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施凤宁, 阳辉, 刘湘伟, 王雨春, 苏禹铭, 胡明明, 包宇飞, 李姗泽, 温洁. 滇池外海藻类时空分布及其与环境因素间非线性相关分析[J]. 水生生物学报, 2022, 46(7): 1070-1079. DOI: 10.7541/2022.2021.0159
引用本文: 施凤宁, 阳辉, 刘湘伟, 王雨春, 苏禹铭, 胡明明, 包宇飞, 李姗泽, 温洁. 滇池外海藻类时空分布及其与环境因素间非线性相关分析[J]. 水生生物学报, 2022, 46(7): 1070-1079. DOI: 10.7541/2022.2021.0159
SHI Feng-Ning, YANG Hui, LIU Xiang-Wei, WANG Yu-Chun, SU Yu-Ming, HU Ming-Ming, BAO Yu-Fei, LI Shan-Ze, WEN Jie. SPATIAL-TEMPORAL DISTRIBUTION OF PHYTOPLANKTON IN WAIHAI OF DIANCHI LAKE AND ITS NONLINEAR CORRELATION ANALYSIS WITH ENVIRONMENTAL FACTORS[J]. ACTA HYDROBIOLOGICA SINICA, 2022, 46(7): 1070-1079. DOI: 10.7541/2022.2021.0159
Citation: SHI Feng-Ning, YANG Hui, LIU Xiang-Wei, WANG Yu-Chun, SU Yu-Ming, HU Ming-Ming, BAO Yu-Fei, LI Shan-Ze, WEN Jie. SPATIAL-TEMPORAL DISTRIBUTION OF PHYTOPLANKTON IN WAIHAI OF DIANCHI LAKE AND ITS NONLINEAR CORRELATION ANALYSIS WITH ENVIRONMENTAL FACTORS[J]. ACTA HYDROBIOLOGICA SINICA, 2022, 46(7): 1070-1079. DOI: 10.7541/2022.2021.0159

滇池外海藻类时空分布及其与环境因素间非线性相关分析

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

  • 摘要: 文章基于滇池外海监测数据(2014—2020), 分析了滇池外海不同区域间的藻类分布情况, 并运用最大信息系数(Maximal Information Coefficient, MIC)定量分析了滇池外海中环境因素与藻类间的非线性关系。主要结果如下: (1)滇池外海藻密度呈现明显的北高南低的趋势, 蓝藻在所有藻类中占绝对优势, 且主要在夏季表现出最高的藻类密度占比, 绿藻的藻类占比次于蓝藻但远高于其他藻类且在春季的藻类占比相对最高; (2)总体上藻类密度与结果变量存在明显的线性关系, 同时与原因变量间的非线性关系显著; (3)蓝藻的水质驱动因素主要为水温(MIC: 0.27, P<0.01)和氨氮(MIC: 0.22, P<0.01), 且相较于其他氮源, 氨氮对蓝藻的影响更大。绿藻的水质驱动因素主要为总磷(MIC: 0.27, P<0.01)和总氮(MIC: 0.21, P<0.01), 其他形态的氮对绿藻的影响可能较氨氮更强。在气象条件中, 蓝藻和绿藻主要受气温及辐射量的控制。

     

    Abstract: 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.

     

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