Lookup NU author(s): Dr Colin Tosh
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One theory to explain the high incidence of niche specialization in many animals is that it reduces attentional load during resource-seeking behaviour and thus leads to more accurate resource selection.A recent neural network model reﬁned the predictions of this theory, indicating that a cognitive advantagein specialists is likely to occur under realistic ecological conditions, namely when ‘mistakes’ (i.e. selectionof non-host resources) contribute moderately but positively to ﬁtness. Here, we present a formal empiricaltest of the predictions of this model. Using a human– computer interactive, we demonstrate that the central prediction of the model is supported: specialist humans are more accurate decision-makers thangeneralists when their mistakes are rewarded, but not when mistakes are punished. The idea thatincreased decision accuracy drives the evolution of niche width in animals has been supported inalmost all empirical systems in which it has been investigated. Theoretical work supports the idea, andnow the predictions of a key theoretical model have been demonstrated in a real biological informationprocessing system. Considering these interlocking pieces of evidence, we argue that specialization throughincreased decision accuracy may contribute signiﬁcantly, along with other mechanisms, to promote nichespecialization in animals.
Author(s): Tosh CR, Ruxton GD, Krause J, Franks DW
Publication type: Article
Publication status: Published
Journal: Proceedings of the Royal Society B: Biological Sciences
Print publication date: 13/04/2011
ISSN (print): 0962-8452
ISSN (electronic): 1471-2954
Publisher: The Royal Society Publishing
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