Understanding the constraints on sex ratio adaptation using artificial neural networks

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How perfect should behaviour be? There is little doubt that, given sufficient time, and genetic variation, natural selection can produce organisms displaying startlingly precise adaptations to their surroundings. At the same time, a variety of processes can constrain the ability of populations to reach adaptive peaks. Determining the relative importance of these processes is a major challenge still facing evolutionary biology. We will work on a model system that will allow us to say how obtaining and processing information can limit adaptation. We will work on parasitic wasps, which can choose the sex of their offspring by deciding whether or not to fertilize their eggs. The choice of offspring sex in this group has been the subject of much previous work, and the wasps generally show a good but imperfect fit to predicted behaviour. We will ask if we can better understand the behaviour shown in this group of organisms by incorporating the limitations of sensory and nervous systems into our predictions using a modeling approach known as artificial neural networks. The new predictions will then be tested against existing datasets and against new data, obtained by manipulating the information available to a parasitic wasp in the laboratory.