Meeting Linnean, Wallacean, and Darwinian shortfalls in global biodiversity hotspots: A model study from the Indian Himalayan Region

Abstract Despite recent efforts to make large‐scale biodiversity datasets available, several data shortfalls still exist that preclude our progress in achieving global conservation and sustainability goals. In this study, we present a comprehensive native tree dataset (1689 species) from the Indian Himalayan Region (IHR)—home to two global biodiversity hotspots—assembled from an extensive data synthesis. Based on this database, we investigate the geographic patterns and drivers of α‐ and β‐taxonomic and phylogenetic diversity of the native trees among 13 different provinces of IHR. Our results revealed a considerable variation in the α‐ and β‐taxonomic and phylogenetic diversity among the provinces of IHR, with the highest values in eastern provinces. We found phylogenetic clustering mostly in the western provinces, and phylogenetic dispersion in the eastern provinces. We found a positive correlation between the taxonomic and phylogenetic dissimilarity across the IHR. Also, the different sets of explanatory variables explained the variation of tree species richness, standardized effect size of phylogenetic diversity, net relatedness index, and nearest taxon index, with maximum contribution by temperature seasonality (Bio4). Furthermore, temperature‐related climatic distance individually explained most of the variation in the taxonomic and phylogenetic dissimilarity between the provinces of IHR. Overall, our findings unveil the patterns of taxonomic, biogeographic, and phylogenetic dimensions of tree flora in the IHR, which in turn can help in formulating scientific data‐based regional policy and conservation strategies. Looking forward, we presented a model study for bridging the Linnean, Wallacean, and Darwinian shortfalls in the globally data‐deficient biodiversity‐rich regions.