Global climate change and agricultural disturbance often drive freshwater biodiversity changes at the regional level, particularly in the Midwestern US. Agricultural conservation practices have been implemented to reduce sediment and nutrient loading (e.g., crop rotation, cover crops, reduced tillage, and modified fertilizer application) for long-term economic sustainability and environmental resilience. However, the effectiveness of these efforts on freshwater biodiversity is not conclusive. In this study, we used the Kaskaskia River Watershed, Illinois as an example to evaluate how agricultural conservation practices affects both taxonomic and functional diversity under climate changes. The measures of trait-based functional diversity provide mechanistic explanations of biological changes. In specific, we model and predict 1) species richness (SR), 2) functional dispersion (FDis), and 3) functional evenness (FEve). FDis and FEve were based on ecology (life history, habitat preference, and trophic level) and physiology (thermal preference, swimming preference, etc.). The best random-forest regression models showed that flow, temperature, nitrate, and the watershed area were among the top predictors of the three biodiversity measures. We then used the models to predict the changes of SR and FDis under RCP8.5 climate change scenarios. SR and FDis were predicted to decrease in most sites, up to 20 % and 4 % by 2099, respectively. When agricultural conservation practices were considered together with climate changes, the decreasing trends of SR and FDis remained, suggesting climate change outweighed potential agriculture conservation efforts. Thus, climate-change effects on temperature and flow regimes need to be incorporated into the design of agricultural practices for freshwater biodiversity conservation.
Keywords: Best management practices; Freshwater fish; Functional diversity; Random forest; Soil & Water Assessment Tool; Species distribution modeling.
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