the influence of ecohydrological factors on the

Acta Zoologica Lituanica, 2011, Volumen 21, Numerus 2

DOI: 10.2478/v10043-011-0013-3

ISSN 1648-6919

The influence of ecohydrological factors on the cenosis of the Daugava River zooplankton Rasma DEKSNE1, 2, Artūrs ŠKUTE2 ¹Rezekne Higher Education Institution, Latgale Sustainable Development Research Institute, Atbrīvošanas aleja 76, LV-4601 Rezekne, Latvia. E-mail: [email protected] ²Institute of Ecology, Daugavpils University, Vienības St. 13, LV-5401 Daugavpils, Latvia. E-mail: [email protected] Abstract. The correlation between the dynamics of quantitative and qualitative indicators of zooplankton cenosis in the Middle Daugava River and changes in environmental factors was examined. It was found that changes in the abundance, biomass and taxa of zooplankton were significantly affected by thermal conditions, hydrological regime, chlorophyll-a and phosphates. The possible role of environmental factors (lucidity, dissolved oxygen, conductivity, pH, oxidation reduction potential, nitrate, chemical oxygen demand) in controlling dynamics of the Daugava River zooplankton is indicated. Key words: large river, Rotifera, Copepoda, Cladocera, hydrological regime, temperature

Introduction The opinion that typical river zooplankton does not exist because of the impossibility of reproduction in water current has been prevalent in hydrobiology for a long time (Czerniawski & Domagała 2010b; Krylov 2005). Contrary to the popular belief, many species can find suitable conditions for the development of abundant populations in stream habitats (Ejsmont-Karabin & Kruk 1998; Lair 2006; Krylov et al. 2003; Pace et al. 1992; Thorp et al. 1994). The qualitative and quantitative structure of zooplankton cenosis is determined by the interaction of abiotic environmental factors along with nutrition guarantee and producer-consumer relations (Dubovskaya 2009). Plankton in rivers remains primarily governed by unpredictable physical processes and depends on the age of water and availability of habitats (Lair 2006; Pace et al. 1992; Basu & Pick 1996). As to the role of water flow and geomorphology, which determine characteristics of river habitats and plankton distribution, it should be noted that physical control precedes biological control (Lair 2006). Stream velocity is one of the key factors in limiting the development of lentic zooplankton (Dubovskaya 2009; Rzóska 1978; Bening 1941; Greze 1957). Climate, as a regulator of water flow, initiating changes in hydro-morphology of the river, also exerts an important control over fluvial communities, and natural disturbances are the cause of large variations among rivers, as well as annual changes within the same river (Kļaviņš et al. 2008). Among the major factors affecting river plankton the following should be mentioned:

floading, current velocity, river length and its catchment area, density and spread of macrophyte overgrowth, the morphological and ecological state of water plants (Lair 2006; Krylov 2005; Krylov et al. 2003; Czerniawski & Domagała 2010a, b; Chang et al. 2008). Thorp and Mantovani (2005) point out that five abiotic environmental factors are of importance to lotic zooplankton: 1) turbidity (especially from suspended sediment); 2) water turbulence; 3) hydrological retention, which is influenced by stream discharge and access to sheltered, low velocity sites (slackwaters); 4) thermal conditions; and 5) ultraviolet radiation. Factors determining the population structure of water organisms, their distribution and dynamics, and prediction of changes in population numbers are some of the most significant tasks in hydroecological studies. Although river studies are carried out all over the world, river zooplankton is the subject that is still insufficiently studied: data available on lake zooplankton are much more abundant (Thorp & Casper 2002). The knowledge of plankton functioning in rivers is needed to develop a relevant multidisciplinary approach that encompasses the knowledge of river habitats and river inhabitants. Therefore the aim of this study is to examine factors that influence Middle Daugava zooplankton communities and dynamics.

Material and methods The Daugava River (Zapadnaja Dvina) is a river in the north of Eastern Europe rising in the Valdai Hills, Rus-

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Deksne R., Škute A.

sia, and flowing through Russia, Belarus, and Latvia into the Gulf of Riga, an arm of the Baltic Sea. The total length of the river is 1005 km, 352 km of which or 35% of its total length fall to Latvia (The summary of overground water quality 2003). The Daugava River basin with the watershed area of 87900 km² stretches over the territory of five countries, Russia, Belarus, Lithuania, Estonia and Latvia with 24700 km² or 28% of its total area falling to Latvia. At its source (the Lake Dvineca), the river is only 6 to 8 m wide, but in some places further the width of the river bed reaches 50 m. On the Latvian border, the river runs along a 0.5 km wide ancient valley and the riverbed is up to 200 m wide. The section from Krāslava to Daugavpils is highly curved and has many rapids. The longitudinal gradient changes from 0.10 to 0.15 m/ km, and the stream velocity from 0.3 m/s to 0.7 m/s in most sections. Downstream of Daugavpils the river is slow, with gently sloping banks and wide floodplains (Kavacs 1994). The biggest natural floodplain in Latvia is located within the Daugava valley stretch from Daugavpils city down to Jersika, where the river cuts through the Baltic Morainic Ridge and in its further course flows across the Eastern Latvian lowland. The territory of the floodplain which is inundated by the highest level spring flood, covers an

area of 208.25 km² and includes the Middle Daugava River and part of the ancient river bed of the Dviete stream, its left bank tributary (Škute et al. 2008). The territory is characterised by a temperate semihumid climate influenced by the westerly transfer of oceanic air masses. The mean annual precipitation does not exceed the range of 600 to 700 mm/year. Seasonal fluctuation in water level in the stretch of the Middle Daugava is mainly determined by natural factors, such as the amount of snow accumulated in the drainage area during winter, air temperature increase rate and snow melt in spring or formation of ice jams during spring floods (Gruberts 2006). About half of the total mean annual amount of the Daugava runoff is formed during spring floods (Briede et al. 2001). During the expeditions to the following Daugava River stretches – from Surozha in Belarus to Dunava in Latvia (21 sampling sites) in 2008, the Kraslava–Dunava stretch (13 sampling sites) in 2009 and the Krauja– Silupe stretch (3 sampling sites) in 2010, zooplankton was sampled at the right and left banks, as well as in the middle of the river (Fig. 1, Table 1). Samples of zooplankton were collected by filtering 100 l of river water using a 65-μm mesh-sized plankton net. Zooplankton individuals smaller than 65 μm in size

Table 1. Sampling sites in the Daugava River and sampling dates. No 1 2 3 4 5 6 7 8 9

Sampling site coordinates Surozha 55°25.400'N 30°44.183'E Above Vitebsk 55°17.016'N 30°15.530'E Below Vitebsk 55°10.148'N 29°44.106'E Beshenkovichi 55°04.516'N 29°31.012'E Ula 55°14.296'N 29°13.417'E Above Plock 55°27.598'N 28°51.187'E Disna 55°34.166'N 28°12.283'E Verhnedvinsk 55°48.516'N 27°48.541'E 4 km above Krāslava 55° 51.431'N 27°11.705'E

10 11 12 13

4 km below Krāslava 55°52.513'N 27°05.873'E Kaplava 55°52.091'N 27°00.282'E Līdakas 55°52.423'N 26°55.822'E Ververu krauja 55°53.375'N 26°52.286'E

14 15 16

Muravki 55°53.061'N 26°46.075'E Elernas karjeri 55°55.288'N 26°42.442'E Krauja 55°54.787 'N 26°40.059'E

17 18

1.5 km below Daugavpils 55°53.311'N 26°28.401'E Silupe 55°57.322 'N 26°24.271'E

19 20 21

Below Glaudāni 56°03.779'N 26°20.208'E Nīcgale 56°08.169'N 26°19.981'E Dunava 56°13.055'N 26°12.818'E

2008

2009

2010

23 July

24 July

31 May, 1 August, 15 5 June, 11 July, 27 September August, 2 October 31 May, 2 August 31 May, 1 August 31 May, 2 August, 15 September 31 May, 2 August 31 May, 1 August 28 May, 1 August, 15 September 28 May, 2 August 28 May, 2 August, 15 September

6 June, 12 July, 25 August 5 June, 11 July, 27 August, 2 October 5 June, 11 July, 25 August, 2 October 6 June, 12 July, 25 August, 2 October

6 June, 12 July, 25 August 28 May, 2 August 28 May, 2 August, 16 September

16 May, 2 June, 17 June, 1 July, 12 July, 30 July, 19 August, 30 August, 16 October, 30 October

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Cenosis of the Daugava River zooplankton

A

Pearson’s correlation coefficient (r) was calculated using MS Excel. Multivariate statistical analyses were conducted using CANOCO 4.5 for Windows. Detrended Canonical Correspondence Analysis (DCCA) was performed to test linear versus unimodal response of the data. The gradient length of the first axis was < 4 (1.4 and 3.1) suggesting a linear response. Therefore, Redundancy Analysis (RDA) was chosen as a method for zooplankton data ordination against environmental variables. The Monte Carlo permutation test was performed.

Estonia Gulf of Riga

Latvia

Russia

Riga

Daugavpils

Lithuania Kaunas

Vitebsk

Vilnius

Belarus Minsk

Poland

B

0

125 250 km

Rezekne

20

19 18 17 16 15 13 14

11 9

10 Daugavpils 12 Kraslava

Table 2. Environmental characteristics of the Daugava River at the surveyed sites (2008–2010).

8 7

Lithuania

Navapolack Polack 6

Belarus

2

5

3 4

Smarhon'

Vilejka

The total number of the recorded taxa was 144, of which 86 belonged to Rotifera, 39 to Cladocera, and 19 to Copepoda. Environmental characteristics of the Daugava River at the surveyed sites are presented in Table 2.

N

Russia

Latvia

21

Results

1

Vitebsk

0 25 50

100 km

Figure 1. Sites in the Middle Daugava sampled during the 2008–2010 expedition.

were not included in this research. Collected samples were fixed in 4% formalin. A Carl Zeiss light microscope was used for the analysis of zooplankton; three subsamples (2 ml each) were examined at 100–400× magnification. The aim of the qualitative study was to identify Rotifera, Cladocera, and Copepoda taxa. All taxa of zooplankton were identified using keys of Kutikova (1970), Borutsky (1960), Manuilova (1964). The chemical oxygen demand (COD), PO43-, NO 3was measured with a photometer DR-2800 manufactured by Hach Lange (USA). Water temperature (°C), pH, conductivity (mS/cm), dissolved oxygen (mg/l, %), turbidity (self-cleaning) (NTUs), oxidation reduction potential (ORP) (mV), chlorophyll-a (NTU) and were measured with a Hydrolab MS5 Sonde. Water discharge data were obtained from the database of the company ‘Latvian Environment, Geology and Meteorology Centre’.

Parameters Avg ± SE Min–Max Temperature, ° C 17.21 ± 0.38 9.11–24.71 pH 7.92 ± 0.06 6.54–9.88 Conductivity, mS/cm 0.32 ± 0.01 0.21–0.56 Dissolved oxygen (DO), 8.38 ± 0.31 2.31–19.53 mg/l Dissolved oxygen (DO), 81.42 ± 3.71 12.23–221.01 % Oxidation reduction poten- 429.02 ± 4.77 167.34–542.09 tial (ORP), mV 5.03 ± 0.20 2.11–14.37 Chlorophyll-a, mg/l Turbidity (self-cleaning), 15.38 ± 1.76 5.61–223.10 NTU Water discharge, m³/s 336.88 ± 18.18 125.45–981.13 PO4³-, mg/l 0.05 ± 0.004 0.01–0.37 NO3-, mg/l 0.05 ± 0.01 0.003–0.26 Chemical oxygen demand 36.33 ± 0.69 25.50–51.41 (COD), mg O2/l Lucidity, cm 88.25 ± 2.08 34.45–120.03

In Figure 2, eigenvalues of the 1st and 2nd RDA axis were 0.187 and 0.016 respectively, the cumulative percentage variation of the first two axes was 99.2%, and the sum total of all canonical eigenvalues was 0.205. In the Daugava River, zooplankton abundance was positively correlated with water temperature (r = 0.19; p = 0.050) and the concentration of phosphates (r = 0.28; p = 0.034). A significant positive correlation was established between the abundance of Rotifera and COD (r = 0.28; p = 0.008) and the concentration of phosphates (r = 0.20; p = 0.028). The abundance of Cladocera was found to be positively correlated with water temperature (r = 0.21;

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p = 0.034), DO% (r = 0.12; p = 0.032), chlorophyll-a (r = 0.24; p = 0.014) and phosphate concentration (r = 0.24; p = 0.042), but negatively with turbidity (r = -0.10; p = 0.051) and water discharge (r = -0.21; p = 0.050). The abundance of Copepoda correlated positively with water temperature (r = 0.20; p = 0.014), chlorophyll-a (r = 0.18; p = 0.012) and phosphate concentration (r = 0.20; p = 0.036), but negatively with water discharge (r = -0.29; p = 0.004) (Fig. 2, Table 3). A significant positive correlation was established between zooplankton biomass and chlorophyll-a (p = 0.006; r = 0.34). The biomass of Rotifera was found to be correlated with chlorophyll-a (r = 0.16; p = 0.008), water discharge (r = 0.41; p = 0.002) and COD (r = 0.10; p = 0.004). The biomass of Cladocera correlated with chlorophyll-a (r = 0.34; p = 0.006). It was found that the biomass of Copepoda correlated with chlorophyll-a (r = 0.55; p = 0.002), ORP (r = 0.35; p = 0.006) and inversely with turbidity (r = -0.20; p = 0.048) (Fig. 2). 0.8

COD

PO4

ROT. abu Flow rate TurbSC

ROT. biom. NO3

-0.6

DO pH

Lucidity Zoopl. abu. COP. abu. Temp ORP

CLA. abu. Zoopl. biom. CLA.biom.

COP. biom. CHL DO%

Cond -0.6

0.6

Figure 2. RDA ordination plot of zooplankton communities and environmental variables (Temp – Temperature; Cond – Conductivity; DO – Dissolved oxygen, mg/l; DO% – Dissolved oxygen, %; ORP – Oxidation reduction potential; CHL – Chlorophyll-a; TurbSC – Turbidity (self-cleaning); PO4 – phosphates; NO3 – nitrates; COD – Chemical oxygen demand; Lucidity – Lucidity; Flow rate – Water discharge; Zoopl. abu. – Zooplankton abundance; Zoopl. biom. – Zooplankton biomass; ROT. abu. – Rotifera abundance; CLA. abu. – Cladocera abundance; COP. abu. – Copepoda abundance; ROT. biom. – Rotifera biomass; CLA. biom. – Cladocera biomass; COP. biom. – Copepoda biomass).

0.6 Kerat. c. B. longi. Kerat. q. Polyarth. Poly. do. PO4 Pompholu Synchaet.

Br. quad. Ceriod. Cerid. r. Br. caly Eucyc. s Sim. vet Eucyc. m. MacrothrixCHL Copepodi Rhy. Ros. Trich. r NO3 Euch. di. Sida cry. Nauplii Al. quad. Chyd. ov. DOChyd. sp. Al. rect

COD Flow rate

Lucidity

-0.6

-0.6

ORP

Temp Acro. ha. TurbSC Alona sp.

Cyclops

pH

DO%

Cond

0.8

Figure 3. RDA ordination plot of the abundance of zooplankton taxa and environmental variables (Br. caly. – Brachionus calyciflorus calyciflorus; Br. quad. – Brachionus quadridentatus quadridentatus; Euch. di. – Euchlanis dilatata; Kerat. q. – Keratella quadrata quadrata; Kerat. c. – Keratella cochlearis cochlearis; Pompholu – Pompholyx sulcata; Poly. do. – Polyarthra dolichoptera; Polyarth – Polyarthra vulgaris; Trich. r. – Trichocerca rattus; Synchaet. – Synchaeta sp.; Acro. ha. – Acroperus harpae; Alona sp. – Alona sp.; Al. rect. – Alona rectangula; Al. quad. – Alona quadrangularis; B. longi. – Bosmina longirostris; Ceriod. – Ceriodaphnia affinis; Ceriod. r. – Ceriodaphnia reticulata; Chyd. ov. – Chydorus ovalis; Chyd. sp. – Chydorus sphaericus; Macrothrix – Macrothrix hirsuticornis; Rhy. ros. – Rhynchotalona rostrata; Sim. vet. – Simocephalus vetulus; Sida cry. – Sida crystallina; Copepodi – Copepodite; Eucyc. m. – Eucyclops macruroides; Eucyc. s. – Eucyclops serrulatus; Cyclops – Cyclops sp.; Nauplii – Nauplii).

In Figure 3, eigenvalues of the 1st and 2nd RDA axes were 0.190 and 0.038 respectively, and the cumulative percentage variation of the first two axes was 89.5%, the sum total of all canonical eigenvalues was 0.255. The RDA analysis showed that temperature (p = 0.05) has a significant influence on the main changes in the abundance of zooplankton taxa, chlorophyll-a (p = 0.016) and water discharge (p = 0.032) (Fig. 3). A statistically significant Pearson’s correlation coefficients (r) for the abundance of zooplankton taxa and environmental variable relationships are given in Table 3.

Discussion The diversity and density of zooplankton species vary significantly with current velocity across river networks in general and are positively correlated with hydrologi-

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Table 3. Statistically significant (p < 0.05) Pearson’s correlation coefficients (r) for zooplankton and environmental variable relationships. Taxa Rotifera Brachionus calyciflorus calyciflorus Pallas, 1766 Brachionus quadridentatus Hermann, 1783 Euchlanis dilatata Ehrenberg, 1832 Keratella quadrata O. F. Müller, 1786 Keratella cochlearis cochlearis Gosse, 1851 Polyarthra dolichoptera Idelson, 1925 Polyarthra vulgaris Carlin, 1943 Pompholyx sulcata Hudson, 1885 Synchaeta sp. Trichocerca rattus O. F. Müller, 1776 Cladocera Alona sp. Alona rectangula Sars, 1862 Alona quadrangularis O. F. Müller, 1776 Acroperus harpae Baird, 1834 Bosmina longirostris O. F. Müller, 1785 Ceriodaphnia reticulata Jurine, 1820 Ceriodaphnia affinis Lilljeborg, 1900 Chydorus ovalis Kurz, 1875 Chydorus sphaericus O. F. Müller, 1785 Macrothrix hirsuticornis Norman & Brady, 1867 Rhynchotalona rostrata Koch, 1841 Sida crystallina O. F. Müller, 1776 Simocephalus vetulus O. F. Müller, 1776 Copepoda Cyclops sp. Copepodite Eucyclops macruroides Lilljeborg, 1901 Eucyclops serrulatus Fischer, 1851 Nauplii

Temperature

Chlorophyll-a

Discharge

0.30 0.41

0.37

-0.22 -0.26

-0.21

0.49

-0.15

Turbidity

0.45 0.27

0.20 -0.10

0.58

-0.09

0.29 0.24

0.28 -0.10 0.20

0.28 0.31

-0.22 -0.22

-0.28 0.20 0.24

-0.19

-0.16 0.18 0.30 0.16

cal retention within the riverscape of larger rivers, except where taxa are restricted by other abiotic environmental conditions (e.g. oxygen, temperature, substrate type) (Thorp & Mantovani 2005). This study revealed that in years when the water level was low, i.e. in 2008 and 2010, river discharge correlated with the abundance and biomass of zooplankton negatively (Deksne, unpubl.). The research carried out by Paidere (2008) in 2005–2006 also showed that during the maximal flood discharge, a decrease in numbers of zooplankton organisms is observed in the Daugava River. Thorp and Mantovani (2005) indicated that the mean river discharge itself was not a good predictor of zooplankton densities in their study, but this hydrological parameter must impinge on zooplankton through current velocity, water depth, and turbulence. Basu and Pick (1995), who studied zooplankton communities in the Rideau River, also noted that the relatively low discharge always favours plankton development. Zooplankton

-0.27 -0.17

biomass is inversely related to discharge in many rivers, including the Apure (Saunders & Lewis 1988), Hudson (Pace et al.1992), and Ohio (Thorp et al. 1994). Pace et al. (1992), Thorp et al. (1994) and Kobayashi et al. (1998) noticed that there existed a negative correlation between zooplankton abundance and river discharge in the Hudson, Ohio Rivers (USA) and the HawkesburyNepean River (Australia), respectively. Similarly, Basu and Pick (1996) observed that across the range of 31 rivers in Ontario, Canada, zooplankton biomass was positively related to water residence time. Critical for the development of lentic crustaceans is the current velocity of 0.25 m/s (Dubovskaya 2009). In general, the reproduction of zooplankton is severely impeded at current velocities >0.4 m/s (Rzóska 1978). Dubovskaya points out that at the current velocity of 0.5–0.8 m/s in the river, the development of potamoplankton that mainly consists of Rotifera takes place (Bening 1941; Greze 1957). At the high current velocity of 1–8 m/s

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zooplankton as a biocenotical unit whole does not exist (Dubovskaya 2009). However, there was a positive correlation found between zooplankton biomass and throughput rate in the Benin River in Nigeria (Onwundinjo & Egborge 1994). Czerniawski and Domagała (2010a) also pointed out the positive influence of discharge on the abundance of small cladocerans and small rotifers in outlets of the Korytnica stream, mainly in months when discharge increased rapidly. It was found that Brachionidae represented the most common family in the Daugava River study area. Lair (2006) notes that zooplankton species that are able to continue growing at the current velo city of 20 cm/s, such as Brachionid species, are usually dominant in rivers. In the Daugava River, the negative correlation of the abundance of Cladocera and Copepoda with water discharge could be explained by the fact that among Copepoda calanoids stand out as active swimmers in contrast to several species of cyclopoids and harpacticoids, which are poor swimmers (Lair 2006). Cladocerans, including typically euplanktonic species and littoral forms living in near-shore areas among macrophytes or in benthic boundary layers are also inhabitants of potamoplankton, all the more so as most species are able to swim (Lair 2006). They are better adapted to river conditions than copepods because of their shorter development duration and the possibility of reproducing parthenogenetically, a mode common to rotifers (Lair 2006). Campbell (2002) claims that high water flow and current velocity are favourable to the abundance of zooplankton as in such conditions it is more difficult for fish to catch zooplankton. Thorp and Mantovani (2005), who carried out studies in the Ohio and St. Lawrence Rivers, arrived at a conclusion that Crustacean densities were positively related to the degree of hydrological retention except current velocity (negatively to current velocities). However, rotifer densities were significantly depressed by current velocities only when river discharge was high, making slackwaters even more valuable. Ephemeral sandbars may not provide sufficient hydrological retention in time and space to sustain viable crustacean populations, but they are adequate to help sustain the growth of rotifer populations. In the Daugava River, the biomass of Rotifera was found to be significantly positively correlated with water discharge, which could be explained by the following facts: 1) for somatic and reproductive growth, rotifers need shorter water retention periods in rivers than microcrustaceans (Pace et al. 1992; Kobayashi 1997; Akin-Oriola Gbemisola 2003; Lair 2006; Thorp & Mantovani 2005); 2) the appearance of rotifers of the order Bdelloida in zooplankton is the result of their leaching from the horizontal blanket of


the water body bottom determined by current velocity (Zarubov 1991); 3) the impact of planktivorous fish on rotifers is negligible (Ning et al. 2010; Akin-Oriola Gbemisola 2003; Lair 2006; Thorp & Mantovani 2005; Pourriot et al. 1997); 4) in springs, when water level in the Daugava River is high, there is a hydrological compatibility between the river and lakes in the flood-land system. As a result, in its drainage phase zooplankton flows from lakes into the river. During the spring months of 2010, when water level in the Daugava River was high, the abundance and biomass of Rotifera correlated positively with discharge (Deksne, unpubl.), which could be explained by the fact that rotifers could be washed up from floodplain lakes (Paidere 2008; Gruberts 2006). In June and July 2009, as a result of intensive downfall the level of water in the Daugava River was high and the abundance of crustaceans correlated positively with discharge, which, undoubtedly, could be explained by the development of macrophytes and rising water temperature. However, Kalff (2002) shows that an increase in crustacean diversity is related to floodplain effluents, especially in the case of floods. The maximum throughput phase of the 2006 autumn flood revealed the following effects of flood on zooplankton: the share of Synchaeta oblonga in floodplain lakes and in the Daugava River increased, and the Renkonen similarity index increased from 34% to 82% in the lowwater period (in August). An increase in numbers of taxa and the appearance of littoral or periphytic/littoral forms of zooplankton in the Daugava River during the flood drainage phase were indicative of lake and river water mixing (Paidere 2008, 2009). Seasonal studies carried out in the Daugava River stretch Krauja (before floodplains of the Daugava River) – Berezovka mouth in 2005–2008 as well as studies conducted in spring 2007 at the time of meltwater (in March) in the Rugeli– Dunava stretch prove that at the Berezovka mouth, where meltwaters from rivers and lakes of the Dviete and Ilukste floodplains flow into, larger numbers of taxa and organisms are recorded (Paidere 2010). A similar situation is observed in other river floodplain systems (José de Paggi & Paggi 2007; Keckeis et al. 2003). The examination of the distribution of plankton populations in the Middle Loire and in other rivers showed that the flow regime, which plays a central role in organizing river habitats, explains the presence/absence of these fast-growing organisms (Lair 2006). A complex system of channels and slackwaters is to varying degrees directly beneficial to most aquatic organisms in all rivers, but individual taxa may suffer indirectly from concomitant increase in competition and predation in these habitats (Thorp & Mantovani 2005). It is clear that river ecologists should consider both biological and physical


loss factors when assessing zooplankton populations in large rivers (Jack & Thorp 2002). Although plankton populations in the main channel of many rivers often seem to be physically controlled (e.g. Pace et al. 1992), the growing number of evidence suggests that biotic interactions may play a significant role in rivers, at least in slackwater areas, where plankton productivity is the highest (Baranyi et al. 2002). In situ experiments conducted in a slackwater area of the St. Lawrence River (Thorp & Casper 2002) and in the main channel of the Ohio River (Jack & Thorp 2000, 2002) reveal that both competition and predation/suspension feeding can be important in regulating density and relative abundance of river zooplankton. However, many authors, such as Luecke et al. (1990), Mehner et al. (1998), Hulsmann et al. (1999), Romare et al. (1999), Thorp and Casper (2003) point out that the role of predators in zooplankton dynamics is not great. It has been observed that increased water discharge and current velocity cause increased water turbidity (Škute et al. 2008). Among numerous physicochemical variables affecting river biota, inorganic turbidity is known to have an impact on zooplankton filtration rates and, as a consequence, development rates (Hart 1991). When reporting results of his studies conducted in the Daugava River, Paidere (2010) points out that GML analysis showed a significant negative correlation between turbidity and species diversity by number. This study proved that the abundance and biomass of crustaceans negatively correlates with water turbidity. The comparison of the average river turbidity over many years with recent zooplankton sampling data revealed that in turbid rivers, such as those in the US Great Plains, rotifers fared better, while microcrustaceans worse (Thorp & Mantovani 2005). These results are consistent with laboratory findings (Kirk & Gilbert 1990) that suspended clay reduces population growth rates of Cladocera much more than those of rotifers. What is more, they are also in agreement with findings obtained from various field studies conducted around the world (Shiel 1985; Pace et al. 1992; Thorp et al. 1994). The explanation could be that rotifers indirectly benefit from river turbidity because their competitors for food (Cladocera) and predators (e.g. cyclopoid copepods and visually feeding fish) are relatively more susceptible to suspended sediments. Hence, rotifers probably do better in turbid rivers not because these environmental conditions favour them but rather due to pernicious effects of competition and predation that are partially alleviated by high suspended sediment loads (Thorp & Mantovani 2005). At the transparency less than 10 cm and suspended sediments loads more than 150 g/m³, not only such filtrators as Rotifera and Cladocera cannot survive,

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but also Diaptomas, which are able to filtrate coarse particles (Rivjer 1982). Kirk and Gilbert (1990) established that growth rates of Bosmina longirostris (the dominant branchiopod in our system) and other three Cladocera species were slowed at heavy inorganic turbidities, while rotifers (such as Polyarthra vulgaris, our most abundant species) were generally unaffected. They also reported that addition of suspended clay reversed the results of competition between Cladocera and Rotifera for food. This study also confirmed the existence of positive correlation between water temperature and zooplankton abundance that had been earlier reported by Kobayashi et al. (1998), Czerniawski and Domagała (2010a, b), Rossetti et al. (2009), Lair (2005). The correlation of Cladocera and Copepoda with temperature could be explained by the fact that water warming activates flora growth, which favours zooplankton growth. Some authors (Nilsson et al. 1989; Hamilton et al. 1990; Lair 2005; Czerniawski & Domagała 2010a, b) point out the positive effect of macrophytes on the development of zooplankton communities, especially those of Cladocera and Copepoda. Dubovskaya (2009) notes that an increase in temperature can have various negative effects on Daphnia communities, e.g. decreased food assimilation and filtration speed as well as degeneration and abortion of eggs. In conditions of changeable temperatures, growth rate increases significantly, enhancing effectiveness of the assimilated energy use and species survival (Galkovskaya & Sushenya 1978). Wolska and Piasecki (2009) noted that temperature alone is not a key factor in regulating the occurrence of particular species in the Oder River. Its influence is rather indirect, and temperature may merely enhance or hamper the growth of zooplankton populations acting conjointly with other abiotic and biotic factors. It has to be taken into consideration that the annual amount of precipitation, temperature and other factors influencing zooplankton cenosis vary from year to year, therefore zooplankton’s productivity strongly varies from year to year (Deksne, unpubl.). Zaytsev et al. (1989) mention that fluidity of zooplankton from year to year depends on the duration of the low temperature period in spring and water level. The correlation of Rotifera with temperature was not significant. That could be explained by the fact that in spring, when the temperature is low the abundance of Rotifera increases at the expense of zooplankton, which flows into the river from floodplain lakes during the flood drainage phase. Another reason behind that is a short life-history of Rotifera. Kutikova (1970) points out that most Rotifera are eurytherms. Rotifers of the order Bdelloida are able to adapt to survival within a wide temperature range. Bērziņš and Pejler (1989a)

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concluded that rotifers generally exhibit a very wide tolerance to temperature, many common species remaining abundant at temperatures ranging from 1 to 22°C. Studies performed by Galkovskaya et al. (1988) have not confirmed the correlation between the abundance of Rotifera and water temperature. This study established that the abundance and biomass of Cladocera and Copepoda significantly positively correlate with chlorophyll-a. Rossetti et al. (2009), Kobayashi et al. (1998) also indicate a positive correlation between the abundance of zooplankton and the chlorophyll-a concentration. Zooplankton feed on different food resources – detritus, seaweeds, animals. Phytoplankton is one of zooplankton’s food resources. Many species have their typical range of favourite food. However, if such food is not available, they can feed on the food that is obtainable (Dubovskaya 2009). The availability of phytoplankton as a food resource may constrain zooplankton growth (Pace et al. 1992). Basu and Pick (1997) note that the positive relationship between chlorophyll-a and zooplankton biomass is indicative of the effect phytoplankton resource has on zooplankton. In the Daugava River studies, Paidere (2010) indicated a significant positive correlation between chlorophyll-a and the abundance of Rotifera as well as taxa. In this study, only the biomass of Rotifera was found to be significantly positively correlated with chlorophyll- a. This could be explained by the fact that Rotifera use nearly all trophic resources in water bodies: many representatives of plant and animal classes, as well as detritus (Galkovskaya et al. 1988), and therefore it is not so much dependent on the availability of phytoplankton. The low coefficient of determination for the chlorophyll-a – zooplankton relationship, however, indicates that additional factors (e.g. benthic filtration) may regulate the biomass of zooplankton. Longitudinal patterns of zooplankton could also be affected by phytoplankton availability which, in turn, could vary longitudinally in response to other planktivory and various physical and chemical factors (Thorp & Casper 2003). Undoubtedly, there is a correlation between zooplankton and dissolved oxygen in water (Grishankov & Stepanova 2009; Mikschi 1989; Ivleva 1969; Dubovskaya 2009; Lazareva 2010). However, zooplankton destruction due to the lack of oxygen in natural conditions is not very likely. In conditions of low oxygen concentration the mortality rate of zooplankton populations does not increase, just the organism growth rate decreases (Dubovskaya 2009). Among crustaceans, Cyclopoida and Cladocera better withstand the lack of oxygen (Ivleva 1969; Dubovskaya 2009). Of all zooplankton groups, the abundance of Rotifera correlates most strongly with the amount of dissolved oxygen. Rotifera do not have any respiratory or circulatory systems, therefore


they breath with all their body surface (Grishankov & Stepanova 2009; Bakaeva & Nikanorov 2006). Bērziņš and Pejler (1989b) established that most coldstenothermal rotifer species prefer an environment rich in oxygen, but there are a few exceptions. There was no significant correlation recorded between warmstenothermal rotifer species and oxygen. Active water reaction (pH) together with other environmental factors influences zooplankton division in reservoirs (Kutikova 1970; Bērziņš & Pejler 1987). However, Dubovskaya (2009) mentions that the range of pH for zooplankton existence is rather wide 5.5–10.5. However, 3.5–10.5 pH itself is not a determinative factor in Rotifera abundance, it only reflects the whole of physical-chemical and biological conditions (Bakaeva & Nikanorov 2006; Grishankov & Stepanova 2009). In acid headwater streams in southern England, water chemistry is an important predictor of the distribution of microcrustaceans (Rundle & Hildrew 1992). In this study, PO4³- had a positive correlation with an overall zooplankton abundance, especially that of Rotifera. It has to be taken into consideration that at a small concentration, the influence of phosphates on zooplankton is favourable, while at big concentrations – negative (Deksne, unpubl.). Krylov (2005), Czerniawski and Domagała (2010a), Kobayashi et al. (1998) also note that with an increase in the amount of phosphates, the abundance of zooplankton, especially that of Rotifera, grows, which is connected with the growth of Rotifera food resources. An increase in the concentration of phosphates is accompanied by a significant increase in the abundance of Bdelloidea, because these Rotifera are resistant to environmental changes. However, if pollution is excessively high, environmental toxicity increases also and, as a result, there is less food and Rotifera disappear. Krylov (2005) also specifies that with an increase in the amount of phosphates, the number of Rotifera organisms grows, which is related to an increase in the Rotifera nutritive base, especially for Bdelloida since these are more resistant to environmental changes. However, when pollution level and resultant environmental toxicity are excessively high, nutrition resources shrink causing a rapid decrease in the abundance of Rotifera. With an increase in the PO4³- concentration, the proportion of small Rotifera individuals grows resulting in a reduction of the Rotifera biomass.

Conclusions Studies of the Daugava River zooplankton show that the number of zooplankton species, abundance and biomass can differ in different river stretches and sea-


sons. These fluctuations are determined by the synergism of river abiotic and biotic factors. Out of abiotic environmental factors studied, especially important to lotic zooplankton in the Daugava River are: 1) thermal conditions, 2) hydrological regime, 3) chlorophyll-a and 4) phosphates. The lotic system is considered to be very impermanent and conditions that influence zooplankton are varied and changeable. As a result, data from year to year can differ considerably. Therefore the study of the lotic system requires abundant data and thorough long-term research.

Acknowledgements The author would like to thank Dr Biol. Renāte Škute for her help with the identification of zooplankton. This work has been supported by the European Social Fund within the Project ‘Support for the implementation of doctoral studies at Daugavpils University’. Agreement No 2009/0140/1DP/1.1.2.1.2/09/IPIA/VIAA/015.

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Ekologinių bei hidrologinių veiksnių įtaka Dauguvos upės zooplanktono bendrijai R. Deksne, A. Škute Santrauka Ištirta koreliacija tarp Dauguvos vidupio zooplanktono bendrijos kiekybinių ir kokybinių rodiklių dinamikos bei aplinkos veiksnių kaitos. Buvo nustatyta, kad zooplanktono taksonų gausos bei biomasės pokyčiams ženklią įtaką turi terminės sąlygos, hidrologinis režimas, chlorofilo-a ir fosfatų kiekis. Konstatuota, kad aplinkos veiksniai (šviesos režimas, ištirpusio deguonies kiekis, laidumas, pH, oksidacijos redukcijos potencialas, nitratų kiekis, cheminis deguonies poreikis) gali įtakoti zooplanktono pokyčius Dauguvos upėje. Received: 30 March 2011 Accepted: 6 June 2011