Hydrobiologia 342/343: 117–124, 1997. 117L. Kufel, A. Prejs & J. I. Rybak (eds), Shallow Lakes ’95.c 1997 Kluwer Academic Publishers. Printed in Belgium.

Meiobenthos communities of some subarctic lakes

Vladimir V. SkvortsovInstitute for Lake Research of Russian Ac. Sci., Sevastyanova, 9, 196199 St. Petersburg, Russia

Key words: meiobenthos, subarctic lakes, oil pollution, regression model

Abstract

Meiobenthos communities of 19 relatively small tundra lakes (area 0.2–320 ha) were studied during summerseasons of 1986–1988 and 1993. The lakes are located in the northeastern region of European Russia. All lakesare separated into deep (with mean depth from 2.0 to 8.0 m) and shallow ones (mean depth is less than 1.5 m).Several lakes were low – or strongly polluted by crude oil. Concentrations of hydrocarbons in lake water wererespectively 0.42–0.92 mg l�1 and 7.4–6.3 mg l�1. Species composition, number and biomass of meiobenthos wereinvestigated. Relationships between those parameters and environmental and trophic factors were analyzed.

Meiobenthos biomass ranged from 0.003 to 0.911 g m�2 in central zones of deep lakes and from 0.38 to 17.61 gm�2 in littoral zones. The biomass of littoral Cladocera, Harpacticoida and Nematoda was higher in deep unpollutedmesotrophic lakes. The biomass of Bivalvia positively correlated with primary production of phytoplankton.

Oil pollution caused structural changes of communities. Benthic Cladocera and Chironomidae are more vulner-able to the effect of oil pollution. They were only abundant at unpolluted and law-polluted localities of the lakebottom. Highest bionnass of meiobenthic Bivalvia occurred in low polluted lakes. Cyciopoida is the most resistantcornponent of meiobenthos communities. Their abundance was highest at most polluted localities.

Introduction

Meiobenthos community consists of both constant(nematods, microcrustaceans, tardigrads) and tempo-ral (juvenile forms of oligochaets, molluscs and insectlarvae) components. A significance of this communityin lakes of temperate zone is reasonably well known.In particular, my previous studies have shown thatmeiobenthos biomasses ranged from 5 to 40% of totalbottom community biomass in these lakes (Skvortsov,1985; Skvortsov et al., 1988). Some factors such as laketrophic level, hydrochemical and hydrophysical prop-erties of sediments and human impacts can affect struc-ture, abundance, biomass and production of meioben-thos of temperate lakes (Holopajnen & Paasivirta,1977; Stanczykowska, 1967; Prejs & Stanczykowska,1972; Sarkka, 1979, Sarkka, 1987).

Meiobenthos biomass forms about 50% (in aver-age) of biomass of the entire bottom community insubarctic lakes (Belyakov & Skvortsov, 1994). How-ever, relationships between meiobenthos community

and environmental factors was still poorly known forsubarctic area.

The proposed study has main objectives: to charac-terize the structure, abundance, and spatial distributionof meiofauna in subarctic lakes in relation with essen-tial environmental factors and to investigate the pollu-tion response patterns of whole meiobenthos commu-nities.

Study area

Nineteen lakes located in the central part of Bol-shezemelskaya tundra (North Eastern region of Euro-pean Russia) were investigated during summer seasonsof 1986–1988 and 1993 (Table 1).

The main characteristics of lake morphometry,hydrochemical properties, productivity of phytoplank-ton and level of oil pollution are given in Table 2.All these data were taken from the recently published

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Table 1. Location of studied lake territories andyears of investigations.

Territory N E Years

I 67� 500 59� 000 1986-1987

II 67� 300 57� 000 1988

III 68� 300 58� 300 1993

papers (Drabkova, & Bystrov, 1994; Kuznetsov, 1994;Trifonova, 1994).

The investigated lakes can be divided on deep(mean depth >2 m) and shallow (mean depth <2 m)ones. The deepest lakes were located only within theterritories I and III, all lakes of the territory II were shal-low. The deep lakes had funnel-shaped basins. Theseones had a distinct wide littoral zone, a sublittoral and aprofundal. Basins of the shallow lakes had a plane bot-tom surface. In the littoral of the deep lakes, sedimentswere presented by fine sands (Md = 0.10–0.17 mm), toa depth of 2 meters. In the sublittoral and profundal ofthe deep lakes and in central zone of the shallow onesthere were muddy sediments with an organic mattercontent from 5 to 40% (Strukova, 1994).

The investigated lakes were similar in main hydro-chemical parameters. The concentrations of nutrientswere ranged within limits: Pinorg 0.00–0.02 mg l�1,Ptot 0.01–0.32 mg l�1, Ninorg 0.00–0.67 mg l�1, Ntot

0.00–2.66 mg l�1. The values of parameters charac-terizing an organic matter content were varied withinrange: BOD 0.8–6.50 mg O2 l�1, COD 4.48–64.8 mgO l�1, and pH 6.2–8.21. However, the whole set oflakes can be divided on two different groups at signifi-cance level of 0.05%. The division on two clusters wasbased on distinctions of water color (F -ratio = 73.955,p = 0.000) and concentration of major ions (F -ratio= 5.949, p = 0.016). The lakes of the first group (# #1–12) were characterized by low colored waters andhigh concentration of major ions (Pt-Co units = 4.00–52.00, CMI = 19.50–88.5 mg l�1), while the lakes ofthe second group (# # 13–19) had more colored watersand low concentration of major ions (Pt-Co units =80.35–199.20, CMI= 13.00–29.00 mg l�1.

Materials and methods

The samples of meiobenthos were taken by MB-TE-type corer (Travianko & Evdokimova, 1968) with asurface 12.6 cm in 3–5 replicates from main biotops oflakes. The collected samples were sifted through a 106�m mesh and were preserved with a weak solution of

formalin (4%). The samples were taken twice on Julyand August 1986 and 1988 in each lake, seven timesthrough July to September 1987 in lakes # # 1 and 7,and ones in August 1993 in lakes # # 9–11. Specialsurveys were carried out on 28 sites of Mitrofan lake(# I) on July 25 and August 23, 1986 in order to studya spatial distribution of meiobenthos. The count ofmeiobenthos animals was made with use a dissectingmicroscope. Body weight of the animals was deter-mined under appropriate formulas (Ankar & Elmgren,1976; Tsalolichin, 1981; Balushkina, 1982, Methodi-cal recommendations, 1982, 1983). Following statisti-cal methods were applied to determine relationships ofmeiobenthos biomass to environmentalcharacteristics:ANOVA (analysis of variance), factor analysis, simpleand multiple linear regressions, and nonlinear regres-sion (SYSTAT, 1992). Meiobenthic and environmentaldata were not transformed.

Results

Species composition

The determinations of the species was made only forCladocera, Cyclopoida, Chironomidae larvae, Mollus-ca and predominant Nematoda. The complete list ofmeiobenthos species has been published in our previ-ous paper (Belyakov & Skvortsov, 1994).

Altogether forty-three species of invertebrate ani-mals have been found out in investigated lakes. Chi-ronomidae were presented by the highest number ofspecies (22). The following chironomid species weremeeting the most frequently: Clodotanytarsus mancus(Walk.), Tanytarsus holochlorus Edw., Paratanytar-sus lauterbornii (Kieff), Limnochironomus nervosus(Staeger), Polypedilum nubeculosum (Mg.), Procla-dius choreus Meig., Psectrocladius psilopterus Kieff.

Cladocera were presented by: Alona affinis Ley-dig, Alona rectangula Sars, Alonopsis elongata (Sars),Camptocercus rectirostris Shoedler, Chydorus ovalisKurz., Eurycercus lamellatus (O.F.Muller), Ilyocrip-tus acutifrons Sars, Acanthocyclops viridis (Jur.) werethe most usual among Cyclopoida. Bivalve molluscswere presented mainly by juvenile forms of Euglesasp. and Sphaerium amnicum (Mull.). Nematods werepresented by Dorylaimus stagnalis Dujardin, Ironustenuicaudatus de Man, Mononehus truncatus Bastianand Tobrilus sp.

Despite essential distinctions between lakes, theydistinguish insignificantly by a species structure

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of meiobenthos communities (calculated Sorensen’sindex is equal to 0.71). It is possible to note that E.lamellatus was found only in deep lakes on sandy sed-iments, and I. acutifrons in shallow ones with muddybottom. Common A. viridis have been replaced by A.gigas (Claus) in the most oil polluted lake (Lake # 8).These crustaceans were almost unique components ofthe meiobenthos community in this lake.

Spatial distribution

Sediment-depended distribution of meiobenthos wasinvestigated. The obtained data have shown thatmeiobenthos concentrated in the upper part of littoralzone. The highest number of meiobenthos (60 000ind m�2 has been registered at depth about 1 meter,decreasing to 8000 ind m�2 at 2 m depth, in the sub-littoral and profundal the meiobenthos abundance didnot exceed 1000 ind m�2. It is important to note, thatthe number of meiobenthos inhabiting a shorewaterboundary (depth less than 0.5 m) reduced down to15 000 ind m�2, likely due to a regular wave-action onmeiobenthos organisms dwelling in this bottom area.

Different groups of meiobenthos populations pre-ferred sediments with a different particle size. Aparticle-size range of sediment preferred by meioben-thos was determined by occurrence of their abundancepeaks. Bottom Cladocera, Harpacticoida, Cyclopoi-da and Ostracoda did not display an association withmedian particle size. Only chironomid larvae andNematoda preferred more coarse littoral sands from0.12 to 0.17 mm median particle size (t=3.607, p<0.01and t=3.030, p<0.01 respectively) .

Abundance of meiobenthos

As it has been shown above, the meiobenthos commu-nity was most abundant in a lakeshore zone in deeplakes. The number of meiobenthos organisms in cen-tral parts in these lakes ranged in limits from 200 to4500 ind m�2, and biomass from 0.003 to 0.91 g m�2

wet weight. The abundance of meiobenthos in centerof shallow lakes was, as a rule higher, than directlyat beach. At the further analysis I shall operate withdata relating to littoral zone, considering central bot-tom biotops of shallow lakes as littoral ones.

The average values of biomass of littoral meioben-thos of investigated lakes are given in Table 3. Todetermine major factors, which controlled meioben-thos community in littoral, I was consistently usingsome statistical procedures: factor analysis, two-way

Figure 1. Relationship of meiobenthic biomass with envirom-nental data (on the results of factor analysis). 1- Cladocera,2-Cyclopoida; 3-Chironomidae, 4-Nematoda, 5-Ostracoda; 6-Bivalvia, 7-Oligochaeta; 8-Harpacticoida; 9-Pinorg; 10-Ptot; 11-Ninorg; 12-Ntot; 13-BOD; 14-pH; 15-COD; 16-Color; 17-CMI, 18-Oil; 19-Chlorophyll a; 20-mean depth.

ANOVA, step-wise multiple regression procedure andnonlinear regression.

The factor analysis was based on data on meioben-thos and the following variables: concentrations ofinorganic and total forms of P and N, pH, water color(Pt-Co units), CMI, BOD, COD, oil-products concen-tration, mean lake depth, and chlorophyll a concentra-tion.

As a result, four factors have been determined.These factors explain 66.5% of total variance of envi-ronmental and meiobenthic data (Table 4).

The first factor (25.9% explained variance)describes differences between two groups of the lakes.This factor positively correlates with such parameters,as the average lake depth and concentration of CMI.Simultaneously it negatively correlates with chloro-phyll a concentration, water-color and contents of theforms of nitrogen in water.Thus, it is possible to formu-late that the deep and low productive lakes are placedalong the positive part of first factor axis, whereas shal-low polyhumic and high productive lakes are placedalong the negative part of the first factor axis. Figure1 shows, that Cladocera, Halpacticoida and Nemato-da have almost similar requirements to environmen-tal conditions. An optimal combination of these con-ditions for these taxonomic groups of meiobenthosoccurred in deep lakes. Ostracods are placed in thenegative area of this factor, that is evidence for theirpreference of shallow and water- colored lakes.

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Table 2. Main characteristics of the lakes investigated. DEPTH- mean depth (m); CMI- concentrationof major ions (mg l�1); Color- Pt-Co units; OIL - oil concentration (mg l�1); PP - primary production(g C m�2 d�1); CHL - chlorophyll a concentration (�g l�1).

# # Lake Territory Area DEPTH CMI Color OIL PP CHL

names ha

1 Mitrofan I 30.9 6.1 88.5 45.4 0.00 0.407 1.471

2 Izjato I 334.9 2.4 34.0 20.6 0.00 0.300 1.190

3 Hasujto I 45.5 1.7 48.0 25.0 0.00 0.275 3.643

4 Pjartavto I 51.2 1.1 19.5 28.9 0.00 0.336 6.023

5 Nahyto I 32.6 2.4 39.5 44.8 1.90 0.194 4.450

6 Nocmato I 10.7 1.0 48.0 27.5 0.00 0.054 1.157

7 Talijto I 10.5 0.9 48.0 43.8 0.00 0.295 2.407

8 Tibejto I 27.0 2.4 67.0 52.9 6.30 0.522 8.300

9 Naulto III 322.0 8.0 4.0 0.00 0.220 0.800

10 Lake I III 0.7 5.8 4.0 0.00 0.390 0.640

11 Lake 2 III 0.2 2.2 4.0 0.00 0.280 0.530

12 Kyvtanhasyrej II 120.0 0.9 38.5 0.43 1.950 46.000

13 N1 II 3.3 1.0 13.0 98.8 0.01 0.127 4.300

14 N2 II 8.8 0.9 29.0 119.2 0.01 0.942 84.150

15 N3 II 21.6 0.6 13.0 199.2 0.01 0.215 3.900

16 N4 II 6.4 1.3 23.0 94.2 2.40 1.480 71.550

17 N5 II 10.0 0.5 24.0 98.0 0.01 0.184 3.450

18 N6 II 2.1 1.5 14.0 80.4 0.01 0.222 1.500

19 N7 II 3.5 1.1 23.0. 86.4 0.64 0.070 1.100

Table 3. Average biomass of the littoral meiobenthos (g m�2, wet weight). CLAD - Cladocera, CYCL- Cyclopoida, CHIR - Chironomidae, NEM - Nematoda, OSTR -Ostracoda, BIV - Bivalvia, OLIG -Oligochaeta, HARP - Harpacticoida; lake # # are the same as in Table 2.

Lake # # CLAD CYCL CHIR NEM OSTR BIV OLIG HARP Total

1 0.576 0.211 0.298 0.242 0.131 0.203 0.038 0.260 1.960

2 1.058 0.121 1.306 0.431 0.415 0.032 0.025 3.388

3 0.013 3.164 0.124 0.044 3.345

4 0.002 0.277 2.777 0.161 2.890 0.005 0.001 6.113

5 0.445 0.888 1.360 0.764 0.216 4.679 0.186 0.118 8.654

6 0.026 0.064 0.130 0.080 0.059 0.438 0.011 0.808

7 0.133 1.218 1.352

8 3.715 0.075 0.214 4.004

9 0.474 0.183 0.254 0.030 2.110 0.266 3.315

10 0.145 0.069 0.006 0.357 0.349 0.842 1.768

11 1.000 0.117 0.004 0.136 8.238 0.817 10.312

12 0.047 0.157 1.090 0.036 0.254 15.607 0.422 17.613

13 0.008 0.191 0.896 0.028 0.108 0.498 1.729

14 0.013 0.011 1.669 0.003 0.461 2.156

15 0.092 0.113 1.212 0.117 0.483 0.036 2.051

16 0.266 0.049 0.030 0.040 0.384

17 0.008 0.135 1.124 0.071 0.050 0.071 1.459

18 0.004 0.035 0.479 0.005 0.008 0.036 0.567

19 0.004 0.132 0.459 0.004 0.004 0.602

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Table 4. Loadings in factor analyses for some environmentalcharacteristics and littoral meiobenthos biomass.

Factor

Variable I II III IV

Cladocera 0.516 �0.247 0.389 �0.125

Cyclopoida 0.484 0.765 �0.163 0.17

Chironomidae �0.124 �0.168 0.181 0.405

Nematoda 0.528 �0.182 0.543 0.285

Ostracoda �0.434 0 047 0.698 0.192

Bivalvia 0.359 �0.121 0.275 0.556

Oligochaeta 0.674 0.556 0.168 0.302

Harpacticoida 0.594 �0.218 0.582 �0.315

Pinorg 0.532 0.525 �0.248 0.166

Ptot �0.365 0.663 0.416 0.146

Ninorg �0.607 0.607 0.169 �0.379

Ntot �0.442 0.418 0107 �0.318

BOD 0.207 0.25 �0.37 0.13

pH 0.313 0.688 0.012 �0 211

COD �0.414 0.372 0.276 0.464

Color �0.666 0.08 0.215 0.052

CMI 0.695 0.164 0.16 �0.374

Oil 0.374 0.878 �0.141 0.059

CHL �0.613 0.485 0.36 �0.24

Depth 0.726 �0.054 0.391 �0.413

% of variance 25.9 20.3 11.5 8.8

The second factor (20.3% explained variance)describes conditions, caused by oil pollution. This fac-tor positively correlates with oil concentration, nutri-ents content and pH. Distribution of Cyclopoida andOligochaeta is associated with the second factor (Fig-ure 1).

The third factor (11.5% explained variance), Ithink, reflects the tendency of increase of an abundanceCladocera, Harpacticoida and Nematoda with increaseof lake productivity within limits of their optimum con-ditions.

The fourth factor (8.8% explained variance) shows,that the optimum environmental and trophic conditionsfor Chironomidae and Bivalvia occurred in shallowlakes with high contents of dissolved organic matter.

ANOVA has been conducted with the same data set(Table 5). Basically, the conclusions received earlierhave been confirmed. Also, additional information hasbeen received. So, reliable influence of pH to Nema-toda abundance has been marked. A positive influenceof oil pollution on biomass of Bivalvia, and a weaknegative one of high concentrations of major ions onChironomidae has been revealed.

Figure 2. Predicted and observed values of cyclopoid biomass.

Factor analysis and ANOVA permitted only to eval-uate an influence of the factors at a qualitative level, butthey are not suitable for creation of predictive models.For this purpose can serve simple and multiple regres-sion procedures.

I have constructed a set of empilical regressionmodels (Table 6), which if they do not describe con-nections of meiobenthos with the environmental andtrophic factors with high accuracy, then demonstratethem. Equations 1 and 2 show, that the abundance ofChironomidae larvae was conditioned mainly by thetrophic factor. The Cyclopoida abundance on 73% wasexplained by the factor, reflecting trophic conditionsin lake (inorgorganic phosphorus content) too (Equa-tion 3). Only the equation 3 it is possible to use as apredictive model (Figure 2), other are only descriptiveones.

In my opinion, a more realistic approach to adescription of interaction of meiobenthos communitywith environmental factors is to use nonlinear regres-sion models. For approximation of field observations,I have chosen a function; that has the form:

Y = Constant+ a �Xb� ecX ;

whose a graphic representation depends on signs of itscoefficients (Bronshtein; Semendyaev, 1953).

Figure 3 displays the dependence of biomass ofjuvenile Bivalvia on oil concentration (r2=0.725). Itis clear, that optimum conditions for this group ofmeiobenthic animals have been occurred in moder-ate oil pollution area. Besides the nonlinear interactionof Bivalvia witl daily primary production of phyto-plankton was found out too (r2=0.352). The creationof two-factor model was a further step of a nonlinearregression analysis (r2=0.913), whose graphic repre-

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Table 5. Analyses of variance for the effect of some environmental characteristics onlittoral meiobenthos biomass. Color -Pt-Co units; OIL - oil concentration (mg l�1) CMI-concentration of major ions (mg l�1); DEPTH - mean depth (m)

Group Parameter F -ratio Significance % of variance Effect

level explained

Nematoda pH 4.72 0.015 16 negative

DEPTH 18.96 0.0001 33 positive

Bivalvia Color 3.12 0.056 12 negative

OIL 5.22 0.001 20 positive

Cladocera CMI 3.85 0.03 16 positive

DEPTH 5.00 0.031 10 positive

Chironomidae CMI 3.75 0.032 16 negative

Cyclopoida OIL 6.32 0.005 25 positive

Ostracoda Color 3.24 0.053 26 positive

Table 6. Regression equations predicting meiobenthos biomass. PP -primary production (g C m�2

d�1); Bzoo - zooplankton biomass (g m�3) COD - chemical oxigen demand (mg O l�1); OIL -oilconcentration (mg l�1)

# # Group Predictor Coefficient SE t-value Significance r2

level

1 Chironomidae PP 0.576 0.189 3.045 0.005 0.416

Bzoo 0.126 0.045 2.770 0.010

2 Chironomidae COD 0.029 0.006 4.650 0.004 0.603

3 Cyclopoida Pinorg 43.83 14.38 3.048 0.009 0.941

OIL 0.41 0.052 7.725 0.000

Figure 3. Dependence of bivalves biomass on oil concentration(r2=0.725).

sentation is given in Figure 4. This model also shows,that the abundance of meiobenthic molluscs was con-trolled by the trophic factors. The optimum conditionsfor Bivalvia occur in productive (2.1 g C m�2 d�1 andmoderately oil polluted (0.49 mg l�1) lakes.

Discussion

Meiobenthos of freshwater lakes of moderate lati-tudes of Russia is rather well-known (Babitsky, 1980;Skvortsov, 1985, Skvoltsov et al., 1988; Kurashov& Belyakov, 1987, Kurashov, 1994). Informationabout a species structure of meiobenthos, its abun-dance, distribution and reaction on environmental fac-tors is widely available (Holopajnen & Paasivirta,1977; Stanczykowska, 1967, Prejs & Stanczykowska,1972; Sarkka, 1979; Sarkka, 1987). At the same time,the meiofauna of tundra lakes was not investigatedenough so far.

As have shown our studies, a species structure ofmeiobenthos of subarctic lakes did not practically dif-fer from those in lakes of the temperate zone of Europe(Sarkka, 1983; Skvortsov et al., 1988; Kurashov,1994).

The distribution of meiobenthos organisms in deeptundra lakes differed as a rule from distribution ofmeiofauna in deep lakes of a moderate zone. In con-trast to them, the maximum abundance of meiobenthoswas marked in littoral zone. The connection between anabundance of meiobenthos invertebrate and size of sed-

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Figure 4. Bivalves biomass as the function of oil concentration and daily primary production (r2=0.913).

iment particles was found out only for Chironomidaelarvae and Nematoda. The increase of number of nema-tods with increase of sizes of particles was marked alsoin Lake Michigan (Nalepa & Quigly, 1983).

A reaction of taxonomic groups of meiobenthos ofsubarctic lakes on environmental factors in the majorityof cases was identical with described in the literature.As well as in Finnish Lake Paijanne (Sarkka, 1979), intundra lakes Nematoda preferred oligohumic sites andwith low COD. Besides in investigated tundra lakeswithin the framework of the optimum combinationof the environmental factors Nematoda biomass posi-tively correlated with chlorophyll a concentration (thethird factor, Table 4). Some authors indicated, that aheavy organic pollution caused an increase of an abun-dance of Cyclopoida, Harpacticoida and Nematoda(Sarkka, 1975; Kansanen, 1981). Sarkka (1979) speci-fied, that meiobenthic Eucyclopinae and resting stagesof Cyclopoida positively correlated with COD, Ntot,Ptot water color and phytoplankton biomass. Underour observations, the biomass of Cyclopoida increaseswith increase of Pinorg concentration and oil pollution(Table 6). The highest biomass (Acanthocyclops gigas)was found in the most oil polluted lake. However, thecorrelation with other variables was expressed muchmore poorly (Table 4, Figure 2).

In the same work it was specified, that the abun-dance of mollusc Pisidium conventus Clessin was neg-atively connected with such variables, as COD, Ptot

and color, that coincides with our observations (Table4, Figure 1).

The influence of oil pollution was investigatedmainly on marine meiobenthos in field experiments.

Results of experiments, indicated in those papers wereinconsistent. Some researchers (Alongi et al., 1983)marked initial decreases in abundance of meiobenthos,other did not mark decrease, but registered enhancednematod and copepod abundance (FIeeger & Chan-dler, 1983). The computed theoretical curve fitting therelationship between the nematod biomass and oil con-centration (r2=0.647) has shown, that the maximumabundance of nematods should be occurred in pollut-ed lakes (oil content 1.4 mg l�1). However, I can notinsist on it, as there are not appropriate field data forthis range of oil concentrations.

Effect of oil on bivalve Macoma balthica (L.) isdescribed (Eimgren et al., 1983). The authors haveshown, that M. balthica was more resistant organismto oil pollution. After oil spill the increase of biomassof this mollusc occurred. The authors connected thiseffect to a reduction of pressure of benthic predatorson juvenile bivalves. According to our observations,juvenile bivalves displayed maximal biomass in oilpolluted localities. Dependence of their biomass on oilpollution had complex nonlinear character (Figures 3and 4). Probably, the increase of the bivalve biomass inmoderate polluted sites connected with trophic factorsand may be explained by the high resistance to toxicaction of oil.

Acknowledgments

I am very gratefull to The John D. and Catherine T.MacArthur Foundation for the financial support of

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my participation in ‘Shallow Lakes’95’ Conference(August 21–26, 1995, Mikołajki, Poland).

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