文献类型： 外文期刊

作者： Xin, Yuan ¹ ; Zhang, Junya ² ; Lu, Tiedong ⁵ ; Wei, Yuansong ² ; Shen, Peihong ¹ ;

作者机构： 1.Guangxi Univ, Coll Life Sci & Technol, Guangxi Res Ctr Microbial & Enzyme Engn Technol, State Key Lab Conservat & Utilizat Subtrop Agrobio, Nanning 530005, Guangxi, Peoples R China

2.Chinese Acad Sci, Res Ctr Ecoenvironm Sci, State Key Joint Lab Environm Simulat & Pollut Cont, Beijing 100085, Peoples R China

3.Helmholtz Ctr Environm Res, Dept Isotope Biogeochem, UFZ, D-04318 Leipzig, Germany

4.Univ Chinese Acad Sci, Beijing 100049, Peoples R China

5.Guangxi Acad Agr Sci, Inst Agr Resources & Environm, Nanning 530007, Guangxi, Peoples R China

关键词： Reservoir; Heavy rainfall; Prokaryotic community; Eukaryotic community; Algal community

期刊名称：JOURNAL OF ENVIRONMENTAL MANAGEMENT （ 影响因子：8.7； 五年影响因子：8.4 ）

ISSN： 0301-4797

年卷期： 2023 年 334 卷

页码：

收录情况： SCI

摘要： The global climate change made the heavy rainfall happen more frequently, and the non-point source pollution caused by it would exacerbate the risk to the water ecological environment. In this study, we took a reservoir (Shahe reservoir, Beijing, China) supplied with reclaimed water as an exapmle to investigate how spatiotemporal changes in the quantity and diversity of prokaryotic, eukaryotic, and algal communities respond to heavy rainfall. Results showed that heavy rainfall could directly impact the composition of the prokaryotic community by introducing amounts of runoff closely associated bacterium especially for the human potential pathogens such as Aliarcobacter, Aeromonas and Pseudomonas in the Shahe reservoir area. While the eukaryotic community was rather stable, and the development and changes in algal communities occurred in the last few days after heavy rainfall. The microbial source tracking through FEAST indicated that Nansha river (S) was the major contributor to the development of all the three concerned communities in the reservoir. The co-occurrence analysis showed that the modules with the highest cumulative abundance in each community were all strongly and positively connected with Chl-a, pH, turbidity, COD and TOC, but negatively correlated with NO3-N (p < 0.01). The network analysis showed that the eukaryotes played a key role in the interaction network among the three communities, and were more likely to interact with algae and prokaryotes. It was suggested that the controlling of human potential pathogens associated with prokaryotic community should be emphasized at the beginning of the heavy rainfall, but the prevention of the eutrophication bloom should be another focus after the heavy rainfall. This study provided valuable information concerning the role of heavy rainfall on the water ecological environment from the perspective of microbial community.