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Walking the line: search behavior and foraging success in ant species


  • Jessica M.C. Pearce-Duvet
  • Coen P.H. Elemans
  • Donald H. Feener


Finding food is one of the most important tasks an animal faces. Although the impact of behavior and morphology on individual foraging success is well characterized, an understanding of the extent of interspecific differences in these traits as well as their influence on resource competition is lacking. Temperate ant communities represent an ideal opportunity for examining how search behavior and morphology affect a species' ability to find food first because ant species demonstrate both a wide range of foraging patterns and intense interspecific competition for food resources. For 10 species across 2 communities, species-specific speed and turning rate were quantified by filming their foraging behavior in nature; we also measured the ratio of leg length to body length of their foragers. Food discovery ability was determined by observing which species found baits first when they were present in the immediate environment. Our results show that foraging patterns are species specific, suggesting that search behavior is an important component of niche separation in ant communities. We also suggest that ant species maximize discovery success at the community level using both behavioral and morphological mechanisms. Good discoverers moved in straighter lines, thereby possibly increasing their chances of finding food, and had longer legs relative to their body size, increasing their efficiency of movement. Copyright 2011, Oxford University Press.

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  • Jessica M.C. Pearce-Duvet & Coen P.H. Elemans & Donald H. Feener, 2011. "Walking the line: search behavior and foraging success in ant species," Behavioral Ecology, International Society for Behavioral Ecology, vol. 22(3), pages 501-509.
  • Handle: RePEc:oup:beheco:v:22:y:2011:i:3:p:501-509

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    References listed on IDEAS

    1. Bates, Douglas & M├Ąchler, Martin & Bolker, Ben & Walker, Steve, 2015. "Fitting Linear Mixed-Effects Models Using lme4," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 67(i01).
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