Indicators for lake environmental assessment considering water quality and biological resources: Analysis using a food chain model with the Monte Carlo method

Lakes are globally important freshwater resources, and their sustainable management requires not only controlling eutrophication but also maintaining biological productivity and ecosystem health. In this study, we proposed a statistical method to analyze the relationships among indicators of water quality and biological resources using a food chain model combined with the Monte Carlo method. This approach overcomes the limitations of conventional mathematical models, specifically their dependence on unknown parameters and the resulting uncertainty. The method was applied to Lake Biwa to identify indicators that contribute to both water quality improvement and enhancement of biological resources including fish stocks. The results showed that the biomass ratio of planktivorous fish to phytoplankton and the integrated trophic position (iTP) were positively associated with higher trophic transfer efficiencies (TE), indicating the importance of efficient energy flow through the food chain. A higher phosphorus-to-carbon (P:C) ratio in phytoplankton was also linked to improved fish biomass and water clarity. In contrast, dissolved phosphorus (DP) concentration showed no clear relationship with phytoplankton biomass and did not serve as a useful predictor under stable nutrient loading conditions. When a 1.5-fold increase in DP loading was simulated, changes in biomass and nutrient concentrations were small, suggesting that internal nutrient recycling plays a dominant role in the phosphorus dynamics in Lake Biwa. Therefore, simply increasing nutrient inputs to enhance fish biomass is unlikely to produce the desired effects.