Modeling species richness and abundance of phytoplankton and zooplankton in radioactively contaminated water bodies

Publication date: December 2018
Source:Journal of Environmental Radioactivity, Volume 192
Author(s): Igor Shuryak
Water bodies polluted by the Mayak nuclear plant in Russia provide valuable information on multi-generation effects of radioactive contamination on freshwater organisms. For example, lake Karachay was probably the most radioactive lake in the world: its water contained ∼2 × 10⁷ Bq/L of radionuclides and estimated dose rates to plankton exceeded 5 Gy/h. We performed quantitative modeling of radiation effects on phytoplankton and zooplankton species richness and abundance in Mayak-contaminated water bodies. Due to collinearity between radioactive contamination, water body size and salinity, we combined these variables into one (called HabitatFactors). We employed a customized machine learning approach, where synthetic noise variables acted as benchmarks of predictor performance. HabitatFactors was the only predictor that outperformed noise variables and, therefore, we used it for parametric modeling of plankton responses. Best-fit model predictions suggested 50% species richness reduction at HabitatFactors values corresponding to dose rates of 10⁴-10⁵ μGy/h for phytoplankton, and 10³-10⁴ μGy/h for zooplankton. Under conditions similar to those in lake Karachay, best-fit models predicted 81-98% species richness reductions for various taxa (Cyanobacteria, Bacillariophyta, Chlorophyta, Rotifera, Cladocera and Copepoda), ∼20-300-fold abundance reduction for total zooplankton, but no abundance reduction for phytoplankton. Rotifera was the only taxon whose fractional abundance increased with contamination level, reaching 100% in lake Karachay, but Rotifera species richness declined with contamination level, as in other taxa. Under severe radioactive and chemical contamination, one species of Cyanobacteria (Geitlerinema amphibium) dominated phytoplankton, and rotifers from the genus Brachionus dominated zooplankton. The modeling approaches proposed here are applicable to other radioecological data sets. The results provide quantitative information and easily interpretable model parameter estimates for the shapes and magnitudes of freshwater plankton responses to a wide range of radioactive contamination levels.



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