, Volume 605, Issue 1, pp 99–112 | Cite as

Community analysis of Belarusian lakes: correlations of species diversity with hydrochemistry

  • Alexander Y. Karatayev
  • Lyubov E. Burlakova
  • Stanley I. Dodson
Primary research paper


Our purpose was to explore relationships of freshwater planktonic and benthic community species richness with water chemistry parameters using a dataset of biological, chemical, and physical data from 550 lakes. This was done using multivariate (ordination), graphical, and correlation analyses. Although the lakes are rather similar in location (Belarus) and in being mostly eutrophic, they do show variations in water chemistry. We ordinated lakes by water chemistry variables, and then looked for correlations between the ordination axes and species richness in 10 taxonomic groups: Cyanobacteria, Chlorophyta, Bacillariophyta, Cladocera, Copepoda, Rotatoria, Mollusca, Trichoptera, Chironomidae, and aquatic macrophytes. The first four Principal Components Analysis (PCA) axes explained about 67% of the total variability in water chemistry. The axes represent water hardness (DIC, dissolved inorganic carbon), organic content (DOC, dissolved organic carbon), nutrients, and chlorides and sulfates. The PCA ordination revealed environmental gradients, but not the distinctive clusters of lakes. Species richness was most strongly correlated with the first PCA axis (DIC), which accounted for 29% of the total variation in water chemistry. Species richness was positively correlated with DIC for eight of 10 taxonomic categories. The second PCA axis (DOC), which accounted for 20% of total variation in water chemistry, was correlated with species richness in the three phytoplankton groups, and with chironomid species richness. The third PCA axis (nutrients, especially nitrogen, 11%) was correlated with species richness of copepoda, chironomids, and macrophytes. The fourth PCA axis (chloride and sulfate) accounted for only 7% of the total variance in water chemistry, and was significantly negatively correlated with species richness of rotifers, molluscs, and chironomids. In addition to these linear correlations, there were several significant non-linear relationships. DIC variables showed curvilinear (hump-shaped) relationship with benthos (all groups combined) and especially with molluscs, and DOC variables—with phytoplankton and benthos. Each community, and often separate taxonomic groups within community have their own optimal ranges of chemical concentrations, and various water chemistry variables showed significant curvilinear relationships with biodiversity, suggesting that the diversity of different major aquatic groups may be influenced by different chemicals.


Phytoplankton Zooplankton Zoobenthos Hydrochemistry Biodiversity 



We thank the faculty and staff of Lakes Research Laboratory and General Ecology Department of Belarusian State University, who took part in the data collection and analysis. The Center for Limnology, University of Wisconsin, provided facilities for data analysis, and Dodson was supported by NSF LTER grant # DEB-9632–853.


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Copyright information

© Springer Science+Business Media B.V. 2008

Authors and Affiliations

  • Alexander Y. Karatayev
    • 1
  • Lyubov E. Burlakova
    • 1
  • Stanley I. Dodson
    • 2
  1. 1.Great Lakes CenterBuffalo State CollegeBuffaloUSA
  2. 2.Zoology Department-Birge HallUniversity of WisconsinMadisonUSA

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