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Honeybee colonies achieve fitness through dancing

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  • Gavin Sherman

    (University of California)

  • P. Kirk Visscher

    (University of California)

Abstract

The honeybee dance language, in which foragers perform dances containing information about the distance and direction to food sources, is the quintessential example of symbolic communication in non-primates1,2. The dance language has been the subject of controversy3,4, and of extensive research into the mechanisms of acquiring1,5,6, decoding7,8 and evaluating9 the information in the dance. The dance language has been hypothesized, but not shown, to increase colony food collection1,9,10. Here we show that colonies with disoriented dances (lacking direction information) recruit less effectively to syrup feeders than do colonies with oriented dances. For colonies foraging at natural sources, the direction information sometimes increases food collected, but at other times it makes no difference. The food-location information in the dance is presumably important when food sources are hard to find, variable in richness and ephemeral. Recruitment based simply on arousal of foragers and communication of floral odour, as occurs in honeybees1, bumble bees11 and some stingless bees12, can be equally effective under other circumstances. Clarifying the condition-dependent payoffs of the dance language provides new insight into its function in honeybee ecology.

Suggested Citation

  • Gavin Sherman & P. Kirk Visscher, 2002. "Honeybee colonies achieve fitness through dancing," Nature, Nature, vol. 419(6910), pages 920-922, October.
    • Handle: RePEc:nat:nature:v:419:y:2002:i:6910:d:10.1038_nature01127
    DOI: 10.1038/nature01127
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    Cited by:

    1. Becher, M.A. & Grimm, V. & Knapp, J. & Horn, J. & Twiston-Davies, G. & Osborne, J.L., 2016. "BEESCOUT: A model of bee scouting behaviour and a software tool for characterizing nectar/pollen landscapes for BEEHAVE," Ecological Modelling, Elsevier, vol. 340(C), pages 126-133.
    2. Dussutour, Audrey & Nicolis, Stamatios C., 2013. "Flexibility in collective decision-making by ant colonies: Tracking food across space and time," Chaos, Solitons & Fractals, Elsevier, vol. 50(C), pages 32-38.
    3. Anna Dornhaus, 2011. "Finding optimal collective strategies using individual-based simulations: colony organization in social insects," Mathematical and Computer Modelling of Dynamical Systems, Taylor & Francis Journals, vol. 18(1), pages 25-37, May.
    4. Sun, Zhe & Wang, Ning & Bi, Yunrui & Srinivasan, Dipti, 2015. "Parameter identification of PEMFC model based on hybrid adaptive differential evolution algorithm," Energy, Elsevier, vol. 90(P2), pages 1334-1341.
    5. Istvan Karsai & Andrew Runciman, 2011. "The ‘common stomach’ as information source for the regulation of construction behaviour of the swarm," Mathematical and Computer Modelling of Dynamical Systems, Taylor & Francis Journals, vol. 18(1), pages 13-24, May.

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