摘要:松花江是黑龙江在我国境内的最大支流，流经吉林、黑龙江两省。松花江哈尔滨段是哈尔滨市工农业生产与生活用水的重要水资源，近年来由于人类活动的频繁影响，水体质量有所下降。鉴于此，于2018年春、夏、秋三季（4月、8月和10月），在松花江哈尔滨段设置14个采样点，对电导率、总氮和总磷等理化指标进行测定，同时对其浮游植物群落结构及环境因子相关性进行研究。利用群落相似性分析（ANOSIM）探讨浮游植物群落时空分布差异；通过SIMPER分析筛选出影响群落时空格局的关键物种。基于优势种和10项理化指标的冗余分析（RDA）揭示了浮游植物群落生态分布特征并对关键影响因子进行识别。研究结果表明，调查期间共鉴定浮游植物136种，其中优势种15种，群落结构主要以硅藻门和绿藻门的物种构成。松花江哈尔滨段浮游植物群落结构与过去10余年间相比较为稳定。ANOSIM和SIMPER分析表明，季节变化和人为活动干扰对浮游植物群落时空格局具有一定驱动作用，蓝藻门物种的空间分布活动干扰影响明显。RDA分析表明，浮游植物分布特征与水环境时空异质性关系密切，驱动松花江哈尔滨段浮游植物群落时空分布的主要水环境因子为电导率、总磷、浊度和pH。



Abstract:The Songhua River, the largest tributary of the Heilongjiang River, flows through Jilin and Heilongjiang province. The Harbin section of the Songhua River starts from the upstream of Zhu Shuntun and ends at the Dadingzi Mountain in the lower reaches. It is an important water resource for industrial, agricultural and domestic use in Harbin city. Recent years, the intensively anthropogenic activities have resulted in water pollution. The water quality and biodiversity of Harbin section of the Songhua river has been attracted wide attention. At present, more and more studies focused on phytoplankton diversity and community structure. However, the study on phytoplankton in Harbin section of the Songhua River is still in its infancy. To explore the phytoplankton community structure and its relationship with environmental factors in Harbin section of the Songhua River, multivariate statistical analysis was conducted in this study. All sampling sites of Harbin section of the Songhua River were divided into two parts, sampling sites under intense human disturbance and other less polluted sites. A total of 14 sampling sites, the phytoplankton community and 10 environmental parameters were investigated in the spring (April), summer (July), and autumn (October) of 2018. The spatial and temporal distribution differences of phytoplankton community were analyzed by analysis of similarity (ANOSIM). The key species with contribution to the spatio-temporal patterns were identified by similarity percentage (SIMPER) analysis. Additionally, the redundancy analysis (RDA) based on dominant species and 10 environmental variables revealed the ecological distribution of phytoplankton community and identified main factors. The results showed that a total of 136 species of phytoplankton were detected, including 15 dominant species. The species composition was dominated by Bacillariophyta and Chlorophyta (76%), followed by Cyanobacteria (12%), Cryptophyta (7%) and others. Compared with the past 10 years, the community structure belonging to Bacillariophyta-Chlorophyta was relatively stable. Among the three seasons, except for the physical and chemical indicators of specific conductivity (SpCond.), oxidation-reduction potential (ORP) and total phosphate (TP), others were significant differences (P<0.05). During the study, the abundance of phytoplankton in Harbin section of the Songhua River was 7.92×10⁶-21.76×10⁶ ind./L, and the average was 15.27×10⁶ ind./L. The independent sample t-test showed that there were significant differences in total nitrogen (TN), chemical oxygen demand (COD_Mn) and chemical oxygen demand (BOD₅) among the sampling sites affected by human disturbance and other sites (P<0.01). Additionally, there was significant difference of SpCond. at the 0.01 level in different sites, while other physical indicators such as pH did not change greatly (P>0.05). ANOSIM and SIMPER analysis showed that seasonal changes and human-induced disturbances in Site 4 to Site 7 had effects on the spatial and temporal patterns of phytoplankton community. The spatial distribution of Cyanobacteria species was significantly affected by human activity. The results of RDA analysis found that the distribution characteristics of phytoplankton were closely related to the spatio-temporal heterogeneity of water environment. SpCond., TP, turbidity (Tur.) and pH were the key driving factors of phytoplankton community in Harbin section of the Songhua River.





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