Exploring Dynamics of the Chlorophyll α-Total Phosphorus Relationship at the Lake-Specific Scale: a Bayesian Hierarchical Model

Lake eutrophication has become a worldwide challenge, and the empirical chlorophyll a-total phosphorus (Chla-TP) relationship provides a management target for TP concentrations. Neglecting the dynamics of the relationship at the lake-specific scale would mislead the eutrophication control strategy. The Bayesian hierarchical model (BHM) is a flexible tool to explore dynamics of the Chla-TP relationship and improves the overall estimation accuracy by partial pooling of data. In this study, we used the BHMto show the spatial and seasonal dynamics of the Chla-TP relationship in one of themost eutrophic lakes in China (Lake Dianchi). We defined an indicator (the Chla/TP ratio, CPR), to represent the susceptibility of Chla to TP. We conducted a model selection process and used the CPR-TP curves to show the spatial and seasonal dynamics of the ChlaTP relationships. We determined that the wind caused the spatial dynamics due to the horizontal transport of phytoplankton, while the water temperature and the percentage of soluble reactive phosphorus led to the seasonal dynamics via increasing the growth rate of phytoplankton. These findings helped the eutrophication control in Lake Dianchi. We found that compared with the strategy to decrease the TP concentration, decreasing the susceptibility is expected to be more effective. Finally, we concluded that exploring the dynamics of the Chla-TP relationship provided an important basis for eutrophication control at the lake-specific scale.