Nest-site selection in honey bees: how well do swarms implement the "best-of-N" decision rule? View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2001-04

AUTHORS

Thomas D. Seeley, Susannah C. Buhrman

ABSTRACT

. This study views a honey bee swarm as a supraorganismal entity which has been shaped by natural selection to be skilled at choosing a future home site. Prior studies of this decision-making process indicate that swarms attempt to use the best-of-N decision rule: sample some number (N) of alternatives and then select the best one. We tested how well swarms implement this decision rule by presenting them with an array of five nest boxes, only one of which was a high-quality (desirable) nest site; the other four were medium-quality (acceptable) sites. We found that swarms are reasonably good at carrying out the best-of-N decision rule: in four out of five trials, swarms selected the best site. In addition, we gained insights into how a swarm implements this decision rule. We found that when a scout bee returns to the swarm cluster and advertises a potential nest site with a waggle dance, she tunes the strength of her dance in relation to the quality of her site: the better the site, the stronger the dance. A dancing bee tunes her dance strength by adjusting the number of waggle-runs/dance, and she adjusts the number of waggle-runs/dance by changing both the duration and the rate of her waggle-run production. Moreover, we found that a dancing bee changes the rate of her waggle-run production by changing the mean duration of the return-phase portion of her dance circuits. Differences in return-phase duration underlie the impression that dances differ in liveliness. Although a honey bee swarm has bounded rationality (e.g., it lacks complete knowledge of the possible nesting sites), through its capacity for parallel processing it can choose a nest site without greatly reducing either the breadth or depth of its consideration of the alternative sites. Such thoroughness of information gathering and processing no doubt helps a swarm implement the best-of-N decision rule. More... »

PAGES

416-427

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s002650000299

DOI

http://dx.doi.org/10.1007/s002650000299

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1040313737


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