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Synthesizing selection mosaic theory and host-pathogen theory to explain large-scale pathogen coexistence

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Abstract

Selection mosaic theory explains observations of polymorphism in host-pathogen interactions in terms of spatially variable natural selection but does not account for population dynamics. In contrast, classical host-pathogen theory easily explains observations of population cycles, but does not explain the persistence of pathogen polymorphism. Here, we synthesize these two frameworks to understand the effects of population cycles on pathogen polymorphism. We show that geographic variation in the frequency of two morphotypes of a baculovirus that infects the Douglas-fir tussock moth (Orgyia pseudotsugata) depends on the frequency of Douglas-fir (Pseudotsuga menziesii), an important tussock moth host tree. The morphotype frequency data are best explained by host-pathogen models that combine a selection mosaic with population cycles. In our model, population cycles intensify pathogen competition across a selection mosaic, leading to a strong effect of Douglas-fir frequency on morphotype frequency that matches the data. Models without host-pathogen cycles or a selection mosaic project only weak effects of varying Douglas-fir frequency. Our model further projects that a biopesticide made up of both viral morphotypes would be more effective than the current single-morphotype biopesticide, demonstrating that our synthesis of selection mosaic theory and host-pathogen theory provides useful insights into pest management.

Data availability

The raw data for the morphotype frequency dataset, field experiments, and line search results supporting the findings of this study are openly available in the GitHub repository at https://github.com/kpd19/Two_Pathogen_Evolution/, with a persistent identifier assigned to version 1.0.0 via Zenodo: https://doi.org/10.5281/zenodo.17574036. The Bayesian model outputs from Stan are very large and are available from the first author upon request. The data from the increased realizations from the line search results are also very large and are available from the first author upon request. The previously published data included as part of our morphotype frequency dataset can be found in Fig. 1 from Hughes37, Table 1 from Williams and Otvos65, and Table 1 from Williams et al.40. The National Forest Type Dataset for the continental United States was previously publicly available from the USDA Forest Service. The dataset is no longer hosted by the USDA and is available from the first author upon request. State and Province administrative boundaries for the United States and Canada used in the maps for this paper are publicly available for download from GADM v4.1 via https://geodata.ucdavis.edu/gadm/gadm4.1/shp/. Source data are provided with this paper.

Code availability

All code to perform the simulations and statistical analysis, as well as for plotting Figs. 1–6 and the supplementary data figures, is openly available in the GitHub repository at https://github.com/kpd19/Two_Pathogen_Evolution/, with a persistent identifier assigned to version 1.0.0 via Zenodo: https://doi.org/10.5281/zenodo.17574036.

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Acknowledgements

We are extremely grateful for the support of many dedicated and talented field technicians: Rhiannon Archerelle, Ari Freedman, Amy Gannon, Laurel Haavik, Sophia Horigan, Amy Huang, Alison Hunter, Jessica Johnson, August Kramer, Allie Kreitman, Kate-Lynne Logan, and Chelsea Miller. Special thanks to the field technicians who made the work possible in the Summer of 2020, as well as Mary Johnson and Luis Marmolejo, who managed shipping. We thank Roy Magelssen and Connie Mehmel at the Forestry Sciences Laboratory in Wenatchee, Washington, for providing important institutional and biological knowledge of the system, and Joe Mihaljevic for important guidance in doing transmission experiments. We would like to thank Cara Brook, Sarah Cobey, and Tim Wootton for providing important feedback on earlier drafts of this work. Computational Resources were provided by the Research Computing Center at the University of Chicago. Help in morphotyping isolates was provided by the Electron Microscopy Center at the University of Chicago. Our work was supported by EEID NSF grant DEB-2109774 to G.D. and V.D. K.P.D. was supported by the University of Chicago Data Science for Energy and Environmental Research (DSEER) training grant as part of an NSF Research Traineeship program (1735359) and the U.S. Department of Education Quantitative Ecology GAANN training grant (P200A150101). W.T.K. and K.P.D. received separate awards from the University of Chicago Hinds Fund for Student Research. Our work was further supported by a grant from the Western Wildlands Environmental Threat Assessment Center to C.M.P., by NIFA Biological Sciences grant 2019-67014-29919 to V.D., by an ARCS Foundation Fellowship to W.T.K., and by a Theodore Roosevelt Memorial Grant through the American Museum of Natural History to W.T.K.

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Authors and Affiliations

  1. Department of Ecology and Evolution, University of Chicago, Chicago, IL, USA

    Katherine P. Dixon, William T. Koval & Greg Dwyer

  2. Pacific Northwest Research Station, USDA Forest Service, Wenatchee, WA, USA

    Carlos M. Polivka

  3. Department of Biology, Lewis & Clark College, Portland, OR, USA

    Grace Bird

  4. Department of Applied Mathematics, University of Colorado, Boulder, CO, USA

    Vanja Dukic

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  1. Katherine P. Dixon
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  2. William T. Koval
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  3. Carlos M. Polivka
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  4. Grace Bird
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  6. Greg Dwyer
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Contributions

G.D. and K.P.D. planned and designed the research. W.T.K., C.M.P., G.B., G.D., and K.P.D. collected the data. K.P.D. analyzed the data. K.P.D., G.D., V.D., and C.M.P. contributed substantially to the discussion of the results and the writing of the manuscript.

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Greg Dwyer.

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Dixon, K.P., Koval, W.T., Polivka, C.M. et al. Synthesizing selection mosaic theory and host-pathogen theory to explain large-scale pathogen coexistence.
Nat Commun (2025). https://doi.org/10.1038/s41467-025-67952-6

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