4.7 Article

Nitrate as a predictor of cyanobacteria biomass in eutrophic lakes in a climate change context

Journal

SCIENCE OF THE TOTAL ENVIRONMENT
Volume 818, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.scitotenv.2021.151807

Keywords

Eutrophication; Nitrogen; Land use; cyanobacteria; Empirical modelling; Fertilizer; Catchment model

Funding

  1. Estonian Research Council [PSG32, PRG709, PRG1167]
  2. European Regional Development Fund through Estonian-University of Life Sciences ASTRA project Valuechain based bio-economy
  3. European Union [951963]
  4. Estonian Scholarship Programme for international students, researchers and academic staff (Archimedes)

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The study aimed to predict cyanobacteria biomass and nitrate concentrations in Lake Vortsjarv, Estonia. A model chain combining a mechanistic model and an empirical, generalized linear model was used to achieve this. The models successfully predicted the variations in cyanobacteria biomass and nitrate concentrations, providing results for different scenarios. The findings underscore the significance of reducing anthropogenic pressures on lake catchments to mitigate the proliferation of harmful pollutants and microalgae.
We aimed to predict cyanobacteria biomass and nitrate (NO3-) concentrations in Lake Vortsjarv, a large, shallow, and eutrophic lake in Estonia. We used a model chain based on the succession of a mechanistic (INCA-N) model and an empirical, generalized linear model. INCA-N model calibration and validation was performed with long term climate and catchment parameters. We constructed twelve scenarios as combinations of climate forcing from the Intergovernmental Panel on Climate Change (IPCC, 3 scenarios), land conversion (forest to agriculture, 2 scenarios), and fertilizer use (2 scenarios). Models predicted 46% of the variance of cyanobacteria biomass and 65% of that of NO3- concentrations. The model chain simulated that scenarios comprising both forest conversion to agricultural lands and a greater use of fertilizer per surface area unit would cause increases in lacustrine NO3- (up to twice the historical mean) and cyanobacteria biomass (up to a four-fold increase compared to the historical mean). The changes in NO3- concentrations and cyanobacteria biomass were more pronounced in low and moderate warming scenarios than in high warming scenarios because of increased denitrification rates in a warmer climate. Our findings show the importance of reducing anthropogenic pressures on lake catchments in order to reduce harmful pollutant and microalgae proliferation, and highlight the counterintuitive effects of multiple stressor interactions on lake functioning. (C) 2021 Elsevier B.V. All rights reserved.

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