Linking the network topology of plant traits with community structure, functioning, and adaptive strategies of submerged macrophytes.

Plant trait network analysis can calculate the topology of trait correlations and clarify the complex relationships among traits, providing new insights into ecological topics, including trait dimensions and phenotypic integration. However, few studies have focused on the relationships between network topology and community structure, functioning, and adaptive strategies, especially in natural submerged macrophyte communities. In this study, we collected 15 macrophyte community-level traits from 12 shallow lakes in the Yangtze River Basin in the process of eutrophication and analyzed the changes in trait network structure (i.e., total phosphorus, TP) by using a moving window method. Our results showed that water TP significantly changed the topology of trait networks. Specifically, under low or high nutrient levels, the network structure was more dispersed, with lower connectance and higher modularity than that found at moderate nutrient levels. We also found that network connectance was positively correlated with community biomass and homeostasis, while network modularity was negatively correlated with community biomass and homeostasis. In addition, modules and hub traits also changed with the intensity of eutrophication, which can reflect the trait integration and adaptation strategies of plants in a stressful environment. At low or high nutrient levels, more modules were differentiated, and those modules with higher strength were related to community nutrition. Our results clarified the dynamics of community structure and functioning from a new perspective of plant trait networks, which is key to predicting the response of ecosystems to environmental changes.