Macrobenthos taxonomic and functional diversity are key indicators of ecosystem health. River–lake ecotones are key macrobenthos habitats. However, we don’t fully understand macrobenthos biodiversity patterns in these ecotones. We studied water environment, sediment heavy metal contents, and macrobenthos community, which we sampled simultaneously from 29 sampling sites along the Fu River–Baiyangdian Lake gradient in Northern China with five field surveys from 2018 to 2019. Six trait classes resolved into 25 categories were allocated to macrobenthos through a binary coding system. We used the RLQ framework (R, environmental variables; L, species of taxa; Q, traits) and fourth-corner analyses to evaluate the relationship between environmental variables and macrobenthos traits. Finally, we carried out variance partitioning to assess the contributions of environmental variables to variation of macrobenthos diversities. As the results, TN and TP contents in the river and lake mouths were lower than those in the adjacent river and lake, indicating that the river–lake ecotones played a role in purifying the water and buffering pollution. High taxonomic diversity of macrobenthos in the lake mouth and the presence of unique taxa in the two ecotones revealed edge effects, but the macrobenthos abundance and biomass were extremely low compared with those in the adjacent river and lake. We found no significant correlation between the taxonomic and functional diversity indices in the river and lake mouths. Water depth, water transparency, TN, and TP were the main water environmental drivers of macrobenthos taxonomic and functional diversity, explaining up to 45.5% and 56.2% of the variation, respectively. Sediment Cd, Cr, Cu, Pb, and Zn contents explained 15.1% and 32.8%, respectively, of macrobenthos taxonomic and functional diversity. Our results suggest that functional diversity approaches based on biological traits can complement taxonomic approaches in river–lake ecotones. Furthermore, improving water depth, transparency, eutrophication, and heavy metal pollution will improve macrobenthos diversity in these ecotones and maintain ecosystem health.

Assessing food web structural properties and energy fluxes under changing hydrological regimes and water quality reveals the temporal patterns of ecosystem dynamics in shallow lakes. Here, we studied northern China’s largest shallow lake (Lake Baiyangdian) using quantitative food web models for five representative years (1958, 1980, 1993, 2009, and 2019). We analyzed the temporal patterns of food web structure and function by combining a Bayesian isotope mixing model with a food web energetics model. We further examined the temporal changes of unweighted and weighted food web topological attributes. Lake Baiyangdian changed from a detritus-based into a phytoplankton-based food web based on the relative contributions of basal food sources and energy flux distributions. The trophic position of fingerlings, large omnivorous fish, and carnivorous fish decreased with increasing eutrophication. The highest energy fluxes were from detritus to zooplankton and mollusks in 1958, from detritus and phytoplankton to zooplankton in 1980, 1993, and 2009, and from phytoplankton to zooplankton and detritus to mollusks in 2019. The highest total energy flux was in 1993, followed by 2019, with the lowest value in 1958. Unweighted food web metrics showed similar patterns. We observed more pronounced temporal variability in the node- and link-weighted food web metrics than in the unweighted metrics. In addition, hydrological factors (threshold, duration, reversals between high, and low water levels), eutrophication, and some water quality factors (chemical oxygen demand, dissolved oxygen, and pH) played important roles in the temporal changes of food web dynamics in Lake Baiyangdian. Our findings demonstrate the importance of integrating unweighted and weighted indicators to holistically comprehend how highly aggregated food webs respond to changing hydrological regimes and water quality, thereby improving management and restoration of shallow lake ecosystems.