Multi-region occupancy models reveal broad-scale land-use effects on medium-sized mammals

Understanding wildlife responses to both anthropogenic pressures and natural environmental gradients requires large-scale and standardized surveys across broad spatial extents, enabling the identification of general patterns to assist tailored management strategies. Here, we aimed to identify the main environmental drivers shaping the occupancy patterns of widespread medium-sized mammals across multiple contrasting regions to support broad-scale inference on species-environment relationships. Using a well-replicated camera-trap dataset from 15 study areas distributed across three macrobioclimatic regions in mainland Portugal, we assessed how species occupancy was influenced by land-use composition and configuration, elevation, human footprint, seasonality, prey availability and hunting regimes, while accounting for spatial dependencies through nested random effects. Hierarchical modelling revealed that species detectability was weakly affected by covariates, whereas occupancy was primarily associated with broad-scale patterns of land-use composition and configuration, with additional effects of elevation for some species. In contrast, human footprint, hunting regimes and seasonality showed little or no detectable influence on occupancy across species at the broad spatial scale considered. Responses to land-use patterns differed among taxa, with lagomorphs showing strong but contrasting occupancy patterns along gradients of agricultural habitat structure, and carnivores exhibiting weaker and more variable responses associated with landscape heterogeneity. Overall, our results revealed consistent species-specific effects of land-use composition and configuration on broad-scale occupancy patterns of medium-sized mammals. These findings demonstrate the value of large-scale monitoring frameworks for moving beyond site-specific inference and informing transferable conservation strategies guided by land-use management across multiple regions and environmental contexts.