基于GAM模型的硅藻群落与环境因子相关性分析  

Analysis on correlation of diatom community and environmental factors in Longjiang River based on GAM model

作　　者：杨佳星 蔡德所[1,2] 姚文婷[1] 张昆 散剑娣 YANG Jiaxing;CAI Desuo;YAO Wenting;ZHANG Kun;SAN Jiandi(College of Hydraulic and Environment,China Three Gorges University,Yichang 443000,China;Guangxi Water Resources and Electric Power Survey and Design Institute,Nanning 530023,China)

机构地区：[1]三峡大学水利与环境学院,湖北宜昌443000 [2]广西水利电力勘测设计研究院,广西南宁530023

出　　处：《人民长江》2020年第6期43-48,共6页Yangtze River

基　　金：国家自然科学基金项目(40971280)。

摘　　要：底栖硅藻水质生物监测技术是被广泛研究与使用的一种监测河流水质及生态质量的理想手段。通过将CCA排序和GAM分析两种方法相结合,分析了对龙江区域河流附生硅藻群落分布影响较大的环境因子。GAM模型画出了各个水环境因子对硅藻完整性指数IBI的响应机制,偏CCA分析进一步确认了营养盐因子对河流硅藻群落的重要性。将两种方法的结果进行比较,最终得出营养盐和电导率是影响龙江附生硅藻群落结构变化的主要因子,流速和水温为次要影响因子。两种分析方法相结合增加了结果的可靠性。The diatom water quality biological monitoring technology is an ideal method for monitoring river water quality and ecological quality.Through the combination of CCA ranking and GAM analysis,the main environmental factors influencing the distribution of diatom communities in the Longjiang River were analyzed.The GAM model decribed the response mechanism of various water quality factors to the diatom integrity index IBI.The partial CCA analysis further confirmed the importance of nutrient factor to the river diatom community.The results of the two methods were compared,and the results showed that the nutrient and electrical conductivity were the main factors affecting the diatom community in Longjiang River,and the flow rate and water temperature were the secondary factors.The combination of the two analysis methods increased the reliability of the results.

关 键 词：硅藻群落 CCA排序 GAM模型 营养因子 IBI指数 龙江 

分 类 号：X823[环境科学与工程—环境工程] Q89[生物学]