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Multispecies migratory connectivity indicates hemispheric-scale risk to bird populations from global change

Nature Ecology & Evolution volume 9, pages 491–504 (2025)Cite this article

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Abstract

Global agreements to reduce the extinction risk of migratory species depend critically on intersecting migratory connectivity—the linking of individuals between regions in different seasons—and spatial patterns of environmental change. Here we integrate movement data from >329,000 migratory birds of 112 species to develop a parameter representing exposure to global change: multispecies migratory connectivity. We then combine exposure with projected climate and land-cover changes as a measure of hazard and species conservation assessment scores as a metric of vulnerability to estimate the relative risk of migratory bird population declines across the Western Hemisphere. Multispecies migratory connectivity (exposure) is the strongest driver of risk relative to hazard and vulnerability, indicating the importance of synthesizing connectivity across species to comprehensively assess risk. Connections between breeding regions in Canada and non-breeding regions in South America are at the greatest risk, which underscores the particular susceptibility of long-distance migrants. Over half (54%) of the connections categorized as very high risk include breeding regions in the eastern United States. This three-part framework serves as an ecological risk assessment designed specifically for migratory species, providing both decision support for global biodiversity conservation and opportunities for intergovernmental collaboration to sustain migratory bird populations year-round.

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Fig. 1: Three-component framework for quantifying and mapping risk of migratory bird population declines across the Western Hemisphere.
Fig. 2: Connections between Canada and South America are at the greatest risk and two breeding regions account for nearly half the very high risk connections.
Fig. 3: A large proportion of very high risk connections include breeding regions in the eastern United States and very high risk connections represent disproportionally more species.
Fig. 4: Very high risk connections are distributed across the hemisphere and include species from the some of the fastest-declining bird groups.
Fig. 5: The riskiest connections are due to high exposure and high vulnerability.
Fig. 6: Land-cover change is the primary driver of hazard and exposure is the strongest driver of migratory bird risk.

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Data availability

The tracking data shared with MBI are proprietary and were contributed through data sharing agreements that limit the ability to reshare. Requests for data should be directed to the contributing data provider or organization, according to the data owner’s terms set on Movebank; a list of participating data providers is available at https://movebank.org/cms/movebank-content/audubon-mbi-collection. Band re-encounter data are available through the USGS BBL at https://usgs.gov/labs/bird-banding-laboratory/data. Land-cover vulnerability to change by 2050 spatial data are available on the ArcGIS Living Atlas (https://livingatlas.arcgis.com/landcover-2050) and the temperature change by mid-century spatial data are available from the IPCC WGI Interactive Atlas (https://interactive-atlas.ipcc.ch). Conservation assessment scores are available through the PIF ACAD at https://pif.birdconservancy.org/avian-conservation-assessment-database.

Code availability

Code and example data to run analyses and download capabilities of data products from the full analysis, including multispecies connectivity (exposure) and uncertainty estimates, study species and estimates of risk and its other components (vulnerability, hazard and its components) for each of the 921 hemispheric connections are provided in Audubon’s GitHub repository (https://github.com/audubongit/multispecies_connectivity_risk) and permanently archived on Zenodo (https://zenodo.org/doi/10.5281/zenodo.13361404) (ref. 75).

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Acknowledgements

This analysis was made possible by the researchers who kindly shared migratory bird tracking data with the Audubon Migratory Bird Initiative (MBI; see Supplementary Table 6 for a list of data providers and attributions), and by the researchers and members of the public who have banded birds and reported re-encounters of banded birds to the USGS Bird Banding Lab. We are thankful to MBI’s partners who contributed to data acquisition efforts. We appreciate the support of the following organizations and individuals who helped archive, curate and make bird tracking and banding data accessible for this work: Movebank (S. Davidson), Birds Canada and the Motus Wildlife Tracking System (S. Mackenzie), the USGS Bird Banding Lab (A. Celis-Murillo) and the USGS Alaska Science Center (L. Tibbitts and D. Douglas). This study uses data from the eBird Status and Trends Project at the Cornell Lab of Ornithology, eBird.org. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the Cornell Lab of Ornithology. This work was funded by generous gifts to MBI from J. Ellis, E. L. and B. Doolin, and Knobloch Family Foundation. This research was conducted while S.P.S. was supported by the National Science Foundation (DEB- 2213566), which provided funding for overall research activities related to global change impacts on birds. We are grateful to J. Fuller for providing bird illustrations. Thank you to E. Zipkin and E. Schneider for their insights on an earlier version of the manuscript.

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Authors and Affiliations

  1. National Audubon Society, Science Division, New York, NY, USA

    Sarah P. Saunders, William V. DeLuca, Brooke L. Bateman, Jill L. Deppe, Joanna Grand, Erika J. Knight, Timothy D. Meehan, Nicole L. Michel, Nathaniel E. Seavy, Melanie A. Smith, Lotem Taylor, Chad J. Witko & Chad B. Wilsey

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  1. Sarah P. Saunders
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Contributions

S.P.S. and W.V.D. led conceptualization, formal analysis and writing of the original draft, with methodological, investigative and data curation support from B.L.B., J.L.D., J.G., E.J.K., T.D.M., N.L.M., N.E.S., M.A.S., L.T. and C.J.W. The research project and supportive funding were administered by J.L.D., N.E.S. and C.B.W. All authors contributed to review and editing of drafts.

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Correspondence to Sarah P. Saunders.

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Extended data

Extended Data Fig. 1 Migratory connectivity regions (MCRs) used to map migratory bird risk.

Map of migratory connectivity regions (MCRs) and their associated numeric codes. MCR codes match those used to produce connectivity results between breeding and non-breeding MCRs for each study species (n = 112), which were then used to quantify multispecies migratory connectivity. MCR codes were also used to stratify hazard and vulnerability for calculating risk to migratory birds (see Methods for more details).

Extended Data Fig. 2 Multispecies migratory connectivity (exposure) and uncertainty estimates.

Caterpillar plot of all multispecies migratory connectivity estimates (weighted means and non-weighted means for those connections with just single species) and associated credible intervals (CI) for each of the 20 breeding migratory connectivity regions (MCRs; shown as facets) with each nonbreeding MCR (indicated on y-axes). For weighted means, two CIs are shown (80% and 95% CI as thicker and thinner lines, respectively) to differentiate from non-weighted means for single species (only 95% CI shown). Dark blue indicates those means that are significantly above the average connectivity proportion (that is, 95% CI does not overlap 0.071 indicated by dashed black vertical line) across all MCR pairs (n = 921 MCR pairs).

Extended Data Fig. 3 Components of hazard: land-cover change and temperature change by mid-century.

a, Projected mean land-cover vulnerability to modification by humans by 2050 per migratory connectivity region (MCR), relative to 2010–2018 baseline. Data were obtained from ESRI/Clark Labs and summarized by MCR by averaging across 300 m grid cells (native resolution of dataset). Two values were then averaged for every MCR pair (n = 921) to yield an average measure of land-cover change for all connections. b, Projected mean annual temperature change (°C) by mid-century per MCR relative to an historic baseline of 1995–2014 under SSP5-8.5. Data were obtained from the Intergovernmental Panel on Climate Change (IPCC) Working Group 1 (WG1) Interactive Atlas and summarized per MCR by averaging across 1° grid cells (native resolution of dataset). Two values were then averaged for every MCR pair to yield an average measure of climate change for all connections.

Extended Data Fig. 4 Multispecies connectivity estimates (exposure) for four representative connections.

Variation in exposure (scaled to sum to one in each panel) for all nonbreeding migratory connectivity regions (MCRs) connected to each of four breeding MCRs (yellow outlines): (top left) the Arctic Plains/Mountains; (top right) New England/Mid-Atlantic Coast; (bottom left) Northern Rocky Mountains; and (bottom right) Prairie Potholes. Gray represents nonbreeding MCRs that do not connect to the given breeding MCR. White MCRs are breeding-only. Black outlines denote nonbreeding MCRs with statistically significant multispecies connectivity (Extended Data Fig. 2). Purple circles show the number of study species (n = 112) contributing to the multispecies connectivity estimate for the given significant connection. These four breeding MCRs have the most statistically significant connections.

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Saunders, S.P., DeLuca, W.V., Bateman, B.L. et al. Multispecies migratory connectivity indicates hemispheric-scale risk to bird populations from global change. Nat Ecol Evol 9, 491–504 (2025). https://doi.org/10.1038/s41559-024-02575-6

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