青草沙邻近水域网采浮游植物群落结构特征

根据2012年2-11月在青草沙邻近水域的采样调查,对调查水域网采浮游植物的群落结构特征进行了研究。共鉴定出浮游植物7门46属71种,浮游植物以硅藻为主,蓝藻和绿藻在群落中占有一定比重,此外还有少量的甲藻、金藻、隐藻和裸藻。浮游植物物种多为温带近岸物种并有少量淡水物种,骨条藻Skeletonema spp.在该水域全年都具有较高的优势度。青草沙邻近水域网采浮游植物平均细胞丰度春季最高,为548.09 ind/ml,夏季其次,冬季最低,为2.19 ind/ml,冬季各站之间细胞丰度差异最小。该水域浮游植物密集区日迁移主要受潮汐作用影响,而季节变动则主要受冲淡水转向影响,与长江冲淡水季节性扩展方向吻合。聚类分析结果表明,调查水域浮游植物类群存在季节差异,长江径流量的季节变动与长江冲淡水季节性转向可能是造成这种差别的主要原因。典范性对应分析表明,环境因子驱动长江口浮游植物群集产生季节变动,不同年份间存在相似性。

The netz-phytoplankton assemblage structure of Qingcaosha Reservoir adjacent waters

Changjiang River estuary is the major economic offshore fishing water. Construction of Qingcaosha Reservoir may become unfavorable factors of juvenile growth and complementary resources in Changjiang Delta. This may eventually lead to the degradation of estuarine spawning grounds and abnormal biological community structure, and may restrict the sustainable use of fishery resources. Ecological characteristics of phytoplankton are important indicators of environmental quality assessment of fisheries. A muhidisciplinary study on netz-phytoplankton assemblage structure was carried out in Qingcaosha Reservoir adjacent waters during February to November, 2012. This study identified 7 phyla, including 46 genera and 71 species, in which diatoms dominated, and Cyanophyta, Chlorophyta, Dinoflagellates, Chrysophyta, Cryptophyta and Euglenophyta were also found. Skeletonema spp. was prevailed cross-season in the whole investigation period. Temperate coastal species were the major ecotype, while fresh water species were occasional. Cell abundance decreased in turn from spring, summer, autumn to winter and the average value of spring and winter were 548.09 and 2. 19 ind/ml, respectively. The major factor of daily migration was tidal impact, while the seasonal variation was affected by diluted water. Seasonal variation patterns in the survey area were discriminated by the cluster analysis of the phytoplankton assemblages. The change in seasonal runoff of the river and direction transformation of Changjiang diluted water was responsible for the variations. The canonical correspondence analysis （CCA） showed that the environmental factors drive the assemblage variation during all seasons.