| 引用本文: | 张云,马徐发,郭飞飞,李建柱,熊邦喜.湖北金沙河水库浮游植物群落结构及其与水环境因子的关系.湖泊科学,2015,27(5):902-910. DOI:10.18307/2015.0517 |
| ZHANG Yun,MA Xufa,GUO Feifei,LI Jianzhu,XIONG Bangxi.Community structures of phytoplankton and their relationships with environmental factors in the Jinshahe Reservoir, Hubei Province. J. Lake Sci.2015,27(5):902-910. DOI:10.18307/2015.0517 |
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| 湖北金沙河水库浮游植物群落结构及其与水环境因子的关系 |
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张云, 马徐发, 郭飞飞, 李建柱, 熊邦喜
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华中农业大学水产学院, 武汉 430070
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| 摘要: |
| 为探明长江中游大型水库水质状况,并为饮用水源安全保障提供科学依据,于2013-2014年按季节对湖北红安金沙河水库浮游植物群落结构及其多样性进行调查,并运用多元统计定量分析浮游植物群落结构与环境因子之间的关系.共鉴定出浮游植物8门94属216种,其中绿藻门为优势种群,其种类数占总物种数的51.39%,其次是硅藻门和蓝藻门.金沙河水库优势种随季节变化而变化,夏季以尖针杆藻(Synedra acus)的优势度最大(0.195),秋季以小胶鞘藻(Phormidium tenus)(0.180)和中华尖头藻(Raphidiopsis sinensia)(0.171)的优势度最大,冬季以具星小环藻(Cyclotella stelligera)(0.220)和圆筒锥囊藻(Dinobryon cylindricum)(0.234)的优势度最大,春季则是链状曲壳藻(Achanthidum catenatum)成为绝对优势种(0.910);金沙河水库浮游植物群落总的变化规律为夏季的硅藻门、蓝藻门和绿藻门,秋季的蓝藻门、绿藻门、硅藻门和隐藻门,向冬季的硅藻门和金藻门转变,春季则是硅藻门为绝对优势类群.Shannon-Wiener多样性指数和Pielou均匀度指数显示,浮游植物在秋季的多样性和均匀度较高,春季的多样性指数和均匀度指数显著低于其它季节,这是因为春季有绝对单一的优势物种,而秋季没有,且秋季的物种数最多,因此其Margalef丰富度指数也最高.将各季节优势种和经Pearson相关性分析筛选出的环境因子进行冗余分析,结果表明筛选的环境因子中磷酸盐、总磷和溶解氧浓度是影响金沙河水库浮游植物群落结构的主要环境因子.从藻类季节变化规律来看,金沙河水库夏、秋季水质污染程度较春、冬季严重;但从藻类丰度和多样性指数来看,春、夏季水质较秋、冬季污染严重. |
| 关键词: 金沙河水库 浮游植物 群落结构 环境因子 冗余分析 |
| DOI：10.18307/2015.0517 |
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| 基金项目:湖泊水库养殖容量及生态增养殖技术研究与示范项目(201303056)资助. |
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| Community structures of phytoplankton and their relationships with environmental factors in the Jinshahe Reservoir, Hubei Province |
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ZHANG Yun, MA Xufa, GUO Feifei, LI Jianzhu, XIONG Bangxi
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College of Fisheries, Huazhong Agricultural University, Wuhan 430070, P. R. China
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| Abstract: |
| In order to evaluate the water quality of drinking water resource in the middle reaches of the Changjiang River, phytoplankton community structures and their diversities were investigated seasonally from August, 2013 to April, 2014 in the Jinshahe Reservoir, Hubei Province. Meanwhile, multivariate statistics was used to analyze the relationships between phytoplankton assemblages and environmental variables. The results showed that there were total of 216 species of phytoplankton belonging to 8 phyla and 94 genera. Chlorophyta which made up of 51.39% of the total numbers of the species was the dominant group, followed by Bacillariophyta and Cyanophyta. Dominant species varied in different seasons. In summer, the ecological dominance of Synedra acus was the highest (0.195), and in autumn, Phormidium tenus (0.180) and Raphidiopsis sinensia (0.171) had the highest ecological dominance. In winter, Cyclotella stelligera (0.220) and Dinobryon cylindricum (0.234) had the highest ecological dominance, and Achanthidum catenatum was the absolute dominant species with its ecological dominance of 0.910. In general, Cyanophyta, Bacillariophyta and Chlorophyta were dominant groups in summer, and Cyanophyta, Bacillariophyta, Chlorophyta and Cryptophyta were dominant groups in autumn. Bacillariophyta and Chrysophyta were dominant groups in winter, and Bacillariophyta was the absolute dominant group in spring. Biodiversity indices showed that phytoplankton had higher values of the Shannon-Wiener diversity and the Pielou diversity in autumn, but the lowest values in spring because the absolute dominant species appeared in spring other than in autumn. In addition, the highest value of Margalef diversity occurred in autumn because of its larger number of species. Redundancy analysis was used to analyze the relationships between the dominant species in each season and the environmental factors filtered by Pearson correlation analysis. The results showed that phosphate, total phosphorus and water temperature were the main environmental factors that have influenced phytoplankton assemblages. The reservoir had worse water quality in summer and autumn than in spring and winter which impacted on the variations of dominant groups of phytoplankton in different seasons, and had worse water quality in spring and summer than in autumn and winter which impacted on the cell abundance and biodiversity indices. |
| Key words: Jinshahe Reservior phytoplankton community structures environmental factors redundancy analyses |
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