4.5 Article

Evolution of self-organized division of labor in a response threshold model

期刊

BEHAVIORAL ECOLOGY AND SOCIOBIOLOGY
卷 66, 期 6, 页码 947-957

出版社

SPRINGER
DOI: 10.1007/s00265-012-1343-2

关键词

Response threshold model; Specialization; Emergent properties; Genetic task determination

资金

  1. Centre for Ecological and Evolutionary Studies, University of Groningen
  2. Swiss NSF
  3. ERC

向作者/读者索取更多资源

Division of labor in social insects is determinant to their ecological success. Recent models emphasize that division of labor is an emergent property of the interactions among nestmates obeying to simple behavioral rules. However, the role of evolution in shaping these rules has been largely neglected. Here, we investigate a model that integrates the perspectives of self-organization and evolution. Our point of departure is the response threshold model, where we allow thresholds to evolve. We ask whether the thresholds will evolve to a state where division of labor emerges in a form that fits the needs of the colony. We find that division of labor can indeed evolve through the evolutionary branching of thresholds, leading to workers that differ in their tendency to take on a given task. However, the conditions under which division of labor evolves depend on the strength of selection on the two fitness components considered: amount of work performed and on worker distribution over tasks. When selection is strongest on the amount of work performed, division of labor evolves if switching tasks is costly. When selection is strongest on worker distribution, division of labor is less likely to evolve. Furthermore, we show that a biased distribution (like 3:1) of workers over tasks is not easily achievable by a threshold mechanism, even under strong selection. Contrary to expectation, multiple matings of colony foundresses impede the evolution of specialization. Overall, our model sheds light on the importance of considering the interaction between specific mechanisms and ecological requirements to better understand the evolutionary scenarios that lead to division of labor in complex systems.

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