Phylobetadiversity incorporates phylogenetic information and beta diversity,and can account for the ecological similarities between communities with a phylogenetic perspective.Although different phylobetadiversity indices reflect differences in different characteristics between communities,the results of different phylobetadiversity indices are not comparable.In this study we examined phylobetadiversity indices for a 24-hm 2 plot in the Gutianshan National Nature Reserve.It was found the abundanceweighted D pw was almost identical to Rao's D of Rao's quadratic entropy.PhyloSor had a similar ecological meaning and algorithm to UniFrac.Although Dnn was different in definition from UniFrac and PhyloSor,they were all strongly correlated.The effect of species abundance on phylobetadiversity was not significant when scales were relatively small,but was significant at larger scales.These contrasts likely resulted from reductions in evenness in communities as scales increased.P ST and Rao's H better reflected the distance-decay changes caused by spatial and habitat variation than other indices at larger scales,whereas AW-D nn and D nn better reflected these changes at small scales.
Aims Recent mechanistic explanations for community assembly focus on the debates surrounding niche-based deterministic and dispersalbased stochastic models.This body of work has emphasized the importance of both habitat filtering and dispersal limitation,and many of these works have utilized the assumption of species spatial independence to simplify the complexity of the spatial modeling in natural communities when given dispersal limitation and/or habitat filtering.One potential drawback of this simplification is that it does not consider species interactions and how they may influence the spatial distribution of species,phylogenetic and functional diversity.Here,we assess the validity of the assumption of species spatial independence using data from a subtropical forest plot in southeastern China.Methods We use the four most commonly employed spatial statistical models—the homogeneous Poisson process representing pure random effect,the heterogeneous Poisson process for the effect of habitat heterogeneity,the homogenous Thomas process for sole dispersal limitation and the heterogeneous Thomas process for joint effect of habitat heterogeneity and dispersal limitation—to investigate the contribution of different mechanisms in shaping the species,phylogenetic and functional structures of communities.Important Findings Our evidence from species,phylogenetic and functional diversity demonstrates that the habitat filtering and/or dispersal-based models perform well and the assumption of species spatial independence is relatively valid at larger scales(50×50 m).Conversely,at local scales(10×10 and 20×20 m),the models often fail to predict the species,phylogenetic and functional diversity,suggesting that the assumption of species spatial independence is invalid and that biotic interactions are increasingly important at these spatial scales.
