Autor: |
Sun RX; School of Municipal and Environmental Engineering, Shenyang Jianzhu University, Shenyang 110168, China.; South China Institute of Environmental Sciences, Ministry of Ecology and Environment, Guangzhou 510535, China.; State Environmental Protection Key Laboratory of Water Environmental Simulation and Pollution Control, Guangzhou 510530, China., Xu L; School of Municipal and Environmental Engineering, Shenyang Jianzhu University, Shenyang 110168, China., Liang RC; South China Institute of Environmental Sciences, Ministry of Ecology and Environment, Guangzhou 510535, China.; State Environmental Protection Key Laboratory of Water Environmental Simulation and Pollution Control, Guangzhou 510530, China., Cai QJ; South China Institute of Environmental Sciences, Ministry of Ecology and Environment, Guangzhou 510535, China.; State Environmental Protection Key Laboratory of Water Environmental Simulation and Pollution Control, Guangzhou 510530, China., Ma QL; South China Institute of Environmental Sciences, Ministry of Ecology and Environment, Guangzhou 510535, China.; State Environmental Protection Key Laboratory of Water Environmental Simulation and Pollution Control, Guangzhou 510530, China., Geng ZY; School of Municipal and Environmental Engineering, Shenyang Jianzhu University, Shenyang 110168, China.; South China Institute of Environmental Sciences, Ministry of Ecology and Environment, Guangzhou 510535, China.; State Environmental Protection Key Laboratory of Water Environmental Simulation and Pollution Control, Guangzhou 510530, China., Lin XZ; South China Institute of Environmental Sciences, Ministry of Ecology and Environment, Guangzhou 510535, China.; State Environmental Protection Key Laboratory of Water Environmental Simulation and Pollution Control, Guangzhou 510530, China., Yang YY; South China Institute of Environmental Sciences, Ministry of Ecology and Environment, Guangzhou 510535, China.; State Environmental Protection Key Laboratory of Water Environmental Simulation and Pollution Control, Guangzhou 510530, China., Yao LA; South China Institute of Environmental Sciences, Ministry of Ecology and Environment, Guangzhou 510535, China.; State Environmental Protection Key Laboratory of Water Environmental Simulation and Pollution Control, Guangzhou 510530, China., Zhao R; South China Institute of Environmental Sciences, Ministry of Ecology and Environment, Guangzhou 510535, China.; State Environmental Protection Key Laboratory of Water Environmental Simulation and Pollution Control, Guangzhou 510530, China. |
Abstrakt: |
To explore the characteristics of phytoplankton communities and their relationship with environmental factors in different habitats of Hedi Reservoir, the inflow rivers, estuaries, and reservoir area of Hedi Reservoir were investigated in February (recession period), April (flood period), July (flood period), and December (recession period) of 2022. During the investigation, 231 species of phytoplankton that belong to seven phyla were identified, and the cell density of phytoplankton ranged from 2.94 × 10 6 - 8.04 × 10 8 cells·L -1 . Phytoplankton cell density in flood periods were higher than that in recession periods, and that was higher in estuaries and the reservoir area than that in inflow rivers. Meanwhile, the cell density of phytoplankton in the estuarine and reservoir area was dominated by Cyanobacteria throughout the year, especially Raphidiopsis raciborskii , whereas the cell density of phytoplankton in inflow rivers was dominated by Cyanophyta, Chlorophyta, and Bacillariophyta. In the inflow river area, the dominant species of cyanobacteria were Microcystis aeruginosa , Limnothrix redekei , Pseudanabaena circinalis, and Merismopedia punctata ; the dominant species of Chlorophyta were Chlorella vulgaris and Crucigenia tetrapedia ; and the dominant species of Bacillariophyta were Chlorella vulgaris and Melosira granulate . The highest biodiversity (Shannon-Wiener Index, Pielou index, and Margalef index) were observed in the inflow river area of Hedi Reservoir. The correlation analysis (Pearson) indicated that the environmental factors that were significantly correlated to phytoplankton communities included water temperature, dissolved oxygen, pH, conductivity, nitrogen, and phosphorus concentration. The RDA analysis indicated that phytoplankton communities in the inflow river area were mainly affected by pH and total nitrogen concentration, which were majorly affected by water temperature and pH in the estuarine area and chiefly affected by turbidity and pH in the reservoir. The pH affected the changes in phytoplankton communities in all three different habitats, whereas the inflow river area was significantly affected by total nitrogen concentration, and the estuarine and reservoir were significantly affected by water temperature and turbidity, respectively. |