Integrating biodiversity assessment into landscape planning: A configuration optimization framework for bird conservation under climate change in urban agglomerations

Climate change and urbanization drive biodiversity loss, posing significant threats to bird conservation in urban agglomerations. While previous studies have primarily relied on species distribution models to predict habitat responses to climate and land-use change, their outputs largely remain at the level of predictive spatial mapping, providing limited support for land management. To address this limitation, this study proposes a landscape configuration optimization framework that integrates biodiversity assessment with a landscape-based approach under coupled climate and land-use change. Using the Beijing-Tianjin-Hebei region as a case study, we combined the PLUS and MaxEnt models to simulate land-use change and predict bird habitat suitability under multiple climate scenarios. IndVal analysis at the scale of landscape units was then applied to establish species-landscape associations and identify strategic landscape types whose configuration optimization can most effectively enhance habitat suitability. Results show that eleven strategic landscape types were identified, with highly fragmented forest/grass/cropland landscapes and homogeneous urban landscapes showing the greatest potential for improvement. Although spatial patterns of habitat change vary across climate scenarios, optimizing these strategic landscape configurations consistently enhances habitat suitability for bird species groups. Given that over 25% of species are projected to experience persistent habitat loss, management should prioritize configuration optimization within habitat-change hotspots and the ranges of climate-threatened species. This study provides a replicable framework for translating biodiversity assessment into actionable landscape optimization strategies, offering practical guidance for biodiversity conservation while accommodating human land-use demands in urban agglomerations.