Biodiversity data synthesis on trees of Indian Himalayan Region: Policy and management implications

Abstract

The recent adoption of Kunming-Montreal Global Biodiversity Framework requires empirical synthesis of biodiversity data spanning across broad biogeographic scales to inform conservation policy and management. Although the availability and access to biodiversity databases have recently improved, yet majority of these databases lack sufficient geographic coverage, especially from the biodiversity hotspot regions of developing countries, thereby severely limiting their utility and generalizability across the globe. Here, we present a comprehensive tree database (2199 species) of the Indian Himalayan Region (IHR) – home to two global biodiversity hotspots – collated from a quantitative synthesis of 234 studies published over the last one century. Taking leverage of this novel database, we unravel the patterns of diversity, distribution, and drivers of the trees of IHR. We found that the species richness, compositional similarity, distribution patterns, and biome affiliation of the tree diversity vary significantly across the IHR, with nearly half of the tree species affiliated with the wet tropical biome. Of the 10 climatic and environmental drivers used, the annual mean temperature and elevation width in combination best predicted the variation in tree diversity across the IHR. We also document 117 endemic and 88 threatened tree species in the IHR, which merit conservation priority. Our findings have significant utility in formulating management and restoration strategies for biodiversity conservation across the IHR. Overall, our study showcases a model biodiversity database with wide policy implications in the planning and management of tree-focussed environmental programs to restore the degraded forest landscapes and plantation-specific climate change mitigation strategies in the region.

Keywords

• Biodiversity databases
• Trees
• Biodiversity hotspots
• Conservation
• Management