Predicting the Movement Speeds of Animals in Natural Environments

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Abstract

An animal's movement speed affects all behaviors and underlies the intensity of an activity, the time it takes to complete it, and the probability of successfully completing it, but which factors determine how fast or slow an animal chooses to move? Despite the critical importance of an animal's choice of speed (hereafter designated as "speed-choice"), we still lack a framework for understanding and predicting how fast animals should move in nature. In this article, we develop a framework for predicting speed that is applicable to any animal-including humans-performing any behavior where choice of speed occurs. To inspire new research in this area, we (1) detail the main factors likely to affect speed-choice, including organismal constraints (i.e., energetic, physiological, and biomechanical) and environmental constraints (i.e., predation intensity and abiotic factors); (2) discuss the value of optimal foraging theory in developing models of speed-choice; and (3) describe how optimality models might be integrated with the range of potential organismal and environmental constraints to predict speed. We show that by utilizing optimality theory it is possible to provide quantitative predictions of optimal speeds across different ecological contexts. However, the usefulness of any predictive models is still entirely dependent on being able to provide relevant mathematical functions to insert into such models. We still lack basic knowledge about how an animal's speed affects its motor control, maneuverability, observational skills, and vulnerability to predators. Studies exploring these gaps in knowledge will help facilitate the field of optimal performance and allow us to adequately parameterize models predicting the speed-choice of animals, which represents one of the most basic of all behavioral decisions.

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APA

Wilson, R. S., Husak, J. F., Halsey, L. G., & Clemente, C. J. (2015). Predicting the Movement Speeds of Animals in Natural Environments. In Integrative and Comparative Biology (Vol. 55, pp. 1125–1141). Oxford University Press. https://doi.org/10.1093/icb/icv106

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