Factors controlling the three-decade long rise in cyanobacteria biomass in a eutrophic shallow lake
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Kuupäev
2018
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Kirjastaja
Elsevier
Abstrakt
We aimed at quantifying the importance of limnological variables in the decadal rise of cyanobacteria biomass in
shallow hemiboreal lakes. We constructed estimates of cyanobacteria (blue-green algae) biomass in a large, eutrophic lake (Estonia, Northeastern Europe) from a database comprising 28 limnological variables and spanning
more than 50 years of monitoring. Using a dual-model approach consisting in a boosted regression trees (BRT)
followed by a generalized least squares (GLS) model, our results revealed that six variables were most influential
for assessing the variance of cyanobacteria biomass. Cyanobacteria response to nitrate concentration and rotifer
abundance was negative, whereas it was positive to pH, temperature, cladoceran and copepod biomass. Response
to total phosphorus (TP) and total phosphorus to total nitrogen ratio was very weak, which suggests that actual
in-lake TP concentration is still above limiting values. The most efficient GLS model, which explained nearly two
thirds (r2 = 0.65) of the variance of cyanobacteria biomass included nitrate concentration, water temperature
and pH. The very high number of observations (maximum n = 525) supports the robustness of the models.
Our results suggest that the decadal rise of blue-green algae in shallow lakes lies in the interaction between cultural eutrophication and global warming which bring in-lake physical and chemical conditions closer to
cyanobacteria optima.
This research was supported by Start-Up Per- sonal Research Grant PUT 777 to FC and IUT 21-2 of the Estonian Ministry of Education and Research and by MARS project (Managing Aquatic ecosystems and water Resources under multiple Stress) funded under the EU 7th Framework Programme, Theme 6 (Environment including Climate Change), Contract No.: 603378 (http://www.mars- project.eu).
This research was supported by Start-Up Per- sonal Research Grant PUT 777 to FC and IUT 21-2 of the Estonian Ministry of Education and Research and by MARS project (Managing Aquatic ecosystems and water Resources under multiple Stress) funded under the EU 7th Framework Programme, Theme 6 (Environment including Climate Change), Contract No.: 603378 (http://www.mars- project.eu).
Kirjeldus
Märksõnad
phytoplankton, nitrates, boosted regression trees, generalized least squares model, zooplankton, Estonia, articles