Susannah C. Buhrman’s research while affiliated with Cornell University and other places

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.

This study renews the analysis of honey bee swarms as decision-making units. We repeated Lindauer's observations of swarms choosing future home sites but used modern videorecording and bee-labelling techniques to produce a finer-grained description of the decision-making process than was possible 40 years ago. Our results both confirm Lindauer's findings and reveal several new features of the decision-making process. Viewing the process at the group level, we found: (1) the scout bees in a swarm find potential nest sites in all directions and at distances of up to several kilometers; (2) initially, the scouts advertise a dozen or more sites with their dances on the swarm, but eventually they advertise just one site; (3) within about an hour of the appearance of unanimity among the dancers, the swarm lifts off to fly to the chosen site; (4) there is a crescendo of dancing just before liftoff, and (5) the chosen site is not necessarily the one that is first advertised on the swarm. Viewing the process at the individual level, we found: (1) the dances of individual scout bees tend to taper off and eventually cease, so that many dancers drop out each day; (2) some scout bees switch their allegiance from one site to another, and (3) the principal means of consensus building among the dancing bees is for bees that dance initially for a non-chosen site to cease their dancing altogether, not to switch their dancing to the chosen site. We hypothesize that scout bees are programmed to gradually quit dancing and that this reduces the possibility of the decision-making process coming to a standstill with groups of unyielding dancers deadlocked over two or more sites. We point out that a swarm's overall strategy of decision making is a “weighted additive strategy.” This strategy is the most accurate but also the most demanding in terms of information processing, because it takes account of all of the information relevant to a decision problem. Despite being composed of small-brained bees, swarms are able to use the weighted additive strategy by distributing among many bees both the task of evaluating the alternative sites and the task of identifying the best of these sites.