Optimal movement decisions in complex landscapes

Understanding and predicting optimal movement decisions in complex and dynamic landscapes requires identifying the mechanisms driving movements, beyond correlations or simple energetic trade-offs between costs and gains. This is increasingly important as human activities transform landscapes at unprecedented rates, altering environmental predictability. As a result, animals must continually relearn and adapt to transformed, often degraded, environments, with consequences for their movement and fitness. We propose a structured movement framework that integrates abiotic and biotic drivers of foraging decisions. The net energyscape reflects spatial variation in net energy gains, while the optimal movement landscape includes non-energetic external modifiers, such as the landscape of fear. This framework opens improved avenues for more accurately identifying critical habitats and informing effective conservation strategies.