Optimal Performance

Movement is fundamental to animal behavior, governing the way animals use habitats, interact with conspecifics, avoid predators, obtain food and even negotiate human-modified landscapes. The rapidly expanding field of movement ecology offers a unifying paradigm for the causes, consequences, underlying mechanisms and patterns of movement-related phenomena.

But what determines how fast an animal chooses to move? This may seem like a simple question, but it is a key one: movement speed underlies the intensity of an activity, the time it takes to complete it and the probability of successful completion. Despite the universal importance of speed and its central role in movement ecology, we still lack a framework for understanding and predicting how fast or slow animals should—or do—move through their environments. 

Historically, speed has been studied within the context of animal form and function rather than behaviour—functional traits such as morphology, physiology and biochemistry are linked with reproductive success and survival via whole-animal performance . Whole-animal performance is usually defined as the maximum speed or effort an individual can attain in a movement task relevant to their fitness, with better performers thought to have better survival and reproduction. This has led to a fundamental bias in the study of animal movement—the idea that animals should always perform at their maximum capabilities, or at least in tasks that directly affect their survival, like escaping from predators or catching prey. Though this idea is appealing, field observations show that animals rarely move at their maximum capabilities in nature, even during predator escape and prey capture scenarios. Maximum speeds are energetically costly, constrain motor control and manoeuvrability and affect visibility and safety. Speed—even in extreme situations like escaping predation—should be based on compromises between factors.

Such constraints on movement speed also impact human behavior during everyday activities – intuitively, we are all aware of this. Humans rarely use their maximal speeds for common daily tasks for the same reasons, high speeds increase energetic costs and can decrease the control and accuracy of a movement.

Just consider how one would approach typing out a text message if one were already late to an important meeting. We may not wish to be even later to the meeting – especially given the social costs of delaying colleagues - so getting the text message done without delay may make rapid typing favorable. However, typing requires accurate finger placement and a potential mistake, which is more likely at higher speeds, could be very costly, both because of the social embarrassment of sending a message that is full of mistakes and because it may be incomprehensible. Typing at a slower and more measured speed is likely to improve readability of the message and decrease any chances of having to retype a message. In this case, there may be an optimal speed for movement that is a compromise between speed, accuracy and social constraints. We expect similar constraints to operate on the movement speeds of animals across natural ecological contexts, with the ultimate selection of speed based on a compromise between competing demands.

In our lab, we are developing a general framework for predicting movement speeds that is applicable to any animal—including humans—performing any behavior where choice of speed occurs. Testing these ideas will require a trans-disciplinary approach, incorporating expertise from the fields of metabolic physiology, neurophysiology, biomechanics, mathematical modelling, behavior, evolution, and ecology. Because this work is conceptual in basis, we can apply the same framework to questions in the sports sciences when we are attempting to identify the best strategy for maximising winning success.

The questions we are addressing on wild animals in this research program include:

Aim 1: How fast do animals choose to move when escaping from predators?

Aim 2: How fast do animals choose to move when moving between foraging patches?

Aim 3: How fast do animals choose to move as they actively forage?

Selected publications in this area

Wilson RS, Husak JF. 2015. Introduction to the Symposium: Towards a General Framework for Predicting Animal Movement Speeds in Nature. Integrative and Comparative Biology 5 (6): 1121-1124. doi: 10.1093/icb/icv107

Clemente CJ & Wilson RS. 2015. Balancing biomechanical constraints: Optimal escape speeds when there is a trade-off between speed and manoeuvrability. Integrative and Comparative Biology.  55 (6): 1142-1154 doi:10.1093/icb/icv103

Wilson RS, Husak JF, Halsey L & Clemente CJ. 2015. Predicting the movement speeds of animals in natural environments. Integrative and Comparative Biology. 55 (6): 1125-1141 doi:10.1093/icb/icv106

Wheatley R, Angilletta MJ, Niehaus AC & Wilson RS. 2015. How fast should an animal run when escaping? An optimality model based on the trade-off between speed and accuracy. Integrative and Comparative Biology doi: 10.1093/icb/icv091.

Clemente C & Wilson RS. 2015. Speed and maneuverability jointly determine escape success during simulated games of escape behaviour. Behavioural Ecology. doi: 10.1093/beheco/arv080

Wynn ML, Clemente C, Amir Abdul Nasir AF & Wilson RS. 2015. Running faster causes disaster: trade-offs between speed, manoeuvrability and motor control when running around corners in northern quolls (Dasyurus hallucatus). Journal of Experimental Biology 218: 433-439.

Lailvaux S, Wilson RS & Kasumovic M. 2014. Trait compensation and sex-specific aging of performance in male and female professional basketball players. Evolution 68(5):1523-32.

McElroy E, Wilson RS, Biknevisius A & Reilly S. 2014. A comparative study of single leg ground reaction forces in running lizards. Journal of Experimental Biology 217: 735-742.

Wilson RS, Niehaus AC, David G, Hunter A & Smith M. 2014. Individual quality masks the detection of performance trade-offs: A test using analyses of human physical performance. Journal of Experimental Biology 217: 545-55.

Cameron SF, Wynn ML, and Wilson RS. 2013. Sex-specific trade-offs and compensatory mechanisms: bite force and sprint speed pose conflicting demands on the design of geckos (Hemidactylus frenatus). Journal of Experimental Biology 216: 3781-3789.

Niehaus AC, Angilletta MJ, Sears M, Franklin CE & Wilson RS. 2012. Predicting the physiological performance of ectotherms in fluctuating thermal environments. Journal of Experimental Biology 215: 694-701.

Latimer, CA, Wilson RS and Chenoweth SF. 2011. Quantitative genetic variation for thermal performance curves within and among natural populations of Drosophila serrata. Journal of Evolutionary Biology 24: 965-975.

Alton LA,  Wilson RS & Franklin CE. 2011. A small increase in UV-B increases the susceptibility of tadpoles to predation. Proceedings of the Royal Society of London Series B 278, 2575-2583. View abstract here.

Wilson RS, Lefrancois C, Domenici P & Johnston IA. 2010. Environmental influences on unsteady swimming behaviour: consequences for predator-prey and mating encounters in teleosts In Fish Locomotion: An eco-ethological perspective (Eds Domenici, P & Kapoor, BG). Science Publishers, NH, USA. 

Wilson RS, Condon CH, David G, FitzGibbon SI, Niehaus AC & Pratt K. 2010. Females prefer athletes, males fear the disadvantaged: different signals used in female choice and male competition have varied consequences. Proceedings of the Royal Society of London Series B 277: 1923-1928. View abstract here.

Condon CH, Chenoweth SF & Wilson RS. 2010. Zebrafish take their cue from temperature but not photoperiod for the seasonal plasticity of thermal performance. Journal of Experimental Biology 213, 3705-3709. View abstract here.

Barth B & Wilson RS. 2010. Life in Acid: interactive effects of pH and natural organic acids on growth, development and locomotor performance of larval striped marsh frogs (Limnodynastes peronii). Journal of Experimental Biology 213: 1293-1300. View full text here.

Lowe K, FitzGibbon SI, Seebacher F & Wilson RS. 2010. Physiological and behavioural responses to seasonal changes in environmental temperature in the Australian spiny crayfish Euastacus sulcatus. Journal of Comparative Physiology B 180: 653-660. View abstract here.

Bowndes C, Wilson RS and Marshall DJ. 2010. Why do colder mothers produce larger eggs? An optimality model. Journal of Experimental Biology 213, 3796-3801. View abstract here.

Wilson RS, James RS, Bywater C, Seebacher F. 2009. Costs and benefits of increased weapon size differ between sexes of the slender crayfish, Cherax dispar. Journal of Experimental Biology 212:853-858. View abstract here.

Angilletta MJ, Wilson RS, Niehaus AC & Ribiero P. 2008. The fast and the fractalous: tradeoffs between running speed and manoeuvrability in leaf-cutter ants. Functional Ecology 22:78-83. View abstract here.
James RS & Wilson RS. 2008. Explosive jumping: Morphological and physiological specialisations for extreme jumping in Australian rocket frogs. Physiological and Biochemical Zoology 81:176-185. View abstract here.

Kraft P, Wilson RS & Franklin CE. 2005. Phenotypic plasticity as a defence strategy in tadpoles of Limnodynastes peronii: Induction cues, costs and benefits. Austral Ecology 30:558-563.     

Wilson RS & James RS. 2004. Constraints on muscular performance: trade-offs between power output and fatigue-resistance in skeletal muscle. Proceedings of the Royal Society of London B 271: S222-S225.

Van Damme R, Wilson RS, Van Hooydonck B, & Aerts P. 2002. Performance constraints in decathletes. Nature 415:755-756. View abstract here.

Wilson RS, Franklin CE, James RS & Johnston IA. 2000. Allometric scaling relationships of jumping performance in the striped marsh frog Limnodynastes peronii. Journal of Experimental Biology 203: 1937-1946. View abstract here.