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ABSTRACT Disparate bodies of literature implicate risk avoidance and energy conservation as important drivers of animal movement decisions. Theory posits that these phenomena interact in ecologically consequential ways, but rigorous empirical tests of this hypothesis have been hampered by data limitations. We fuse fluid dynamics, telemetry, and attack data to reconstruct risk and energy landscapes traversed by migrating juvenile salmon and their predators. We find that migrants primarily use midriver microhabitats that facilitate migration at night. During daylight, predators become more aggressive in the midriver, and prey reduce midriver use in favour of nearshore microhabitats, resulting in increased energy expenditure and decreased migration efficiency. Predators attack most when migrants are not prioritising threat avoidance and during ephemeral periods of low lighting. Our findings suggest that predator–prey interactions result from an interplay between landscapes of fear and energy, which can determine the degree to which predators affect prey through mortality or fear. 

Predator–prey interactions are fundamental to ecological and evolutionary dynamics. Yet, predicting the outcome of such interactions—whether predators intercept prey or fail to do so—remains a challenge. An emerging hypothesis holds that interception trajectories of diverse predator species can be described by simple feedback control laws that map sensory inputs to motor outputs. This form of feedback control is widely used in engineered systems but suffers from degraded performance in the presence of processing delays such as those found in biological brains. We tested whether delay-uncompensated feedback control could explain predator pursuit manoeuvres using a novel experimental system to present hunting fish with virtual targets that manoeuvred in ways that push the limits of this type of control. We found that predator behaviour cannot be explained by delay-uncompensated feedback control, but is instead consistent with a pursuit algorithm that combines short-term forecasting of self-motion and prey motion with feedback control. This model predicts both predator interception trajectories and whether predators capture or fail to capture prey on a trial-by-trial basis. Our results demonstrate how animals can combine short-term forecasting with feedback control to generate robust flexible behaviours in the face of significant processing delays.