Cross-boundary footprints: Modelling biodiversity responses to urbanization, agriculture, and climate variability

Understanding how human and climatic drivers shape biodiversity requires models that capture both local dynamics and cross-boundary interactions. This study employs the Spatial Durbin Model (SDM) to investigate biodiversity patterns across 22 administrative regions, integrating species richness and the Shannon–Wiener Index derived from 21 taxonomic groups spanning vertebrates, invertebrates, and plants. Explanatory variables include industrial revenue, road density, population density, farmland, and long-term variation in rainfall and temperature. Results indicate that industrial activity consistently reduces biodiversity, while farmland and population density show positive local associations but generate negative spillovers, highlighting the need for regional coordination. Climatic variability exerts contrasting effects: rainfall instability undermines biodiversity both locally and regionally, whereas temperature variation produces local losses but regional gains as species redistribute across boundaries. Model diagnostics confirm strong spatial dependence, underscoring the necessity of spatially explicit frameworks. By combining biodiversity indicators with spatial econometrics, this research demonstrates that ecological outcomes emerge from multi-scalar processes shaped by land use, urban growth, and climate change. The findings provide a modelling framework for predicting biodiversity responses and designing conservation strategies in interconnected landscapes.