Choices to landscapes: Mechanisms of animal movement scale to landscape patterns

Abstract

Understanding the geographic distributions of animals is central to ecological inquiry and conservation planning. Movement-based habitat selection models offer a powerful tool for identifying preferred environmental attributes, yet applying these models to predict animal geographic distributions faces methodological and computational challenges. Here, we present a framework that integrates habitat selection and movement behaviors to generate landscape-scale space use predictions. Through simulations and empirical data, we demonstrate that combining local selection and movement dynamics yields highly accurate emergent spatial distribution predictions. Our framework outperforms occurrence-based frameworks across individual, population, and regional scales. By explicitly addressing the role of movement constraints and selection patterns in heterogeneous environments, our framework bridges animal movement and spatial distribution modeling in a scalable manner. This approach offers a new paradigm to link organism-environment interactions from individual space use to habitat connectivity and population distributions relevant to policy and conservation.