Influence of fishery management on trophic interactions and biomass fluxes in Lake Taihu based on a trophic mass-balance model exercise on a long-term data series

With increasing anthropogenic activities, freshwater ecosystems around the world are becoming increasingly affected by various pressures, including eutrophication, overfishing, and irrational stocking, which may have a negative impact on the food web structure. Despite the extensive research and proposed management measures for eutrophic lakes, there are only few analysis on long-term monitoring data regarding fishery resources. Additionally, there is a lack of evaluation and prediction of the effectiveness of current fish management policies. To remedy this, we analyzed long-term monitoring data from Lake Taihu, China, a severely eutrophicated lake with a skewed fish size structure exhibiting dominance of small individuals. We first constructed 14 Ecopath models to investigate how trophic interactions and biomass fluxes changed from 2007 to 2020. Subsequently, the Ecosim model was used to predict how the biomass of fish and the ecosystem network respond to the initiated 10-years fishing ban. Our results demonstrate long-term changes in fish biomass and ecosystem stability. The analyses revealed that 1) the biomass development in different feeding types of fish is controlled by human activities (mainly catches and stocking) and trophic interactions and 2) the rate of decline in ecosystem network stability slows down during the fishing ban. The primary focus of this study was to fill the gap in long-term serial studies of fish monitoring data and ecosystem stability in the lake and, for the first time, to predict the outcome of the fishing ban from an ecosystem perspective using the Ecosim model. Overall, our results emphasize the importance of rational stocking and fishing policies and provide a better understanding of the changes in the ecological dynamics in Lake Taihu of relevance for the management and restoration of the lake.