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Reduced foraging investment as an adaptation to patchy food sources: a phasic army ant simulation

View ORCID ProfileSerafino Teseo, View ORCID ProfileFrancesco Delloro
doi: https://doi.org/10.1101/101600
Serafino Teseo
1Independent scholar
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  • For correspondence: serafinoteseo@yahoo.it
Francesco Delloro
2Material Research Center (CNRS 7633), MINES ParisTech, Evry, France
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Abstract

Colonies of several ant species within the subfamily Dorylinae alternate stereotypical discrete phases of foraging and reproduction. Such phasic cycles are thought to be adaptive because they minimize the amount of foraging and the related costs, and at the same time enhance the colony-level ability to rely on patchily distributed food sources. In order to investigate these hypotheses, we use here a simple computational approach to study the population dynamics of two species of virtual ant colonies that differ quantitatively in their foraging investment. One species, which we refer to as “phasic”, forages only half of the time, mirroring the phasic activity of some army ants; the other “non-phasic” species forages instead all the time. We show that, when foraging costs are relatively high, populations of phasic colonies grow on average faster than non-phasic populations, outcompeting them in mixed populations. Interestingly, such tendency becomes more consistent as food becomes more difficult to find but locally abundant. According to our results, reducing the foraging investment, for example by adopting a phasic lifestyle, can result in a reproductive advantage, but only in specific conditions. We thus suggest phasic colony cycles to have emerged together with the doryline specialization in feeding on the brood of other eusocial insects, a resource that is hard to obtain but highly abundant if available.

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Posted January 20, 2017.
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Reduced foraging investment as an adaptation to patchy food sources: a phasic army ant simulation
Serafino Teseo, Francesco Delloro
bioRxiv 101600; doi: https://doi.org/10.1101/101600
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Reduced foraging investment as an adaptation to patchy food sources: a phasic army ant simulation
Serafino Teseo, Francesco Delloro
bioRxiv 101600; doi: https://doi.org/10.1101/101600

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