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Constraints on adaptation: explaining deviation from optimal sex ratio using artificial neural networks

Lookup NU author(s): Dr Colin Tosh


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Determining processes constraining adaptation is a major challenge facing evolutionary biology, and sex allocation has proved a useful model system for exploring different constraints. We investigate the evolution of suboptimal sex allocation in a solitary parasitoid wasp system by modelling information acquisition and processing using artificial neural networks (ANNs) evolving according to a genetic algorithm. Theory predicts an instantaneous switch from the production of male to female offspring with increasing host size, whereas data show gradual changes. We found that simple ANNs evolved towards producing sharp switches in sex ratio, but additional biologically reasonable assumptions of costs of synapse maintenance, and simplification of the ANNs, led to more gradual adjustment. Switch sharpness was robust to uncertainty in fitness consequences of host size, challenging interpretations of previous empirical findings. Our results also question some intuitive hypotheses concerning the evolution of threshold traits and confirm how neural processing may constrain adaptive behaviour.

Publication metadata

Author(s): Lewis HM, Tosh CR, O'Keefe S, Shuker DM, West SA, Mayhew PJ

Publication type: Article

Publication status: Published

Journal: Journal of Evolutionary Biology

Year: 2010

Volume: 23

Issue: 8

Pages: 1708-1719

Print publication date: 17/06/2010

ISSN (print): 1010-061X

ISSN (electronic): 1420-9101

Publisher: Wiley-Blackwell Publishing


DOI: 10.1111/j.1420-9101.2010.02038.x


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