The paper reviews the defining features of human-modified environments and their effects on animal movement drivers, framed within the movement ecology paradigm (external environment, internal state, navigation, and motion capacity). It calls for a shift from purely correlative models toward mechanistic, dynamical systems approaches that incorporate functional parameters, experimental observations, and data collected across diverse taxa and contexts. The authors emphasize the importance of targeted data collection, careful treatment of scale and bias, and integration of new and historical datasets. They highlight opportunities such as rewilding and translocation projects, which provide natural experiments to test model predictions in novel settings. Ultimately, the paper argues that movement ecology is transitioning from being descriptive to predictive, a necessary step to provide robust, evidence-based tools for management and policy in a rapidly changing world.
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