No abstract

Water eutrophication creates unfavorable environmental conditions for submerged macrophytes. In these situations, biotic interactions may be particularly important for explaining and predicting the submerged macrophytes occurrence. Here, we evaluate the roles of biotic interactions in predicting spatial occurrence of submerged macrophytes in 1959 and 2009 for Dianshan Lake in eastern China, which became eutrophic since the 1980s. For the four common species occurred in 1959 and 2009, null species distribution models based on abiotic variables and full models based on both abiotic and biotic variables were developed using generalized linear model (GLM) and boosted regression trees (BRT) to determine whether the biotic variables improved the model performance. Hierarchical Bayesian‐based joint species distribution models capable of detecting paired biotic interactions were established for each species in both periods to evaluate the changes in the biotic interactions. In most of the GLM and BRT models, the full models showed better performance than the null models in predicting the species presence/absence, and the relative importance of the biotic variables in the full models increased from less than 50% in 1959 to more than 50% in 2009 for each species. Moreover, co‐occurrence correlation of each paired species interaction was higher in 2009 than that in 1959. The findings suggest biotic interactions that tend to be positive play more important roles in the spatial distribution of multispecies assemblages of macrophytes and should be included in prediction models to improve prediction accuracy when forecasting macrophytes’ distribution under eutrophication stress.

Underwater light reduction is presumably becoming more frequent and intensified due to eutrophication and algal blooms, which may significantly affect submerged macrophytes’ growth. However, a comprehensive understanding of how light reduction influences growth-related traits and responses is currently lacking. Here, we compiled data from 333 records of 62 published works that used controlled experiments to explore the responses of functional traits associated with growth to light reduction. Our results indicated that light reduction significantly decreased the relative growth rate (RGR), ramet number (RM), shoot biomass (SB), root biomass (RB), soluble carbohydrates (SC), and leaf number (LN) by 38.2%, 60.0%, 59.2%, 55.4%, 30.0%, and 56.1%, respectively, but elevated the chlorophyll content (Chl) by 25.8%. Meanwhile, the responses of RGR to light reduction increased significantly with the responses of RM, SB, RB, and root-to-shoot ratio (R/S). Considering the relationships among the growth-related traits, we further found that the responses of RGR to light reduction were mainly driven by the RM rather than leaf photosynthetic capability, indicating the importance of tiller ability under low light stress. We also identified a tipping point of the response of RGR to light reduction, which might be incorporated into hydrophyte dynamic models to improve precision. Our results highlight the importance of growth-related traits, andthese traits may need to be incorporated into models to improve the prediction of distribution and area for submerged species or to provide guidance for the restoration and sustainable development of aquatic ecosystems.