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Gradient rise in seepage pollution levels in tailings ponds shapes closer linkages between phytoplankton and bacteria

文献类型： 外文期刊

作者： Geng, Yuchen 1 ; Peng, Chengrong 1 ; Zhou, Weicheng 1 ; Huang, Shun 1 ; Zhou, Panpan 1 ; Wang, Zhicong 1 ; Qin, Hongjie 2 ; Li, Dunhai 1 ;

作者机构： 1.Chinese Acad Sci, Inst Hydrobiol, Key Lab Algal Biol, Wuhan 430072, Peoples R China

2.Guangdong Acad Agr Sci, Environm Hort Res Inst, Guangdong Key Lab Comprehens Innovat Utilizat Orna, Guangzhou 510640, Peoples R China

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

关键词： Phytoplankton-bacteria interaction; Seepage pollution; Spatiotemporal scales; Tailings pond

期刊名称：JOURNAL OF HAZARDOUS MATERIALS （ 影响因子：14.224； 五年影响因子：12.984 ）

ISSN： 0304-3894

年卷期： 2022 年 437 卷

页码：

收录情况： SCI

摘要： A large number of tailings ponds formed by slag accumulation have become serious environmental hazards. Spatially high potential energy and long-term accumulation may result in gradient-changing seepage pollution. The assemblages of phytoplankton and bacteria are widely used as assessment indicators. In this study, we investigate the changes in phytoplankton and bacterial assemblages in tailing pollution. The results showed that there are temporal and spatial variabilities in seepage pollution. The abundance and diversity of phytoplankton and bacteria decreased with increasing pollution. However, Synedra acus (diatom) and Polynucleobacter (bacteria) were positively correlated with pollution levels (r = 0.37, P < 0.05; r = 0.24, P < 0.05). Heavy metals are the main contributors to bacterial changes (16.46%), while nutrients are for algae (13.24%). Tailings pond pollution reduced the number of phytoplankton and bacterial linkages. However, more pollution broke the originally independent modules of phytoplankton and bacteria, and they produced more positive correlations (79.39%; 87.68%). Microcystis sp. and Limnobacter were the key nodes of the co-occurrence network in the polluted areas. Exploring the interactions between bacteria and phytoplankton within different pollution levels could provide insights into biological interaction patterns and the bioremediation of tailings ponds.

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