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Spontaneous formation of multiple routes in individual desert ants (Cataglyphis velox)

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  • Michael Mangan
  • Barbara Webb

Abstract

Desert ants make use of various navigational techniques, including path integration and visual route following, to forage efficiently in their extremely hostile environment. Species-specific differences in navigation have been demonstrated, although it remains unknown if these divergences are caused by environmental adaptation. In this work, we report on the navigational strategies of the European ant Cataglyphis velox, which inhabits a visually cluttered environment similar to the Australian honey ant Melophorus bagoti, although it is more closely related to other North African Cataglyphis species. We show that C. velox learn visually guided routes, and these are individual to each forager. Routes can be recalled in the absence of global path integration information or when placed in conflict with this information. Individual C. velox foragers are also shown to learn multiple routes through their habitat. These routes are learned rapidly, stored in long-term memory, and recalled for guidance as appropriate. Desert ants have previously been shown to learn multiple routes in an experimental manipulation, but this is the first report of such behavior emerging spontaneously. Learning multiple paths through the habitat over successive journeys provides a mechanism by which ants could memorize a series of interlaced courses, and thus perform complex navigation, without necessarily having a map of the environment.

Suggested Citation

  • Michael Mangan & Barbara Webb, 2012. "Spontaneous formation of multiple routes in individual desert ants (Cataglyphis velox)," Behavioral Ecology, International Society for Behavioral Ecology, vol. 23(5), pages 944-954.
  • Handle: RePEc:oup:beheco:v:23:y:2012:i:5:p:944-954.
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    File URL: http://hdl.handle.net/10.1093/beheco/ars051
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    Cited by:

    1. Olivier J N Bertrand & Jens P Lindemann & Martin Egelhaaf, 2015. "A Bio-inspired Collision Avoidance Model Based on Spatial Information Derived from Motion Detectors Leads to Common Routes," PLOS Computational Biology, Public Library of Science, vol. 11(11), pages 1-28, November.

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