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  • 1
    Publication Date: 2015-06-27
    Description: Collective decision-making is a characteristic of societies ranging from ants to humans. The ant Temnothorax albipennis is known to use quorum sensing to collectively decide on a new home; emigration to a new nest site occurs when the number of ants favouring the new site becomes quorate. There are several possible mechanisms by which ant colonies can select the best nest site among alternatives based on a quorum mechanism. In this study, we use computational models to examine the implications of heterogeneous acceptance thresholds across individual ants in collective nest choice behaviour. We take a minimalist approach to develop a differential equation model and a corresponding non-spatial agent-based model. We show, consistent with existing empirical evidence, that heterogeneity in acceptance thresholds is a viable mechanism for efficient nest choice behaviour. In particular, we show that the proposed models show speed–accuracy trade-offs and speed–cohesion trade-offs when we vary the number of scouts or the quorum threshold.
    Keywords: behaviour, ecology, computational biology
    Electronic ISSN: 2054-5703
    Topics: Natural Sciences in General
    Published by Royal Society
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  • 2
    Publication Date: 2015-10-01
    Description: Even though grouping behaviour has been actively studied for over a century, the relative importance of the numerous proposed fitness benefits of grouping remain unclear. We use a digital model of evolving prey under simulated predation to directly explore the evolution of gregarious foraging behaviour according to one such benefit, the ‘many eyes’ hypothesis. According to this hypothesis, collective vigilance allows prey in large groups to detect predators more efficiently by making alarm signals or behavioural cues to each other, thereby allowing individuals within the group to spend more time foraging. Here, we find that collective vigilance is sufficient to select for gregarious foraging behaviour as long there is not a direct cost for grouping (e.g. competition for limited food resources), even when controlling for confounding factors such as the dilution effect. Furthermore, we explore the role of the genetic relatedness and reproductive strategy of the prey and find that highly related groups of prey with a semelparous reproductive strategy are the most likely to evolve gregarious foraging behaviour mediated by the benefit of vigilance. These findings, combined with earlier studies with evolving digital organisms, further sharpen our understanding of the factors favouring grouping behaviour.
    Keywords: behaviour, ecology, computational biology
    Electronic ISSN: 2054-5703
    Topics: Natural Sciences in General
    Published by Royal Society
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  • 3
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    Royal Society
    Publication Date: 2015-10-01
    Keywords: evolution
    Electronic ISSN: 2054-5703
    Topics: Natural Sciences in General
    Published by Royal Society
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  • 4
    Publication Date: 2015-10-31
    Description: Social insects such as ants have evolved collective rather than individual immune defence strategies against diseases and parasites at the level of their societies (colonies), known as social immunity. Ants frequently host other arthropods, so-called myrmecophiles, in their nests. Here, we tested the hypothesis that myrmecophily may partly arise from selection for exploiting the ants’ social immunity. We used larvae of the wax moth Galleria mellonella as ‘model myrmecophiles’ (baits) to test this hypothesis. We found significantly reduced abundance of entomopathogens in ant nests compared with the surrounding environment. Specific entomopathogen groups ( Isaria fumosorosea and nematodes) were also found to be significantly less abundant inside than outside ant nests, whereas one entomopathogen ( Beauveria brongniartii ) was significantly more abundant inside nests. We therefore hypothesize that immunological benefits of entering ant nests may provide us a new explanation of why natural selection acts in favour of such a life-history strategy.
    Keywords: evolution
    Electronic ISSN: 2054-5703
    Topics: Natural Sciences in General
    Published by Royal Society
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