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  Lotka–Volterra dynamics kills the Red Queen: population size fluctuations and associated stochasticity dramatically change host-parasite coevolution

Gokhale, C. S., Papkou, A., Traulsen, A., & Schulenburg, H. (2013). Lotka–Volterra dynamics kills the Red Queen: population size fluctuations and associated stochasticity dramatically change host-parasite coevolution. BMC Evolutionary Biology, 13(1): 254. doi:10.1186/1471-2148-13-254.

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Gokhale, Chaitanya S.1, Author           
Papkou, Andrei, Author
Traulsen, Arne1, Author           
Schulenburg, Hinrich, Author
Affiliations:
1Research Group Evolutionary Theory, Max Planck Institute for Evolutionary Biology, Max Planck Society, ou_1445641              

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Free keywords: host-parasite coevolution; Red Queen hypothesis; Lotka-Volterra dynamics; genetic drift; population bottleneck
 Abstract: Background: Host-parasite coevolution is generally believed to follow Red Queen dynamics consisting of ongoing oscillations in the frequencies of interacting host and parasite alleles. This belief is founded on previous theoretical work, which assumes infinite or constant population size. To what extent are such sustained oscillations realistic? Results: Here, we use a related mathematical modeling approach to demonstrate that ongoing Red Queen dynamics is unlikely. In fact, they collapse rapidly when two critical pieces of realism are acknowledged: (i) population size fluctuations, caused by the antagonism of the interaction in concordance with the Lotka-Volterra relationship; and (ii) stochasticity, acting in any finite population. Together, these two factors cause fast allele fixation. Fixation is not restricted to common alleles, as expected from drift, but also seen for originally rare alleles under a wide parameter space, potentially facilitating spread of novel variants. Conclusion: Our results call for a paradigm shift in our understanding of host-parasite coevolution, strongly suggesting that these are driven by recurrent selective sweeps rather than continuous allele oscillations.

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Language(s): eng - English
 Dates: 2013-08-082013-11-132013-11-19
 Publication Status: Published online
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 Rev. Type: -
 Identifiers: DOI: 10.1186/1471-2148-13-254
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Title: BMC Evolutionary Biology
Source Genre: Journal
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Publ. Info: BioMed Central
Pages: - Volume / Issue: 13 (1) Sequence Number: 254 Start / End Page: - Identifier: ISSN: 1471-2148
CoNE: https://pure.mpg.de/cone/journals/resource/111000136905006