SPATIAL-TEMPORAL DISTRIBUTION OF PHYTOPLANKTON IN WAIHAI OF DIANCHI LAKE AND ITS NONLINEAR CORRELATION ANALYSIS WITH ENVIRONMENTAL FACTORS

Algal bloom caused by eutrophication is a serious ecological problem in the Waihai of Dianchi Lake. Due to the difficulties in calculating the nonlinear relationship between environmental factors and phytoplankton, traditional correlation methods have difficulties disentangling the driving factors of algal blooms. To nonlinearly understand the complex relationship, This study analyzed the temporal and spatial distribution of phytoplankton and quantitatively assessed the nonlinearity between environmental factors and phytoplankton using Maximal Information Coefficient (MIC) based on the monitoring data (2014—2020) in Waihai of Dianchi Lake. The main results were as follows: (1) The algae density was obviously high in the north and low in the south in Waihai of Dianchi Lake. Cyanobacteria dominated among all algae, and the highest proportion of algae density was in summer. The proportion of algae of Chlorophyta was inferior to that of Cyanobacteria but much higher than other algae. The proportion of algae density in spring was the highest among all seasons; (2) In general, there was an obvious linear relationship between the algae density and variables, and the nonlinear relationship between the algae density and the cause variable was more significant than the linear relationship; (3) Water temperature (MIC: 0.27, P<0.01) and ammonia nitrogen (MIC: 0.22, P<0.01) were the mainly driving factors of water quality of Cyanobacteria. Compared with other nitrogen sources, ammonia nitrogen has a greater impact on Cyanobacteria. Total phosphorus (MIC: 0.27, P<0.01) and total nitrogen (MIC: 0.21, P<0.01) were the driving factors of water quality of Chlorophyta, and the influence of other forms of nitrogen on Chlorophyta may be stronger than ammonia nitrogen. In meteorological conditions, Cyanobacteria and Chlorophyta were mainly controlled by temperature and radiation. This study applied a novel statistical measurement of the correlation coefficient to calculate the nonlinearity between environmental factors and phytoplankton, providing a new perspective and theoretical basis for the quantitative analysis of lake eutrophication.