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. 2010 Nov;23(6):459-471.
doi: 10.1007/s10905-010-9229-5. Epub 2010 Sep 14.

Modeling the Adaptive Role of Negative Signaling in Honey Bee Intraspecific Competition

Brian R Johnson, James C Nieh

Modeling the Adaptive Role of Negative Signaling in Honey Bee Intraspecific Competition

Brian R Johnson et al. J Insect Behav. 2010 Nov.

Abstract

Collective decision making in the social insects often proceeds via feedback cycles based on positive signaling. Negative signals have, however, been found in a few contexts in which costs exist for paying attention to no longer useful information. Here we incorporate new research on the specificity and context of the negative stop signal into an agent based model of honey bee foraging to explore the adaptive basis of negative signaling in the dance language. Our work suggests that the stop signal, by acting as a counterbalance to the waggle dance, allows colonies to rapidly shut down attacks on other colonies. This could be a key adaptation, as the costs of attacking a colony strong enough to defend itself are significant. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s10905-010-9229-5) contains supplementary material, which is available to authorized users.

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Figures

Fig. 1
Fig. 1
Flow diagram of the behavioral control structure for foraging honey bees. Grey shading indicates behavioral states, while white shading indicates a decision making procedure. Black bubbles represent, yes, while white bubbles, represent, no. The structure is a simplification of that of de Vries and Biesmeijer (1998). To improve readability some connections are replaced with a color coding pattern to indicate the next transition. After Delay-2, for example, the bee transitions to scouting, which then results in leaving the nest and either finding a site or not. The other two examples of transitioning to scouting are shaded the same color to indicate that their following acts are identical. This choice was made because including lines to the next state in these cases would decrease the readability of the figure. Return to nectar source is treated in the same manner. Find r find receiver
Fig. 2
Fig. 2
Comparison of the model’s output (means of 50 simulations) with the day 1 empirical results of Seeley et al. (1991). The model is able to replicate both the build-up of foragers at the first site and switching to the second. The parameter settings that lead to this result are shown in the text
Fig. 3
Fig. 3
Effect of the stop signal on the number of foragers attacking another colony with varying rates of guard recruitment in the attacked colony. Results are the means of 50 simulations. All attacked colonies eventually post sufficient guards to defend themselves. At high rates of recruitment, the stop signal has little effect, because most attackers are repelled by guards and do not recruit. As the guard recruitment rates decreases, the effect of the stop signal is more pronounced. As real colonies are slow to recruit guards, the middle and bottom panels are likely to be most relevant for honey bee intraspecific competition
Fig. 4
Fig. 4
Effect of the stop signal on the number of foragers attacking another colony with variation in the total number of guards they are able to post. Results are the means of 50 simulations. The percentage of foragers the attacked colony is maximally able to repel (% rejection) is shown on each panel. At low rates of rejection, the attacking colony recruits heavily and fully attacks. At intermediate rates of rejection, the number of attacking foragers either builds slowly or levels off, while at high rates of rejection at the foreign colony the attack is called off. In each case, the stop signal decreases the probability required to cause each outcome. The stop signal thus ensures that colonies only fully attack weak neighbors
See this image and copyright information in PMC

References

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