The ecological environment of plateau lakes is very sensitive to temperature changes. Higher temperatures accelerate the cycling processes between lake sediments and water nutrients. Quantitatively investigating the influence mechanism of regional climate change and sediment phosphorus release over a long time series is difficult in revealing the causes of eutrophication in plateau lakes. This paper quantitatively reveals the long-term response mechanism of endogenous phosphorus release to temperature change in Dianchi, the largest plateau eutrophic lake in China, based on nearly 50 years of temperature and sediment phosphorus data from 1964 to 2013, and taking advantage of the Random Forest machine learning algorithm for deep processing of long time series and nonlinear relation. The results showed that: (1) Over the past 50 years, endogenous phosphorus release and temperature showed no trend for 22 years, followed by a consistent, significant increase in both after 1986. (2) Random Forest analysis showed that before the increase of temperature, the contribution to the phosphorus release was weak, while after the mutation, the contribution reached 52.6%, and typically was concentrated from March to August each year. (3) The response relationship between temperature and endogenous phosphorus release had non-linear variation with a threshold interval of 18.3 °C-19.2 °C. This research aims to explore the theoretical scientific knowledge of endogenous phosphorus release processes and complex mechanisms in plateau lakes under changing environments, and further explores the effects of long-term temperature variability on endogenous phosphorus loading in plateau lakes. That is, long-term temperature mutations can alter the internal cycling processes of sedimentary phosphorus by stimulating algal growth, which have a more drastic effect than short-term temperature variations.
Keywords: Climate change; Dianchi lake; Eutrophication; Random forests (RF); Sediment phosphorus; Temperature.
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