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Phytoplankton Sensitivity to Heavy Metals in Baltic Coastal Lakes

Author

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  • Monika Szymańska-Walkiewicz

    (Department of Hydrobiology, University of Kazimierz Wielki in Bydgoszcz, 85-090 Bydgoszcz, Poland)

  • Katarzyna Glińska-Lewczuk

    (Department of Water Resources and Climatology, University of Warmia and Mazury in Olsztyn, 10-719 Olsztyn, Poland)

  • Paweł Burandt

    (Department of Water Resources and Climatology, University of Warmia and Mazury in Olsztyn, 10-719 Olsztyn, Poland)

  • Krystian Obolewski

    (Department of Hydrobiology, University of Kazimierz Wielki in Bydgoszcz, 85-090 Bydgoszcz, Poland)

Abstract

This study aimed to compare concentrations of chlorophyll-a between individual phytoplankton groups for four shallow Baltic coastal lakes, varying in type of connection with the sea. For two years, the research focused on quantifying the effects of abiotic factors—concentrations of heavy metals (Ba, Bi, Cr, Cu, Mn, Fe, Ni, Pb, and Zn) and hydrological connectivity—on phytoplankton composition, biomass, and photosynthetic activity. Our results show that hydrological factors are the main predictors of phytoplankton structure. The lakes differed in salinity: freshwater vs. brackish vs. transitional lakes. Irrespective of lake type, the dominant group was that of Cyanobacteria (~80%), but their percentage contribution was lower in the brackish lake. Baltic seawater intrusion resulted in a decrease in heavy-metal concentrations in lake water for Fe, Zn, Pb, and Bi. Redundancy analysis (RDA) suggested positive effects of some heavy metals on the biomass of the Chlorophyta and Bacillariophyta. For the Cryptophyta only, a slight decrease in biomass was linked with increased metal concentrations in open water.

Suggested Citation

  • Monika Szymańska-Walkiewicz & Katarzyna Glińska-Lewczuk & Paweł Burandt & Krystian Obolewski, 2022. "Phytoplankton Sensitivity to Heavy Metals in Baltic Coastal Lakes," IJERPH, MDPI, vol. 19(7), pages 1-13, March.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:7:p:4131-:d:784010
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    References listed on IDEAS

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    2. Simon N. Wood, 2004. "Stable and Efficient Multiple Smoothing Parameter Estimation for Generalized Additive Models," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 673-686, January.
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