Predicting bird potential distribution: A method linking changes in functional connectivity of green spaces in high-density cities

Land use changes in high-density cities profoundly affect green space functional connectivity (GSFC) and bird distributions. However, most existing studies have not yet clarified the dynamic influence patterns of land use change on GSFC, nor how the coupled evolution of land use and GSFC drives the spatial restructuring of potential distributions for bird species with different ecological habits. To fill this gap, an innovative interdisciplinary framework is proposed by coupling the PLUS model, circuit theory, and MaxEnt model to explore causal relationships between land use change, GSFC variation, and bird redistribution in downtown Shanghai. Land use patterns for 2014–2024 and a 2034 planning scenario were simulated via the PLUS model, GSFC quantified using circuit theory, and integrated with climatic and other environmental variables into MaxEnt for bird distribution prediction. Results revealed that: (1) green space area increased markedly (+16%) in 2014–2024, driving GSFC improvement; the 2034 scenario saw slowed, fragmented green space expansion, constraining GSFC. (2) MaxEnt achieved high accuracy (mean AUC > 0.87), with GSFC as the second most influential variable (14.6% contribution)—a key non-climatic driver complementing climatic factors. (3) future highly/moderately suitable bird habitats contracted by 13.6% and 11.2%, with species' divergent responses linked to dispersal capabilities and habitat requirements. Findings highlight GSFC as a pivotal mediator between land use change and bird distribution. Future urban ecological planning should prioritize GSFC over mere green coverage, optimizing spatial structure, functional quality, and ecological corridors. This study provides a scientific basis for bird diversity conservation and ecological network optimization, with a replicable model coupling framework for similar high-density urban contexts.