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Host-parasite coevolution in populations of constant and variable size

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Song,  Yixian
Department Evolutionary Theory, Max Planck Institute for Evolutionary Biology, Max Planck Society;

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Gokhale,  Chaitanya S.
Department Evolutionary Theory, Max Planck Institute for Evolutionary Biology, Max Planck Society;

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Traulsen,  Arne
Department Evolutionary Theory, Max Planck Institute for Evolutionary Biology, Max Planck Society;

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Citation

Song, Y., Gokhale, C. S., Papkou, A., Schulenburg, H., & Traulsen, A. (2015). Host-parasite coevolution in populations of constant and variable size. BMC Evolutionary Biology, 15(212): s12862-015-0462-6. doi:10.1186/s12862-015-0462-6.


Cite as: https://hdl.handle.net/11858/00-001M-0000-0027-F87F-9
Abstract
The matching-allele and gene-for-gene models are widely used in math- ematical approaches that study the dynamics of host-parasite interactions. Agrawal and Lively (Evolutionary Ecology Research 4:79-90, 2002) captured these two models in a single framework and numerically explored the associated time discrete dynamics of allele frequencies. Here, we present a detailed analytical investigation of this unifying framework in continuous time and provide a generalization. We extend the model to take into account changing population sizes, which result from the antagonistic nature of the interaction and follow the Lotka-Volterra equations. Under this extension, the population dynamics become most complex as the model moves away from pure matching-allele and becomes more gene-for-gene-like. While the population densities oscillate with a single oscillation frequency in the pure matching-allele model, a second oscillation frequency arises under gene-for-gene-like conditions. These observations hold for general interaction parameters and allow to infer generic patterns of the dynamics. Our results suggest that experimentally inferred dynamical patterns of host-parasite coevolution should typically be much more complex than the popular illustrations of Red Queen dynamics. A single parasite that infects more than one host can substantially alter the cyclic dynamics.