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AIM: The relationship between the proportion of sites occupied by a species and the area of a site [occupancy–area relationship (OAR)] offers key information for biodiversity management and has long fascinated ecologists. We quantified the variation in OAR for 3,157 woody species in 17 forest plots worldwide and tested the relative importance of environment and species traits for explaining this variation and evaluated overall model predictive ability. LOCATION: Global. TIME PERIOD: Early 21st century. MAJOR TAXA STUDIED: Woody plants. METHODS: We used mixed‐effect regression to examine the observed shape of the OAR (its “slope”) against species‐specific and plot‐wide predictors: coarse‐grain occupancy, tree size, plot species richness, energy availability and topographic complexity. RESULTS: We found large variation in OAR slopes, and the variation was strongest among species within plots. The OAR slopes showed a latitudinal trend and were steeper near the equator. As predicted, coarse‐grain occupancy and tree size negatively affected OAR slopes, whereas species richness had a positive effect and explained most of the variance between plots. Although hypothesized directionalities were broadly confirmed, traits and environment had relatively limited overall predictive power. MAIN CONCLUSIONS: These results document the variation of the OAR for 3,157 species at near‐global extent. We found a latitudinal gradient in OAR slopes and confirmed key hypothesized predictors. But at this global extent and over the large set of species analysed, the remaining unexplained variation in OAR slopes was substantial. Nevertheless, this large‐scale empirical analysis of the OAR offers an initial step towards a more general use of OARs for the fine‐scale prediction of species distributions and abundance.

Aims With the aim of understanding why some of the world's forests exhibit higher tree beta diversity values than others, we asked: (1) what is the contribution of environmentally related variation versus pure spatial and local stochastic variation to tree beta diversity assessed at the forest plot scale; (2) at what resolution are these beta-diversity components more apparent; and (3) what determines the variation in tree beta diversity observed across regions/continents? Location World-wide. Methods We compiled an unprecedented data set of 10 large-scale stem-mapping forest plots differing in latitude, tree species richness and topographic variability. We assessed the tree beta diversity found within each forest plot separately. The non-directional variation in tree species composition among cells of the plot was our measure of beta diversity. We compared the beta diversity of each plot with the value expected under a null model. We also apportioned the beta diversity into four components: pure topographic, spatially structured topographic, pure spatial and unexplained. We used linear mixed models to interpret the variation of beta diversity values across the plots. Results Total tree beta diversity within a forest plot decreased with increasing cell size, and increased with tree species richness and the amount of topographic variability of the plot. The topography-related component of beta diversity was correlated with the amount of topographic variability but was unrelated to its species richness. The unexplained variation was correlated with the beta diversity expected under the null model and with species richness. Main conclusions Because different components of beta diversity have different determinants, comparisons of tree beta diversity across regions should quantify not only overall variation in species composition but also its components. Global-scale patterns in tree beta diversity are largely coupled with changes in gamma richness due to the relationship between the latter and the variation generated by local stochastic assembly processes.