Honeybees are able to share the workload dynamically among the colony members. This division of labor is flexible and robust and is not controlled by a central unit. Thus, it is a 'swarm intelligent' feature. Several models of proximate mechanisms have been proposed which aim to explain how single workers decide on which task they work. We elaborated on an existing model of a honeybee colony which predicts the flow of workforce, information, and nutrients. We tested several models of proximate mechanisms and predicted colony-level fitness parameters: brood survival and net nectar gain. We found significant differences in the impact of specific proximate models on ultimate observables which describe colony fitness. Thus, our model could serve as a tool to predict benefits and costs of these mechanisms in honeybees. It contributes to the discussion of their potential evolutionary background.
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