Yan Guang-Han, Yin Xue-Yan, Wang Xing, Huang Min-Sheng, Huang Dai-Zhong, Wang En-Rui, Zhang Yun-Yu
National Engineering Laboratory for Lake Pollution Control and Ecological Restoration, Chinese Research Academy of Environmental Sciences, Beijing 100012, China.
State Environmental Protection Key Laboratory of Drinking Water Source Protection, Chinese Research Academy of Environmental Sciences, Beijing 100012, China.
Huan Jing Ke Xue. 2023 Nov 8;44(11):6125-6136. doi: 10.13227/j.hjkx.202212107.
Phytoplankton is the most important component of water ecosystems, which could indicate the state of the water environment owing to its sensitivity to water environment variation. However, its response to the environment is influenced by classification methods. To understand the phytoplankton population(phyla and genera) and functional groups(FG) for driving response characteristics and applicability to the environment in Dongting Lake, a total of four samples were collected from the lake from March to December 2019, and the distribution characteristics of the phytoplankton population and functional groups and their responses to environmental factors were compared and analyzed. Meanwhile, the applicability of the TLI index, Shannon-Wiener index, and index was compared in Dongting Lake. The results showed that a total of 61 genera belonging to six phyla of phytoplankton were detected in Dongting Lake, which could be divided into 23 functional groups and nine dominant functional groups. The succession trend of functional groups was P/MP/D(March)→MP/P/J(June)→MP/H1(September)→Y/P/MP(December). The results of hierarchical segmentation showed that the population distribution and change in phytoplankton were driven by environmental factors more than the area in Dongting Lake. The main environmental factors affecting phytoplankton population and functional groups were water temperature(WT), permanganate index, dissolved oxygen(DO), conductivity(Cond), water level(WL), and total phosphorus(TP). RDA analysis showed that phytoplankton functional groups identified phytoplankton response to environmental factors better than phytoplankton population. It was shown that using the index to evaluate water quality had better applicability in Dongting Lake.
浮游植物是水生态系统中最重要的组成部分,由于其对水环境变化较为敏感,能够指示水环境状况。然而,其对环境的响应受到分类方法的影响。为了解洞庭湖浮游植物种群(门和属)和功能类群(FG)对环境的驱动响应特征及适用性,于2019年3月至12月在该湖共采集了4个样本,对浮游植物种群和功能类群的分布特征及其对环境因子的响应进行了比较分析。同时,对洞庭湖的综合营养状态指数(TLI)、香农-威纳指数和单因素污染指数的适用性进行了比较。结果表明,洞庭湖共检测到浮游植物6门61属,可分为23个功能类群和9个优势功能类群。功能类群的演替趋势为P/MP/D(3月)→MP/P/J(6月)→MP/H1(9月)→Y/P/MP(12月)。层次分割结果表明,洞庭湖浮游植物的种群分布和变化受环境因子的驱动作用大于面积。影响浮游植物种群和功能类群的主要环境因子为水温(WT)、高锰酸盐指数、溶解氧(DO)、电导率(Cond)、水位(WL)和总磷(TP)。冗余分析(RDA)表明,浮游植物功能类群比浮游植物种群能更好地识别浮游植物对环境因子的响应。结果表明,利用单因素污染指数评价洞庭湖水质具有较好的适用性。