Using intraspecific variation of functional traits and environmental factors to understand the formation of nestedness patterns of a local forest community

The concept of nestedness originated from the field of biogeography decades ago and has been widely used in metacommunities and biological interaction networks, but there is still a lack of research within local communities. Moreover, studies about nestedness usually rarely incorporate the functional traits of the species and the environmental characteristics of the sites. In this study, we constructed a species presence-absence matrix of a 50-ha forest plot, used the simulated annealing algorithm to reveal the maximum nested structure, and further tested the significance of nestedness patterns by constructing null ensembles. The nested ranks were used to represent the orders of species and quadrats in the maximum nestedness matrix. The regression tree analysis was used to reveal the relationships of nested ranks with environmental factors and functional traits. We found that the co-occurrence pattern of local plant communities was significantly nested. The regression tree results showed that the nested ranks of quadrats were determined by soil available phosphorus, soil water content, soil organic carbon, and soil pH. Intraspecific variation of functional traits, including leaf C, leaf pH, leaf dry matter content, and maximum photosynthetic rate rather than means of functional traits, provided a better explanation for the formation of species' nested ranks. Understanding the causes of species and quadrats nested ranks provides novel lens and useful insights into ecological processes underlying nestedness, and further improves our knowledge of how local plant communities are assembled.