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南京玄武湖浮游细菌群落结构的季节变化及其与环境因子的关系
引用本文:沈烽,赵大勇,黄睿,王司辰,曹新益,徐慧敏,曾巾,余钟波. 南京玄武湖浮游细菌群落结构的季节变化及其与环境因子的关系[J]. 湖泊科学, 2017, 29(3): 662-669
作者姓名:沈烽  赵大勇  黄睿  王司辰  曹新益  徐慧敏  曾巾  余钟波
作者单位:河海大学水文水资源与水利工程科学国家重点实验室 南京 210098;河海大学水文水资源学院 南京 210098,河海大学水文水资源与水利工程科学国家重点实验室 南京 210098;河海大学水文水资源学院 南京 210098,河海大学水文水资源与水利工程科学国家重点实验室 南京 210098;河海大学水文水资源学院 南京 210098,河海大学水文水资源与水利工程科学国家重点实验室 南京 210098;河海大学水文水资源学院 南京 210098,河海大学水文水资源与水利工程科学国家重点实验室 南京 210098;河海大学水文水资源学院 南京 210098,河海大学水文水资源与水利工程科学国家重点实验室 南京 210098;河海大学水文水资源学院 南京 210098,中国科学院南京地理与湖泊研究所湖泊与环境国家重点实验室 南京 210008,河海大学水文水资源与水利工程科学国家重点实验室 南京 210098;河海大学水文水资源学院 南京 210098
基金项目:国家自然科学基金项目(41371098,41571108);水文水资源与水利工程科学国家重点实验室专项研究经费项目(20145027312,20155019012);中央高校基本科研业务费项目(2015B14214);湖泊与环境国家重点实验室开放基金项目(2014SKL010)
摘    要:应用16S rRNA基因末端限制性片段长度多态性技术和多元统计方法,探究了南京玄武湖浮游细菌群落结构的季节性变化,并找出了浮游细菌群落组成分布的主要影响因子.结果表明,玄武湖4个季节中夏季Invsimpson指数、Shannon-Wiener指数和Pielou指数最高,而春季最低.非度量多维尺度分析结果显示浮游细菌群落结构存在着明显的季节性变化.Mantel检验、典范对应分析、变量分割分析表明影响玄武湖细菌群落结构最显著的环境因子为温度,其次为pH.营养盐浓度对玄武湖细菌群落结构的影响不显著.总的来说,本研究将有助于更好地理解富营养化水体中的浮游细菌群落组成的季节变化规律.

关 键 词:浮游细菌  末端限制性片段长度多态性技术  多元统计  玄武湖
收稿时间:2016-03-23
修稿时间:2016-07-13

Seasonal variation of bacterioplankton community structure in Xuanwu Lake(Nanjing) and its relationship with environmental factors
SHEN Feng,ZHAO Dayong,HUANG Rui,WANG Sichen,CAO Xinyi,XU Huimin,ZENG Jin and YU Zhongbo. Seasonal variation of bacterioplankton community structure in Xuanwu Lake(Nanjing) and its relationship with environmental factors[J]. Journal of Lake Science, 2017, 29(3): 662-669
Authors:SHEN Feng  ZHAO Dayong  HUANG Rui  WANG Sichen  CAO Xinyi  XU Huimin  ZENG Jin  YU Zhongbo
Affiliation:State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, P.R.China;College of Hydrology and Water Resources, Hohai University, Nanjing 210098, P.R.China,State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, P.R.China;College of Hydrology and Water Resources, Hohai University, Nanjing 210098, P.R.China,State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, P.R.China;College of Hydrology and Water Resources, Hohai University, Nanjing 210098, P.R.China,State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, P.R.China;College of Hydrology and Water Resources, Hohai University, Nanjing 210098, P.R.China,State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, P.R.China;College of Hydrology and Water Resources, Hohai University, Nanjing 210098, P.R.China,State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, P.R.China;College of Hydrology and Water Resources, Hohai University, Nanjing 210098, P.R.China,State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, P.R.China and State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, P.R.China;College of Hydrology and Water Resources, Hohai University, Nanjing 210098, P.R.China
Abstract:To explore the seasonal variations of bacterioplankton community structure in Xuanwu Lake and identify the main factors affecting bacterioplankton community composition, the bacterial 16S rRNA terminal restriction fragment length polymorphism technology and multivariate statistical methods were applied. The results show that the Invsimpson, Shannon-Wiener and Pielou indexes were the highest in summer, and the lowest in spring. Nonmetric multidimensional scaling analysis showed that bacterioplankton community structure exhibited a seasonal pattern. Mantel test, canonical correlation analysis and variation partitioning analysis show that the most significant environmental factor on the bacterioplankton community structure was temperature, and followed factor was pH. The influence of nutrient concentration was not significant. Overall, this study will be helpful for better understanding of the bacterioplankton community composition in eutrophic lakes.
Keywords:Bacterioplankton  terminal restriction fragment length polymorphism technology  multivariate analysis  Xuanwu Lake
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