Predicting the movement speeds of animals in natural environments

Wilson, Robbie S., Husak, Jerry F., Halsey, Lewis G. and Clemente, Christofer J. (2015). Predicting the movement speeds of animals in natural environments. In: Towards a General Framework for Predicting Animal Movement Speeds in Nature, West Palm Beach, Florida, (1125-1141). 3-7 January 2015. doi:10.1093/icb/icv106

Author Wilson, Robbie S.
Husak, Jerry F.
Halsey, Lewis G.
Clemente, Christofer J.
Title of paper Predicting the movement speeds of animals in natural environments
Conference name Towards a General Framework for Predicting Animal Movement Speeds in Nature
Conference location West Palm Beach, Florida
Conference dates 3-7 January 2015
Convener Wilson, Robbie S.
Journal name Integrative and Comparative Biology   Check publisher's open access policy
Place of Publication Oxford, United Kingdom
Publisher Oxford University Press
Publication Year 2015
Year available 2015
Sub-type Fully published paper
DOI 10.1093/icb/icv106
Open Access Status Not Open Access
ISSN 1557-7023
Volume 55
Issue 6
Start page 1125
End page 1141
Total pages 17
Collection year 2016
Language eng
Abstract/Summary 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.
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status UQ

Document type: Conference Paper
Collections: Official 2016 Collection
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