The Interplay between Environmental Factors and Algal Community Growth in Shanzai Reservoir

Abstract

【Objective】 This study delves into the successional interrelationship between algal communities and environmental factors to uncover the mechanisms behind water bloom outbreaks in Shanzai Reservoir. 【Method】 Utilizing redundancy analysis and correlation analysis, we investigated the temporal variations in water temperature, pH, dissolved oxygen (DO), transparency, and dominant algal species in Shanzai Reservoir from 2020 to 2021. We explored the seasonal succession and vertical distribution of the algal community. A machine learning approach was used to establish the relationship between pertinent environmental factors and chlorophyll a. 【Result】 The average total nitrogen (TN) and total phosphorus (TP) concentrations in Shanzai Reservoir measured in the studied period were (0.675±0.137) mg/L and (0.021±0.006) mg/L, respectively. Water quality in the reservoir was Class III grade. The dominant algal species in the reservoir are diatoms and cyanobacteria. Diatom blooms were prevalent from May to July, particularly under moderate temperature and reduced light conditions. In contrast, cyanobacteria proliferated from July to September, leading to a reduction in pH, DO and water quality. The cyanobacterial outbreaks had a significant positive correlation with water temperature, pH, water turbidity, and TP, with their R2 being 0.71, 0.77, 0.65, and 0.74, respectively. Diatoms were negatively correlated to water temperature, pH, turbidity, and TP, with their R2 ranging from -0.43 to -0.37. Using machine learning algorithms can improve the R2 to 0.852 6. 【Conclusion】 There were differences in outbreak timings between different algae species in Shanzai Reservoir due to the difference in their underlying mechanism. Machine learning model has a good applicability and can be used for accurate analysis of algal blooms in Shanzai Reservoir.

Keywords

• reservoir
• algal community succession
• environmental factors
• water bloom
• rda analysis