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Host-parasite coevolution in populations of constant and variable size

Overview of attention for article published in BMC Evolutionary Biology, September 2015
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (84th percentile)
  • Good Attention Score compared to outputs of the same age and source (74th percentile)

Mentioned by

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15 tweeters
reddit
1 Redditor

Citations

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30 Dimensions

Readers on

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54 Mendeley
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Title
Host-parasite coevolution in populations of constant and variable size
Published in
BMC Evolutionary Biology, September 2015
DOI 10.1186/s12862-015-0462-6
Pubmed ID
Authors

Yixian Song, Chaitanya S Gokhale, Andrei Papkou, Hinrich Schulenburg, Arne Traulsen

Abstract

The matching-allele and gene-for-gene models are widely used in mathematical 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.

Twitter Demographics

The data shown below were collected from the profiles of 15 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 54 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 2%
Denmark 1 2%
France 1 2%
Unknown 51 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 13 24%
Researcher 10 19%
Student > Master 9 17%
Professor 5 9%
Student > Bachelor 4 7%
Other 6 11%
Unknown 7 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 28 52%
Biochemistry, Genetics and Molecular Biology 7 13%
Mathematics 4 7%
Environmental Science 1 2%
Computer Science 1 2%
Other 2 4%
Unknown 11 20%

Attention Score in Context

This research output has an Altmetric Attention Score of 10. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 07 October 2015.
All research outputs
#1,206,816
of 11,126,160 outputs
Outputs from BMC Evolutionary Biology
#489
of 2,187 outputs
Outputs of similar age
#38,574
of 243,786 outputs
Outputs of similar age from BMC Evolutionary Biology
#20
of 79 outputs
Altmetric has tracked 11,126,160 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,187 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.9. This one has done well, scoring higher than 77% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 243,786 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 84% of its contemporaries.
We're also able to compare this research output to 79 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 74% of its contemporaries.