| 三峡水库大宁河支流浮游植物演变过程及其驱动因素 |
| 摘要点击 2575 全文点击 901 投稿时间：2016-06-20 修订日期：2016-09-09 |
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| 中文关键词 浮游植物 演替模式 驱动因素 生态功能组 三峡水库 |
| 英文关键词 phytoplankton succession pattern driving factors ecological functional groups Three Gorges Reservoir |
| 作者 | 单位 | E-mail | | 张佳磊 | 湖北工业大学土木建筑与环境学院, 河湖生态修复与藻类利用湖北省重点实验室, 武汉 430068 | zhangjialei2015@sina.com | | 郑丙辉 | 中国环境科学研究院, 环境基准与风险评估国家重点实验室, 国家环境保护饮用水水源地保护重点实验室, 北京 100012 | zhengbh@craes.org.cn | | 刘德富 | 湖北工业大学土木建筑与环境学院, 河湖生态修复与藻类利用湖北省重点实验室, 武汉 430068 | | | 王丽婧 | 中国环境科学研究院, 环境基准与风险评估国家重点实验室, 国家环境保护饮用水水源地保护重点实验室, 北京 100012 | | | 谭纤茹 | 湖北工业大学土木建筑与环境学院, 河湖生态修复与藻类利用湖北省重点实验室, 武汉 430068 | |
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| 中文摘要 |
| 基于大宁河不同水文期（2012-04-27~2013-01-19）的监测数据，运用数理统计分析手段，探索三峡水库支流浮游植物不同水文期演替模式及其影响因素.结果表明：①研究期间表层叶绿素浓度和藻类细胞密度最大值均出现在汛限期，依次是蓄水期、泄水期和高水位运行期.基于生态功能组原理，不同水文期大宁河的浮游植物演替模式为：CR-R（高水位运行期）-CS（泄水期）-CR/CS（汛限期）-R-CR（蓄水期）.②丰富度指数最大值出现在蓄水期，最小值出现在高水位运行期和泄水期；均匀度指数最大值出现在汛限期，最小值出现在高水位运行期和泄水期；多样性指数最大值出现在汛限期，最小值出现在蓄水期和泄水期；演替速率最高值出现在蓄水期，最低值出现在泄水期.③利用数理统计分析方法，高水位运行期，浮游植物生物量与生境参数并不存在显著的相关关系，水动力参数（RSCW）和光热参数（Et和Ef*）是影响浮游植物群落结构的关键要素；泄水期，Et和Ef*均与浮游植物生物量呈显著正相关，营养盐参数（TP）与浮游植物生物量呈显著负相关关系，营养盐参数（TP）和光热参数[Deu（λPAR）/Dmix]是影响浮游植物群落结构的关键要素；汛限期，光热参数（Ef*）与浮游植物生物量呈显著正相关，营养盐参数（TP）与浮游植物生物量呈显著负相关关系，光热参数（[Deu（λPAR）/Dmix]、Et和Ef*）和营养盐参数（TP）是影响浮游植物群落结构的关键要素；在蓄水期，TP与Chl-a浓度呈极显著正相关关系，光热参数[Deu（λPAR）/Dmix]是影响浮游植物群落结构的关键要素. |
| 英文摘要 |
| To elucidate succession pattern of phytoplankton in the Daning River and its driving factors, multivariate statistical analysis was conducted. By using the monitoring data in different seasons of Daning river during April 2012 to January 2013, this paper analyzed the succession pattern of phytoplankton in the Daning River and its driving factors in typical tributaries of river-style reservoirs. According to the characteristics of water level, the operational period of the TGR was classified into following four stages:stage Ⅰ (pre-November-April), stage Ⅱ (May-July), stage Ⅲ (July-September) and stage Ⅳ (September-November). ① The results indicated that the values of Chlorophyll-a concentrations and algal density showed similar seasonal variations, with the highest values occurring in stage Ⅲ, followed by stages Ⅳ, Ⅱ and Ⅰ. Succession of C-R-S growth strategies was the same generally:CR-R type dominated in stage Ⅰ, CS, CR/CS and R-CR dominated in stage Ⅱ, Ⅲ and Ⅳ, respectively. ② The mean values of Margalef index and Pielou index in stage Ⅳ and Ⅲ were significantly greater than those in stage Ⅱ and Ⅰ; the value of Shannon-waver index showed that the highest value in stage Ⅲ, followed in a descending order by stage Ⅰ,Ⅱ and Ⅳ; the successional rate had the highest value in stage Ⅳ, followed in descending order by stage Ⅲ, Ⅰ and Ⅱ. ③ The results of Correlation analysis suggested that no significant relationships were observed between the environmental parameters and phytoplankton abundance in stage Ⅰ. The results indicated that relative water column stability(RWCS), index of feasible energy for phytoplankton (Et) and index of feasible energy (Ef*) were key regulatory factors for phytoplankton community in stage Ⅰ. The results indicated that Et, Ef* and total phosphorus (TP) were key regulatory factors for phytoplankton abundance in stage Ⅱ. The results of the redundancy analysis (RDA) suggested that RWCS, TP and the ratio of euphotic depth[Deu(λPAR)] to mixing depth (Dmix)[Deu(λPAR)/Dmix] were key regulatory factors for phytoplankton community composition in stage Ⅱ. The results indicated that Ef* and TP were key regulatory factors for phytoplankton abundance in stage Ⅲ. The results of the RDA suggested that[Deu(λPAR)/Dmix],Et, Ef* and TP were key regulatory factors for phytoplankton community composition in stage Ⅲ. The results indicated that TP was key regulatory factor for phytoplankton abundance in stage Ⅳ. The results of the RDA suggested that[Deu(λPAR)/Dmix] was key regulatory factor for phytoplankton community composition in stage Ⅳ. |
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