长江源地处青藏高原腹地,水体环境特殊,关于源区间浮游植物特征差异及环境作用因子尚不清晰。对比了2012—2016年长江三源浮游植物特征,并采用主成分分析(PCA)、典范对应分析(CCA)揭示了浮游植物特征与13种环境因子间的关系。结果表明:隐藻门仅在南源当曲被发现,长江南源样点的浮游植物平均种类数最多,为18种,长江北源最少,为9种;北源的浮游植物平均密度最大,为37.70×10⁴ ind/L,南源平均密度最小,为28.90×10⁴ ind/L;长江南源的浮游植物平均生物多样性指数最高,达到3.04,北源平均生物多样性指数最低,为1.84;长江源区总体上浮游植物密度较低,水体处于贫营养状态。各源环境因子PCA结果显示:第一轴主要成分(71.23%)可解释为总氮、电导率,主要代表了河流营养物特征;第二轴主要成分(28.77%)可解释为海拔、床沙中值粒径、水温、含沙量和化学需氧量,主要代表河流生境状况。物种和主要环境因子CCA结果表明蓝藻门种类数与总氮、隐藻门种类数与海拔和床沙中值粒径,绿藻门种类数与海拔、化学需氧量和床沙中值粒径均呈明显的正响应关系,隐藻门和绿藻门种类数和含沙量、水温呈明显的负响应关系。

Located in the Qinghai-Tibetan plateau, the headwaters of the Yangtze River features with specific water environment due to harsh weather conditions. Differences in the characteristics of phytoplankton in the headwaters and their interaction with environmental factors are still unclear. By comparing the characteristics of phytoplankton in the headwaters of the Yangtze River in 2012-2016, we revealed the relations between phytoplankton characteristics and thirteen environmental factors through principal component analysis (PCA) and canonical correspondence analysis (CCA). Our findings unveiled that Cryptophyta only appeared in Dangqu. The southern source of the Yangtze River boasted the largest number of average phytoplankton species (18 species), and the northern source the smallest, only 9 species. In terms of average density of phytoplankton, however, the northern source had the largest, up to 37.70×10⁴ ind/L, while the southern source the least, 28.90×10⁴ ind/L. The average biodiversity index of phytoplankton in the southern source of the Yangtze River was the highest, reaching 3.04, while that of the northern source was the lowest, merely 1.84. In general, the headwaters of the Yangtze River had a relatively low density of phytoplankton, indicating that the water bodies in the headwaters were all in an oligotrophic state. PCA result of various environmental factors showed that the main components of the first axis (71.23%) could be interpreted as total nitrogen and electrical conductivity, which mainly represented the characteristics of river nutrients, while the main components of the second axis (28.77%) were interpreted as altitude, median particle diameter of bed sand, water temperature, sand content and chemical oxygen demand, mainly representing river habitat conditions. In the meantime, the results of CCA illustrated positive relations between the number of Cyanophyta species and total nitrogen, between the number of Cryptophyta species and altitude and median sand diameter, between the number of Chlorophyta species and altitude, as well as between chemical oxygen demand and median sand diameter. The number of Cryptophyta species and Chlorophyta species stayed in negative relation with sand concentration and water temperature.