Dynamics of phytoplankton functional groups in river-connected lakes and the major influencing factors: A case study of Dongting Lake, China

Identifying the drivers that impact phytoplankton biomass and dynamics of functional groups (FGs) is crucial to the management of lake aquatic systems. To explore the interactive effects of hydrological characteristics, physicochemical parameters and phytoplankton FGs in the largest river-connected lake, a case study was carried out at Dongting Lake, China. We analyzed the changes in the hydrological characteristics of the lake as well as in the phytoplankton biomass throughout the year to explore the driving factors that influence phytoplankton FGs. Four periods were defined in our study based on water level (WL) fluctuations including the rising periods (RI and RII) and the falling periods (FI and FII). The phytoplankton biomass in Dongting Lake was the highest in RII, followed by RI, FI, and FII. And the trend of FGs dominance through the four periods were P/MP/D (RI)-* P/ MP/J (RII)-* MP (FI)-* MP/P/Y (FII). Changes in phytoplankton biomass and FGs were the result of a com-bination of hydrological characteristics and physicochemical parameters. Throughout the water period, the hydrological characteristics did not directly influence phytoplankton, instead exerting a more indirect effect on phytoplankton biomass and FGs by affecting the water's physicochemical parameters, e.g., permanganate index (CODMn), nitrogen nutrients, dissolved oxygen (DO), water temperature (WT), and conductivity (Cond). CODMn might be a significant predictor of phytoplankton biomass and FGs in all water periods, explaining 36.6% of the variability, followed by Cond, WT, ammonia nitrogen (NH4+-N), and DO explaining 17.6%, 12.3%, 11.3%, and 7.2%, respectively. However, according to each water phase analysis, the WL was the key factor for phyto-plankton growth in RII. Nitrogen nutrients, WT and Cond had more pronounced effects on phytoplankton in RI, FI and FII, respectively., Based on the findings of our study, we suggest that increased control of organic matter input into the lake and nitrogen fertilizer use at nearby agricultural surface sources are effective actions that are needed to prevent and control algal blooms in Dongting Lake.

Automated summary

A case study was conducted at Dongting Lake, China to explore the drivers impacting phytoplankton biomass and dynamics of functional groups. The study found that water level fluctuations, CODMn, and temperature were important factors influencing phytoplankton biomass and functional groups.