Patterns and drivers of avian taxonomic and phylogenetic beta diversity in China vary across geographical backgrounds and dispersal abilities

Geographical background and dispersal ability may strongly influence assemblage dissimilarity;however,these aspects have generally been overlooked in previous large-scale beta diversity studies.Here,we examined whether the patterns and drivers of taxonomic beta diversity(TBD)and phylogenetic beta diversity(PBD)of breeding birds in China vary across(1)regions on both sides of the Hu Line,which demarcates China’s topographical,climatic,economic,and social patterns,and(2)species with different dispersal ability.TBD and PBD were calculated and partitioned into turnover and nestedness components using a moving window approach.Variables representing climate,habitat heterogeneity,and habitat quality were employed to evaluate the effects of environmental filtering.Spatial distance was considered to assess the impact of dispersal limitation.Variance partitioning analysis was applied to assess the relative roles of these variables.In general,the values of TBD and PBD were high in mountainous areas and were largely determined by environmental filtering.However,different dominant environmental filters on either side of the Hu Line led to divergent beta diversity patterns.Specifically,climate-driven species turnover and habitat heterogeneity-related species nestedness dominated the regions east and west of the line,respectively.Additionally,bird species with stronger dispersal ability were more susceptible to environmental filtering,resulting in more homogeneous assemblages.Our results indicated that regions with distinctive geographical backgrounds may present different ecological factors that lead to divergent assemblage dissimilarity patterns,and dispersal ability determines the response of assemblages to these ecological factors.Identifying a single universal explanation for the observed pattern without considering these aspects may lead to simplistic or incomplete conclusions.Consequently,a comprehensive understanding of large-scale beta diversity patterns and effective planning of conservation strategies necessitate the consideration of both geographical background and species dispersal ability.

Remote sensing of subtropical tree diversity:The underappreciated roles of the practical definition of forest canopy and phenological variation

Tree species diversity is vital for maintaining ecosystem functions,yet our ability to map the distribution of tree diversity is limited due to difficulties in traditional field-based approaches.Recent developments in spaceborne remote sensing provide unprecedented opportunities to map and monitor tree diversity more efficiently.Here we built partial least squares regression models using the multispectral surface reflectance acquired by Sentinel-2 satellites and the inventory data from 74 subtropical forest plots to predict canopy tree diversity in a national natural reserve in eastern China.In particular,we evaluated the underappreciated roles of the practical definition of forest canopy and phenological variation in predicting tree diversity by testing three different definitions of canopy trees and comparing models built using satellite imagery of different seasons.Our best models explained 42%–63%variations in observed diversities in cross-validation tests,with higher explanation power for diversity indices that are more sensitive to abundant species.The models built using imageries from early spring and late autumn showed consistently better fits than those built using data from other seasons,highlighting the significant role of transitional phenology in remotely sensing plant diversity.Our results suggested that the cumulative diameter(60%–80%)of the biggest trees is a better way to define the canopy layer than using the subjective fixeddiameter-threshold(5–12 cm)or the cumulative basal area(90%–95%)of the biggest trees.Remarkably,these approaches resulted in contrasting diversity maps that call attention to canopy structure in remote sensing of tree diversity.This study demonstrates the potential of mapping and monitoring tree diversity using the Sentinal-2 data in species-rich forests.