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Spatially structured eco-evolutionary dynamics in a host-pathogen interaction render isolated populations vulnerable to disease

Author

Listed:
  • Layla Höckerstedt

    (00014 University of Helsinki
    Finnish Meteorological Institute)

  • Elina Numminen

    (00014 University of Helsinki)

  • Ben Ashby

    (University of California
    Simon Fraser University)

  • Mike Boots

    (University of California
    University of Exeter)

  • Anna Norberg

    (University of Zürich)

  • Anna-Liisa Laine

    (00014 University of Helsinki
    University of Zürich)

Abstract

While the negative effects that pathogens have on their hosts are well-documented in humans and agricultural systems, direct evidence of pathogen-driven impacts in wild host populations is scarce and mixed. Here, to determine how the strength of pathogen-imposed selection depends on spatial structure, we analyze growth rates across approximately 4000 host populations of a perennial plant through time coupled with data on pathogen presence-absence. We find that infection decreases growth more in the isolated than well-connected host populations. Our inoculation study reveals isolated populations to be highly susceptible to disease while connected host populations support the highest levels of resistance diversity, regardless of their disease history. A spatial eco-evolutionary model predicts that non-linearity in the costs to resistance may be critical in determining this pattern. Overall, evolutionary feedbacks define the ecological impacts of disease in spatially structured systems with host gene flow being more important than disease history in determining the outcome.

Suggested Citation

  • Layla Höckerstedt & Elina Numminen & Ben Ashby & Mike Boots & Anna Norberg & Anna-Liisa Laine, 2022. "Spatially structured eco-evolutionary dynamics in a host-pathogen interaction render isolated populations vulnerable to disease," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-33665-3
    DOI: 10.1038/s41467-022-33665-3
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    References listed on IDEAS

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    1. Youyong Zhu & Hairu Chen & Jinghua Fan & Yunyue Wang & Yan Li & Jianbing Chen & JinXiang Fan & Shisheng Yang & Lingping Hu & Hei Leung & Tom W. Mew & Paul S. Teng & Zonghua Wang & Christopher C. Mundt, 2000. "Genetic diversity and disease control in rice," Nature, Nature, vol. 406(6797), pages 718-722, August.
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    3. Bates, Douglas & Mächler, Martin & Bolker, Ben & Walker, Steve, 2015. "Fitting Linear Mixed-Effects Models Using lme4," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 67(i01).
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