-------
Table 2. TCG fish analysis - method validation.
FISH
WEIGHT (g)
(ig TCG ADDED
H3/3 (THEORETICAL)
M9/9 (ANALYTICAL)
X RECOVERY
C-14
C-11
C-10
C-18
C- 5
C-15
6.22
5.57
5.90
5.09
6.48
4.22
0
5
10
20
50
100
0
0.898
1.69
3.93
7.72
23.7
0
0.892
1.51
3.68
6.67
24.2
.
99.3
89.3
93.6
86.4
102
no differences could by measured. This may not be a valid test with so few numbers;
however, one-way analysis of Variance (ANOVA) applied to all three groups of uptake rate
data suggested that the differences in the means of the groups was no more significant than the
variability within each group.
ACKNOWLEDGEMENT
This research was funded in part by the U.S. Environmental Protection Agency,
Environmental Research Laboratory, Athens, Georgia, through Cooperative Agreement
CR 995189.
REFERENCES
Dence, C. W. 1971. Reactions of lignins, halogenation and nitration. In: Lignins,
occurrence, formation, structure and reactions. K.V. Sarkanen and C.H. Ludwig
[ed.]. John Wiley and Sons, Inc., New York, N.Y.
Folch, J., M. Lees, and G.H. Stanley. 1957. A simple method for the isolation and
purification of total lipides from animal tissues. Journal of Biology and Chemistry
226: 497-509.
Gehrke, P.C., L.E. Fidler, D.C. Mense, and D.J. Randall. 1990. A respirometer with
controlled water quality and computerized data acquisition for experiments with
swimming fish. Fish Physiology and Biochemistry 8: 61-67.
Landner, L., K. Lindstrom, M. Karlsson, J. Nordin, and L. Sorensen. 1977.
Bioaccumulation in fish of chlorinated phenols from kraft pulp mill bleachery
effluents. Bulletin of Environmental Contamination and Toxicology 18: 663-673.
Leach, J.M., and A.N. Thakore. 1973. Identification of constituents of kraft pulping
effluent that are toxic to juvenile coho salmon (Oncorhynchus kisutch). Journal of the
Fisheries Research Board of Canada 30: 479-484.
62
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Leach, J.M., and A. N. Thakore. 1975. Isolation and identification of constituents toxic to
juvenile rainbow trout (Salmo gairdneri) in caustic extraction effluents from kraft pulp
mill bleach plants. Journal of the Fisheries Research Board of Canada 32: 1249-
1257.
Niimi, A.J., H.B. Lee, and G.P. Kisson. 1990. Kinetics of chloroguaiacols and other
chlorinated phenolic derivatives in rainbow trout (Salmo gairdneri). Environmental
Toxicology and Chemistry 9: 649-653.
Paasivirta, J., P. Klein, M. Knuutila, J. Knuutinen, M. Lahtipera, R. Paukku, A.
Veijanen, L. Welling, M. Vuorinen, and P. Vuorinen. 1987. Chlorinated
anisoles and veratroles in fish. Model compounds. Instrumental and sensory
determinations. Chemosphere 16: 1231-1241.
Pressley, T.A., and I.E. Longbottom. 1982. The determination of chlorinated
herbicides in industrial and municipal wastewater - Method 615. Environmental
Monitoring and Support Laboratory, U.S. Environmental Protection Agency,
Cincinnati, Ohio.
Renberg, L., O. Svanberg, B. Bengtsson, and G. Sundstrom. 1980. Chlorinated
guaiacols and catechols bioaccumulation potential in bleaks (Alburnus alburnus,
Pisces) and reproductive and toxic effects on the harpacticoid Nitocra spinipes
(Crustacea). Chemosphere 9: 143-150.
63
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AN INVESTIGATION OF THE LOWER DON RIVER WATER QUALITY
USING SIMULATION MODELS
by
M. G. Yereschukova1, E. Z. Hosseinipour2, R. B. Ambrose3, V. V. Tsirkunov1,
R. C. Russo3 and A. M. Nikanorov1
ABSTRACT
This paper describes a hydrodynamic and water quality modeling effort on the Don
River in Russia. The waterway is one of the largest rivers of Russia and has been adversely
impacted by development; its lower part in particular is severely impacted by anthropogenic
processes. Don River basin is an intensively exploited region with respect to agricultural and
industrial activities. Waters of the Lower Don system are diverted for municipal and industrial
uses, as well as for irrigation of agricultural fields. Preliminary results from water samples
collected in the summer of 1990 indicated that conventional pollutants and synthetic organic
materials are the major contaminants of concern. The developed linked model of the system
consists of a river hydraulics and sediment transport code (RIVMOD), its modified version for
handling branched systems (RIVNET), and the water quality modeling package (WASP4).
Simulation results indicate that detailed morphometric characteristics are needed at the Don
mouth for better model performance. Hydrodynamic and water quality data should also be
collected on the main branches of the Don at its mouth on a concurrent basis in order to be
useful for modeling purposes. To determine the best management alternative for water
quality improvement, watershed models should be used to delineate the nonpoint source
loading patterns. For these purposes, information on water uptake from the river and
wastewater loading to the river are also required. Although evaluation of model performance
is difficult due to inadequacy of information and uncertainty about representativeness of
available data, nevertheless results are useful for designing data collection networks for
long-term water management and further simulation studies.
1Hydrochemical Institute, Rostov-On-Don, Russia.
2South Florida Water Management District, Planning Department, West Palm Beach, FL
(USA).
3U.S. Environmental Protection Agency, Environmental Research Laboratory, Athens, GA
(USA).
64
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INTRODUCTION
Among the large rivers of Russia, the Don-and in particular its lower part-is severely
affected by anthropogenic impacts. Runoff and irrigation return waters from fields,
discharges from industrial plants along the river, and discharges from municipalities adversely
impact the quality of Don waters. Although there are heavy industrial complexes in the river
basin, preliminary data from water samples showed that conventional pollutants and synthetic
organic materials are the major contaminants of concern. For water quality modeling,
information about hydrological regime, transport and transformation of contaminants carried
to the river, and river ecosystem characteristics are required. Such data and associated
simulation results from modeling can then provide necessary inputs for water management
alternatives that are environmentally and ecologically sound and economically feasible. To
this end, hydrodynamic and water quality modeling of the Lower Don River system can shed
some light on the processes active in the waterway and provide insights that could be helpful
in selection of water quality management alternatives.
In this paper only the stretch of the Don River from Razdorskaya to Taganrog Gulf is
considered in the simulations. Analysis of data collected by the Hydrochemical Institute in
Russia, and the Environmental Protection Agency's Athens Environmental Research
Laboratory (AERL) in the U.S., showed that the main water quality problems of the Lower
Don system are associated with processes of eutrophication, contamination by organic
matter, and pesticides. Besides, high sediment load and turbidity may essentially influence
the aquatic ecosystem and hence self-purification processes.
PHYSICAL SETTING
The Don region covers an area of about 323,000 km2. The Don watershed consists of
three different physiographic zones: mixed forest, partially wooded steppe, and steppe. This
region is part of the Don River watershed, supplying much of its annual flow. The Don River
is situated between 44 and 54°N latitude and 37-45°E longitude. The maximum north-south
spread is 650 km, and the east-west spread is about 160 km. The Don is a relatively large
river, approximately 1870 km long and is fed by a watershed with an area of about 422,000
km2. The river's headwaters are on the east side of the Middle Russian Hills. The Don flows
into the Taganrog Gulf on the Azov Sea. In the upper parts, the river flows through a narrow
valley and its channel has high right banks. In these parts the river also intercepts many
ravines and has a number of shoals, which are formed by the sediment transport from
tributaries and inflows from ravines. The river channel is very winding and often meanders in
the flat sections.
In the middle section the river valley is significantly wider, though the river channel
runs close to the right side of the valley with elevated banks. At the end of the Don's middle
section the natural flow is altered by a hydropower and water supply dam behind which is the
Tsimlyansk Reservoir. Downstream from the dam the river valley is quite wide with lateral
stretches up to 30 km. Water depth in the river channel at the thalweg can be as much as
20 m. The river estuary is situated downstream from the city of Rostov-On-Don. The estuary
covers an area of approximately 340 km2. In the lower reach of the river more tributaries
discharge into the Don.
65
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Anthropogenic activity plays a significant role in transformation of natural features of
the Don River. The river basin is one of the most exploited regions of the country with
respect to industry and agriculture. Ecological problems such as soil plugging, forest cutting,
and soil erosion are widespread. In addition to the Tsimlyansk Reservoir on the Don, a
number of reservoirs also are in place on the Don's tributaries, as well as hydraulic
engineering structures such as dams and irrigation channels. Almost 7500 km2 of agricultural
fields are irrigated in the Don River basin. The Don River and its tributaries are sources of
water supply for many large industrial complexes. The stretch of the Don River from the
Tsimlyansk Reservoir to the Taganrog Gulf is referred to as the Lower Don River. The area
of the watershed in the lower part is over 160,000 km2; the length is about 313 km. The river
in the lower part meanders through the valley with a spread of usually about 11-12 km,
though it can reach up to 22-25 km. The river width varies from 400 to 600 m in the lower
part. Average water depth during low-water regime is in the range of 4-6 m in the main
channel, and decreases to 0.7 m in shoal areas.
HYDROLOGY OF THE LOWER DON RIVER SYSTEM
The Lower Don region is situated in a semiarid climate zone with characteristics of
which are irregular precipitation and highly variable surface and ground waterflow. The main
source of water is precipitation. Average total runoff is estimated to be about 30 mm per
year of which 20 mm is produced by surface runoff and the rest from ground water runoff as
interflow or baseflow. Direct surface runoff to the river from precipitation produces 75% of
the flow of which snow accounts for about 67%. The rainfall component of surface runoff is
no more than 8% of whole river flow. Hence, the majority of the river discharge takes place
in spring during snowmelt. Overall, summer rains and winter snow characterize the
hydrology of the Lower Don River system and contribute most of the annual flow. The
hydrochemical composition of the Lower Don River is influenced by many factors. The
primary chemical characteristic and biological features are defined by the waters behind the
Tsimlyansk Reservoir. As water flows downstream, its chemical composition transforms
significantly. This transformation is due to loading of the dissolved matter which is
anthropogenic and of natural origin. Yereschukova et al. (1992) give more details on the
river system.
WATER QUALITY CONSTITUENTS
SEDIMENT WASHOFF AND ITS CHARACTERISTICS
Most sediment washoff to the river occurs during spring high flows. Suspended
sediment distribution across the channel cross-section is both temporally and spatially very
heterogeneous. Turbidity increases in the middle sections of the river and near the bed.
Surface soil layers in the watershed of the Lower Don River have a highly impermeable crust.
This feature causes rapid accumulation of water from rainfall, since very little water can
infiltrate the soil crust. Runoff carries with it all the accumulated fine materials from the soil
surface. The concentrated flow can harness enough energy to induce erosive power to the
point of gully erosion and heavy sediment load to the river system.
66
-------
During spring more than 70% of annual solid loads are transported to coastal waters.
The annual load of suspended matter is close to 1.6 million tonnes in the Lower Don. About
40% of these materials are accumulated in the river channel; only 1 million tonnes are
transported to the coastal-sea areas (Yereschukova et al. 1992). The composition of
suspended materials in the lower part of the river may provide some hint concerning
conventional water quality parameters. The transported sediments consist of mineral matter,
detritus and live bacteria, phytoplankton, and zooplankton. Analysis of transported materials
showed that during spring 1984 solid load comprised 24.3% and live organisms and minerals
75.5% of the total load. The water column saturation with mineral load has negative effect
on the biota of the Lower Don. Phytoplankton is a source of significant biomass; composition
of different species is sufficiently stable. During spring much of the phytoplankton consists of
diatoms (61-93% of total biomass). Also represented are the greens and goldens which are
about 2-29% and 0.08-39%, respectively; bluegreens do not play a very significant role (1-
17% of total biomass). Quantitative analysis indicates that phytoplankton distribution is very
uneven. Total biomass changes from 0.5 to 6.8 mg/L, with an average value of 3.0 mg/L.
DISSOLVED OXYGEN REGIME AND OTHER CONTAMINANTS
The dissolved oxygen regime of the river is fairly stable. Oxygen content has never
decreased below critical level (i.e., 5 mg/L). At the same time, in Tsimlyansk Reservoir,
during intensive growth of blue-green algae anoxic conditions may prevail and the oxygen
concentration in the bottom layers can go down to 1 mg/L. Concentrations of heavy metals,
phenols, and synthetic surfactants are generally stable within the study area and slightly
exceed maximum allowable concentration value. Concentrations of chloro-organic pesticides
such as DDT, lindane, and their metabolites are also measured for routine monitoring
purposes. These pesticides were detected in more than 50% of the samples for all locations.
Maximum concentrations of DDT may reach dozens of micrograms per liter, while lindane
concentrations of several hundred parts per billion are not uncommon. Determinations of
concentrations for trace organic pollutants showed that detectable concentrations were
predominantly in zones of direct influence from major point sources of pollution. Most of
these pollutants are biodegradable, so they may have only local toxic effects.
NUTRIENTS
Part of the chain in the nutrient recycling process is dissolved organic matter. The
amount of dissolved organic matter is measured by the amount of oxygen needed for
oxidation of the organic load or the biochemical oxygen demand. The concentration of
dissolved organic matter is highly variable. In 1984 it ranged from 4.32 up to 15.52 mg O2/L.
The organic load distribution along the river is uneven. There is a small increase in the
amount of dissolved organic matter from Tsimlyansk Dam to the mouth of the Don (6.08 to
7.2-11.52 mg O2/L). This trend is disturbed only at the mouth of tributaries Sal and Manuch.
There is a clearer trend in distribution of organic matter in the Don across the river
section. Higher concentrations have been observed at the right bank of the river. The
reason is that more sources of anthropogenic pollution are situated on the right bank of the
river. The nutrient load to the Lower Don River system changes unevenly during the year
67
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and from 1 year to the next. Nutrients come to lower parts of the Don River from upstream
tributaries and lateral point and nonpoint sources. The average load through the
Rasdorskaya cross-section is presented in Table 1.
Sources of the phosphorus supply to the Lower Don are varied. Part of it is due to
decay of dead organisms; another part is supplied through bottom erosion processes. A
significant portion of phosphorus load can be attributed to return water from agricultural
fields, stock farms, and municipal wastewater treatment plants. During spring the mean
concentration is about 0.009 mg/L (with a range of 0.006-0.012). In spring, concentrations of
phosphorus in the Lower Don River are at background levels. In summer, concentrations rise
to very high levels, sometimes up to 0.3 mg/L, and the waterbody shows signs of low level
phosphorus contamination. In autumn, phosphorus concentrations decline to 0.09 mg/L.
TABLE 1. NUTRIENT LOADS TO THE LOWER DON RIVER SYSTEM (IN METRIC TONNES PER
YEAR)
Month
NO,
NO,
NH4
Si
January
February
March
April
May
June
July
August
September
October
November
December
830
1120
1770
2550
3630
3060
1010
1090
1860
1450
3080
1770
74
88
223
78
147
162
42
60
217
32
70
26
400
590
85
1670
1480
60
250
360
290
320
460
280
8
29
60
105
76
53
41
50
50
46
59
25
4
5
8
10
10
6
4
7
5
7
8
5
WATER QUALITY PROBLEMS IN THE LOWER DON SYSTEM
Based on data from observations, water quality problems of the Lower Don can be
characterized only in general terms. For example, the high hydrocarbon level can be
explained by intensive use of the river as a waterway for navigation and transportation.
Petroleum products, such as gasoline and diesel fuel, may leak from small boats and ships
used for transport and recreational purposes and from underground storage tanks in the
vicinity of the river; these are considered major sources of hydrocarbon contamination. In
addition, more hydrocarbon loadings may be added to the river from urban runoff. Partially
treated wastewater from domestic sources through sewage treatment plants or by direct
discharge may be contributing to high nitrite concentrations. Detectible pesticide
concentrations can be interpreted as a result of intensive application on crops and other
plants in the surrounding watersheds.
68
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THE MODELING FRAMEWORK
The above brief description of characteristics of the Lower Don River system shows
that, in order to get a feel for the enumerated problems, models that can describe the
hydrodynamic, sediment transport, and water quality processes in branched river systems are
needed. The most appropriate models for this kind of study are those with dynamic riverine
water quality simulation. However, most available models did not have the capability for
sediment transport or handling branched systems. Because of familiarity and previous
experience we used the WASP4 water quality modeling package (Ambrose et al. 1988) in
association with a river hydraulic and sediment transport model, RIVMOD (Hosseinipour and
Martin 1991). The water quality model of the system is based on mass balance in a
compartment of a waterbody. Hydrodynamic parameters for the water quality model were
supplied by a modified version of RIVMOD for branched systems called RIVNET. The model
is based on the one-dimensional equations of continuity and momentum for a branching or
channel-junction computations network. The resulting unsteady hydrodynamic information
from RIVNET are averaged over large time intervals and stored for later use by the water
quality component of the simulation package. Simulations were conducted for spring high
flows, considering branches and creeks flowing into the system.
WATER QUALITY SIMULATIONS
Hydrochemical processes play an important role in mixing and transport of chemical
and biological compounds in natural waterbodies. To simulate hydrochemical and
hydrobiological processes in rivers, discharges, velocities, and depths are needed.
Therefore, water quality modeling of the Lower Don River system was started with
hydrodynamic simulation. At the upstream of this part of the river, daily discharge and stage
are available, but these data belong to the period before 1987. Besides, short-term
variations in flow may not be significant in long-term simulations. Thus, average values of
discharge for the 10-day period were chosen as a boundary value. Downstream boundary
values for discharge or depth can be specified only approximately because very little data on
the branches at the mouth of the Don River exist. Lack of precise information induces
increasing uncertainty about modeling results. To estimate the influence of errors with regard
to boundary conditions on results of simulation, an uncertainty analysis was conducted
(Yereschukova et al. 1992). To compare results of different experiments, the measure of
deviations between base runs and solutions with modified input data sets was introduced as
follows:
] d)
/V /=1 /V /=i
where
A = absolute measure of error influence
Xb(t,) = the value of characteristic at time t,, which is obtained from the
simulation with the basic .input data
X(t,) = the value of characteristic at time t,, which is obtained from the
simulation with modified input data
N = the number of time steps during the simulation.
69
-------
The relative measure is a more representative estimator of uncertainty. The relative measure
can be calculated by the following formula (Jorgensen 1 986):
A
1 N
~ £
N M (2)
6= - 100%
where
6 = the relative measure of changes in %
Ap/p = the relative change in the parameter value (here in the boundary value).
The above formulas were applied to estimate the change in water distribution between
branches, which are caused by a change in boundary conditions. Such information is very
important in identification of water quality parameters for modeling. To provide accurate
simulation of the hydrodynamic regime at the mouth of the Don River, downstream boundary
conditions have, to be specified as accurately as possible, and no less accurately than
upstream boundary conditions. This accuracy is even more important for simulation of low
flow events. The last cross-section where discharge is measured is near Razdorskaya. The
discharge does not change significantly along the river channel; the high discharge period
coincided with the beginning of the study, and after that their deviations from average flow do
not exceed 15% of mean value. Hence, it is possible to use constant discharge for water
quality simulation. An example of results of discharge simulations from May to October 1983
are presented in Fig. 1 .
As stressed above, one of the main water quality problems in the Lower Don River
system is eutrophication. Simulations could help to detect crucial parameters affecting the
river ecosystem. Once those parameters are determined, the trophic level of this waterbody
can be estimated more precisely. Therefore, the model used for this purpose has to contain
the stated variables at least for the description of algal biomass and organic and inorganic
nutrients. During preliminary analysis of available water quality data, we found that the data
are not adequate for model calibration. However, calibration of the model, even with
incomplete data, could be useful for exploration of the main stated variables and other
parameters of interest. As a whole, simulation results can hardly be used for testing different
management strategies for water quality improvement in the region. However, simulations
can help determine areas that need more research and plan for data collection and further
investigations.
Eutrophication simulation was conducted using the EUTRO4 module of the WASP4
modeling package. This package allows several choices for eutrophication modeling.
Considering the fact that adequate data were not available to describe dynamics of different
phytoplankton groups, the following stated variables were included in the model: biomass of
total phytoplankton, organic nitrogen and phosphorus, and inorganic phosphorus and nitrogen
constituents (including ammonium and nitrate). Although diatoms constitute a large part of
spring phytoplankton and silicon is the nutrient that affects their dynamics, this nutrient cycle
is not taken into consideration because it is not taken up by the other groups of algae.
70
-------
Rostov-on-Don
700
650
600
550
500,
May
June July August September October
O
UJ
CO
UJ
O
O
(0
5
£
111
i
280
260
240
220
200
180
160
Azov
I I 1_
420
410
400
390
380
370
360
350
340
May June July August Septeirber October
Dug 1 no
j I | I
__i * * I i
May
June
July
August September October
Fig. 1. Water discharges in the Don mouth.
71
-------
Implicitly, the water quality model assumes that silicon is never depleted enough to limit
diatom growth. Water temperature and light intensity significantly affect phytoplankton
dynamics. These parameters are included in the model as forcing functions.
SENSITIVITY ANALYSIS
Sensitivity analysis is an important step in environmental transport and fate modeling,
especially in situations where data are incomplete and/or unreliable. Such analysis allows
researchers to look into the most crucial parameters of the model and get a feel for their
impact on the overall analysis. To quantify the influence of parameter changes on dynamics
of the stated variables, equation 2 was applied. Values were varied +10% of their base
values. The analysis was conducted according to a 1-factor plan. Maximum values of
relative changes based on equation 2 are presented in Table 2.
TABLE 2. MODEL SENSITIVITY DUE TO PARAMETER VARIATIONS. PARAMETERS AFFECTING
PHYTOPLANKTON DYNAMICS ARE MAXIMUM GROWTH RATE (G), RATES OF DECOMPOSITION
OF ORGANIC PHOSPHORUS AND NITROGEN (Kp, KN), MORTALITY RATE (M), LIGHT SATURATION
COEFFICIENT (L), AND CARBON-TO-CHLOROPHYLL RATIO (r)
Variable G Kn KN M L r
Phytoplankton
Ammonia
Nitrate
Organic nitrogen
Inorganic phosphorus
Organic phosphorus
0.0850
0.1641
0.0237
0.0438
0.0248
0.0041
0.0014
0.0018
0.0006
0.0005
0.0616
0.3633
0.0000
0.3643
0.0601
0.0000
0.0000
0.0000
0.0220
0.3800
0.0592
0.0029
0.0010
0.0219
0.9444
0.1810
0.0259
0.0484
0.0272
0.0045
0.9991
0.1178
0.0283
0.0340
0.0185
0.0729
It should be noted that the model is structurally stable in the domain of parameter
values in Table 2, because the values of criterion do not exceed 1.0. Since phytoplankton
dynamics are most sensitive to variations in carbon-to-chlorophyll ratio, it would be useful to
determine more precisely the species composition of algae and their elemental composition.
Among factors affecting phytoplankton dynamics, light intensity plays the most important role
and is probably the most limiting factor on this ecosystem. Nitrogen influence on
phytoplankton dynamics is not very significant, in part because its concentrations in Lower
Don waters are significantly higher than its half-saturation value. Changes in phosphorus
dynamics do not affect significantly the algae biomass, because its concentrations are not
significantly below half-saturation values.
Effect of waterflow on the modeled ecosystem was investigated. Flow monitoring data
and hydrodynamic simulations indicate that the discharge does not fall below 400 m3/sec in
the Lower Don system during the growing season. At times the discharge may reach as high
as 1800 nrvVsec in the beginning of spring (e.g., 1979), but after a short time it decreases to
about 500-600 m3/sec. A discharge of 600 m3/sec was chosen as the baseflow. The model
72
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was run with the same input data set, except discharges were changed to 400 and 1000
m3/sec (see Fig. 2). It appeared that the maximum concentration of phytoplankton biomass
does not change significantly with flow. Values were close to those at the upstream
boundary. Even increasing travel time when discharge is low did not cause intensive
blooming of phytoplankton. We attempted to estimate the influence of flow redistribution
between branches on phytoplankton dynamics at the mouth of the Don River. As described
above, significant changes in distribution of flow can be caused by errors in specifying
hydrodynamic boundary conditions. During water quality simulations, however, only slight
deviations in biomass (2% of maximum value) were discovered. It should be noted that only
part of the Don River mouth was modeled, and travel time along the branches did not
increase sufficiently to allow phytoplankton to bloom.
Observations indicate that phytoplankton distribution is very uneven along and across
the river. Near the banks, concentrations of phytoplankton biomass may be very high.
Simulation of this phenomenon with a 1-D model is difficult and because hydrological and
hydrodynamic data are sparse, 2-D modeling is not feasible. It is possible, nevertheless, to
estimate probable effect of phytoplankton spots on average phytoplankton concentrations on
this reach of the river under certain assumptions. It was assumed that the five upstream
segments of this part of the Don River are connected with shallow pools, where
concentrations of phytoplankton reach their maximum values of nearly 6-7 mg/L.
Phytoplankton from these pools may be transported to the main channel by dispersion.
Simulations including this extra load of phytoplankton did not result in significantly higher
phytoplankton biomass concentrations in the main channel. Maximum concentrations
increased only about 7%. Hence, a major part of phytoplankton biomass comes from
upstream, and is not significantly augmented by phytoplankton that may disperse into the
main river channel from shallow waters near the banks.
MODEL TESTS
Hydrologic data on water stage applicable in modeling are available only on the
segment of the river from Razdorskaya to Rostov-on-Don. Therefore, simulations were
conducted for this part of the river. Hydrodynamic model parameters were identified for July
1-10, 1979, and the model was run to simulate the system for this period. In other tests, the
model was run with an input data set corresponding to February 5-15 and September 1-10.
Modeling results compared well with observed data; the difference between simulated and
measured values of stages did not exceed 5%. The period of simulation, corresponding to
March 1-10, 1979, seemed to be a good start. During this time of year snow starts to melt
on the watershed of the Lower Don River system, and lateral inflows are a significant part of
the river total flow. Simulations were conducted with zero lateral inflows to the segments,
because the real values of lateral inflows were unknown. As a result, simulated values of
stages were less than observed values by about 30% in the middle segments of the river.
Sediment transport simulation was conducted with hypothetical data because of lack
of real data. The model was run for data corresponding with particle sizes from 0.07 to 0.20
mm. Results of simulation showed that the river capacity for sediment transport is very
uneven from segment to segment. The capacity is high for the marginal segments, and lower
in the middle portion of the river. Results conform with the fact that shoaling is proceeding
73
-------
I
o
o
o
•cH
II
a
o
o
0)
o
o
o
t-l
0)
^1
0)
-M
PL,
0)
en
en
J3
tn
o
o
0)
Pi
(H f
CM
en
74
-------
very intensively in the Lower Don River system. Sediment transport capacity depends on the
size of the particles. Sand, with diameter of particles about 0.07 mm, is transported with the
discharge from 0.002 up to 0.036 rrvVsec. For particles with a diameter of 0.20 mm, the
discharges are significantly less and vary from 0.004 up to 0.005 m3/sec. Sediment
discharges in shallower branches are higher than the deeper ones by about 2.5 times.
CONCLUSIONS
Modeling results and experimentation with simulations on the Lower Don River system
led to come conclusions that are helpful in planning future investigations. First of all, more
detailed morphometric information on the'mouth of the Don River is needed. Additional
information is required concerning channel segment lengths, depth, widths, and bottom and
surface slopes of branches and creeks in the delta and particularly near the junction of the
Don with inflowing and outgoing branches at the mouth. Discharges and/or water stages
need to be measured at the junctions as well. Also, stage or discharge near the Taganrog
Gulf have to be measured with the same frequency as those at the upstream of the Lower
Don River system for boundary condition specification.
Simulation of eutrophication processes showed that the main factor controlling
phytoplankton dynamics is the river discharge. The river flow is sufficient to inhibit intensive
phytoplankton blooms in the portion of river from Razdorskaya to the Azov Sea. According to
the data, most phytoplankton biomass passing through this reach comes from upstream.
These primary water quality simulations allow us to draw only general conclusions about
some features of the ecosystem. To estimate the eutrophication level at the Don River
mouth, the stretch of river from Dugino to the Taganrog Gulf has to be studied in more detail.
For this purpose, information about the segment should be collected as well as about the
whole Lower Don River system. For a comprehensive study, the data collection plan should
include gathering information about phytoplankton dynamics and nutrient cycle with at least 2
week frequency and at 10 km intervals along the river. Quantitative information about
phytoplankton species composition can also be very useful. Additional study of macrophyte
distribution and their role in the eutrophication process would be very helpful in simulating
phytoplankton and nutrient dynamics more accurately.
REFERENCES
Ambrose, R. B., T. A. Wool, J. P. Connoly and R. W. Schanz. 1988. WASP4, a
hydrodynamic and water quality model-model theory, user's manual, and
programmer's guide. U.S. Environmental Protection Agency (U.S. EPA), US
EPA/600/3-87/039, Athens, GA.
Hosseinipour, E. Z. and J. L. Martin. 1991. RIVMOD-a one-dimensional hydrodynamic and
sediment transport model. Model theory and user's manual. South Florida Water
Management District, West Palm Beach, FL.
75
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Jorgensen, S. E. 1986. Developments in ecological modeling. Pages 37-53 in Agricultural
nonpoint source pollution: modeling and application. Elsevier, Amsterdam, The
Netherlands.
Yereschukova, M. G., E. Z. Hosseinipour, R. B. Ambrose, R. C. Russo, A. M. Nikanorov and
V. V. Tsirkonov. 1992. A hydrodynamics and water quality modeling study of the
Lower Don River, Russia. Final Report 02.02-12, Environmental Research
Laboratory, U.S. EPA, Athens, GA.
76
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EARLY DEVELOPMENT OF STRUCTURE-ACTIVITY
RELATIONSHIPS FOR ENVIRONMENTAL
TOXICOLOGY IN RUSSIA
Robert L. Lipnlck1, Vladimir A. Fttov2, and
Rosemarte C. Russo3
ABSTRACT
Quantitative structure-activity relationships have proved to be an essential tool in
assessing the risks to humans and the environment from exposure to industrial organic
chemicals. One of the pioneers in the application of structure-activity relationships to
toxicology was Nikolai Vasilyevich Lazarev (1895-1974) at the Leningrad Institute of
Industrial Hygiene and Worker Safety. Among his accomplishments was the
recognition that toxicity could be limited by water solubility, a finding that has been
applied decades later by the U.S. Environmental Protection Agency in defining an
appropriate set of tests for a chemical under review. His pioneering work, then,
presaged modern approaches in drug design and the assessment of toxicological
effects to man and to organisms in the environment.
INTRODUCTION
Of increasing international concern is our ability to Identify those untested
industrial organic chemicals likely to have the potential to produce adverse effects to
human health and to the environment. Even with active international cooperation
and data sharing, resources are not likely to be adequate in the foreseeable future to
test all industrial chemicals for all possible effects. For this reason, environmental
regulatory agencies need scientifically defensible methods for setting testing priorities.
Ideally, one would like to be able to write the structure of an organic
compound and use this information to predict its spectrum of possible or likely
1U.S. Environmental Protection Agency, Office of Pollution Prevention and Toxics (TS-796),
Washington, DC 20460, USA.
"Department of Chemistry, Biology and Toxicology of Anti-tumor Compounds, Petrov Research
Institute of Oncology, Leningradskaya St. 68, Pesochny-2, St. Petersburg 189646, Russia.
3U.S. Environmental Protection Agency, Environmental Research Laboratory, College Station
Road, Athens, GA 30613, USA.
77
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lexicological effects. Such approaches-referred to as quantitative structure-activity
relationships (QSAR)--have been used for some time in pharmacology, and are
becoming of increasing importance in toxicology.
Under Section 5 of the Toxic Substances Control Act, the U.S. Environmental
Protection Agency is authorized to asssess, prior to their manufacture, what risks new
industrial chemicals may pose to human health and the environment. Under this
legislation, however, the chemical manufacturer is not required to provide EPA with
any data other than that in its files at the time of the submission. EPA scientists must
then determine if a case can be developed as to why testing needs to be performed
prior to introductbn of the chemical into the marketplace. A parallel chemical
selection and review process exists for chemicals already in commercial production.
Structure-activity relationships have provided an essential tool to EPA in meeting these
statutory requirements, for the more than 20,000 cases thus far reviewed.
In 1975 (WHO, 1979), an international symposium Methods Used In the USSR for
Establishing Biologically Safe Levels of Toxic Substances was held in Moscow,
sponsored by the World Health Organization. Part of the Symposium was devoted to
estimations of toxfclty from physicochemical properties and chemical structure, which
made reference to the pioneering work of Nikolai Vasilyevich Lazarev (1895-1974) (Fig.
1) in Leningrad. Lazarev's contributions have been extensively cited in a Russian
toxicology textbook (available in English) by four of his students (Fitov, et al., 1979).
Fig. 1 Portrait of Nikolai Vasilyevich Lazarev (courtesy of V.A. Fitov).
78
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LA2AREVS PIONEERING STUDIES
DEVELOPMENT OF INDUSTRIAL HYGIENE STANDARDS
Lazarev's application of structure-activity relationships to toxicology provided
the foundation for the development of industrial hygiene standards in the Soviet Union
(Lipnick and Fitov, 1992). White leader of a group of toxicologists at the "Krasny
Treugolnik" (Red Triangle), Lazarev became interested in developing generalizations
about the toxicity of simple nonetectrolytes based upon his work on petroleum
hydrocarbons (Lazarev, 1931). He continued this work at the Leningrad Institute of
Industrial Hygtene and Worker Safety, where in 1932 he began serving as head of the
toxicology laboratory. He and his co-workers studied the toxicity of over 200 industrial
chemicals at this Institute from 1941. During these studies, they also discovered
systematic relationships between the chemicals' potency and certain
physicochemical properties. These relationships were documented in a number of
books (Lazarev and Astakhantsev, 1933; Lazarev, 1938, 1940, 1941, 1944, and 1958).
LAZAREV'S DATABASE
In an effort to investigate the Interrelationship of various physicochemical
properties such as water solubility, partition coefficient, boiling point, and molar
refractivity to one another, Lazarev assembled an extensive set of data from the
literature for his analyses. In his 1944 monograph (Lazarev, 1944) Nonelectrolytes,
subtitled Quantitative Classification of Biological, Physical, and Chemical Properties
(Fig. 2), he used these data to develop a systematic approach for the classification of
nonelectrolytes.
GROUP NUMBER
Lazarev confirmed the earlier discovery made independently by Meyer (Lipnick,
1989a) and Overton (Lipnick, 1986; Overton, 1991) that the partition coefficient
between water and an immiscible organic phase provides the most useful property for
describing the biological activity of simple nonetectrolytes. For the sake of simplicity,
Lazarev proposed the use of a classification system involving nine groups. He chose
the olive oil/water partition coefficient as the basis for his physicochemical
classification of nonelectrolytas. Compounds belonging to group 1 (the most
hydrophilic compounds), were termed weak nonelectrolytes. This group includes
compounds for which log K,,,/^., falls within the range of -3 to -2. In Lazarev's group
number system, the most hydrophobic compounds were classified as group 9. These
were termed strong nonelectrolytes and have log «<„,„,«„,„ values within the range 5 to
6.
Fig. 3 shows a plot of the relationship between Lazarev's Group Number and
chain length for nine different homologous series of compounds. Lazarev found this
type of systematic behavior very useful for predicting the Group Number for
compounds for which measured values were not available, and which is analogous to
the re- and fragment constant systems for estimating partition coefficient from
chemical structure (Hansch and Leo, 1979; Rekker, 1977; Rekker and Mannhold, 1992).
Once he was able to establish relationships between Group Number and biological
79
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MEAHKO-CAHHTAPHOE VtlPABJlEHHE BM<&
BOEHHOMOPCKAH MEflHUHHCKAH AKAflEMHH
nojIKOBHHK MCA. CJiyivfibl
npo<|). H. B. JIA3APEB
H E 9 JI E K T P 0 JI H T bl
OFlblT EMO;iOrO-H3HKO-XMMMMECKOfi
MX CHCTEMATHKH
H 3 A A H H E
BOEIIHO-MOPCKOA MEAHUHHCKOfl AKAAEMHH
HEHHHTPHH 1*44
*
Fig. 2 Title page of Neelektrollty (courtesy of the Library of Congress).
transport and response, this method of estimating partition coefficients became
critical for the application of predictive methods in toxicology.
USE OF A LOG-LOG SCALE
Lazarev investigated relationships between partition coefficient and biological
activity graphically using log-log plots. Such plots provided the means to compare
data over nine orders of magnitude, and presaged the use of logarithmic
transformations in the development of extrathermodynamic linear free energy
relationships (Leffler and GrunwakJ, 1963) and quantitative structure-activity
relationships (Hansch and Leo, 1979).
80
-------
CD
O
CO
E
o
c
o
u
<« —
o
t_
CD
.O
E
3
KOIL/WATER
123456789
Group
Fig. 3 Relationship between Lazarev's Group Number and chain Jength for nine
different homologous series of compounds (adapted from Fig. 4, Lazarev, 1944).
SOLUBILITY IN WATER
A typical plot from Neelektrollty is shown in Fig. 4, depicting the relationship
between water solubility and oil/water partition coefficient. The data have been
presented as partition coefficient ranges defined by Lazarev's Group Number with the
lowest and highest water solu-bilities within each of these Groups represented by
open and closed circles, respectively. Fig. 5 is a similar plot, with data on compounds
whose molecular weight is less than 100 Daltons. In this case, the correlation is much
better4. In contrast, Lazarev found that the relationship between group number and
log Kwcrt
-------
CORRELATION OF GROUP NUMBER WITH TOXICITY
Fig. 6 shows a log-log plot of ocular irritation and tongue irritation versus group
number. In each case there is an increase (i.e., lower concentrations of test
substance are required to produce a standard toxlcotogical response) in irritant action
with increasing group number. Similarly, Fig. 7 presents a log-log plot of hypnotic dose
of urea derivatives as a function of log
Lazarev was able to demonstrate similar graphical relationships between
partition coefficient or water solubility for various other effects such as arrest of
Isolated frog heart, contraction in isolated segments of frog heart ventricle, paralysis of
isolated rabbit intestine, narcosis in tadpoles and small fishes, and concentration in
mammalian blood associated with changes in reflex time, narcosis, respiratory failure,
or death.
EFFECT OF METABOLISM ON ELIMINATION
Lazarev recognized that an important function of metabolism was to Increase
the rate of elimination of foreign substances by decreasing their lipophlUcity, as
|2
^^*
cn 1
CT>
O
-•o
-1
-2
-3
COMPLETE MISCIBILITY
-421
50
oAVERTIN
I I I I I
0 12345
K
-3 -2
I nn k
OIL/WATER
1 23456789
Group
Fig. 4 Relationship between water solubility and oil/water partition coefficient
(adapted from Fig. 10, Lazarev, 1944).
82
-------
E
en
o
0
-1
-2
-3
MI5CIBLE
-045"
'-048
-072
I I I I
-3-2
0
K
OIL/WATER
23456
Group
2 34 5
789
Fig. 5 Relationship between water solubility and oil/water partition coefficient for
compounds with molecular weight less than 100 Daltons (adapted from Fig. 12,
Lazarev. 1944).
illustrated In Fig. 8. Thus, benzene upon its biotransformation to phenol and then to
hydroquinone changes from group 6 to group 2. Similarly, metabolism of ethytene
glycol to oxalic acid produces a change from group 2 to group 1.
MATHEMATICAL PREDICTIVE MODELS
From his data base and log-log plots, Lazarev derived mathematical models
relating partition coefficient to physteochemteal properties. In vttro effects, and In vivo
effects.
Physlcochemical propwttot
to9 Kb^^/wo*. = 1 -06 tog K01/walw + 0.32
tog S = -0.89 tog K,,,/,,^^- 3.15, where S = Solubility in water (mmol/L).
In VHm effects
tog Ch9mot^ = -0.62 log K^/^,^, + 2.45, where C = Effect concentration (mmol/L).
83
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In Vivo effects
tadpoi, narco*
-°-69 log
+ 1 .06. where C = Effect concentration
(mmol/L).
tofl ctadpoie norco* = °-72 tog S - 1 .04, where C = Effect concentration (mmol/L).
!°9 Ccc****** = °-72 toQ s - O-60' where C =. Effect concentration (mmol/L).
Although these models were apparently not derived using regression analysis,
they serve the same function as that served today by certain statistically-derived
QSAR models in predictive toxicology (Lipnick 1990).
WATER SOLUBILITY CUTOFF
Lazarev, like Overton, recognized that toxicity could be limited by water
solubility. Lazarev appears to be the first to have represented this phenomenon
graphically, and to have predicted the cutoff point by solving the two tog-log
4
3
§2
E
0
3,89
3.61
3.13
2.0
Tongue Irritation
.62
1.180
Chloral
0.70°
Phenol
0.98
Ocular Irritation
.30
20
-3 -2
\
-1012
L°9 K OIL/WATER
7
8
23456
Group
Fig. 6 Relationship between Lazarev's Group Number and ocular and tongue irritation
(adapted from Fig. 57, Lazarev, 1944).
84
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functions of partition coefficient.5 A graph showing this cutoff for In vitro hemolysis is
depicted in Fig. 9.
USE OF THE WATER SOLUiUJTY CUTOFF IN EPA ENVIRONMENTAL ASSESSMENTS
The solubility-based cutoff in toxicity discussed above has been applied in a
practical way in defining an appropriate set of tests for a chemical under review. For
example, for simple nonetectrolytes acting by a non-specific mechanism such as the
ones Lazarev used in his models, the concentration C (moles/L) producing narcosis in
the tadpole Rana temporarla can be described by the following QSAR model
(Lipntek, 1989b), expressed as the Hansch convention (reciprocal of biological
activity):
tog (1/C) = 0.909 tog P + 0.727, where P = octanol/water partition coefficient.
As an example of the use of this relationship and the solubility cutoff criteria
discussed previously, experimental toxicity tests show that phenanthrene produces
tadpole narcosis at 2 mg/L, which compares well with the QSAR prediction of 2.78
mg/L. Thus, for phenanthrene, the toxicity effect occurs close to, but does not
exceed, the water solubility (Lipntek, 1989b):
Log P (octanol/water)6 = 4.49
Melting point * 97.5 to 98.5°C
Water solubility = 3.3 mg/L
Molecular weight = 178.22
Similarly, Lazarev's oil-water correlation predicts effects at 1.5 mg/L; his solubility
correlation at 0.9 mg/L. Therefore, no soRjblHty cutoff for phenanthrene should have
been expected.
On the other hand, anthraquinone shows no effect at saturation for the same
test. This should not be surprising since with a melting point of 286° and log P
(octanol/water) value of 2.72, the predicted water solubility is 0.051 mg/L, which is
greatly exceeded by the predicted toxic concentration from the above QSAR of 132
mg/L.
Log P (octanol/water) = 2.72
Melting point = 286°C
Water solubility (est.) = 0.051 mg/L
Molecular weight = 208.22
Therefore, the solubility cutoff should be anticipated for this chemical.
5The position of this cutoff would shift to lower group numbers as a function of increasing melting
point for liquid solutes (Ljpnfck, 1990).
"Calculated using the CLOGP computer program, Version 3.3 (Leo and Weininger, 1985)
85
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CONCLUSION
Nikolai Vasilyevich Lazarev was clearly a scientist ahead of his time. The
methods that he pioneered were not widely known outside of Russia, but presaged
modern approaches in drug design and the assessment of toxlcotogical effects to
man and to organisms in the environment.
REFERENCES
Banerjee, S., S.H. Yalkowsky, and S.S. Valvani. 1980. Water solubility and octanol/water
partition coefficients of organics. Limitations of the solubility-partition coefficient
correlations, Environ. Sci. Technol., 14, 1227-1229.
Filov, V.A., A.A. Golubev, E.I. Liublina, and N.A. Tolokontsev. 1979. Quantitative
Toxicology. John Wiley, New York.
Hansch, C. and A. Leo. 1979. Substituent Constants for Correlation Analysis in
Chemistry and Biology. Witey-lnterscience, New York.
en
°5
en
o
O
u
o
c.
a.
"
0
-0.5
-3
-2
0
LogK
'HEXANE/WATER
Fig. 7 Relationship between intraperitoneal hypnotic dose of urea derivatives to white
mice and hexane/water partition coefficient (adapted from Fig. 74, Lazarev,
1944).
86
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-3
8
Fig, 8 Effect of metabolism on decreasing lipophilicity for benzene, toluene,
ethylbenzene, xytene, methanol, and ethytene glycol (adapted from Fig. 75,
Lazarev, 1944).
Lazarev, N.V. 1931. Benzin kak Promyshtennyi lad (Benzene as an Industrial Toxicant),
Sotsekgiz.
Lazarev, N.V, and P.I, Astakhantsev. 1933. Khimicheski Vrednye Veshchestva v
Promyshtennosti. 1. Organlcheskie Veshchestra (Harmful Chemical Substances in
Industry. 1. Organic Substances), Khkntekhizdat.
Lazarev, N.V. 1938. Obshchiye Osnovy Promysgkebbiu Tokslkotogii (General Principles
of Industrial Toxicology), Medgiz.
Lazarev, N.V, 1940. Narkotiki (Narcotics), Institut Gigiyeny Truda I Profzabotevaniy.
Lazarev, N.V. 1941. Biologischeskoye Deistviye Gazov pod Davleniyem (Biological
Action of Gases Under Pressure).
87
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lazarev, N.V. 1944. Neetekrolity (Nonetectrolytes). Voennomorskaya, Medicinskaya
Akademiya.
Lazarev, N.V. 1958. Obshchee Ucheniye o Narkotikakh i Narkoze (General Theory of
Narcotics and Narcosis) Voenno-Morskaya Meditsinskaya Akaderniya.
Leffler, J.E. and E. GrunwakJ. 1963. Rates and Equilibria of Organic Reactions John
Wiley, New York.
Leo, A. and D. Weininger. 1985. Medchem Software Release 3.33, Medicinal
Chemistry Project, Pomona College, Ctaremont, CA.
Lipntek, R.L. 1986. Charles Ernest Overton. Narcosis Studies and a Contribution to
General Pharmacology. Trends Pharmacol. Sci., 5, 161-164.
Lipnfck, R.L. 1989a. Hans Horst Meyer and the LipokJ Theory of Narcosis. Trends
Pharmacol. Scl., 10, 265-269.
o
en
o
-2
_ -4.93
104
-2
0
2 3
OIL/WATER
567
8
Group
Fig. 9 Relationship between water solubility (solid circles and solid line) and In vitro
hemolysis (open circles and dashed line) as a function of oil/water partition
coefficient. The point of intersection represents the highest partition coefficient
or lowest water solubility at which hemolysis is not water solubility limited
(adapted from Fig. 64, kazarev, 1944).
88
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Lipnick, R.L. 1989b. A quantitative structure-activity relationship study of Overton's
data on the narcosis and toxicity of organic compounds to the tadpole, Rana
temporarla, in Aquatic Toxicology and Environmental Fate: Eleventh Volume
(G.W. Suter, II, and M.A. Lewis, Eds.), ASTM STP 1007, American Society for
Testing and Materials, Philadelphia, pp. 468-489.
Lipnick, R.L. 1990. Narcosis: fundamental and baseline toxicity mechanism for
nonelectrolyte organic chemicals. In W. Karcher and J. Devillers (Eds.) Practical
Applicatbns of Quantitative Structure-Activity Relationships (QSAR) in
Environmental Chemistry and Toxicology. Kluwer, Dordrecht.
Lipnick, R.L. and V.A. Fitov. 1992. Nikolai Vasilyevich Lazarev, toxteobgist and
pharmacologist, comes in from the cold. Trends Pharmacol. Sci., 13, 56-60.
Overton, C.E. 1991. Studies of Narcosis. (R.L. Lipnick, Ed.), Chapman and Hall,
London.
Rekker, R.F. 1977. The Hydrophobic Fragmental Constant. Ebevier, Amsterdam.
Rekker, R.F. and R. Mannhold. 1992. Calculation of Drug Lipophilicity. VCH,
Weinheim.
WHO, World Health Organization. 1975. Methods Used in the USSR for Establishing
Biologically Safe Levels of Toxic Substances. World Health Organization,
Geneva, Switzerland.
89
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MERCURY CONTENT AND ULTRASTRUCTURE OF GILLS
AND SCALES OF FISH FROM LAKES IN NORTH AND NORTHWESTERN
RUSSIA THAT ARE POLLUTED BY ATMOSPHERIC DEPOSITION
Terry Haines", Victor Komovb, Charles Jagoec, and Victoria Mateyb
ABSTRACT
Field studies were conducted of lakes in Darwin National Reserve in 1989, and in Karelia
in 1991. Darwin National Reserve is 300 km north of Moscow at the west end of Rybinsk
Reservoir. The terrain is generally flat and consists of thick sandy till covered with hardwood
forest. Karelia is north of St. Petersburg and consists of hilly terrain underlain with precambrian
bedrock. In each case, remote lakes were visited and sampled for water and fish, primarily perch
Perca fluviatilis. Water samples were analyzed for pH, color, specific conductance, and major
cations and anions. Fish were weighed and measured, dorsal muscle tissue was collected and
analyzed for mercury, and gills and scales were sampled for examination by light and electron
microscopy. In both locations acidic lakes (acid neutralizing capacity <0) were common. Acidic
lakes were both clear and colored and the dominant anion in both types was sulfate, indicating
that the lakes were acidic because of atmospheric deposition of strong acids and not because of
organic acids. Mercury content of fish was increased in acidic and in colored lakes. Mercury
appears to enter the lakes by atmospheric deposition, as there are no local sources. Organic acids
are believed to increase mercury bioavailability in lakes by transporting mercury from terrestrial
regions and possibly contributing to methylation. Also, mercury methylation is probably enhanced
in acidic lakes, increasing bioavailability. Gills of perch from acidic lakes had thicker lamellar
epithelia and more ion-transporting cells than those collected in circumneutral lakes. The density
of microridges on gill surfaces was reduced in perch from acidic lakes. These differences in gill
structure serve to decrease gill surface area, increase diffusion distances, increase active ionic
influx, and represent responses that allow perch to inhabit acidic waters. Scales of perch from
acidic lakes had little or none of the pattern of ridges at the foci observed in scales of perch from
higher pH lakes. This probably results from development and growth in low pH, low Ca water,
and may be a useful indicator of stressful acidic conditions during early life stages.
"U.S. Fish and Wildlife Service, National Fisheries Contaminant Research Center, Field Research
Station, 313 Murray Hall, University of Maine, Orono, Maine 04469 USA
Institute for Biology of Inland Waters, Academy of Sciences of Russia, 152742 Borok, Nekouz,
Yaroslavl. RUSSIA
"University of Georgia, Savannah River Ecology Laboratory, P.O. Drawer E, Aiken, South Carolina
29802 USA
90
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INTRODUCTION
Atmospheric transport and deposition of contaminants is a world-wide problem. The
importance of atmospheric transport in contamination of aquatic ecosystems was first documented
for emission of acidic gases such as sulfur oxides and nitrogen oxides and the deposition of strong
acids, which resulted in water acidification and loss of fish populations (Schindler 1988). This
process is also important in the mercury contamination of fish in waters of low acid neutralizing
capacity (ANC) in northern Europe and North America (Lindqvist et al. 1991; Spry and Wiener
1991). Further, lake acidification increases mercury concentration in fish (Grieb et al. 1990;
Hakanson et al. 1990; McMurtry et al. 1989).
Atmospheric deposition of sulfur compounds in Europe has been estimated using a model
developed by the Cooperative Programme for Monitoring and Evaluation of the Long Range
Transmission of Air Pollutants in Europe (EMEP). The results of this model give a deposition rate
of 800-1,640 eq S/ha per year for northern Russia, which is comparable to or exceeds deposition
rates for regions in Scandinavia where lake acidification and fish mercury accumulation has
occurred (Chadwick and Kuylenstierna 1991). In undertaking this study, our objectives were to
confirm the previously reported presence of clear-water and brown-water acidic lakes in two areas
of Russia to determine whether fish inhabiting these lakes contained elevated levels of mercury,
and to determine whether these fish exhibited symptoms of damage from acidity.
METHODS
This study was conducted in two phases. In May and June 1989 we sampled lakes in
Darwin National Reserve, Yaroslavl Region, and in June 1991 we sampled lakes in the Karelia
Autonomous Republic (Figure 1). Darwin National Reserve is a protected natural area created in
1943, located at the western end of Rybinsk Reservoir. It is characterized by thick tills and sandy
soils (Ager 1980), and the lakes are primarily precipitation-dominated seepage lakes. In Karelia
we visited lakes in the vicinity of Suoyarvi, which were primarily highly colored lakes, and lakes in
the vicinity of Kondopoga, which were primarily clear-water lakes. Both areas were underlain by
granitic bedrock covered with thin soil (Ager 1980), and the lakes were primarily drainage lakes.
Most lakes were in forested catchments with no dwellings or roads. An exception was Suoyarvi
Lake, which has a settlement at the southern end.
At each lake, a water sample was collected by immersion of cleaned polyethylene bottles
just below the surface near the point of maximum depth. Bottles were tightly capped, held in the
dark, and within a few hours analyzed for pH (Orion model SA210 meter equipped with a Ross
combination electrode), ANC (acid neutralizing capacity, measured by inflection point titration),
and true color (visual comparison with platinum-cobalt standards). The remaining water sample
from each lake was refrigerated and later analyzed for major cations and anions. Calcium,
magnesium, and sodium were determined by flame atomic absorption spectropho tome try, chloride,
fluoride, sulfate, and nitrate by ion chromatography, and total aluminum by graphite furnace
atomic absorption spectrophotometry.
Perch (Perca fluviatilis) were collected by angling from various points around the shoreline
of each lake, except for Suoyarvi Lake, where fish were captured in a gill net set overnight. The
second and third gill arches were dissected from each fish and fixed in either 0.1 M cacodylate
buffer, pH 7.3, containing 2.5% glutaraldehyde, or in 0.1 M HEPES buffer, pH 7.4, containing 1%
glutaraldehyde, 4% formaldehyde, and 5% sucrose. Fish were then placed in plastic bags and
frozen (-5°C) within a few hours, and remained frozen until they were analyzed for mercury. Fish
and fixed gill tissue were transported to the Institute for Biology of Inland Waters, Borok, in 1989,
and the Institute for Research on Northern Fishes, Petrozavodsk, in 1991.
At the laboratories, the fish were thawed, weighed to the nearest gram, and measured
(total length) to the nearest millimeter. Scales were removed from the left side of the fish adjacent
to the dorsal fin and placed in paper envelopes for future ultrastructure determination. Fish were
91
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T3
3
O
S
O
c
o>
2
to
I
IJJ
•s
Q.
92
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placed on an acid-washed plexiglass plate and a 2- to 3-g sample of skeletal muscle was dissected
from the left side of the fish, adjacent to the dorsal fin and extending from the rib cage to the
center of the dorsal surface. All dissecting instruments were stainless steel, and all instruments
and glassware were cleaned with 10% nitric acid and rinsed with distilled water.
Moisture content of muscle tissue was determined by placing a portion of the tissue in a
dried, tared glass dish and weighing before and after drying at 105°C. The remaining tissue,
typically 1 to 2 g, was placed in a tared glass beaker, weighed, and digested in a 1:1 mixture of
nitric acid and hydrogen peroxide (FAO/SIDA 1983).
Fish were processed in batches of 5 to 10. Two fish from each batch were randomly
selected for use in determination of accuracy and precision of mercury determination. For these
fish, the tissue was divided into two nearly equal portions. A known amount of mercury standard
solution was added to one portion of tissue, and all portions were digested and analyzed. A sample
of National Institute of Science and Technology (NIST) tuna reference material and a reagent
blank was included with each batch of samples. After digestion, solutions were cooled and diluted
to 25 ml with distilled water, and 1- to 2-ml portions were analyzed for total mercury with a gold
film analyzer (Arizona Instrument Co., Jerome, Arizona USA). Each digestate was analyzed in
duplicate. Mercury in all samples exceeded our calculated detection limit of 5 ng. The recovery of
mercury from spiked samples averaged 95.4% (range 90-102%). The percent difference between
replicate samples averaged 2.9% (range 1.7-5.2%). The measured mercury content of NIST tuna
averaged 0.93 /Ag/g (range 0.88-0.96 /ig/g), and all analyses were within the certified range for this
material.
Gill tissue was postfixed in buffered OsO4 for two hours and dehydrated through a graded
ethanol series into absolute acetone. Whole gill arches were critical point dried under liquid CO2,
sputter-coated with gold, and examined using a JEOL JSM-25S electron microscope operated at 15
KV. Scales were first placed in glass vials with 5% NaOH for 6-12 h, then hydrolyzed in a
saturated solution of K2Cr2O1 in 10% NaOH for 1-7 d. The scales were then washed in distilled
water until all yellow color was removed, placed in 3:1 mixture of absolute ethanol and acetone
and then in absolute acetone for 10-15 min each, air dried, mounted on stubs, and coated with gold
and examined in the same manner as were gills.
RESULTS
The lakes surveyed varied in pH from 4.6 to 8.1 and in color from 3 to 188 Hazen (Figure
2, Table 1). Drainage and seepage lakes were relatively uniformly distributed over the range of
color values, but all seepage lakes surveyed were acidic (pH <5.0). The lakes in Darwin Reserve
were predominately seepage lakes whereas the lakes in Karelia were predominately drainage
lakes.
The fish collected ranged in weight from 8 to 515 g, and in mercury content from 0.06 to
3.04 /ig/g wet weight (0.76-17.9 pg/g dry weight) (Table 2). Omitting two unusually large fish from
Tyomnoye Lake reduces the maximum weight to 196 g and the maximum mercury content to 1.03
/ig/g wet weight (6.87 /*g/g dry weight). Fish mercury content was correlated with fish size,
especially weight (R2=0.32, p=0.0001); therefore the least square mean mercury concentration,
which represents fish mercury concentration normalized by fish weight, was computed by analysis
of covariance using weight as the covariate.
Plotting fish mercury concentration against lake pH and color (Figure 3) indicates that fish
from high pH lakes have relatively low mercury content regardless of lake color but in low pH
lakes fish mercury content increases with lake color. Accordingly, stepwise regression analysis was
performed using the non-intercorrelated variables pH, color, and sulfate, with the data stratified
by lake drainage type. The results (Table 3) indicate that color is more important in the
regression than is pH for seepage lakes, and that the relation between fish mercury and lake pH is
not significant in the absence of color data for drainage lakes. The inclusion of lake sulfate did not
significantly improve the regression for seepage lakes.
93
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TABLE 1. PHYSICAL AND CHEMICAL CHARACTERISTICS OF THE STUDY LAKES.
Lakes
Darwin Lakes
Dorojiv
Dubrovskoye
Hotavets
Motykino
Rybinsk
Tyomnoye
Uteshkovo
Karelia Lakes
Blue Lamba
Chuchyarvi
Grushna Lamba
Ilyakalkenyarvi
Kabozero
Lamba Vegarous
Leukunyarvi
Sargozero
Suoyarvi
Uros
Vegarousyarvi
Venderskoye
Vuontelenyarvi
Mean Values
Drainage Lakes"
Seepage Lakes
Area
(ha)
200
20
160
2
395,000
20
5
307
112
3
104
210
7
-
200
6,070
426
1,880
998
394
1,045
84
Depth
(m)
3
2
3
4
30
2
3
4
5
5
6
3
4
-
4
5
3
5
6
3
4.2
3.5
Drainage
Type
Seepage
Seepage
Drainage
Seepage
Impoundment
Seepage
Seepage
Seepage
Seepage
Seepage
Drainage
Drainage
Drainage
Drainage
Drainage
Drainage
Drainage
Drainage
Drainage
Drainage
Drainage
Seepage
Color
(Hazen)
13
182
188
19
55
70
150
3
8
3
171
141
182
182
25
104
9
105
23
186
120
56
PH
4.6
4.6
8.1
4.8
8.0
4.7
4.8
4.6
5.0
4.6
4.6
5.5
4.5
4.9
7.9
5.8
5.9
5.1
7.0
4.6
5.8
4.7
ANC
(/teq/1)
-41
-50
227
-38
1,369
-53
-33
-17
-9
-19
-25
13
-39
-9
252
23
16
-2
167
-24
56
-33
S04
Oieq/1)
71
64
32
49
420
52
29
67
48
48
54
60
75
68
29
83
72
49
44
68
58
53
'Rybinsk omitted.
95
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TABLE 2. MEAN AND RANGE OF FISH WEIGHT, MOISTURE CONTENT, AND MERCURY
CONCENTRATION IN FISH, AND LEAST SQUARE MEAN MERCURY CONCENTRATION IN
FISH FROM THE STUDY LAKES.
Lake
Blue Lamba
Chuchyarvi
Dorojiv
Dubrovskoye
Grushna Lamba
Hotavets
Ilyakalkenyarvi
Kabozero
Lamba Vegarous
Leukunyarvi
Motykino
Rybinsk
Sargozero
Suoyarvi
Tyomnoye
Weight, g
Mean
(Range)
22
(18-28)
59
(18-133)
62
(31-94)
27
(23-30)
38
(28-48)
62
(37-150)
35
(20-78)
35
(24-47)
55
(28-80)
30
(8-54)
60
(43-75)
86
(59-163)
18
(8-27)
98
(53-131)
155
(50-515)
Moisture, %
Mean
(Range)
85.6
(81.1-89.7)
90.6
(83.2-93.9)
80.9
(78.0-86.2)
83.6
(77.8-88.1)
81.5
(76.9-86.0)
88.6
(80.4-93.8)
82.4
(72.0-94.2)
81.5
(61.7-87.2)
80.5
(75.9-85.1)
88.2
(82.8-96.3)
81.4
(79.3-87.9)
80.8
(78.1-82.6)
85.2
(75.0-89.6)
81.5
(79.6-83.6)
79.6
(74.6-83.4)
Mercury, ju.g/g wet weight
Arithmetic Least Square
Mean Mean
(Range)
0.34
(0.26-0.44)
0.10
(0.08-0.13)
0.50
(0.36-0.71)
0.64
(0.56-0.68)
0.30
(0.20-0.43)
0.11
(0.08-0.16)
0.28
(0.19-0.36)
0.31
(0.22-0.39)
0.40
(0.30-0.52)
0.21
(0.17-0.24)
0.57
(0.43-0.97)
0.19
(0.08-0.45)
0.12
(0.09-0.18)
0.29
(0.19-0.38)
1.06
(0.45-3.04)
0.41
0.08
0.47
0.71
0.33
0.09
0.31
0.34
0.39
0.25
0.54
0.11
0.19
0.18
0.56
96
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Uros
Uteshkovo
Vegarousyarvi
Venderekoye
Vuontelenyarvi
19
(14-21)
45
(18-98)
26
(17-45)
41
(12-107)
43
(16-196)
83.7
(76.1-90.3)
80.4
(75.7-85.8)
79.5
(76.9-82.8)
79.8
(72.9-81.0)
84.5
(76.9-93.0)
0.12
(0.06-0.18)
0.78
(0.54-0.97)
0.34
(0.20-0.44)
0.15
(0.10-0.24)
0.53
(0.32-1.03)
0.19
0.80
0.41
0.17
0.54
TABLE 3. STATISTICALLY SIGNIFICANT (P <0.05) REGRESSION EQUATIONS,
CORRELATION COEFFICIENTS, AND PROBABILITY FOR STEPWISE REGRESSION OF
LAKE PHYSICAL AND CHEMICAL VARIABLES ON FISH MERCURY CONTENT. ANALYSES
ARE PRESENTED FOR ALL LAKES, AND STRATIFIED BY DRAINAGE TYPE.
Lake
Type
All
Seepage
Drainage
Number of
Variables
1
2
3
1
2
t
2
3
Equation
-0.0347 PH + 0.317
-0.0336 pH + 0.000144 color + 0.298
-0.0331 pH + 0.000143 color
-0.000019 sulfate + 0.297
0.000711 color + 0.128
0.000671 color - 0.173 pH + 0.946
-0.0260 pH + 0.000030 color + 0.252
-0.0256 pH + 0.0000284 color
-0.0000167 sulfate + 0.251
R2
0.46
0.49
0.50
0.56
0.69
0.68
0.68
P
0.001
0.0035
0.0119
0.0332
0.05
0.0058
0.0216
The structure of the gills of perch has been previously described by Matey (1984). Primary
lamellae or filaments project in two parallel rows from the gill arch, and each primary lamella
supports two rows of secondary lamellae (Figure 4a). The epithelium covering the gill consists
primarily of thin, squamous respiratory cells, along with mucous cells and chloride (ion
transporting) cells, underlain by undifferentiated cells. Most chloride cells occur in the primary
lamellar epithelium, especially in the spaces between secondary lamellae. Normally, the surfaces
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Figure 4. Scanning electron micrographs of normal gill structure. A. Gill filaments with
secondary lamellae. Bar= 1 mm. B. Epithelial surface. Bar= 10 /im.
of the respiratory cells are covered by a well-developed system of microridges, which may serve to
anchor mucus, increase surface area, or create micro-turbulence (Figure 4b). This structural
arrangement is found in most teleost fishes (Hughes 1984; Laurent 1984).
For the Darwin Reserve lakes, all fish examined from Hotavets Lake (pH 8.1) had normal,
well-formed gills. The primary lamellar epithelia contained pavement cells with well-formed
microridges and few chloride cells (Figure 5a), and secondary lamellae were thin and regular
(Figure 5b). Perch from the more acidic lakes (Dubrovskoye, Dorojiv, Motykino, and Uteshkovo
lakes) all had alterations in gill structure. Chloride cell numbers were greatly increased along the
primary lamellae (Figure 5c). Some chloride cells had apical crypts (Figure 5d), which were not
observed in fish from the higher pH lake. Chloride cells were also present on many secondary
lamellae (Figure 5e). Mucus secretion was elevated, as evidenced by increased numbers of mucus
droplets and secretory pores associated with mucous cell activity (Figure 5f). The density of
microridges on the gill epithelia was reduced in fish from the acid lakes compared with fish from
the higher pH lake (Figure 5g; compare with Figure 4b).
For the highly colored lakes in Karelia, fish from lakes of pH <5.5 had thickened and
swollen secondary lamellae (Figure 6a). This phenomenon was especially severe in fkh from
Leukunyarve, Vegarousyarvi, and Lamba near Vegarous lakes, where epithelial hyperplasia
produced regions of fused secondary lamellae (Figure 6b). These fish also often had locally swollen
or evaginated regions on the primary lamellae (Figure 6c), although these abnormalities were not
observed in fish from Ilyakalkenyarvi Lake, which had a pH of 4.6. Chloride cell number on
primary lamellae appeared to increase with decreasing pH, and was greatly elevated in fish from
Vuontelenyarvi, Ilyakalkenyarvi, and Lamba near Vegarous lakes (Figure 6d). In perch from lakes
with pH below 5.1, chloride cells were also abundant on secondary lamellar epithelia (Figure 6e).
99
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Figure 5. Scanning electron micrographs of gills from Darwin Reserve fish. Bar=10 /Ltm in all
cases. A. Primary lamellar epithelium of a fish from a high pH lake, showing respiratory
pavement cells and a lack of chloride cells. B. Secondary lamellar epithelium of a fish from the
same lake as A. C. Primary lamellar epithelium of a fish from an acidic lake showing numerous
chloride cells (arrow). D. Chloride cell with an apical crypt (arrow). E. Secondary lamellar
epithelium of a fish from an acidic lake showing numerous chloride cells (arow). F. Secondary
lamellar epithelium of a fish from an acidic lake showing numerous secretory pores (arrow). G.
Primary lamellar epithelium of a fish from an acidic lake showing reduced microridge density.
100
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Figure 6. Scanning electron micrographs of gills of fish from colored, acidic Karelian lakes. A.
Swollen and thickened secondary lamellae (arrow). Bar=100 /xm. B. Epithelial hyperplasia
(arrow). Bar=l mm. C. Primary lamelar epithelial swelling (arrow). Bar=100 pm. D. Primary
lamellar epithelium with numerous chloride cells (arrow). Bar=100 ^tm. E. Secondary lamellar
epithelium with numerous chloride cells (arrow). Bar=10 p.
101
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Figure 1. Scanning electron micrographs of gills of fish from Karelian lakes. A. Epithelial
hyperplasia leading to secondary lamellar fusion (arrow) in a fish from a colored, acidic lake.
Bar=100 ju.m. B. Cell surface microridge density in a fish from a high pH lake. Bar=10 /u,m. C.
Cell surface microridge density in a fish from a low pH, clear lake. Bar=10 ju.m. D. Cell surface
microridge density in a fish from a low pH, colored lake. Bar=10 ju,.
102
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Alterations in gill structure associated with low pH appeared less severe in fish from clear-
water lakes in Karelia than in those from colored-water lakes. Epithelial hyperplasia leading to
secondary lamellar fusions was observed only in fish from Chuchyarvi, pH 5.0 (Figure 7a).
Secondary lamellae were somewhat swollen and thickened in fish from the lower pH clear-water
lakes. Chloride cell numbers were increased on both the primary and secondary lamellae in fish
from lakes with pH <5.9. Compared with perch from lakes of higher pH (Figure 7b), cell surface
microridge density was slightly decreased in fish from the most acidic clear-water lakes (Figure
7c). In contrast, fish from low pH, colored-water lakes had substantially reduced microridge
patterns, with the typical labyrinth appearance replaced by shorter, smaller surface ridges (Figure
7d).
Perch have typical ctenoid scales (Figure 8a). The scales of perch from Hotavets (pH 8.1)
were characterized by a focus consisting of a number of microridges creating a complex pattern
(Figure 8b). These microridges were lacking in the scales of the fish from lakes in Darwin Reserve
with pH 4.4-4.8 (Figures 8c, 8d).
DISCUSSION
The areas of Russia where we surveyed lakes receive relatively high levels of sulfur
deposition. Karelia receives 420-800 eq/ha/yr, comparable to southern Finland, Sweden, and
Norway, and Yaroslavl region receives 800-1640 eq/ha/yr, comparable to northern Germany
(Chadwick and Kuylenstierna 1991). The critical loading of acidity is estimated at 200 eq/ha/yr or
less for Karelia and 200-500 eq/ha/yr for Yaroslavl region, and deposition is estimated to exceed
critical loading by 500-1000 eq/ha per year in Karelia, but only 200 eq/ha per year or less in
Yaroslavl region (Hettelingh et al. 1991). Consequently, we found no acidic drainage lakes in
Darwin Reserve. The seepage lakes were precipitation-dominated as reflected in the low ion
content, and were not influenced by the chemistry of the soils or surficial material. The acidity of
the seepage lakes in Darwin Reserve reflects the acidity of the precipitation they receive. In
Karelia, both drainage and seepage lakes were acidic. The situation here is similar to that in
Finland, Sweden, and southern Norway, where acidic precipitation falling on a landscape
consisting of resistant bedrock and thin, nutrient-poor soils has resulted in the acidification of
thousands of lakes, with resultant biological effects (Rosseland et al. 1986).
The mercury content of perch from undisturbed lakes in Russia is comparable to that
reported for this species from similar lakes in Sweden and Finland, disregarding the two large fish
from Tyomnoye lake, which had unusually high mercury concentrations. Mercury concentrations
were reported to be 0.2 to 2.0 /Ltg/g dry weight for "small" perch and 0.6 to 6.0 /ig/g dry weight for
"large" perch in Swedish forest lakes (Lindqvist et al. 1991). Mercury content of perch muscle
tissue in 11 Swedish lakes of pH 5.2-6.2 was between 0.04 and 0.29 pg/g wet weight (Paulsson and
Lundbergh 1991). In Finland, mercury concentrations between 0.03-0.53 pg/g in perch from
circumneutral lakes and 0.15-0.63 in fish from acidic lakes have been noted (Verta et al. 1990).
The larger fish from the most acidic lakes in our study approached or exceeded mercury
concentrations believed harmful to fish consumers (Wiener 1987; Grant 1991).
The association of elevated mercury content in fish with low water pH has been widely
reported (Lindqvist et al. 1991; Spry and Wiener 1991). Our results confirm these findings and
extend them to two regions of Russia not previously investigated. However, the phenomenon is
much more complex than a simple water acidity-fish mercury relation. An extensive study of
mercury accumulation by fish in Swedish forest lakes led to the conclusion that concentrations
were determined by the bioavailability of mercury to lower trophic levels, and that lake humicity,
productivity, and acidity controlled bioavailability (Lindqvist et al. 1991). Our results suggest that
acidity and humicity are important factors in affecting fish mercury content in Russian lakes (we
did not investigate productivity). We found low concentrations of mercury in fish from high pH
lakes regardless of color, which suggests that acidity is a necessary but not sufficient factor in
mercury accumulation by fish in these lakes.
103
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S
104
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Humic matter was found to control the solubility and watershed export of mercury
deposited in precipitation in Sweden and Canada (Iverfeldt and Johansson 1988; Mierle and
Ingram 1991). Further, water concentrations of mercury were highly correlated with water color
(Meili et al. 1991). Most of the mercury in clearwater lakes was deposited in the sediment whereas
most of the mercury in humic lakes was retained in the water column (Meili 1991). Thus humic
matter may affect fish mercury content by affecting the mercury loading to a lake and by retaining
mercury in the water column where it is available for uptake in biota.
Alterations in gill morphology have been reported in a number of fish species in response to
water acidification (Jagoe and Haines 1983; Matey 1984; Evans et al. 1988; Tietge et al. 1988).
Most studies have examined effects after laboratory exposure; relatively few studies have been
conducted on wild fish from chronically acidic environments. Chevalier et al. (1985) reported gill
abnormalities associated with acidification in brook trout (Salvelinus fontinalis) collected from
acidic lakes, and Leino et al. (1987) found changes in the gill epithelium of two species of cyprinids
collected from an experimentally acidified lake. Our results expand these observations to perch
inhabiting acidified environments in Russia, and allow comparisons from colored and clear acidic
waters.
Exposure to low pH water causes osmoregulatory and ionoregulatory disturbances in fish
(McDonald 1983), primarily because of increased passive efflux of sodium. The changes in gill
morphology we observed may represent adaptation of acclimation to minimize this effect. The
thickening of the epithelium would lengthen the diffusion pathway by which ion losses occur, and
increasing numbers of chloride cells would allow increased active uptake of ions from the
environment. Perch are known to be relatively acid tolerant and are frequently the only species of
fish inhabiting acidic lakes (Rask and Tuunainen 1990), including the ones we studied. Perhaps
these changes in gill morphology allow this species to survive at low pH.
Ctenoid fish scales consist of two layers: an upper, ridged osseous layer with cteni and a
lower fibrillary plate (Fouda 1979). The focus is formed early in the life of the individual (Sire
1986) and does not change appreciably after formation. Thus the morphology of this structure
reflects environmental conditions early in the life of the fish. The loss of microridges from the
scale focus in fish from acidic lakes may reflect disruption of calcium metabolism in these fish.
Steingraeber and Gingerich (1991) found that brook trout exposed to pH 5 water had reduced body
calcium, and Reader et al. (1989) found a similar effect for brown trout (Salmo trutta) at pH 4.5.
Majewski et al. (1990) found reduced bone calcium concentration in adult Atlantic salmon (Salmo
solar) held in a river of pH 4.7-5.2. Therefore, scale structure may be a sensitive measure of
physiological stress from water acidity in fish. Because scale structure remains unchanged after
formation, examination of scales of older fish could be used as an indicator of water chemistry at
the time the scale was formed.
SUMMARY AND CONCLUSIONS
We surveyed 20 lakes in two regions of Russia to assess lake acidity, and to determine the
effects of water acidity on fish mercury content and gill and scale ultrastructure. The lakes
surveyed ranged in pH from 4.5 to 8.1 and in color from 3 to 188 Hazen. The mercury content of
fish ranged from 0.06 to 3.04 fig/g wet weight, which was comparable to that reported for this
species from forest lakes in Sweden and Finland. Inasmuch as these were all remote lakes with no
local sources of pollution, atmospheric deposition is presumed to be the source of both acidity and
mercury. Lake acidity and color, or humic content, were the major lake characteristics related to
fish mercury content. Fish from high pH lakes were low in mercury regardless of other lake
characteristics. Fish from low pH lakes varied widely in mercury content, with fish from colored
lakes having higher concentrations than those from clear lakes. Regressions including lake pH
and color, separated by drainage type, explained about 70% of the variance in fish mercury
content. Acidity and color may affect fish mercury content by regulating loading and
bioavailability of mercury to lower trophic levels in these lakes.
105
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Gills and scales of fish from acidic lakes were morphologically different from those of fish
from circumneutral lakes. In acidic lakes, fish gills had thickened secondary lamellae, increased
numbers of chloride cells, apical crypts in some chloride cells, increased mucous production, and
decreased microridge density. These changes were more severe in highly colored acidic lakes than
in clear-water lakes. Scales of fish from acidic lakes lacked microridges in the focus. The gill
abnormalities are all changes that would tend to reduce the effects of ion loss, which is the major
physiological effect of water acidity to fish. The scale abnormality may result from disrupted
calcium metabolism in acidic lakes.
ACKNOWLEDGMENTS
Financial support for this study was provided by U.S. Fish and Wildlife Service, U.S.
Environmental Protection Agency, and U.S. Department of Energy through contract DE-AC09-
76SROO-819 to the University of Georgia's Savannah River Ecology Laboratory in the United
States, and the Institute for Biology of Inland Waters, Russian Academy of Sciences in Russia.
Research space and facilities was provided by the Institute for Research on Northern Fishes in
Petrozavodsk, and by the Laboratory of Physiology and Toxicology, Institute for Biology of Inland
Waters in Borok.
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MORTALITY AND GILL DAMAGE FROM BERYLLIUM IN ACIDIC WATER:
A COMPARISON OF ACUTE AND CHRONIC RESPONSES IN THREE
FRESHWATER FISH SPECIES
by
V. E. Matey1, C. H. Jagoe2, T. A. Haines3,
V. T. Komov1 and L. Cleveland4
ABSTRACT
Increased concentrations of toxic trace metals such as Aluminum (Al) are found in
waters acidified by acid deposition, and elevated Beryllium (Be) levels occur in some acidic
waters in eastern Europe. Beryllium and Al are chemically similar, suggesting that their toxic
effects may be similar as well. We exposed fry of roach and two species of perch to Be in
soft water (calcium [Ca] = 2 mg/L) at two levels of pH (4.5 and 5.5) using static and
flow-through bioassays. In acute toxicity tests with Perca fluviatilis, 10 ug/L or more Be at pH
5.5 produced gill abnormalities including chloride cell hyperplasia and hypertrophy, increased
mucous production, and hyperplasia of the primary lamellar epithelium. At high
concentrations, we observed fusion and loss of secondary lamellae, progressing to fusion of
adjacent primary lamellae. Less gill damage occurred at pH 4.5, but mortality was much
higher at low Be concentrations. Roach were killed only when Be was >50 ug/L, regardless
of pH. Roach gills were damaged by 50 ug/L Be or more at both pH 4.5 and 5.5. With
chronic exposure, similar abnormalities were caused in P. flavescens gills by 6.25 ug/L or
more Be regardless of pH. The different responses observed may represent interspecies
variation, but were probably influenced by small differences in age among species.
Concentrations of Be similar to those reported in some polluted waters produce gill
pathologies indicative of ionoregulatory stress. The effects of Be and Al are analogous, but
Be is toxic at lower concentrations.
Institute for the Biology of Inland Waters, Russian Academy of Science, Borok, Nekouz,
Yaroslaval, Russia.
2University of Georgia, Savannah River Ecology Laboratory, PO Drawer E, Aiken SC 29802
(USA).
3National Biological Survey, Midwest Science Center (formerly U.S. Fish and Wildlife
Service, National Fisheries Contaminant Research Center) Field Station, Department of
Zoology, University of Maine, Orono ME 04469 (USA).
4National Biological Survey, Midwest Science Center, 4200 New Haven Road, Columbia, MO
65201 (USA).
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INTRODUCTION
The concentration of Be in most surface waters is very low. These levels reflect both
the relative insolubility of BeOH2 at circumneutral pH (Baes and Mesmer 1976) and the
overall scarcity of Be in the earth's crust (Reeves 1986). Although the average Be content of
soils is low, some soils and soft coals are enriched in Be (Wilber 1980) in portions of eastern
Europe (Vesely et al. 1989).
Acid deposition increases the mobility of many trace metals (Norton 1982), resulting in
elevated concentrations of toxic trace metals such as Al in surface waters (Cronan and
Schofield 1979). Dickson (1980) showed that cadmium, magnesium, zinc, and lead levels
were elevated in some acid waters, and these trace elements were apparently mobilized by
acid deposition. Vesely et al. (1989) reported elevated Be concentrations in acidified waters
in eastern Europe and suggested that Be was mobilized by acid deposition. Both Be and Al
have comparable speciation properties in water (Baes and Mesmer 1976, Vesely et al. 1989).
Given the analogous geochemical properties of Be and Al, Be may also be an important toxic
agent in some acidic waters.
Few studies have examined toxic effects of Be on fish. Slonim (1973) showed that
relatively high concentrations of Be were toxic to guppies Lebistes reticulatis at circumneutral
pH in hard water (400 mg/L Ca). Slonim and Slonim (1973) found that Be was more toxic to
guppies as Ca levels decreased, but even the lowest Ca concentrations they tested were
much higher than those present in most acidic waters. In the very dilute waters typical of
acidified lakes and streams, Be would be much more toxic than previously suspected. Fish
gills are damaged by Al (Karlsson-Norrgren et al. 1986, Jagoe et al. 1987, Evans et al. 1988,
Tietge et al. 1988), which also causes ionoregulatory disturbances (Witters 1986, Booth et al.
1988). By analogy, similar effects might result from Be exposure.
MATERIALS AND METHODS
We performed acute toxicity bioassays at the Institute for the Biology of Inland Waters
in Borok, Russia, in June 1989 to evaluate the toxicity of Be in low pH water and to
determine effects of Be on gill structure (Jagoe et al. 1992). European perch (P. fluviatilis)
and roach (Rutilus rutilus) from the Rybinsk Reservoir were allowed to spawn in artificial
ponds, and fry (perch 0.08-0.15 g and roach 0.7-0.9 g) were collected and acclimated to
reconstituted soft water for 72 hours. This water simulated the ionic composition of
low-alkalinity lakes in the region (Haines et al. 1992), and was prepared by adding salts to
distilled water (final concentrations in mg/L: 2 Ca, 1 sodium, 0.25 potassium, 0.25
magnesium, 1 SO4, and 2.6 chlorine).
Fish were exposed to Be at two levels of pH in 2 L polyethylene aquaria (n = 10
fish/aquarium), two replicates per treatment, at room temperature (20-22°C). Dilute sulfuric
acid was added to the reconstituted soft water to obtain a pH of 4.5 or 5.5, and a BeSO4
solution (nominal concentration 1 mg/mL, measured concentration 0.907 mg/mL, SD = 0.12,
N = 3) was added to yield final nominal concentrations of 0, 10, 25, 50, 100 or 150 ug/L Be.
Controls (pH 7.0) received neither acid nor Be. Acute exposures were performed
sequentially, with perch tested first, followed by roach. Dead fry were counted and removed
110
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at 24-hour intervals, and pH recorded and adjusted if necessary. The cumulative number of
fish killed by each treatment after 96 hours exposure were compared by analysis of variance.
Separate analyses were conducted for each species and pH level. When significantly
different levels of mortality were found among the Be treatments, those treatments which
differed significantly from the control were identified by Dunnetts' t-test (SAS 1988).
All fish surviving 96 hours were collected and fixed. During the experiments, some
moribund fry were removed, scored as dead, and fixed to obtain samples for microscopy
from treatments exhibiting high mortality. Whole fry were fixed in 1% glutaraldehyde and 4%
formaldehyde in 0.1 m HEPES buffer, pH 7.4. Only fish that were alive when fixed were
used for microscopic examination.
To better understand the consequences of chronic exposure to low levels of Be on
fish, we exposed juvenile yellow perch (P. flavescens) at pH 4.5 and 5.5 for 30 days in May
and June 1990 in laboratory experiments at the Midwest Science Center in Columbia,
Missouri. Perch (8-10 months old, average weight 1.5 g) were obtained from the National
Biological Survey, National Fisheries Research Center in La Crosse, Wisconsin. Exposures
were conducted at 20°C in reconstituted soft water using a flow-through proportional diluter
system as previously described (Cleveland et al. 1986). Test water contained 2 mg/L Ca,
and was very similar in composition to the water used in acute toxicity experiments
conducted in Russia in 1989. The water was acidified to pH 4.5 or 5.5 using a mixture of
sulfuric and nitric acid, and Be was added (as BeCI2) to nominal concentrations of 0, 6.25,
12.5, 25, or 50 ug/L. Fish were exposed in 77-L aquaria, and test solutions were renewed at
the rate of about 8 L/hour. Control treatments (pH 6.9-7.1) received neither acid nor Be.
Fish were fed a commercial fish diet ad libitum three times daily. In each treatment, pH was
determined daily; oxygen, alkalinity, and conductivity were determined twice each week; and
Be was measured weekly. Initially, 40 fish were placed in each treatment, and 5 were
removed from each after 5, 15, and 30 days of exposure and fixed for microscopic
examination as described above.
Fish from both sets of experiments were prepared for scanning electron microscopy
(SEM) using the same protocols. After at least 24 hours of fixation, the samples were treated
with 1% OsO4 for 1 or 2 hours to increase specimen conductivity, dehydrated using a graded
ethanol or ethanol-acetone series, then critical-point dried. European perch and roach fry
were dried whole, mounted on aluminum specimen stubs, and the opercula removed using
fine-tipped forceps to expose the branchial baskets. For yellow perch, gill arches were
removed and dried individually. The specimens were spatter-coated with gold or a
gold-palladium mixture, and examined by SEM at accelerating voltages of 5 or 15 kV.
RESULTS AND DISCUSSION
ACUTE TOXICITY
No European perch or roach held at pH 7.0 without Be died during the acute toxicity
experiments. Exposure to pH 5.5 and Be <50 ug/L did not kill any fish within 96 hours (Figs.
1a and 2a). Mortality of perch fry exposed for 96 hours to 100 or 150 ug/L Be was
significantly higher than mortality of perch fry exposed to lower concentrations at pH 5.5
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a pH 5.5
*
*
b. pH 4.5
25 50
% MORTALITY
75
100
Fig. 1. Mortality of European perch fry exposed to beryllium (Be) at pH 4.5 and 5.5. Values
represent the means of two replicates _±_ standard error. Asterisks indicate significant differences (p
< 0.05) compared to the control (pH 7.2, 0//g/L Be) treatment.
a. pH 5.5
b. pH 4.5
25 50
% MORTALITY
75
100
Fig. 2. Mortality of roach fry exposed to beryllium (Be) at pH 4.5 and 5.5. Values represent the
means of two replicates _+. standard error. Asterisks indicate significant differences (p < 0.05)
compared to the control (pH 7.2, 0 fjg/L Be) treatment.
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(p < 0.05; Fig. 1a). Similarly, roach fry were killed by exposure to 100 and 150 |jg/L Be at
pH 5.5 (Fig. 2a) for 96 hours. Because of variation among the replicates, at pH 5.5 only
mortality at 150 ug/L Be was significantly greater than control mortality in roach (p < 0.05).
At pH 4.5, mortality of European perch was lowest in the 0 and 50 ug/L Be treatments
(Fig. 1b), which did not differ significantly from each other or the control treatments (pH 7.0,
no Be). All other Be concentrations tested at pH 4.5 caused significantly higher mortality of
European perch fry after 96 hours (p < 0.05). Roach were less sensitive to Be at low pH
than the perch. Roach fry were killed only at the highest Be concentrations (100 and 150
ug/L) at pH 4.5, and mortality was significantly greater than control mortality (p < 0.05) only
at the highest concentration tested.
In European perch, mortality was similar at both levels of pH tested at Be >50 ug/L.
Lower concentrations of Be (<25 ug/L) were more toxic to European perch at pH 4.5 than at
pH 5.5. Apparently the pH 4.5 treatment without Be was also stressful to European perch, as
over 25% of the fish in this treatment died. The reduction in mortality observed in 50 ug/L
Be, pH 4.5, could have resulted from a dilution error; however, this situation is unlikely
because reduced toxicity occurred in both replicates and the water in these was prepared
independently. A similar response has been observed in Al exposures; survival and body
ion content of brook trout (Salvelinus fontinalis) fry at low pH were reduced at high and low
Al levels, but were enhanced at moderate levels (Wood et al. 1990). Polyvalent Al species
present at low pH may stabilize membranes at intermediate concentrations (Baker and
Schofield 1982, Wood et al. 1988a) and Be may function in a similar manner.
Dissolved Ca clearly influences Al toxicity at low pH (Brown 1983, Wood et al. 1990),
probably by modifying gill epithelial permeability. Previous work on Be toxicity (Slonim 1973,
Slonim and Slonim 1973) showed that guppies in hard water (400 mg/L Ca) at circumneutral
pH had a 96-hour median tolerance limit for Be of 27 mg/L (Slonim 1973). Toxicity increased
as dissolved Ca concentration decreased; the 96-hour median tolerance limit for guppies was
about 0.2 mg/L Be when Ca = 22 mg/L. In acidified waters, even less Ca is typically present
than used in these previous studies. Our studies yielded 96-hour LC50s of approximately 80
ug/L for European perch fry and 100 ug/L for roach fry at pH 5.5 when Ca = 2 mg/L.
GILL DAMAGE DUE TO ACUTE EXPOSURE
Both juvenile perch and roach held in pH 7.0 water without Be had well-formed gills
with no visible abnormalities (Fig. 3a, b). Secondary lamellae appeared regular in size and
configuration, and individual cells covered with microridges were observed, with little mucous
visible at higher magnification (Fig. 3c). No gross morphological changes were observed at
pH 5.5 in the absence of Be in gills of European perch (Fig. 4a) or roach (Fig. 4b). Surface
microridges appeared somewhat less abundant, but no swelling or mucous accumulation was
evident (Fig. 4c). Exposure to pH 4.5 without Be also had little effect on the gross
morphology of European perch gills (Fig. 4d) or roach gills (Fig. 4e), although we observed
effects typical of low pH stress, such as greater chloride cell numbers. Swelling of mucous
cells indicative of increased mucous production, and many chloride cells with apical crypts
were visible at higher magnification (Fig. 4f).
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Fig. 3. Scanning electron micrographs of gills at pH 7.0 with no beryllium: a) European perch, scale
bar = 100/urn; b) roach, scale bar = 1000//m; and c) European perch, scale bar = 100//m.
114
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Fig. 4. Scanning electron micrographs of gills of fry exposed to low pH (5.5) without beryllium
(Be): a) European perch, scale bar = 100//m; b) roach, scale bar = 1000/;m; c) European perch,
scale bar = 100//m; d) European perch, scale bar = 100//m; e) roach, scale bar = 1000//m; and
f) European perch, scale bar = 10 fjm.
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In European perch, exposure to as little as 10 ug/L Be at pH 5.5 caused changes in
gill morphology. Chloride cell apical crypts were present in perch exposed to 10 ug/L Be
(Fig. 5a), but not in perch exposed to pH 5.5 without Be. We also found some swelling of
epithelial cells and a reduction in microridges on cell surfaces. Microridge loss and swelling
of primary lamellar epithelial cells were more marked in European perch after 96 hours
exposure to 25 ug/L Be, pH 5.5. Exposure to 50 ug/L Be at pH 5.5 caused hyperplasia of
the primary lamellar epithelium in European perch, which filled in the spaces between
secondary lamellae, causing the secondary lamellae to appear shorter and less distinct (Fig.
5b). This hyperplasia became more severe at higher Be concentrations; above 100 ug/L Be,
massive epithelial hyperplasia fused adjacent primary lamellae in perch gills into a continuous
mass (Fig. 5c). Low Be concentrations produced few effects on roach gills at pH 5.5. At pH
5.5 with 50 ug/L Be, primary and secondary lamellae of roach thickened, the density of
microridges on the surfaces of epithelial cells was markedly reduced, and increased numbers
of enlarged mucous cells appeared on primary lamellae (Fig. 5d). Gill abnormalities became
more severe at higher Be concentrations. Mucous cells were enlarged in gills of roach
exposed to 100 ug/L Be, pH 5.5, and many secretory pores were visible, indicating increased
mucous secretion (Fig. 5e). After 96 hours exposure to 150 ug/L Be at pH 5.5, hyperplasia
of both the primary and secondary lamellar epithelia was pronounced in roach (Fig. 5f),
resulting in gills appearing greatly thickened and clubbed. Fusion of adjacent primary
lamellae, as found in European perch fry, was not observed in roach.
At pH 4.5, high mortality occurred in European perch, but the effects of Be on gill
structure were less striking than at pH 5.5. European perch exposed to 50 ug/L Be at pH 4.5
for 96 hours exhibited swelling of the primary lamellar epithelia, some loss of microridges,
and increased mucous secretion (Fig. 6a). After exposure to Be at concentrations of 100
ug/L or more at pH 4.5, areas devoid of microridges were visible (Fig. 6b) and hyperplasia
caused fusion of adjacent secondary lamellae in a number of regions (Fig. 6c). In this
species, the hyperplasia at pH 4.5 was much less severe than at pH 5.5.
In roach exposed to Be concentrations of 50 ug/L or higher at pH 4.5, epithelial
hyperplasia occurred. Primary lamellae became enlarged, with few surface microridges
visible (Fig. 6d). At 100 |jg/L Be, pH 4.5, hyperplasia was severe in roach gills; many
secondary lamellae fused as the interlamellar spaces filled in (Fig. 6e). At 150 ug/L Be, pH
4.5, numerous secondary lamellae were lost in roach gills (Fig. 6f), and epithelial hyperplasia
resulted in thickened, club-like primary lamellae. Many chloride cell apical crypts and swollen
mucous cells were seen. Although fewer roach than European perch died at pH 4.5, gill
abnormalities we observed were more severe in the roach at this pH.
Conversely, Be at pH 4.5 killed most European perch, although they exhibited fewer
gill abnormalities. Most of the deaths occurred quickly, within 48-72 hours of exposure. The
secondary lamellae of European perch dying at nigh Be concentrations were extremely
swollen and irregular, with increased amounts of mucous. This observation suggests Be at
the low pH damaged epithelial cells and destroyed their function as a water- and ion-tight
barrier. Disruption of this barrier function likely produced rapid, severe ionoregulatory stress
that killed the fry before compensatory mechanisms could occur, such as epithelial
hyperplasia to increase both chloride cell numbers and the thickness of the diffusion pathway.
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Fig. 5. Scanning electron micrographs of gills of fry exposed to beryllium (BE) at pH 5.5:
a) European perch, 10//g/L Be, scale bar = 10//m; b) European perch, 50//g/L Be, scale bar = 10
//m; c) European perch, 100/;g/L Be, scale bar = 100/mi; d) roach, 50//g/L Be, scale bar = 100
; e) roach, 100^g/L Be, scale bar = 100/vm; and f) roach, 150//g/L Be, scale bar = 100//m.
117
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\
Fig. 6. Scanning electron micrographs of gills of fry exposed to beryllium (Be) at pH 4.5: a)
European perch, 50//g/L Be, scale bar = 10 fjm; b) European perch, 100//g/L Be, scale bar = 10
//m; c) European perch, 150//g/L Be, scale bar = 100jum; d) roach, 50//g/L Be, scale bar = 100
fjm; e) roach, 100 fjg/L Be, scale bar = 100//m; and f) roach, 150jug/L Be, scale bar = 100//m.
118
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EFFECTS OF CHRONIC EXPOSURE
Survival of yellow perch was not affected by exposure to Be at concentrations up to
50 ug/L at either pH level tested. During the first week of exposure, hyperactivity and
abnormal schooling behavior were observed in yellow perch exposed to 50 ug/L Be at both
pH 4.5 and 5.5, but these effects disappeared as exposure continued.
The gross morphology of gills was not noticeably different among yellow perch
exposed for 30 days to pH 7.0 (Fig. 7a), pH 5.5 (Fig. 7b), or pH 4.5 (Fig. 7c) without Be.
Both primary and secondary lamellae were distinct and normal in appearance. Mucous
droplets were more abundant after exposure to the lower levels of pH. Numerous chloride
cells were present on primary lamellae at all levels of pH, probably resulting from prolonged
exposure to relatively soft water. Laurent et al. (1985) and Leino et al. (1987) have also
reported chloride cell proliferation in fish held in very soft water.
In contrast, 30 days exposure to Be produced gill abnormalities, even at the lowest
concentration tested. Compared to controls (pH 7.0, no Be; Fig. 8a), the secondary lamellae
of yellow perch exposed to 6.25 ug/L Be at pH 5.5 (Fig. 8b) were swollen and wrinkled, and
increased numbers of chloride cells were present in the secondary lamellar epithelia. The
gills of yellow perch exposed to 6.25 ug/L Be at pH 4.5 were coated with mucous that
obscured much surface detail, and epithelial hyperplasia had reduced the spaces between
adjacent secondary lamellae, making them shorter and less distinct (Fig. 8c). This shortening
and loss of secondary lamellae also occurred at 6.25 ug/L Be at pH 5.5, and was most
noticeable near the tips of the primary lamellae (Fig. 8d). At both levels of pH, 6.25 ug/L Be
caused loss of cell surface microridges (Fig. 8e) and a noticeable increase in chloride cell
surface area. We also observed an unusually high number of mucous cell secretory pores,
along with bulging, convex chloride cell apices in yellow perch exposed to 6.25 ug/L Be at pH
4.5 (Fig. 8f).
As in acute exposure experiments, gill abnormalities in yellow perch became more
severe at higher Be concentrations. Thirty days exposure to 25 ug/L Be at pH 5.5 caused
more severe epithelial hyperplasia, causing secondary lamellae to thicken and grow together
(Fig. 9a). This hyperplasia resulted in increased numbers of chloride cells as well (Fig. 9b).
Hyperplasia leading to secondary lamellar loss and primary lamellar thickening also occurred
at 25 ug/L Be at pH 4.5 (Fig. 9c). Abnormalities were not obviously more severe at the
highest Be level tested (50 ug/L) than at 25 ug/L Be. SecondaryHamellae were also
shortened, thickened, and fused by exposure to 50 ug/L Be for 30 days at pH 5.5 (Fig. 9d).
Exposure to the 50 ug/L Be at pH 4.5 caused similar effects on secondary lamellae (Fig. 9e,
f), and surface microridges were sparse with considerable mucous visible (Fig. 9f).
The first and fourth gill arches in young yellow perch always had a row of noticeably
shortened primary lamellae. In fish exposed to pH 7.0 with no Be, the morphology of these
short primary lamellae was very similar to the adjacent longer ones (Fig. 10a). Exposure to
pH 4.5 without Be for 6 days did not affect the morphology of these shortened lamellae (Fig.
10b), but they were severely damaged by the presence of Be (Fig. 10c). To our knowledge,
this report is the first of the presence of these short filaments in the species. Perhaps these
primary lamellae are rapidly growing and developing in young yellow perch, as their size and
structure is similar to that reported in other young fish (Morgan 1974, EI-Fiky et al. 1987),
119
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Fig. 7. Scanning electron micrographs of gills of yellow perch fry held at various levels of pH
without beryllium (Be); scale bars = 100//m: a) pH 7.0, b) pH 5.5, and c) pH 4.5.
120
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Fig. 8. Scanning electron micrographs of gills of yellow perch fry: a) pH 7.0, no beryllium (Be),
scale bar = 10/vm; b) pH 5.5, 6.25//g/L Be, scale bar = 10/ym; c) pH 4.5, 6.25 fjg/L Be, scale bar
= 10//m; d) pH 5.5, 6.25 fjg/L Be; scale bar = 100/;m; e) pH 5.5, 6.25//g/L Be, scale bar = 10
fjm; and f) pH 4.5, 6.25/yg/L Be, scale bar = 10^m.
121
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I: V.
Fig. 9. Scanning electron micrographs of gills of yellow perch fry: a) pH 5.5, 25 jjg/L beryllium
(Be), scale bar = 100 fjm; b) pH 5.5, 25 fjg/L Be, scale bar = 10//m; c) pH 4.5, 25 fjg/L Be, scale
bar = 100//m; d) pH 5.5, 50/jg/L Be, scale bar = 100 //m; e) pH 4.5, 50pg/L Be, scale bar =
100/ym; and f) pH 4.5, 50//g/L Be, scale bar = 10 //m.
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Fig. 10. Scanning electron micrographs of the gills of yellow perch fry showing the shortened row
of primary lamellae on the first and fourth gill arches; scale bars = 100//m: a) pH 7.0, no beryllium
(Be), 30 days exposure; b) pH 4.5, no Be, 6 days exposure; and c) pH 4.5, 25 fjg/\- Be, 6 days
exposure.
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although these authors do not mention large differences in size among adjacent rows of
lamellae. If this situation is true, the rapidly growing structures may be especially susceptible
to pollutant damage, as we observed for Be, and may also be a very sensitive indicator of
pollutant-induced stress.
COMPARISON BETWEEN SPECIES AND pH LEVELS
The three fish species tested seemed to respond differently to Be. These results may
reflect interspecies differences; for example, roach differs from perch in sensitivity to low pH
(Johansson and Milbrink 1976). A more thorough comparison of interspecies sensitivity must
consider differences in size and age of fish tested. European perch fry were somewhat
smaller than roach fry, and both were younger than yellow perch fry. Newly hatched fish and
those just beginning to feed are especially sensitive to low pH and metal-induced stress
(Peterson et al. 1982). As fish grow, they become more resistant. Thus, the difference in
size and age among the species tested makes evaluation of true interspecies differences in
sensitivity difficult.
Both Be and Al speciation are pH dependent. Calculation of equilibrium species
distributions from thermodynamic data indicated that the major species present in both the
acute and chronic toxicity experiments were monomeric Be2+ and BeOH+, depending on pH
(Garrels and Christ 1965, Smith and Martell 1976). Be2+ accounts for 88% of the total Be
present at pH 4.5, while at pH 5.5, 56% would be in the form BeOhT. In European perch, the
most striking abnormalities in gills occurred at pH 5.5, when most Be present was in the
hydroxide form. In roach and yellow perch, abnormalities occurred at both levels of pH.
Aluminum-induced gill abnormalities also occur both at pH levels where AIOH species
dominate (Karlsson-Norrgren et al. 1986, Jagoe et al. 1987) and lower pH levels where AI3+
becomes important (Evans et al. 1988, Tietge et al. 1988).
COMPARISON OF EFFECTS OF BE AND AL
Aluminum at low pH causes gill abnormalities, including hyperplasia resulting in
epithelial thfckening, increased mucous production, and changes in chloride cell and mucous
cell number and structure (Evans et al. 1988, Jagoe 1988, Tietge et al. 1988). Epithelial
hyperplasia, partly due to increased production of chloride cells, can cause fusion and
disappearance of primary and secondary lamellae: this greatly reduces the functional surface
of the gill (Karlsson-Norrgren et al. 1986, Jagoe et al. 1987). Gill physiological processes
known to be affected by Al include ion regulation (Witters 1986, Booth et al. 1988) and gas
exchange (Wood et al. 1988b, Playle et al. 1989). Beryllium causes the same gill
abnormalities, which strongly suggests that the same physiological processes are affected by
the two metals.
The altered chloride cell morphology we observed suggests that Be interferes with ion
regulation, because chloride cells are responsible for ion uptake in freshwater fish (Laurent et
al. 1985). Also, exposure to Be causes apical crypts to develop in chloride cells. Chloride
cell apical crypts normally occur only in seawater-adapted fish (Foskett and Schelley 1982),
but also occur in freshwater fish experiencing ionoregulatory disturbances caused by low pH
124
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(Leino and McCormick 1984) and At (Jagoe et al. 1987). Increased chloride cell production
may represent a compensatory response to offset ionic losses if initial exposure to the Be is
not acutely lethal. However, such hyperplasia involves a trade-off; in exchange for increased
ionic uptake sites, the functional surface area for gas exchange is greatly decreased.
CONCLUSIONS
Vesely et al. (1989) found Be concentration was highly correlated with decreased pH
in acidified waters in Czechoslovakia. In the waters they sampled, Be >5 ug/L was found at
27 sites, at concentrations as high as 58 ug/L This study demonstrates that these Be
concentrations would be harmful to fishes, and likely cause gill abnormalities or damage.
Our results also suggest that the effects of Be and Al are analogous. In some areas where
Be is abundant in soils or because of extensive use of lignite coal usage (Wilber 1980), Be
may be an important toxicant whose behavior and effects are still poorly understood.
ACKNOWLEDGMENTS
C.H.J. was partly supported by contract DE-AC09-76SROO-819 between the U.S.
Department of Energy and the University of Georgia's Savannah River Ecology Laboratory.
Financial support was also provided by the U.S. Department of the Interior, Fish and Wildlife
Service; the U.S. Environmental Protection Agency; and by the Institute for the Biology of
Inland Waters, Academy of Sciences of Russia. We thank Boris Flerov, Chief of the
Laboratory of Toxicology and Physiology, Institute for the Biology of Inland Waters, and
Richard Schoettger, Director, National Biological Survey's Midwest Science Center, for
assistance with logistics and facilities.
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Soil Poll. 18:289-309.
Booth, C. E., D. G. McDonald, B. P. Simons and C. M. Wood. 1988. Effects of aluminum
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development of anaerobic power in the larvae of cyprinid fish (Pisces, Teleostei).
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morphology in rainbow trout, Salmo gairdneri. Environ. Biol. Fish. 22:299-311.
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salt-secretory cell in teleosts. Science 215:164-166.
Garrels, R. M. and C. L. Christ. 1965. Solutions, minerals and equilibria. Freeman Cooper,
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Haines, T. A., V. T. Komov and C. H. Jagoe. 1992. Lake acidity and mercury content offish
in Darwin National Reserve, Russia. Environ. Poll. 78:107-112.
Jagoe, C. H. 1988. A histological and ultrastructural study of the effects of low pH and
aluminum upon the gills of Atlantic salmon. PhD Thesis, Univ. Maine, Orono.
Jagoe, C. H., T. A. Haines and D. R. Buckler. 1987. Abnormal gill development in Atlantic
salmon (Salmo salai) fry exposed to aluminum at low pH. Pages 375-386 in H.
Witters and O. Vanderborght (eds.), Ecophysiology of acid stress in aquatic
organisms, Suppl. 1, vol. 117, Annals Soc. Royal. Zool. Belgium, Antwerp.
Jagoe, C. H., V. E. Matey, T. A. Haines and V. T. Komov. 1993. Effect of beryllium on fish
in acid water is analogous to aluminum toxicity. Aquat. Toxicol. 24:241-256.
Johansson, N. and G. Milbrink. 1976. Some effects of acidified .water on the early
development of roach (Rutilus rutilus L.) and perch (Perca fluviatilis L.). Water Res.
Bull. 12:39-48.
Karlsson-Norrgren L, I. Bjorklund, O. Ljungberg and P. Runn. 1986. Acid water and
aluminum exposure; experimentally induced gill lesions in brown trout, Salmo trutta L.
J. Fish Dis. 9:11-25.
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relative to calcium in gill morphology of freshwater fish. Cell Tiss. Res. 240:675-692.
Leino, R. L. and J. H. McCormick. 1984. Morphological and morphometrical changes in
chloride cells of the gill of Pimephales promelas after chronic exposure to acid water.
Cell Tiss. Res. 236:121-128.
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Leino, R. L, J. H. McCormick and K. M. Jensen. 1987. Changes in gill histology of fathead
minnows and yellow perch transferred to soft water and acidified soft water with
particular reference to chloride cells. Cell Tiss. Res. 250:389-399.
Morgan, M. 1974. Development of secondary lamellae of the gills of the trout, Salmo
gairdneri (Richardson). Cell Tiss. Res. 151:509-523.
Norton, S. A. 1982. The effects of acidification on the chemistry of ground and surface
waters. Pages 93-102 in T. A. Haines and R. E. Johnson (eds.), Acid rain/fisheries,
Am. Fish. Soc., Bethesda, MD.
Peterson, R. H., P. G. Daye, G. L. Lacroix and E. T. Garside. 1982. Reproduction in fish
experiencing acid and metal stress. Pages 177-196 in T. A. Haines and R. E.
Johnson (eds.), Acid rain/fisheries, Am. Fish. Soc., Bethesda, MD.
Playle, R. C., G. G. Goss and C. M. Wood. 1989. Physiological disturbance in rainbow trout
(Salmo gairdneri) during acid and aluminum exposures in soft water of two calcium
concentrations. Can. J. Zool. 67:314-324.
Reeves, A. L. 1986. Beryllium. Pages 95-116 in L. Friberg, G. Nordberg and V. Vouk
(eds.), Handbook on the toxicology of metals, vol. II: Specific metals, Elsevier,
Amsterdam, The Netherlands.
SAS. 1988. SAS/STAT Users Guide, Release 6.03 ed. SAS Institute, Inc., Gary, NC.
Slonim, A. R. 1973. Acute toxicity of beryllium to the common guppy. J. Water Poll. Cont.
Fed. 45:2110-2122.
Slonim, C. B. and A. R. Slonim. 1973. Effect of water hardness on the tolerance of the
guppy to beryllium sulfate. Bull. Environ. Contam. Toxicol. 10:295-301.
Smith, R. E. and A. E. Martell. 1976. Critical stability constants, vol.4, Inorganic complexes.
Plenum Press, New York.
Tietge, J. E., R. D. Johnson and H. L. Bergman. 1988. Morphometric changes in gill
secondary lamellae of brook trout (Salvelinus fontinalis) after long-term exposure to
acid and aluminum. Can. J. Fish. Aquat. Sci. 45:1643-1648.
Vesely, J., P. Benes and K. Sevcik. 1989. Occurrence and speciation of beryllium in
acidified freshwaters. Water Res. 23:711-717.
Wilber, C. T. 1980. Beryllium: a potential environmental contaminant. C. C. Thomas,
Springfield, IL.
Witters, H. E. 1986. Acute acid exposure of rainbow trout, Salmo gairdneri Richardson:
effects of aluminum and calcium on ion balance and hematology. Aquat. Toxicol.
8:197-210.
127
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Wood, C. M., D. G. McDonald, C. E. Booth, B. P. Simons, C. G. Ingersoll and H. L Bergman.
1988a. Physiological evidence of acclimation to acid/aluminum stress in adult brook
trout (Salvelinus fontinalis). 1. Blood composition and net sodium fluxes. Can. J.
Fish. Aquat. Sci. 45:1587-1596.
Wood, C. M., R. C. Playle, B. P. Simons, G. G. Goss and D. G. McDonald. 1988b. Blood
gases, acid-base status, ions and hematology in adult brook trout (Salvelinus
fontinalis) under acid/aluminum exposure. Can. J. Fish. Aquat. Sci. 45:1575-1586.
Wood, C. M., D. G. McDonald, C. G. Ingersoll, D. R. Mount, O. E. Johannsson and H. L.
Bergman. 1990. Whole body ions of brook trout (Salvelinus fontinalis) alevins:
responses of yolk sac and swim up stages to water acidity, calcium and aluminum,
and recovery effects. Can. J. Fish. Aquat. Sci. 47:1604-1615.
128
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IMPACT OF PERMETHRIN ON ZOOPIANKTON
IN HIGH LATITUDE EXPERIMENTAL PONDS
by
Thomas W. La Point1, O.D. Zhavoronkova2 and D.F. Pavlov2
ABSTRACT
This study evaluated the effect of a range of concentrations (0.5-
50 ug liter"1) of permethrin on experimental pond zooplankton in northern
USSR. Each pond was dosed once and the experiment was unreplicated.
Samples were collected from each pond prior to, 7 days and 11 days after
sampling. High sampling variances precluded measuring statistically
significant differences among the ponds, with the exception of rotifers.
Certain rotifer species appear to be highly sensitive to pyrethroid
insecticides. The value of this descriptive study is in outlining
future studies of the response of planktonic organisms to one-time or
pulsed dosing of chemicals in experimental ecosystems. The frequency
and duration of exposure needs to be taken into account relative to the
generation time and reproductive capacity of the organisms under study.
INTRODUCTION
A critical consideration in measuring the effect of pesticides on
non-target aquatic species is integrating exposure and effect, relative
to life history characteristics of the exposed organisms. Trophic
status, including nutrient concentration, suspended particulate, and
HJ.S. Fish and Wildlife Service, National Fisheries Contaminant Research
Center, Columbia, MO (USA) Present address: Department of Environmental
Toxicology and Institute of Wildlife and Environmental Toxicology
(TIWET), Clemson University, Pendleton, SC 29670 (USA).
Institute of Biology of Inland Waters, Russian Academy of Sciences,
Borok, Jaroslavl Region, Russia
129
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dissolved and particulate organic matter affects chemical
bioavailability in surface waters (Kaiser 1980, McCarthy & Bartell
1988). Morpho-edaphic components of the environment (depth, slope,
current, physical-chemical nature of the substrate) also exert a strong
influence on the nature of the biota in aquatic environments (Minshall
1988, Johnson et al. 1993). Biotic response to a contaminant depends
upon life history characteristics of the individual species (body size,
reproductive potential, and habitat and food requirements) (Barnthouse
et al. 1987, Barnthouse et al. 1990, La Point 1994). Further,
consideration must be made for conservatism, as little is known of
inter-specific interactions in planktonic food webs. Most of the work
to date has dealt with effects on zooplankton (Liber et al. 1994,
DeNoyelles et al. 1994), benthos (Fairchild et al. 1992, Lozano et al.
1992, Giddings et al. 1994) and fishes (Fairchild et al. 1994,
Barnthouse et al. 1987). Planktonic and benthic fauna are important in
that they form the base of food webs in natural ecosystems and are
chiefly responsible for decomposition of particulate and in influencing
the overall secondary production within aquatic ecosystems. How these
not-target groups respond to pesticides will influence rates of
decomposition, primary production, nutrient cycling, and effects on
organisms higher in the food chain (Dewey and DeNoyelles 1994).
Increasingly, more information is being collected on micro fauna,
particularly the zooplankton. However, one group of micro invertebrates
for which there is very little information is that of water mites,
Hydracarina. Hydracarina are widely distributed all over the world,
except the Antarctic region, and inhabit almost all types of water
bodies (Gledhill 1985). The population density of water mites may reach
extremely high levels (Tuzovshiy 1972). The nymphs and imagoes of water
mites are mainly predators and play a great role in the functioning of
aquatic ecosystems (Ten Winkel and Davids 1985, Kutikova 1977). At the
same time, this group of Chelicerata is comparatively poorly studied in
most aspects of aquatic ecology and particularly in aquatic
ecotoxicology. The number of papers or reports dealing with the
influence of various toxic substances on water mites is comparatively
small and the conclusions made in these papers are often contradictory
(Alexeev 1971, Nair et al. 1977, Stephenson 1982). For example, V.A.
Alexeev (1986) stated that Hydracarina are generally resistant to a
variety of toxicants. On the other hand, it has been shown that they
are very sensitive to toxic action of pesticides and may be useful for
the purposes of bioindication (Nair et al. 1977).
Synthetic pyrethroids are becoming widely used in agricultural
regions across the world. This class of insecticide is characterized by
low water solubility, high lipophilicity, high toxicity to fish and
invertebrates, and relatively low toxicity to mammals. Because
synthetic pyrethroids are widely used within the USA and Russia, it is
important that the effect of these chemicals on non-target aquatic
species and ecosystems be studied. The research described in this paper
was conducted at the experimental ponds of the Institute of Biology of
Inland Waters (IBIW), Russian Academy of Sciences, Borok, Jaroslavl
Region, Russia. Permethrin (3-phenoxybenzyl (IRS)-cis, trans-3-(2,2-
dichlorovinyl)-2,2-dimethylcyclopropanecarboxylate) was used as the
commercial product Pounce, manufactured by FMC, Inc. Pounce has 38.47%
active ingredient, 50.7% xylene, and 10.8% related reaction and inert
products.
130
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MATERIALS AND METHODS
DESCRIPTION OF STUDY PONDS
The IBIW is located on the Rybynsk Reservoir in the Jaroslavl
Region of Russia, roughly 330 km northeast of Moscow at 58 degrees N
latitude. The experimental ponds at the IBIW have a surface area of 800
m2, volume of 400 m3, and average depth of 50 cm. The ponds are
characteristic of high-latitude, oligotrophic ponds (Table 1).
Five ponds were used in this experiment: control, acetone control,
and three ponds treated with permethrin to achieve concentrations of
0.5, 5.0 and 50.0 ug liter"1 (pond numbers 1, 2, 3, 4, and 5,
respectively). Acetone was used as the carrier for permethrin; 1 liter
was dosed into each pond with the permethrin by sub-surface application
(at 15 to 20 cm depth) using a hand-held sprayer. The concentration of
permethrin in 1-liter acetone was 0.52 ml, 5.2 ml, and 52.0 ml to
achieve the 0.5, 5.0 and 50.0 ug liter"1 concentrations, respectively.
The chemical was mixed into the ponds by transects taken across the
surface in a boat. Ponds were treated once, on May 25, 1989.
RESIDUE ANALYSIS
Permethrin samples were intended to be analyzed by gas
chromatography following collection and transport to the USA.
Permethrin samples were collected on days 1 and 11 following dosing.
Collected water samples were extracted onto C-18 packed glass columns,
frozen, and carried to the National Fisheries Contaminant Research
Center in Columbia, Missouri, for analysis. Unfortunately, the samples
were not allowed into the country; hence, results are in terms of
nominal permethrin concentrations.
Table 1. Water chemistry of Russian Academy of Sciences Institute (IBIW) ponds at
Sunuga, Borok, USSR.
Pond No.
Acetone 0.5 5.0
Control Control pg/1 A"3/l
50.0
Total suspended
particulates, rag/1 1.0 1.9 1.9 5.5 6.0
Total inorganic
phosphorus, pg/1 27.5 6.0 5.0 8.0 8.0
NOj-N, fig/I 0.7 000 0
NOj-N, fig/1 10.0 2.0 2.6 4.0 4.0
Total N, mg/1 0.81 0.70 0.58 0.78 0.73
Biological oxygen
demand, mg O2/l 1.3 1.3 1.1 1.7 2.5
Total organic
carbon, mg/1 11.6 11.1 14.0 12.2 11.9
Total suspended
particulate carbon,
mq/1 0.6 0.3 nd 1.1 1.2
131
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SAMPLING PROCEDURE FOR POND MICROBIOTA
Pond microbiota sampled included bacteria, protozoa, algae, and
zooplankton. During the 1-month study, samples were taken 5 times from
each pond (except the control pond, where samples were taken 4 times).
We sampled once prior to treatment and at 4-day intervals subsequent to
dosing. Sediments were collected from each pond and subsampled for
chlorophyll a, heterotrophic activity, and percentage organic matter.
Bacterial density was determined using epifluorescence microscopy
and direct counts on membrane filters stained with erythrosin stain.
Heterotrophic flagellates were quantified using epifluorescence
microscopy with primulin stain. Rotifera were live-counted in
Sedgewick-Rafter cells. Zooplankton were sampled using a 10-liter
bucket following standardized techniques for small, shallow water bodies
(Metodika izutchenia 1976). In each pond, ten 10-liter zooplankton
samples were collected along a transect from the shore to the center for
a total of 100 L water per sample. Each 100-liter sample was
concentrated using a Juday net with brass screen (No. 73) to volume of
30 ml and preserved in 4 % formalin. In the laboratory, two subsamples
of either 0.5, 1, or 2 ml (depending on visual density of zooplankters)
were pipetted into Bogorov's counting chamber and zooplankters counted
and identified using a binocular microscope.
To collect water mites, the water volume filtered for sampling' was
approximately 4.25 m3per sample. In all experimental ponds, except in
the control, 3 samples were collected during the study period: before
dosing, after 7 days, and after 11 days. In the control pond, the
samples were collected before dosing and after 11 days.
Collected water mites were preserved immediately with Oudemans
fixation liquid. The identification of water mites' taxonomic status
was conducted in accordance with the classification "of B.A. Wainstein
(1980). Water mite species were identified using I.I. Sokolov's keyword
book (1940).
DATA ANALYSIS
For species identification, we used Manuilova (1964), Kutikova
(1970), Bening (1941) and Opredelitel presnovodnykh bespozvonotcnhykh
(1977). For quantifying uncommon zooplankton species, the entire sample
was enumerated. All zooplankters were divided into five groups:
Cladocera, Copepoda, Rotatoria, copepod nauplii and copepod copepodites,
and numerical analyses were performed on these groups.
The pond treatments were unreplicated. Comparisons were drawn
from responses over time for the various taxonomic groups. Data were
transformed by logarithms or arc-sine, as appropriate, to minimize
correlations between the mean and variance of samples.
RESULTS
Before the permethrin application, planktonic communities differed
among the ponds (Tables 2-4). At this time, Cladocerans dominated the
zooplankton in all ponds studied; however, density of Cladocera, as well
132
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Table 2. Density of common cladoceran species (individuals per liter pond water),
SPECIES
Control Pond
Bosmina longirostris
Ceriodaphnia sp.
Diaphanosoma brachiurum
Polyphemus pediculus
Simocephalus vetulus
Total density
Number of species
Acetone Control
Bosmina longirostris
Ceriodaphnia sp.
Polyphemus pediculus
Scapholeberis mucronata
Total density
Number of species
0.5 ug/1
Bosmina longirostris
Ceriodaphnia sp.
Polyphemus pediculus
Simocephalus vetulus
Total density
Number of species
5.0 pg/1
Bosmina longirostris
Ceriodaphnia sp.
Diaphanosoma brachiurum
Polyphemus pediculus
Sida ceystallina
Total density
Number of species
50.0 fig/1
Bosmina longirostris
Ceriodaphnia sp.
Polyphemus pediculus
Total density
Number of species
0
3.6
144.3
0.6
304.8
6.3
465.0
10
172.5
139.6
3.5
4.0
423.5
10
0.3
30.2
40.3
0.3
83.3
11
np
110.4
18.5
6.0
4.8
144.3
9
54.9
307.8
190.2
655.8
10
1
3.6
20.4
3.0
558.0
1.2
600.0
9
40.0
3.7
2.7
0.6
54.3
10
43.5
275.5
8.0
13.5
367.0
9
0.9
0.1
np
np
np
1.0
7
1.2
np
4.2
6.6
4
Density
sample day1
6
12.5
42.5
7.0
6.0
14.5
98.0
9
3.5
3.0
2.6
np
13.2
7
101.5
2.5
36.6
np
142.8
6
112.0
2.5
np
3.5
np
122.5
6
7.0
np
np
7.0
1
10
-
-
-
-
-
-
—
2.6
105.9
0.1
19.7
134.3
9
0.5
40.0
14. t
6.0
66.6
9
42.0
3.0
np
np
1.0
47.3
6
2.0
np
np
2.0
1
15
31.2
np1
19.0
np
np
63.6
6
161.5
26.0
4.0
36.5
238.5
9
3.0
2.0
3.0
9.5
45.0
12
69.0
2.0
np
7.5
0.5
89.5
5
15.6
np
np
15.6
1
'Days following pond dosing
2np » not present.
133
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Table 3. Density (individuals per liter pond water) of common copepod species
and of nauplii and copepodites.
SPECIES
Control Pond
Cyclops sp.
Eudiptomus gracilis
Heterocope appendiculata
Mesocyclops leuckarti
Paracyclops fimbriatus
Nauplii
Copepodites
Total density
Number of species
Acetone Control
Acanthocyclops viridis
Eudiaptomus gracilis
E. graciloides
Heterocope apendiculata
Mesocyclops leuckarti
Nauplii
Copepodites
Total density
Number of species
0.5 ug/i
Eudiaptomus gracilis
E. graciloides
Heterocope appendiculata
Mesocyclops leuckarti
Nauplii
Copepodites
Total density
Number of species
5.0 pg/1
Eudiaptomus graciloides
Heterocope
Mesocyclops leuckarti
Nauplii
Copepodites
Total density
Number of species
50.0 uafi
Acanthocyclops viridis
Cyclops strenuus
Mesocyclops leuckarti
Nauplii
t Copepodites
Total density
Number of species
'Days following pond dosing.
2np = not present.
3u = single organism
0
0.6
0.6
np
0.2
np
np
0.1
1.8
8
7.0
3.6
np
4.0
4.0
np
7.4
26.7
5
1.7
np
0.3
np
np
1.2
2.4
3
np
0.3
np
0.6
11.4
20.0
5
3.0
13.2
nd
nd
9.6
16.2
3
4'
1
0.6
np
1.8
1.2
np
np
6.0
3.6
3
0.3
1.2
10.5
6.3
np
0.5
2.4
18.3
4
2.0
1.0
0.2
2.0
4.5
1.1
5.4
7
0.6
1.0
5.5
7.0
5.5
8.2
6
nd
nd
nd
2.4
0.6
0
0
0/1
Density
sample day1
6
np2
0.1
0.1
1.5
np
7.0
15.5
1.7
3
0.1
0.8
1.0
0.3
0.1
4.0
5.0
2.3
5
0.2
np
2.0
np
12.0
18.0
2.2
2
1.0
1.5
3.0
13.0
12.5
5.5
3
nd
nd
nd
1.0
1.0
0
0
10
-
-
-
-
-
-
-
—
np
np
21.0
7.0
0.5
3.0
1.5
28.5-
3
0.2
np
0.6
3.5
14.5
11.5
4.4
4
0.3
0.1
6.3
29.0
18.0
7.6
7
nd
nd
u3
3.0
3.0
0
1
15
9.6
np
np
14.4
7.2
464.4
538.8
32.4
4
np
np
np
np
2.5
121.0
57.0
2.5
1
np
np
np
10.0
8.0
14.0
10.0
1
np
np
36.5
45.0
84.5
40.0
4
nd
nd
9.6
9.6
39.6
9.6
1
-------
Table 4. Density (individuals per liter pond water) of common Rotifera species.
SPECIES
Density
sample day1
10
15
Control Pond
Asplanchna priodonta
Brachiounus angularis
B. calcyciflorus
B. diversicornis
Filinia longiseta
Keratella quadrata
Synchaeta sp.
Trichocerca cylindrica
Total density
Number of species
Acetone Control
Brachiounus angularis
B . calcycifl orus
Euchlanis dilatata
F. longiseta
Filinia mayer
K. cochlearis
Keratella quadrata
Total density
Number of species
0.5
Asplanchna priodonta
Euchlanis dilatata
Filinia longiseta
F. mayer
K. cochlearis
Keratella quadrata
Lecane luna
Total density
Number of species
S.O ug/1
Asplanchna priodonta
Brachiounus calcyciflorus
Conochilus sp.
Euchlanis dilatata
Keratella quadrata
Total density
Number of species
np
np
np
np
np
np
0.3
np
0.3
1
6.0
np
0.6
np
3.6
4.2
np
np
18.6
8
10.0
35.0
13.0
5.5
5.5
21.0
np
4.5
169.0
19
12.0
200.4
1.2
202.8
194.4
1.2
np
327.6
1348.2
18
1.0
1.0
np
np
4.0
2.0
4.0
14.0
7
1.5
2.0
0.5
np
2.0
2.0
7.0
17.5
8
1.0
1.0
np
1.0
1.5
0.5
11.5
20.0
11
np
1.0
1.5
np
2.0
3.0
11.5
23.5
10
32.0
np
20.5
35.0
np
1.0
1.5
117.5
11
0.3
np
np
np
np
0.3
np
1.2
4
1.0
np
4.0
np
np
6.5
np
16.5
7
79.0
np
27.0
190.0
107.5
342.0
3.0
1008.5
18
1.5
8.0
np
5.0
2.5
53.0
11.5
94.0
15
0.5
8.0
1.0
np
np
3.0
5.0
21.0
11
1.5
np
0.2
nd
1.5
2.7
3
2.5
6.5
33.0
1.5
19.0
80.0
15
71.0
66.0
1.5
nd
215.5
603.0
21
44.0
157.0
2.0
64.0
120.0
592.0
21
np
np
np
23.0
18.5
64.5
11
135
-------
Table 4. (continued)
Density
SPECIES sample day1
01 6 10 15
50.0
Asplanchna priodonta
Brachiounus calcyciflorus
Euchlania dilatata
F, longiaeta
Filinia nayer
K. cochlearia
Keratella quadrata
Lee ana luna
Total density
Number of species
226.8
np
np
np
np
np
2.7
2.4
236.1
5
139.2
0.6
1.8
np
np
np
0.6
np
144.0
7
30.0
66.5
2.5
18.0
np
11.0
87.5
4.0
283.5
18
8.0
9.0
8.0
6.0
35.0
28.0
50.0
6.0
206.3
18
48.0
32.4
99.6
296.4
np
12.0
9.6
164.5
786.7
17
'Days following pond dosing.
2np » not present.
as dominant species from other orders, differed among ponds (Figure 1,
Table 2). The lowest initial density of Cladocera was in pond 3 (83.3
individuals per liter), while the highest density was in pond 5 (655.8
individuals per liter). Polyphemus pediculus and Ceriodaphnia sp.
dominated populations in ponds 1,3, and 5. Bosmina longirostris and
Ceriodaphnia sp. Were dominant in pond 2, and Ceriodaphnia sp. and
Diaphanosoma brachiurum in pond 4 (Table 2).
Initial copepod density was much less than that of the Cladocera
(range 1.8 to 26.7 individuals per liter, Table 3). Copepod density was
greatest in pond 2 and least in pond 1 (Figure 2, Table 3). Before
treatment, copepod nauplii were found only in pond 4 and their density
was very low, less than 1 nauplius per liter. Copepod copepodites were
present in all ponds, but at very low densities (Table 3).
Initially, the highest rotifer density was in pond 5 (Table 4).
However, this stemmed from one dominant rotifer species, Asplanchna
priodonta, which, at 226.8 individuals per liter, was very high compared
to the densities of all other rotifers in all ponds. Typically, total
rotifer density was much lower, not exceeding 14.0 individuals per
liter. Among the other rotifers, Keratella quadrata was dominant in
ponds 2-4, while in the control pond, the only species present at this
time was Synchaeta sp.
Density dynamics of zooplankton during the post-treatment period
are shown in Figures 1-4. Quantitative and qualitative changes occurred
in all ponds. By the end of the second week, cladoceran densities were
reduced in all ponds; however, their response dynamics were different
(Figure 1). In the control and 0.5 ug/1 permethrin ponds, cladoceran
136
-------
Acetone Control 0.5 //g/L Permethrin
—e— •
5.0 //g/L Peimethrin 50.0 /jg/L Permethrin
3 6 9 12 15
Days Post-dosing
Figure 1. Number of cladocera per liter in
IBIW experimental ponds dosed
with permethrin.
density initially increased, gradually decreasing to less than pre-
treatment densities. In these ponds, the initially codominant species,
Ceriodaph/iia sp. and Polyphemus pediculus, were replaced by Bosmina
longirostris (in the control pond) and Simocephalus vetulus (in the 0.5
ug/1 pond).
In ponds treated with 5.0 and 50.0 ug liter"1 permethrin (ponds 4
and 5, respectively), and in the control plus acetone pond (pond 2),
cladoceran densities decreased dramatically beginning on day 1. After
day 3, however, cladoceran density increased in ponds 2 and 4, but not
in 5. The only cladoceran species that survived in pond 5 was Bosmina
longirostris. This species became the most common cladoceran at the end
of the observation period in the acetone control and the 5.0 ug liter"1
permethrin ponds (Table 1).
Density dynamics of early life-stage copepods were generally
similar among the ponds (Figure 4). However, there were marked
numerical differences among the populations. In the control pond,
copepod nauplii and copepodites reached densities as high as 464.4 and
538.8 individuals per liter, respectively (Figures 3 and 4
respectively). In all other ponds, and especially in the 50.0 ug liter"1
permethrin pond, their densities were much less (Table 3). However,
after day 15, there was a distinct increase in copepodites and nauplii.
This phenomenon has been described by Solomon et al. (1980) and Kaushik
et al. (1985). The copepodites and nauplii may show recovery as the
permethrin concentrations in the ponds decrease.
137
-------
By the end of the observation period, Mesocyclops leuckarti was
the most common copepod species in all ponds. However, it was the only
copepod species in the acetone control, 0.5 ug liter'1, and 50.0 ug
liter'1 permethrin ponds, while in the control and 5.0 ug liter"1
permethrin ponds, each copepod population consisted of four species.
But, in fact, the copepod community was less complex in the 5 ug liter"1,
because M. Leuckarti was accompanied only by single individuals of
Cyclops sp., Acanthocyclops sp., and Ectocyclops sp., while in the
control pond Cyclops sp. and Paracyclops fimbriatus were codominant with
M, leuckarti (Table 3).
Rotifers increased in both the control and acetone control ponds
(Figure 5); however, there was an order of magnitude difference in
density between the two ponds at the end of the experiment (Table 4). In
the control pond, four rotifer species were codominant: Filinia
longiseta, Brachionus angularis, M. diversicornis and Trichocerca
cylindrica, while in the acetone control pond, F. Longiseta, B.
angularis, and Euchlanis dilatata dominated the population.
Rotifer density in the 0.5 ug liter'1 permethrin ponds peaked 4
days after permethrin application and then decreased to pre-treatment
Control Acetone Control 0.5 j/g/L Permethrin
5.0 >jg/L Permethrin 50.0 pg/L Permettirin
0
12
15
Days Post-dosing
Figure 2. Number of copepods per liter in IBIW
experimental ponds dosed with permethrin.
138
-------
500
Control Acetone Control 0.5 £ig/L Permethrin
5.0 //g/L Permethrin 50.0 fjg/L Permethrin
0
12
15
Days Post-dosing
Figure 3. Number of copepod nauplii per liter
in IBIW experimental ponds dosed
with permethrin.
levels. The peaks in density were primarily a function of the increased
number of Keratella quadrata in both ponds, K. cochlearia and Filinia
mayer in pond 3, and Asplanchna priodonta and Brachionas calyciflorus in
pond 4 (Figure 4). By the end of the experiment, K. quadrata and
Euchlanis dilatata codominated the rotifer populations in both ponds,
but their densities were low. In pond 5, 1 day after permethrin was
applied, total rotifer density was slightly decreased. However, the
rotifers gradually increased and reached a density of 786.7 individuals
per liter. The dominant species at the beginning of the experiment in
pond 5, Asplanchna priodonta, became much less abundant than Filina
longiseta and Euchlanis dilatata by day 15. Interestingly, the rotifer
population in pond 5 consisted of 17 species, which was nearly that of
the control pond (with 18 species) (Table 4).
Water mites of Eylais and Fiona genera were dominant in all the
experimental ponds. The list of water mites collected from the IBIW
ponds is provided in Table 5. Water mites of other species were found
only in single exemplars. Before permethrin was added to any ponds, the
greatest density of water mites of Eylais was found in pond 3 and for
Fiona, the greatest density was in pond 4. During the experimental
period, the number of Eylais increased in ponds I (control) and 2
(control plus acetone) by 26% and 300%, respectively.
After permethrin was added, the number of water mites of both
genera decreased in all treated ponds (except for the Fiona mites in
139
-------
pond 3). In pond 3, after 7 days, the number of Eylais decreased 32.5%
compared to. pre-treatment levels and decreased by 29.1% after 11 days
post-treatment. In pond 4, density decreased to 20.4% of original at 7
days and thereafter. The Fiona in pond 3 increased in number, but this
increase was very slight. We assume these mite densities, in fact, did
not change after adding permethrin at a concentration of 0.5 ug liter"1.
In pond 4, the decline in number of water mites of this genus was much
more pronounced. Seven days after treatment, the number was only 27.5%;
11 days after treatment only 14.5% compared to pre-treatment period. In
pond 5, no water mites of either Eylais and Fiona, as well as other
genera, were found after pond dosing.
DISCUSSION
Published laboratory and field experiments have demonstrated that
synthetic pyrethroids exert a toxic effect on zooplankton, especially
crustaceans (Day 1989, Crossland 1982, Kaushik et al. 1984, Perevoznikov
et al. 1984). Permethrin concentrations as low as 1.0 ug liter"1 and less
were referred as acutely toxic for the variety of crustaceans (Day
1989). However, exposures simulating natural conditions help to
complete a full evaluation of the effects of pyrethroid insecticides on
natural planktonic communities.
Our pond experiments have shown that at a nominal permethrin
concentration of 0.5 ug liter"1, acutely toxic for a variety of aquatic
invertebrates when tested in laboratory conditions, did not produce a
marked direct effect even on species shown to be sensitive to a variety
of toxicants, such as Ceriodaphnia (Winner 1988). Furthermore, while
600
Control
5.0 /jg/L Permethrin 50.0 //g/L Permethrin
Acetone Control 0.5 fig/L Permethrin
12
15
Days Post-dosing
Figure 4. Number of copepod copepodites per
liter in IBIW experimental ponds
dosed with permethrin.
140
-------
Acetone Control 0.5 ug/L Permethrin
—©—
5.0/jg/LPermethrin 50.0/jg/LPermethn
12 15
Days Post-dosing
Figure 5. Number of rotifers per liter in
IBIW experimental ponds dosed with
permethrin.
5.0 ug liter"1 permethrin led to a dramatic decrease in density of
cladocerans and copepods, the effects were less than would be expected
on the basis of laboratory-measured responses.
Our results indicate that, in the control and acetone-control
ponds, the density of Eylais water mites increased during the
observation period. In the permethrin-treated ponds at concentrations of
0.5 and 5.0 ug liter"1, their density decreased (Figure I). On the other
hand, Fiona density decreased both in controls and in the 5.0 ug liter"1
permethrin-treated pond; however, in the treated pond, the effect was
more pronounced. The concentration of 0.5 ug liter"1 seems to have no
effect on this genus of mites (Figure 2). Eylais mites seem to be more
susceptible to the permethrin than the Piona. However, at the
permethrin concentration of 50.0 ug liter"1, all Eylais and Piona water
mites suffered complete mortality.
Hence, results of this study demonstrate the susceptibility of
certain water mites to permethrin under field conditions. This is in
good accordance with published results on the toxicity of insecticides
to water mites (Nair et al. Stephenson et al. 1986, Crossland and Wolff
1985). However, our results are quite different from the results of
investigations on the effects of industrial pollutants on aquatic mites
(Alexeev 1986). Evidence exists to indicate that the primary reason for
the elimination of water mites was the direct toxic effect of
permethrin. That the elimination of this planktonic invertebrate was
due to an elimination of more sensitive prey zooplankters seems unlikely
because the mites have been shown to survive more than 15 to 20 days
when starved (Zhavoronkova, unpubl.).
141
-------
Table 5. Acari present in Sunuga ponds.
FAMILY SPECIES
Hydrachnidae Hydrachna ap.
Eylaidae Eylaia mullari Koenike, 1897; E. extender*a O.F.
Mull., 1776; E. hamata Koenike, 1897; E. koenikei,
1903
Hydriphantidae Hydryphantea ap., Hydrodroma ap.
Limneaiidae Limnesia ap.
Hygrobatidae Fiona coccinea (C.L. Koch), 1836; P. nodata (O.F.
Muller), P. variabilia (C.L. Koch), 1836;
Hydrochoreutoa ap., Acercua ap.
Arrhenuridae Arrhenurus ap.
Our experiment was performed in mature ponds, all with extensive
macrophyte growth. The biomass of submerged higher aquatic plants was
high, as was the concentration of suspended solids. The propensity of
permethrin to adsorb quickly onto solid surfaces (e.g., suspended
solids, particulate organic matter, etc.) is well known (Muir et al.,
Sharom and Solomon 1979).
The IBIW ponds are relatively productive. High ecosystem
productivity, with associated high plant surface area and concentration
of particulate organic material, lessened the bioavailability of
pentachlorophenol in a mesocosm study (Robinson-Wilson et al. 1983).
Functional redundancy in the macrophyte community within mesocosms also
lessens the potential for measuring ecological damage (Fairchild et al.
1994). Empirical laboratory results (McCarthy and Bartell 1988) show
that for periphyton, macrophytes and detritivorous fish, there is a
decrease in toxic effects of phenol to daphnia. The lessened toxicity
was directly related to increased particulate organic matter (POM).
However, for phytoplankton , zooplankton, benthic invertebrates and
omnivorous fish, greater reduction in toxic effects corresponded to
increasing dissolved organic material (DOM) in the system. Bacterial
and zooplanktonic growth was dramatically enhanced as a function of
available organic material and, presumably, greater surface area for
microbial activity.
Higher levels of primary production corresponded to lower
pentacholorophenol (PCP) residues and toxicity to fish in a pond-
mesocosm study (Robinson-Wilson et al. 1983). Yet, lower PCP toxicity
could not be ascribed solely to an increase in primary production.
Their results indicated that the larger surface area available within
142
-------
the macrophyte-dominated ponds contributed to an active epiphytic
community which degraded the PCP. In a similar manner, the adsorption
of permethrin onto plant surfaces and suspended solids in these ponds
was apparently high and may explain the less pronounced direct toxic
effect of the 0.5 and 5.0 ug liter"1, permethrin concentrations, and the
greater susceptibility of active filter-feeding cladocerans (Polyphemus
pediculua, Sida crystallina, Diaphanosoma brachlurum) and copepods
(Eudiaptomus gracioloides), while predatory copepods such as Mesocyclops
leuckarti appeared to be much less susceptible to the insecticide.
Among the active filter-feeding zooplankters, such as Polyphemus
pedlculus, Daphnia longispina, Sida crystallina, Eudiaptomus gracilis,
and E. Graciloides, are the most sensitive to the toxic effects of
permethrin. Of the zooplankton collected in our experiment, Rotifera
were the most resistant to permethrin. This agrees well with previous
results reported by Kaushik et al. (1985). The reasons for such
resistance, as well as factors influencing rotifer population dynamics
as a function of permethrin, were discussed by these authors in detail.
The reasons for the noted changes in zooplankton density following
acetone application are not clear. The decline in Cladocera no doubt
stems from unmeasured pond-to-pond differences. Such pond-to-pond
differences have recently been documented in a separate study
(Hellenbrant 1994). Different rates of decline and growth in
zooplankton as a result of permethrin exposure were observed by Kaushik
et al. (1985). They note zooplankton numerically respond to an
insecticide in two ways, direct reduction from acute toxicity and
indirect numerical responses attributed to release from predatory or
competitive pressures.
There is evidence that the recovery of zooplankton populations in
mesocosms is a function of their relatively short generation times, the
number of times they are exposed, and the persistence of the pesticide
in the water column (Fairchild et al. 1991). In that study, zooplankton
responded much more dramatically to pulsed addition (6 dosing periods
over 12 weeks) of esfenvalerate than to similar concentratioins dosed
twice over the same period. There was a minimal effect on cladocerans in
ponds dosed one time at 0.1 mg liter"1 carbaryl (Hanazato and Yasuno
1990). In ponds dosed twice, the cladocerans were able to recover
within to 15 days. However, in ponds dosed 10 times over a period of 20
days, each time at the 0.1 mg liter"1 concentration, the cladocerans
failed to recover.
Recovery of copepod densities after permethrin application in this
experiment occurred after 2 weeks, even in the highest concentration.
The major source of recovery was the appearance of the neonatal
individuals (Figures 3 and 4).( High resistance of eggs of these
copepods to a variety of the environmental stressors has been noted by
previous investigators (Makrushin 1984). It is important to note that
another route of recovery for planktonic populations exists, that of
immigration of smaller or younger forms into the experimental ponds.
This remains an uncontrolled variable in similar ponds and mesocosm
studies.
The effect of pesticides on aquatic organisms needs to be studied
relative to the potential for recovery and recolonization of the
species. An important aspect of disturbance on communities is the rate
143
-------
at which the habitat becomes less suitable in relation to the
requirements of the organisms (Southwood 1988). In effect, the number of
dosing intervals and the concentration of the pesticide become points on
disturbance and adversity axes. Over sufficient time, disturbance and
periods of adversity have a strong influence on the biotic structure of
communities. Incorporating such factors into future mesocosm studies
will allow a study of species dynamics relative to the degree and
frequency of disturbances.
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THE EFFECT OF HEAVY METALS AND CHLORPYRIFOS. SEPARATELY AND
IN COMBINATION. ON A CONTINUOUS FLOW MESOCOSM AQUATIC SYSTEM
by
G. A. Vinogradov1, F. Stay2, P. P. Umorin1, A. S. Mavrin1, A. K. Klerman1,
E. I. Koreneva1, S. A. Kurbatova1, I. O. Solntseva1 and G. I. Vinogradova1
ABSTRACT
Pollutants selected for testing were heavy metals and the pesticide chlorpyrifos. A
flow-through aquatic system was found to be useful to test biological effects of these
toxicants separately and in combination. The continuous flow is more natural, as pollutants
are usually being continuously added to a waterbody. This ecosystem-level testing is seen
as the only strategy available to obtain ecologically relevant information. A good fit of
predicted and observed effects shows that mathematical modeling can be applied to such
systems.
INTRODUCTION
Test systems at different levels of biological order can be used to identify potential
impacts of pollutants in an attempt to predict possible damage that would occur in natural
ecosystems. Ecosystem-level testing is advocated as the only strategy available to obtain
ecologically relevant information, and a variety of model ecosystems are used in studies of
aquatic pollution (Andrushkaitis et al. 1989, Lundgren 1985).
This research was carried out by the Experimental Ecology Laboratory of the Institute
for the Biology of Inland Waters, Russian Academy of Science, as a part of the joint USA and
USSR project on the evaluation of techniques used to predict effects of environmental
pollutants. In 1986, the Environmental Research Laboratory at Duluth, Minnesota, performed
studies on effects of chlorpyrifos on a natural aquatic system using littoral enclosures. We
developed a flow-through mesocosm test system using 1.5 m3 tanks designed to measure
toxicant effects on main ecosystem structure variables. The rationale behind this test system
is that it is large enough to include larger organisms, such as fish, and it is more easily
Institute for the Biology of Inland Waters, Russian Academy of Science, Borok, Nekouz,
Yaroslaval, Russia.
2U.S. Environmental Protection Agency, Environmental Research Laboratory, Duluth, MN
(USA).
148
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controlled and monitored than bigger systems such as ponds. The continuous flow regime
was chosen because flow-through systems tend to approach a steady state depending on
system inputs and, therefore, are easier to control and to model mathematically. The other
factor which contributed to the decision to work with this system was to compare different
approaches to the same problem used in the USA and USSR. Since many contaminants
contribute to the pollution of natural aquatic systems, it was of interest to look at effects of
the combination of some pollutants. Heavy metals and the pesticide chlorpyrifos were
selected because of the high priority status given these substances in both countries.
METHODS
Twenty-four fiberglass tanks half filled with water were placed into a pond and served
as a thermostat. The experiment was conducted at natural illumination and temperature.
The tanks were filled to a volume of 1.5 m3 with pond water containing natural plankton
assemblages, and a 5 cm thick layer of bottom sediments taken from the same pond was
added to each tank. The pond water first passed through plankton gauze net (mesh size 80
/vrn) and was then continuously pumped into the tanks at a dilution rate of 0.33/day. The
same kind of net was installed at the outlet of each tank to prevent washout of organisms
bigger than 80 //m.
The experimental design consisted of eight treatment tanks, each with three
replicates. Treatment tanks (the first four tanks were without fish) were as follows: 1 =
chlorpyrifos (Ch), 2 = heavy metals (HM), 3 = chlorpyrifos and heavy metals (Ch + HM), 4 =
control (C); the second four, tanks 5-8, received the same treatments but with fish (+ F). The
HM included zinc, cadmium, copper, and mercury in concentrations of 150.0, 15.0, 7.5, and
1.5 /yg/L, respectively. The mixture of the HM was continuously supplied to the tanks by a
diluter designed by G. A. Vinogradov (Vinogradov and Tagunov 1989) to provide the above
concentrations in the total inflow. These concentrations were selected taking into account
our mesocosm experiments of 1989 which revealed different crustacean species' sensitivity
to the heavy metals used in this research. Chlorpyrifos was added manually once a week to
attain a concentration in the tank of 0.1 //g/L. This concentration was chosen on the basis of
the results of preliminary 10-day experiments with zooplankton communities, which showed
that this chemical causes statistically significant changes in the abundances of crustaceans
without elimination of any of the zooplankton groups. Fish treatments initially contained 10
bream (Abramis brama) underyearlings (each weighing 0.4 g on the average) per tank.
According to preliminary 10-day experiments, such a density offish exerted the same
influence on zooplankton as the toxicants.
To measure effects of the toxicants, we monitored weekly what we believe to be
principal structural ecosystem variables. They included phytoplankton (chlorophyll a
concentration), bacterioplankton (number of cells), and zooplankton (number and size
structure of crustaceans and rotifers). Concentrations of principal ions, nutrients, dissolved
oxygen, and organic matter were determined to provide information about general conditions
under which the experiments were performed. No significant differences were found in these
parameters among treatments and over the time period. Average values are given in Tables
1-4. Fish studies included determinations of linear and mass growth of fish and their
resistance to flow.
149
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TABLE 1. CONTENTS OF PRINCIPAL IONS IN THE MESOCOSM WATER, MMOL/L
CaH
Na+
HCO
SO
Cl
PH
0.43
1.04
0.21
0.10
1.70
0.22
0.15
6.9-9.0
TABLE 2. CONCENTRATIONS OF NUTRIENTS (MG/L), DISSOLVED ORGANIC MATTER (DOM,
MG/L), AND DISSOLVED OXYGEN (DO, MG/L) IN THE MESOCOSM WATER
Nitrate Nitrite
Ammonium P miner P total
DOM
DO
max1
DO
50
1.0
30
20
40
10
9.0-12.8 6.8-9.0
fDO max measured at 1 pm; DO min measured at 5 am.
TABLE 3. TEMPERATURE REGIME IN MESOCOSMS
T min
T max
25/07
16.7
20.6
02/08
15.8
19.3
09/08
18.3
23.7
16/08
17.2
20.8
23/08
18.0
17.3
30/08
10.1
13.2
12/09
9.6
11.3
TABLE 4. AVERAGE MEASURED CONCENTRATIONS OF HEAVY METALS IN THE CONTROL AND
HEAVY METAL TREATMENTS, MG/L (MEANS AND STANDARD ERRORS)
Control
Heavy metal treatments
Zn
Zn
Cd
Cu
Hg
14.9 1.9
103.4 17.2
< 1
'Below analytical detection level.
150
-------
To analyze experimental results, we used mostly multivariate statistics (Dillon and
Goldstein 1984). Differences among treatments and effects were assessed using 2-way
ANOVA with repeated measures (Vanni 1986). To predict major changes in the principal
ecosystem living components in response to the influence of some anthropogenous pollutants
(such as heavy metals and pesticides), a mathematical model was developed.
MODEL DESCRIPTION
Because of the lack of space, only some principal aspects of the model are described
here. The model includes the usual components of trophic levels found in any ecosystem:
higher aquatic plants, planktonic and periphytic (or benthic) algae and bacteria, herbivorous
and carnivorous zooplankton, and fish. Dead organic matter is represented by detritus
(particulate matter), dead plants, and fish.
For the purpose of ecosystem simulation, various biotic components have been
subdivided into groups, based upon size, trophic function, and sensitivity to a toxicant. For
instance, copepods are divided into two trophic groups, herbivorous and carnivorous.
However, to assess their sensitivity to the toxicant, they are classified as one group. Further,
algae are divided into two size classes to measure growth rates and consumption by
herbivores; however, they are combined into one group to assess their sensitivities to the
toxicant. Herbivorous copepods and cladocera are lumped into one group of "herbivorous
Crustacea," but they are split into two groups according to their sensitivity to toxicants (i.e.,
cladocera are generally much more sensitive to toxicants than are copepods). This
generalization is carried through into the model equations (Baudouin and Scoppa 1974,
Anderson 1982, Kaushik et al. 1985).
Mathematically, the model is essentially a system of differential equations. These are
mass balance equations describing the flow of one chemical element through various trophic
levels in aquatic systems. It is nitrogen in the model, but could be applied to any other
biostructural element without changing the model structure. The model is based upon the
following assumptions: growth rates of the organisms are functions of food substrate
concentrations which follow generally accepted Michaelis-Menten kinetics. Equations for the
living components are Verhulst-Pearl equations, whereby the natural mortality of the
organisms is proportional to the square of their biomass. A limiting substrate for the
planktonic and periphytic algae and bacteria is assumed to be mineral nitrogen dissolved in
the water. Higher plants are assumed to take their nitrogen from a source external to (not
part of) the system (e.g., deeper layers of the bottom sediments). However, the material is
added to the system during lysis of dead bodies; therefore, this assumption is valid for only
rooted submersed vegetation.
As for benthic and periphytic organisms, their carrying capacities are assumed to be
functions of the area available for their settling, i.e., surfaces of bottom sediments, higher
plants, and side walls (or banks) of the containers.
Generally, the equations describe biomass growth, food consumption (including
grazing and predation), natural mortality, and the effect of chemical toxicity to these biotic
151
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components. Coefficients of feeding selectivity are incorporated using the entire diet, with
proportions established based upon percentages in the diet.
At this initial stage, the model is meant to describe changes over relatively short time
periods, usually used in experimental studies (not more than 2 months). For these shorter
time periods, seasonal periodicity in the organisms' reproduction, and changes in the light
and temperature regime can be neglected. The model will serve to describe batch (static)
and flow-through systems.
Model parameters used in simulations were taken from the literature (Eppley et al.
1969, Buhr and Miller 1983, Kokova 1982, Kruychkova 1974, Zaika 1972, 1983). It should be
noted, however, that cited literature sources do not usually contain the needed parameters;
the latter had to be recovered from the quantitative data provided in the sources. With these
parameters, the model predicted correctly (qualitatively and in many cases, quantitatively) the
effects of factors applied in the experiments. After experimental data were obtained, the
model was calibrated to achieve a better fit of predicted and observed effects. Tables below
contain model simulation data after such calibration.
RESULTS AND DISCUSSION
Here we present the results of observations of the main ecosystem variables over a
period of 1 month (from July 27 until August 27) during which time toxicants were applied to
the experimental mesocosms. The period of recovery that followed is not considered. The
most pronounced changes due to toxicant application occurred in the zooplankton
community.
The natural seasonal course of zooplankton, as observed in the control mesocosms,
was characterized by an increase in Cladocera from 25 to 55% of total zooplankton
abundance. At the same time, Copepoda decreased from 72 to 38%. The abundance of
Rotifera only slightly increased during the observation period (from 3 to approximately 15%).
Effects of the toxicants, separately or in combination, are shown in Tables 5-9. They
were calculated as differences between the means of treatments and corresponding controls,
so that positive values mean an increase and negative values a decrease compared to the
control. Fish are also considered as a factor which influences other ecosystem variables.
Since biomasses of the mesocosm living components were not estimated and the
model provided data in terms of biomass, we do not compare here the time courses of the
components in the model and the experiments. Still, we can assess effects of factors within
the model and the experiments and compare these effects. Comparisons are valid provided
there are no significant differences in the size structure of the compared populations among
treatments, so that linear relationships between biomass and number may be assumed. This
was not the case with crustaceans; therefore, model values of their biomasses were
converted into organism numbers for assessments of the effects, taking into account the size
structure of their populations.
152
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TABLE 5. EFFECTS (PERCENT OF CONTROL) OF INDIVIDUAL FACTORS UPON MAIN ECOSYSTEM
VARIABLES. UPPER LINE FOR EACH CELL REPRESENTS EXPERIMENTAL DATA, LOWER LINE =
COMPUTER SIMULATION, SIGN. 1 = SIGNIFICANCE LEVEL
Ecosystem
variables
Cladocera
abundance
Copepoda
abundance
Rotifera
abundance
Algae
abundance
Bacteria
abundance
Number of
Cladocera
Copepoda
Rotifera
Heavy metals
Effect
-44.76
-36.30
16.78
11.39
-42.66
-29.22
-4.25
3.94
9.24
8.33
species
-5.64
-1.87
-11.70
Sign. 1
<0.01
0.07
<0.01
0.35
0.25
0.20
0.35
<0.05
Chlorpyrifos
Effect
-53.24
-57.54
33.32
21.65
37.31
11.34
24.29
4.43
12.60
13.41
-26.15
-18.44
-3.02
Sign. 1
<0.01
<0.01
<0.01
<0.05
0.14
<0.01
<0.01
0.31
Fish
Effect
-44.26
-50.25
53.34
49.29
75.36
73.16
60.04
13.57
43.80
27.26
-6.64
-5.88
24.46
Sign. 1
<0.01
<0.01
<0.01
<0.01
<0.01
<0.05
0.08
<0.01
Analysis of the whole body of data (Tables 5-7) has shown that the direct individual
effect of heavy metals and Chlorpyrifos is a reduction in abundance of the most sensitive
species due to acute toxicity. This was indicated by an overall decline in abundance of
cladocerans. These crustaceans have been found to be the species most sensitive to
toxicants in many other studies (Baudouin and Scoppa 1974, Hurlbert 1975, Kaushik et al.
1985). In our experiments, only three species persisted in the toxicant treatments. These
were Ceriodaphnia quadrangula, Bosmona longirostris, and Daphnia longispina.
Judging by a reduction in the number of species, both types of pollutants are directly
toxic to copepods but to a lesser extent than to cladocerans. On the whole, Chlorpyrifos
appeared to be more toxic than the heavy metals as seen by the greater reduction in
cladoceran abundance and a greater and highly statistically significant reduction in species
richness of both groups of crustaceans. The mathematical model used here showed a
decrease in the biomass of copepods exposed to both toxicants. In real experiments,
however, abundance (number of individuals) of the copepods significantly increased. An
analysis of the size structure of the copepod population revealed that elimination of larger
species and specimens occurred, and the ratio of large to small individuals suffered an
almost 5-fold decrease. One of the events was complete elimination of the adults of
Mesocyclops crassus and M. oithonoides. The copepod population consisted mostly of
nauplii and copepodites rather than adults, probably because the toxicants induced some
153
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hindrances to growth or moulting. It is only after model biomass data were converted into
organism numbers that a good fit of the observed and predicted effects of factors was
obtained.
As seen from Table 5, the mixture of heavy metals in the concentrations used is
probably directly toxic to rotifers because the effect is great and statistically significant. In the
literature (Moore and Ramamoorthy 1984), rotifers have been noted to be among the
organisms most sensitive to heavy metals. The toxic effect of chlorpyrifos is insignificant
judging by a decrease in species richness and by the fact that their abundance did not
diminish.
Both types of toxicants apparently were not directly toxic to algae and bacteria, as
negative effects are small and statistically insignificant. Concentrations of toxicants used in
the experiments were below acute toxicity and growth inhibition concentrations reported in
the literature for algae and bacteria (Hurlbert et al. 1972, Roberts and Miller 1970, Maly and
Ruber 1983, Stratton et al. 1980, Moore and Ramamoorthy 1984).
TABLE 6. EFFECTS (PERCENT OF CONTROL) OF A COMBINATION OF FACTORS UPON MAIN
ECOSYSTEM VARIABLES. UPPER LINE FOR EACH CELL REPRESENTS EXPERIMENTAL DATA,
LOWER LINE = COMPUTER SIMULATION, SIGN. 1 = SIGNIFICANCE LEVEL, INTER. =
INTERACTION
Ecosystem
variables
Cladocera
abundance
Copepoda
abundance
Rotifera
abundance
Algae
abundance
Bacteria
abundance
Number of
Cladocera
Copepoda
Rotifera
Heavy metals
Effect
-72.05
-75.21
54.21
35.52
-22.35
-21.34
18.20
8.57
-4.91
23.77
species
-30.36
-19.49
-14.33
Sign. 1
<0.01
<0.01
<0.01
0.11
0.36
<0.01
<0.01
<0.05
+ chlorpyrifos
Inter.
25.85
18.63
4.12
2.47
16.99
-3.46
-2.14
0.89
-1.50
1.33
1.43
0.82
0.39
Sign. 1
0
>0
0
0
>0
0
0
0
.27
.05
.07
.26
.50
.25
.30
.46
Heavy metals + fish
Effect
-61.99
-73.09
86.36
67.41
0.68
12.12
63.22
18.53
56.81
39.72
-10.78
-7.63
10.58
Sign. 1
<0.01
<0.01
>0.50
<0.01
<0.05
0.09
0.16
0.15
Inter.
22.93
13.46
16.24
6.72
-32.03
-31.81
7.43
1.04
3.71
4.11
0.50
0.13
-2.17
Sign. 1
0.29
0.35
0.47
<0.01
>0.50
0.46
>0.50
0.35
154
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TABLE 7. EFFECTS (PERCENT OF CONTROL) OF A COMBINATION OF FACTORS UPON MAIN
ECOSYSTEM VARIABLES. UPPER LINE FOR EACH CELL REPRESENTS EXPERIMENTAL DATA,
LOWER LINE = COMPUTER SIMULATION, SIGN. 1 = SIGNIFICANCE LEVEL, INTER. =
INTERACTION
Ecosystem
variables
Cladocera
abundance
Copepoda
abundance
Rotifer a
abundance
Algae
abundance
Bacteria
abundance
Number of
Cladocera
Copepoda
Rotifer a
Chlorpyrifos + fish
Effect
-72.63
-81.52
103.92
81.13
91.19
85.57
94.32
19.46
24.98
48.49
species
-30.63
-22.66
19.46
Sign. 1
<0.01
<0.01
<0.01
<0.01
0.28
<0.01
<0.01
<0.05
Inter.
24.86
26.28
17.26
10.18
-21.48
-31.81
9.69
1.45
-23.40
7.79
1.16
1.67
-1.97
Sign. 1
0.27
0.21
<0.01
<0.01
>0.50
0.25
0.10
0.28
Heavy metals + Chlorpyrifos + fish
Effect
-83.75
-88.20
136.72
123.43
-11.38
35.18
78.72
25.74
17.05
70.69
-39.11
-21.13
-1.94
Sign. 1
<0.01
<0.01
0.42
<0.01
0.23
<0.01
<0.01
0.41
Inter.
58.41
55.89
33.28
41.07
-81.39
-20.09
-1.66
3.79
-23.40
21.67
-1.68
5.08
-11.67
Sign. 1
0.11
0.16
0.06
<0.01
>0.50
0.16
<0.05
0.48
When fish are considered as another factor (actually predation by fish), the effect is,
superficially, similar to effects of the toxicants; although some principal differences emerge.
Fish presence caused almost the same magnitude of decline in cladoceran abundance and in
the biomass of copepods as did toxicants, but their effect on crustacean population size
structure was more dramatic. Fish predation appeared to be much more size selective than
toxicity: the ratio of small cladoceran forms to larger ones in the toxicant treatments
increased only slightly over the control ratio, while in the fish treatment, the large forms were
near complete extinction. As for copepods, this ratio in the presence of fish was almost twice
as great as in toxicant treatments. On the whole, the main effect of fish is selective
elimination of large crustacean forms.
Concerning direct effects of fish on rotifers, algae, or bacteria, it seems from the
information stated, that fish did not feed on any of them, as their diet consisted mostly of
crustaceans.
Several indirect effects of factors applied here were observed. Indirect or secondary
effects may be described as changes in ecosystem variables resulting from changes caused
by direct toxicity to some most sensitive populations (or by predation in case of fish). The
155
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decline in the cladoceran population due to toxicant effects caused a significant increase in
the number of algae (mostly small forms as the model showed), which comprise the main
food item for herbivorous copepods and for immature stages of the predators (Wylie and
Currie 1991). This led to release of these forms of copepods (and rotifers in the case of
chlorpyrifos) from competition pressure and to an increase in their abundance. The model
and experimental observations showed an increase in small herbivorous copepods; predators
changed very little. Correlation analysis of the whole body of experimental data revealed a
negative relationship between abundances of herbivorous copepods and cladocerans
(r = -0.82, p < 0.05), which supports the paradigm of their competition.
Secondary effects offish addition also included increases in abundances of algae,
bacteria, rotifers, and copepods. These effects were even more pronounced than those of
the toxicants because in addition to cladocerans, fish also greatly reduced large copepods
which are mostly predatory. Therefore, rotifers and herbivorous copepods were released not
only from competition but also from predation. Both invertebrate predation and competition
have been found to be very important in determining freshwater zooplankton community
structure (Vanni 1988, Soto and Hurlbert 1991) and contribute to the scarcity of small
TABLE 8. EFFECTS (PERCENT OF CONTROL) OF INDIVIDUAL FACTORS AND THEIR
COMBINATION UPON MAIN ECOSYSTEM VARIABLES WITHOUT FISH. UPPER LINE FOR EACH
CELL REPRESENTS EXPERIMENTAL DATA, LOWER LINE = COMPUTER SIMULATION, SIGN. 1 =
SIGNIFICANCE LEVEL, INTER. = INTERACTION
Ecosystem
variables
Cladocera
abundance
Copepoda
abundance
Rotifera
abundance
Algae
abundance
Bacteria
abundance
Number of
Cladocera
Copepoda
Rotifera
Heavy
Effect
-51.78
-35.38
36.78
13.15
-8.20
-25.34
32.44
7.34
7.99
18.44
species
-8.82
-2.41
1.46
metals
Sign.
1
<0.01
0.50
Chlorpyrifos
Effect
-55.82
-58.02
35.18
28.71
46.29
38.14
13.14
11.78
-17.63
33.33
-24.32
-23.02
-14.77
Sign.
1
<0.01
<0.05
<0.01
0.26
0.19
<0.01
<0.01
0.09
Heavy metals
Effect
-75.81
-75.92
76.55
46.71
15.24
3.70
43.77
20.15
-10.90
60.34
-30.17
-24.65
-12.90
Sign.
1
<0.01
<0.01
<0.05
0.10
0.32
<0.01
<0.01
0.20
+ chlorpyrifos
Inter.
31.79
17.48
11.59
4.85
19.25
-9.44
-1.80
1.02
-1.26
8.57
2.98
0.78
0.40
Sign.
1
0.28
>0.50
0.17
0.34
>0.50
0.16
0.42
>0.50
156
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TABLE 9. EFFECTS (PERCENT OF CONTROL) OF INDIVIDUAL FACTORS AND THEIR
COMBINATION UPON MAIN ECOSYSTEM VARIABLES WITH FISH. UPPER LINE FOR EACH CELL
REPRESENTS EXPERIMENTAL DATA, LOWER LINE = COMPUTER SIMULATION, SIGN. 1 =
SIGNIFICANCE LEVEL, INTER. = INTERACTION
Ecosystem
variables
Cladocera
abundance
Copepoda
abundance
Rotifer a
abundance
Algae
abundance
Bacteria
abundance
Number of
Cladocera
Copepoda
Rotifer a
Heavy
Effect
-30.03
-38.40
5.46
10.24
-57.28
-31.79
-21.82
1.04
10.12
1.03
species
-2.15
-1.29
-21.09
metals
Sign. 1
0.12
0.38
<0.01
0
<0.05
0.32
>0.50
>0.50
<0.01
Chlorpyrifos
Effect
-48.35
-46.42
31.06
23.66
13.98
-2.70
32.39
-1.62
-9.02
0.00
-28.04
-13.31
7.55
Sign. 1
<0.01
<0.05
<0.01
<0.01
0.39
<0.01
<0.05
0.19
Heavy metals
Effect
-73.62
-63.62
37.92
34.81
4.69
-33.63
3.40
-0.59
0.21
1.03
-30.57
-13.85
-15.56
Sign. 1
<0.01
<0.05
>0.50
0.43
>0.50
<0.01
0.06
0.07
4- chlorpyrifos
Inter.
4.75
21.19
1.39
0.91
-38.01
0.68
-7.16
-0.02
-0.89
0.00
0.39
0.75
-2.01
Sign. 1
0.37
>0.50
0.17
0.35
>0.50
-0.50
0.48
0.29
plankton in fishless habitats. Therefore, the indirect effects of fish in our experiments
consisted in the removal of invertebrate predators and large herbivores, thus securing the
proliferation of small planktonic organisms. The model also showed an increase of
protozoans which were not observed in the experiments.
As far as the experimental design including treatments where more than one factor
was present at a time, it was possible to assess the combined effect of factors and to find out
if the factors interacted with each other. Interactions were calculated as differences between
observed effects of two or three factors present in a given treatment and the sum of the
individual effects of these factors taken from other treatments. This sum was considered to
be equal to the additive effect. Therefore, if the interaction effect coincides by its sign (plus
or minus) with the observed combined effect of factors, the interaction is synergistic; if not, it
is antagonistic. As seen from Tables 2 and 3, a combination of factors in most cases caused
purely additive effects; interactions of factors were small in magnitude and statistically
insignificant. Only some interactions involving fish and observed through the effects on
rotifers and algae were large and significant, but these are indirect secondary effects, so
these interactions may not be interactions of the factors themselves but just reflections of
interactions of the ecosystem living components.
157
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To see whether an ecosystem with one vertebrate predator on the top differs in
responses to toxicants from an ecosystem without such a predator, we divided the
experimental data into two, one with fish and another without fish, and performed the same
kind of analysis separately on each half. The results are presented in Tables 4 and 5.
It can be seen from the tables that, in the presence of fish, effects of both toxicants on
crustaceans were damped down, the effect of heavy metals on rotifers increased, and the
effect of chlorpyrifos diminished. It seems that there is no regularity in this pattern, but the
following reasoning may serve as a probable explanation. If a living population is well
developed and flourishing, then negative effects on it are pronounced, the positive ones are
barely observed, and vice versa. Cladocerans are well developed without fish, so adverse
effects of the toxicants were manifested better than with fish. Copepods attained high
numbers in the presence of fish; therefore, the stimulatory effect of toxicants on their
abundance was smoother. Rotifers flourished in the presence of fish so the negative effect of
heavy metals on them was amplified, and the positive effect of chlorpyrifos was diminished.
Of course, these explanations should be taken cautiously because the fish presence imparted
great variability to experimental results and rendered many values statistically insignificant.
As for effects on algae and bacteria, at the present stage of the investigation they are hard to
interpret.
When fish are considered as another ecosystem component, the effects of toxicants
on their principal characteristics can be determined. As seen in Fig. 1, heavy metals alone
and in combination with chlorpyrifos, each induced almost 2-fold decreases in linear growth
and weight of fish. The greatest negative effect was caused by the combination of heavy
metals and the pesticide. In view of this, the significant stimulation of fish growth by 25%
compared to the control that was observed in the chlorpyrifos treatment is of great interest.
Investigations of resistance of fish to waterflow, reflecting general physiological fitness
of fish (Pavlov and Fomin 1978), showed that the underyearlings which had been exposed to
chlorpyrifos manifested the greatest resistance to flow (Fig. 2). These were, on the average,
18% more resistant than those in the control. In the heavy metals treatment, they showed
5% lower resistance, and in the treatment heavy metals + chlorpyrifos, their resistance was
reduced by 20%. After 30 days of recovery from toxicants, the length and mass of fish
exposed to combined effects of chlorpyrifos and metals was greater than in control fish. The
largest were fish from the chlorpyrifos treatment, although differences in size and weight
were, on the whole, statistically insignificant.
If we judged the whole ecosystem by fish conditions, it would seem that the
ecosystem flourished when exposed to chlorpyrifos since the top link of the trophic chain was
in a better state than in clear water. This misleading evidence shows that the whole
ecosystem testing involving many organisms belonging to different trophic levels is more
appropriate to assess toxicant effects.
CONCLUSIONS
In general, results presented here agree well with those obtained by the
Environmental Research Laboratory, especially concerning major effects of toxicants on the
158
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66-
80-
56
so •
46 •
40 •
35 •
33 •
s-
20
Ch HM Ch+HM C
65
80-
JB
SO
45 •
40 •
S •
30 •
25 •
20 •
Ch HM Ch+HM C
MO
220
200
180
160
140
120
103
BO
240
220
200
180
180
140
120
103
60
Ch HM Ch-t-HM C
Ch HM Ch+HM C
Fig. 1. Growth in mass and length of bream underyearlingSs Experimental treatments: Ch =
chlorpyrifos, HM = heavy metals, Ch + HM = chlorpyrifos + heavy metals, C = control; a)
increases in length after 30 days of exposure, b) increases in length after 30 days of recovery, c)
increases in mass after 30 days of exposure, and d) increases in mass after 30 days of recovery.
a b
9r
Ch
HM Ch+HM
Ch HM Ch+HM C
Fig. 2. Resistance of the fish to flow. Index of resistance of fish to flow expressed as V/L, where
V is velocity of the flow (cm/sec) and L is length of the fish in sm; a) resistance of bream to flow
after 30 days of exposure and b) resistance of bream to flow after 30 days of recovery.
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zooplankton community (U.S. EPA 1986). Earlier, similar effects were shown in the studies
of Moscow University using static mesocosms (Filenko 1984). Results demonstrate the
flow-through mesocosm protocol's utility to test biological effects of different kinds of toxicants
used separately or in combination. In some aspects, the continuous system is better than
stationary systems, as it allows easier simulations of natural conditions, whereby pollutants
are usually being continuously added to a waterbody. A good fit of the predicted and
observed effects of anthropogenous factors shows that mathematical modeling can be
successfully applied to such systems.
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invertebrates. Environ. Entomol. 11:1251-1257.
Andrushkaitis, A. G., A. Kh. Avens, and Z. K. Seusuma. 1989. The methods of
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Baudouin, M. F. and P. Scoppa. 1974. Acute toxicity of heavy metals to freshwater
zooplankton. Bull. Environ. Contam. Toxicol. 12:745-751.
Buhr, H. O. and S. B. Miller. 1983. A dynamic model of the high-rate algal-bacterial
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(In Russian.)
Hurlbert, S. H., M. S. Mulla and H. R. Willson. 1972. Effects of organophosphorus
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interactions. Ecol. Monogr. 61:245-265.
Stratton, G. W., A. L. Huber and C. T. Corke. 1980. The effect of pesticides and their
metabolites, alone and in combination, on algal processes. Can. Tech. Rep., Fish.
Aquat. Sci. 975:131-139.
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invertebrate predators and large herbivores to a small species community. Can. J.
Fish. Aquat. Sci. 45:1758-1770.
Vinogradov, G. A. and V. B. Tagunov. 1989. An installation to study the effects of various
substances on fish and invertebrates under continuous flow conditions. Hydrobiol. J.
25. (In Russian.)
Wylie, J. L. and D. J. Currie. 1991. The relative importance of bacteria and algae as food
sources for crustacean zooplankton. Limnol. Oceanogr. 36:708-728.
Zaika, V. E. 1972. Specific production of invertebrates. Kiev, Naukova dumka. (In
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Russian.)
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BIOCHEMICAL AND PHYSIOLOGICAL INDICATORS OF CONTAMINANT
STRESS IN AQUATIC ORGANISMS OF LARGE RIVER SYSTEMS
by
Denny R. Buckler1 and Donald E. Tillrtt1
ABSTRACT
Examination of the biochemical and physiological responses of organisms to xenobiotic
chemicals has been an area of scientific investigation for many years. Historically, these
techniques have been used in the development and screening of natural and synthetic
Pharmaceuticals, biocides, and other biologically active chemicals and in elucidating their modes
of action. However, only recently have these techniques been applied as indicators of the nature
and extent of chemical pollution of aquatic ecosystems. Today, research on the effects of
chemical contaminants at the molecular level of biological organization is one of the most rapidly
developing and intensively studied areas in the field of environmental toxicology. In this paper,
we discuss the relationship of biochemical and physiologic responses to effects at higher levels
of biological organization, examine general categories and provide specific examples of
techniques that are presently being applied to aquatic systems, and provide recommendations
for implementation of biochemical and physiological techniques in aquatic contaminant
assessment programs.
INTRODUCTION
Water, soil, and sediments serve as the ultimate sinks for most chemicals produced and
used by man. General sources of anthropogenic chemical contaminants are from industrial,
agricultural, and urban uses. These uses result in both point and nonpoint source pollution of our
environment. Large rivers are of particular concern because they receive and integrate
pollutants from man's activities and land use practices over large geographical regions. Large
rivers are the direct recipients of municipal and industrial effluents and additionally receive
contaminant loadings from tributaries and agricultural practices in their watersheds.
These multiple sources of contaminant input result in complex mixtures of contaminants
being present in the water and sediments of large river systems. Unfortunately, most of our
knowledge and understanding of the effects of chemical contaminants in aquatic organisms is
based upon the effects of single compounds tested in the laboratory. Much less is known about
the effects of complex environmental mixtures. Field studies can document the correlation of
population-level effects with contaminant exposure, but the complexity of environmental variables
and multiple contaminant exposure makes it difficult to establish cause and effect relationships
with specific chemical pollutants. Environmental scientists are presently focusing more effort on
'National Fisheries Contaminant Research Center, U.S. Fish and Wildlife Service, Columbia, MO
65201-9643, USA
162
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expanding our understanding of the effects of pollutants at the molecular level to help
discriminate among the various environmental stressors affecting aquatic populations and
communities.
Management practices for aquatic resources and regulatory practices regarding
contaminant discharge are primarily directed at the population level. However, biochemical and
physiological measures of contaminant stress have received increased attention in recent years
due to their rapid response, sensitivity, and potential to provide a further level of discrimination in
the environmental risk assessment process. In this paper, we discuss the relationship between
contaminant effects at the biochemical level and those at higher levels of biological organization,
examine general categories and specific examples of techniques that can be applied to aquatic
systems, and provide recommendations for integration of biochemical and physiological
measures of contaminant stress with other environmental risk assessment procedures.
RELATIONSHIP OF BIOCHEMICAL AND PHYSIOLOGICAL STRESS
TO EFFECTS AT HIGHER LEVELS OF BIOLOGICAL ORGANIZATION
A basic premise in the field of toxicology is that to elicit a toxic response, a chemical must
first reach and interact with its biomolecular site of action. This response on a molecular level
may then be followed by a tissue response, an organ response, a whole animal response, and
finally a population or community response, but it must occur first at the biomolecular level.
Each level possesses an inherent resiliency, or assimilative capacity, that allows it to
maintain homeostasis. To provide a continuum of response, the magnitude of effect at each
level of organization must be great enough to exceed the assimilative capacity of the next higher
level. Ultimately, for a contaminant to elicit a response at the population or community level, it
must exceed the capacity of all lower levels to absorb or mitigate the insult.
These relationships and interdependencies provide both promise and challenge to the
use of biochemical and physiological responses as indicators of aquatic community health. First,
it is apparent that biochemical changes must be the first and most sensitive biological responses
that occur following contaminant exposure. Thus, bioindicators may be useful as early warning
indicators of contaminant problems. Alternatively, because the continuum may be broken at
subsequent levels of biological organization, effects at the biochemical level may not be
ecologically significant. Thus, the challenge facing the environmental scientist is to develop an
understanding of the magnitude of effect at the biochemical level that is required to elicit an
ecologically significant response at higher levels of organization.
Toxicants interact with organisms on the molecular level in a variety of ways that can
challenge the maintenance of homeostasis. Metals can bind to various proteins disrupting
membrane integrity, ion transport, and cellular metabolism. For example, mercury can bind to
sulfhydryl groups on structural proteins (Luckey and Venugopal 1977), thereby disrupting
membrane integrity. Copper can interfere with ion transport by affecting gill ATPase activity,
reducing the ability of coho salmon (Oncorhynchus kisutch) to adapt to seawater (Lorz and
McPherson 1976). Lead can deactivate 6-aminolevulinic acid dehydratase (ALAD), disrupting
red blood cell metabolism.
Organic contaminants also interact with organisms on the molecular level by disrupting
membrane integrity and function, displacing endogenous substrates of enzymes, or by
diminishing energy reserves through increased demands upon detoxification mechanisms. For
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example, pentachlorophenol uncouples oxidative phosphorylation by interacting with the
mitochondrial membrane (Moreland 1980). Organophosphates and carbamates can displace
acetylene-line and inhibit its hydrolytic cleavage by acetylcholinesterase (ACHe), thereby affecting
nerve transmission (O'Brien 1976). Widdows and Donkin (1991) report a variety of ways that
toxicants can diminish the energy reserves of an organism to the detriment of survival.
To cause effects at higher levels of biological organization, the effects at the molecular
level mentioned above must be of sufficient severity to challenge the organism's ability to
maintain homeostasis. Organisms invite a variety of mechanisms for dealing with toxicants. In
some cases, they may be able to detect and avoid the toxicant (Folmar 1976). They may
sequester the toxicant (e.g., through induction of metal-binding proteins, such as
metallothioneins), or they may metabolically alter the compound to a less toxic form that may be
more readily eliminated (e.g., oxidative metabolism of pyrethroid insecticides). Alternatively, they
may simply repair the cellular damage caused by the toxicant. Each of these mechanisms incurs
some physiologic cost on the part of the individual organism (Calow 1991). When the organism's
ability to absorb or mitigate the toxic insult is exceeded, stress will be applied to the higher levels
of organization such as the population or community.
At present, a wide range of biochemical and physiological parameters are known to be
responsive to chemical exposure. However, our understanding of how these responses are
quantitatively linked to effects at the aquatic population and community levels is much more
limited. Relatively few of the measurable biochemical and physiological responses are specific to
certain chemical classes (e.g., ACHe inhibition by Organophosphates and carbamates; ALAD
inhibition by lead). The majority of responses are sensitive to a wide variety of chemical
compounds and other environmental stressors. Thus, with a few exceptions, the majority of
biochemical and physiological measures are more useful as general indicators of organism
health rather than specific indicators of specific chemical exposure. It is important to recognize
the range of sensitivity of the indicators we use in aquatic contaminant risk assessment, because
our goal is to establish cause and effect between contaminant exposure and responses at the
population and community level. Responses that are general indicators of organism health must
be used in concert with other measures of chemical exposure, such as chemical residue
analysis. Responses that are more specific indicators of individual chemical exposure must be
calibrated to quantify the continuum of response from the biochemical to the population and
community level.
Within the broad range of measurable biochemical and physiological parameters, a
further distinction can be made between regulated parameters and regulatory mechanisms.
Regulated parameters are usually maintained within relatively narrow ranges to maintain
physiological function. Contaminant exposure that displaces these parameters beyond the
tolerated range will usually result in acute injury or death (Zachariassen et al. 1991). However,
the regulatory mechanisms that govern these parameters may fluctuate much more widely before
significant injury or death occurs in an attempt to maintain the optimal range, and may be more
responsive and sensitive indicators of contaminant insult (Zachariassen et al. 1991). For
example, the level of ATP present in an organism is a highly regulated parameter. ATP levels
can be maintained at the expense of other endogenous high-energy phosphate compounds.
Aunaas et al. (1991) demonstrated that sublethal exposure of the blue mussel (Mytilus edulis) to
contaminants generally resulted in larger fluctuations of components of the phosphate pool other
than ATP. Thus, the regulatory mechanism (the phosphate pool) was more responsive than the
regulated parameter (ATP).
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The range of sensitivity, level of variability, and relationship to responses at higher levels
of biological organization are all important parameters for consideration in selecting biochemical
and physiological indicators for application in aquatic contaminant risk assessment programs.
CATEGORIES AND EXAMPLES OF TECHNIQUES
Biochemical and physiological indicators of contaminant stress can be categorized in a
variety of ways-general versus specific sensitivity to compounds, regulatory versus regulated
parameters, indicators of exposure versus indicators of effect, or by category of biochemical and
physiological function. In this section, we will identify general categories of biochemical and
physiological function and discuss representative examples of indicator techniques for each
category that are presently being used or show promise for further development.
OSMOREGULATION
A variety of inorganic and organic environmental pollutants affect osmoregulation in
fishes. For this reason, many osmoregulatory stress indicators are more useful as indicators of
general organism health rather than diagnostic tools for identification of specific pollutants.
Plasma ion concentrations are responsive to heavy rnetal exposure. Sublethal exposure
to copper causes transient decreases in plasma chloride concentrations in brown bullheads
(Ictalurus nebulosus) and brook trout (Satvelinus fontinalis)', however, the levels return to normal
after about 3 weeks even during continuous exposure, indicating the presence of a
compensatory mechanism for maintenance of homeostasis (Christensen et al. 1972, McKim et
al, 1970). Zinc and cadmium also affect plasma ion concentrations (Lewis and Lewis 1971,
McCarty and Houston 1976).
Gill ATPase activity in fishes is also sensitive to chemical exposure. This measure of
osmoregulatory ability is affected by a wide range of environmental pollutants including copper
(Lorz and McPherson 1976), PCBs (Davis et al. 1972), and a variety of chlorinated pesticides
(Davis et al. 1972). Gill ATPase activity has direct ecological relevance in that it is intimately
linked to the migratory success of anadromous fish species (Epstein et al. 1967, Zaugg and
Wagner 1973).
Histological and histochemical examination of gill tissue has also been used successfully
to demonstrate the effects of osmoregulatory stressors. As with ATPase activity, a wide variety
of environmental contaminants can cause histological lesions in fish gill. Aluminum (Jagoe et al.
1987), copper (Baker 1969), mercury (Wobeser 1975), sodium arsenite (Gilderhaus 1966), and
zinc (Skidmore and Tovell 1972) are some of the metals that cause gill lesions in fishes. A wide
variety of organic compounds also cause histological lesions in fish gill. Endrin (Eller 1971),
heptachlor (Andrews et al. 1966), methoxychlor (Lakota et al 1978), mirex (Van Valin et al. 1968),
naphthalene (DiMichele and Taylor 1978), and phenol (Mitrovic et al. 1968) are only a few of the
organic contaminants that cause gill lesions.
METAL SEQUESTRATION AND REGULATION
Metallothioneins are a class of metal-binding proteins found in a wide variety of
organisms (Roesijadi 1992) that are inducible after exposure to Cd, Cu, Hg, and Zn (Noel-Lambot
et al. 1978). Metallothioneins are thought to reduce the toxicity of heavy metal exposure by
sequestration (Hamilton and Mehrle 1986), with toxicity occurring only after its binding capacity is
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exceeded (Brown and parsons 1978). Hepatic metallothionein levels in feral fishes from lakes
contaminated with Cu, Zn and Cd are closely correlated to metals exposure (Roch et al. 1982).
The inducible nature of metallothioneins suggests that they represent a regulatory mechanism,
and as such provide a useful indicator of exposure to certain metals. Other metal-binding
proteins such as ferritin (Fe) and copper-chelatin (Cu) have been less thoroughly studied in
aquatic organisms.
OXIDATIVE METABOLISM
Oxidative metabolism serves three important functions in eukaryotic organisms that
provide useful biochemical indicators of stress. First, oxidative metabolism plays a central role in
catabolic energy production. The resultant storage currency is adenylate, and its utility as a
biochemical indicator of contaminant stress is discussed in the next section.
Secondly, oxidative metabolism is associated with the reduction of oxygen radicals and
the maintenance of oxidative homeostasis within the cell. This critical function also lends itself
for use as a biochemical indicator of stress in aquatic organisms. Oxygen radicals are formed as
intermediates of cytosolic enzymes, electron transfer systems, and by activated cells of the
immune system. Inducible prophylactic enzymes such as superoxide dismutase, catalase, and
glutathione peroxidase serve a vital role in protecting the cell from oxidative stress and are useful
indicators of contaminant stress in aquatic organisms (DiGiulio et al. 1989). Additionally, the
pools (and relative ratios) of reducing equivalents (e.g., glutathione, a-tocopherol, and
ascorbate) that are required to maintain oxidative homeostasis are useful indicators of
contaminant stress. These antioxidant defense mechanisms of the cell are sensitive to
compounds that block or inhibit electron flow and, in particular, those that can undergo cyclic
reactions (redox cycling) to produce oxygen radicals. These important classes of environmental
contaminants include paraquat, diquat, and various amines.
The third, and probably the most thoroughly studied, function of oxidative metabolism is
xenobiotic metabolism. Xenobiotic metabolism associated with the cytochrome P450
monooxygenases (MO) has been reviewed for use in biomonitoring by Payne et al. (1987), who
concluded that induction of MO could be a sensitive biochemical indicator of exposure in many
aquatic organisms. Induction of MO activity is caused by a wide variety of chemical
contaminants (e.g., PAHs, PCBs, PCDDs, and PCDFs). The MO system plays a central role in
the detoxification of these and many other hydrophobic compounds largely by facilitating their
elimination. Additionally, MOs are highly conserved phylogenetically. All of these characteristics
enhance the potential utility of MO activity as a biochemical indicator of contaminant stress.
However, its use in feral organisms has been limited because of the confounding factors of age,
sex, reproductive status, diet, disease, and general health conditions that can all greatly affect
the MO response to xenobiotics (Neal 1980). A thorough understanding of the effects caused by
these variables is lacking in most species of fish and wildlife. Even if these relationships were
understood in aquatic species, it is often difficult to obtain such information on feral organisms.
Thus, MO activity in this context offers a more qualitative than quantitative measure of
contaminant exposure. However, successful use of MO activity as a quantitative bioindicator of
contaminant stress in the field has been accomplished using caged fish studies (Lindstrom-
Seppa and Oikari 1990) and by using developing embryos (Hoffman et al. 1987). In both of
these cases, the organismal and environmental factors affecting MO activity could be controlled
or monitored during the period of exposure.
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Another alternative to limiting the confounding factors that influence MO activity is the use
of in vitro systems where the conditions are tightly controlled. In these assays, the
environmental contaminant mixture is brought to the laboratory to expose the system, as
opposed to taking the system (organisms) to the environment for exposure. An example of such
an in vitro model system for MO activity is the H4IIE hepatoma cell bioassay (Tillitt et al. 1991).
In this bioassay, environmental contaminants are extracted from the species of concern and
serial dilutions are used to dose the H4IIE cells. After a period of incubation, ethoxyresorufin-o-
deethylase (EROD) activity is measured in the cells. The MO response of the H4IIE cells is
highly correlated to the effects observed in the whole organism (Safe 1987). Therefore, the MO
response in vitro can integrate the interactions of complex mixtures of environmental
contaminants at the cellular/biochemical level and serve as a quantitative measure of both
exposure and effect in the whole organism from which the contaminants were extracted. Recent
studies have demonstrated the ability of the H4IIE bioassay to be predictive of contaminant
responses at higher levels of biological organization, such as egg mortality rates in PCB-exposed
populations of fish-eating birds (Tillitt et al. 1992).
MAINTENANCE OF ENERGY STATUS
Adenylate energy charge is a term developed by Atkinson (1968) to describe the dynamic
equilibrium between the various components of the cellular energy system-ATP, ADP, and AMP.
It is calculated as (ATP + 0.5 X ADP)/(ATP + ADP + AMP) and its value reflects the energy
status of the organism. Adenylate energy charge is sensitive to a variety of environmental
factors such as food availability and temperature (Moal et al. 1991), season (Giesy and Dickson
1981), salinity (Ivanovici 1980), and pollutants (Verschraegen et al. 1985). Because ATP levels
are regulated within relatively narrow limits in many organisms, Aunaas et al. (1991) have
proposed the use of a phosphorus index-which reflects the status of a larger phosphorus pool--
as a more sensitive indicator of energy status. The broad spectrum of environmental stressors
to which energy status is sensitive indicates that this biochemical parameter may be most useful
as a general indicator of organism health, rather than a specific indicator of contaminant
exposure.
REPRODUCTION
Another category of biochemical and physiological function that is sensitive to
contaminant exposure is reproduction. The complexity of the reproductive process in aquatic
organisms and the confounding influence of behavior, nutritional status, seasonality, and other
variables makes it difficult to ascertain the effect of contaminants on the reproductive success of
natural populations. However, a number of biochemical reproductive parameters have been
investigated in the laboratory in terms of their sensitivity to contaminant exposure. Vitellogenin is
the major yolk protein in salmonids and many other species. It is produced in the liver and
transported to the ovaries in the blood. Blood levels of vitellogenin are elevated during ovary
maturation. Vitellogenin levels in brook trout and rainbow trout are affected by low pH exposure
(Tam et al. 1987, Parker and McKeown 1987). Reproductive endocrine function in fishes has
also been studied to a limited extent in terms of the effects of contaminants on steroid hormone
levels. Thomas (1990) demonstrated an increase in plasma hormone levels in Atlantic croaker
(Micropogonias undulatus) after exposure to lead, benzo(a)pyrene, or Arochlor 1254;
vitellogenin levels were similarly affected by cadmium and PCBs.
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NEUROTRANSMISSIOM
One of the more specific biochemical indicators of contaminant exposure is measurement
of the neurotransmitter acetylcholinesterase (ACHe). Organophosphates and carpamrates are
specific inhibitors of ACHe activity (O'Brien 1976), although other physiological factors can
influence activity levels. It should be noted that measurement of brain activity levels represents
primarily true acetylcholinesterase whereas plasma levels generally reflect both
acetylcholinesterase and butyryl(pseudo)cholinesterase (O'Brien 1976). Depressed ACHe
activity is associated with a variety of behavioral responses in fishes (Symons 1973) and it has
been measured in feral fishes from polluted waters (Williams and Sova 1966). However, brain
activity levels resulting in death of fishes can be quite variable (Weiss 1961).
INTERACTIONS WITH GENETIC MATERIAL
The genotoxic effects of contaminants are receiving increased interest in the area of
environmental contaminant assessment. A variety of techniques are becoming available for use
in aquatic systems. Detection of the presence of DNA adducts using 32p-postlabeling is one
method of assessing exposure to contaminants that are capable of interacting with genetic
material. Varanasi et al. (1989) used this method to correlate DNA adducts in livers of English
sole (Parophrys vetulus) and winter flounder (Pseudopleuronectes americanus from Pugent
Sound, with exposure to PAHs in sediments. Another method that shows promise is the use of
the DNA alkaline unwinding assay. Toxic chemicals that interact with genetic material can cause
strand breaks in DNA. The rate of unwinding of the DNA double helix when placed in an alkaline
solution is a measure of DNA integrity that has been shown to be related to exposure of fish to
genotoxic chemicals (Shugart 1988).
IMMUNOLOGY
A wide range of environmental pollutants affect the immune system of fishes (Zeeman
and Brindley 1981). Immunosuppression can result in increased susceptibility of fishes to
disease (Sinderman 1979). Contaminant-reduced immunocompetence of fishes has been a
subject of study in both feral fishes from polluted environments (Warinner et al. 1988), and
laboratory studies with single compounds (Walczak et al. 1987) and complex mixtures
(Secombes et al. 1991). Various approaches to assessment of immune status have been used.
These include differential white blood cell counts (Gardner and Yevich 1970), serum protein
levels and ratios (Smith et al. 1976), agglutination liter (Roales and Perlmutter 1977),
phagocytosis (Secombes et al. 1991), and disease susceptibility (Hansen et al. 1971). As with
many other biochemical and physiological indicators, measures of immunocompetence are more
useful as indicators of general organism health rather than a diagnostic indicator of specific
contaminant exposure.
RECOMMENDATIONS FOR IMPLEMENTATION
In this brief overview, we have had the opportunity to focus on only a minute fraction of the
biochemical and physiological response of aquatic organisms that have been measured in relation
to contaminant exposure. Of the literally hundreds of measurable biochemical and physiological
responses of organisms, most have been studied at least to some extent in relation to exposure to
one chemical or another. The wide variety of species of aquatic organisms and the wide variety of
chemicals that pose a threat as environmental pollutants provides an extremely extensive and
complex matrix of possible combinations of exposure and response for study.
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Relatively few biochemical and physiological responses of aquatic organisms are specific
to individual chemicals (e.g., ALAD); several others are sensitive to general chemical classes
(e.g., acetylcholinesterase activity; EROD activity). These specific indicators may be very useful
in environmental assessments where sources and types of contaminants are unknown, by
directing evaluation efforts toward particular chemicals. The sensitivity of these tests may also
make them useful for documenting the fringes of environmental disturbance or areas of subtle
contaminant exposure when the types of contaminants present in a system are known. Their
use, coupled with supportive analytical chemistry, can provide important information for
establishing cause and effect relationships and interpreting observed effects at higher levels of
biological organization.
The majority of biochemical and physiological responses of aquatic organisms are
sensitive to broad ranges of chemical contaminants and other environmental stressors. For this
reason, these techniques can provide sensitive measures of organism health, but are not
diagnostic for specific chemical exposure. These general indicators are most effectively applied
in environmental contaminant assessments in concert with other measures of contaminant
effects and exposure. The use of general biochemical indicators should be coupled with
chemical analysis, on-site and in-situ toxicity assays, infaunal surveys, and other classical
contaminant assessment procedures to identify the nature and extent of the contaminant
problem. As with specific indicators of contaminant exposure, these general indicators of
organism health may provide additional sensitivity in identifying the fringes of environmental
disturbance and areas of subtle contaminant exposure. However, supporting information for
establishing cause and effect is extremely important when general indicator techniques are
applied in environmental contaminant assessments.
In summary, measurement of the biochemical and physiological responses of aquatic
organisms to toxic chemicals has provided extensive insight into the modes of action of
environmental contaminants. However, their use in the identification and monitoring of the nature
and extent of aquatic pollution is a relatively new application. Their rapid response and
sensitivity provides potential for adding a further level of discrimination in the environmental risk
assessment process, particularly in marginally impacted areas. Proper application of these
techniques requires a thorough understanding of their specificity in regard to the types of
environmental stressors to which they are sensitive, and a quantitative understanding of the
linkages between effects at various levels of biological organization. For many biochemical and
physiological indicators, these are topics of current and future work.
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CLASSIFICATION OF WETLANDS OF RUSSIA
by
A. M. Nikanorov1, A. V. Zhulidov1 and W. Sanville2
ABSTRACT
The term "wetland," which is new for the Russian scientific literature, describes a
diversity of zones lying between typical terrestrial habitats and deep water ones. There is no
unified classification of wet habitats in Russia. In order to classify Russian wetlands, we
used the well-known publication, "Classification of Wetlands in the United States," because of
its ecological comprehensiveness and simplicity.
INTRODUCTION
Habitats at the water and land interface are complex structures in which we observe
the interaction of water, air, soil, bottom sediments, and living organisms. These habitats are
quite common at marine coasts, lake and river shores, relief depressions, and ground water
outlets. In Russia we use a whole set of terms designating such ecosystems. They may be
terms which are quite common, such as wet meadows, bogs, swamps, and coasts or local
specific terms such as laid, alas, plav, tugai, zaimizche, kardash, iskar, urem, grass visk,
sogr, saz, ryam, ols, vatt, badaran, etc. Sometimes, one term is understood differently in
different areas of Russia. For instance, the term "laid" is used for designation of the
meadows at marine coasts; lakes in Vasugany, Siberia; and wet depressions in the tundra.
These wet areas may be attributed both to terrestrial and aquatic ecosystems which
are diverse and specific. From the biogeochemical point of view these areas, when
compared to deep water habitats, are characterized by lower and more variable spacial pH
values, lower concentrations of dissolved oxygen, extreme reducing conditions, a higher
probability of photodegradation and biodegradation, chelation and formation of organic and
organomineral complexes, and higher sulfide concentrations. Hydrology is the controlling
factor in all of these wet areas, in spite of their diversity. All these ecosystems are
periodically flooded or saturated with water. In accordance with Polynov classification, these
habitats are attributed to "aqual" and "superaqual" elementary landscapes (biogenosis).
1Hydrochemical Institute, Federal Survey of Russia for Hydrometeorology and Environmental
Monitoring, Rostov-on-Don, Russia.
2U.S. Environmental Protection Agency, Environmental Research Laboratory, Duluth, MN.
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Wetland, which is a new term in Russian scientific literature, describes a diversity of zones
lying between typical terrestrial habitats and deep water ones.
The U.S. Fish and Wildlife Service (USFWS) developed and published the
classification of U.S. wetlands entitled "Classification of Wetlands and Deepwater Habitats of
the United States" (Cowardin et al. 1979). This classification is not the only one in use in the
U.S., but its ecological comprehensiveness and simplicity has provided an excellent
classification tool. Because of this, we believe it would have an excellent possibility for
classifying Russian wetlands.
The USFWS system standardizes wetland classification and provides the basis for a
wetland inventory. There is no unified classification of wet habitats in Russia. The first
project undertaken by American and Russian specialists was to evaluate the USFWS
classification in Russia and determine its applicability to Russian wetlands. These
investigations were carried out in the framework of Cooperative American-Russian Project
02.02.14. "Influence of Pollutants on Wetland Ecosystems" in accordance with an
Intergovernmental Agreement in the Field of Environmental Protection.
Below is a brief review of the application of the USFWS wetland classification system
used in Russia. This is preliminary and the work will be continued. Some details of USFWS
classification are omitted purposefully to underline the principles of classification.
BRIEF ANALYSIS OF THE USFWS CLASSIFICATION OF WETLANDS
Wetland is understood as a wet habitat periodically flooded or saturated with water.
The USFWS defines a wetland as transitional between terrestrial and deepwater ecosystems
with the water table at the surface or close to the ground surface. To classify an
environment as a wetland it must possess at least one of the three following features: 1) the
area should be inhabited by hydrophytes, at least periodically; 2) the surface substrate is not
continuously drained, and hydromorphic soils are formed; and 3) soils are saturated with
water or flooded during some part of the yearly growing season, i.e., the hydrological regime
may be variable-from permanent flooding or saturation to occasional water at the land
surface.
According to USFWS classification of hydrophytic plants, hydrophytes are plants
inhabiting environments characterized by recurring anaerobic conditions or close to anaerobic
conditions because of high moisture content. The substrate of wetlands may not necessarily
be a hydromorphic soil, e.g., sand and gravel beaches, but at least for some period during
the vegetation growing season the substrate must be saturated or flooded.
Because of the absence of a distinct interface between dry and wet habitats, there
may not be indisputable determinations of wetland boundaries. We have to use the term
wetland even though it is somewhat artificial from a scientific point of view. In Russian
scientific literature, much less definite terms are used to describe these areas, i.e., wet boggy
areas, which cannot be taken as synonymous with the term wetland.
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Only definite biogenoses may be attributed to wetlands. This is illustrated by Table 1.
However, the basic features of wetlands differ in different climatic zones of Russia. In all
climatic zones there are plants and animals that cannot survive saturated or flooded soils.
Wetland spatial boundaries also differ. If marine, delta, riverine, and lacustrine
wetlands along moisture gradients (from deepwater to terrestrial habitats) are considered,
wetland boundaries will be determined by minimum and maximum water levels during the
vegetation growing season. One of the conventional boundaries of riverine and lacustrine
wetlands is the distribution of emergent vascular plants (for lacustrine wetlands this is the
2 m depth zone). Beyond this is the deepwater habitat typical of aquatic ecosystems. The
boundaries between terrestrial ecosystems and wetlands are the areas in which hydrophytes
are replaced by mesophytes and xerophytes. There are also signs of variation in
hydrological regime indicating occasional flooding or soil saturation.
Table 2 presents USFWS classification with the hierarchical structure of wetlands at
three groups: systems, subsystems, and classes. Experience with the USFWS classification
system in Russia (Caucasus, southern part of the country; Rostov region, forest steppe zone
of Voronezh; Kursk regions, taiga of the European part of the country; and basins of the
Olekma and Amga rivers in Yakutia, Siberia) indicated that at the levels of systems,
subsystems, and classes, the system can be applied for classification of Russian wetlands.
No wetlands endemic to Russia could not be classified at the level of class or higher. Some
Russian wetlands did not appear to meet the classification criteria at the level of subclass, so
it may be necessary to develop specific subclasses for Russian wetlands.
TABLE 1. BASIC FEATURES OF WETLANDS"
Lacustrine
Palustrine
With hydrophytes
Phragmites
Scirpus, Carex,
Salix and others
Carex, Salix,
Phragmites,
Scirpus and
others
Peat bogs
Without hydrophytes
Wetland
system
Marine
Delta
Riverine
With hydric
soils
Rocky shore
Aquatic bed
Without
hydric soils
Plavni
Phragmites,
With hydric
soils
Sand beaches
Temporal
Without
hydric soils
Salt marsh
streams
Man-made
pool banks
'Absence of wetland terms in some columns does not mean there are no wetlands with such
features.
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TABLE 2. CLASSIFICATION OF RUSSIAN WETLANDS AT LARGE TAXONOMIC GROUP LEVELS
Systems
Marine
Delta
Subsystems
Subtidal
Tidal
Subtidal
Tidal
Classes
Rock bottom; unconsolidated bottom; aquatic bed
Aquatic bed; rocky shore; unconsolidated shore
Rock bottom; unconsolidated bottom; aquatic bed
Aquatic bed; stream bed; unconsolidated shore;
emergent wetland; shrub wetland; forested wetland
Riverine Tidal
Lower perennial
Upper perennial
Intermittent
Lacustrine Limnetic
Littoral
Palustrine
Rocky bottom; unconsolidated bottom; aquatic bed;
rocky shore; unconsolidated shore; emergent
wetland
Rock bottom; unconsolidated bottom; aquatic bed;
rocky shore; emergent wetland
Rock bottom; unconsolidated bottom; rocky shore;
unconsolidated shore
Stream bed
Rock bottom; unconsolidated bottom; aquatic bed
Rock bottom; unconsolidated bottom; aquatic bed;
rocky shore; unconsolidated shore; emergent
wetland
Rock bottom; unconsolidated bottom; aquatic bed;
unconsolidated shore; moss-lichen wetland;
emergent wetland; shrub wetland; forested wetland
The structure of the higher levels of the USFWS classification system, presented in
Table 2, are unified and may be used for description of different wetlands. This could not be
achieved using common geographic and geochemical systems for classification of
landscapes.
Table 2 also shows that the highest taxonomic level in the USFWS classification
scheme is system. This is determined as a complex of wetlands exposed to the influence of
similar hydrological, geomorphological, and biogeochemical factors. According to the
USFWS classification there are five wetland types at the system level: marine, delta, riverine,
lacustrine, and palustrine. These systems, with the exception of palustrine, are subdivided
into subsystems based on hydrological and geomorphological factors. As a result, marine
and delta systems possess two similar subsystems: 1) located below the level of the tidal
zone and those flooded permanently and 2) located above the level of the tidal zone and
occasionally flooded and exposed.
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The riverine system is subdivided into four subsystems. These are enumerated from
the mouth to the head of the river: 1) tidal, exposed to the influence of tides and wind
induced tides; 2) lower perennial with features typical of plains rivers; 3) upper perennial with
features typical of mountain rivers; and 4) intermittent, flooded occasionally during a year.
The Lacustrine system also comprises two subsystems: 1) limnetic and 2) littoral
subsystem.
Subsystems of wetlands are divided into classes based on life forms and plant cover.
While identifying classes of wetlands, two additional factors should be taken into
consideration: 1) structure of the substrate cover if there are no soils and 2) water chemical
composition. These factors will largely determine vegetative composition. In case plant
cover is less than 30% of the wetland area, this wetland may be included in one of the
following five classes: 1) rock bottom, 2) rocky shore, 3) unconsolidated bottom, 4)
unconsolidated shore, and 5) stream bed.
Where plant cover occupies greater than 30% of the wetland area, the wetland may
be included in the following five classes: 1) aquatic bed, 2) moss-lichen, 3) emergent
vascular plants, 4) shrub, and 5) forested.
These classes are subdivided into subclasses (Table 3) identified by detailed analysis
of the life forms of plants and a sublayer of the soil. The following subclasses were isolated
in Russia, based primarily on the plant character and life forms of dominant plants: 1)
persistent, 2) nonpersistent, 3) emergent, 4) moss, 5) lichen, 6) broad-leaved deciduous, 7)
broad-leaved evergreen, 8) needle-leaved evergreen, 9) deciduous, and 10) dead.
On the basis of the substrate sublayer, classes are divided into the following
subclasses: 1) bedrock, 2) rubble, 3) cobble-gravel, 4) mud, 5) sand, and 6) organic matter
(detritus).
Subclasses are further subdivided into dominance types, determined by dominant
plant and animal species. The dominance types describe individual features of each wetland
and the number of dominant types is indefinite.
Four types of modifiers are used to more accurately identify characteristics of
wetlands: 1) water regime, 2) water chemical composition, 3) soil, and 4) special.
Water regime modifiers describe flood conditions or the degree of wetland saturation.
In this case they are divided into two basic groups: 1) subtidal, intermittently exposed,
permanently flooded, and intermittently flooded; and 2) permanently flooded, intermittently
exposed, semipermanently flooded, seasonally flooded, and artificially flooded.
Some delta and riverine wetlands are exposed to the influence of tidal and nontidal
hydrologic regimes. It is difficult to determine flooding patterns and saturation levels for such
wetlands.
Water chemical composition modifiers consist of two parameters: mineralization and
pH. These are divided into two groups: 1) marine and delta wetlands exposed to tidal and
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wind induced influence and 2) riverine, lacustrine, and palustrine wetlands not exposed to
tidal and wind induced influence.
Soil modifiers are developed for two groups of soils: those rich in organic matter
(more than 20% in a 40 cm layer) and mineral soils.
The following specific modifiers describe anthropogenic and zoogenic impact on
wetlands: excavated, impounded, ditched, partially drained, farmed, and artificial.
TABLE 3. CLASSES AND CORRESPONDING SUBCLASSES OF RUSSIAN WETLANDS.
Number
Classes
Subclasses
1 Rock bottom
2 Unconsolidated bottom
3 Aquatic bed
4 Streambed
5 Rocky shore
6 Unconsolidated shore
7 Moss-lichen
8 Emergent vascular plants
9 Shrub
10 Forested
Bedrock, rubble
Cobble-gravel, mud, sand, organic matter
Algal, aquatic moss, rooted vascular,
floating vascular
Bedrock, rubble, cobble-gravel, sand, mud,
organic matter
Bedrock, rubble
Cobble-gravel, moss-lichen
Moss, lichen, moss-lichen
Persistent, nonpersistent
Broad-leaved deciduous, broad-leaved
evergreen, needle-leaved evergreen, dead
Broad-leaved deciduous, broad-leaved
evergreen, dead
WETLANDS OF THE AMGA RIVER BASIN, YAKUTIA
APPLICATION OF THE USFWS CLASSIFICATION SYSTEM
To compare characteristics of wetland habitats using the USFWS wetland
classification scheme and the physico-geographic description common in Russia, we chose
the Amga River Valley. This river flows through the Olekma Preserve, Yakutia.
In July 1991 a 30-day field survey was carried out by the Laboratory of Ecological
Investigations to study the wetlands of this area.
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Within the Olekma Preserve, the Amga River has two distinct sections. The first
extends from the headwaters to the inflow of the river Olobochor. In this section the Amga
River consists of many branches. There is also a chain of islands along the river. Along the
shore are sand-rubble ridges, and the bed consists of a shallow pebble bottom. The second
section extends from the point of the Olobochor River inflow to the boundary of Olekma
Preserve. During this transit, the Amga River Valley becomes wider and the river meanders
extensively. Many of the meanders are eventually cut off from the river and form bogs within
the floodplain. The area located in front of the wide floodplain terrace contains many bogs.
Ecological conditions of the Amga River section correspond to the criteria of the upper
perennial subsystem of the USFWS classification. In the lower section, there are some
features of the low perennial subsystem: flow current velocity in the pools decrease and the
proportion of fine fractions in sediment sublayer increases. In small bays, with the local
name "kuria," the sediment sublayer is mud with organic matter. Some river tributaries
flooded in the period of peak flow may be classified intermittent.
Elements of the Amga River such as stream bottom, banks, and pools may be
classified as riverine wetlands of the upper perennial subsystem: class = unconsolidated
bottom; subclass = cobble-gravel (sometimes subclass = sand or mud); water regime is
permanently flooded, fresh water.
Elements of the Amga River floodplain composition such as bichevnik (local Russian
term), that is pebble beach, levees, spits, beaches, summits, and tails of the islands can be
attributed to riverine wetlands of the upper perennial subsystem: class = unconsolidated
shore; subclass = cobble-gravel (sometimes, subclass = sand or mud); water regime is
seasonally flooded, temporarily flooded, and intermittently flooded, freshwater.
The section of the Hatyn River at the point of inflow to the Amga River possesses
features of the lower perennial subsystem. The wetlands at the mouth of the Hatyn River are
class = unconsolidated bottom; subclass = mud.
Palustrine wetlands were found at the floodplain of the Olobochor River. They were
classified as wetlands of class = shrubs; subclass = broad-leaved deciduous; dominant genus
= willows (Salix); water regime is semipermanently flooded, fresh waters. Upstream of the
Olobochor River class = moss-lichen wetlands; subclass = mosses, possessing saturated
water regime.
In the vicinity of the point Hatyn, there is a hillocky bog that was classified as class =
emergent; subclass = persistent. In all cases the wetland water was fresh.
Wet habitats were not limited to the riverbed or floodplain of the Amga River. In the
historical records of Olekma Preserve, other wet areas are mentioned: stream mouths and
willow thickets in the valleys, intermittently exposed beds of the streams, needle-leaved
deciduous and broad-leaved deciduous forests located at sedge sphagnum palustrine
wetlands, shrub wetlands, spring wetlands, etc. This list does not include all wet habitats of
the area.
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Thus, the USFWS Classification tested at the Amga River, Yakutia, allowed us to
place the wet habitats in a hierarchical structure and to describe them with unified terms.
Though the definition of wetlands is sometimes rather long, USFWS classification is still
convenient and may be easily used in Russia if you understand the principles of its structure.
This classification does not need any transformation above the level of subclass. It may,
however, be necessary to include additional subclasses describing wetlands endemic for
Russia (Euro-Asia).
REFERENCES
Cowardin, L. M., V. Carter, F. C. Golet and E. T. LaRoe. 1979. Classification of wetland and
deepwater habitats of the United States. FWS OBS-79/31, Washington, DC.
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ECOLOGICAL STATE OF THE UPPER VOLGA RIVER AS INFLUENCED BY
COMPLEX ANTHROPOGENIC FACTORS
by
N. P. Smimov and A. I. Kopylov1
ABSTRACT
Ever increasing degradation of wetland and aquatic habitat has caused great urgency
to maintain biological diversity and protect the gene pools of plant and animal populations
native to the Volga River. Observations point to a sharp decrease in biological diversity and
loss of species-for instance, many species of aquatic and littoral plants are on the verge of
extinction. There is need to identify the degree of anthropogenic disruption of
structural-functional components of the ecosystem, its ability to restore itself to the original
condition, and potential methods for remediation.
INTRODUCTION
The Volga River-3530 km long-is the largest river in Europe and the sixth largest in
the world. In general, the Volga is divided into three parts: Upper, Middle, and Lower. The
dam of Rybinskoye Reservoir, near the town of Rybinsk, is considered the boundary between
the Upper and Middle Volga. The Volzhskaya Hydro-electro Power Station and dam
separates the Middle from the Lower part of the Volga River.
The Upper Volga, about 800 km long, includes the Verhnevolzhskoye, Ivankovskoye,
Uglichskoye, and Rybinskoye reservoirs. All the reservoirs, except the Verhnevolzhskoye,
are about 50 years old and differ significantly in morphometric characteristics (Table 1).
Today, flora and fauna of the Upper Volga are relatively well studied, due mainly to
investigations of the Institute of Biology of Inland Waters (IBIW), Russian Academy of
Science (Table 2). There are 1018 species and varieties of algae and 342 species of higher
aquatic plants. The total number of invertebrate and fish species found in reservoirs of the
Upper Volga is 2288, including 62 species that are considered rare. Insects, nematodes, and
Institute for the Biology of Inland Waters, Russian Academy of Science, Borok, Nekouz,
Yaroslaval, Russia.
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TABLE 1. PRIMARY MORPHOMETRIC CHARACTERISTICS OF RESERVOIRS ON THE UPPER
VOLGA RIVER
Depth
Reservoir
Upper Volga
Ivankovo
Uglich
Rybinsk
Volume
(km3)
794
1,120
1,245
25,420
Area
(km3)
179
327
249
4,550
Length
(km)
92
120
143
250
Mean
(m)
4.4
3.4
5.0
5.6
Maximum
(m)
16.1
19.0
23.2
30.4
Dates of creation
and reconstruction
1843 (1943-47)
1937
1940
1941-47
TABLE 2. FLORA AND FAUNA OF THE UPPER VOLGA RIVER
General groupings
Algae
Vascular plants
Protozoa
Spongia
Coelenterata
Platyhelminthes
Nemathelminthes
Acanthocephala
Annelida
Mollusca
Tentaculata
Arthropods
Chordata
Species numbers
1018
342
139
2
1
240
610
7
79
64
9
720
32
rotifers are the most rich in species. In total, there are more than 3000 species of
autotrophic and heterotrophic eukaryotic organisms in the Upper Volga basin.
Regular observations of floral and faunal species composition over many years can be
a sensitive indicator, or monitoring tool, to evaluate the state of the ecosystem. Available
data suggest a sharp decrease in biological diversity and an irreparable loss of species and
even biocoenosis in the region. Also, the role of invading species from northern waterbodies
seems to be decreasing. Siltation of flooded channels resulted in the disappearance of
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mysids and gammarids from some areas. Changes in hydrophilic flora have been observed,
and many species of aquatic and littoral plants are on the verge of extinction.
At the same time, unusual species or those previously exotic to the region are
appearing in the reservoirs, or entire drainage of the Upper Volga. For example, the Caspian
polychaeta (Hypania invalida), common in southern reservoirs, was found in Ivankovskoye
Reservoir in 1986. The ostracod (Stenocirpis malcolmsoni)~a typical inhabitant of European
botanical gardens and heated basins-has also been discovered in the same reservoir. It is
interesting that uncommon parasites are appearing in the area. Mass infections of cyprinid
fry (roach, Rutilus rutilus; and white bream, Blicca bjoerkna) by the ectoparasite infusorium
(Ambiphrya ameiruri) has been noted in the Rybinskoye Reservoir. This infusorium was
brought to Europe in the 1980s along with its host-trie American catfish (Ictalurus
punctatus)~and passed on to other native species in fish farms of the country. Invasion of
the ectoparasites into the Upper Volga is apparently linked to conditions favorable for
reproduction of the infusorium (high concentrations of dissolved organic matter and abundant
plankton microflora), which occur in some areas. These are the primary foods for this
infusorium. The ectoparasites are distributed evenly on the skin epithelium and sometimes
cover 60% of the surface.
Significant changes in the species composition of plankton and benthic communities
are primarily the result of eutrophication and pollution from anthropogenic sources in the
Upper Volga basin. Anthropogenic loads on waterbodies have greatly increased within the
last decade. Primary anthropogenic sources include industrial and municipal wastes released
into waterbodies, air pollution, more intensive use of the Volga basin for transportation and
recreation purposes, industrial construction along the banks of the river and it's basin,
dredging for construction purposes, and intensive use of biological resources.
This manuscript presents just a small part of the information on the effects of
anthropogenic eutrophication and anthropogenic pollution of the Upper Volga reservoirs
gained by scientists of the IBIW.
EUTROPHICATION OF THE UPPER VOLGA RIVER
Reservoirs are unique aquatic ecosystems where biological succession is a
complicated and infinitely long process. The succession, or aging, of reservoir ecosystems
differs markedly from that of lakes. Anthropogenic factors affect reservoirs from the moment
of their completion and play a lead role in reservoir ecosystem dynamics.
Trophic level changes in different stages of reservoir succession are caused by a
variety of factors and are not always associated with anthropogenic enrichment by biogenes.
Therefore, eutrophication of reservoirs is not always caused by anthropogenic factors. Thus,
it is more correct to consider changes in the structural and functional characteristics of
aquatic communities to be the result of a combination of natural and anthropomorphic
eutrophication. Ivankovskoye Reservoir is a good example to illustrate this combined
eutrophication process. In addition to diatoms, pyrrophytic and blue-green algae begin to
dominate in phytoplankton communities, and can be used as indicators of eutrophic
conditions. Before 1970, the blue-green algae biomass had not exceeded 7 g/m3, but within
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the last decade it has reached hundreds of grams per cubic meter. Intensive increases in
these algal species groups have become characteristic of all reservoirs in the region. In
comparison to the 1950s, total biomass of plankton has increased by 2.0-6.6 times. Data on
phytoplankton primary production from the 1980s shows that production in the photosynthetic
zone has increased by 1.2-6.5 times during the same period.
Along with phytoplankton, total numbers and biomass of zooplankton increased
significantly over the last few years. The number of species that are indicative of
eutrophication has increased sharply as has filter feeding zooplankton. Also, ratios between
taxonomic groups have changed.
The present state of eutrophication in Ivankovskoye Reservoir is characterized by
increases in annual macrophyte production, and percent area of coverage by emergent
plants. Simultaneously, the process of endogenous succession is resulting in increased
dominance of plants typical of bogs. The appearance of herbaceous floating mats followed
by replacement with brushy and woody plants is common for this type of endogenous
succession. The following scheme illustrates the change in plant communities in general:
1) emergent plants; 2) emergent plants and floating mats; 3) floating mats and islands; and,
finally, 4) floating islands with individual willow shrubs and trees, and birch and fir forest. At
the willow development stage, shallow waters are converted into boggy soil, over a period of
30-40 years. The Ivankovskoye Reservoir has been in existence for 40 years, and due to
endogenic succession, floating mats now cover 14% (13 km2) of littoral area, and 3%
(11 km3) of the total area of the reservoir has been turned into boggy soil (Table 3).
TABLE 3. HIGHER AQUATIC PLANTS OF IVANKOVSKOYE RESERVOIR
Observation 1957 1973 1980
Area of vegetation (km2) 55 79 83
Degree of overgrowth (%) 17 24 28
Annual production of organic
matter (higher water plants,
thousands of tons) 25 54 68
POLLUTION OF THE UPPER VOLGA RESERVOIRS
Effects of discharge of large amounts of industrial and municipal wastewater have
been studied in the northern part of the Sheksna Reach of the Rybinskoye Reservoir (near
the town of Cherepovets). Major pollutants include oil products, polychlorinated biphenyls
(PCBs), di- and polyaromatic hydrocarbons (PAHs), heavy metals, and others. According to
1990 data, taken from some locations, the concentration of oil exceeded the maximum
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permissible concentration by four times, and the concentration of PAHs by 150 times (Table
4).
The pollution of bottom sediments by PAHs presents a serious hazard. The
concentrations, extrapolated from benzopyrene, for the majority of samples were 25-53 mg/g
of dry weight, which exceeds by 3-4 orders of magnitude the background concentration in
unpolluted areas. Bottom sediments and fish also contained a number of genotoxic
substances which are known to cause mutagenic effects. The portions of Skeksna Reach
receiving these wastes should be considered toxic to aquatic resources. During summer, the
length of this pollution zone is about 7 km. As oxidation/reduction transformations of the
various pollutants occur at this time, the toxic environment expands into a zone of intensified
eutrophication that extends for 20-25 km downstream.
Ecological impacts of pollutants can be observed at the organism, population, and
community levels. The disturbance of some physiological functions, changes in behavior,
reduced growth rates, and increased morbidity and mortality are caused by direct poisoning
and decreased tolerance to different stresses. Aquatic organisms in toxic zones accumulate
these pollutants (Table 5). According to 1990 data, the concentrations of persistent and
accumulable PCBs were higher in invertebrates than in bottom sediments. Fish containing
PCB residues were found in areas of the reservoir considerable distances away from the
zone directly polluted by this substance. In addition, we have observed a number of
moribund mollusks (Unio sp.) with different stages of liver degeneration and glandular cancer.
Fish captured in the polluted sections of Skeksna Reach were found to have a
60-90% incidence of immune system deficiency, whereas fish taken from habitats remote
from Cherepovets had an incidence of 0-30%. The livers and tissues associated with the
immune system of immuno-deficient fish showed severe cirrhosis and had little natural
immunity to disease.
Crayfish (Bythotrephes longimanus) collected in the reach were moribund, and
examination showed severe degeneration of the intestinal epithelium and abnormal
TABLE 4. POLLUTANTS IDENTIFIED IN WATER AND BOTTOM SEDIMENTS IN THE NORTHERN
PART OF THE SHEKSNA REACH (RYBINSK RESERVOIR, NEAR CHEREPOVETS 1990-91)
Water Bottom sediments
Pollutants (//g/L) (mg/g dry weight)
Polychlorinated biphenyls Trace = 0.29 Trace = 0.60
Oil products:
Hydrocarbons 0.05-0.19 0.56-0.62
Resinous components 0.00-0.03 0.44- 2.65
Polyaromatic hydrocarbons 0.10-0.64 3.33-49.73
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development of the placental structure leading to the brood pouch. This can lead to mortality
of parthenogenetic embryos developing in the pouch. As a result, crayfish reproduction and
population levels have declined, and its distribution has narrowed. In the near future, we
expect crayfish to disappear altogether.
At the population level, pollution causes changes in number and biomass, birth and
mortality, and in dimensional structure and dynamics in aquatic organisms. The
concentrations of saprophytic bacteria, as well as specialized groups of microorganisms
which oxidize phenol, naphthalene, oil, and other organic pollutants, increases sharply in
polluted waters. The presence of these toxicants in water has an especially negative impact
on large crayfish with prolonged life cycles (Bythotrephes sp., Heteroscope sp., Eudiaptomos
sp.). Genetic and population-level analyses have shown considerable disturbance in the
genetic structure of fish inhabiting areas receiving industrial wastewaters. These genetic
changes are similar to those observed in the zones of radioactive pollution at the Chernobyl
Nuclear Station.
TABLE 5. RESIDUES OF POLLUTANTS IN TISSUES OF FISH AND BENTHIC INVERTEBRATES IN
THE NORTHERN PART OF THE SHEKSNA REACH (RYBINSKOYE RESERVOIR, NEAR
CHEREPOVETS, 1990-91)
Organism
Tissues
PCS*
(mg/kg)
PAC + OPCT
(mg/kg)
Oil products
(mg/kg)
White bream
Pike perch
(Lucioperca
vo/gens/s)
Blue bream
(Abramis ballerus)
Dreissena
Chironomidae
Oligochaetes
Viviparus
(pulmonate snails)
Muscle
Liver
Muscle
Liver
Muscle
Liver
FISH
0.00-0.53
0.45-5.41
0.00-0.49
0.77-1.76
0.25
0.87
INVERTEBRATES
Whole organism 0.20-1.40
Whole organism 1.15-0.67
Whole organism 0.00-0.42
Whole organism 0.14-1.32
3.60-39.4
0.40-23.3
15.4
20.0
14.465
10-140
17.0
17.0
9.0-37.0
39.0-733.0
*PCB = polychlorinated biphenyl.
tPAC = Polyaromatic hydrocarbon; OPC = oxidized polynuclear compound.
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At the ecosystem level, pollution affects the structure and function of plankton and
benthic communities. Areas, such as the Sheksna Reach, receiving heavy loads of industrial
and municipal wastes from Cherepovets, characteristically have a low index of species
diversity and a low quantity and biomass of phytoplankton and zooplankton (Table 6).
Trophic food chains are shortened in these aquatic communities and the number of predators
has declined sharply. In spite of extremely high concentrations of biogenic elements, the
intensity of photosynthesis in these areas is low, which is probably related to low water
transparency and toxic effects of wastewaters. The significant increase of bacterial
production over primary production is the likely result of the intensive destruction of microflora
and microfauna that feed on bacteria, such as rotifers, etc. Such increases in development
of planktonic bacteria in comparison to phytoplankton is related to the input of large amounts
of anthropogenic organic matter. These relationships are demonstrated by ratios of primary
production to total heterotrophic decay (Table 6). South of the Cherepovets area, toxic
effects of pollution decrease and eutrophication occurs: photosynthesis increases sharply and
total biomass of the plankton community increases. An increase in species diversity is also
observed, but the role of predators in the total biomass of zooplankton remains insignificant.
Pollution of bottom sediments greatly influences the structure and function of benthic
communities. Monitoring of microbiological processes taking place in the bottom sediments
TABLE 6. STRUCTURAL/FUNCTIONAL CHARACTERISTICS OF PLANKTON COMMUNITIES IN THE
POLLUTED SHEKSNA REACH AND TWO DOWNSTREAM ZONES OF THE RYBINSKOYE
RESERVOIR, SUMMER 1989
Downstream zones
Parameters
Zooplankton
(Shannon Index) t
Total plankton biomass
Ratio, biomass of predator
zooplankton to prey (%)
Sheksna Reach*
1.4-1.7
7.1
22.2
Eutrophic
3.9
17.0
14.0
Relatively clean
2.0-2.5
3.8
84.7
Photosynthesis
(mg carbon [C]/M3/hour) 0.94 2.21 0.77
Bacterial production 2.97 2.10 1.20
(mg C/m3/hour)
Ratio, primary production to
total heterotrophic decay 0.45-0.73 0.44-1.51 2.24-3.73
*Data from 1986-88.
t Index of biodiversity.
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of the toxic zone can be used as an indicator of the adverse effects of long-term chronic
pollution, such as that caused by wastes discharged in the Cherepovets area. The specific
activity of dark assimilation of C14 tagged carbon dioxide in sediments collected in the
polluted zone was higher than in sediments from other regions of the reservoir (Table 7).
These results suggest that certain microflora in sediments function actively to break down the
different pollutants in spite of their low abundance. In contrast to less polluted regions, there
is a sharp decrease in aerobic processes and an increase in anaerobic methane-forming and
sulfate-reducing microflora. Thus, the pollution-induced destruction of the aerobic bacterial
community, and development of a stable anaerobic community has seriously inhibited natural
self-purification processes in the sediments, and further, has caused secondary pollution in
the form of anaerobic decay products in downstream waters.
Anthropogenically caused changes in the Sheksna Reach of the Volga have been
caused by heavy industrial discharges, and the situation can be considered an ecological
disaster. It is obvious that the return of this ecosystem to its original condition through
self-renewal is impossible without compulsory remediation. The development of local zones
with varying degrees of adverse changes in their structural-functional ecosystem components
can be found near other large industrial centers. In addition, the riverine ecosystems
downstream of these polluted zones can be considered "at ecological risk" due to increased
eutrophication. However, it is possible to return these ecosystems to their original condition
naturally by remediating upstream pollution.
TABLE 7. FUNCTIONAL CHARACTERISTICS OF BENTHIC MICROFLORA IN THE POLLUTED
SHEKSNA REACH AND TWO DOWNSTREAM ZONES IN THE RYBINSKOYE RESERVOIR, SUMMER
1986-89
Downstream zones
Parameters Sheksna Reach Eutrophic Relatively clean
Dark assimilation 2.7 2.0 1.8
Specific activity per 1 x 10s
celts of bacteria 1.7 0.5 0.2
Aerobic decay,
mgC/rr»2/day 87 203 18O
Methane transformation,
mt/dm3/day
Formation 2.5 0.06
Oxidation 1.6 0.01
Intensity of sulfate
reduction, mg S/kg/day 41.1 3.1 1.1
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CONCLUSIONS
With a growing trend of wetland and aquatic habitat degradation, there is even greater
urgency to maintain the biological diversity and protection of gene pools of aquatic plant and
animal populations native to the Volga River. The present situation requires enhancement of
research to estimate the tolerance (resistance) of biological systems and frequency of their
anthropogenic-caused changes. Complex ecological investigations of areas under the
influence of industrial-municipal wastes have special significance because they permit us to
identify the degree of anthropogenic disruption of structural-functional components of the
ecosystem, its ability to restore itself to the original condition, and to evaluate potential
methods of remediation.
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RESTORING AQUATIC RESOURCES TO THE LOWER
MISSOURI RIVER: ISSUES AND INITIATIVES
by
David L. Galat1, John W. Robinson2 and Larry W. Hesse3
ABSTRACT
Large, low-gradient rivers, such as the Volga and the lower Mississippi, are dependent on the
river-floodplain linkage and periodic flood pulse for their integrity. The Missouri River is the longest
river in the United States and in presettlement times exhibited extensive channel migration and high
turbidity. The flora and fauna of the river-floodplain complex reflected this physical dynamic equilibrium.
Presently, about one-third of the river has been channelized, one-third impounded, and the hydrograph
of the remaining one-third severely altered. Additionally, agricultural, industrial, and urban development
in the river basin has degraded water quality. Physical and chemical consequences of these alterations
are reviewed as well as impacts on biological structure and function, including commercial and sport
fishery resources. Restoration of the Missouri River necessitates a return of the ecosystem to an
approximation of its former condition, including recreating both structural and functional components.
Objectives to attain this goal include reestablishment of a semblance of the precontrol hydrograph and
sediment regime, restoration of some of the precontrol channel structural diversity and the river-
floodplain linkage, reestablishment and enhancement of native Missouri River fishes and their
migrations, reduction of major point and nonpoint sources of pollution, and restoration of native
terrestrial and wetland plant communities along the river channel and floodplain. Several recent
initiatives are summarized that attempt to resolve competing watershed interests and address one or
more of these objectives. These initiatives are the Mississippi Interstate Cooperative Resource
Agreement, the Cooperative Interjurisdictional Rivers Fisheries Resources Act of 1992, the Missouri
River Initiative (MOR-CARE), and the Missouri River Fish and Wildlife Migration Project. Successful
restoration of the Missouri or any river-riparian ecosystem necessitates a holistic perspective at the
landscape scale of the river basin.
1Missouri Cooperative Fish and Wildlife Research Unit, U.S. Fish and Wildlife Service, 112
Stephens Hall, University of Missouri, Columbia, MO 65211, USA
2Missouri Department of Conservation, Columbia, MO 65201, USA
3Nebraska Game and Parks Commission, Norfolk, NE 68701, USA
192
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INTRODUCTION
Most large rivers in developed countries have been severely influenced by human
alteration (Petts 1984, Davies and Walker 1986, Hynes 1989) and the Missouri River is no
exception. Significant Anglo intervention began after the Louisiana Purchase, when in 1804
Lewis and Clark were commissioned by the federal government to find a road to the west for
economic development (Keenlyne 1988). Subsequently, the Missouri River became the first
great highway for exploitation and settlement of the American west. The Missouri River today,
like the Volga, has been so radically altered by damming, channelization, and pollution that its
fundamental aquatic character and processes no longer approximate natural conditions.
Our goal is to share with our Russian colleagues existing information on the lower Missouri
River. To accomplish this goal we have four objectives: 1) review the theoretical framework
for perceiving large river-floodplain ecosystems and natural versus man-induced disturbance,
2) briefly describe the lower Missouri River ecosystem, 3) summarize major alterations to it
and their effects on the biota, and 4) conclude by recommending restoration approaches and
reviewing current restoration efforts. We believe that despite obvious differences between the
Missouri and Volga rivers they share the fundamental similarities of all large rivers. Moreover,
both rivers have experienced comparable alterations (Hesse et al. 1989a, Pavlov and Ya
Vilenkin 1989). Collaborative research is essential to achieve our mutual goals of
understanding and restoration of both systems. Exchange of information is the first step to
facilitate collaborative research (Biette et al. 1989) and to develop the knowledge or
approaches needed to restore and manage the aquatic communities of these large rivers.
RIVER-FLOODPLAIN INTERACTIONS IN LARGE RIVERS
Disturbance and recovery of large rivers cannot be understood without a conceptual
framework of their normal behavior. Streams and rivers exist in a state of dynamic equilibrium
(National Research Council 1992). Local physical features are naturally created, change
through time, and eventually disappear, while the overall pattern (e.g., riffle-pool sequence,
meandering) remains constant at large spatial and long temporal scales. This dynamic
equilibrium in the physical system creates a corresponding dynamic equilibrium in the
biological system.
Contemporary perceptions of the structural and functional properties of lotic waters
are largely expressed in two paradigms: the River Continuum Concept (RCC, Vannote et al.
1980, Minshall et al. 1985) and the resource spiraling concept (Webster and Patten 1979,
Newbold et al. 1981, Elwood et al. 1983). The RCC says that a continuous gradient of
physical conditions and resources exists from a river's headwaters to its mouth. The stream's
physical features provide much of the habitat templet for stream community structure and
function. River networks are viewed as longitudinally connected systems of ordered biotic
193
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assemblages, forming a temporal continuum of synchronized species replacements.
Ecosystem level processes in downstream reaches are linked to those upstream through
processing inefficiencies or leakage so that upstream energy loss becomes downstream
energy gain. Consequently, there is a trade-off between maximizing nutrient and energy use
within a reach via retention mechanisms that minimize downstream energy loss and the
dependency on this material to drive downstream processes.
Within this framework a storage-cycle-release phenomenon termed resource spiraling
(rather than recycling) becomes apparent because of the unidirectional flow of water and
continuous transport of materials in lotic ecosystems (Webster and Patten 1979, Elwood et al.
1983). Efficiency of utilization of nutrients and organic carbon within a reach is associated
with the tightness and magnitude of the spirals. Physical retention, microbial activity, and
macroinvertebrate processing are important activities for defining the tightness of resource
spiraling and preventing rapid throughput of materials (Minshall et al. 1985).
The RCC and resource spiraling concepts were developed largely from small
temperate streams, and their usefulness as generalized paradigms for large rivers has been
questioned (Davies and Walker 1986, Statzner and Higler 1985, Welcomme 1985, Cuffney
1988, Junk et al. 1989, Sedell et al. 1989). A more relevant framework has now emerged in
which to test and clarify concepts about the structure and function of large floodplain river
ecosystems (Dodge 1989). This complementary perspective is termed the flood pulse
concept (Junk et al. 1989). Junk et al. postulate that the bulk of aquatic biomass in many
unaltered large floodplain rivers is derived directly or indirectly from production within the
floodplain and not from downstream transport or organic matter produced elsewhere in the
basin. Whereas longitudinal linkages in small to moderate sized streams are the basis for the
continuum aspect within the RCC, lateral exchange between the floodplain and river channel
and nutrient recycling within the floodplain have a more direct impact on the biota and
biological activity in large rivers. Whereas downstream losses of organic matter in small
streams are reduced primarily by instream structure (e.g., pools, debris dams), geomorphic
features within the lateral floodplain (e.g., sloughs, side channels, backwaters) are largely
responsible for retention of organic matter and nutrients in large low-gradient rivers. The
foundation of the flood pulse concept is that seasonal pulsing of flood flows onto the
floodplain is the driving force controlling the river-floodplain complex (Junk et al. 1989,
Welcomme et al. 1989, Sparks et al. 1990, Bayley 1991, Schlosser 1991).
While contributions of organic matter from floodplains may be quantitatively smaller
than from upstream sources, they may be nutritionally of higher quality. Fremling et al. (1989)
postulate that organic matter from tributary sources consists largely of dissolved humic acids
or refractory particles by the time it is delivered to the main stem Mississippi River. The more
nutritious fractions have been utilized or retained by upstream communities. They conclude
that local sources of primary production, largely from within the floodplain, are responsible for
the high fish production observed in large floodplain rivers.
Floodplain wetlands are regarded as among the most productive ecosystems in the
world (Lieth and Whittaker 1975, Brinson et al. 1981). In situ primary production is high, and
effective retention mechanisms contribute to efficient internal recycling of most carbon and
nutrients (Junk et al. 1989). Although nutrient and organic matter losses from the floodplain
complex to the river channel may be small relative to internal inputs within the floodplain,
leakage from the floodplain to the river during the annual flood pulse is the principal source of
194
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level of
floodplain —«*•
FLOODPLAIN
SURFACE
FLOOD;'LAIN
DEPRESSIONS
RIVER
INUNDATED
CONNECTED TO
RIVER
CONNECTED TO
FLOODPLAIN
TERRESTRIAL
ISOLATED EPHEMERAL
AND PERMANENT
AQUATIC HABITATS
CONFINED TO
CHANNEL
X ^^^^
"7 ^^^^MH
8
10
13
Fig. 1. Idealized changes in water level over an annual cycle for a riverine floodplain.
Numbered horizontal bars indicate characteristic annual periodicity patterns for some
major interactions as follows: 1) nutrients released as floodplain surface is flooded; 2)
nutrient subsidy from river; 3) rapid growth of aquatic plants and invertebrates on
floodplain; 4) major period of detrital processing on floodplain; 5) DOM and FPOM
exported to river; 6) maximum plankton production in floodplain depressions; 7) drift of
plankton, benthos and macrophytes to river; 8) fishes enter floodplain from river and
fishes that survived dry season in floodplain depressions move to floodplain surface;
9) major period offish spawning on floodplain; 10) period of maximum fish growth; 11)
fishes move from floodplain to river; 12) heavy fish predation losses at mouth of
drainage channels; 13) high mortality of fishes stranded in floodplain depressions.
(Source: Ward 1989.)
these materials to the main channel in unaltered rivers (Mulholland 1981, Cuffney 1988,
Grubaugh and Anderson 1989, Junk et al. 1989, Ward 1989, Sparks et al. 1990).
Fishes capitalize on this highly productive floodplain environment for feeding,
spawning, nurseries, and as refuge from adverse river conditions (Fig. 1). Indeed, floodplain
wetlands are considered the essential component responsible for the high fish production
recorded in large, low gradient-rivers (Welcomme 1985, Ward 1989). Risotto and Turner
195
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Stage
use by fish
Temp.
0)
O)
2
CO
Jan.
CL
I
-------
NATURAL AND ANTHROPOGENIC DISTURBANCE
Disturbance in lotic waters has been defined as any unpredictable, discrete event that
disrupts structure or function at the ecosystem, community, or population level (Resh et al.
1988). Lack of predictability is an important component of this definition. Resh et al. (1988)
consider disturbances as events characterized by a frequency (rate of occurrence of events)
and intensity (physical force of event per time) that are outside a predictable range (see Poff
[1992] for an alternative perspective). Periodic flood pulses of large rivers are predictable
events under this definition. Indeed, the periodic flood pulse is critical to maintenance of
aquatic populations, communities, and ecosystem processes. From this perspective, floods
are not disturbances, unless so amplified, reduced, or mistimed that they fall outside the long-
term pattern (Sparks et al. 1990). Large floods are not disruptive events in the long term, as
they contribute to the dynamic equilibrium of the system. Such flood events can reset late
successional stages to earlier stages, thereby increasing habitat and species diversity (Sparks
et al. 1990). Sand islands are an example of such an ephemeral early successional habitat in
the Missouri River. Grace (1985) reported 46 species, or two-thirds of the total lower Missouri
River fish fauna, utilized this habitat. Also, two federally listed birds, the least tern (Sterna
antillarum) and piping plover (Charadrius melodus) nest primarily on sand islands.
Man has isolated rivers from their floodplains by draining and filling wetlands,
channelizing river segments, constructing levees to contain flood flows within the main
channel, and constructing mainstream dams and impoundments to reduce downstream
flooding and regulate flow (Petts 1984, Brookes 1988, Ward and Stanford 1989, Bayley 1b91).
These activities have drastically affected aquatic communities and processes and severed the
river-floodplain linkage. Channelization and damming, together with agricultural, municipal,
and industrial pollution, constitute the major man-induced disturbances to the integrity of the
world's large river ecosystems. We will briefly describe the nominal state of the Missouri River
and then summarize effects of these disturbances.
MISSOURI RIVER ECOSYSTEM
The Missouri River's present southeasterly diagonal course across the midcontinent of
the United States (U.S.) traces the southern limits of Pleistocene glaciation (Fig. 3). It is the
longest river in the U.S., 3,768 km, with a drainage basin encompassing about 1,327
thousand km2 or about one-sixth of the continental U.S. Four physiographic provinces
comprise its drainage basin: 142 thousand km2 of the Rocky Mountains in the west, 932
thousand km2 of the Great Plains in the center of the basin, 228 thousand km2 of Central
Lowlands in the north lower basin, and 24.5 thousand km2 of the Interior Highlands in the
south lower basin (Slizeski et al. 1982, Robison 1986). River slope varies from about 38 m
km'1 in the Rocky Mountains to an average of 0,17 m km"1 in the Great Plains and Central
Lowlands (USAGE 1985). A prominent feature of the Missouri River's drainage pattern is that
most major tributaries in the upper and middle portions of the basin enter on the right bank,
flowing to the east or northeast.
Climate of the basin is controlled by three air circulation patterns: one originating in
the Gulf of Mexico, another in the northern Pacific Ocean, and the third in the northern polar
197
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Canyon Ferry Reservoir
(RK 3.688) .
-Fort Peck (Fort Peck Dam) (RK 2.851)
. Sakakawea (Garrison Dam) (RK 2.237)
• Oahe (Oahe Dam) (RK 1,725)
Sharp* (Bif Bend Dam) (RK 1,588)
Francis Case (Fort Randall Dam) (RK 1.416)
Yankton(RK 1,295)
Lewis and dark (Gavins Point Dam)
(RK UOS)
Iowa
Fig. 3. The Missouri River Basin showing most of the civil works projects completed by the
U.S. Army Corps of Engineers and U.S. Bureau of Reclamation. RK represents river
kilometer. (Source: Hesse et al. 1989a.)
region (USAGE 1985). The freeze-free season ranges from fewer than 40 days in the Rocky
Mountains to more than 120 days in the Interior Highlands (Hesse et al. 1989a). The
drainage basin is generally arid and subject to seasonal and long-term droughts due to the
dominance of the Great Plains physiographic region. Average annual precipitation ranges
from more than 80 cm in the Rocky Mountains, to about 45 cm in the Great Plains, and more
than 90 cm in the Interior Highlands (Hesse et al. 1989a).
Annual Missouri River discharge to the Mississippi River is about 7.0 x 1010 m3. Two
seasonal periods of flooding occurred prior to impoundment (Fig. 4). The first, or March rise,
was caused by snow melt in the Great Plains and break-up of ice in the main channel and
tributaries. The second, or June rise, was produced by runoff from snow melt in the Rocky
Mountains and rainfall throughout the basin.
In presettlement times the Missouri River was one of the most turbid river systems in
North America, earning it the nickname Big Muddy. The magnitude of the Missouri River's
sediment load can best be illustrated by its influence on the Mississippi River. Average
turbidity of the Mississippi River upstream of the preimpounded Missouri River was reported
198
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r "%
6
o
55
O
600
500 •
400 -
300 •
200
100 ^
,-J
w
600 •
500 -
400 -
300 •
200 -
100 -
-^ X
/Vf
60 120 160 240 300
JULIAN DATE
360
Fig. 4. Mean (solid line), maximum (dotted line) and minimum (dashed line) stages of the pre-
(upper panel) and post-regulated (lower panel) Missouri River at Omaha, Nebraska
(Rkm 1107). Pre-regulated stages are based on averages of daily stage recordings
between 1880 and 1899 and post-regulated stages are based on averages between
1966 and 1985. (Modified from Hesse and Mestl 1992.)
by Plainer (1946) as 300 ppm, whereas below the mouth of the Missouri River the average
increased to 1,800 ppm.
The Missouri River's course through highly erodible soils resulted in major changes in
channel configuration during flooding. During normal flows the channel was characterized by
continuous bank erosion, a braided shifting configuration, and numerous sand islands and
bars. Extensive channel migration in the lower river resulted in a floodplain width of 2.4 to
27.4 km, averaging 8.1 km (Hesse et al. 1989a). For example, about one-third of the
floodplain of the lower Missouri River was reworked by the river between 1879 and 1930
(Schmudde 1963).
Erosional and depositional characteristics of this dynamic equilibrium resulted in a
range of serial forest communities in the Missouri River floodplain (Bragg and Tatschl 1977).
Recently deposited and exposed sandbars are rapidly colonized by willows fSa//x spp.) and
succeeded by cottonwood (Populus deltoides), which dominates the canopy for up to 30
199
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Date
TABLE 1. SELECTED CHRONOLOGY OF SIGNIFICANT EVENTS
IN THE HISTORY OF LOWER MISSOURI RIVER DEVELOPMENT
(PRINCIPAL SOURCES: FUNK AND ROBINSON 1974, FORD 1982,
HESSE 1987, HESSE ETAL 1982, 1989A, BENSON 1988, SCHMULBACH ET AL 1992)
Event
1803 Acquisition of basin to U.S. from France through Louisiana Purchase.
1804-06 Captains M. Lewis and W. Clark expedition of Missouri River from mouth at St Louis,
Missouri, to origin in Montana
1819 First steamboat travel on Missouri River.
1829 First commercial steamboat barge line: St. Louis to Leavenworth, Kansas-Steamboat
era begins.
1832 Snag removal authorized under Act of Congress.
1838 2,245 large trees removed from river channel and 1,700 overhanging trees cut from
bank in 619 km of river upstream from St Louis.
1867-68 Major C. W. Howell Survey and Report on Improvement of Missouri River.
1869 Peak of steamboat era; 47 steamboats deliver about 9,000 mt of cargo to Ft. Benton,
Montana, 3,540 km upstream from St. Louis.
1881 Lt. Col. C. R. Suter Report detailing long-range plans for aiding navigation on river.
1884 Missouri River Commission established by Congress to improve navigation of river by
contracting its width, stabilizing channel location, protecting banks from erosion, and
snag removal.
1885-1910 Snag removal systematic and intensive; 17,676 snags, 69 drift piles, and 6,073
overhanging bankline trees removed in 866 km of river in 1901 alone.
1902 Repeal of Act establishing Missouri River Commission. Railroads dominate freight
traffic-Steamboat era ends.
1902 Congress enacts Reclamation Act of 1902 (PL 57-161) to survey, construct, and
maintain irrigation works in arid lands of the western United States. Start of reservoir
development planning.
1902-12 No maintenance of Commission structures-most wash out.
1910 Increase in typhoid deaths in towns along Missouri River.
1912 Congress authorizes 1.8 m deep, 61 m wide channel from Kansas City, KS to St.
Louis, Missouri (PL 62-241).
(continued)
200
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Table 1. (continued)
Date
Event
1912-17 Active dike and revetment construction to stabilize channel.
1913 U.S. Public Health Service (USPHS) report identifies sewage pollution in river as a
major factor in typhoid deaths.
1917-33 Maintenance of channel structures, active period of levee construction.
1920-58 Records and studies of water suppliers and USPHS confirm bacterial contamination.
Treatment by most water suppliers does not meet USPHS standards.
1925 PL 68-585 authorizes 200 ft wide channel, Kansas City, Missouri, to mouth.
1927 Extension of 1.8 m deep channel to Sioux City, IA (PL 70-560).
1934 Passage of Fish and Wildlife Coordination Act (PL 73-121) requiring that fish and
wildlife receive equal consideration to other purposes of federal planning in federally
funded or approved water development projects.
1936 Passage of Flood Control Act (PL 74-738) to develop "works of improvement" on more
than 50 major river throughout the U.S.
1937 Construction completed on the first mainstem dam and impoundment on Missouri
River, Ft. Peck Dam and Reservoir, Montana, to supply water for river navigation.
1944 Flood Control Act of 1944 (PL 78-534) authorized Pick-Sloan Plan to construct 6 dams
on mainstem of Missouri River. Missouri River Bank Stabilization and Navigation
Project authorized for flood control, bank stabilization, land reclamation, hydropower
generation, and development and maintenance of navigation channel.
1945 Rivers and Harbors Act (PL 79-14) passed, provided a 2.7-m deep, 91.4-m wide
navigation channel from St. Louis to Sioux City.
1946 Fish and Wildlife Coordination Act of 1946 (PL 79-732) passed, required federal
agencies to construct water projects with a view to preventing loss of and damage to
wildlife resources.
1946-55 5 additional dams and reservoirs constructed on Missouri River. See Table 4 for
details.
1956 Federal Clean Water Act (PL 84-660) passage strengthens water quality regulations.
1958 Fish and Wildlife Coordination Act of 1958 (PL 85-624) required the cost of water
project modifications or land acquisition earlier required under PL 79-732 to prevent
loss or damage to wildlife be included as part of the project costs.
(continued)
201
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Table 1. (continued)
Date
Event
1960- Replacement of permeable pile dikes with impermeable rock dikes.
1960-70 Construction of primary wastewater treatment facilities for major discharges on lower
river.
1964 Fish kill in Missouri River extending more than 161 km downstream from Kansas City,
Missouri.
1965 Federal Water Project Restoration act (PL 89-72) required non-federal public agencies
to administer fish, wildlife, and recreation on project lands and pay one-half of costs
allocated to these resources.
1969 Flavor tests reveal unacceptable tastes in fishes from several locations in Missouri
River. PCB levels in common carp pose potential threat.
1969 Federal Water Pollution Control Authority, and later U.S. Environmental Protection
Agency (USEPA), establishes downstream minimum daily average flow requirements
to maintain federally approved water quality standards.
1970-71 25% of fishes sampled from a bay in Lake Oahe, South Dakota, contained unsafe
levels of methylmercury. Source of mercury was mining operations on a tributary
stream.
1970-74 PCBs, aldrin, and dieldrin levels in fishes at Hermann, Missouri, pose potential health
threat.
1971 USEPA study reveals levels of Salmonella, fecal coliform bacteria, and viruses in
Missouri River present a potential hazard for drinking water or recreation.
1972 Federal Water Pollution Control Act of 1972 (PL 92-500) passed requiring USEPA to
establish national effluent and toxic discharge standards.
1972-88 Construction of secondary wastewater treatment facilities for most major dischargers
to lower river.
1973 Endangered Species Act (PL 93-205) passed requiring U.S. Fish and Wildlife Service
to list species threatened or endangered with extinction; authorizes programs for their
recovery; prohibits authorization of federal projects that jeopardize listed species or
their habitats. See Table 6 for Federally listed Missouri River biota.
1975-80 U.S. Army Corps of Engineers (USAGE) constructs environmental notches in 1,306
wing dikes from Sioux City to St. Louis to create fish habitat on downstream side of
dike.
1976-78
PCBs, aldrin, dieldrin, and chlordane residues in fishes exceed safe limits.
(continued)
202
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Table 1. (continued)
Date
Event
1976
1977
1978
1980
1984-86
1986
1987-
1988
1988-90
1989
1989-
1990-
1990
Toxic Substances Control Act (PL 94-469) passed phasing out use of PCBs and
restricting use of chlordane.
Clean Water Act of 1977 (PL 95-217) established national effluent standards for water
pollutants; required cities to implement secondary sewage treatment and provided
federal grants to aid construction; set target date for discharge elimination of 129
priority pollutants; required USEPA permit for point source discharge of pollutants.
240 km of free-flowing Missouri River in Montana and 93 km below Gavins Point Dam
incorporated into National Wild and Scenic Rivers System.
37 common industrial solvents (13 metals, 23 organic compounds, and cyanide)
detected in St. Louis water treatment plants.
Chlordane levels in fish flesh from lower Missouri River reported to exceed safe limits
for consumption.
Water Resources Development Act (PL 99-662) authorizes USACE to mitigate aquatic
and terrestrial habitat fosses from past projects.
Missouri Department of Health advisories issued warning against consumption of
specific commercial fish species from areas of Missouri River due to toxic
contamination.
Missouri River Natural Resources Committee (MRNRC) established to promote
preservation, wise utilization, and enhancement of natural and recreational resources
of Missouri River.
Major drought in Missouri River Basin. Water shortage precipitates conflict over water
allocations for navigation versus recreation. USACE initiates Master Manual Review
and updates to develop and evaluate alternative water management operations for
mainstem reservoir system.
Mississippi Interstate Cooperative Resource Agreement (MICRA) formed by various
entities in the Mississippi River Basin (see text).
More stringent discharge permit limitations for toxic metals and organics imposed on
wastewater treatment facilities of major cities along lower Missouri River, Missouri.
Upper Missouri River Basin states (Montana, N. and S. Dakota) sue USACE claiming
reservoir operation should consider upstream recreation needs in addition to lower
river navigation needs for water releases.
Missouri River Initiative (Missouri River-Conserving a River Ecosystem, MOR-CARE)
formed to facilitate cooperation among governmental, Tribal, and private parties for
optimal recovery of natural resource values and environmental health of Missouri River
ecosystem (see text).
(continued)
203
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Table 1. (continued)
Date Event
1990 Nonindigenous Aquatic Nuisance Prevention and Control Act of 1990 (PL 101-646)
passed to prevent and control infestations of coastal inland waters by zebra mussel
and other nonindigenous aquatic nuisance species.
1991 USAGE mitigation projects begin on lower Missouri River, include land purchases in
floodplain and construction to enhance aquatic resources (see text).
1991 A 63 km section from Ft. Randall Dam to headwaters of Lewis and Clark Lake,
including 40 km of lower Niobrara River and 13 km of Verdegie Creek, designated a
National Recreation River
1991 Missouri Department of Conservation publishes Big River Fisheries 10 year Strategic
Plan.
1992 Introduction of Gunderson Bill (H.R. 4169) to establish a Council on Interjurisdictional
Rivers Fisheries and to provide funds to MICRA to conduct a comprehensive study of
the status, management, research, and restoration needs of fisheries of Mississippi
River drainage basin (see text).
1992 Closure of commercial fishing for all catfish species in lower Missouri River (see text).
years. Box elder (Acer negundo), silver maple (Acer saccharinum), red mulberry (Morus
rubra), and American elm (Ulmus americana) replace cottonwood as an intermediate serial
stage. Mature floodplain forests contain several species of oaks (Quercus spp.) and hickories
(Carya spp.), plus hackberry (Celtis occidentalis), American elm, black walnut (Juglans nigra),
green ash (Fraxinus pennsylvanica), sycamore (Plantanus occidentalis), basswood (Tilia
americana), and-almost exclusively in old growth forests-pawpaw (Asimina triloba) (Weaver
1960, Bragg and Tatschl 1977). Little light penetrates the dense canopy of mature Missouri
River floodplain forests resulting in an understory dominated by climbing vines (Weaver 1960),
including poison ivy (Rhus radicans), Virginia creeper (Partenocissus quinquefolia), and wild
grapes (Vitis spp.).
Studies of the structural and functional biology of the Missouri River abound. Sowards
and Maxwell (1985) list more than 600 Missouri River references and Hesse et al. (1982,
1989a) provide comprehensive reviews of phytoplankton, periphyton, invertebrates, fishes,
and energy dynamics of the river and its mainstem reservoirs. Many of these studies treat
how biota and processes have been influenced by river alteration, and are referenced in
Table 1. Lower Missouri River fish and fisheries are treated in a separate section.
ALTERATIONS TO THE MISSOURI RIVER ECOSYSTEM
Modifications to the integrity of the natural Missouri River-floodplain ecosystem have
been immense and ongoing for more than 150 years (Table 1). Presently, 35% (1,316 km) of
the river's length is impounded, 32% (1,212 km) is channelized or stabilized, and the
204
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remaining 33% (1,241 km) is free-flowing (Schmulbach et al. 1992). Major civil works projects
included channelization, channel maintenance, and impoundment and reservoir operation.
Total cost for construction, operation, and maintenance of civil works projects through 1984
was $5.9 billion dollars (Table 2, Hesse 1987). Agricultural, industrial, and urban development
within the basin also significantly modified the Missouri River and produced extensive water
pollution (Table 1).
CHANNELIZATION
Abundant large woody debris (snags) in the river channel, fluctuating water levels, and
extensive channel migration made early Missouri River navigation perilous. Modifications of
the river to facilitate navigation included snag removal; channel dredging; and construction
and maintenance of dikes, revetments, and levees. Stabilizing a river channel contrasts
sharply with the concept of dynamic equilibrium discussed earlier. Stabilized channels are
static. They lack the successional pattern and periodic disturbance events that maintain
physical habitat diversity. Consequently, structure and function of the biological system also
become stabilized. Funk and Robinson (1974) described how channelization and associated
activities were accomplished in the lower Missouri River and we summarize its chronology in
Table 1. Presently all of the Missouri River from Sioux City, Iowa, to its mouth at St. Louis,
Missouri, is channelized. Even during flooding only about 10% of the original floodplain is
inundated, as high agricultural levees confine the river to a width of 183-335 m (Schmulbach
et al. 1992). Impacts of snag removal and channelization have been numerous and severe on
TABLE 2. SUMMARY STATISTICS FOR CIVIL WORKS PROJECTS IN THE MISSOURI RIVER BASIN
THROUGH 1984. CONSTRUCTION COSTS ARE ACTUAL DOLLARS SPENT, AS ARE OPERATIONS
AND MAINTENANCE ON CORPS OF ENGINEERS PROJECTS, BUT OPERATIONS AND
MAINTENANCE HAD TO BE ESTIMATED FOR BUREAU OF RECLAMATION PROJECTS. THE
DOLLARS DEPICTED IN THIS TABLE ARE CONSIDERED CONSERVATIVE ESTIMATES. (SOURCE:
HESSE 1987)
Millions of dollars
Numbers of Construction Operations and Total
Project type projects cost maintenance costs
Channel
Levee
Reservoir
Other construction
Federal recreation
Total
19
2
77
NA
19
117
561.5
92.2
3948.1
235.0
21.8
4858.6
369.0
NA
921.7
1.6
NA
1292.3
930.5
92.2
869.8
236.6
21.8
150.9
205
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TABLE 3. SUMMARY OF EFFECTS OF RIVER CHANNELIZATION (C), INCLUDING SNAG REMOVAL,
AND CONSTRUCTION OF DIKES, REVETMENTS, AND LEVEES; CONSTRUCTION AND OPERATION
OF MAINSTREAM DAMS (D), AND BOTH TYPES OF ALTERATIONS (CD) ON THE LOWER MISSOURI
RIVER ECOSYSTEM
Physical
C Changes in channel geomorphology:
8% reduction in channel length
27% reduction in bank-to-bank channel area
50% reduction in original surface area of river
98% reduction in surface area of islands
89% reduction in number of islands
97% reduction in area of sandbars
resulting in reduction in channel diversity through loss of side channels, backwaters,
islands, and meandering (Funk and Robinson 1974, Hesse et al. 1988).
C Change in physical substrate from dominance of silt, sand, and wood to rock rip-rap.
C Increased water depth and velocity in main channel.
D Pre- versus post-impoundment declines in suspended sediment loads at Omaha,
Nebraska, and St. Louis, Missouri, of 175 to 25 and 250 to 125 million tonnes per year
(Schmulbach et al. 1992).
D Reduction in river sediment load resulting in channel bed degradation including
channel deepening, increased bank erosion, and drainage of remnant backwaters
downstream from dams (Hesse et al. 1988, 1989a, b).
D Silt-clay fraction of suspended sediment load reduced by 50%, but sand fraction
increased 260%, following closure of Gavins Point Dam in 1954 (Slizeski et al. 1982).
D Reduction in turbidity resulting in increased light penetration (Morris et al. 1968,
Pflieger and Grace 1987).
D Modification of natural flow regime by evening maximum and minimum discharges and
eliminating periodic flood pulse.
D Reduction in annual temperature range.
CD Loss of periodic flooding and floodplain connectivity.
Chemical
Higher water velocities reduce travel time for dissolved ions, nutrients, and
contaminants.
(continued)
206
-------
Table 3. (continued).
Chemical (continued)
D Increase in dissolved oxygen concentrations below mainstem dams (Morris et al.
1968).
D Higher postimpoundment summer flows for navigation dilute impacts of point source
discharged pollutants (Ford 1982).
D Reductions in nitrogen and phosphorus concentrations downstream from reservoirs
and changes in spiraling patterns (Ward and Stanford 1983, Schmulbach et al. 1992).
Biological
C Decline in habitat richness resulted in presumed decrease in diversity of periphytic
algae (Farrell and Tesar 1982).
C Elimination of plankton and invertebrates produced in standing water chutes and
sloughs with loss of these habitats (Whitley and Campbell 1974).
C Loss of instream snag habitat and functions of organic matter retention and substrate
for invertebrates and fishes (Benke et al. 1985).
C Greater standing crop of benthic invertebrates in main stream of unchannelized versus
channelized river sections (Berner 1951, Morris et al. 1968, Nord and Schmulbach
1973).
C Smaller standing crops of benthic invertebrates in chutes and mud banks of
unchannelized versus channelized sections (Morris et al. 1968).
C Larger standing crop of drift in unchannelized than channelized sections of river and
little similarity between drift and benthos (Morris et al. 1968, Modde and Schmulbach
1973).
C 67% reduction in benthic area suitable for invertebrate colonization (Morris et al. 1968).
C 54% decline in benthic invertebrate production from all unchannelized habitats of
Missouri River downstream from mainstem dams between 1963 and 1980 and 74%
decrease in production in chute/backwater habitats (Mestl and Hesse 1992).
C Loss of river-floodplain connection for fish migration, spawning and rearing.
C Reduction in microhabitats resulting in decreased abundance of fish
species in channelized versus unchannelized section of river in Nebraska
(Schmulbach et al. 1975).
C Higher standing crop of sportfishes in unchannelized sections of river in Nebraska
compared with channelized sections attributed to more backwater habitat and greater
habitat diversity (Groen and Schmulbach 1978).
(continued)
207
-------
Table 3. (continued)
Biological (continued)
C Loss of nesting habitat for sandbar/sand island birds leading to drastic population
declines (e.g., Sterna albifrons. Charadrius melodus).
D Elimination of riparian forests and stream channels in areas flooded by reservoirs,
totaling more than one-third entire length of Missouri River (Hesse et al. 1988).
D Entrainment of fluvial paniculate organic matter in reservoirs.
D Temperature induced shifts in periphyton and phytoplankton community structure,
particularly below dams (Farrell and Tesar 1982, Reetz 1982).
D Increase in periphyton primary production below dams (Ward and Stanford 1983).
D Increased relative importance of phytoplankton biomass and primary production
compared with upstream allochthonous inputs.
D Increase in diversity and density of zooplankton community in river downstream from
reservoirs (Repsys and Rogers 1982).
D Changes in standing crop and diversity, and shifts in functional feeding groups of
benthic macroinvertebrates in river downstream from reservoirs (Ward and Stanford
1979).
D Alteration of emergence cues, egg-hatching, diapause-breaking, and maturation of
aquatic insects due to thermal modifications below reservoirs (Ward and Stanford
1979, Petts 1984).
D Blockage of riverine fish migration.
D Inundation of floodplain fish spawning and nursery habitats.
D Development of extensive sportfisheries in reservoirs and tailwaters (Hesse et al.
1989a).
CD Near elimination of natural riparian community (Hesse et al. 1988, 1989a, b). Changes
reported:
-41% deciduous vegetation
-12% grasslands
-39% wetlands
CD 25% decrease in post-dam tree growth in North Dakota floodplain compared with
pre-dam period related to absence of annual soil profile saturation, lowering of water
table in spring to reduce downstream flooding (Reiley and Johnson 1982), and lack of
nutrient silt deposition (Burgess et al. 1973).
(continued)
208
-------
Table 3. (continued)
Biological (continued)
CD Increasing proportion of mature forest to other successional stages in remaining
floodplain (Bragg and Tatschl 1977).
CD 80% decline in organic carbon load of post-control Missouri River to Mississippi River
compared with pre-control (Hesse et al. 1988).
CD Loss of major floodplain habitat types reduced populations of associated flora and
fauna (Clapp 1977).
CD Decreases in endemic large river fishes (e.g., Scaphirhvnchus albus. Polydon
spathula. Cycleptus elongatus. Hvbopsis gracilis) and increases in pelagic planktivores
(e.g., Dorosoma cepedianum. Alosa chrysochloris) and sight-feeding carnivores (e.g.,
Morone chrysops. Lepomis macrochirus) (Pflieger and Grace 1987, Hesse et al. 1992).
CD Population declines of 11 native Missouri River Basin biota leading to listing as
Federally threatened or endangered (Table 7).
CD As much as an 80% decline in commercial fishery in Nebraska and 97% decline in
tailwater recreational fishery below Gavins Point Dam (Hesse and Mestl 1992).
CD Decline in legal-sized catfishes in Missouri River, Missouri, attributed in part to
increased susceptibility to exploitation due to lost habitat diversity (Funk and Robinson
1974, Robinson 1992).
CD Introduction and establishment of non-native fishes and invertebrates (e.g.,
Oncorhynchus spp., Osmerus mordax. Mvsjs relicta). See Table 6 for list of
introduced fishes.
Social
D Hydroelectric power generation of over 2.2 Gw, sales totaling $1.5 billion from 1943-86
(Sveum 1988).
D Development of major reservoir-based recreation and associated commercial services,
supported spending of $65 million in 1988 (General Accounting Office 1992).
CD Commercial navigation industry transports about 2 million tonnes goods, producing
gross revenues of $17 million in 1988 (General Accounting Office 1992).
CD Water supply provided to 40 cities (3.2 million people), 21 power plants, and 2
chemical manufacturers in lower Missouri River (General Accounting Office 1992).
CD 4,000% increase in area of agricultural land use (Hesse et al. 1988).
CD 95% of protected floodplain now in agricultural, urban, and industrial uses (Hesse et
al. 1989b).
209
-------
the physical, chemical, and biological structure and function of the Missouri River and its
floodplain (Table 3). The most damaging of these alterations to aquatic communities has
been the near complete isolation of the river from its floodplain, subsequent loss of floodplain
habitat, a drastic reduction in area and diversity of river channel habitats, and an increase in
main channel flow velocity. See Brookes (1988) for a further review of the general physical
and biological impacts of river channelization.
DAM CONSTRUCTION AND OPERATION
Widespread flooding during the war years of 1942-44 was the impetus for passage of
the 1944 Flood Control Act to construct a six-dam mainstem Missouri River flood control
system (Keenlyne 1988). Called the Pick-Sloan Plan, it would "...provide for the most efficient
utilization of waters of the Missouri River Basin for all purposes including irrigation, navigation,
power, domestic and sanitary purposes, wildlife, and recreation" (House Report No. 475
1944).
The last project, Big Bend, was completed in 1963 yielding a total storage capacity for
the six reservoirs of 91.5 km3, the largest of any system in the U.S. (Table 4). Other large
storage reservoirs, more than 1,300 smaller impoundments, and farm ponds also have been
built on the Missouri River mainstem and tributaries (Schmulbach et al. 1992). Sveum (1988)
summarized the controversial operating history of the six mainstem reservoirs for their
designed multiple uses.
Impacts of mainstem regulation on downstream lotic ecosystems are numerous and
well documented (Ward and Stanford 1979, 1983, Lillehammer and Saltveit 1984, Petts 1984,
Davies and Walker 1986, Dodge 1989, National Research Council 1992). Reduction in
suspended sediment loads and turbidity in the lower Missouri River has been one of the most
obvious results of upstream impoundment (Morris et al. 1968, Whitley and Campbell 1974,
Ford 1982, Slizeski et al. 1982, Schmulbach et al. 1992).
Average annual suspended loads decreased between 67 and 99% among various
lower river cities (Table 5) and mean annual turbidity at the mouth of the Missouri River above
St. Louis, Missouri, decreased fourfold from the 1930s to the 1970s (Fig. 5). Changes in
particle sizes of suspended sediment, periphyton growth, and fish functional feeding groups
have all been associated with reductions in suspended load and increased water clarity
(Table 3). Concurrently, sediment retention by mainstem reservoirs has increased the erosive
power of water discharged from dams. The river's bed 8.3 km downstream from Gavins Point
Dam downcut 2.3 m between 1929 and 1980 and degradation continues to occur at least 346
km downstream to the mouth of the Platte River (Hesse et al. 1989a).
Alteration of the natural hydrograph has undoubtedly been the most significant impact
of dam construction to the lower Missouri River and constitutes a major disturbance (sensu
Resh et al. 1988) to the system. Bimodal March and June discharge maxima evident prior to
impoundment have been replaced by a flat hydrograph for the April through November
navigation season (Hesse and Mestl 1992, Fig. 4). Present water management has also
reduced flushing flows or flows that exceed bank-full discharge (Hesse and Mestl 1992).
Bank-full discharge is responsible for maintaining channel configuration and substrate
composition, and is the discharge above which the floodplain is inundated in floodplain rivers
(Stalnaker et al. 1989). Earlier we discussed the importance of the flood pulse to the integrity
210
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211
-------
TABLE 5. AVERAGE ANNUAL SUSPENDED SEDIMENT LOAD (MILLION METRIC TONNES) IN THE
LOWER MISSOURI RIVER, MODIFIED FROM FORD (1982)
Sediment load
River Percent
Location (km) <1953 >1955 change
Yankton, South Dakota 1305 125.0 1.3 -99
Sioux City, Iowa 1178 10.7
Omaha, Nebraska 1107 148.6 25.9 -83
Nebraska City, Nebraska 904 42.7
St. Joseph, Missouri
Kansas City, Missouri
Boonville, Missouri
Hermann, Missouri
727
579
290
161
233.3
215.9
317.5
295.9
52.3
71.7
91.4
-78
-67
-69
of large river ecosystems. Hesse and Mestl (1992) calculated bank-full discharge (the
maximum instantaneous flow with a recurrence interval of about 1.5 years, Stalnaker et al.
1989) for the Missouri River between 1929 and 1948 as 3,115 rrvYsec. This discharge
occurred in 15 of 24 mostly predam years (1929-1952), but in only 2 of 33 years following
closure of mainstem dams (1954-1986). Channelization and impoundment of the Missouri
River have effectively decoupled the lower river from its floodplain and disrupted the annual
flood pulse. This disruption has resulted in widespread and severe disturbance to the
physical, chemical and biological character of the lower river (Table 3).
WATER POLLUTION
Settlement of the Missouri River floodplain was accompanied by discharge of a variety
of pollutants into the river. As early as 1909 increases in typhoid deaths within
towns along the lower Missouri River prompted investigations into the sources of river water
pollution (Ford 1982). Significant water pollution events in the lower Missouri River include
contamination from municipal, industrial, and agricultural sources (Table 1).
Organic pollution from untreated human sewage, the meat packing industry, and
stockyards produces bacterial and viral contamination of drinking water supplies, sludge
deposition, and low dissolved oxygen concentrations resulting in fish kills (Ford 1982). Major
industrial pollutants in the lower Missouri River include petroleum wastes, heavy metals
(primarily mercury), and PCBs from urban industries and the processing of mined ores.
Petroleum contamination has resulted in reports of off flavors in fishes (Ford 1982), and PCB
212
-------
3000
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1000
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PREIMPOUNDMENT
. * TRANSITION
. .. POSTIMPOUNDMENT .
•. I I
1930
1940 1950 1960
YEAR
1970
1980
Fig. 5. Mean annual turbidities (JTUs) of the Missouri River determined from daily
measurements at the St. Louis water-treatment facility. (Source: Pflieger and Grace
1987.)
concentrations in fish tissue have routinely exceeded allowable federal standards (Ford 1982,
Bush and Grace 1989). Levels of PCBs in fishes from the Missouri reach of the Missouri
River, have been declining since their manufacture and use was discontinued in 1979 (Bush
and Grace 1989). Methylation of mercury, its bioaccumulation, and biomagnification in
Missouri River tributaries, the mainstem river, and reservoirs, has created severe
environmental hazards to fish and fish-eating birds and poses a potential threat to human
health (Hesse et al. 1975, Schmulbach et al. 1992).
Concentrations of the agricultural pesticides dieldrin and DDT occasionally violated
lower Missouri River water quality standards during the 1970s (Ford 1982). Violations of
federal standards for dieldrin in fish were reported during the late 1970s (Ford 1982), but were
below advisory levels by the mid 1980s (Bush and Grace 1989). Chlordane is a pesticide
formerly used extensively in the Midwest for termite control in houses. High concentrations in
fish tissue resulted in public health advisories against consumption of selected species and
from specific river reaches in Missouri and Nebraska (Bush and Grace 1989, Christiansen et
al. 1991). Chlordane use was banned in 1988 and fewer fish are currently exceeding unsafe
levels (Bush and Grace 1989). More extensive reviews of these and other contaminants in
213
-------
the lower Missouri River can be found in Ford (1982) and Schmulbach et al. (1992). Water
quality legislation and enforcement requiring permits for point source pollution discharge to
rivers, use of the best available technology to control toxic pollutants, and improved
wastewater treatment for municipalities have done much to improve water quality in the lower
Missouri River (See Table 1 for a summary of important environmental legislation).
FISHES AND FISHERY RESOURCES OF THE LOWER MISSOURI RIVER
The Mississippi River Basin, of which the Missouri River is a major tributary, supports
the richest freshwater fish fauna in North America, about 260 species (Robison 1986).
Freshwater dispersants make up about 88% of these species (Moyle and Cech 1988),
predominantly Cyprinids (30%), Percids (26%), Centrarchids (7%), Catostomids (9%), and
Ictalurids (5%); while diadromous (7%) and freshwater representatives of marine families (5%)
are poorly represented. The Mississippi River Basin was also uniquely important in North
America as a center of fish evolution, as a refuge during times of glaciation from which
species have been able to reoccupy water vacated during glacial advances and as a refuge
of ancient fish faunas (Moyle and Cech 1988). The archaic families Acipenseridae,
Polyodontidae, Lepisosteidae, and Hiodontidae are all extant in the Missouri River Basin.
Hesse et al. (1989a) reviewed the fishes and fisheries of the entire Missouri River
Basin. We will, therefore, concentrate on selected aspects of the lower basin. Ninety-one fish
species have been reported from the mainstem Missouri River, Missouri (Table 6, Grace and
Pflieger 1989). Surveys made at approximately 20-year intervals from 1940 to 1983 in the
Missouri reach were analyzed by Pflieger and Grace (1987) and show an increase in the
number of species collected and substantial changes in their relative abundances. Species
reported to become established or more abundant were mostly pelagic planktivores and
sight-feeding carnivores: skipjack herring, gizzard shad, white bass, bluegill, white crappie,
emerald shiner, and red shiner (see Table 6 for scientific names). These shifts appear related
to decreased turbidity (Fig. 5) and changes in the flow regime following impoundment.
Fishes that declined over the same period included common carp, river carpsucker,
bigmouth buffalo, and two endemic large river species-pallid sturgeon and flathead chub.
The pallid sturgeon was never reported as abundant throughout its range in the
Missouri-Mississippi River Basin (Kallemeyn 1983). However, dangerously low populations
and hybridization with shovelnose sturgeon (Carlson et al. 1985) posed such threats to the
species survival that it was listed in 1990 as endangered under the Endangered Species Act
(Table 7, 16 U.S.C. 1531). Habitat alteration and destruction due to dam construction and
channelization, as summarized in Table 3, are cited as major factors responsible for this
species' decline (Deacon et al. 1979, Kallemeyn 1983, Pallid Sturgeon Recovery Team 1992).
Reported declines in numbers of other mainstem Missouri River fishes in the Nebraska
reach include several large species: paddlefish, sauger, flathead catfish, and blue sucker; in
addition to several chub species: flathead, speckled, sturgeon, sicklefin, and silver (Hesse
and Mestl 1992). Similar reductions in populations of small fishes were reported by Pflieger
and Grace (1987) in the uppermost sections of the Missouri reach, but populations in
lowermost sections of the Missouri reach appear stable or increasing. Populations of two
silvery minnows (western silvery minnow and plains minnow), which typically occur in
backwater habitats, have also declined throughout the lower Missouri River because of
habitat loss (Pflieger and Grace 1987, Hesse and Mestl 1992).
214
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TABLE 6. FISH FAMILIES AND SPECIES OF THE MISSOURI RIVER, MISSOURI, INCLUDING
PRESENT FEDERAL (CANDIDATE FOR LISTING: C2, THREATENED: FT, ENDANGERED: FE) AND
MISSOURI (WATCH LIST: WL, RARE: R, ENDANGERED: SE) STATUS AND IF INTRODUCED (I) TO
THE BASIN. (SOURCES: GRACE AND PFUEGER 1989, MISSOURI DEPARTMENT OF
CONSERVATION 1991)
Family and species Status
Petromyzontidae
Chestnut lamprey, Ichthvomvzon castaneus
Acipenseridae
Lake sturgeon, Acipenser fulvescens C2, SE
Shovelnose sturgeon, Scaphirhvnchus platorynchus
Pallid sturgeon, Scaphirhvnchus albus FE, SE
Polyodontidae
Paddlefish, Polyodon spathula WL
Lepisosteidae
Shortnose gar, Lepisosteus platostomus
Longnose gar, Lepisosteus osseus
Anguillidae
American eel, Anquilla rostrata
Clupeidae
Skipjack herring, Alosa chrvsochloris
Alabama shad, Alosa alabamae R
Gizzard shad, Dorosoma cepedianum
Hiodontidae
Goldeye, Hiodon alosoides
Mooneye, Hiodon tergisus R
Osmeridae
Rainbow smelt, Osmerus mordax I
Esocidae
Northern pike, Esox lucius
Cyprinidae
Common carp, Cyprinus carpio I
Grass carp, Ctenopharyngodon idella I
Bighead carp, Hypophthalmichthvs nobilis I
Silver carp, Hypophthalmichthys molitrix I
Golden shiner, Notemigonus crysoleucas
Creek chub, Semotilus atromaculatus
Silver chub, Hybopsis storeriana
(continued)
215
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TABLE 6. (continued)
Family and species Status
Cyprinidae (continued)
Gravel chub, Hvbopsis x-punctata
Speckled chub, Hvbopsis aestivalis SE
Flathead chub,
Hvbopsis gracilis
Sturgeon chub, Hvbopsis gelida C2, R
Sicklefin chub, Hvbopsis meeki C2, R
Suckermouth minnow, Phenacobius mirabilis
Emerald shiner, Notropis atherinoides
Rosyface shiner, Notropis rubellus
Western redfin shiner, Notropis umbratilis umbratilis
Silverband shiner, Notropis shumardi
Common shiner, Notropis cornutus
Striped shiner, Notropis chrysocephalus
River shiner, Notropis blennius
Bigeye shiner, Notropis boops
Bigmouth shiner, Notropis dorsalis
Spotfin shiner, Notropis spilopterus
Red shiner, Notropis lutrensis
Sand shiner, Notropis stramineus
Channel mimic shiner, Notropis wickliffi
Ghost shiner, Notropis buchanani WL
Brassy minnow, Hvbognathus hankinsoni R
Western silvery minnow, Hvbognathus argyritis
Plains minnow, Hvbognathus placitus
Bluntnose minnow, Pimephales notatus
Fathead minnow, Pimephales promelas
Central stoneroller, Campostoma anomalum
Largescale stoneroller, Campostoma oliqolepis
Catostomidae
Blue sucker, Cycleptus elongatus C2, WL
Bigmouth buffalo, Ictiobus cyprinellus
Black buffalo, Ictiobus niger
Smallmouth buffalo, Ictiobus bubalus
River carpsucker, Carpiodes carpio
Highfin carpsucker, Carpiodes velifer R
Quillback, Carpiodes cyprinus
White sucker, Catostomus commersoni
Northern hog sucker, Hypentelium nigricans
Golden redhorse, Moxostoma erythrurum
Shorthead redhorse, Moxostoma macrolepidotum
Ictaluridae
Black bullhead, Ictalurus melas
Yellow bullhead, Ictalurus natalis
(continued)
216
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TABLE 6. (continued)
Family and species Status
Ictaluridae (continued)
Channel catfish, Ictalurus punctatus
Blue catfish, Ictalurus furcatus
Tadpole madtom, Noturus gyrinus
Freckled madtom, Noturus noctumus
Stonecat, Noturus flavus
Flathead catfish, Pylodictis olivaris
Gadkjae
Burbot, Lota lota
Cyprinodontidae
Blackstripe topminnow, Fundulus notatus
PoecilikJae
Mosquitofish, Gambusia affinis
Atherinidae
Brook sitverside, Labidesthes sicculus
Percichthyidae
White bass, Morone chrvsops I
Striped bass, Morone saxatilis I
Hybrid striper, Morone chrvsops x Morone saxatilis I
Centrarchidae
Spotted bass, Micropterus punctulatus
Smallmouth bass, Micropterus dolomieu
Largemouth bass, Micropterus salmoides
Warmouth, Lepomis gulosus
Green sunfish, Lepomis cyanellus
Orangespotted sunfish, Lepomis humilis
Longear sunfish, Lepomis megalotis
Bluegill, Lepomis macrochirus
Rock bass, Ambloplites rupestris
White crappie, Pomoxis annularis
Black crappie, Pomoxis nigromaculatus
Percidae
Walleye, Stizostedion vrtreum vitreum
Sauger, Stizostedion canadense
Slenderhead darter, Percina phoxocephala
Ozark logperch, Percina caprodes fulvitaenia
Johnny darter, Etheostoma nigrum
Sciaenidae
Freshwater drum, Aplodinotus grunniens
217
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Enrichment of lower Missouri River fish species diversity during the past 40 years
appears due largely to accidental (e.g., Asian carps) and intentional (e.g, rainbow smelt,
Morone spp.) introductions (Table 6), and an increased frequency of species in the
mainstem that are stragglers from tributaries (Pflieger and Grace 1987). Regulation of the
river appears to have reduced environmental constraints on these species.
COMMERCIAL AND RECREATIONAL FISHERY IN THE MISSOURI REACH
Data have been compiled since 1945 by the Missouri Department of Conservation
(Robinson 1992) for the Missouri River, Missouri, on the number of licensed commercial
fishers (determined from permit sales), weight of their reported catches, and amount and type
of gear used. Numbers of commercial fishers gradually decreased from 1948 to 1963,
remained fairly stable through 1969 and then increased to a peak of 1,039 in 1982 (Fig. 6).
Causes for these fluctuations are unknown. However, the subsequent decline in permit sales
TABLE 7. FEDERALLY LISTED CANDIDATE (C1, C2, C3), THREATENED (T) AND
ENDANGERED (E) SPECIES ENDEMIC TO THE MISSOURI RIVER FLOODPLAIN MISSOURI.
(SOURCE: WHITMORE AND KEENLYNE 1990)
Species Status
Plants
Western prairie fringed orchid, Platanthera praeclara T
Insects
American burying beetle (Nicrophorous americanus) E
Regal fritillary butterfly (Speyeria idalia) C2
Six-banded longhorn beetle (Drvobius sexnotatus) C2
Fish
Listings included in Table 6
Reptiles
Alligator snapping turtle (Macroclemys temminckii) C2
Birds
Interior least tern (Sterna antillarum) E
Piping plover (Charadrius melodus) T
Whooping crane (Grus americana) E
Bald eagle, Haliaeetus leucocephalus E
Peregrine falcon, Falco peregrinus E
Swainson's hawk (Buteo swainsoni) C3
Eskimo curlew (Numenius borealis) E
Migrant loggerhead shrike (Lanius migrans) C2
Swallow-tailed kite (Elanoides forficatus) C3
Mammals
Gray bat (Myotis grisescens) E
Indiana bat (Myotis sodalis) E
218
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45 SO 55 60 65 70 75 80 85 90
1945
1950
1955
1960
1965 1970
Years
1975
1980
1985
1990
Fig. 6. Number of commercial fishers from the Missouri River, Missouri, and their reported
harvest of all fish species and catfish species, 1945-1990.
from 1982 to 1988 may be due to increased commercial fishing fees implemented in 1984,
and health advisories issued from 1987 to 1990 warning against consumption of Missouri
River fishes (Robinson 1992). Total harvest first peaked in 1945 at 228 mt, then declined
gradually to 35 mt in 1966, paralleling the decrease in numbers of fishers (Fig. 6). Methods of
estimating annual harvest changed in 1967, yielding a more accurate but higher reported
harvest. Methods of estimating harvest have been constant since 1975 and harvest has
gerierally increased since then, with 1989 and 1990 being the highest years recorded (Fig. 6).
These record harvests occurred despite the dramatic decline in numbers of fishers observed
in the mid 1980s. Reasons for these high catches vary, but include low river water resulting
from a basin-wide drought, increased vulnerability to gear, more accurate reporting of catch,
and lack of concern over successive health warnings (Robinson 1992). The most important
species in the commercial catch are common carp, buffalo fishes, and catfishes. Additional
species contributing to the commercial harvest include: freshwater drum, carpsuckers,
paddlefish, and shovelnose sturgeon.
Catfish harvest, particularly channel catfish, has increased dramatically during the past
10 years (Fig. 6). Concomitantly, there has been a continuous decline in the proportion of
219
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16-r
— Channel Catfish - Flatheod Catfish
1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991
Fig. 7. Percentage of legal length (>381 mm total length) channel and flathead catfishes
captured by 2.5 cm mesh hoopnets (channel catfish) and electrofishing (flathead
catfish) from Missouri River, Missouri, August-November 1990.
legal (>381 mm total length) channel and flathead catfishes in research harvests from
Missouri (Fig. 7) and other states bordering the lower Missouri River. Record high
commercial catfish catches and a shift in population size structure to sublegal lengths implies
overharvest. Consequently, all states bordering the lower Missouri River have recently
prohibited commercial catfish harvest.
An additional impetus for closure of the lower Missouri River commercial catfish fishery
was that most of the commercial harvest was captured by very few fishers while Missouri
River recreational fishing is ranked as the number one public activity on the river (Weithman
and Fleener 1988). Analysis of the number of commercial fishers and their reported harvest
shows that 84% reported total annual catfish catches of less than 230 kg, while only 3%
reported catches over 2000 kg. Nearly 50 and 70% percent of the total 1990 Missouri reach
commercial catfish catch of 132,120 kg was reported by 10 and 25 fishers, respectively (Fig.
8). Weithman and Fleener (1988) estimated recreational fishing on the Missouri reach to be
86,000 days per year (96 visits/km or 3.1 visits/ha) from 1983 to 1985. Seventy percent of this
effort was for catfishes, contributing 57% of the total catch (212,000 fish) and 69% of the total
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14000
12000
10000
in 8000
6000
4000
2000
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 29 24 25
Fisherman Rank
Fig. 8. Rank of the top 25 fishers and their reported total catch of all catfish species from
Missouri River, Missouri, 1990.
fish harvested by the recreational fishery. Net annual economic benefits of recreation were
estimated at $1.9 million and recreational fishing at $660,000 on the Missouri reach. These
totals compare with an estimated net wholesale value of the commercial catch for all species
from the Missouri River of $128,000 in 1987 (Robinson 1989). Future recreational worth of the
Missouri River is perceived by resource professionals as the highest of Missouri's six
watersheds (Bachant et al. 1982). Closure of the lower Missouri River commercial catfish
fishery should allocate a greater proportion of this resource to a larger number of citizens and
yield greater economic benefit to the area.
RESTORATION OF THE LOWER MISSOURI RIVER
Restoration is defined by the National Research Council (1992) as the return of an
ecosystem to a close approximation of its condition prior to disturbance. This definition
necessitates that both ecosystem structure and function be recreated. Merely recreating the
form without the functions, or the functions in an artificial configuration with little resemblance
to the natural river, does not constitute restoration (National Research Council 1992).
Restoration must be conducted as a holistic process at the landscape scale of the river basin.
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It cannot be achieved through isolated manipulation of individual structural or functional
elements or river segments.
The essence of a fluvial system is the dynamic equilibrium of the physical system,
which in turn establishes a dynamic equilibrium in the biological system (National Research
Council 1992). The goal of fluvial restoration, therefore, is reestablishment of this dynamic
equilibrium. The National Research Council's (1992) report on Restoration of
Aquatic Ecosystems lists four general objectives for fluvial restoration that can be applied to
the Missouri, Volga, or any large river. These objectives are:
1. Restore the natural water and sediment regime. Time scales of daily-to-seasonal
variations in water and sediment loads and the annual-to-decadal patterns of floods and
droughts constitute this regime.
2. Restore the natural channel geometry, if restoration of the water and sediment
regime does not.
3. Restore the natural riparian plant community, if the natural plant community does
not restore itself upon completion of objectives 1 and 2.
4. Restore native aquatic plants and animals if they do not recolonize on their own.
Restoring the natural water and sediment regimes and the dynamic equilibrium of the
Missouri and Volga rivers is a tremendous challenge, given their size, present state of
alteration, competing uses for water, existing water and channel control structures, and
floodplain development. However, as acknowledged by the National Research Council
(1992), fluvial restorations are exercises in approximation, and restoration of the Missouri and
Volga rivers will only be successful through compromise among competing interests.
If restoration of the Missouri River is to succeed, the four broad objectives listed above
must be realized. We believe this goal can be accomplished by the groups described below
through coordinating management of all significant ecological elements at a comprehensive
river basin scale, termed integrated aquatic ecosystem restoration (National Research Council
1992). Restoration should include both nonstructural methods (that do not involve physical
alteration or building of structures) as well as traditional structural techniques (National
Research Council 1992), and follow specific approaches recommended by Hesse et al.
(1989a, 1989b), Hesse and Mestl (1992), and Hesse et al. (1992). We summarize these
approaches as six Missouri River restoration objectives and recommend a range of strategies
to attain them.
Objective 1. Reestablish a semblance of the precontrol natural hydrograph
Strategies-
1.1. Hesse and Mestl (1992) suggest timing reservoir releases to emulate the
precontrol hydrologic cycle as a daily percentage of total annual discharge (Fig. 9). They
contend this approach would recreate the timing of the historic March and June rises while
minimizing flooding and incorporate flexibility for drought or wet years.
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1.2. Controlled flooding is necessary to reestablish the river-floodplain linkage and
maintain habitat diversity. True river restoration must take discharge dynamism into account
by allowing enough spatial and temporal scope for flooding to occur (National Research
Council 1992). The capability for controlled flooding through reservoir releases currently
exists.
1.3. Deauthorize irrigation projects of the Pick-Sloan Plan. Water supply in the
Missouri River Basin is insufficient to meet the extensive development envisioned by this plan
and poses the greatest threat to current water uses (Lord et al. 1975).
Objective 2. Reestablish a semblance of the precontrol sediment regime
Strategies-
2.1. Reduce sediment entrapment in reservoirs. Hesse et al. (1989a) and Singh and
Durgunoglu (1991) suggest methods to bypass sediment through reservoirs, which if
implemented or modified for Missouri River reservoirs would benefit the reservoirs by
improving water quality, increasing hydropower potential, and increasing reservoir storage life.
Sediment bypass would benefit the river by reducing downstream channel bed degradation,
providing material for restoration of natural channel geometry and habitats, contributing
sediment and organic matter to downstream reaches, and favoring native turbid-water fishes
over sight-feeding carnivores.
Objective 3. Restore some of the precontrol channel structural diversity and the
river-floodplain linkage
Strategies-
3.1. Accomplish Objectives 1 and 2. This will do much to meet Objective 3.
3.2. Implement a variety of nonstructural floodplain management methods that
promote floodplain restoration, including:
3.2.1. Congressional establishment of U.S. Army Corps of Engineers'
reservoir operating priorities based on economic, environmental, social, and other
benefits to be derived from all authorized project purposes (General Accounting
Office 1992);
3.2.2. Adoption of regulatory floodway zones (Brookes 1988), purchase of
easements to prevent construction in the floodplain, increase land acquisition by
willing purchase, buy out of drainage or levee districts, easements, and fee-title
acquisition;
3.2.3. Support changes in flood damage insurance policies to discourage
continued urban and industrial floodplain development;
3.2.4. Reduce public financial support for private sector economic gain
by allocating maintenance costs of channel regulatory structures to direct
beneficiaries (i.e., navigation companies and drainage and levee districts).
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Jon
Jun Jut
Month
Nov
Dec
Fig. 9. Percentage of annual discharge for the Missouri River at Boonville, Missouri (Rkm
317), by month for the preregulation years 1929-1948. This is an example of
the natural hydrograph approach Hesse and Mestl (1992) advocate to restore the
natural water regime of the lower Missouri River.
3.3. Structural techniques for channel restoration should stress low-cost, low
maintenance soft engineering (recreation of the natural river channel geometry using fluvial
geomorphic principles and locally available materials) over traditional hard hydraulic
engineering approaches which use concrete, rip-rap, and other imported materials and have
high maintenance costs. See Brookes (1988) and National Research Council (1992) for
additional structural techniques.
3.4. Expand the Missouri River Mitigation Project to include the entire length of
existing river channel and mainstem and tributary impoundments, and have it incorporate an
integrated aquatic ecosystem approach to mitigation.
Objective 4. Reestablish and enhance native Missouri River fishes and their migrations
Strategies-
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4.1. Construct fish bypasses or elevators at selected dam barriers.
4.2. Modify reservoir releases of water to provide precontrol thermal cues including
synchronization of river stage-temperature relationships.
4.3. Enhance the present species-centered recovery efforts by incorporating fish
guild/community and habitat based approaches.
4.4. Implement a more equitable balance between management for river recreational
fisheries and native species restoration.
4.5. Implement more restrictive commercial and sport fishery harvest regulations
where populations of native fishes show declining trends (e.g., sauger, blue sucker, and other
species in Nebraska, Hesse et al. 1992).
Objective 5. Reduce or eliminate major point and nonpoint sources of pollution
Strategies-
5.1. Improve enforcement of existing point-source water quality regulations. Establish
long-term goal of upgrading water quality of the lower Missouri River to meet criteria for
whole-body contact.
5.2. Continue to expand governmental support for agricultural land use practices that
reduce soil erosion and crop overproduction and conserve or enhance wetlands (e.g.,
Conservation Reserve and Wetlands Reserve programs).
5.3. Incorporate a multi-level water quality restoration strategy, including elements of
isolation, removal, transfer, and dilution through space and time (Herricks and Osborne 1985).
Objective 6. Reestablish native terrestrial and wetland plant communities along the river
channel and floodplain. including native prairie, wet meadow, bottomland hardwood forests.
sandbar, and sand island successional plant communities and vegetated islands (Hesse et al.
1989a)
Strategies-
6.1. Remnants of native plant communities exist and should become reestablished
upon achievement of Objectives 1 -3.
RESTORATION INITIATIVES AFFECTING THE MISSOURI RIVER
After decades of degradation, there is now a flurry of restoration activity for Missouri
River Basin natural resources. Current initiatives, strategies, and action plans, if implemented,
have the potential to greatly enhance lower Missouri River aquatic resources. We summarize
several of these to illustrate how U.S. governmental and administrative processes operate in
the area of environmental management. Our attention as ecologists is often focused on the
biological details of our disciplines. However, we must be equally cognizant of the policy
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aspects of river management, because it is here that the decisions are made and the money
allocated which enable restoration to occur.
Mississippi Interstate Cooperative Resource Agreement (MICRA)
Large river drainage basins seldom exist within a single political boundary; rather, they
typically are interjurisdictional. Interjurisdictional rivers are defined as crossing or common to
two or more state, provincial, country, etc., boundaries and coming under the shared
jurisdiction of two or more governmental entities. Restoration of interjurisdictional rivers is
hampered by the multiplicity of authorities responsible for their management. The MICRA is
an example of an attempt at a unified approach to restoration of the Mississippi River and its
over 90 interjurisdictional tributaries. Twenty-eight State conservation departments having
fisheries jurisdiction in the Mississippi River drainage system, plus the American Fisheries
Society and U.S. Fish and Wildlife Service (USFWS), have invited other federal, nonfederal,
tribal, and private entities to band together, 'To assess the Mississippi River drainage fishery
resources and habitat requirements to protect, maintain, and enhance interstate fisheries in
the basin" (Rasmussen 1991). The Mission of MICRA is to "Improve the conservation,
development, management, and utilization of interjurisdictional fishery resources in the
Mississippi River Basin through improved coordination and communication among the
responsible management entities" (Rasmussen 1991). MICRA is managed by an interagency
Steering Committee composed of personnel from member states and entities. They
completed a Comprehensive Strategic Plan in August 1991 (Rasmussen 1991) detailing step-
by-step goals and objectives to complete MICRA's mission. Goals set by MICRA are
presented here as an example of a river basin-wide restoration effort.
A. Develop a formal framework and secure funding for basin-wide networking and
coordination mechanisms that complement existing and emerging administrative entities.
B. Develop public information and education programs to disseminate information that
supports fishery resource management in the Mississippi River Basin.
C. Develop an information management program based on standardized methods for
collecting and reporting fishery resource data basin-wide.
D. Determine and document the socio-economic value of fishery resources and
related recreation.
E. Improve communication and coordination among entities responsible for fisheries
resources management in the Mississippi River Basin.
F. Periodically identify and prioritize issues of concern in the Mississippi River Basin
for coordinated research that supports cooperative resource management.
G. Identify and coordinate fishery management programs to address species and
habitat concerns from an ecosystem perspective.
H. Develop compatible regulations and policies for fishery management to achieve
interstate consensus on allocation of fishery resources.
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I. Develop protocols, policies, and regulations for disease control, introduction of
exotics, maintenance of genetic integrity, and maintenance and enhancement of indigenous
species.
J. Preserve, protect, and restore fishery habitats basin-wide.
MICRA is seeking federal funding to accomplish these goals through the Cooperative
Interjurisdictional Rivers Fisheries Resources Act of 1992.
Cooperative Interjurisdictional Rivers Fisheries Resources Act of 1992 (H.R. 4169)
A nationwide consensus is emerging that construction and maintenance of waterway
developments are responsible for much of the decline of large river natural resources in the
U.S, and the public has become increasingly aware of the need for restoration of the river-
riparian ecosystem (National Research Council 1992). Moreover, they recognize that without
demonstrable changes in current management strategies there will be further loss of
large-river fisheries and reduced opportunities for recreational, commercial, subsistence, and
aesthetic uses of our river-floodplain ecosystems. Several programs have been proposed or
are currently underway, including those described herein, to resolve conflicts among
management strategies. The Cooperative Interjurisdictional Rivers Fisheries Resources Act of
1992 was introduced to the U.S. Congress to improve coordination, cooperation, research,
and information sharing at the national level on the variety of present programs to conserve
fisheries resources of major U.S. interjurisdictional rivers.
If approved, this bill will fund and establish for 3 years a Council on Interjurisdictional
Rivers Fisheries (Council) and authorize a pilot test of MICRA. Funds requested include $1
million per year to support Council activities and $2 million per year for MICRA. Membership
on the Council would include high-level representatives of federal and state agencies with
interests in fisheries resources on interjurisdictional rivers. The Council is to develop
strategies on the management of interjurisdictional rivers fisheries. These strategies would
include a) listing the 10 highest-priority interjurisdictional rivers in need of cooperative fisheries
management and b) development of comprehensive fishery strategic plans for the five
highest-priority interjurisdictional rivers identified in a).
The pilot test of MICRA would include nine tasks. Briefly these tasks are
1. Identification and description of each of the river ecosystems in the Mississippi
River Basin and their associated fishery resources and habitat.
2. Identification and description of impacts of, and mitigation for, water and waterway
development projects on fishery resources.
3. Analysis of existing data on regional depletion of important fish stocks and the
potential for their restoration.
4. Identification of major information gaps and technological needs to improve the
cooperative management of interjurisdictional fisheries resources.
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5. A comprehensive study of the status, management, research, and restoration
needs of the interjurisdictional fisheries of the Mississippi River Basin.
6. Development of recommendations for MICRA participants to undertake cooperative
management and research projects.
7. Development of plans and projects for restoration and enhancement of depleted
fish stocks and their habitats.
8. Evaluation of MICRA and the merits of extending such a program to other river
basins in the U.S.
9. Estimates of funds required to implement 6, 7, and 8.
MISSOURI RIVER INITIATIVE
A specific example of a Mississippi River subbasin effort to address management
strategies is the USFWS's proposed Missouri River Partnership or MOR-CARE (Missouri River-
-Conserving a River Ecosystem). The goal of MOR-CARE would be similar to MICRA's, but is
restricted to the Missouri River Basin. MOR-CARE has four draft objectives (Brabander 1992):
1. To facilitate establishment and coordination of an operational Missouri River
environmental research, management, restoration, and enhancement program involving
federal, state, tribal, and local governments and public interest groups.
2. To coordinate the preparation, facilitation, and implementation of a comprehensive
Action Plan for the management, restoration, and enhancement of fish, wildlife, and related
environmental and recreational resources within the Missouri River ecosystem in concert with
existing and future navigation, flood control, and water supply needs.
3. To develop and implement plans for providing fish and wildlife resource-based
recreational opportunities for the people of the Missouri River ecosystem.
4. To establish a functional outreach program to involve and exchange information
with the public concerning problems, opportunities, and resource management and
restoration needs in the Missouri River ecosystem.
MOR-CARE would operate through a Steering Committee organized similarly to
MICRA. This Steering Committee would identify resource management problems and
information needs and establish Working Groups to develop information and alternatives for
problem solution. Products of the Working Groups would be incorporated by the Steering
Committee into a Missouri River Plan of Action. This Plan would include a Cooperative
Agreement for signature by MOR-CARE partners indicating all would agree to utilize their
resources to accomplish the goals of the Plan.
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MISSOURI RIVER FISH AND WILDLIFE MITIGATION
The National Research Council (1992) defines mitigation as, "...actions taken to avoid,
reduce, or compensate for the effects of environmental damage." Possible mitigation actions
include restoration, enhancement, creation, or replacement of damaged ecosystems.
Channelization of the Missouri River directly eliminated 40,591 ha of aquatic habitat
and 151,479 ha of wetlands and terrestrial habitat from the river and its floodplain from Sioux
City, Iowa, to St. Louis, Missouri (Hesse et al. 1989b). The initial attempt to mitigate for these
habitat losses was Section 601 (a) of the Water Resources Development Act of 1986 (PL 99-
662), which authorized the Missouri River Fish and Wildlife Mitigation Project within the states
affected by river channelization (Missouri, Kansas, Iowa and Nebraska).
Estimated cost of the Missouri River Mitigation Project between 1990 and 1999 is
$67.7 million. Funds are to be allocated among four main project elements (USAGE 1992): 1)
48% of requested funds will be for habitat development of 12,100 ha of newly acquired
nonpublic lands and 7,365 ha of existing public lands; 2) 44% will be for acquisition of the
nonpublic lands to provide aquatic and terrestrial habitat for fish and wildlife; 3) 5% will be for
planning, engineering, and design of the project, including 0.4% for baseline evaluation and
monitoring; and 4) 3% will be for construction management.
The Missouri River Mitigation Project will acquire 6.3% of the habitat lost in the original
floodplain (Hesse et al. 1989b), a small beginning toward restoration of the Missouri River
ecosystem. The authorization plan recognizes that restoration of the Missouri River is a long-
term goal rather than short-term objective (Hesse et al. 1989b). This acknowledgment is
important because this first mitigation step displays a piecemeal strategy, an example of,
"...the isolated manipulation of individual elements approach," (National Research Council
1992) and therefore insufficient by itself to achieve restoration.
CONCLUSIONS
Fewer than 200 years have elapsed since Lewis and Clark encountered the abundant
natural resources of the Missouri River Basin. Europeans have a much longer history of river
modification than we in the U.S. Consequently they also are more familiar with river
restoration and we should look to them for guidance (Petts 1984, Brookes 1988, Dodge
1989). The days of the truly Big Muddy are history. Missouri River restoration should be
directed toward reestablishment of a basin-wide dynamic equilibrium and maintenance of
natural functions and characteristics, albeit in a more limited scope.
Missouri River mitigation does not yet embody this holistic view toward restoration of
the structural and functional attributes of the unaltered river on the landscape scale of the
entire basin. This is not to say that current small-scale restoration efforts are ineffective.
However, success in recreating a self-sustaining Missouri River ecosystem is more probable if
individual mitigation and restoration projects are planned within the context of the basin
landscape. Decisions about restoration and management of aquatic resources should not be
made on a small-scale, short-term, site-by-site basis, but should be made to promote the
long-term sustainability of all aquatic resources (National Research Council 1992). The task
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of such groups as the Council on Interjurisdictional Rivers Fisheries, MICRA and MOR-CARE's
Steering Committee will be to provide this perspective.
ACKNOWLEDGMENTS
Views expressed in this paper reflect the opinions of the authors and do not
necessarily represent policies of their agencies. We thank J. Brabander, J. Bush, G. Farabee,
K. Keenlyne, M. LaValley, W. Pflieger, J. Rasmussen, R. Sparks, and N. Stucky for reviewing
this manuscript. Dennis Figg, Missouri Department of Conservation (MDC), provided
information on federal listings of Missouri River biota. Brenda Gary, MDC prepared some of
the figures; and Sandy Clark, Missouri Cooperative Fish and Wildlife Research Unit, edited the
manuscript. This is a contribution from the Missouri Cooperative Fish and Wildlife Research
Unit (U.S. Fish and Wildlife Service, Missouri Department of Conservation, University of
Missouri, and Wildlife Management Institute cooperating).
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HYDROLOGIC MODIFICATION TO IMPROVE HABITAT
IN RIVERINE LAKES: MANAGEMENT OBJECTIVES.
EXPERIMENTAL APPROACH. AND INITIAL CONDITIONS
by
Barry L Johnson1, John W. Barko2'4, Yuri Gerasimov3,
William F. James4, Alexander Litvinov3, Teresa J. Naimo1,
James G. Wiener1, Robert F. Gaugush2,
James T. Rogala2, and Sara J. Rogers2
ABSTRACT
The Finger Lakes habitat-rehabilitation project is intended to improve
physical and chemical conditions for fish in six connected backwater lakes in Navigation Pool 5 of the
upper Missouri River. The primary management objective is to improve water temperature, dissolved
oxygen concentration, and current velocity during winter for bluegills, Lepomis macrochirus, and black
crappies, Pomoxis nigromaculatus, two of the primary sport fishes in the lakes. The lakes will be
hydrologically altered by installing culverts to introduce controlled flows of oxygenated water into four
lakes, and an existing unregulated culvert on a fifth lake will be equipped with a control gate to regulate
inflow. These habitat modifications constitute a manipulative field experiment that will compare pre-
project (1991 to summer 1993) and post-project (fall 1993 to 1996) conditions in the lakes, including
hydrology, chemistry, rooted vegetation, and fish and macroinvertebrate communities. Initial data
indicate that the Finger Lakes differ in water chemistry, hydrology, and macrophyte abundance.
Macroinvertebrate communities also differed among lakes; species diversity was highest in lakes with
dense aquatic macrophytes. The system seems to support a single fish community, although some
species concentrated in individual lakes at different times. The introduction of similar flows into five of
the lakes will probably reduce the existing physical and chemical differences among lakes. However,
our ability to predict the effects of hydrologic modification on fish populations is limited by uncertainties
concerning both the interactions of temperature, oxygen, and current in winter and the biological
responses of primary and secondary producers. Results from this study should provide guidance for
similar habitat-rehabilitation projects in large rivers.
National Fisheries Research Center, U.S. Fish and Wildlife Service, P.O. Box 818, La Crosse, Wl
54602, USA
Environmental Management and Technical Center, 575 Lester Drive, Onalaska, Wl 54650, USA
Institute of Biology of Inland Waters, Russian Academy of Sciences, Borok, Nekuzkyi Raion,
Yaroslavskaya Obi. 152742, Russia
4Eau Galle Limnological Laboratory, Waterways Experiment Station, U.S. Army Corps of
Engineers, P.O. Box 237, Spring Valley, Wl 54767, USA
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INTRODUCTION
Large rivers are diverse, dynamic ecosystems that are heavily affected by human
activities (Hynes 1989). Yet information on the structure and function of large riverine
ecosystems, needed to establish effective management and rehabilitation policies, is scant
(Regier et al. 1989; Ward and Stanford 1989). In addition, few of the potential management
approaches for large rivers have been critically evaluated (Petts et al. 1989).
The Mississippi River is the largest river in North America and one of the world's major
rivers in size, physical diversity, and biotic productivity (Fremling and Claflin 1984; Fremling
et al. 1989). The upper Mississippi River extends 1078 km from St. Anthony Falls,
Minnesota, to the confluence with the Ohio River. In the 1930s, the upper Mississippi River
was divided by a series of locks and dams into 29 navigation pools to enhance commercial
navigation (a navigation pool is the reach between two consecutive locks and dams). The
upstream portions of many navigation pools contain multiple channels characteristic of the
unimpounded river, whereas the downstream reaches are similar to reservoirs. This
impounded river contains large areas of diverse habitats that support economically
important sport fisheries (Fremling et al. 1989).
Man's activities have adversely affected the quality of the riverine environment. Much of
the watershed of the upper Mississippi is intensively cultivated, and many tributary streams
deliver substantial loads of nutrients, pesticides, and sediment from eroding farmland. This
sediment accumulates in quiescent riverine lakes and backwaters and in Impounded areas
behind dams (McHenry et al. 1984) - all important habitats for fish. Substantial loadings of
point-source pollutants are discharged into the river from bordering Industrialized
metropolitan areas. For example, organic pollution depleted dissolved oxygen in 100 km of
river below metropolitan Minneapolis-St. Paul, Minnesota, for several decades (Fremling
1964; Fremling and Johnson 1990). Water quality in this reach improved since the late
1970s, because of better treatment of wastewater in the metropolitan area. Yet the river is
still a nutrient-enriched, eutrophic system, where fish are occasionally affected by oxygen
depletion in both winter and summer (Bodensteiner and Lewis 1992).
Federal and state resource-management agencies have initiated several rehabilitation
and enhancement projects to improve certain degraded riverine habitats for fish and wildlife
as one component of the Environmental Management Program for the Upper Mississippi
River System. In this paper, we describe the Finger Lakes Project, a habitat-rehabilitation
project intended to improve water quality for fish in a series of backwater lakes. We present
the management objectives of the project and outline the experimental approach used to
evaluate the limnologic, population, and community responses to hydrologic modification of
the lakes. Last, we summarize baseline information on the initial physical and chemical
conditions and biotic communities (rooted vegetation, fish, and benthic macrolnvertebrates)
in the lakes during summer and fall 1991.
MANAGEMENT OBJECTIVES
The Finger Lakes system near Kellogg, Minnesota, contains six connected Jakes (Gear,
Lower Peterson, Schmokers, Third, Second, and First) in Navigation Pool 5 of the upper
Mississippi River, just below the dike at Lock and Dam 4 (Figure 1). Some of these shallow,
240
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PETERSON LAKE (POOL 4)
SPILLWAY
LOWER
PETERSON
LAKE
OUTLET CHANNEL
Location of Study Area
FIGURE 1. Map of the Finger Lakes study area in Pool 5 of the upper Mississippi River near
Kellogg, Minnesota, USA (star on inset map), at an elevation of 201.2 m above
mean sea level, showing depth contours (0.5-m intervals), water sampling
stations (•), and distribution of aquatic macrophytes (cross-hatched areas)
during summer 1991.
241
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eutrophic lakes have periodically undergone oxygen depletion In winter and summer
(Grunwald 1977), which reduces their suitability for fish. A culvert through the dike allows
flow into Lower Peterson Lake from Upper Peterson Lake, which Is part of the impoundment
behind Lock and Dam 4. A mean flow of 2.3 m3/s through the culvert provides sufficient
dissolved oxygen to Lower Peterson and Schmokers lakes for fish, but reduces water
temperatures in winter to near 0°C. Many sport fishes in the upper Mississippi River are
intolerant of such low temperatures, particularly in the presence of flow (Sheehan et al.
1990). At normal pool elevation, all six lakes drain through a common outlet to the main
channel of the Mississippi River (Figure 1).
The primary management objective of the Finger Lakes Project is to provide suitable
water temperature, dissolved oxygen concentration, and current velocity in winter for
bluegills and black crappies the two primary sport fishes in the lakes. To achieve these
objectives, the culvert on Lower Peterson Lake will be equipped with a control gate to
regulate flow, and culverts will be installed to introduce and regulate flow into Clear, First,
Second, and Third lakes.
The principal objectives of our research are to determine (1) the response of the Finger
Lakes ecosystem to these hydrologic modifications, and (2) the flow rates that will optimize
winter temperature, dissolved oxygen concentration, and current velocity in these lakes for
bluegills and black crappies. We consider the habitat modifications to be a manipulative
field experiment that will entail comparisons of the pre-project and post-project status of lake
hydrology, lake chemistry, rooted vegetation, fishes, and benthic macroinvertebrates. The
study began in 1991 and will continue through 1996. Results from this study should provide
guidance for other habitat-rehabilitation projects on the river.
EXPERIMENTAL APPROACH
HYDROLOGIC MODIFICATION
Three new culverts will be installed through the dike of Lock and Dam 4 in 1992 and will
become operational by summer 1993. Two culverts, each 0.9 m in diameter, will provide
flow to Clear and Third lakes. A third culvert, 1.2 m in diameter, will provide flow to both
Second and Rrst lakes through a junction box. Gates for controlling flow will be installed on
the Inlets of each new culvert, on the existing culvert in Lower Peterson Lake, and on the
junction box.
Operation of the culverts and determination of their flow rates will be based on the
oxygen deficit of each lake. Preliminary estimates, based on lake morphometries and
limited chemical data, indicated that flow rates averaging about 0.8 m3/s for Lower Peterson
Lake and 0.2 to 0.3 m3/s for other lakes should maintain dissolved oxygen concentrations of
at least 5 mg/L in winter (U.S. Army Corps of Engineers, St. Paul, Minnesota, unpublished
data). Total inflow through all culverts would average about 1.7 m3/s for the entire system,
which is less than the 2.3 m3/s that now flows into Lower Peterson Lake.
242
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PHYS1COCHEMICAL
Annual water budgets will be modeled with the following mass-balance equation:
(1) culvert + groundwater + dike = channel + evaporation.
Inflow inflow seepage outflow
Inflow and outflow will be monitored every 2 weeks from August 1991 through
September 1996. Evaporative losses will be estimated from weather data. The sum of
groundwater Inflow and seepage through the dike will be estimated by difference.
We will determine flow patterns and water exchange rates within the system from the
movement of a fluorescent dye injected into the water. Dye studies will be conducted
before the installation of the culverts (winter 1991-1992) and again during culvert operation
(winter 1994-1995) under conditions of similar river discharge and water elevation.
We will sample water at two stations in each lake (Figure 1), at weekly intervals during
ice-free periods, and less frequently during ice cover. At each station, Secchi disk
transparency will be measured, and depth profiles of temperature, dissolved oxygen, pH,
and conductivity will be determined jnjjtu. Water samples collected at depths of 0.1 m
below the surface and 0.1 m above the sediment-water interface at each station will be
analyzed for alkalinity, seston dry mass, paniculate organic matter, dissolved organic
carbon, total and dissolved nitrogen, ammonia-nitrogen, total and dissolved phosphorus,
soluble-reactive phosphorus, dissolved iron, dissolved manganese, chlorophyll, and
phaeopigments.
VEGETATION
We will survey and map aquatic vegetation annually with a combination of transect
sampling, visual surveys, and aerial photography. Transects will be established at 50-m
intervals across each lake. At 10-m intervals along each transect, plants will be sampled
with a plant rake to estimate the relative density of plant species within a 1-m radius. In the
area between transects, vegetation beds larger than 5 m in diameter will be visually
surveyed to determine species composition and bed size. Aerial photographs (scale
1:15,000) taken In August of each year will be used to map the extent of vegetation beds
identified In field surveys.
MACROINVERTEBRATES
Macroinvertebrates will be sampled from Clear, Lower Peterson, and Third lakes to
determine taxonomic composition, density, and biomass. Sampling will be conducted twice
annually, in April or May (coinciding with minimum macrophyte abundance) and in August
(coinciding with maximum macrophyte abundance). In each lake, a maximum of 15 sample
sites will be randomly selected in each of three habitats: benthic substrate in non-vegetated
areas, benthic substrate under vegetation, and vegetation. Three samples will be collected
at each site. Substrates will be sampled with a ponar grab (0.0225 m2) and washed through
a 595-pim mesh sieve. Macroinvertebrates associated with vegetation will be sampled by
243
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cutting a standard length of non-branching stem (50 cm for Nuphar. Nvmphaea. and
Nelumbo: 25 cm for other plant species) from the uppermost portion of five plants of the
predominant species at a site. Ail samples will be preserved in 10% formalin.
FISH
We will describe the fish community of the lakes and the population biology of three
target species (blueglll, black crappie, and largemouth bass Mlcropterus salmoldes) before
and after culvert operation. Population and community characteristics will be assessed in
relation to habitat features both within lakes and among lakes. Second Lake will not be
routinely studied because access to the lake is restricted for both fish and investigators.
Standardized sampling will be done in each lake with fyke nets and electrofishing during
spring, summer, and fall (Nielsen and Johnson 1983) to determine community composition
and the relative abundance of fish species. Target species will be measured and weighed,
and scale samples for age estimation and back-calculation of growth will be taken in spring.
Diets of each target species will be described by analyzing stomach contents from fish
captured seasonally. Age 1 and older fish of each target species will be fin-clipped for
mark-recapture population estimates. Age 2 and older fish of each target species
(approximated by total lengths of at least 150 mm for biuegills, 170 mm for black crappies,
arid 200 mm for largemouth bass) will be tagged with individually numbered anchor tags.
Anglers will be surveyed in winter to estimate fishing effort and harvest. The survival rates of
target species will be estimated directly from spring and fall mark-recapture studies and also
from the return rate of tagged fish (Ricker 1975; Burnham et al. 1987).
Movements of fish within the Finger Lakes will be determined in part by the locations of
recaptured, tagged fish caught by anglers and during our sampling. Fyke nets will also be
set in the outlet channel during spring, summer, and fall to determine rates of immigration
and emigration for the system.
The effect of habitat modification on the movement of biuegills and black crappies will
be further examined in two radio-telemetry studies - both in winter -one before and one
after installation of the culverts. Radio transmitters will be implanted in 20 biuegills and 20
black crappies during each study. Fish will be located at least weekly, and dissolved
oxygen concentration, temperature, and current velocity will be measured at each fish's
location.
DATA MANAGEMENT
We will determine spatial coordinates based on the Universal Transverse Mercator
System for all sample points and transects, and will develop Geographic Information System
(GIS) data bases for both the pre- and post-modification periods. These data bases can be
combined to determine the distribution of habitat features over Jime. GIS maps will be
developed to examine both spatial and temporal changes in habitat and fish populations.
These spatial analyses will complement traditional statistical analyses, and will help to
identify spatial patterns and the relations between changes in habitats and biota.
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INITIAL CONDITIONS
Data from the first sampling period of this study were collected in late summer and fall
In 1991 and are summarized herein.
MORPHOMETRY
A bathymetric survey conducted in July 1991 provided morphometric information for the
lakes (Table 1). The total surface area of the Finger Lakes system is 100 ha; individual lakes
range in area from 8 to 19 ha. Lower Peterson Lake is generally deeper (mean depth 1.2 m;
maximum, 4.3 m near the culvert) than the other lakes, whose mean depths ranged from 0.6
to 0.9 m and whose maximum depths ranged from about 1 to 2 m. The only shoreline
development in the system consists of 25 houses and a boat ramp, all located on the
western shore of Clear Lake.
HYDROLOGY
At present, the hydrology of the Finger Lakes depends primarily on the inflow through
the culvert into Lower Peterson Lake and on outflow through the outlet channel. Pool
elevations in Upper Peterson Lake are nearly constant at 203.1 m above mean sea level,
except during spring floods, and have never exceeded 206.8 m, the level needed to overflow
the dike. Therefore, the flow rate through the culvert is primarily controlled by the elevation
of the Mississippi River in the tailwater below Lock and Dam 4, which is determined by
discharge through the dam. Inflow through the culvert remains at about 2.3 m3/s at
dam-discharge rates up to 1,700 m3/s. Higher dam-discharge rates raise tailwater
elevations, reducing flow through the culvert to a minimum of about 1 m3/s. Discharges
through Lock and Dam 4 exceed 1,700 m3/s only about 10% of the time, primarily during
spring floods; thus, flow through the culvert does not vary widely during the year.
During late summer and fall 1991, the volume and surface elevation of the Finger Lakes
was closely correlated with elevation of the Lock and Dam 4 tailwaters (Figure 2A) and was
regulated primarily by flow through the outlet channel. Inflow through the culvert and
outflow through the outlet channel were similar (Figure 2B) except in mid-September, when
increased discharge through Lock and Dam 4 raised the tailwater; this increase reversed the
direction of flow through the outlet channel (negative value in Figure 2B), increasing the
volume of the lakes. A rapid decrease in tailwater elevation in late September produced
large outflows, rapidly decreasing lake volume.
PHYSICOCHEMICAL
Mean physicochemical characteristics varied among lakes during late summer and fall
1991 (Table 2). We present only data collected from 0.1 m below the surface because
values from 0.1 m below the surface and 0.1 m above the sediment-water interface were
similar within lakes, except as noted.
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TABLE 1. MORPHOLOGY OF THE FINGER LAKES, MINNESOTA, AT A WATER SURFACE
ELEVATION OF 201.2 M ABOVE MEAN SEA LEVEL
Lake
Clear
Lower Peterson
Schmokers
Third
First
Outlet channel
(including bays)
Total system
Mean
depth
(m)
0.8
1.2
0.9
0.6
0.6
0.6
Maximum
depth
(m)
1.4
4.3
1.3
2.0
1.1
1.7
Surface
area
(ha)
10
8
19
15
10
8
100*
Volume
(1000 m3)
84
94
164
95
56
49
542
'Includes 30 ha of surface area in isolated lakes, contiguous ponds, and wetlands.
246
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40
o
x
£ 35
0)
E
o
30
Volume
*
Tailwoter Elevation /M-,
202
201.5
c
O
"-*->
o
_a>
LJ
August
September
Month
October
0
to
2:
0
6
5
4
£ 0
-1
-2
Inflow
1
August
September
Month
October
FIGURE 2. Hydrologic characteristics of the Finger Lakes, Minnesota, during August
through October 1991. (A) Volume of the Finger Lakes and elevation (meters
above mean sea level) of the tailwaters of Lock and Dam 4. (B) Inflow from the
culvert in Lower Peterson Lake and outflow through the Finger Lakes outlet
channel.
247
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TABLE 2. MEAN VALUES (RANGE IN PARENTHESES) FOR SELECTED PHYSICOCHEMICAL
CHARACTERISTICS OF THE FINGER LAKES, MINNESOTA, MEASURED OR SAMPLED AT 0.1 M BELOW THE
WATER SURFACE. MEANS WERE CALCULATED FROM DATA FROM TWO SAMPLING LOCATIONS PER
LAKE ON 10 SAMPLING DATES DURING AUGUST THROUGH OCTOBER, 1991 (N = 20 PER LAKE).
Variable
Temperature, °C
Dissolved oxygen,
mg/L
Conductivity,
pS/cm
PH
Alkalinity,
mg/L (as CaCO3)
Seston, mg/L
Paniculate organic
matter, mg/L
Dissolved organic
carbon, mg/L
Ammonia-nitrogen,
mg/L
Chlorophyll,
mg/m3
Gear
15.0
(6.4-24.6)
8.9
(5.5-12.4)
303
(282-341)
7.8
(7.2-8.5)
143
(133-150)
39.6
(11.7-71.9)
13.4
(9.1-21.3)
19.9
(8.0-29.2)
0.08
(0.01-0.69)
79.0
(32.1-150)
Lower
Peterson
16.3
(9.0-24.6)
9.0
(6.4-11.8)
467
(399-521)
8.0
(7.6-8.4)
173
(153-189)
12.0
(7.0-18.7)
3.1
(0.7-5.2)
25.0
(17.9-30.1)
0.05
(0.01-0.2)
13.9
(5.6-33.2)
Lake
Schmokers
16.3
(8.1-25.3)
9.3
(6.8-11.9)
467
(395-561)
8.0
(7.8-8.5)
171
(151-184)
21.8
(6.9-58.7)
4.9
(2.5-15.2)
25.1
(14.6-29.3)
0.05
(0.01-0.11)
20.0
(10.7-45.4)
Third
15.4
(7.8-24.4)
7.3
(4.4-10.6)
392
(367-452)
7.4
(7.1-7.8)
194
(177-208)
10.4
(4.6-22.2)
4.5
(1.4-13.2)
21.3
(13.0-30.9)
0.18
(0.01-0.5)
26.0
(2.1-76.2)
First
16.6
(7.9-27.1)
10.6
(7.3-17.8)
432
(366-519)
8.1
(7.7-8.9)
173
(154-181)
31.9
(8.3-64.6)
7.9
(2.7-18.9)
24.3
(11.3-30.1)
0.07
(0.01-0.41)
43.4
(14.4-114)
248
-------
Mean water temperatures were similar among lakes, which indicates that inflow to
Lower Peterson Lake had little effect on temperature during summer and fall 1991.
Conductivity, pH, alkalinity, and dissolved organic carbon were similar among Lower
Peterson, Schmokers, and First lakes, but differed from values in Clear and Third lakes.
These data suggest that flow from the culvert into Lower Peterson Lake moved directly
through Schmokers Lake to the system outflow, with little water entering Third and Clear
lakes. Conductivity, alkalinity, and temperature were lowest in Clear Lake, probably because
of the influence of groundwater inputs. Mean and minimum dissolved oxygen
concentrations were lowest in Third Lake, the only lake that exhibited temperature and
oxygen stratification during summer 1991. Minimum dissolved oxygen concentrations
approached zero in the hypolimnion of Third Lake, and were associated with high
concentrations of ammonia-nitrogen. Lower Peterson Lake, the deepest lake, did not
stratify, probably because of mixing caused by inflow from the culvert.
Mean concentrations of seston, paniculate organic matter, and chlorophyll were highest
in Clear Lake, which suggests higher primary productivity than in the other lakes (Table 2).
In contrast, concentrations of these biogenic components were generally lowest in Lower
Peterson Lake, but progressively higher In Schmokers and First lakes. These data indicate
that phytoplankton production increases from the inflow to the outflow and suggest that
there was a net export of biogenic matter from the system.
VEGETATION
Eleven species of submersed and floating-leaved aquatic vegetation were found in the
Finger Lakes (Table 3). Based on our samples and on aerial photographs taken in 1991,
Third Lake was the most heavily vegetated and dear Lake the most sparsely vegetated of
the Finger Lakes (Figure 1). Nelumbo was the most common macrophyte in Clear Lake,
whereas some combination of Ceratophvllum. Myriophyllum. and Nymphaea dominated in
the other lakes. Plant beds generally occurred in strips near shorelines. In First and Third
lakes, the upper third of each lake and most protected bays contained dense beds of
Ceratophvllum and often contained the free-floating macrophyte, duckweed (Lemna spp.).
Beds of Mvriophyllum existed offshore in Schmokers Lake, and small beds of Nelumbo were
found in Lower Peterson, Schmokers, and Gear lakes. The other six plant species were
rare.
MACROINVERTEBRATES
We collected 276 samples of macroinvertebrates from three of the Finger Lakes in
August 1991. Based on initial analyses of about 10% of the samples from each lake and
habitat type, the benthos were dominated by digochaetes, followed by chironomids, and in
Third Lake, by the amphipod Hyalella azteca (Table 4). Amphipods and chironomids were
the dominant macroinvertebrates on vegetation. Odonate larvae, primarily Enallaama spp.,
were common on vegetation but rare elsewhere. Bivalve molluscs were common in
sediments from non-vegetated areas of Lower Peterson Lake. Diversity of
macroinvertebrates was highest in Third Lake, which had 26 taxa (Table 4). Densities of
macroinvertebrates in vegetated areas (benthic plus plant-associated) were higher than in
249
-------
TABLE 3. FREQUENCY OF OCCURRENCE (PERCENT OF SITES CONTAINING THE
SPECIES) OF SUBMERSED AND FLOATING-LEAFED AQUATIC PLANTS IN THE
FINGER LAKES, MINNESOTA, IN AUGUST 1991. "P" INDICATES THAT THE PLANT
WAS PRESENT IN THE LAKE, BUT NOT SAMPLED ON TRANSECTS.
Lake
Species
Ceratophytlum
demersum
Vallisneria
americana
Myriophvllum so.
Elodea
canadensis
Najas
flexHis
Potamoqeton
americanus
Potamoqeton
zosteriformls
Potamoqeton
crispus
Heteranthera
dubia
Netumbo
lutea
Nymphaea
tuberosa
Nuphar
tuteum
Lemnaspp.
Clear
0
0
0
0
0
0
0
0
0
P
P
0
0
Lower
Peterson Schmokers
Submersed plants
23
10
20
4
0
P
4
0
0
Floating-leafed plants
11
25
P
0
16
0
38
0
P
3
0
0
3
P
9
0
0
Third
92
0
0
2
0
P
0
0
0
0
38
P
P
First
45
0
7
1
0
4
0
2
0
0
9
0
P
250
-------
TABLE 4. TAXONOMIC LIST AND RELATIVE PERCENTAGE BY NUMBER OF MACROINVERTEBRATES IN
THREE HABITAT TYPES (V = ON VEGETATION, S = SUBSTRATES UNDER VEGETATION, N = SUBSTRATES
IN NON-VEGETATED AREAS) IN CLEAR, LOWER PETERSON, AND THIRD LAKES IN AUGUST 1991.
Macroinvertebrate
taxon
Class Ollgochaeta
Class Crustacea
Order Isopoda
Caecidotea
Order Amphipoda
Hyalella azteca
Class Arachnoidea
Hygrobates
Umnesla
Neumanla
Class Bivalvia
Family Sphaeriidae
Family Unionidae
Class Insecta
Order Diptera
Family Chironomidae
Family Ceratopogonidae
Family Psychodidae
Family ChaoborkJae
Chaoborus
Order Odonata
Suborder Zygoptera
Enallagma
Order Coleoptera
Order Ephemeroptera
Caenls
Miscellaneous taxa
Number of samples
Mean number
per sample
Clear Lake
V
0
0
0
0
0
0
0
0
100
0
0
0
0
0
0
0
0
1
8
S
91
0
0
0
1
0
0
0
4
3
0
0
0
0
0
0
2
2
69
N
95
0
0
0
1
0
0
0
0
1
0
2
0
0
0
1
0
10
34
Lower Peterson
Lake
V
5
0
43
0
0
0
0
0
37
1
0
0
0
11
1
3
0
3
59
S
48
3
2
0
1
0
0
0
38
0
0
0
1
0
2
3
3
2
93
N
32
0
0
4
0
0
18
7
29
7
0
0
0
0
0
4
0
2
14
Third Lake
V
12
1
41
0
0
0
0
0
24
0
0
0
1
7
1
2
11
4
73
S
69
6
2
0
1
2
2
0
12
0
1
1
1
0
0
0
4
4
44
N
53
0
37
0
0
2
0
0
4
0
0
1
0
0
0
1
2
3
70
251
-------
non-vegetated areas. All macroinvertebrate communities were dominated by small
organisms, which suggests Intensive, size-selective predatlon by fish.
FISH
The fish assemblage of the Finger Lakes (Table 5) was typical of Upper Mississippi River
backwaters. In summer, bluegills and black crappies dominated the catch In all lakes,
followed by catostomids. Catch rates for bluegllls and black crappies were highest In Lower
Peterson Lake. In fall, catch rates increased in most lakes because age-0 fish were large
enough by then to be caught in fyke nets (Table 5). Bluegills and black crappies were
concentrated In Third and First lakes. Catches hi Clear, Lower Peterson, and Schmokers
lakes were dominated by young-of-the-year white bass Morone chrvsops and gizzard shad
Dorosoma cepedianum.
These data agree with population estimates for age-1 and older fish in fall 1991, which
showed that numbers and densities of bluegills and black crappies were greatest in Third
Lake (Table 6). Largemouth bass, the primary plscivore in the system, are less vulnerable to
fyke nets, but population estimates indicated that largemouth bass were concentrated in
Lower Peterson Lake (Table 6).
Tag returns from anglers indicated that fish moved freely within the Finger Lakes
system, and that few fish left the system. Through 31 March 1992, 49% of the 125 bluegill
tags and 58% of the 73 black crappie tags received from anglers were from fish recaptured
in a lake other than that where they were tagged. Only two bluegills and four black
crappies, representing only 3% of all tag returns, were recaptured outside the Finger Lakes
system. These initial data suggest that the Finger Lakes system forms a spatial boundary
for populations of bluegill and black crappie, but that these populations are not confined to
individual lakes within the system.
Preliminary analysis of stomach contents from fish sampled in fall 1991 showed that
both bluegills and black crappies fed mainly on macroinvertebrates, mostly amphipods and
dipterans. Zooplankton were important in the diets of young-of-the-year fishes. Adult black
crappies occasionally ate fish, primarily gizzard shad and Lepomis spp. Largemouth bass
consumed mostly gizzard shad. Lepomis spp.. and darters Etheostoma. but smaller bass
also ate macroinvertebrates.
CONCLUSIONS AND UNCERTAINTIES
Initial data Indicate that the Finger Lakes differ in water chemistry, hydrology, and
macrophyte abundance. Clear Lake had the highest chlorophyll concentrations, probably
received groundwater inputs with lower conductivity, and had few aquatic macrophytes.
Lower Peterson and Schmokers lakes, which were heavily influenced by inflow from the
culvert, were both low in chlorophyll and paniculate organic matter, had high conductivity,
and had moderate production of aquatic macrophytes. Third Lake, which was intermediate
in physicochemical characteristics, contained dense aquatic macrophytes, and exhibited
oxygen depletion during summer. The upper portion of First Lake was similar to Third Lake,
but the lower portion, near the system outlet, was influenced by flow from the culvert and
252
-------
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exhibited characteristics similar to Schmokers Lake. Macro-invertebrate communities differed
among lakes, with aquatic macrophytes providing an important substrate for colonization.
The macroinvertebrate community was most diverse in Third Lake, where macrophytes were
most dense, but was composed almost exclusively of chironomids and oligochaetes in dear
Lake, where macrophytes were sparse. The Finger Lakes system appears to have a single
fish community, although some species concentrate in individual lakes at different times.
The extensive data base collected during the pre-culvert studies should allow us to
estimate optimal temperature, dissolved oxygen concentration, and current velocity, and to
then re-estimate the inflows needed to achieve optimal conditions in each lake. Although
the estimated inflows may change, the flow regime after culvert installation will presumably
involve simitar, low rates of inflow to each lake. Lower Peterson and Schmokers lakes will
have reduced flows relative to present conditions, whereas flows will increase in the other
lakes. Total inflow to the system should be near or below present levels.
Responses of the system to modification in the flow regime are presently difficult to
predict, particularly for the fish populations. Fish may respond to changes in habitat, trophic
dynamics, or species interactions through altered survival, growth, reproduction, or
emigration. Changes in any of these fish-population variables could affect the relative
abundance of species and the community composition of fishes.
The introduction of similar, low flows into each lake will probably reduce the
physicochemical differences among lakes that existed in 1991. Inflow may eliminate anoxia
in summer and increase available habitat for fish and macroinvertebrates. Winter oxygen
concentrations can be increased by introduced flows, improving habitat for aquatic biota,
but this could also decrease water temperature and increase current velocity, which could
be stressful to certain fishes - including our target species (Sheehan et al. 1990;
Bodensteiner and Lewis 1992). Consequently, the flow rates needed to create optimal
winter conditions for Wuegills and black crappies must be accurately determined.
Increased flows could affect the production of macrophytes in various ways. Physical
disturbance caused by flows may eliminate macrophytes in some areas, particularly near the
mouths of the culverts. Changes in transparency can modify the depth of the photic zone,
but it is difficult to predict how increased flow will alter transparency. Increased inflow may
reduce transparency by increasing the concentration of suspended solids or by stimulating
phytoplankton production. Conversely, increased flow may increase transparency by
flushing phytoplankton, suspended solids, and non-rooted aquatic plants, such as duckweed
and Ceratophyllum. from the system. Changes in vegetation abundance may affect
spawning and nursery habitat for many fish species.
Fish populations in the Finger Lakes may be indirectly affected by trophic changes. The
food of target fishes seems to consist primarily of macroinvertebrates. Increased oxygen
concentrations in winter may improve the over-winter survival of macroinvertebrates, thereby
increasing the food supply for target fishes. Population densities of macroinvertebrates
seem strongly related to the abundance of aquatic plants; thus, changes in aquatic
macrophytes could greatly influence the food chain supporting key fishes.
Our ability to predict the effects of hydrologic modification on fish populations is limited
by uncertainties in the physical responses of the Finger Lakes system, particularly the
255
-------
interactions of temperature, dissolved oxygen, and current velocity in winter, and by
uncertainties in the responses of primary and secondary producers. The ability to regulate
flows should allow us to reduce undesirable responses and to determine appropriate inflows
for each lake that will optimize the quality of habitat across the system as a whole.
The response of this system to a modified hydraulic regime could not be predicted from
controlled laboratory experiments because of the size and complexity of the system.
Questions about systems of this size can best be answered when management programs
are treated as large-scale field experiments whose results are carefully evaluated (Walters
1986). Results from this project should yield hypotheses concerning the responses of
backwater systems to modified flows which can be used to develop new management
strategies for similar ecosystems.
ACKNOWLEDGMENTS
We thank the Minnesota Department of Natural Resources, especially Mike Davis and Al
Stevens, for field assistance, manuscript review, and cooperation in all aspects of this study.
The manuscript was also reviewed by Steve Gutreuter, William Swink, and Steve Zigler.
Partial funding for this study was provided by the U.S. Army Corps of Engineers through the
Environmental Management Program.
256
-------
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