Improving island occupancy predictions using ecologically informed metrics of area and isolation

Understanding how species occupy islands and habitat patches remains a central question in biogeography, landscape ecology, conservation, and management, especially as natural and anthropogenic processes reconfigure habitat size and connectivity over time. The insular distribution function (IDF) provides a framework for predicting occupancy patterns for a species based on island area and isolation as proxies for extinction risk and colonization likelihood. While this model provides a conceptual bridge between island biogeography and metapopulation models, it has seen limited recent application in large part due to reliance on simplistic geometric measures of area and isolation. Here, we advance the implementation of the IDF by pulling from ecological niche modeling and landscape ecology to incorporate ecologically informed quantifications of area and isolation. We apply this framework to the montane sky-islands of the Great Basin of the western United States, testing predictions for the Western Water Shrew (Sorex navigator). Compared with those based on traditional geometric metrics, the ecologically informed IDFs produced a discriminant function with lower classification error, stronger class separation, and different biological conclusions regarding the species' inferred response to isolation and area. The results from the ecologically informed IDF provide a contrast to IDF based on geographic axes and the classical interpretations for the system. Specifically, the steeper slope and lower intercept of the ecologically informed IDF point toward a system structured not so strongly by extinction-driven relaxation, but by a more compensatory trade-off in which both colonization and extinction have shaped occupancy patterns. Simulations of false-absence rates (which affect datasets in lesser-sampled systems) showed that the same inferences persisted in the presence of incomplete sampling. These results highlight the potential of integrating contemporary approaches with classic biogeographic models, as well as strengthening and clarifying links between island biogeography and landscape ecology. This updated analytical framework offers new opportunities for assessing subpopulation vulnerability, incorporating ecologically informed measures into occupancy-based statistical frameworks, forecasting patchy species distributions across a full community, and studying how past and future environmental changes shape biodiversity patterns.