Habitat modifica-
tion, particularly the loss of cover for juvenile fish, and removal of suitable
spawning sites may reduce certain fish populations. Other groups appear to be
well adapted to turbid conditions and may replace more desirable species. In
addition, sediment may affect fish production by regulating primary and '
secondary production or by limiting the accessibility of food organisms.
9.5.2 Sediment Impact by Regions
A survey of the distribution of sediment related research suggests that
studies are concentrated in areas with economically important aquatic resources
and specific environmental problems. Provinces receiving intensive study
include Laurentian Mixed Forest, Eastern Deciduous Forest, Prairie Parkland,
Rocky Mountain Forest, Willamette-Puget Forest, and Pacific Forest. In the
Laurentian Mixed Forest region there is an emphasis on studies on the Great
Lakes, especially in terms of sediment toxicity, effects of taconite tailings,
the effect of turbidity on primary production, and the impact of sediments on
salmonid fisheries. The relatively large number of studies in the Eastern
Deciduous Forest Province can be attributed to the large area involved, as
well as to concern with extensive development in terms of agriculture, forestry,
mining, and construction. Research in the Prairie Parkland region developed
from concern over limitation of primary production by clay suspensions and the
resulting decline in fish yield in numerous farm ponds and reservoirs.
Several studies were located in the Rocky Mountain Forest province. Most
of these considered the effects of development (impoundment, mining, construc-
tion) on benthos and fish. Studies in the Pacific Forest and Willamette-Puget
Forest provinces considered the effect of sediment produced from logging,
mining, or impoundment on existing salmonid fisheries and potential food
organisms. Few studies were found in areas with low relief or low runoff.
These areas include the Outer Coastal Plain Forest and 14 western provinces
[California Parkland (2610), Great Plains Short Grass Prairie (3110), Palouse
Grassland (3120), Intermountain Sagebrush (3130), Mexican Highlands Shrub
Steppe (3140), Chihuahuan Desert (3210), American Desert (3220), Sierran
Forest (M2610), California Chaparral (M2620), Upper Gila Mountains Forest
(M3120), Colorado Plateau (P3130), and the Wyoming Basin (A3140)].
Water related problems in the 14 western regions are similar since
precipitation is low in many areas and existing surface waters are extensively
regulated by inter- and intra-state agreements. Extensive management and
diversion of existing surface waters across regional boundaries for domestic,
industrial, agricultural, and energy uses often conflict with the needs of
aquatic biota. An assessment of the extent of aquatic research in these
regions must acknowledge that institutional arrangements dictate that, in
certain areas, aquatic biota are of secondary importance to more pressing
demands.
9.5.3 Management of Sediment Impacts
The preferred approach to management of sediment impacts on biota is to
prevent high sediment losses from watersheds to the water. Surface erosion
may be reduced by maintenance of vegetated watersheds and river banks.
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Disturbances to the watershed should be minimal and timed to occur during
periods of low flow since most impacts by sediment are associated with snow
melt or storm events. Since sediment carries nutrients, the time of sediment
addition to water also may be a crucial factor in stimulating eutrophication.
Controlling existing sediment impacts may be best accomplished by using
mitigating structures which provide habitats and reduce abrasion and scour by
bed load sediment. High suspended sediment levels may require precipitation
by chemicals.
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1972. A reappraisal of Needham and Usinger's data on the
variability of a stream fauna when sampled with a Surber sampler.
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Claffey, J. C. 1955. The productivity of Oklahoma waters with special
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Coleman, M. I., and H. B. Hynes. 1970. The vertical distribution of the
invertebrate fauna in the bed of a stream. Limnol. Oceanogr. 15:31-40.
Cooper, A. C. 1965. The effect of transported stream sediments on the
survival of sockeye and pink salmon eggs and alevin. Internet. Pacific
Salmon Fish. Comrn. Bull. No. 18. 71 p.
Cordone, A. J., and D. W. Kelley. 1961. The influences of inorganic sedi-
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Trautman, M. B. 1957. The fishes of Ohio with illustrated keys. Ohio Div.
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Trowbridge, A. C. (ed.) 1962. Dictionary of geological terms. American
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CHAPTER 10
THE ROLE OF PHOSPHORUS AND NITROGEN IN FRESHWATER ECOSYSTEMS
AND THEIR IMPACT ON BIOTA
10.1 INTRODUCTION
Interest in the role of nutrients in influencing aquatic metabolism has
been stimulated recently because nutrients have been implicated in accelerat-
ing eutrophication in many freshwater systems. Eutrophication is a natural
aging process, whereby lake or stream basins gradually fill in, blooms of
undesirable algae appear, and discoloration or loss of oxygen from the water
with associated fish kills are observed. Man's urban, industrial, and agri-
cultural activities result in increased nutrient loading and often accelerate
the natural eutrophication process.
Two of the most important nutrients affecting aquatic metabolism are
phosphorus and nitrogen. Phosphorus is involved in many cellular processes
and is a critical component in basic metabolic reactions. Phosphorus has
received considerable attention in freshwater ecosystems since it is often
the least abundant of the major nutrients required in biological metabolism
(Vollenweider 1968; Edmondson 1972; Schindler 1977). Therefore, levels of
phosphorus frequently regulate primary productivity and additions of it to
water bodies often are responsible for declining water quality. Nitrogen
limits productivity in some systems and may become limiting seasonally in
others. Organisms need nitrogen for building structural components, as an
energy source, and for synthesizing proteins and pigments. Nitrogen is
especially important to bacterial breakdown of detritus. Since species have
individual nutrient needs, the levels of nitrogen and phosphorus are important
in determining the species composition and the succession rate of a system.
In this chapter the impact of nutrients on biota has been examined by
considering both the internal cycling and the result of external nutrient
addition to various system types. Concentrations of various nutrient forms
and the mechanisms of exchange between them are presented since the initial
nutrient levels and rates of transformation determine system response to
additional nutrient input. Cultural activities enhance nutrient additions to
aquatic systems; therefore, the effect of these additions has been explored
by considering studies of external loading of nutrients to water bodies.
Lakes, streams, and reservoirs are all considered, since biotic response to
nutrient addition may depend on system type. Methods for predicting biotic
response are examined and suggestions for management made.
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10.1.1 Forms and Distribution of Nutrients
Phosphorus A
Phosphorus can be found in dissolved, colloidal, or particulate form,
where it often is sorbed to other particles; it occurs as inorganic ortho-
phosphate, polyphosphate, or as organic phosphorus (Kramer et al. 1972).
Chemical analyses are based upon the reactivity of phosphorus with molybdate
to form molybdophosphoric acid. Of the eight forms of phosphorus recognized,
five have been widely used (Strickland and Parsons 1965). These forms are
based on particle size, acid digestion, and reactivity with molybdate. Com-
pounds requiring digestion with an oxidizing acid solution after membrane
filtration (0.45 u) are termed soluble phosphorus (SP). Compounds which react
spontaneously with molybdate after filtration are designated soluble reactive
phosphorus (SRP). Soluble unreactive phosphorus (SUP) is the difference
between SP and SRP and is often referred to as organic phosphorus, although
it is unclear whether all SUP compounds are, in fact, organic in nature.
Total phosphorus (TP) is measured after acid digestion of unfiltered water
with a strong oxidant such as potassium persulfate or perchloric acid. The
total phosphorus minus the soluble phosphorus is termed particulate phosphorus
(PP). The other three phosphorus fractions are subdivisions of the previously
mentioned fractions. However, these are not operationally defined since they
are not easily quantified. Particulate phosphorus is subdivided into reactive
PP and inorganic and organic unreactive PP, while the components of SP consist
of enzyme hydrolyzable phosphate and polyphosphates.
In many lakes, total organic phosphorus comprises up to 95 percent of the
total phosphorus. However, orthophosphate phosphorus (PO^-P or soluble
inorganic phosphate) is probably the only form of phosphorus directly avail-
able to algae. This fraction, considered part of the SRP fraction, constitutes
less than five percent of the total phosphorus found in temperate lakes. The
P04-P pool turns over very rapidly and may be less than 0.02 mg/1 in phosphorus-
limiting waters (Rigler 1966). During summer, the turnover time (the time
required to replace the phosphorus within a compartment) of PO^P in the
epilimnion is generally between one and eight minutes, regardless of the
trophic state of the water body (Rigler 1978). The SRP fraction has been
found to be an overestimate of P04-P in many instances (Rigler 1966;
Chamberlain and Shapiro 1969; Peters 1977). Only a small percent of the
chemically determined SRP fraction may be PO/i-P, as was shown in Kuenzler and
Ketchum (1962). Errors in determining the Plty-P content of lakes may result
from orthophosphate or organic phosphorus being released from ruptured cells
during filtration, from organic phosphorus being hydrolyzed to P04-P during
acidification, or from interferences with arsenate or germanium (Rigler 1966).
However, the SRP-POa-P discrepancy may only be significant when phosphorus is
limiting (Rigler 1973).
The supply of and demand for phosphorus will vary from lake to lake and
from organism to organism. The-average range of total phosphorus levels in
lentic and lotic freshwaters of the United States is from 0.1 to 0.2 mg/1
(Macgregor and Keeney 1975). Lakes exhibit standing total P concentrations
ranging from 0.005 - 0.030 mg/1 in summer to 0.008 to 0.08 in winter. Total
P concentration in United States' rivers may range from 0.002 to 5.04 mg/1,
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with industrial loading increasing this value (Sanders 1972). For the Great
Lakes, total P was found to be lowest in Lake Superior with a concentration of
0.005 mg/1 and highest in Lake Ontario at 0.08 mg/1 (Vollenweider 1968).
The amount of phosphate needed for optimal growth for phytoplankton will
vary among individual species (Kuhl 1974), depending upon the amount of phos-
phorus available and the algal capacity for storing phosphorus. The phosphorus
incorporated into algal cells can occur as polyphosphates, which can be
accumulated and used when needed. This storage of an element in excess of
normal metabolic requirements is known as luxury consumption (Hutchinson 1975).
It is not known if luxury consumption occurs in all algae, but upper limits
of phosphate tolerance for various algae have been found through culture
experiments. The reason for phosphorus inhibition of growth in cultures is
not clear (Rodhe 1948); however, it is rarely observed in situ (Fogg 1973).
Phosphates have seldom been found in sufficient concentration to exhibit toxic
effects upon higher organisms (McKee and Wolf 1971).
Nitrogen
The most biologically important inorganic forms of nitrogen in freshwater
are ammonium (Nfy-N), nitrate (NO^-N), nitrate (N02-N), and molecular nitrogen
(N?-N). Organic nitrogen occurs in particulate form (PON) as living organisms
and detritus and in dissolved from (DON) in compounds such as ami no acids,
amines, polypeptides, humic acids, purines, pyrimidines, porphorines, vitamins,
and urea. Separation of PON from DON is usually accomplished by retention on
a 0.45 y filter (Isirimah 1972).
Nitrogen concentrations in lakes vary with season and depth. Generally
epilimnetic nitrogen concentrations are NH^-N from 0-5 mg/1; NOg-N from
0-0.1 mg/1; N03-N from 0-4 mg/1; DON from detectable to a few mg/1 (Keeney
1973). In most deep temperate lakes minimum concentrations of epilimnetic
organic nitrogen are found before overturn, with a sharp increase in concen-
tration afterward. Nitrate is usually more abundant than ammonia, and nitrite
is scarce or absent in waters that are well oxygenated. However, both nitrite
and ammonia levels can be high in very productive water where reduced condi-
tions are frequently encountered. In the anaerobic hypolimnion of lakes and
in the interstitial sediment water, levels of ammonium can be above 10 mg/1
and nitrite can range up to 1 mg/1 (Hutchinson 1957; Konrad et al. 1970).
Softwater lake sediments contained about twice the total N concentrations of
hardwater Jakes in Wisconsin (Keeney et al. 1970). Most of the nitrogen in
lake sediments is organic (Keeney et al. 1970).
Streams are not as stable chemically as are lakes. They have more tem-
poral variations associated with changes in river flow (Livingstone 1963).
Total N concentration of United States rivers varies between 1 and 54 mg/1
(Sanders 1972). Most of the inorganic nitrogen is oxidized and in the form
of N03-N (Keeney 1976). The mean N03-N concentration of North American river
water has been reported as being near 1 mg/1 (Livingstone 1963; Golterman 1975)
DON often comprises over 50 percent of the total soluble nitrogen in
freshwater, and probably much of the DON is in the form of amino nitrogen
compounds (Peterson et al. 1925; Birge and Juday 1926; Hutchinson 1957;
233
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Manny 1972; Macgregor and Keeney 1975). DON of both lakes and streams is often
greater than PON, except under more eutrophic conditions when the pools may be
equal (Peterson et al. 1925; Hutchinson 1957), Seasonal distribution of DON
appears to be largely unpredictable and different for individual lakes
(Lueschow et al. 1970; Manny 1972),
The optimal inorganic nitrogen concentration of planktonic diatom cultures
is below 1 mg N/l and for green and blue-green algae is above 1 mg N/l (Vollen-
weider 1968). Due to luxury consumption, the nitrogen uptake may exceed the
minimal concentration necessary for growth.
Several nitrogen forms can be toxic to higher biota. In most water the
Nfty-N form of ammonia predominates; however, in very alkaline or warm water
the NH3-N form increases [Environmental Protection Agency (EPA) 1976]. The
toxicity of ammonia to fish and invertebrates is a result of the NH3-N fraction
which is 50 times more toxic than NH/^-N (Tabata 1962). The Environmental
Protection Agency (1976) has set the criterion for maximum permissible levels
of NH3-N in freshwater at 0.02 mg/1. The toxicity of nitrite to fishes varies
according to species and size (Russo and Thurston 1976). Sensitive species
may be killed by acute exposure as low as 1 mg N02-N/1 (Russo et al. 1974;
Smith and Williams 1974; West!in 1974; Russo and Thurston 1975). Chronic
exposure to lower concentrations may be toxic to some species or to fry which
may be more sensitive [Sprague 1971; National Academy of Science (NAS) 1978].
The criterion of 10 mg/1 NOo-N is based on the hazard to warm-blooded organisms
when high nitrate intake and subsequent reduction to nitrite impair hemoglobin
transport of oxygen (EPA 1976).
10.1.2 Transformations of Phosphorus
The transformations of phosphorus involve biological and chemical
constituents. Phosphorus assimilation and excretion by biota account for much
of the recycling of phosphorus between its various forms. Chemical trans-
formation occurs-mainly through phosphorus complexing with other elements, A
clearer understanding of phosphorus movement between its important forms has
been obtained through the use of tracer studies. These studies generally
employ compartmental analysis. The number of compartments in lakes or streams
can be extremely large and are usually combined into operationally defined
compartments. Much of the previous work on phosphate uptake measurements
indicated that only two pools, soluble inorganic phosphorus and particulate
phosphorus were important, with particulate phosphorus containing greater
than 95 percent of the total phosphorus. However, two other fractions may
contribute significantly to the inorganic phosphate pool (Lean 1973a, 1973b).
These are a low molecular weight, organic compound (designated XP) derived
from the particulate fraction, and a high molecular weight compound, actually
a very small particulate form (Paerl and Lean 1976), referred to as colloidal
phosphorus. Both of these fractions are potentially available for phosphorus
uptake by plankton through the release of phosphate to the soluble inorganic
fraction. The majority of the phosphorus is found in the particulate phase
if all compartments are equally labelled (Fig. 10.1). Complete labelling of
all compartments does not always occur. Rate constants, represented by k^
have been determined for several phosphorus exchanges (Lean 1973a) with kj,
the uptake of PO/j, occurring most rapidly (0.9 relative mass units/min).
234
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COLLOIDAL
PHOSPHORUS
1.16 %
0.13 %
- XP *
P04
0.21 %
PARTICULATE
PHOSPHORUS
98.5 %
Fig. 10.1. Relative amounts of available phosphorus in the four principal
compartments and exchange processes within the epilimnion. The
Ik's represent rate constants. (From Lean 1973a.)
Figure 10.2 is a model of phosphorus cycling in the epilimnion of a
eutrophic lake during summer (Rigler 1973). The arrows demonstrate the major
phosphorus fluxes while the thickness of the arrow denotes the importance of
the phosphorus exchanges. However, no rate constants are given. The model
describes P04-P interactions and other components including the SUP pool
represented by ^ and emphasizes the overall importance of the rapid turnover
of P04-P. The phytoplankton are divided into two size classes to illustrate
their relative roles in the rate of cycling of P04-P. A similar model describ-
ing phosphorus, flows in a shallow, polluted river showed that P04-P was the
major form assimilated by biota (Aiba and Ohtake 1977).
In most situations, a constant flux of phosphorus exists where organisms
incorporate phosphorus and release itjto the system through excretion and
decay (Confer 1972; Kramer et al. 1972). The direct release of inorganic
phosphorus compounds by ultraplankton, excretion by zooplankton, and enzymatic
hydrolysis of organic material are postulated as three mechanisms which return
P04-P to solution (Rigler 1973).
The cycling of phosphorus in the water is of extreme importance since it
constitutes a main source of available phosphorus for biota. Primary pro-
ducers, bacteria, and zooplankton are the major biotic cyclers, while complex-
ing and dissociation are chemical mechanisms regulating phosphorus flows.
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EPILIMNETIC
SOLUBLE PHOSPHORUS
EPILIMNETIC
PARTICULATE PHOSPHORUS
INPUT
Fig. 10.2. The phosphorus cycle in a eutrophic lake indicating the importance
of soluble PO^-P and the exchanges occurring among compartments.
Letters A, and ]3 represent soluble phosphorus other than P04-P.
The least significant flows are dotted while the most significant
flows are thickest. (From Rigler 1973.)
Algae
Assimilation of phosphorus by algae may vary by species and has been
studied in relation to their growth (Fuhs and Canelli 1970). The growth
kinetics of algae cannot be predicted from the amount of P04-P in water
(Rhee 1972), since the concentration gives no indication of turnover rate.
Even at high phosphate levels, cells take up and release phosphorus rapidly,
although a lag phase often is seen before rapid growth begins (Lean and
Nalewajko 1976). However, the rate of assimilation may depend on the concen-
tration of P04-P in the water and thus be described by the Michaelis-Menten
equation (discussed in the nitrogen assimilation section). An organism's
236
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ability to attach to surfaces, its sinking velocity, and its surface area to
volume ratio are also significant factors affecting phosphorus uptake (Fuhs
et al. 1972). Other factors such as pH (Schumacher and Whitford 1965; Viner
1975; Steeman-Nielsen and Rochon 1976), light (Kalff and Welch 1974; Jensen
et al. 1976), temperature (McCombie 1960), or water velocity (Fogg 1973;
Jensen et al. 1976) also may influence phosphate assimilation by algae.
Macrophytes
Phosphorus uptake in macrophytes has been studied mainly with regard to
their ability to remove phosphorus from sediments and translocate it through
their foliage (Bristow and Whitcombe 1971). Macrophytes also can remove
phosphorus from the water. Whether the nutrient source is obtained mainly
from the sedimens or water column depends upon the species and the relative
concentration of phosphorus in the two compartments (Bristow 1974).
Bacteria
Bacteria absorb phosphorus as orthophosphate and excrete it in an organic
form that may not be immediately available to algae (Phillips 1964). The
rapid uptake of phosphorus by bacteria may be the primary reason that phosphorus
turnover in lakes occurs rapidly. Within 20 minutes planktonic bacteria are
capable of absorbing 95 percent of 32P added to lake water (Rigler 1956). The
competition for phosphorus by bacteria may retard algal growth, but bacterial
growth may not be adversely affected to a great extent by algae (Rhee 1972).
Release of organic phosphorus by bacteria has not been found to correlate
with their growth rate or population size. Rapidly growing populations and
those approximating steady state conditions both have been found to release
significant amounts of dissolved organic phosphorus (Barsdate and Pretki 1974).
Zooplankton
Zooplankton act as rapid cyclers of phosphorus through microplankton
grazing and fecal pellet production. Of the total amount of phosphorus
ingested in the consumption of algae by zooplankters, approximately half is
released as orthophosphate while the rest is excreted in feces. Since this
grazing accounts for 12.6 percent of the total P removed from the trophogenic
zone, whereas sedimentation only amounts to about 2 percent, the fecal
material from Zooplankton has presumably remained in the trophogenic zone
where it can be consumed as detritus (Peters and Rigler 1973). In laboratory
studies, the rate of phosphorus excretion from zooplankton was one-third to
two-thirds less in the presence of bacteria. Phosphorus excretion by crusta-
ceans and rotifers under certain conditions may be equal to the daily phos-
phorus requirement of phytoplankton (Hargrave and Geen 1968). The amount of
phosphorus excreted daily by zooplankton may be nearly equivalent to their
body weight of phosphorus. These zooplankton excretion products, mainly
orthophosphate, can be incorporated and utilized by other biota (Peters and
Lean 1973). Algal production can be regulated by zooplankton grazing and the
rate of regeneration of P04-P in the water (Rigler 1974). Other factors con-
sidered to have an effect upon phosphorus release from zooplankton include:
temperature, food supply (Butler et al. 1969), the size of zooplankton (Barlow
and Bishop 1965), and detritus levels (Ferrante 1976).
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Phosphorus Complexes
The complexing of phosphorus with metal ions in the open water depends on
the amount and type of phosphates and metals present, the pH, and the presence
of organic species, sulfates, and carbonates. MetaT ions that complex and
that may have a significant influence on phosphorus forms and distribution
include ferric iron, manganese, zinc, copper, and aluminum. Humic and fulvic
acids found in bogs and lakes also can form colloidal aggregates with iron and
phosphorus (Shapiro 1964). With phosphorus addition to a fulvic acid-metal
complex, fulvic acid is displaced from the metal and then reacts with the
phosphate. When the metal is absent, no reaction occurs between phosphorus
and fulvic acid (Levesque and Schnitzer 1967). Iron compounds differ in their
affinity for phosphorus based on the oxidation state of iron and the presence
of particulate organic matter (Koenings and Hooper 1976). Ferric oxyhydroxide
complexes or nonreactive ferric iron are more effective at binding phosphorus
than is a ferric colloidal complex (reactive ferric iron).
10.1.3 Transformations of Nitrogen
Figure 10.3 diagrams the important nitrogen transformations to be
discussed:
VOLATILIZATION
ORGANIC N
AMMONIFICATION ^
4
"ASSIMILATION
NH4-N
NITRIFICATION ^
4
"ASSIMILATION
NOj-N
DENITRIFICATION ^
W
4
" FIXATION
N2
Fig. 10.3. Simplified biotic and abiotic nitrogen transformations. (Modified
from Brezonik 1973 and NAS 1978.)
Assimilation
Assimilation is the incorporation of ammonium, nitrate, or organic nitro-
gen into living biomass (incorporation of molecular N? will be discussed as
fixation). Most phytoplankton can use Nfy-N, or N02-N for the synthesis of
cellular materials, but ammonium is reported to be preferred by most species
(Syrett 1962; Brezonik 1972; Caperon and Meyer 1972; McCarthy et al. 1977).
Use of reduced forms requires less energy expenditure. Energy is required
238
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both to reduce oxidized forms and to induce special enzyme systems for assimi-
lation of the more oxidized forms (Eppley et al. 1969). When nitrogen is
limiting, phytoplankton use all forms (Nfy, urea, Nlh, NOg) in proportion to
their availability (Dugdale and Dugdale 1965; McCarthy et al. 1977).
Laboratory culture experiments, although not necessarily representative
of in situ conditions, indicate nitrate as an important nitrogen source for
plankton (Chu 1943; Eppley et al. 1969). Optimal phytoplankton growth occurs
when NOa-N ranges from 0.9 to 3.5 mg/1. Below 0.1 mg NOs-N/l nitrate can be
limiting and the formation of chlorophyll may be inhibited. The upper limit-
ing level or range is between 8.9 and 17.8 mg Mh-N/l, depending on the species,
and is 17.8 mg NH4-N/1 for all species studied (Chu 1943).
Some algae and macrophytes also can use dissolved organic nitrogen as a
nitrogen source (Lund 1965; Wright and Hobbie 1965; Dugdale and Goering 1967;
McCarthy 1972; North 1975). Bacteria generally utilize organic nitrogen
substrates the most; less than 10 percent of organic nitrogen substrates in
low concentrations are taken up by algae (Wright and Hobbie 1965). However,
some phytoplankton possess permease systems similar to those of bacteria and
are capable of active transport of dissolved organic matter (Shrift 1966;
Hellebust and Guillard 1967; North and Stephens 1967; Hellebust 1970).
Sediments contribute nutrients to water since many transformations occur
there. Benthfc algae and bacteria also may directly assimilate sediment
nutrients. Sediments also are prime nutrient sources for aquatic macrophytes,
especially when nitrogen levels are low in the water (Nichols and Keeney 1976).
The rate of assimilation of nitrogen can be described by the Michaelis-
Menten expression for enzyme kinetics:
V =
Ks
where v is the uptake rate, Vm is the maximum uptake rate, S is nutrient con-
centration, and Kg, the ha If -saturation constant, is related to the uptake
mechanism (Eppley et al. 1969; Eppley and Thomas 1969; Caperon and Meyer 1972;
Toetz 1973). Thus, at intermediate nitrogen concentrations, assimilation is
proportional to nitrogen concentrations. Plants concentrate nitrogen by rapid
uptake when levels are low and incorporate proportionately less when ambient
concentrations are high.
The Kg of individual species is considered to be ecologically significant.
Variations in growth rates and nutrient assimilation at different nutrient
concentrations are important characteristics of species that may determine
their geographic and seasonal distribution (Eppley and Thomas 1969; Eppley
et al. 1969). Phytoplankton in oligotrophic systems have a lower Ks than
those in a more eutrophic system (Maclssac and Dugdale 1969). Oligotrophic
populations adapted to low nutrient concentrations are able to take up
nutrients at a faster rate than species characteristic of a more eutrophic
239
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system (Carpenter and Guillard 1970). Competition for available nutrients at
low concentrations may result in the evolution of species with a low Kg value
(Toetz et al. 1977). Having a lower Ks value might allow a species to compete
with a dominant species with a higher maximum growth rate (Dugdale and Goering
1967). The possession of different Kg and Vmax values for different nutrients
is an important factor in determining species domination or coexistence at
varying levels of nutrients (Tillman 1977).
Other factors influencing assimilation are different regimes of nutrient
preconditioning (Caperon and Meyer 1972); light, needed for assimilation of
the less reduced nitrogen species (Toetz 1971, 1976); and the intracellular
ratio of [02]/[C02], which* when low, can induce the activation of enzymes
for the reduction of oxidized nitrogen forms (Solomonson and Spehar 1977).
Ammonification
Ammonification is the decomposition of organic matter to ammonium by
heterotrophic bacteria. Ammonification occurs simultaneously with assimila-
tion, with the net difference between the transformations being reflected in
the biomass level of nitrogen at a given time (Keeney 1976). Allochthonous
and autochthonous sources of organic matter are decomposed in both the water
column and sediments. The extent to which ammonification occurs in the
sediments or in the water column depends on oxygen availability (Kleerekoper
1953).
In many aquatic systems regeneration by biota of inorganic and organic
nitrogen (which is subject to ammonification) are significant processes.
Many algae have been reported to excrete or release nitrogenous products which
may be available to other organisms (Lund 1965; Wetzel 1969; Wetzel and
Manny 1972; Hellebust 1978). Macrophyte pumping of nutrients from sediments
with subsequent release to the water also increases nutrient availability
(Toetz 1973, 1974; Nichols and Keeney 1976). Zooplankton also are major
producers of regenerated organic nitrogen (Corner et al. 1965; Johannes 1968;
Pomeroy 1970). Some systems may support large numbers of bottom-feeding fish
which excrete significant levels of ammonium (Lamarra 1975a, 1975b). Other
workers consider bacteria to be most important in nutrient cycling in water
(Golterman 1960, 1964; Kuznetzov 1968; McCoy and Sarles 1969), although their
role in converting organic nitrogen to more available forms is not well under-
stood (.Keeney 1973). At low nutrient concentrations they compete with other
organisms and reduce the nutrients available to the rest of the system. How-
ever, under eutrophic conditions, bacteria may be very important in the break-
down of organic compounds to inorganic nutrients.
The ammonium content of sediments represents a large nitrogen pool
potentially available to biota. The highest ammonium concentrations are
associated with enriched sediments or with high organic loading (Brezonik
1973). The formation of ammonium in sediments is greatest at least 10 cm
below the water-sediment interface (Serruya 1974.) The interface is the site
of release of ammonium to the water column so that lower concentrations are
seen in the upper sediments (Isirimah et al. 1976). The reduction of external
nutrient loading can be insufficient to improve water quality due to nutrient
regeneration from sediments (Gibbon 1971). Some sediments tend to sorb
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ammonium which may be more important than biotic immobilization (assimilation)
in the reduction of available ammonium levels [Brooks 1969). Sediment fre-
quently acts as a buffer to maintain a constant level of ammonium in the water
through releasing or sorbing activities (Brooks 1969).
Quantification of ammonification in the nitrogen budget is difficult
since assimilation occurs simultaneously. Ammonification generally exceeds
uptake in studies where both processes have been measured (Alexander 1970;
Hanison 1979; Toetz and Cole 1978). Additional ammonium may be provided by
precipitation, streamflow, and sewage effluent. Presumably, excess Nfy is
deposited in the sediments.
Ammonium Volatilization
Volatilization of ammonium may be a significant nonbiological loss of
nitrogen when temperatures are high and the pH greater than 7.5 (Isirimah
1972). An increase in alkalinity may be associated with high turbulence or
with high rates of ammonification or photosynthesis in lakes or streams
(Stratton 1968, 1969; Istrimah 1972). The significance of this loss for a
variety of aquatic situations needs investigation.
Nitrification
Nitrification is the oxidation of ammonium to nitrate with hydroxylamine,
nitrous oxide, and nitrite formed as intermediates (Focht and Verstraete 1977).
Two steps are involved in nitrification; both steps are mediated primarily by
autotrophic, obiigately aerobic microorganisms (NAS 1978). Nitrosomonas and
Nitrobacter are the primary organisms oxidizing ammonium to nitrate in a
series of steps (Suzuki et al. 1974). These nitrifiers can grow heterotro-
phfcally on organic matter (.Focht and Verstraete 1977; NAS 1978). Other
microorganisms capable of nitrification are present in fewer numbers, are
strickly autotrophic, and have narrower temperature and pH ranges for optimal
growth CFocht and Verstraete 1977}.
The rate-limiting step in nitrification is the conversion of ammonium to
nitrate (Garland 1977). Nitrifying bacteria are mesophilic, preferring temper-
atures in the range of 1 - 37 C (.optimal temperature ca. 30° C), and prefer-
ring a neutral or slightly alkaline environment (Frederick 1956; Alexander
1965; Keeney 1973).
Activity by nitrifiers decreases sharply below pH 7 (NAS 1978). Nitrifi-
cation does not occur significantly in the softwater lakes of Wisconsin
(Chen et al. 1972b). The unbuffered softwater sediments dropped in pH
sufficiently to inhibit microbial transformations. The discovery of signifi-
cant rates of ammonium oxidation in acid environments revealed the occurrence
of heterotrophic nitrification by various bacteria and fungi (NAS 1978).
Although the importance of heterotrophic nitrification is not known, it is
generally believed that autotrophic nitrification is more significant
(Alexander 1971; Keeney 1973; Isirimah et al. 1976). Although oxygen is
required, nitrification will occur at oxygen concentrations as low as 0.3 mg/1,
Oxygen concentration is not as important as the rate of oxygen diffusion into
the system (Greenwood 1962). Nitrification occurs in the water column and in
241
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the sediments, depending upon oxygen availability. In shallow, well-mixed
lakes, nitrification by benthic autotrophs may be important to organisms in
the water column (Trifonova 1963). However, not all of the nitrate formed may
be available to biota in the water, since nitrate can diffuse back to the
sediments where it can be immobilized by benthos or denitrified (Chen et al.
1972b). Nitrification may not be as significant in the water column since
nitrifiers are not successful competitors against phytoplankton for ammonium
at concentrations below 0.1 mg NH/j-N/l (Goering 1972).
Nitrification is not an important process in streams containing less than
0.5 mg NH^-N/l and which lack substrate for nitrifying organisms (Garland 1977).
The majority of nitrifying bacteria are attached to plants or found within the
top centimeter of sediments. Nitrification also is inhibited in grossly
polluted streams which lack oxygen. Oxidation of ammonium is inversely related
to flow since the amount of nitrate formed depends on the period of contact
with the sediments.
In the presence of oxygen, nitrification is an important process in
streams, converting much of the ammonium loading to nitrate. Nitrification in
rivers can result in the conversion of half the ammonium loading to nitrate
and may represent eight times the ammonium assimilated into biomass (Gujer
1978). However, nitrification creates a large oxygen demand in lakes and
streams. To oxidize 1 mg of ammonia to nitrate requires more than 4 mg of
oxygen (Montgomery and Borne 1966; Wezernak and Gannon 1967). In the River
Trent, U.K., nitrification accounted for 75 percent of the total oxygen demand
(Garland 1973).
The process of nitrification is most important in sediments of warm,
shallow lakes and streams which are well-mixed, but the process also might be
observed during turnover in deeper lakes. Although the length of time nitri-
fication occurs in deep lakes may be short, rates of oxidation are rapid, and
significant amounts of nitrate may be formed (Keeney 1973). The amount of
nitrate available in the water column will depend on the rates of diffusion
of nitrate back to the sediments and subsequent denitrification.
Dem'trification
Denitrification, the reduction of nitrite or nitrate to N20 and N2,
results in a loss of nitrogen from aquatic systems. The process occurs in
water or in sediments when oxygen levels are low and where sufficient organic
matter is present to act as an energy source (Broadbent and Clark 1965;
Goering and Dugdale 1966; Brezonik and Lee 1968; Chen et al. 1972a; Koike
et al. 1972; Keeney 1973; Anderson 1977; Tiren 1977). Decomposition of organic
matter also consumes oxygen. When oxygen is depleted, bacteria use nitrate
as a terminal electron acceptor, releasing a reduced form of nitrogen.
Nitrous oxide ^0) can be an intermediate product of denitrification
and is the sole product of some bacteria (Focht and Verstraete 1977).
Although N20 is considered a minor product of denitrification, the proportion
of N20 increases below temperatures of 5° C and below pH values of 5 to 6
(Focht 1974; Stanford et al. 1975). Production of NgO is of concern due to
its role in destruction of stratospheric ozone (NAS 1978).
242
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Facultative anaerobes such as Pseudomonas, Achromobacter, Bacillus, and
Micrococcus are responsible for the reduction of nitrite and nitrate, but
they also are capable of other nitrogen transformations such as ammonification
(Alexander 1961) since the electron transport system of these facultative
anaerobes is identical prior to the terminal enzymes under both aerobic and
anaerobic conditions (Bandurski 1965). Denitrification does not require
completely anoxic conditions but has been reported to occur at low oxygen
levels (Koike et al. 1972; NAS 1978). Since the microorganisms are faculta-
tive they are able to withstand periodic aerobic conditions and may partici-
pate in denitrification in microanoxic zones.
The rate of denitrification is influenced not only by oxygen supply and
available energy sources, but also by temperature, pH, trace minerals, and
nitrate concentration. The temperature range for denitrification is from less
than 5° C (Goering and Dugdale 1966) to 60° (Nommik 1956), although individual
species have narrower ranges. Optimal temperatures are high, near 60° C
(Nommik 1956; Bremmer and Shaw 1958). Denitrification is more important under
neutral or alkaline conditions than under acid conditions, with an optimal pH
from 7 to 8 (Nommik 1956; Bremmer and Shaw 1958; Chen et al. 1972a; Brezonik
1973). Small amounts of molybdenum are required as a component of the enzyme
nitrate reductase. The rate of denitrification also increases with increased
nitrate concentration (Koike et al. 1972).
Denitrification can be a significant loss of nitrogen in eutrophic lakes
(Goering and Dugdale 1966; Brezonik and Lee 1968; Kuznetsov 1968; Chen et al.
1972c; Andersen 1974; Tiren 1977). The nitrogen loss can represent as much
as 80 percent of the nitrogen loading, especially in shallow, polluted lakes
(Vollenweider 1968; Ryding and Forsberg 1977). Transport of nitrate to
anoxic sediments by groundwater seepage may result in nitrogen losses by
denitrification (Keeney et al. 1971). Frequent changing from aerobic to
anaerobic conditions may stimulate nitrogen losses from alternating nitrifica-
tion and denitrification, as has been shown for soils (Reddy and Patrick 1976).
A difficulty encountered in quantifying rates of denitrification is
separating denitrification from other simultaneously occurring transformations.
Ammonification and nitrification are necessary for formation of sufficient
concentrations of nitrate. However, nitrification proceeds most rapidly under
aerobic mixed conditions, while denitrification requires anaerobic conditions.
Assimilatory nitrate reduction also competes with denitrification (Brezonik
and Lee 1968; Keeney et al. 1971; Isirimah et al. 1976). Generally aquatic
sediments are an ideal site for denitrification, since levels of organic
matter are high, and low oxygen conditions are frequently encountered. As
long as sufficient nitrate is supplied, the denitrification process can be a
major nitrogen loss.
Nitrogen Fixation
One major source of nitrogen in aquatic systems is fixation of molecular
nitrogen in surface waters and sediments. In the eutrophic zone, fixation is
associated with blue-green algae and photosynthetic bacteria. In deeper
waters and in sediments, heterotrophic bacteria are responsible for fixation.
Many genera of algae and bacteria are known nitrogen fixers and many others
243
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are believed to have this ability. NAS (1978) provides a summary of these
species and their habitats. With the Introduction of the acetylene reduction
method by Stewart et al. (1967), 1n situ nitrogen fixation measurements are
made frequently. However, several errors can be associated with the technique,
and values reported may not be accurate (Rusness and Burrls 1970; Home and
V1ner 1971; Wong and Burrls 1972; Hague and Burrls 1973; Flett et al. 1975).
Autotrophic Fixation:
Most nitrogen fixing blue-green algae 1n freshwater are filamentous and
have heterocysts. NHrogenase, the enzyme associated with fixation, 1s
located with the heterocysts (Fay et al. 1968) as a protection against high
oxygen levels which Inhibit nltrogenase activity and thus fixation (Lang and
Fay 1971; Fogg et al. 1973; Paerl and Keller 1977; Paerl 1978). Fixation does
occur 1n aerobic waters through the use of structural, chemical, and ecologi-
cal adaptations of blue-greens.
Photosynthetlc bacteria require anoxlc conditions and light simultaneously
so that their role 1n fixation 1s thought to be small (NAS 1978).
Occurrence and rates of fixation may depend on the availability of other
nitrogen sources. High dissolved organic nitrogen levels have been correlated
with high fixation rates, but this may be a noncausatlve relationship since
high phytoplankton blomass would increase dissolved organic nitrogen (Home
and Fogg 1970; Fogg et al. 1973). Some dissolved inorganic nitrogen might be
needed as a "starter" for fixation (Goering and Neess 1964; Home et al. 1972).
Fixation occurs in the presence of nitrate and ammonium, but rates may not be
maximal until these nutrient concentrations are low, although low levels might
represent high turnover. Nitrogen fixation may be more effectively inhibited
by ammonium than by nitrate (Allen 1956; Toetz 1973). The use of inorganic
nitrogen 1s preferred since fixation of molecular nitrogen requires a large
energy Input. Several investigators suggest that nitrogen fixation will
occur regardless of ambient concentrations of inorganic nitrogen whenever
nitrogen demand exceeds supply (Dugdale and Dugdale 1965; Billaud 1967, 1968;
Home et al. 1972).
Fixation also depends on available phosphorus. Phosphorus enrichment
has been shown to stimulate nitrogen fixation (Toetz 1973; Lean et al. 1976).
Other workers have reported high levels of phosphorus associated with nitrogen
fixation (Tew 1959; Dugdale and Dugdale 1962; Granha11 and Lundgren 1971;
Home 1971; Home et al. 1972).
Levels of organic carbon may Influence the amount of nitrogen fixed.
Glucose has no consistent effect on nitrogen fixation in the dark but inhibits
light fixation (Goering and Neess 1964). Since blue-green algae are faculta-
tive heterotrophs, they may switch from photosynthesis to the use of organic
compounds as an energy source in the dark. However, heterotrophic fixation
occurs at a slower rate (Virtanen and Mlettinen 1963).
It has been suggested that blue-green algae become dominant when produc-
tivity levels are high since they are more efficient at obtaining carbon
dioxide ((#2) at low concentrations than green algae (King 1970; Shapiro 1973).
244
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When C02 levels are low, the pH also 1s high. Therefore, the lowering of pH
or the addition of COg may result 1n a shift from blue-green to green algae.
Simultaneous addition of nutrients hastens this process; however, nutrient
addition alone stimulates blue-green algal growth.
Other nutrients required for fixation include: Ca, Mo, B, Fe, and Na
(Tew 1959; Goering and Neess 1964; Fogg et al. 1973). Molybdenum and Iron are
essential components of the enzyme nitrogenase. The other nutrients listed
are needed for growth on elemental nitrogen.
The availability of iron may be an Important factor In determining the
algal composition of an aquatic system. High rates of nitrogen fixation
result in a large demand for Iron (Lean et al. 1976). As iron becomes limit-
Ing, some blue-green algae may produce hydroxamate chelators which not only
Increase the availability of iron but also inhibit the growth of other algae
(Murphy et al. 1976}. The result is an algal community dominated almost
entirely by blue-greens.
Important physical factors affecting nitrogen fixation are temperature
and pH. Nitrogen fixation can occur over a wide range of temperatures (by
different species), although it is usually observed at times of greatest
water temperature In temperate, eutrophic lakes. However, other factors such
as limited nitrogen availability may be more important than temperature in
determining the occurrence of fixation (HAS 1978). Tolerance to a wide range
of pH also is observed for nitrogen fixers as a group, although alkaline
environments are preferred (MAS ]978).
There is some evidence for seasonal and spatial succession among blue-
green nitrogen fixers. Aphanizomenon general1y appears later In warm seasons
than Anabaena (Granhall and Lundgren 1971) and may require higher levels of
phosphorus (Vanderhoef et al. 1974). Aphanizomenon is found deeper 1n the
water and uses reduced carbon rather than CO? (Fogg et al. 1973). Anabaena Is
the more efficient nitrogen-fixer, as it contains more heterocysts per strand
(Granhall and Lundgren 1971). Many species, Including these two, are believed
to produce self-Inhibitors which may be Important in regulating blooms (Home
and Goldman 1972).
A study of blue-green algal succession in Green Bay, Lake Michigan, from
the eutrophic mouth of the Fox River out to more oil gotrophic lake water
revealed that Micrpcystis (a non-fixer) dominated when concentrations of all
nutrients were high (Vanderhoef et al. 1974). Aphanizomenon was found 1n
moderately eutrophic areas and fixed nitrogen as long as phosphorus was
available. As phosphorus levels declined, diatoms became dominant. In a
lake with a distinct and stable nutrient gradient, as in this case, there are
consistent variations 1n algal growth and in fixation rates. In other lakes,
blooms may be distributed randomly and may be moved by lake currents, making
fixation-rate calculations more difficult (Vanderhoef 1976).
The rates of fixation in lakes of varying trophic states have been com-
pared. Fixation may be highest at intermediate levels of eutrophication due
to the opposing effects of organic nitrogen and nitrate concentrations (Home
et al. 1972; Brezonik 1973). Nitrogen fixation in shallow, moderately
245
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eutrophic systems is important in the nitrogen budget and may represent up to
40 percent of the lake's yearly nitrogen loading (Granhall and Lundgren 1971;
Home and Goldman 1972; Torrey and Lee 1976). Oligotrophic lakes lack suffi-
cient nutrients for fixation to be significant. When nutrients are low,
diatoms outcompete blue-green algae to become the dominant phytoplankton
(Welch et alI. 1972; Keating 1978). In stratified, nonoligotrophic lakes,
proper conditions for fixation are found at the end of the spring phytoplank-
ton bloom and during the autumn overturn. Nonstratified, nonoligotrophic
lakes may demonstrate irregular fixation as optimal conditions occur periodic-
ally (Home et al. 1972).
Heterotrophic Fixation:
Optimal physical conditions for heterotrophic fixation are different
from those for autotrophic fixation. Controversial evidence exists for fix-
ation by yeasts and fungi, but bacterial fixation is well documented (Keirn
and Brezonik 1971). The bacteria responsible are facultative anaerobes which
are not sensitive to temperature, allowing fixation to occur over a longer
season and at greater depths (Kerin and Brezonik 1971; Brezonik 1973; Whitney
et al. 1975). They require anoxic conditions or may be found at the anaerobic-
aerobic interface (Brezonik and Harper 1969; Keirn and Brezonik 1971; Brezonik
1973; Whitney et al. 1975). At least 18 genera of heterotrophic bacteria may
be capable of nitrogen fixation (NAS 1978).
The main factor limiting bacterial fixation is a sufficient carbon energy
source, since these bacteria are inefficient users of carbon and also must
compete for available carbon with both fixers and nonfixers (Stewart 1969;
Toetz 1972; Brezonik 1973; Whitney et al. 1975; Hanson 1977a, 1977b).
Additions of sucrose, but not glucose, pyruvate or butyrate have been shown
to stimulate nitrogen fixation in anoxic sediments (Keirn and Brezonik 1971).
However, no relationship has been observed between nitrogen fixation and
sediment ammonium, total organic nitrogen, phosphorus, percent volatile solids,
or nitrogen (Brezonik 1973).
Bacterial fixation in deeper waters and sediments has not received much
attention but may be a significant nitrogen source (Brezonik and Harper 1969;
Keirn and Brezonik 1971; Brezonik 1973; Macgregor et al. 1973; Macgregor and
Keeney 1973). However, nitrogen fixed in sediments may not be available to
biota. Much of it may be denitrified. Although more research is needed to
determine the significance of sediment fixation, it may be of minor quantita-
tive importance in the nitrogen budget of most lakes. The importance of nitro-
gen fixing heterotrophs lies in their widespread distribution and ability to
fix small quantities of nitrogen over prolonged periods of time.
10.1.4 Nutrient Budgets
Nutrient budgets which consider the internal levels of various forms
and the rates of exchange between pools are useful in determining the impact
of nutrient loading. Although a few whole lake budgets have been constructed,
more are needed, especially for different system types and trophic states.
Few phosphorus budgets exist because methods of distinguishing between all
forms are not reliable, turnover between forms is rapid, and concentrations
246
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are low. Mass balance nitrogen budgets for a few lakes have been summarized
by NAS (1978). These budgets consider internal pools and fluxes as well as
external nitrogen sources and losses from fixation and denitrification.
Although the transformations of nitrogen are known, how pool size and rates
of transformations vary from system to system needs more attention. Since
some nitrogen transformations increase, paralleling eutrophication, these
exchange rates can be important predictors of system behavior. Much of the
information obtained from nutrient budgets can be used to develop models
predicting system behavior (see section 10.3.1).
10.2 THE IMPACT OF NUTRIENTS ON BIOTA
10.2.1 Biotic Level of Impact
An increase in primary productivity or a shift in the dominant producer
species usually occurs following nutrient enrichment in systems such as lakes
where productivity exceeds respiration (P/R > 1). However, productivity may
be limited by factors other than nutrients. For example, in reservoirs
productivity frequently is limited due to high turbidity (Silvey and Wyatt
1971), while in streams, producers may be restricted by dense canopy cover or
by turbulent flow. Streams have been described as a continuum from hetero-
trophic headwaters to autotrophic middle stretches to heterotrophic mouths
(Cummins 1975). Only in the heterotrophic reaches of nutrient poor streams
can nutrients limit primary productivity. In the detrital based reaches of
streams (P/R < 1) nutrients are not expected to augment primary production,
although nitrogen addition may stimulate detrital breakdown, thereby stimu-
lating primary or secondary productivity.
A systems's response to nutrient addition will depend upon the degree of
impact. Nutrient input may stimulate productivity up to a certain level.
Thereafter, increased additions no longer will affect the response, or a
negative effect will be observed. This response gradient may be represented
by a "performance curve," where response is plotted on the y-axis and increas-
ing input is plotted on the x-axis (Odum et al. 1979). A series of perfor-
mance curves may represent the succession of populations as nutrient input
increases (Fig. 10.4).
The points at which these curves intersect reflect a shift in the major
dominant group. The figure may represent a phytoplankton succession (i.e.,
diatoms to greens to blue-greens), a succession of macrophytes (i.e., sub-
merged to floating to emergent), or a successional series of higher organisms
such as fish (i.e., trout to bass to carp).
Although the successional changes are correlated with increased nutrient
concentrations, the impact of nutrients often is indirect. Even at the
phytoplankton level, community shifts may not be directly related to nutrient
additions. For instance, blue-green algae may become dominant at low
concentrations, which result from increased productivity, although this
increase in productivity is caused by nutrients initially.
247
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t
I-
-------
TROPHIC LEVELS
SECOND CARNIVORE
FIRST CARNIVORE
HERBIVORE
(GRAZERS & SCRAPERS )
PRODUCER
( BACTERIA )
Fig. 10.5. Productivity pyramid for a low productivity pond. Trophic levels
which apply for streams are indicated in parentheses. (Adapted
from Whittaker 1975.)
10.2.2 Modifiers of Impact Response
Understanding the impact of nutrients in freshwater lakes and streams
requires not only consideration of external factors modifying system behavior
but also consideration of the internal state of the system. External factors,
which include physical and chemical parameters influencing productivity and
watershed activities, are examined first. Then internal factors are con-
sidered, including water properties influencing the trophic state, other
biota present, nutrient ratios, and interactions with sediemnts.
External Physical and Chemical Controls
Spatial heterogeneity across the United States (climatic, geologic,
hydrologic, biotic, etc.) create a wide range of conditions which influence
the nature of water bodies and their responses to nutrient inputs. A consi-
deration of the many variables impinging on an ecosystem makes each system
unique. Some of the more important controls are enumerated in this section.
However, a number of features, i.e., components and processes, are common to
many freshwater ecosystems allowing an aggregation of systems into a hierar-
chical scheme.
Climatic variables have an overriding influence on system behavior.
Temperature, for example, regulates organismal metabolism and affects species
composition. Temperature extremes may control both seasonal and daily mixing.
Increased temperature results in decreased oxygen solubility. The extent to
which evaporation occurs and the amount of ice cover are regulated by temper-
ature. Light levels and the amount of precipitation also are climatic vari-
ables. Major geologic formations and soil types in conjunction with climate
249
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determine the dominant vegetation and level of nutrient loading.
Watershed Activities
The type of watershed has a major influence on external loading rates and
nutrient concentrations observed in the water. Nutrients may enter aquatic
systems from natural or cultural sources. Natural nutrient sources include
contributions such as precipitation, groundwater, and runoff associated with
geology. Cultural sources include inputs from deforestation, agricultural
practices, and urbanization, and from sewage and industrial effluents. Most
phosphorus loading is associated with cultural activities, while the majority
of nitrogen input may be from natural sources. For example, estimations of
nutrient sources for Lake Mendota show that 60 to 70 percent of the phosphorus
results from man's activities, and that the same percentage of nitrogen input
is associated with natural sources (Lee 1969).
Data from several references considering inputs to lakes and streams have
been compiled in Table 10.1. Based on the average values of several studies,
deforestation and agricultural practices increase both nitrogen and phosphorus
loading, although urban runoff contributes a significantly greater proportion
of phosphorus. Precipitation can be an important phosphorus source and gen-
erally is a significant source of nitrogen. Groundwater also contributes
significantly to the nitrogen pool, although it is difficult to manage.
Water Properties
A number of internal properties of freshwater systems influence nutrient
and sediment impacts. Morphometric and hydro!ogic features will affect the
extent to which nutrient loading can be tolerated, as well as determine the
presence or absence of benthic producers. Important chemical factors regula-
ting which biotic forms are present include pH, redox, organic matter, and
the forms and concentrations of nutrients. Indigenous biota will control
rates of nutrient cycling and the availability of nitrogen and phosphorus
compounds.
Nutrient addition stimulates productivity to a greater or lesser degree
dependent upon the site of addition. Injection of nutrients into the epilim-
nion may support a large crop of phytoplankton, since the nutrients are
readily available. When injection is into the hypolimnion most of the nutri-
ents are sedimented, and stratification reduces upward movement. However, in
either situation, by fall turnover the majority of added nutrients may be-
unavailable.
Trophic States
Variations in concentrations of nutrient species are a result of differ-
ing levels of external input as well as varying internal biotic and abiotic
cycling. Concentrations generally refer to the standing quantity of nutrients
at a particular time. This information does not indicate the rate or amount
of flux through the system nor the rate or amount of cycling within it. The
concentrations of nutrients often are lowest at times of highest productivity
due to high rates of flux. However, the mean annual standing quantities do
250
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Table 10.1.
Annual loading of nutrients. [Unmarked - nutrients enter per
surface area of watershed (kg/ha-yr); * - nutrients in waters
entering aquatic systems from watershed (Kg/yr); + - nutrients
entering surface area of water body (kg/ha-lake surface-yr);
average - average of nutrient entering per surface area of
watershed (kg/hr-yr).]
Source
Total N
otal P
Reference
Forest Runoff
"
11
11
1.3-5.0
2.5
4.4
0.084-0.18
.083
.047
Cooper 1969
Keeney 1976
Omernik 1976
Dillon & Kirchner 1975
(Igneous)
.117
(Sedimentary)
Dillon & Kirchner 1975
Average
Forest and Pasture
2.5
0.198*
3.14
1-5
2.5
.019*
0.102
0.15-0.75
.102
Uttormark et al. 1976
Macgregor & Keeney 1975
Vollenweider 1968
Keeney 1976
Dillon & Kirchner 1975
(Igneous)
5.5 .174
.233
(Sedimentary)
Omernik 1976
Dillon & Kirchner 1975
"
Average
Agricultural
Average
0.246*
4.67
5
22.4
5
9.8
10.6
0.164*
0.28
0.18
.046
.308
0.18
Macgregor & Keeney 1975
Uttormark et al. 1976
Montelaro 1970
Dillon & Kirchner 1975
Keeney 1976
Omernik 1976
251
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Table 10.1. (Continued)
Source
Urban Runoff
ii
ii
M
n
ii
Average
Total N
8.8
5
5
7.9
2.010*
6.7
Total P
1.1
1.1-16.6
.301
0.567*
10-14400 ug/1
4.8
Reference
Weibel et al. 1966
Dillon & Kirchner 1975
Uttormark et al. 1976
Keeney 1976
Omernik 1976
Macgregor & Keeney 1975
Sylvester 1961
Ground Water
15.600*
0.130*
Macgregor & Keeney 1975
Industrial
0.680*
0.046*
Macgregor & Keeney 1975
Septic Tanks
4*
Keeney 1976
Precipitation on Lakes
Average
5.8+
1.8-9.8+
10-20
15+
3.160*
8.1*
0.44+
0.15-0.6+
0.24-1.02+
0.071*
.49+
Brezonik et al. 1969
Vollenweider 1968
NAS 1978
Keeney 1976
Dillon & Rigler 1975
Macgregor & Keeney 1975
252
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give the relative abundances of nutrients and do help predict the kinds of
organisms expected. Mean concentration values are used in estimating lake
productivity which, in turn, will influence the response of the lake to
nutrient loading. Table 6.5 in the chapter on impact assessment relates
epilimnetic nutrient concentrations to lake productivity.
Nutrient Ratios
A biotic response is observed upon addition of a limiting factor to a
system. In lakes, evidence suggests that the most important nutrient factors
causing a shift from low to high productivity are phosphorus and nitrogen.
The nitrogen to phosphorus ratio may indicate that one of these nutrients is
limiting. Phosphorus may be limiting above an approximate N:P of 10:1 and
nitrogen limiting below this level (Chiandani and Vighi 1974; Lambou et al.
1976). Lakes exhibiting ratios near 10 may show no response to single
nutrient additions but often respond to additions of both. However, other
nutrients or physical factors may be limiting in other systems.
The optimal N:P ratio is species specific and different species within a
community may be limited by different nutrients simultaneously (Fitzgerald
1964; Rhee 1978). The comparison of the relative residence times of phosphorus
and nitrogen will indicate which nutrient is in greater demand, with the
nutrient that moves through the system faster being limiting (Vollenweider
1975).
In fast flowing detrital based systems nitrogen is the limiting factor
for decomposition of organic matter. Nitrogen or phosphorus may be in short
supply in autotrophic reaches, although both nutrients may be present in
excess if these reaches are eutrophic.
Oligotrophic lakes may be limited by any of several nutrients or elements.
However, since the metabolic demands of organisms require high nitrogen and
phosphorus relative to minor nutrients, either of these elements is more
likely to be limiting. In mesotrophic and moderately eutrophic lakes, phos-
phorus is often the limiting nutrient since nitrogen fixation can resupply
nitrogen losses. Eutrophic lakes may be nitrogen- or phosphorus-limited,
depending upon the amount of phosphorus released from sediments, rates of
denitrification and nitrogen fixation, metabolic activity of biota, and the
type of nutrient input to the lake. Marked nitrogen limitation was observed
associated with point-source pollution even while the main portion of the
water body was limited by phosphorus in large lakes and reservoirs examined
by the National Eutrophication Survey (NES)(Allum et al. 1972). With increas-
ing eutrophication, nitrogen metabolism often is speeded up more than phos-
phorus metabolism so that nitrogen may become the controlling factor
(Vollenweider 1975). The transition from phosphorus- to nitrogen-limitation
as eutrophication proceeds may result from increases in denitrification
rates.
The nutrient limiting a system also may be related to organic carbon
levels. Those systems which have a relative excess of carbon or are detrital
based systems (i.e., headwaters of streams, hypereutrophic lakes, and
estuaries) are more likely limited by nitrogen necessary for decomposition.
253
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Lake productivity, on the other hand, is most frequently limited by phosphorus
since algal carbon and nitrogen needs can be supplied from the atmosphere.
Having different optimal nutrient requirements limits species to particular
system types, trophic structures, or to a particular time in the seasonal
succession.
Interaction of Sediments and Nutrients
Nutrients are accumulated in sediments over time and can be released in
response to biological depletion of nutrients in the water column. It is
well known that the sediments act as a net sink for phosphorus and nitrogen.
Recently, however, the significance of sediments as a nutrient source has
been debated. A conceptual model of sediment-nutrient interactions is given
in Fig. 10.6. This figure illustrates the influence of suspended and bed load
sediment on growth and reproduction of biota and indicates regulation of
nutrient pools by sediments.
Sediment consists of organic and inorganic material produced by weather-
ing of inorganic matter and from decomposition of organisms. The inorganic
fraction consists of clay minerals, iron, and manganese oxides, carbonates,
and the parent material from which these minerals are derived. The organic
fraction consists of compounds ranging from simple amino acids through larger
compounds such as chitin to complex compounds such as humic substances (humic
and fulvic acids), as well as the remains of organisms such as bacteria,
plankton, or cast exoskeletons.
Physical and chemical, as well as biological processes, are involved in
nutrient transformations and exchanges between the sediments and water column
are discussed in the following sections.
Physical and Chemical Processes of Nutrient Movement
Two chemical processes are involved in the movement of nutrients into
and out of sediments. The process of adsorption-desorption can be a signifi-
cant nutrient source or sink, depending on chemical conditions, while diffusion
is a slower, bidirectional process relying on concentration differences. The
accumulation of nutrients in sediments is a result of the physical process of
sedimentation being greater than diffusion or mixing upward.
The phosphorus adsorbed onto sediments occurs mainly as apatite, organic
compounds, and in complexed form with such ions as Fe, Ca, Mg, and Al (Taylor
and Kuniski 1971; Williams et al. 1971; Emerson 1976). The reactive phos-
phorus, or that fraction potentially available to biota upon release from
sediments, often is referred to as labile phosphorus and amounts to less than
5 to 10 percent of sediment total P (Taylor 1967).
Ammonia produced from organic decomposition will accumulate in sediment
pore water. The extent to which ammonia is adsorbed dependsxon the amount of
clay or other inorganic colloids present to bind it, and on the concentrations
of other cations (Ca, Na, K, Mg) it might replace (Grim 1968; Armstrong and
Chesters 1964; Bremmer et al. 1967; Toetz 1970). Adsorption is fast, but
quantities absorbed may not be great (Brezonik and Fox 1976). When sediments
254
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ATMOSPHERE. WATERSHED.
< TRI8JMRY
DISSOLUTION
ION EXCHANGE
ION EXCHANGE
SETTLING
SUSPENDED
SEDIMENT.
RESUSRENSION
RESUSPENSION
SETTLING*
'ATMOSPHERE MTERSHED.
TRIBUTARf OL'TPUT
\'JC1.
CLII
LAND USE
VEGETATION
GEOLOGY
MATE
N:P.C RATIO
OXYGEN
REOOX
CATION RATIO
NUTRIENl UPTAKE
INORGANIC
NUTRIENTS
ION EXCHANGE
RESUSPENSION
DIFFUSION
RELEASE, LYSIS,
EXCRETION, RESPIRATION
DECOMPOSITION 4
ION EXCHANGE
ORGANIC
MATTER
BACTERIA
FUNGI
EXCRETION, LYSIS,
DEATH
ORGANIC UPTAKE
OETRITIVORY
FEEDING INHIBITION
SUBSTRATE TYPE
PARTICLE SIZE
OXYGEN
FLOW RATE
C:N RATIO
PARTICLE SIZE
OXYGEN
pH
SUBSTRATE TYPE
REPRODUCTION
GROWTH
SLDiMENTATION
RESUSPENSION
BIOTA
/NUTRIENT STIMULATION
/ TOXIC EFFECTS
fV / FEEDING INHIBITION
P BURIAL, SCOUR
]/\ HABITAT MODIFICATION
\ REPRODUCTIVE INHIBITION
\ OXYGEN DEPLETION
\SHAOIHG
REPRODUCTION
GROWTH
FEEDING
SETTLING
/WATERFLOW
/ WIND MIXING
N ' STRATIFICATION
I/ L OXYGEN
* \ REOOX
\BIOTIC STIRRING
v \ .
RESUSPENSION
BED LOAD
PERMANENT SEDIMENTS
MACROPHYTE ROOTS
Fig. 10.6.
Sediment-nutrient interactions at a coarse level of resolution.
Major biota, nutrient, and sediment pools are shown in compartments.
Lines indicate material flows, with the controls on these flows also
indicated. Single headed arrows are used when the opposite direc-
tions of flow are labelled.
255
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lack significant clay levels, or when available exchange sites are filled,
little sorbing occurs and the ammonia formed diffuses upward (Brezonik and
Fox 1976).
Sediments contain large quantities of nutrients which are potentially an
internal nutrient source. All lake sediments contain higher nutrient concen-
trations than the overlying water. The concentration of inorganic or organic
nutrients in the water column gives little indication of the amount present in
sediments and the two pools may differ by several orders or magnitude (Wetzel
1975). A mean value of total phosphorus in the sediments of 16 Wisconsin lakes
was 2550 mg/kg dry weight (Armstrong et al. 1971), although the range varied
from 730 to 7000 mg/kg dry weight. Lake sediments generally have from 50 to
200 kg N/ha in the upper 10 cm of sediment (Keeney 1976). The upper 4 cm of
sediment may serve as the immediate source of ammonia to overlying waters, but
as much as 16 cm of sediment may contribute ammonia to the water column
(Byrnes et al. 1972).
Release of nutrients from sediments is not only a function of nutrient
concentration, but also is dependent upon such environmental factors as redox
conditions and the presence of oxygen, various ions, pH, physical mixing, and
organic matter.
Redox and Oxygen Levels:
The oxidation-reduction status of sediments influences not only the
release but also the transformations of nutrients. Redox potential is usually
reported in terms of pE or Eh (millivolts, mV). At the sediment-water inter-
face Eh will range from +100 to +350 mV in the presence of oxygen (Turner and
Patrick 1968; Keeney 1973). Sediments may remain in a reduced condition even
if oxygen is present in the water column (Graetz et al. 1973). Sediments
become more reduced as the hypolimnion becomes anoxic, with Eh values ranging
from 0 to -250 mV (Keeney 1973). When oxygen becomes unavailable, alternate
electron acceptors are used. Nitrate is the first alternative electron acceptor
resulting in release of reduced nitrogen forms.
Whether or not anaerobic conditions in the hypolimnion result in a greater
nutrient release from sediments is currently debated. Following the studies
of Mortimer (1941, 1942), it generally was accepted that reducing conditions
in the sediments and in the hypolimnion caused release of adsorbed phosphorus
compounds from complexes. As long as an oxidized microzone at the sediment-
water interface is maintained, most of the phosphorus will be retained and
unavailable to biota. When oxygen depletion increases and the redox potential
is decreased, previously adsorbed phosphorus becomes free to move from the
sediments (Li et al. 1972; Lean and Charlton 1976).
In one recent study phosphorus was released from sediments under anaerobic
conditions but not under aerobic conditions (Fillos and Biswas 1976). However,
other studies contradict these observations indicating that phosphorus com-
pounds bound in sediments are not affected significantly by the presence or
absence of oxygen (Schindler et al. 1977). In another study phosphorus
release was slower under aerobic conditions than under anaerobic conditions
but rapid enough to play a role in the internal cycling of phosphorus (Lee
et al. 1977).
256
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Many studies also describe increased nitrogen release under anaerobic
conditions (Mortimer 1941; Graetz et al. 1973). However, in some lakes, the
release may not be different under different oxygen regimes or release may
even be greater under aerobic conditions (Austin and Lee 1973; Brezonik and
Fox 1976). Sediment bound ammonia is not a large source of nitrogen to the
water. Instead, most sediment nitrogen is organic and major exchanges are
biologically mediated. Under aerobic conditions, increased microbial assimila-
tion and increased nitrification might result in less ammonium release upward.
Observations of increased ammonium release, when the hypolimnion oxygen levels
are low, also may be a result of increased upward diffusion when high produc-
tivity depletes nutrients in the water.
The causes of nutrient release from sediments and its usefulness to biota
are not yet understood. Aquatic systems undergoing decreases in water column
oxygen are more likely to be productive systems with higher nutrient levels in
the sediments available for release upward. Therefore, nutrient release may
not be a function of aerobic versus anaerobic conditions, but might result
from increased decomposition rates. In addition, nutrients released from
sediments under anaerobic conditions may not be available to biota since the
thermocline may represent an impermeable barrier. To date most experiments
on this subject have been performed in the lab and may not simulate actual
conditions well. In situ experiments in a variety of aquatic systems are
needed to determine the influence of oxygen on release of nutrients.
Ions:
An exchange of nutrients between the sediments and the overlying water
will depend on the forms and charges of various ions present. The organic and
inorganic sediment fractions often are very reactive. Humic substances may
form complexes with di- and tri-valent cations, bind anions in ion exchange
reactions (e.g., PCty), and often are adsorbed strongly by clay surfaces. Clays
may exchange cations (Grim 1968; Malcom and Kennedy 1970), provide sites for
scavenging microbes, and may adsorb iron and manganese oxides. Iron and
manganese oxides also enter into cation and anion exchange reactions (Jenne 1968;
Malcolm and Kennedy 1970; Greenland 1971; Schnitzer and Kahn 1972; Paerl 1977).
Several factors controlling these reactions include: pH, pE, (or Eh), ionic
strength, cation exchange capacity, the type and form of ion being exchanged
or absorbed, and the particle size and composition of the reacting surface.
Inorganic phosphate occurs in forms of salts of orthophosphate consisting
of fluoro, oxy-, and hydroxy-phosphates of mainly Fe, Al, Ca, Mg, and Mn
(Levesque and Schnitzer 1967). Gessner (1939) showed that phosphate was
removed from solution after addition of calcium carbonate due to carbonate-
phosphate co-precipitation. A linear relationship was found between calcium
carbonate addition and phosphorus depletion in highly alkaline waters. The
precipitation of calcium phosphate as apatite is increased under high CaCO-j
levels (Emerson 1976). Although apatite is one of the least soluble phosphate
minerals in freshwater, partial dissociation of orthophosphate from apatite
crystals (enough to support some cultures of algae) has been observed (Smith
et al. 1978). Iron can complex with phosphorus under aerobic conditions.
When conditions become anoxic, phosphate-ferric iron is reduced to a phosphate-
ferrous iron complex which is more soluble, and phosphorus unbinds from the
257
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complex releasing phosphorus to the hypolimnion (Stumm and Morgan 1970). Iron
also may compete with ammonium for sites on clay complexes causing the release
of ammonium in iron-rich environments (Keeney 1976).
PH:
Due to the overriding influence of the redox system, most aquatic systems
show little seasonal pH shifts (Stumm and Morgan, 1970). However, pH shifts
have been noted in eutrophic lakes. For example, at spring overturn the
hypolimnetic waters of Lake Mendota are about pH 8, while during summer stra-
tification the pH is near 6.5 (Keeney 1976). Softwater systems may show a
greater fluctuation in pH over time due to the absence of a CaC02 buffering
system.
The role of pH in sediments in relation to phosphorus release is not
clear. The orthophosphate content of sediments does not appear to be affected
by pH in the neutral to slightly alkaline range (Kamp-Nielsen 1975; Lee et al.
1977). However, the pH of the sediment, when acidic, may stimulate phosphorus
release to the water (MacPherson et al. 1958).
During stratification, increases in the hydronium ion, which is an
effective competitor for exchange sites occupied by NH/j, may result in a
greater release of ammonium to the water.
Recently, investigations have been initiated which examine the influence
on water bodies of increased acidity in rainfall associated with cultural
activities. Natural buffering systems may be exceeded, particularly in soft-
water systems. As pH values decline below 6, detrimental effects on organisms
will be observed (Schindler 1979) and nutrient transformations may be altered.
Microbial nitrogen transformations occur at a more rapid rate in calcareous
sediments of hardwater lakes than in noncalcareous sediments from softwater
lakes. Additions of CaC03 to noncalcareous sediments increased rates of
ammonification, nitrification, and nitrogen fixation (Chen and Keeney 1973).
Lower amounts of ammonia were found in the interstitial water in acid sedi-
ments of a softwater lake (Keeney et al. 1970).
Mixing:
Mixing has been considered to be an important factor influencing nutrient
release from sediments. Most experiments demonstrating the importance of
mixing, however, have been performed in the lab. In situ levels of turbulence
as a result of wind action, underwater currents, gas bubbling, and stirring
by benthic organisms can only be estimated (Brezonik 1973; Petr 1977; Ryding
and Forsberg 1977). The degree of mixing also will depend on the sharpness
of the mud-water interface, the type of sediment, and water depth (Lee 1970).
In shallow lakes, mixing of sediments by wind or wave action or by turnover
can be significant in nutrient release to the water (Zicher et al. 1956).
Seasonal overturn may result in the release of some nutrients but not
others from the sediments to the water column. The nitrogen to phosphorus
ratio of nutrients released from the sediments in Lake Kinnert, Israel, was
71 to 1 (Serruya 1974). The sediments were acting as a source of nitrogen
258
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as a sink for phosphorus in this phosphorus limited lake.
Lab studies show that turbulence increases nutrient release at least
initially by release of interstitial pore water through suspension of sediment
particles (Brezonik and Fox 1976). Continued mixing might prevent a large
buildup of nutrients in pore water. Diffusion is a slow process which may
normally have little importance compared to mixing in releasing nutrients to
the water column, but diffusion may become a significant process during the
static condition encountered during stratification (Gahler 1969; Runnells 1969;
Stumm and Leckie 1971).
Organic Matter:
Organic matter can play an important role in the initial binding of
phosphorus (Harter 1969). Phosphate is adsorbed through an anion exchange
reaction, with phosphate ions replacing hydroxyl ions in the organic matter.
Until the adsorbed phosphorus is precipitated by iron or aluminum the sedi-
ments may be capable of releasing phosphorus from the anion exchange sites to
the overlying water. In a eutrophic condition, where sediments are normally
high in organic matter, phosphorus adsorbed to organic matter could influence
the nutrient status in the water. Organic matter can interfere with phos-
phorus precipitation as 033^04)2 by complexing with calcium and thus releas-
ing the phosphate (Levesque and Schnitzer 1967).
The level of organic matter present in sediments should influence quanti-
ties of inorganic nutrients released since decomposition of the organic matter
is the source of many of these nutrients. A distinct, short-term increase in
inorganic nitrogen released from lake sediments after detrital additions was
found in lab experiments (Brezonik and Fox 1976). It was hypothesized that
nutrients released from sediments arise from recently deposited detritus
rather than from older sediments. Presumably, recently deposited detritus
will have less time to become bound to sediments, will have proportionally
more biologically degradable substances, and will be physically closer to the
water-sediment interface where exchanges occur.
Biological Control of Nutrient Flux
Primary Producers - Algae:
Primary producers have been shown to upset the nutrient equilibrium
between sediments and water. Following the algal uptake of nutrients from
the water column, the system tends toward equilibrium by releasing nutrients
from the mud. The main source of phosphate for the production of phytoplank-
ton in an unfertilized pond was released from sediments (Hepher 1966). A
tenfold increase in the growth rate of Scenedesmus obliquus was observed when
it adsorbed phosphorus released from lake muds (Golterman et al. 1969).
Primary Producers - Macrophytes:
Macrophytes also play a role in the exchange of nutrients between sedi-
ments and water by acting as nutrient pumps and releasing nutrients from the
sediments into the overlying water (McRoy and Barsdate 1970; McRoy et al. 1972;
259
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McRoy and Goering 1974; Toetz 1974). Nutrients can be absorbed by either roots
or foilage depending on the relative concentrations of nutrients in the water
and sediments (Denny 1972). They may be translocated through the plant to the
roots and sediments from the overlying water or be translocated to the leaves
with some nutrient release into the water (Nichols and Keeney 1976; Twilley
et al. 1977). While growing, macrophytes have the ability to give off oxygen
and transmit nutrients to the water column. Upon death and decay they may
sink to sediments, carrying nutrients downward and creating a large oxygen
demand as they decay.
Bacteria:
Bacteria in anaerobic sediments contribute relatively little to the
phosphorus flux from water to sediments. Under aerobic conditions the trans-
port of phosphorus to the sediments by bacteria increases (Hayes 1955). Two
mechanisms are postulated by which phosphorus can be maintained in the water
column. First bacteria in the mud, upon decomposition, may accelerate release
of phosphate back to the water, Second, bacteria in the water column may
rapidly take up phosphate, preventing chemical absorption by mud. The bacteria
may convert phosphate into organic compounds by incorporating it into their
cells making it available at a later time. If bacterial numbers are high,
then the role of bacteria in phosphorus cycling in the overlying water may be
significant (Hayes and Phillips 1958).
Bacteria play a major role in nitrogen exchanges between the sediment and
water column. Most microbial transformations of nitrogen occur in the sedi-
ments or are influenced by sediment conditions, especially ammonification,
nitrification, and denitrification. Microbial components of sediments are
important not only in directly mediating transformations of nutrients, but
also indirectly in their ability to alter pH and oxygen concentrations, and to
produce gas (Brezonik 1973).
Higher Organisms:
The major roles of benthic organisms in nutrient exchanges at the sedi-
ment-water interface are mixing and aeration of sediments and detritivory.
The effectiveness of the sediments in retaining phosphorus under aerobic con-
ditions may be a result of mixing of sediments several centimeters deep by
benthic organisms which causes an increase in the oxidized microzone (Davis
et al. 1975; Schindler 1975). On the other hand, chironomid movement has
been shown to increase phosphate release to the water (Gallepp 1976). Mixing
by bottom feeding fish and aquatic insects also may occur. In addition,
insect emergence from the sediment may result in a loss of nutrients from the
system (Vallentyne 1952; Neame 1977). The role of insects in nutrient removal
may depend upon the concentration and forms of sediment nutrients, numbers of
insects, or the present trophic state of the water. Detritivores assimilate
organic matter thereby making nutrients available by passage through the
feeding webs.
10.2.3 Evidence of Nutrient Impact on Biota
In this section evidence of biotic response to external nutrient loading
260
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is examined. Studies of this type are important in understanding how cultural
activities may influence water quality. Presently, most of these impact
studies concentrate on responses of primary producers in lakes, although an
attempt was made to include impact studies in other system types and on higher
trophic levels.
Since impact studies rely on the ability to detect increased productivity
the methods used should be examined for their accuracy. Considerable spatial
variation in productivity is seen in large lakes (Sorokin 1959; Goldman 1960;
Goldman 1961), requiring sampling at several stations. There also may be
daily or seasonal fluctuations in limiting nutrients so that responses will
depend on the time of nutrient enrichment. In addition, transient and steady
state responses to nutrient additions may be different (Goldman and Carter
1965). Lab studies should be carefully scrutinized since results may have
only limited applicability to processes actually occurring in situ. Containers
placed in the water may exclude important exchanges between surrounding water
and the sediments. Whole system studies, although time consuming and expensive,
may provide important information that might be lost in smaller scale experi-
ments .
Impact of Nutrients jj^ Streams
Nutrient concentrations in streams are closely related to land use
practices (Omernik 1976, 1977). However, within a stream nutrient concentrations
and nutrients removed from the watershed vary over time with changes in flow
patterns. Particularly for small watersheds, greatest phosphorus export may
be associated with infrequent periods of high flow (Allum et al. 1977). There-
fore, the impact of nutrients in streams will not only depend upon watershed
activities but also will vary with different flow regimes within one stream.
Nutrients may not increase primary productivity in streams since stream
behavior may be more influenced by overriding physical factors than by nutri-
ent concentrations. Williams (1964) reported that physical factors may deter-
mine phytoplankton presence regardless of nutrient availability. Stream
characteristics that may influence primary productivity include current speed,
slope, depth, and the stream order.
A stream system in Iowa with high initial phosphate and nitrate levels
did not respond to nitrogen and phosphorus input (Kilkus et al. 1975). Inor-
ganic phosphorus and nitrogen levels were high and algal populations were
regulated by flow, drainage area, and temperature. During low flow periods,
high chlorophyll values were found. It was concluded that neither phosphorus
nor nitrogen were limiting.
In streams diurnal fluctuations of oxygen correlated well with estimated
nutrient loadings and trophic conditions in three rivers in Michigan (the
Jordan with a relatively low nutrient content; the more enriched Au Sable;
and the highly enriched Red Cedar) (Ball et al. 1973). Higher diurnal oxygen
variations occurred in the more enriched river systems. Phosphorus tissue
content of macrophytes was related to the concentration of nutrients in the
water, but the standing crop of plants was controlled by stream morphology
(configuration, flow, and turbidity) rather than levels of nutrient loading.
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In autotrophic reaches of low nutrient streams addition of nutrients may
have a stimulatory effect, Benthic algal biomass increased in Carnation Creek,
Vancouver Island, when phosphorus was added with or without added nitrogen.
Nitrate addition alone had little effect on algal growth (Stockner and Short-
reed 1978).
Frequently, nutrient additions result in enhanced productivity due to an
interaction of nutrients. When nutrient interactions occur, the system
responds most to two or more nutrients added together rather than to additions
of a single nutrient. The N:P ratio can shift frequently and intermediate
values between phosphorus limitation and nitrogen limitation are encountered
for many species. Several species in the natural assemblage may respond to
added nitrogen while others respond to added phosphorus. Nitrogen and phos-
phorus interacted to influence biotic response in streams in the Midlands of
Great Britain. In situ experiments in various river waters showed that the
highest nitrogen level increased growth at the lowest phosphorus level. A
positive correlation between the mean annual dry weight of Cladophora and the
mean annual phosphorus concentration was seen. No significant correlation
between nitrogen and dry weight was observed (Pitcairn and Hawkes 1973).
Impact of_ Nutrients jr^ Reservoirs
A few examples of rapid eutrophication in reservoirs are documented,
including impoundments in Arkansas (Geerhart 1969), North Dakota (Peterka 1970),
Illinois (Wang and Evans 1970), and Oklahoma (Toetz 1972). Since nutrient
loading levels generally are high, reservoirs may not respond to nutrient
additions. Orthophosphate, total phosphate, nitrate, and ammonia levels were
not correlated with chlorophyll a^ concentrations in eastern Nebraska reservoirs
undergoing eutrophication. These nutrients may not be limiting because of
rapid recycling. Physical factors such as temperature, turbidity, and day of
the year appeared to correlate most highly with chlorophyll ^concentrations
(Schwartzkopf and Hergenrader 1978).
On the other hand, some reservoirs receive nutrient loading equivalent
to that which should produce a eutrophic system, but due to high flushing or
sedimentation rates they remain oligomesotrophic (Bachman and Canfield 1979;
Lind 1979).
Impacts of Nutrients JJT_ Lakes
Based upon the literature reviewed, the major influence of nutrients is a
stimulation of primary productivity in lakes. The degree of impact of nutrient
addition has been related to initial nutrient concentrations. Therefore, the
evidence for impacts is divided into sections based on trophic status.
Oligotrophic Waters:
Oligotrophic waters generally show high sensitivity to nutrient loading.
Since they have low nutrient concentrations, factors limiting productivity may
change frequently with minor changes in loading or physical conditions. Most
nutrients have a short residence time in the water column, and they are flushed
from the system or are lost to sediments. Sediments may not contribute
262
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greatly to epilimnetic nutrients, because of extreme depth, because the oxi-
dized hypolimm'on acts as a barrier, or because of little decomposition. Dia-
toms are among the dominant phytoplankton at low nutrient concentrations. At
death, diatoms sink rapidly, removing nutrients from the epilimnion. The only
significant recycling of nutrients is from plant lysis and excretion by consu-
mers. Consumer numbers will be low, so this source of nutrients will be mini-
mal.
Many oligotrophic systems appear to be phosphorus limited. Data have been
compiled relating trophic state to phosphorus loading for 15 oligotrophic lakes.
Phosphorus limitation for these lakes, located mainly in the continental United
States, was found through the use of algal assays and interpretation of N:P
concentration ratios (Yeasted and Morel 1978). Actual phosphorus loading to
an oligotrophic lake in the Experimental Lakes Area (Lake 227) revealed that
phosphorus caused a positive growth response in phytoplankton. The addition
of nitrogen, alone, did not result in any increase in algal standing crop
(Schindler et al. 1973).
Nitrogen may be the primary limiting nutrient in other oligotrophic waters.
Phytoplankton growth, as measured by '4C uptake, was stimulated in all treat-
ments in which nitrate was added to Lake Tahoe, California (Goldman and Carter
1965; Goldman and Armstrong 1969). Phosphorus additions did not stimulate
growth even when added with nitrogen.
Nutrients frequently interact in stimulating productivity in oligotrophic
lakes. For example, phytoplankton in Mirror Lake, New Hampshire, was stimulated
by additions of nitrogen and phosphorus together (Gerhart 1975).
An increase in photosynthesis and in phytoplankton biomass was found
when nitrogen and phosphorus were added to experimental ponds (Mclntire and
Bond 1962). Diatoms were the dominant phytoplankton in the absence of enrich-
ment. Codominance of diatoms and desmids resulted in nitrate enriched ponds.
With nitrate and phosphorus enrichment, flagellates were most important. Zoo-
plankton densities followed fluctuations in phytoplankton abundance. Crusta-
ceans and rotifers, especially, became abundant in enriched ponds. Following
a dense algal bloom and death in a highly enriched pond, organic food was
available for larval midges (Tendipedidae), a few horsehair worms (Gordius),
and dragonfly naiads (Libellulidae). This pond supported the highest benthic
biomass with the total dry weight of two samples being about 15 times that of
an unenriched pond.
Individual additions of nutrients to oligotrophic Eagle Lake, California,
produced little, if any, response; therefore, all essential nutrients except one
were added in each culture (Maslin and Boles 1978). The shallow north basin
was limited most severely by iron and phosphorus, which were tied up in
oxidized sediments. The anoxic conditions in the south basin resulted in a
regeneration of these nutrients so that nitrogen was more limiting. Chloro-
phyll increased in both basins in the presence of added nitrogen, phosphorus,
iron, and sulfur. Nitrogen and phosphorus were most limiting; sulfur and iron
were also limiting, but the order of importance was opposite in the two basins.
When one of these elements was removed, total growth of phytoplankton was
reduced to less than 30 percent. This study also demonstrated the importance
263
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of physical characteristics such as mean depth and flow rate in determining
the most limiting nutrient. It showed variations in response in a lake with
watersheds exhibiting differences in climate, topography, and volume.
Nitrogen, phosphorus, and NTA (a chelator) were added to algal communities
from Lake 240 (Experimental Lake Area, Ontario) and from Katherine Lake,
Manitoba (Stockner and Evans 1974). Phosphorus stimulated growth more than
nitrogen and nitrogen more than NTA in Lake 240. The addition of NTA generally
did not function in a catalytic capacity as might be expected. Lake 240 had
an initial N:P ratio of 18:1 as measured by cellular contents of periphyton,
and might be expected to respond mainly to phosphorus. However, an interaction
was observed whereby median concentrations of both nitrogen and phosphorus
yielded greatest growth. Lake Katherine had an N:P ratio of 9:1 initially and
might be expected to show a greater response to nitrogen additions although
added nutrients of any kind generally inhibited growth in Lake Katherine. The
species present were most likely species that have optimal growth at low
nutrient concentrations, and neither nutrient may have been limiting at an
N:P of 9:1.
Other compounds including silica (Schelske et al. 1972, 1975), dissolved
organic matter (Wetzel 1966a), EDTA, NTA, and other chelators (Stoermer et al.
1978) may interact with nitrogen or phosphorus and play a significant role in
regulating productivity. In oligotrophic lakes all over the world (Africa,
Alaska, California, New Zealand, and Anarctica), 23 of the 28 lakes observed
were deficient in at least one trace element (Goldman 1971). Combinations of
nutrients and trace elements were often necessary to stimulate production.
Several lakes were deficient in molybdenum, which was needed by nitrogen
fixers.
Nutrients added alone to the hardwater marl lakes of Indiana had little
effect and became rapidly unavailable (Wetzel 1966b). These lakes are charac-
terized by low productivity, high pH, and an excess of divalent cations and
carbonates. However with the addition of organic matter and nutrients, stimu-
lation of phytoplankton was observed. These organic compounds act as chelators,
increasing the availability of nutrients. A significant stimulation of phyto-
plankton also was seen in less productive Crooked Lake with the addition of
organic chelators. In the more productive Little Crooked Lake no stimulation
of phytoplankton was observed.
A large increase in phytoplankton productivity (492 percent) resulted
from addition of nitrogen, phosphorus, and EDTA in Lake Crystal, Michigan
(Jordan and Bender 1973). Seven of 15 species examined responded to nutrient
additions. Species composition also changed with enrichment.
Oligotrophic systems, especially, may shift from one limiting nutrient
to another seasonally, since all nutrient levels are low and the ratios may
change frequently. In three oligotrophic Alaskan lakes, a nitrogen deficiency
occurred only during the summer as measured by nitrate stimulation of '^C
uptake by lake phytoplankton in situ, and in experimental cultures (Goldman
1960).
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Mesotrophic Waters:
In mesotrophic lakes, anoxic conditions may be encountered seasonally.
Mesotrophic systems may be unstable since additional nutrient contributions
from external sources and from internal cycling can act to stimulate produc-
tivity and rapidly accelerate the process of eutrophication. On the other
hand, some systems may be maintained at an intermediate level of productivity.
For example, softwater systems generally are low in productivity and may not
respond as quickly to loading since bacterial activity may be slower at low
pH (Chen et al. 1972a, 1972b; Byrnes et al. 1972). The cold conditions of
arctic lakes can result in less year round bacterial activity and slow down
eutrophication. High flushing rates also will dilute nutrient concentrations,
decreasing productivity. However, many temperate mesotrophic systems will
tend to become eutrophic as a result of internal nutrient sources, even if
surface nutrient loading is diminished.
Mesotrophic lakes generally are more limited by phosphorus than nitrogen.
As phytoplankton species change and numbers increase, more nutrients are
released into the system through cell lysing. Zooplankton numbers may accumu-
late in response to increased numbers of phytoplankton and add to the regen-
eration of epilimnetic nutrients by excretion. High phosphorus levels allow
nitrogen fixing blue-green algae to become established. Blue-greens may
become dominant by secretion of substances which inhibit diatoms (Keating 1978).
Nitrogen fixation may add substantially to the nitrogen loading, preventing
nitrogen limitation in the system. Higher organic carbon levels associated
with the increased productivity also stimulate bacterial nitrogen fixation.
In Lake Washington, an increase in phosphorus favored production of blue-
greens, with green algae being less favored and diatoms least abundant (Welch
et al. 1975). Since receiving sewage, Lake Washington showed symptoms of
eutrophication, e.g., increased nutrient concentrations; increased phytoplank-
ton and zooplankton biomass, increased chlorophyll ^concentrations in the
epilimnion, decreased transparency, decreased oxygen concentrations in the
hypolimnion, and a shift from diatom and dinoflagellate dominance to blue-
green dominance (Edmondson et al. 1956; Edmondson 1961). Diversion of the
sewage resulted in a decrease in concentrations of phosphorus by 72 percent
and in concentrations of nitrogen by 20 percent (Edmondson 1966, 1969, 1970).
Two neighboring arctic lakes, oligotrophic Char and mesotrophic Meretta
Lake, were compared by Schindler et al. (1974). Standing crops of phytoplank-
ton were 10-100 times higher in Meretta Lake than in Char Lake, and differences
in species composition were noted. Phosphorus addition was required to
initiate a growth response in Char Lake, although additions of both nitrogen
and phosphorus resulted in the largest responses, indicating nutrient inter-
action. The dominant phytoplankton changed to Peridineae, the same group
dominating Lake Meretta. Limnocalanus macrurus disappeared from Meretta Lake
and has not been replaced by another zooplankter. The Arctic Char (Salvelinus
alpinus) also might be having difficulties surviving in Lake Meretta"Tfie
eggs or fry which over-winter on the bottom are dying as a result of altered
oxygen, food, or sediment conditions.
The upper Great Lakes vary in trophic state from oligotrophic to
265
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eutrophic, and trophic conditions also vary within the lakes. Near cities or
nutrient-rich rivers, conditions may be eutrophic while the interior of the
lake may be oligotrophic. Differences in species and abundance of diatoms as
well as differences in nutrient and pigment concentrations are observed when
comparing inshore and offshore waters of Lake Michigan (Holland and Beeton
1972). Greater numbers of diatoms are seen inshore in waters that are nutrient
rich.
Phosphorus additions have been shown to increase chlorophyll concentration
and the rate of carbon fixation in phytoplankton in Lake Michigan (Schelske
et al. 1975). Also, in Lake Michigan, phytoplankton response varied for
species within the same division. In the Bacillariophyta, growth rates of
Nitzschia and Fragilaria increased with addition of nitrate at low and high
levels of phosphorus.Tn Stephanpdiscus and Nayicula, high nitrate levels
caused inhibition of growth, which was magnified at high phosphorus levels
(Stoermer et al. 1978).
Nitrate concentrations generally are high in the upper Great Lakes which
appear to be limited by phosphorus (Schelske and Roth 1973; Schelske et al.
1974). Although nutrient enrichment experiments indicated highest chlorophyll
a^ production with phosphorus enrichment, some indications of phosphorus and
nitrogen interactions were observed (Schelske et al. 1974). Nitrogen enrich-
ment in Lake Michigan had an effect at the species level even though no effect
on total l^C uptake was observed (Stoermer et al. 1978). A shift from blue-
green to diatom dominance occurred.
Crustacean zooplankton in the Great Lakes were examined with regard to
the trophic status of each lake (Fatalas 1972; Watson 1974). A decreased
significance of calanoids and an increased predominance of cyclopoids and
cladocerans were seen as a general trend from oligotrophic Lake Superior to
eutrophic Lake Erie. The average crustacean abundance was related to temper-
ature, chlorophyll a_ concentrations, and phosphorus loading. Although Lake
Erie had an increased biomass of zooplankton, larger organisms were observed
in Lakes Superior and Huron, Increased numbers of oligochaetes in the benthos
of the Great Lakes occurred under more eutrophic conditions (Cook and Johnson
1974). In addition, large populations of tubificid worms in highly polluted
areas were seen.
Eutrophic Waters:
Shallow systems rapidly respond to increased nutrient loading by becoming
eutrophic. Even large lakes can become eutrophic as they continue to receive
nutrients. Once eutrophic, internal nutrient sources from sediments and biota
may maintain eutrophic conditions in freshwater systems, even with the absence
of significant external loading.
Many measurements of algal response indicate that phosphorus may be limit-
ing in many enriched waters. In several lakes the chlorophyll ^concentration
was measured along with spring total phosphorus concentration (Sakamoto 1966;
Dillon and Rigler 1974; Chapra and Tarapchak 1976). A significant correlation
(r = 0.93) was determined for predicting the average summer chlorophyll a
concentration based on spring total phosphorus. In four Iowa lakes a reduction
266
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in annual phosphorus input resulted in a smaller algal bloom (Jones and Bachman
1975). All lakes had N:P ratios ranging from 13:1 to 30:1, suggesting phos-
phorus limiting conditions.
Eutrophic waters are frequently nitrogen limited. Nitrogen fixation is a
slow process (McCarty 1970) and may not contribute sufficient nitrogen. Losses
of nitrogen through denitrification also may be significant. In addition,
phosphorus loading may exceed nitrogen loading, especially near urban areas.
Sediment also may contribute phosphorus, particularly with increased loading
of organic substances which may act as chelators, increasing the availability
of phosphorus (Jordan and Bender 1973).
Growth of Microcystis, collected from blooms in two eutrophic Wisconsin
lakes, was nitrogen limited, as determined by known optimal growth require-
ments (Gerloff and Skoog 1957). Nitrate stimulation of phytoplankton also was
seen in eutrophic Green Lake, Seattle, Washington. Stimulation was observed
in blue-greens but not in green algae or diatoms (Welch et al. 1972).
Lakes receiving wastewater may become limited by nitrogen since the N:P
ratios of wastewater are frequently low. Nitrogen limited algal growth in
five locations receiving wastewaters along the northeastern U.S. coast
(Goldman 1976). The N:P ratios in the wastewater-seawater mixtures were
between 4 and 12. Enrichment with phosphorus had no effect on algal growth,
but nitrogen additions stimulated growth. However, coastal waters are fre-
quently limited by nitrogen when they do not receive wastes.
Nutrient addition may indirectly influence higher trophic levels under
eutrophic conditions. Partial or complete anoxic conditions resulting from
decomposition of heavy algal blooms led to subsequent summer fish kills in
southwestern Manitoba (Barica 1975).
There are many examples of culturally eutrophied systems which show
changes in productivity and shifts in phytoplankton, fish, zooplankton, and
benthic species due to sewage addition (Hasler 1947; Paloumpis and Starrett
1960; O'Brien and Denoyelles 1976; Caster!in and Reynolds 1977). Sewage
effluent added to a small lake (Grasmere) in the English Lake District
resulted in a change from a mesotrophic lake to a eutrophic lake (Hall et al.
1978). The specific nutrient or nutrients influencing the system are not
always identified. The addition of fertilizer containing nitrogen, phosphorus,
and potassium to experimental eutrophic ponds resulted in increased phyto-
plankton productivity (O'Brien and Denoyelles 1976). A direct relationship
emerged between fertilizer level and chlorophyll admeasurements.
In the National Eutrophication Survey from 1972 to 1975 over 800 lakes
impacted by sewage treatment plant outfalls were studied. The phytoplankton
in several of these lakes were examined using indices such as Nyqaard's Trophic
State (Nygaard 1949) and Palmer's Organic Pollution (Palmer 1969), as well as
diversity and abundance indices to determine relationships between algal
characteristics and trophic status (Hilgert et al. 1977; F. A. Morris et al.
1977; M. -K. Morris et al. 1977, 1978a, 1978b; Taylor 1977; Williams et al.
1977, 1978; Hern et al. 1978). Generally, Cyanophyta, Euglenophyta, centric
diatoms, and some chlorococcales were associated with eutrophic conditions,
267
-------
while desmids and pennate diatoms were found only in oligotrophic waters.
Decreased diversity and evenness also were associated with eutrophic conditions.
Nutrient-algal relationships varied with season in Lake Lillinonah, Con-
necticut (EPA 1975). Growth of Selenastrum was stimulated by nitrogen
additions in July and phosphorus additions in August, while blue-green algal
growth was stimulated by phosphorus additions throughout the season, when
phosphorus addition was reduced, biomass of blue-green algae was reduced
correspondingly.
Many interacting factors may be working together to influence a system's
response to nutrient addition. Factors such as chelators or physical param-
eters such as basin morphometry may influence the role of the primary limit-
ing element (Mackereth 1953; Hutchinson 1957; Vallentyne 1957; Bninska et al.
1976). To obtain the most accurate account of the response, long term, whole
lake studies are critical. Lakes in the Experimental Lakes Area (ELA) were
fertilized with additions of phosphorus, nitrogen, and carbon over a period
of years in order to observe biotic response to increased eutrophication
(Schindler and co-workers 1971, 1973, 1975, 1977). Experiments demonstrated
that carbon and nitrogen deficiencies of algae were corrected for by diffusion
of atmospheric carbon dioxide into the water or by nitrogen fixation by blue-
green algae. Even if phosphorus input was high, phytoplankton growth over
time became proportional to phosphorus concentration. Hypolimnetic micro-
plankton and sediments were the most efficient in rapidly removing phosphorus
from the water suggesting that nutrient diversion to the hypolimnion of the
lake may have a minimal effect in increasing algal blooms. During the six
years of fertilization, input-output data indicated that the majority of
phosphorus and nitrogen added was accumulated in the sediments. Even when
hypolimnetic waters became anoxic, no net return of phosphorus was observed
from the sediments to the water. Further whole lake studies are essential to
the understanding of the nutrient dynamics in freshwaters.
10.2.4 Regionalization of Impacts
The National Eutrophication Survey was an important step in gaining
nationwide baseline information on nutrient conditions in streams, lakes, and
reservoirs across the country. However, the information obtained has some
weaknesses for management use.
Nationwide patterns of nitrogen and phosphorus concentrations in streams
were presented and linked to watershed activities (Omernik 1976, 1977). The
stream data were collected from watersheds having only nonpoint inputs. Infor-
mation was not obtained for streams impacted by point sources and no correla-
tions were made between productivity levels and nutrient concentrations.
Information appears to be lacking on any influence the various concentrations
have on biota.
The data collected on lakes and reservoirs was obtained only from partic-
ular system types. Selection of study sites was limited to large systems
impacted by sewage treatment plant outfalls and with mean hydraulic retention
times of at least 30 days (Allurn et al. 1977). Correlations between trophic
state and phytoplankton species diversity and abundance were obtained for
268
-------
several lakes, although regional comparisons were not made. Trophic state
classifications have been compared to the predictive models based on phos-
phorus loading for 39 eastern, mostly eutrophic, lakes (Hern et al. 1978).
Disagreements were found of 14, 18, and 25 percent, respectively, for the
Dillon (1975), Larsen and Mercier (1976), and Vollenweider (1975) models
(discussed in section 10.3.1). These models should be applied to western lakes
and impoundments and to lakes of other sizes and trophic classifications to
determine how well the models predict whole system response. The situations
where the models do not predict well should be examined to find an alternative
model, such as a nitrogen loading model for nitrogen limited systems, which
might predict response better.
The data obtained for streams should be compared with that obtained for
lakes and impoundments to investigate possible relationships. An integration
of nutrient concentration data with impacts on biota, including higher trophic
levels, also needs to be done. Then decisions can be made for management,
selecting either one system nationwide or using regional criteria; choosing
physical and chemical measurements or biotic indices; and managing for system
properties or for particular species of interest.
The examination of the literature on the impact of nutrient additions on
biota reveals that data exist only for a few regions of the country. Most of
the information available comes from the Northeast, Midwest, and Northwest.
Even within these regions sufficient data are available for only a few bodies
of water.
Although the various trophic categories may be found in every region,
some regional trends may exist. Identification of these trends may be valuable
for management procedures. As a result of this literature review, generaliza-
tions may be made. Most of the oligotrophic systems studied were either large,
deep lakes or were hardwater systems. They were located near the Great Lakes
regions of the country or in California. As expected, a variety of situations
were observed. Depending upon nutrient ratios, a single nutrient may be limit-
ing or the addition of several nutrients together may be required for stimu-
lation of growth.
Few studies on mesotrophic systems were reported, perhaps because the
mesotrophic condition is less stable and therefore less frequently observed.
The mesotrophic condition was generally observed in a narrow area within a
larger water body such as in the Great Lakes. In these studies phosphorus
was the major limiting nutrient.
Studies on eutrophic systems were found for several regions of the country.
Some lakes were limited by phosphorus and others by nitrogen, with the nutrient
limiting a particular system being a function of local factors. The reservoirs
and streams studied in the Midwest did not respond to additions of either
phosphorus or nitrogen. One study on Michigan streams (Ball et al. 1973) of
each trophic category revealed that plant standing crop was regulated by
stream morphology rather than by nutrient loading.
269
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10.3 PREDICTIONS OF BIOTIC RESPONSE TO IMPACTS
10.3.1 Models
Nutrient models are an important tool in predicting behavior following
nutrient addition. Several nutrient mass balance budgets for various lakes
and streams have been calculated taking into account the retention coefficient,
flushing rate, mean depth, and areal loading (Schindler et al. 1971; Patalas
1972; Imboden 1974; Dillon 1974, 1975; Dillon and Rigler 1975; Kirschner 1975;
Larsen and Mercier 1975, 1976; Snodgrass and O'Melia 1975; Vollenweider 1975;
Eisenreich et al. 1977). These models are useful in comparing aquatic respon-
ses over a large number of systems.
Permissible and dangerous loading levels were originally established on
an areal basis as a function of mean depth after examination of 30 lakes in
Europe and North America (Vollenweider 1968). Performing similar analyses in
the United States, specific critical loading levels separating oligotrophic
and eutrophic waters were set at 0.2 - 0.5 g total P/m2/yr and 5 - 10 g total
N/m2/yr (Bartsch 1972). However, not only depth but geomorphological factors
confound simple relationships between loading, concentration, and algal pro-
duction (Vollenweider 1976). Therefore, the loading graph for phosphorus was
modified by plotting loading (L) versus mean depth (z) divided by hydraulic
residence time (Tw), the mean residence time of water (Fig. 10.7) This
function predicts the trophic state of the water based on loading rates in
phosphorus limited lakes. The hydraulic residence time integrates a number
of limnological processes and significantly correlates with trophic state,
although the causal relationships are not readily identifiable, A graph of
this type for nitrogen was not derived, since relationships between nitrogen
loading and trophic state are less clearly defined (NAS 1978), Figure 10.8
plots nitrogen loading as a function of mean depth only. Prediction of the'
trophic state in nitrogen or nonphosphorus limited lakes may not be related
to residence time, and a predictor of the response in these systems needs to
be developed.
However, while these models adequately employ loading and geomorphomen-
trical conditions to determine the system response to nutrient loading, they
ignore the internal biotic cycling occurring within the system. The impor-
tance of internal nutrient dynamics, especially in eutrophic lakes with heavy
sediment nutrient loads, has been stressed (Shapiro et al. 1975). A model
that incorporates biological dynamics and has been validated in several
European lakes is MS. CLEANER (Park et al. 1978). Although this model is
expensive to use and requires considerable data input, application of this
model to a variety of North American lakes may increase the understanding of
system response.
A model based on physical processes was developed for predicting nutrient
losses from watersheds to streams for various types of watersheds (Nan-Hsiung
Ho 1978). This model is useful for indicating how nutrient inputs vary but
does not include measurements of biotic impact. A model of PO/j-P sinks and
sources in a river in Japan has been developed which takes into account not
only the usual physical factors such as diffusion and flow, but also includes
biological factors such as the role algae play in taking up and releasing
270
-------
gTP/m2-y
10-
*EUTROPHIC'
Non - acceptable
9 loading
0.1
L'O-.SO
Lo-,10
Acceptable
loading
.^<'° ° °o
o«
O 0°
• o o
O
0.01
"OUGOTROPHfC*
• eutrophic
• mesotrophtc
o oligotrophic
0.1
1.0
•n—
10
•i i
Fig. 10,7. Correlations of phosphorus loading levels with trophic status
(From Vollenweider 1976.)
271
-------
10.0
„*• 5'°
I
LU
CC
(3
? 2.0
O
z
LU
o
o
cc.
1.0
LU 0.5
0.2
Eutrophic Lakes
Oligotrophic Lake
I
10 20
MEAN DEPTH, m
50
100
Fig. 10.8. Nitrogen loading related to trophic state.
on Vollenweider 1968.)
(From NAS 1978 based
272
-------
POa-P in the river bed and in the flowing water (Aiba and (Make 1977). Stream
modelling, however, has not received adequate consideration in relation to
nutrients. This type of model is lacking due to problems in determining where
and how much loading occurs (sources may be diffuse), problems in relating
nutrient concentrations to impacts on biota, problems in sampling due to the
"patchy" nature of streams, or because nutrients are not limiting in many
streams.
For this report conceptual models have been developed indicating the
major phosphorus and nitrogen flows through all trophic levels and including
the controls on these flows (Fig. 10.9, 10.10). Figure 10.11 combines both
nutrient flows at a coarse level to indicate the nutrient-biotic interactions
that may occur in a system. Since the models are conceptual, they can be
applied to various system types (lakes, streams, or reservoirs) by modifica-
tion of flow rates and depth. However, a conceptual model of this type may
have limited applications since it lacks quantification of flows and may be
too cumbersome to use efficiently in predicting response for any type of
system.
10.3.2 The Standard Aquatic Response
Although each aquatic system is unique, an attempt has been made to
describe a standard response to nutrient addition based on the inputs, outputs,
and the initial state of the system.
In an oligotrophic system the paths of most significant nutrient flows
are indicated by number 1 in Figure 10.12. These flows are of relatively
equal importance. As a system becomes more productive, flows indicated by
number 1 increase, and those flows represented by number 2 may become more
important. As long as loading is not excessive, an oligotrophic system is
maintained. Most nutrients will be lost to sediments and, little upward move-
ment of nutrients occurs. Biotic recycling in the epilimnion is important in
maintaining nutrients in the water column. With continued nutrient inputs,
productivity increases, and the species composition of phytoplankton changes
(diatoms to greens). If productivity is high, anoxic conditions may be
encountered seasonally, indicative of a mesotrophic system. Many mesotrophic
systems may tend to become eutrophic rapidly, even if surface nutrient loading
is not high, due to the positive feedback from biotic cycling and from sedi-
ments. With high epilimnetic nutrient concentrations and high levels of
productivity, nitrogen availability may decrease relative to phosphorus.
Nitrogen fixation may then become important as a supplemental source of nitro-
gen. Once eutrophic, systems may be characterized by particularly high rates
of some nutrient transformations, such as denitrification, which contributes
to nitrogen limitation. Mesotrophic systems may rapidly become eutrophic as
anoxic conditions prevail and as flows 1 and 2 increase.
Changes in primary productivity have profound influences on higher biota.
As primary production rises, a shift in the dominant phytoplankton species
may be seen (greens to blue-greens). A species shift to blue-greens will
usually produce an undesirable food source for zooplankton, subsequently
causing a decline in these organisms. Bottom fauna may be replaced by tubi-
ficid worms. In shallow systems where littoral areas are significant,
273
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D
Ftw un
Mfcmntiw
wme
LAUD ura
•MM QICTM
ROCK TYM
WATC4SNCD ( TNIMJTAJIV OUTPUT
MOUND WATKM INWT
3ROUNO W4TCH OUTPUT
INOROANIC
PHOSPHORUS
oecaumiriM
t>
COilUtATIOM
w»Tnm^t ^
«nm«ME
uxnxua.
,«enviTT
.COMM.ATIOH, UTTUW
ORGANIC
DISSOLVED
PHOSPHORUS
•ITCTIKO
BIOTA
U«HT
WfttN
Ttuniurvm
MOOX
MMM Hvmntim
OWAWC HATTtR
»ARTICULATE
PHOSPHORUS
•ACTCRIA
FUNOI
MATH
jjiarmi
fCTTUW
amnoi
>«T» fLOW
MXTICLC tilt
AuTI
/am
/ win
•c* o
OXVUN
NUTMCNT
koirm
UttlHNt
SCDIMKNT
PHOSPHORUS
Fig. 10.9. Phosphorus flows and interactions in aquatic systems. Major bitftic
and nutrient pools are shown in compartments. Lines indicate
material flows, with the controls on these flows also indicated.
Single headed arrows are used when the opposite directions of flow
are labelled.
274
-------
WIND
PRECIPITATION
FLOW
FLUSHING RATE
LAND USE
DEPTH
WATERSHED AREA
LOCAL GEOLOBY
CLIMATE
WATERIMED INPUT'
ATMOSPHERE
N20
OEMITRiriCATIOH,
gOENITRIFICATION
'RELEASE
FROM SEDIMENT
N2
FIXATION
BLUE-OREEN ALGAE'
BACTERIA
AVAILABLE N
OXYGEN
PHOSPHORUS;
CARBON DIOXIDE/
RELEASE FROM
, SEDIMENT
SEDIMENTATION
WATERSHED*
OUTPU'
OBOUMDWATPt
GEOLOGY
WATER LEVEL!
GROUMDWATER..
ATMOSPHERE.
OXYGEN
pH
TEMPERATURE
OTHER N FORMS
k ASSIMILATION
(SORPTION RELEASE
ASSMILATORY'
REDUCTION
f OXYGEN
LIGHT
BACTERIA
TEMPERATURE
pH
L ORGANIC
V MATERIAL
\>
f BACTERIAL
NUMBERS
OXYGEN
PH
. ORGANIC
k MATTER
OXYGEN'
ORGANIC
MATTER
OTHER N
NITRIFICATION
•ICATIOM
N FORMS
NUTRIENT PRE-
CONDITIONING
. OXYGEN/
CARBON DIOXIDE
LIGHT,
'OTHER N FORMS
OXYGEN
ORGANIC HATTER
TEMPERATURE
'BACTERIAL NUMBERS
pH
OXYOEN
.TEMPERATURE
SEOWENTATION. DIFFUSION
TO SEDIMENTS
ASSIMILATED
NITROGEN
(BIOTIC)
BIOTIC UPTAKE'
DETRITIVORY
SYSTEMS > /[
N
OTHER
FORMS
SECRETION, DEATH
EXCRETION
ORGANIC
N
DISSOLVED
•ARTICULATE
BACTERIA
FUNGI
/OXYGENI
'TURBULENCE
WATER FLOW
ORGANIC MATERIAL
NUTRIENT PUMPING
DEPTH
.BIOTIC STIRRING
RCSUSPENSION
DIFFUSION FROM SEDIMENTS
SEDIMENT
N
Fig. 10.10.
Nitrogen flows and interactions in aquatic systems. Major biotic
and nutrient pools are shown in compartments. Solid lines indicate
material flows, with the controls on these flows also indicated.
Dotted lines represent possible directions of flow. Single headed
arrows are used when the opposite directions of flow are. labelled.
275
-------
WATERSHED,
ATMOSPHERE,
GROUND WATER,
TRIIUTARY INPUT
D
TC SUSPENSION
WkTERSHED,
ATMOSPHERE,
GROUND WATER,
TRIBUTARY OUTPUT
FLANO USE
VEGETATION
CLIMATE
GEOMORPHOMETRY
PRECIPITATION
k WATER FLOW
INORGANIC
NITROGEN
PHOSPHORUS
DECOMPOSITION'
ION EXCHANGE
N:P RATIO!
OXYGEN
WATER FLOW
LIGHT
TEMPERATURE
NUTRIENT
CONCENTRATIONS
pH
\ X
\. / Of
NUTRKNT
UPTAKE
SECRETION
RESPIRATION
KM EXCHANOE
ORGANIC
NITROGEN
PHOSPHORUS
BACTERIA
FUNGI
SETTLMC
KPmOUCTKNN
ORGANIC UPTAKE
EXCRETION
DEATH
FEEOIM
tUHTRATE TYPt
MHTKLC SIZE
1CIN
KATIRUOVEMENT
ABIOTIC INTERACTIONS
MTTUNB
rCNIP
numcLE SIZE
OXYGEN REDOX
, ALKALINITY
SUBSTRATE TYPE
ORGANIC MATERIAL
.TEMPERATURE
l>
NUTRIENT PUMPING
BIOTA
D
/NUTRIENT UHITATION1
' OXVMN
TOHC EFFECT OP
BLUE-GREEN*
SHADING rt ALOAE 4
MACROPHYTE*
LIGHT. pH. TEMPERATURE
.none coMprrmoN
\PREOATION
HEPMOOUCnON
__RE»VBPfll«ON
MUTRCNT PUHPINO
fWATER FLOW
WIND, MIXING
STRATIFICATION
(OXVOEN)
none STiRRura
BACTERIAL TRANSFORMATION
REDOX, TEMPERATURE
MORPHOMETRT
CHELATOR (FE, S)
L ROOTED MACROPHYTH
.SEDIMENTATION
SEDIMENTS
Fig. 10.11.
A conceptual model of combined phosphorus and nitrogen flows and
interactions. Major biotic and nutrient pools are shown in com-
partments. Lines indicate material flows, with the controls on
these flows also indicated. Single headed arrows are used when
the opposite directions of flow are labelled.
276
-------
II
PRECIPITATION
OENITRIFICATION 2
LOADING 2.
'OUTFLOW
i
INORGANIC
ORGANIC
N,P
FIXATION Z
NUTRIENT UPTAKE I ^
NUTRIENT RELEASE!
BIOTA
'
SEDIMENT RELEASE 2 SEDIMENTATION I
OEMTRIFICATION 2
WATER FLOW
OXYGEN
REOOX
SEDIMENT
TYPE
SEDIMENTATION I
1
SEDIMENT
N,P, BIOTA
NUTRIENT
PUMPING 2
EMERGENCE I
Fig. 10.12.
Standard aquatic response to nutrients for various trophic states.
Major biotic and nutrient pools are shown in compartments. Solid
lines indicate material flows, with the controls on these flows
also indicated. Flows followed by a ^ are significant in oligo-
trophic and eutrophic systems. Flows followed by a 2_ are most
important in eutrophic systems.
277
-------
macrophytes, rather than phytoplankton, may be responsible for most of the
primary productivity. Increased decomposiiton associated with increased pro-
duction, as well as increased nitrification, may deplete oxygen levels in the
hypolimnion, especially in shallow, stagnant systems. Reduced oxygen concen-
trations observed in the transition from oligotrophy to eutrophy may eliminate
all fish species or result in changes in the dominant species. Fish popula-
tions also may be responding to decreased numbers of zooplankton which are
unable to graze on blue-green algae. With reduced conditions in the hypo-
limnion, the sediments may release nutrients to the overlying water.
Nutrient loading over an extensive length of time may build up a vast
nutrient reserve in sediments. Under specific conditions sediment nutrients
can be the most significant driving force of biotic processes. Diverting
sewage in Lake Washington did result in a shift from nutrient rich conditions
and high productivity to conditions exhibiting less productivity. However,
Lake Washington had only recently become eutrophic and did not have a large
build up of nutrients in the sediments. Waters that have exhibited eutrophic
conditions for long time periods may be less likely to revert back to more
pristine conditions when nutrient loading is reduced. On the other hand,
nutrients that have accumulated over long time periods in sediments may be
more refractory and permanently unavailable for biotic consumption as was
shown in Lake Norrviken (Ahlgren 1977).
Biotic recycling, especially in nutrient rich waters, also may be respon-
sible for maintaining high nutrient levels observed in some lakes (Shapiro
et al. 1975; Shapiro 1977). Consideration of mechanisms acting to prevent
internal loading might be necessary for successful management. Besides con-
trolling nutrient inputs some ideas for management of aquatic productivity
may include: 1) manipulation of higher trophic levels which have a large
degree of influence of lower levels (addition of zooplankton, particularly
filter-feeders or adjustment of fish species or numbers; 2) control of domi-
nant phytoplankton species (decreasing pH, or addition of C02 or nitrogen,
thereby selecting against blue-greens); or 3) alteration of the physical
environment (increasing circulation or oxygen levels)(Shapiro et al. 1975).
Some management consideration of particular biotic species may be
necessary. Systems with equivalent levels of productivity will not neces-
sarily have the same species of biota. Particularly in highly eutrophic lakes
this phytoplankton-zooplankton relationship depends on species composition
(Vollenweider 1976). Some species may be more desirable than others, and
endangered species may need special consideration. Although primary produc-
tivity may be predicted by a knowledge of nutrient loading levels, species
composition and the impact on a particular species cannot be as easily pre-
dicted. Therefore, it is likely that a standard, nationwide management
approach to regulate eutrophication of surface waters is not feasible. The
problem may be better assessed by a regional and hierarchical organization.
278
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10.4 LITERATURE CITED
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CHAPTER 11
UTILIZATION OF A HIERARCHICAL SYSTEM TO EVALUATE THE IMPACT OF
SEDIMENT AND NUTRIENTS ON FRESHWATER ECOSYSTEMS
The impact of nutrients and sediment on freshwater biota may best be eval-
uated by the use of a hierarchy of ecological organization. For this report
the hierarchical levels of interest are the region, watershed, community, popu-
lation, and individual. In addition to organizing current information, this
scheme may help to identify new directions for research or indicate weaknesses
in our knowledge. For example, limnological studies have emphasized individual
and population studies; relatively fewer studies of aquatic communities or
studies integrating watershed influences on aquatic biota are available. An
integrative approach will lead to an understanding of the dynamic behavior of
the water body, as well as elucidating the indirect impacts of nutrient and
sediment addition on organisms.
The set of characteristics used to describe impact depends upon the level
of ecological organization chosen for study. For instance, a comparison of
aquatic systems in different regions requires information on climatic, geologic,
and vegetational differences which may affect system response. A comparison of
aquatic systems within a given region (the watershed level) may require infor-
mation on primary productivity, sediment and nutrient loading, food chain
structure, trophic state, and other system properties. Impact analysis at the
community level might use data on species diversity, community respiration or
production, and biomass. On the other hand, if biota are defined as populations,
then the points of interest might be density, mortality, changes in growth or
metabolic patterns, and energetics. Consideration of the individual organism
may require, in addition to the population level analysis, information on
mortality for different age classes of a species due to some perturbation.
However, the set gf characteristics needed to be measured are much more easily
identified than are the best methods of obtaining the measurements. Presently,
information obtained through the use of a variety of methods and indices is
compared, reducing the reliability of conclusions.
We also have concluded that all water bodies cannot be managed using one
criterion and that different criteria are required for different levels of
organization. This is true when the desired state of the community ecosystem
and the state of species of interest are different. The principle of community
stability contends that the species may shift in presence, abundance, and
activity while the community properties stay within set limits. A water
body managed so that the impacts of nutrients and sediment do not drive the
system out of a set limit of behavior does not necessarily mean that all
species will stay within their limits of optimal behavior. On the other
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hand, the system may be manipulated to maximize production of a particular
species. The management of a water body so that a species of interest is
undisturbed can result in a change in overall system behavior.
This conflict in the objectives is familiar in resource management.
Resolution of the problem requires the following approach: nationwide stand-
ards can be used for freshwaters, but these standards may be inexact for
certain waters and rather rigid for others. The use of regional standards
may ameliorate this problem. It might be possible to set standards for
separate, major river basins. At a more detailed level, waters might be set
aside for different purposes. For example, some waters may be managed to
yield specific system properties which can be defined publicly as clean water.
Other waters could be managed for species or characteristics of interest. In
some cases both management objectives will coincide and in other cases they
will conflict, but by use of a hierarchical system of organization the extent
of the conflict can be reduced. Through the implementation of our hierarchical
scheme, the important processes at each level can be identified and some
management strategies suggested.
11.1 REGIONAL LEVEL
Regionalization provides an organization of patterns in behavioral
response of aquatic systems over a wide range of environmental conditions.
The biological information obtained to date is weak since various regions
have been studied much more than others. For example, in northern regions,
especially in the Midwest and Northeast, a good deal of data is available
on the ecology of lakes and streams. The southern and western portions of the
nation have relatively fewer data. This unevenness in information means that
a comparison of response and prediction of impact across the United States is
severely limited.
We have made a detailed study of patterns of nutrient, sediment, alkalin-
ity, and land use in the United States using Bailey's ecoregion system. We
used the province level in the ecoregion analysis. The province by province
analysis shows no clear pattern of differences; however, when provinces are
combined, general patterns emerge. Natural differences in nutrient and sedi-
ment loading from watersheds may result from different soil types or from the
amount and frequency of rainfall. The patterns observed also result from
local ecological succession and the climax vegetation. For example, provinces
with a high proportion of land in forests show relatively low sediment and
phosphorus concentrations, and often lower nitrogen levels in streams than
provinces with a high proportion of the land in agriculture. While almost no
climax vegetation remains in most provinces, nevertheless, those with a forest
climax eventually return to forest when agricultural or other cultural uses
of the land are abandoned. Thus, the tendency in these provinces is a return
to the climax state typical for them which results in low sediment, low phos-
phorus, and often low nitrogen in surface waters. For contrast, provinces
where the climax is grass and desert vegetation, abandonment of agriculture
results in a system which can be used for extensive grazing. Overgrazing is
similar to the impact of agriculture, and the high sediment, high phosphorus,
and high nitrogen patterns are retained.
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Natural differences in alkalinity also will influence the biotic compo-
sition and the response of the system to nutrient impact. For example, soft-
water systems predominating the Southeast and extreme Northwest have low pro-
ductivity and may have a higher nutrient loading tolerance since bacterial
transformations are inhibited. Hardwater systems, prevailing in the Midwest
and Southwest generally are low in productivity. Productivity in these areas
may be suppressed by high sediment levels or by organic-inorganic interactions
that bind phosphorus, making it unavailable for biota. Of course, cultural
practices such as the use of fertilizers and urban outputs also can affect
these patterns.
Regionalization might provide a means by which management of aquatic
resources of the entire United States may be accomplished. Whether or not
regional management is useful must await studies of poorly known areas, com-
parisons between regions and system types, and adoption of the most appropriate
regional scheme.
11.2 WATERSHED AND COMMUNITY LEVELS
The behavior of biota in a water body is inseparable from events occur-
ring in the watershed. Disturbances in the watershed increase the amount and
influence the type of sediment and nutrient loading to the water. The extent
to which biota are impacted by sediment and nutrients depends on the magnitude
of inputs and outputs, the trophic state of the system, and the biotic
composition of the system.
High levels of sediment can be detrimental to producers as well as con-
sumer species. As sediment becomes suspended, light penetration is reduced
and primary production may decline. Nutrients associated with sediment
entering the water from runoff may stimulate production. This stimulation
may offset the detrimental effect of sediment, as long as high levels of
sediment are not suspended. When flow rates are high, biota may be affected
by sediment scour, abrasion, or burial. Suspended sediment exerts the greatest
impact in slower flowing systems where it impedes primary production by
reducing light penetration. Bed load movement is more of a problem in
faster flowing systems where it physically damages benthic organisms.
The watershed also provides the major source of nutrients to the water
body. An autotrophic system may respond to nitrogen or phosphorus inputs, or
both, depending upon the initial nutrient ratios in the system. The direct
impact of nutrients is the stimulation of primary productivity. Higher
trophic levels may be affected indirectly by nutrient additions through two
different mechanisms: the impact may result from changes in the physico-
chemical environment associated with increased primary production or may be
determined by the number of steps away from the primary producers in the
feeding web. In heterotrophic systems community productivity may be increased
by addition of nitrogen, which stimulates decomposition.
In lakes the dominant primary producers are a major determinant of other
biota present in the system. Autochthonous sources of nutrients are most
important in slow moving aquatic ecosystems, which are large in volume in
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comparison to the watershed area. In lakes, both autochthonous and allochtho-
nous nutrient inputs modify the composition of primary producers and thereby
the composition of other trophic levels. Depending on the plants which become
dominant, an increase in primary production may increase or decrease the pro-
ductivity of higher trophic levels. In contrast, in many streams, the amount
and composition of allochthonous organic material inputs will determine the
types and numbers of organisms present in the system. Certain organic inputs
may increase the resource base of aquatic animals, whereas an excess of easily
decomposable materials may cause oxygen depletion and feeding inhibitions.
A primary physical factor influencing the degree of impact of nutrients
on biota is water residence time, which is an indication of the dilution of
the incoming nutrients. Thus, the rate of flushing determines the extent to
which a system can tolerate nutrient loading. Permissible nutrient loading
levels, based on hydraulic residence time, have been proposed for the mainte-
nance of different trophic states (Vollenweider and Dillon 1974; Vollenweider
1976). If a system has a low flushing rate, or if it is highly eutrophic,
internal nutrient sources may be significant, and the predictability of the
trophic state may decrease.
Indirect effects on biota, although often overlooked, also are of interest;
therefore, the degree to which impact is propagated thorough an ecosystem food-
web must be considered. Impact on fish, zooplankton, and aquatic invertebrates
is often the result of indirect effects such as oxygen depletion, nutrient
enrichment, changes in food resource composition and diversity, habitat modi-
fication, and toxic effects of blue-green algae. Impact may be transmitted
through several links of a food web before affecting trophic levels removed
from the point of direct impact. Because aquatic ecosystems are circularly
causal (Hutchinson 1948), the indirect response of higher trophic levels may
feed back and affect primary producers. Mathematical models and various
systems analysis techniques provide a means by which the indirect influence of
nutrients and sediment on biota can be examined.
11.3 POPULATION LEVEL
Prediction of the response of a particular group of organisms (i.e., blue-
green algae) to nutrient addition may be possible. However, in most cases
prediction of a species' response is more difficult. An aquatic system is a
network of interacting organisms and physico-chemical processes; the response
of any species is constrained by its position in the system network relative
to system components which impinge upon it. Results of laboratory experiments
can only be applied loosely to field conditions because of the confounding
variables which cannot be controlled in the environment. Even the response of
one species in two adjacent water bodies may be different as a result of vary-
ing environmental parameters. Detailed mathematical models such as MS. CLEANER
(Park et al. 1978) may provide a means of predicting impact on individual
groups of organisms, although the detail required to predict a species'
response may be too unwieldy.
The response of individual species to nutrients conventionally has been
examined under the laws first recognized by Justus Liebig. Liebig's Law of
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the Minimum (1840) states that the factor in shortest supply will limit the
growth of a population if physical conditions are optimal. Liebig's Law
recognizes a portion of a response curve which describes the response of out-
put of a system to a change in input of one essential factor. In this positive
slope portion of the performance curve, addition of the limiting factor stimu-
lates the response. At very high inputs, even though the factor may no longer
be limiting, a negative response may occur as the factor becomes toxic or as
a competitor species becomes dominant. The data in the response or performance
curve are required in a system model for prediction of impact in order to
describe the relationship of one component to another and one component to the
environment.
Liebig's Law can and has been applied to the response of an entire aquatic
system, but Lane and Levins (1977) have questioned whether this is justified
because systems are typically composed of many interacting species with
different physiological responses. However, we feel that justification of
applying Liebig's Law to the response of an entire system can be made. Even
though individual responses are varied, the overall response of the interact-
ing network of an aquatic system is predictable. Addition of nitrogen, phos-
phorus, or both, may positively influence some species, negatively influence
others, or have no effect. Certain species may act to compensate for the
negative response of other species such that system productivity increases.
Qualitative network analyses (Lane and Levins 1977; Hill 1979) can be used to
trace influence through a network to determine the direction of a whole system
response. Quantitative prediction can be done using mathematical models. The
mechanisms for nutrient limitations on a composite phytoplankton community have
been dealt with in recent aquatic system models (Chen and Orlob 1975; DiToro
et al. 1975; Park et al. 1975; Patten et al. 1975).
11.4 INDIVIDUAL LEVEL
From physiological studies on individual organisms, tolerance limits have
been established for many aquatic species. Species which have narrow tolerance
ranges can be used as indicators of water quality and water quality change.
Although the presence of an individual species may not be predictable, its
absence may be. The use of indices based on species diversity where taxonomy
is known or based on diversity of broad functional groups may provide a great
deal of information concerning the condition of the aquatic system.
IT.5 USE OF MODELS
Understanding the impact of nutrients and sediment in aquatic ecosystems
can be facilitated by conceptual and mathematical models. Models are used to
organize information about complex systems and to predict the direction and
degree of change in selected variables. Coarse resolution characteristics of
an ecosystem such as trophic state and primary production rates often can be
predicted with a few easily measured variables. Among the most important of
these are flushing rate, nutrient and sediment loadings, initial trophic state,
and movement to and from sediments. These parameters determine a response
surface which describes the variation of predicted variables. Coarse
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resolution models have been used to predict the response of a number of lakes
(Vollenweider 1972, 1976) and rivers (Streeter and Phelps 1925; O'Connor 1961).
More detailed questions about the chemical and biotic dynamics of aquatic
ecosystems can be addressed with finer resolution models. Fine resolution
mathematical models incorporate the dependency network which links biotic and
chemical components of an ecosystem; both direct and indirect effects of impact
can be evaluated. The impact of nutrients and sediment on ecosystem components
and processes have been quantitatively predicted for lakes and reservoirs (Chen
and Orlob 1975; DiToro et al. 1975; Patten et al. 1975; Park et al. 1978),
swamps (Kadlec 1978; Odum 1978), and rivers (Boling et al. 1975; Mclntire and
Colby 1978).
A premise of this report is that the response of aquatic ecosystems is
largely defined by the nature and magnitude of inputs and outputs as well as
the internal cycling. Although the importance of inputs from the surrounding
watershed in determining aquatic ecosystem behavior has been recognized, water-
shed behavior is rarely reflected in mathematical models. Outputs also are
important in defining ecosystem behavior in impact analysis. Internal mechanisms
such as sedimentation and resuspension rates have been shown to be important in
determining availability of nutrients to biota. Both outputs and internal
cycling must be considered in any predictive model.
By examining aquatic ecosystem models, we have identified components and
processes which have been used to predict and describe the response of aquatic
ecosystems to nutrient and sediment inputs. The categories of components and
processes include biotic and chemical compartments, inputs and outputs, physical
and chemical controlling variables, spatial structure and terrestrial-aquatic
interactions. Using these components and processes, we have constructed
several conceptual models; these models have been used to organize information
in the literature and to establish ecosystem networks necessary for qualitative
prediction of impact of phosphorus, nitrogen, and sediment inputs. Quantitative
prediction of impact on biota can be done using the mathematical models dis-
cussed in Chapter 7.
We have constructed the models at two levels of resolution. At the
coarser level, macroscopic properties of ecosystems have been used to organize
information about impact analyses (see Fig. 10.6). Sediment, nutrients, and
biota are the ecosystem components identified at this level of resolution. At
the finer level of resolution, sediment, inorganic nutrients, particulate
organic materials, macrophytes, bacteria and fungi, vertebrates, invertebrates,
and algae have been identified (Fig. 11.1). Information and variables required
for impact analyses depend on the questions asked of the system and the objec-
tive which the impact analysis is designed to meet.
11.6 LITERATURE CITED
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Systems analysis and simulation in ecology. VoTT III. Academic Press,
New York.
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Chen, C. W., and 6. T. Orlob. 1975. Ecologic simulation for aquatic environ-
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DiToro, D. M., D. J. O'Connor, R. V. Thomann, and J. L. Mancini. 1975. Phyto-
plankton-zooplankton-nutrient in interaction model for western Lake Erie.
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Hutchinson, G. E. 1948. Circular causal systems in ecology. Ann. New York
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Civil Engineering. Univ. of Washington, Seattle, Washington.
Lane, P., and R. Levins. 1977. The dynamics of aquatic systems. 2. The
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Liebig, J. 1840. Chemistry and its application to agriculture and physiology.
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Mclntire, C. D., and J. A. Colby. 1978. A hierarchical model of lotic
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311
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o
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Fig. 11.1. Continued.
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TECHNICAL REPORT DATA
(Please read Instructions on the reverse before completing)
1. REPORT NO. 2.
EPA-600/3-79-105
4. TITLE AND SUBTITLE
IMPACTS OF SEDIMENT AND NUTRIENTS ON BIOTA IN SURFACE
WATERS OF THE UNITED STATES
7. AUTHOR(S)
E.G. Farnworth, M.C. Nichols, C.N. Vann, L.G. Wolfson,
R.W. Bosserman, P.R. Hendrix, F.B. Golley, J.L. Cooley
9. PERFORMING ORGANIZATION NAME AND ADDRESS
Institute of Ecology
University of Georgia
Athens, Georgia 30602
12. SPONSORING AGENCY NAME AND ADDRESS
Environmental Research Laboratory—Athens, Ga.
Office of Research and Development
U.S. Environmental Protection Agency
Athens, Georgia 30605
3. RECIPIENT'S ACCESSION-NO.
5. REPORT DATE
October 1979 issuing date
6. PERFORMING ORGANIZATION CODE
8. PERFORMING ORGANIZATION REPORT NO.
10. PROGRAM ELEMENT NO.
1HE775
11. CONTRACT/GRANT NO.
R804868020
13' 7iFna°f ,R WW9ERI°D C°VERED
14. SPONSORING AGENCY CODE
EPA/600/01
15. SUPPLEMENTARY NOTES
16 ABSTRACT
A review of research on the impacts of sediment, nitrogen, and phosphorus on aqua
tic biota was performed to determine the influences of sediment and nutrients on biota,
to suggest directions for future research, and to provide suggestions for management o1
freshwater systems across the United States. This report is divided into two sections.
The first section provides an organization and background information to enable incor-
poration of large amounts of available information and allow assessment of impacts at
several hierarchical levels. Included are a hierarchical scheme that is the founda-
tion of the analytical study; a regional analysis of the concentrations of sediment,
nitrogen, and phosphorus in surface waters; a review of biotic impact assessment ap-
proaches; and a review of modeling of sediment and nutrient impacts. The second sec-
tion reviews the impacts of sediment, nitrogen, and phosphorus on biota, integrates
this information into the hierarchical scheme developed in the first section, and
shows how the hierarchical scheme can be used for impact analysis.
The need for a holistic approach to the problems of sediment and nutrient impacts
on surface water led to the development of an organizational scheme. This scheme in-
corporates a nested hierarchy of ecosystems combining geographical and biological unit*
plus their environments at different levels of complexity. The levels used are nation,
region, watershed, community, population, and individual ecosystems.
17. KEY WORDS AND DOCUMENT ANALYSIS
a. DESCRIPTORS
Sediment transport Mathematical models
Nitrogen Management
Phosphorus
Aquatic animals
Aquatic plants
Water pollution
18. DISTRIBUTION STATEMENT
RELEASE TO PUBLIC
b.lDENTIFIERS/OPEN ENDED TERMS
19. SECURITY CLASS (This Report)
UNCLASSIFIED
20. SECURITY CLASS (This page)
UNCLASSIFIED
c. COSATI Field/Group
02A
07B
07C
68D
21. NO. QF PAGES
331
22. PRICE
EPA Form 2220-1 (9-73)
315
« U S GOVEIWIiOlt mmtlHG OFTKX IWO-657-146/5489
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