Predator-prey space use as an interactive game


Patterns of habitat use and overlap between predators and prey are clearly critical for understanding predator-prey outcomes that can have important impacts on various issues in basic and applied ecology.  Hundreds of studies have shown that predators tend to go where there are more prey, and that prey tend to avoid areas with more predators.  Interestingly, most of these studies have examined one side of the story, while keeping the other side static.  That is, experimental studies on predator optimal patch use usually use essentially immobile prey (e.g., birds feeding on worms), while studies on prey avoidance of predators usually cage predators to one side of the arena, or provide localized predator cues (e.g., chemical cues) without actual predators.  Of course, in nature, both predators and prey can respond to each other; their joint response can be viewed as a race or game.  If predator responses dominate, then predator and prey distributions should be positively correlated (predators should be more abundant in places where there are more prey), while if prey responses dominate, then the two should be negatively correlated (prey should be less abundant in areas where there are more predators).  Interestingly, if these opposing responses cancel each other, predators and prey might be randomly distributed relative to each other. Surprisingly little work (theoretical or empirical) has focused on understanding how the game between predators and prey determines their joint pattern of space use.

Funded by a recent NSF grant that supported a postdoc, Barney Luttbeg (now an assistant professor at Oklahoma State), and a PhD student, John Hammond, we ran a series of experiments looking at predator-prey joint distributions and behavior (using amphibian larvae and their predators), developed new model choice methods for identifying behavioral mechanisms underlying emergent spatial patterns, collected a large amount of field data on predator-prey spatial distributions, and developed new theory (using genetic algorithms) on this predator-prey game.  To date, this project has produced several theoretical and empirical papers in top journals (Bell et al. 2009; Hammond et al. 2012; Hammond, Luttbeg & Sih 2007; Luttbeg, Hammond & Sih 2009; Luttbeg & Sih 2004; Sih 1998).


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