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Long-distance seasonal migration to the tropics promotes genetic diversity but not gene flow in boreal birds

Nature Ecology & Evolution volume 9, pages 957–969 (2025)Cite this article

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Abstract

Differences in life history can cause co-distributed species to evolve contrasting population genetic patterns, even as they occupy the same landscape. In high-latitude animals, evolutionary processes may be especially influenced by long-distance seasonal migration, a widespread adaptation to seasonality. Although migratory movements are intuitively linked to dispersal and therefore promotion of gene flow, their evolutionary genetic consequences remain poorly understood. Using ~1,700 genomes from 35 co-distributed boreal-breeding bird species that differ in non-breeding latitude and thus migration distance, we find that most long-distance migrants unexpectedly exhibit spatial genetic structure, despite their strong movement propensity. This result suggests evolutionary effects of philopatry—the tendency of many migrants to return to the same breeding site year after year, resulting in restricted dispersal. We further demonstrate that migration distance and genetic diversity are strongly positively correlated in our study species. This striking relationship suggests that the adaptive seasonal shifts in biogeography inherent to long-distance migration may enhance population stability, preserving genetic diversity in long-distance migrants relative to shorter-distance migrants that winter in harsher conditions at higher latitudes. Our results suggest that the major impact of long-distance seasonal migration on population genetic evolution occurs through promotion of demographic stability, rather than facilitation of dispersal.

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Fig. 1: Ecogeographic context of the study.
Fig. 2: Interspecific variation in spatial genetic patterns.
Fig. 3: βIBD and effects of species attributes on βIBD.
Fig. 4: θπ correlates with migration distance.

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Data availability

The sequence data generated during the study have been uploaded to the NCBI Sequence Read Archive under BioProjects PRJNA1043688 and PRJNA1130443. Individual accession numbers for each sample are provided in Supplementary Dataset 1. All other data are available within the manuscript, the repositories described in the Code availability statement and the Supplementary Information files. Source data are provided with this paper.

Code availability

Bioinformatic code used to process sequence data are available via figshare at https://doi.org/10.6084/m9.figshare.27284553 (ref. 119). Code used to conduct comparative analyses are available via a Code Ocean capsule at https://doi.org/10.24433/CO.5578409.v1 (ref. 120).

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Acknowledgements

For comments and advice, we thank G. Bradburd, R. Burner, K. Wacker, E. Gulson-Castillo, V. Gómez-Bahamón, J. Berv, Z. Hancock, M. Hack, A. Marshall, L. Knowles, D. Rabosky, M. Witynksi and A. Benavides. For providing samples, we thank the curators, collections staff and field collectors from the following institutions: American Museum of Natural History, Cleveland Museum of Natural History, Cornell University Museum of Vertebrates, New York State Museum, Royal Alberta Museum, Royal Ontario Museum, University of Alaska Museum of the North, University of Minnesota Museum of Natural History, University of California, Berkeley Museum of Vertebrate Zoology, University of Michigan Museum of Zoology and University of Washington Burke Museum. For additional samples, we thank J. Tremblay (Environment and Climate Change Canada). For field permits, we thank the United States Fish and Wildlife Service, the United States Forest Service, the Minnesota Department of Natural Resources, the Michigan Department of Natural Resources, the Canadian Wildlife Service of Environment and Climate Change Canada, Alberta Fish and Wildlife, and Manitoba Fish and Wildlife. Field sampling was approved by the University of Michigan Animal Care and Use Committee (no. PRO00010608). For assistance in the field, we thank C. Brennan, S. Campbell, S. DuBay, G. M. Erickson, M. M. Ferraro, A. FitzGerald, L. Gooch, E. Gulson-Castillo, J. Ralston, C. Scobie, H. Skeen, V. Ting, K. Wacker and members of the Burg lab. For assistance in the lab, we thank T. Schweizer, C. Rayne, R. Herman, J. Yan, C. Kaczmarek, M. Florkowski, M. Guza, C. Pajka, M. Hack and C. Jordan. Next-generation sequencing for this project was partially carried out in the Advanced Genomics Core at the University of Michigan. This research was also supported in part through computational resources and services provided by Advanced Research Computing (ARC), a division of Information and Technology Services (ITS) at the University of Michigan, Ann Arbor. Funding includes National Science Foundation grant DEB 2146950 (B.M.W.), National Science Foundation Graduate Research Fellowship DGE 1256260, Fellow ID 2018240490 (T.M.P.), Jean Wright Cohn Endowment Fund at the University of Michigan Museum of Zoology, Robert W. Storer Endowment Fund at the University of Michigan Museum of Zoology, Mary Rhoda Swales Museum of Zoology Research Fund at the University of Michigan Museum of Zoology, William G. Fargo Fund at the University of Michigan Museum of Zoology, William A. and Nancy R. Klamm Endowment funds at the Cleveland Museum of Natural History, University of Michigan Rackham Graduate Student Research Grant (T.M.P.), British Ornithologists Union Small Research Grant (T.M.P.), and American Museum of Natural History Chapman Research Grant (T.M.P.).

Author information

Author notes

  1. T. M. Pegan

    Present address: Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA

  2. A. A. Kimmitt

    Present address: Department of Biology, Hofstra University, Hempstead, NY, USA

  3. A. W. Jones

    Present address: Spring Island Trust, Okatie, SC, USA

Authors and Affiliations

  1. Museum of Zoology and Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, MI, USA

    T. M. Pegan, A. A. Kimmitt, B. W. Benz & B. M. Winger

  2. School for Environment and Sustainability, University of Michigan, Ann Arbor, MI, USA

    B. C. Weeks

  3. Environment and Climate Change Canada, Québec City, Québec, Canada

    Y. Aubry

  4. Department of Biological Sciences, University of Lethbridge, Lethbridge, Alberta, Canada

    T. M. Burg

  5. Royal Alberta Museum, Edmonton, Alberta, Canada

    J. Hudon

  6. Cleveland Museum of Natural History, Cleveland, OH, USA

    A. W. Jones

  7. New York State Museum, Albany, NY, USA

    J. J. Kirchman

  8. Department of Biology, Colorado State University, Fort Collins, CO, USA

    K. C. Ruegg

Authors
  1. T. M. Pegan
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Contributions

B.M.W. and T.M.P conceived the study. Genomic samples were contributed by all authors and were prepared for sequencing by T.M.P. and A.A.K. with methodological support from K.C.R. Data were analysed and visualized by T.M.P. and B.M.W. T.M.P. and B.M.W. wrote the paper with input and revisions from all authors. All authors approved the final version of the manuscript.

Corresponding author

Correspondence to B. M. Winger.

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Competing interests

The authors declare no competing interests.

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Peer review information

Nature Ecology & Evolution thanks Leilton Luna and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

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Extended data

Extended Data Fig. 1 The phylogenetic relationship among the species in the study and species attributes included in HMSC models.

The phylogenetic relationship is shown on the tree from birdtree.org used in our analyses. The tree is plotted alongside a heatmap representing interspecific variation in the four species attributes we investigated in HMSC models (migration distance, mass, association with early successional habitat, and genetic diversity). Genetic diversity estimates were calculated in this study (Supplementary Table 1) and values for the other three attributes come from published sources as described in the Methods.

Source data

Extended Data Fig. 2 Migration distance correlates with an estimate of heterozygosity from higher-coverage samples.

Each point represents one species (N = 27) and points are colored by migration distance, as in main text figures, where non-migrants are shown in gray. This plot shows heterozygosity estimated by ANGSD from reference-mapped genomes. The intercept and slope of the line were estimated with a phylogenetic generalized least squares (PGLS) model.

Extended Data Table 1 Species used in analyses
Full size table
Extended Data Table 2 Samples used to generate high-coverage genomes
Full size table
Extended Data Table 3 Comparison of strengths and caveats associated with each of four methods we used to estimate genetic diversity and heterozygosity
Full size table

Supplementary information

Supplementary Information

Legends for Supplementary Datasets 1–3, legends for Supplementary Figs. 1–35 and Supplementary Figs. 1–35.

Reporting Summary

Peer Review File

Supplementary Data 1

List of samples used and metadata for each sample.

Supplementary Data 2

Bioinformatic metadata for each species.

Supplementary Data 3

Information about chromosomes and large genomic regions excluded from analyses based on evidence for possible inversion polymorphism.

Supplementary Data 4

Statistical Source Data for Supplementary Figs. 1–35 in three tabs. The first tab includes data underlying PCA plots and admixture plots (A and B panels), as well as lat/long data shown in panel C. The second tab includes data underlying the scatterplots (D panels). The third tab contains the slope and intercept values plotted on each scatterplot (D panels). Data for all figures are provided together and can be separated using the ‘Species’ column.

Source data

Source Data Fig. 3

Statistical Source Data. Excel file includes HMSC output data for each panel. The Excel file contains 12 tabs, with 4 tabs per panel, reflecting the 4 model chains we ran and then plotted using mcmc_intervals in the R package bayesplot.

Source Data Extended Data Fig. 1

Source file provides the phylogenetic tree. All data plotted alongside the tree is given in Extended_Data_Table1.pdf.

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Pegan, T.M., Kimmitt, A.A., Benz, B.W. et al. Long-distance seasonal migration to the tropics promotes genetic diversity but not gene flow in boreal birds. Nat Ecol Evol 9, 957–969 (2025). https://doi.org/10.1038/s41559-025-02699-3

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