Integrating projected habitat change and existing population trends to prioritise conservation, monitoring, and research for Indian birds

Abstract

Understanding species vulnerability to global change requires approaches that integrate projections of future environmental change with empirical population trends; such integrated assessments remain limited in biodiverse, data-limited tropical regions. In this study, we develop and apply a scalable, decision-oriented framework that synthesises climate and land-cover projections with existing contemporary population data to assess species-level vulnerability and conservation, monitoring, and research priorities for Indian birds. Using an ensemble of machine-learning habitat-suitability models, we projected current and future habitat suitability for 955 species under two 2100 scenarios (SSP3-7.0 and SSP5-8.5). We then integrated these projections with population trends from the State of Indias Birds assessment. We found habitat responses were highly heterogeneous: 507 species were projected to lose suitable habitat under both future scenarios, 327 species were projected to gain habitat, and 121 species exhibited mixed or uncertain responses. The direction and magnitude of projected change varied substantially within and among habitat-specialisation guilds, with overall losses exceeding gains. The synthesis of habitat projections with population trends revealed 121 (mostly wetland) species facing ongoing population decline and future habitat loss, representing high-priority targets for immediate conservation action. A further 300 species, largely forest-associated, were projected to lose habitat but lacked reliable population trend data, highlighting substantial monitoring gaps, while species with mixed or uncertain habitat trajectories emerged as key research priorities. By explicitly integrating projected habitat change, contemporary population trajectories, and data availability, this study advances a transferable framework for prioritising conservation action, monitoring, and research under accelerating global change.