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水库水深变化对不同浮游微生物群落及网络互作关键种的影响
引用本文:王洵,廖琴,王沛芳,袁秋生,胡斌,邢小蕾,徐浩森.水库水深变化对不同浮游微生物群落及网络互作关键种的影响[J].环境科学,2023,44(7):3881-3891.
作者姓名:王洵  廖琴  王沛芳  袁秋生  胡斌  邢小蕾  徐浩森
作者单位:河海大学浅水湖泊综合治理与资源开发教育部重点实验室, 南京 210098;河海大学环境学院, 南京 210098
基金项目:国家自然科学基金青年科学基金项目(42007149);中央高校基本科研业务费专项(B230201026);江苏省环洪泽湖生态农业生物技术重点实验室开放课题项目(HZHLAB2301);国家自然科学基金重大研究计划重点支持项目(92047201);国家自然科学基金重大研究计划集成项目(92047303)
摘    要:为揭示水库水深变化对不同浮游微生物类群多样性及生态网络的影响,于2021年在横山水库采集表层及深层水样,利用16S和18S rDNA分子标记进行高通量测序,探究水深变化对不同微生物类群群落结构、种间互作网络和关键种的影响机制.结果发现,横山水库表层(0.5 m)和深层(5 m)中细菌群落多样性(Richness、 Simpson、 Shannon和Pielou’s Evenness指数)均高于真核微生物群落.细菌群落在不同水深处的主要优势物种为变形菌门、放线菌门和拟杆菌门,其相对丰度在门水平上无明显差异;真核微生物群落在不同水深处群落组成基本相同,但其相对丰度差异较大,包括节肢动物门、纤毛门和淡色藻门等.此外,表层水体微生物网络的图密度、平均聚类系数等均高于深层,表明表层微生物物种间具有较强的关联性,能够较好地传递物质、能量和信息,且对外界变化的响应速度更快;细菌群落分子生态网络节点和边的数量、关键物种数目和种类均高于真核微生物群落,表明细菌群落网络规模更大,种间协同合作关系和网络连通性更强.不同水深处的细菌群落和真核微生物群落间相互作用皆以正相关为主导,两个类群在水库深层的负相关性均...

关 键 词:水库  细菌  真核微生物  共现网络  关键物种
收稿时间:2022/8/21 0:00:00
修稿时间:2022/10/17 0:00:00

Effects of Reservoir Water Depth on Different Plankton Communities and Keystone Species of Network Interaction
WANG Xun,LIAO Qin,WANG Pei-fang,YUAN Qiu-sheng,HU Bin,XING Xiao-lei,XU Hao-sen.Effects of Reservoir Water Depth on Different Plankton Communities and Keystone Species of Network Interaction[J].Chinese Journal of Environmental Science,2023,44(7):3881-3891.
Authors:WANG Xun  LIAO Qin  WANG Pei-fang  YUAN Qiu-sheng  HU Bin  XING Xiao-lei  XU Hao-sen
Institution:Key Laboratory of Integrated Regulation and Resource Development on Shallow Lakes, Ministry of Education, Hohai University, Nanjing 210098, China;College of Environment, Hohai University, Nanjing 210098, China
Abstract:In order to understand the impacts of the reservoir construction on the diversity and ecological network of different microbial communities, seven sampling sites were set up in the Hengshan Reservoir in 2021. Water samples were collected from the surface and bottom of the reservoir. After filtering and extracting total DNA samples, high-throughput sequencing was carried out based on 16S and 18S rDNA to investigate the response of community structure, molecular ecological network, and keystone species of different microbial groups to water environment changes. The results showed that the Richness, Simpson, Shannon, and Pielou''s Evenness indices of bacterial community in the surface and bottom layers were higher than those in the eukaryote community. The dominant community of bacteria included Proteobacteria, Actinobacteria, and Bacteroidetes, and the eukaryote community included Arthropoda, Ciliophora, Ochrophyta, etc. Moreover, the density and average clustering coefficient of the microbial networks in the surface waters of different phytoplankton communities were higher than those in the bottom waters. It was also observed that the microbial ecological networks in the surface waters were more closely related, and the number of nodes and edges, as well as the number of keystone species, of bacterial communities in the surface and bottom layers were significantly higher than those in the eukaryote microbial communities, indicating that the bacterial community network was larger, and the cooperative relationship and network connectivity between species were stronger. The interaction between bacterial community and eukaryote community in different water depths was dominated by positive correlation, and the negative correlation of the two groups in the bottom layer was slightly greater than that in the surface, indicating that the competition between bottom-layer species was greater than that between surface-layer species. In addition, the environmental impact factors of all species and keystone species of the community in surface water were basically the same, but they differed greatly in deep water, indicating that the influence mechanism of water depth change on keystone species was not the same as that of all species. The results further revealed the effects of reservoir construction on the stability and interspecific interactions of different microbial communities and provided a theoretical basis for predicting variations in microbial community and material cycling in reservoirs.
Keywords:reservoir  bacteria  eukaryotic microbes  co-occurrence network  keystone species
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