Global Ecology and Conservation (Jun 2024)
The roles of environmental filtering and competitive exclusion in the plant community assembly at Mt. Huangshan are forest-type-dependent
Abstract
Integrating trait and phylogenetic data are increasingly being used to enhance our understanding of the underlying community assembly processes and optimize the interpretation of unmeasured, phylogenically conserved traits. The biodiversity of Huangshan, China, was higher, but it was suffered from some damage, such as biological invasion and human disturbance. We sampled 176 species from three different forests (EBF: evergreen broadleaf forest; DBF: deciduous broadleaf forest; MNBF: mixed needleleaf and broadleaf forest) which are the representative communities of Mt. Huangshan. Then, we measured six functional traits (leaf thickness, leaf area, specific leaf area, leaf carbon concentration, leaf nitrogen concentration and leaf phosphorus concentration) and constructed a molecular phylogeny tree to assess community structure using species trait-phylogenetic distances. Results showed that six traits are more phylogenetically convergent than predicted, which was not closely related to the evolutionary history of species. The contribution of phylogenetic distance and functional distance to community construction was equal in total layer and more importance was given to functional distances for tree and shrub layer, indicating that closely related species tended to be phenotypically different. The functional trait-phylogenetic of EBF and MNBF was clustering, while DBF exhibited functional trait-phylogenetic over-dispersion. In other words, environmental filtering appears to be the dominant force in EBF and MNBF, while competitive exclusion appears to become more important in DBF. Our study also indicates that spatial factors resulted in a higher explanatory power than environmental factors. In according to better protect forest biodiversity, species coexistence mechanisms should be incorporated into the management of forest communities and to predict their presentation in future environmental scenarios.
