河北大学学报(自然科学版) ›› 2016, Vol. 36 ›› Issue (3): 278-285.DOI: 10.3969/j.issn.1000-1565.2016.03.010

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基于RDA的白洋淀浮游植物群落动态特征分析

刘存歧,孔祥玲,张治荣,田志富   

  • 收稿日期:2015-07-25 出版日期:2016-05-25 发布日期:2016-05-25
  • 作者简介:刘存歧(1967-),男,河北昌黎人,河北大学教授,主要从事水域生态学研究. E-mail:liucunqi@sina.com
  • 基金资助:
    水体污染控制与治理科技重大专项(2009ZX07109-008-02);河北省科学技术研究与发展指导计划(06276905)

Dynamics of phytoplankton community in Baiyangdian Lake based on the redundancy analysis(RDA)

LIU Cunqi,KONG Xiangling,ZHANG Zhirong,TIAN Zhifu   

  1. College of Life Sciences, Hebei University, Baoding 071002, China
  • Received:2015-07-25 Online:2016-05-25 Published:2016-05-25

摘要: 2010年4-11月采样调查了白洋淀浮游植物群落组成和时空变化特征,利用冗余分析(RDA)方法分析了影响浮游植物群落分布的主要环境因子.共检出浮游植物8门183种(属),以蓝藻、绿藻和硅藻为主.浮游植物的密度在8.68×106~314.32×106/L内变化,最大值出现在秋季(9月),最小值出现在冬季(11月).采蒲台水体的Shannon-Wiener指数和均匀度指数最高,王家寨和南刘庄则较低.水温、透明度和高锰酸钾指数对白洋淀浮游植物群落的分布和动态变化影响最大,而pH值和总磷浓度对绿藻门和蓝藻门种类影响较为明显.控制有机污染物和磷的排放是解决白洋淀富营养化的主要措施.

关键词: 白洋淀, 浮游植物, 环境因子, 冗余分析

Abstract: The composition and temporal-spatial dynamics of phytoplankton community in Baiyangdian Lake were investigated from April to November of 2010,and main environmental factors affecting composition of community were analyzed by Redundancy analysis(RDA).Results showed that 183 species(genera)including 8 phyla of phytoplankton were identified,and the dominant phyla were found to be the Cyanophyta,Chlorophyta and Bacillariophyta.Phytoplankton density ranged from 8.68×106 to 314.32×106 /L,and the highest density was observed in autumn(September)and the lowest in winter(November).Shannon-Wiener biodiversity index and evenness in Caiputai were highest,but that in Wangjiazhai and Nanliuzhuang were lower.Water temperature,transparency and CODMn had strong effects on the community of phytoplankton,pH and total phosphorus correlated with species of Cyanophyta and Chlorophyta.To control the enviromental release of organic pollutants and phosphorus is the key approach to reduce the eutrophication risk in Baiyangdian Lake.

Key words: Baiyangdian Lake, phytoplankton, environmental factor, Redundancy analysis

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