Abstract

The increasing global occurrence of cyanobacterial blooms, attributed primarily to human-induced nutrient enrichment, significantly degrades freshwater ecosystems and poses serious risks to human health. The current study examined environmental variables and cyanobacterial biovolume (BCyano) of 28 shallow lakes in the eastern China plains during the spring and summer of 2018. We used a 95% quantile regression model to explore season-specific response of BCyano to total nitrogen (TN), or total phosphorus (TP), and robust linear relationships were observed between log(BCyano+0.001) and log(TN), or log(TP) in both spring and summer periods. Based on these regressions, regional-scale and season-specific TN and TP thresholds are proposed for these lakes to ensure the safety for recreational waters and drinking water source. However, actual BCyano for a given concentration of TN (or TP) for many observations were considerably lower than the results of the 95% regression model predict, indicating that other factors significantly modulated nutrient limitation of BCyano. Generalized additive model and quantile regression model were used together to explore potentially significant modulating factors, of which lake retention time, macrophytes cover and N: P ratio were identified as most important. Thus, it is necessary to develop type-specific nutrient thresholds with the consideration of these significant modulating factors. Furthermore, nutrient-BCyano relationships of our studied lakes with lake retention time>100 days and no macrophyte were further explored and nutrient thresholds of this lake type were proposed. Nutrient thresholds proposed in this study may play an essential role in achieving a cost-effective eutrophication management for shallow lakes both in the eastern China plains and elsewhere with similar climatic background. On a broader scale, the approaches and findings of this study may provide valuable reference to formulate reasonable nutrient reduction targets for other ecoregions with different climatic conditions.

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