Species richness, body size, and range size are among key subjects in animal macroecology and biogeography. To date, the species richness–body size–range size nexus remains largely understudied at a global scale and for large taxonomic groups. Here we examine the relative role of species richness and body size in determining species range size among terrestrial vertebrates across spatial and taxonomic scales. We then test related hypotheses in the context of Rapoport’s rule, latitude, and climate variation. To do this, we used simultaneous autoregressive analysis and structural equation modeling to test for statistical relationships among species richness, body size, and range size for all terrestrial vertebrates and for each continent. We then investigated the relative contributions of richness, body size, latitude, climate variation, and their combinations in the variations in species range sizes. We found that species richness consistently shows strong negative correlations with range size at global, regional, and within-region levels, and for all terrestrial vertebrates, and for each of the four classes (i.e., birds, mammals, amphibians, and reptiles). The strength of the relationships increased with richness and with spatial and taxonomic scales. Globally, species richness explained more variation in species range size than did latitude and climates. Body size contributed significantly to the range sizes of all four classes but especially reptiles and amphibians. However, the relative contributions of these factors varied substantially among the continents and terrestrial vertebrate classes. Comparison with the findings of a previous study shows that there were also significant differences in regional patterns between terrestrial vertebrates and plants and the relative contributions of diversity vs. latitude. Our findings show clear relationships among species richness, body size, and range size, but the strength of the relationships varies among regions and taxonomic groups. In general, species richness could predict species range size better than body size, latitude, and climate. These results have important theoretical and applied implications.

The elevational patterns of plant β diversity and their underlying drivers are known to be scale-dependent, but pinpointing the spatial scales at which different ecological processes occur remains challenging using traditional field inventory methods. Remote sensing has emerged as a promising alternative, providing continuous spatial data for monitoring plant diversity. In this study, we used field inventory data and corresponding Sentinel-2 images from a subtropical mountain to simulate pooled assemblages and assess the potential of using multispectral satellite images in predicting tree β diversity. We further examined the scale-dependent elevational gradient of the spectral β diversity and identified primary topographic variables across different spatial extents (0.16–64 ha). The spectral β diversity showed a consistently positive relationship with the inventory β diversity calculated using various indices (average pairwise Sørensen, Jaccard, and Bray–Curtis dissimilarities, as well as multi-community differentiation measures based on Hill numbers), with the strongest correlation observed for abundance-weighted indices and images from early spring and late autumn (R²_max = 0.63). However, a null model-derived β deviation showed only a weak correlation between remote sensing and field-based measures. A declining trend in the spectral β diversity with an increasing elevation was observed and became more pronounced at larger extents. The topographic heterogeneity, represented by the slope and northness, explained the elevational gradients at spatial extents >4 ha, attesting the significant role of environmental filtering in shaping plant diversity patterns, even at fine scales. While the northness was more influential at smaller spatial extents (4 ha). This study showcases the potential of using readily available remote sensing data to address difficult questions in plant diversity research.

Old trees function as enduring ecological legacies that preserve historical biodiversity within intensively human-modified landscapes, yet the relative influence of environmental versus anthropogenic drivers on their diversity remains unclear. Here, we aim to disentangle the joint effects of climate, urbanization intensity and cultural preservation on old-tree density and community composition. We analyzed a province-wide census of 21,733 old-tree individuals across 115 counties in Shanxi Province, China, encompassing species origin (native vs. nonnative) and growth form (trees vs. shrubs). Old-tree density was assessed using spatial simultaneous autoregressive error models, while compositional dissimilarity was quantified using generalized dissimilarity modeling. In total, 131 species were recorded, with four dominant species comprising more than 75% of all individuals. Old-tree density increased with mean annual temperature, human population density, and cultural heritage abundance, but declined sharply with cropland coverage. Driver importance varied among groups: native species were primarily governed by climatic conditions, nonnative species by land-use intensity, and tree-form old trees were positively associated with cultural heritage abundance, an effect absent in shrub-form old trees. Compositional dissimilarity was driven mainly by climatic gradients and spatial distance, with additional contributions from human-related variables, particularly for nonnative assemblages. Our findings demonstrate that climate and spatial processes establish the regional framework of old-tree community composition, while cultural and demographic contexts promote local retention of old trees. By explicitly integrating ecological filters with socio-cultural drivers, this study advances old-tree research through a large-scale empirical framework, providing both scientific insight and socially relevant guidance for conservation under land-use intensification and climate warming.