Unpredictable movement as an anti-predator strategy

Richardson, Graham, Dickinson, Patrick, Burman, Oliver and Pike, Tom (2018) Unpredictable movement as an anti-predator strategy. Proceedings of the Royal Society B: Biological Sciences, 285 (1885). p. 20181112. ISSN 0962-8452

Full content URL: http://doi.org/10.1098/rspb.2018.1112

Unpredictable movement as an anti-predator strategy
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Prey animals have evolved a wide variety of behaviours to combat the threat of predation, and these have been generally well studied. However, one of the most common and taxonomically widespread antipredator behaviours of all has, remarkably, received almost no experimental attention: so-called ‘protean’ behaviour. This is behaviour which is sufficiently unpredictable to prevent a predator anticipating in detail the future position or actions of its prey. In this study, we used human ‘predators’ participating in 3D virtual reality simulations to test how protean (i.e. unpredictable) variation in prey movement affects participants’ ability to visually target them as they move (a key determinant of successful predation). We found that targeting accuracy was significantly predicted by prey movement path complexity, although, surprisingly, there was little evidence that high levels of unpredictability in the underlying movement rules equated directly to decreased predator performance. Instead, the specific movement rules differed in how they impacted on targeting accuracy, with the efficacy of protean variation in one element depending on the values of the remaining elements. These findings provide important insights into the understudied phenomenon of protean antipredator behaviour, which are directly applicable to predator-prey dynamics within a broad range of taxa.

Additional Information:The final published version of this article can be accessed online at http://rspb.royalsocietypublishing.org/
Keywords:predator-prey interactions, anti-predator defence, unpredictability, virtual reality
Subjects:C Biological Sciences > C120 Behavioural Biology
Divisions:College of Science > School of Life Sciences
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ID Code:32978
Deposited On:20 Aug 2018 13:31

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