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Scope for waterfowl to speed up migration to a warming Arctic

Nature Climate Change volume 15, pages 1107–1114 (2025)Cite this article

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Abstract

Climate change is causing an earlier onset of spring, requiring migratory birds to accelerate their spring migration to avoid arriving late at the breeding grounds. This acceleration hinges on the capacity to shorten the time spent building energy reserves (fuelling) for migratory flight, which is currently thought to be very limited. Combining multiyear global-positioning-system tracking and body mass data from five large-bodied Arctic-breeding waterfowl species, we demonstrate that there is considerable scope for the studied species to migrate faster by shortening the fuelling time, either before departure or at stopovers. With the exception of one species (brent goose), populations were able to largely or fully offset their spring departure date with subsequent fuelling time en route. Still, under the current rates of Arctic warming, this may allow them to mediate only a few more decades of spring advance by migrating faster.

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Fig. 1: Spring migrations and tracking data of five Arctic-breeding waterfowl species.
Fig. 2: Onset of fuelling, migration budgets and migration speed for five Arctic-breeding waterfowl species, in order of increasing body mass.
Fig. 3: Required and observed variability in fuelling time for five Arctic-breeding waterfowl species.
Fig. 4: Relationships of arrival date and en route fuelling time with spring departure and date of snowmelt, for five Arctic-breeding waterfowl species.

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Data availability

The snowmelt data are available via figshare at https://doi.org/10.21942/uva.28597007 (ref. 89). The GPS tracking and body mass data used in the analysis are not openly available, but extracted from www.movebank.org and www.geese.org with permission from the concerned data owners (Supplementary Table 4). The available code includes downloading the data from Movebank for all tracking studies, given that collaborator rights to the studies are acquired. Source data are available with this paper.

Code availability

Code used to perform the analysis, including downloading the data from Movebank for all tracking studies given that collaborator rights to the studies are acquired, is available via figshare at https://doi.org/10.21942/uva.28597007 (ref. 89).

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Acknowledgements

We thank everyone who was involved in catching and tagging birds throughout the years, notably the Dutch Society of Goose Catchers, F. Cottaar, A. Degen, W. Fokkema, P. Glazov, Y. van der Horst, B. Hoye, H. van der Jeugd, F. Jochems, A. Lemazina, J. Ludwig, K. Oosterbeek, J. Pessa, K. Polderdijk, S. Sand, C. Sonne, W. Tijsen, J. Vegelin, P. de Vries, B. Voslamber and M. Wikelski. We are very grateful to the tag suppliers for logistic and technical support, especially T. Gerrits (deceased) and W. Bouten. We thank www.geese.org, Y. van Randen and V. Claassen for curating and providing the body mass data used in the analysis and the Wildfowl & Wetlands Trust (WWT) for providing additional pink-footed goose measurements. We are very grateful to K. K. Clausen for analysing the trend in body condition of pink-footed geese. Lastly, the study greatly benefited from fruitful discussions with people from the Foraging and Movement Ecology group at NIOO-KNAW, the Animal Movement Ecology group at UvA-IBED and the NWO-NPP Arctic Migrants consortium, notably B. Kranstauber, E. Rakhimberdiev, N. Skyllas, E. Gobbens and L. de Vries. The study and the data collection were funded by many different sources; they are listed in Supplementary Table 4.

Author information

Authors and Affiliations

  1. Department of Theoretical and Computational Ecology, Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, Amsterdam, the Netherlands

    Hans Linssen, Michiel P. Boom, Nelleke H. Buitendijk, Jan Geisler, Kees H. T. Schreven, Judy Z. Shamoun-Baranes, E. Emiel van Loon & Bart A. Nolet

  2. Department of Animal Ecology, Netherlands Institute of Ecology, Wageningen, the Netherlands

    Hans Linssen, Michiel P. Boom, Nelleke H. Buitendijk, Jan Geisler, Kees H. T. Schreven & Bart A. Nolet

  3. Groningen Institute for Evolutionary Life Sciences, University of Groningen, Groningen, the Netherlands

    Thomas K. Lameris & Tom S. L. Versluijs

  4. Sovon Dutch Centre for Field Ornithology, Nijmegen, the Netherlands

    Michiel P. Boom

  5. Future for Nature Foundation, Arnhem, the Netherlands

    Rascha J. M. Nuijten

  6. Wildlife Ecology and Conservation Group, Wageningen University and Research, Wageningen, the Netherlands

    Rascha J. M. Nuijten

  7. Faunabeheereenheid Noord-Holland, Haarlem, the Netherlands

    Nelleke H. Buitendijk

  8. Cornell Lab of Ornithology, Cornell University, Ithaca, NY, USA

    Adriaan M. Dokter

  9. Team Animal Ecology, Wageningen Environmental Research, Wageningen University & Research, Wageningen, the Netherlands

    Barwolt S. Ebbinge, Sander Moonen & Gerhard J. D. M. Müskens

  10. Michael-Otto-Institut im NABU, Bergenhusen, Germany

    Götz Eichhorn, Jutta Leyrer & Lisa Vergin

  11. Independent Researcher, Haeska, Estonia

    Trinus Haitjema

  12. Department of Ecology, Radboud Institute for Biological and Environmental Sciences (RIBES), Radboud University, Nijmegen, the Netherlands

    Andrea Kölzsch

  13. Department of Migration, Max Planck Institute of Animal Behavior, Radolfzell, Germany

    Andrea Kölzsch

  14. Institute for Wetlands and Waterbird Research e.V., Aller, Germany

    Andrea Kölzsch & Helmut Kruckenberg

  15. Department of Ecoscience, Aarhus University, Aarhus, Denmark

    Jesper Madsen & Lisa Vergin

  16. Wildfowl & Wetlands Trust, Slimbridge, UK

    Carl Mitchell

  17. Institute of Avian Research, Wilhelmshaven, Germany

    Sander Moonen

  18. Department of Coastal Systems, NIOZ Royal Netherlands Institute for Sea Research, Den Burg, the Netherlands

    Tom S. L. Versluijs

Authors
  1. Hans Linssen
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  2. Thomas K. Lameris
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  3. Michiel P. Boom
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  4. Rascha J. M. Nuijten
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  5. Nelleke H. Buitendijk
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  6. Adriaan M. Dokter
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  7. Barwolt S. Ebbinge
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  8. Götz Eichhorn
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  9. Jan Geisler
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  10. Trinus Haitjema
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  11. Andrea Kölzsch
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  12. Helmut Kruckenberg
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  13. Jutta Leyrer
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  14. Jesper Madsen
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  15. Carl Mitchell
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  16. Sander Moonen
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  17. Gerhard J. D. M. Müskens
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  18. Kees H. T. Schreven
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  19. Lisa Vergin
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  20. Tom S. L. Versluijs
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  21. Judy Z. Shamoun-Baranes
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  22. E. Emiel van Loon
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  23. Bart A. Nolet
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H.L., B.A.N., T.K.L., M.P.B., R.J.M.N., E.E.v.L. and J.Z.S.-B. conceptualized the study. All authors, except T.S.L.V., J.Z.S.-B. and E.E.v.L., collected tracking and/or body mass data for the analysis and T.S.L.V. processed and prepared the snowmelt data for the onset of spring. H.L. prepared the tracking data and performed the analyses, with B.A.N., T.K.L., M.P.B., E.E.v.L., R.J.M.N. and J.Z.S.-B. giving crucial input. H.L. led the writing and T.K.L., M.P.B., R.J.M.N., N.H.B., A.M.D., B.S.E., G.E., J.G., T.H., A.K., H.K., J.L., J.M., C.M., S.M., G.J.D.M.M., K.H.T.S., L.V., T.S.L.V., J.Z.S.-B., E.E.v.L. and B.A.N. provided critical feedback on the paper. All authors approved the final paper. H.L. is the corresponding author.

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Correspondence to Hans Linssen.

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Extended data

Extended Data Table 1 Overview of study species and properties of the body mass data and spring migration tracks
Full size table
Extended Data Table 2 Linear mixed models of en route fuelling time and arrival date at the breeding grounds
Full size table

Extended Data Fig. 1 Relationships between a hypothetical decrease in migration duration (days) and the required hypothetical decrease in total fuelling time (%).

a, ignoring pre-departure fuelling; b, including pre-departure fuelling. Panel b is identical to Fig. 3a. Each thin line represents one tracked spring migration and its slope is derived from that spring migration and indicates how much that migration would have been shortened (in days) by a certain percentage decrease in fuelling time. Thick dashed lines indicate the median slope per population. When pre-departure fuelling was ignored, birds appear more limited in their scope to speed up spring migration, particularly barnacle and brent geese.

Source data

Extended Data Fig. 2 Schematic overview of migrated distance (solid lines) and stored energy (dotted lines) over time in spring, according to two alternative (extreme) hypotheses.

Both hypotheses assume that early- and late-departing individuals have the same fuelling rate and the same net energy expenditure across their migration, that is they generally arrive at the breeding grounds in the same condition. a, Individuals with different departure dates have the same onset of fuelling, and thus different pre-departure fuelling times. Later departure results in higher energy stores at departure and is compensated with less time spent on stopovers, resulting in the same total time spent fuelling and the same arrival. b, Individuals with different departure dates have the same pre-departure fuelling time and are flexible in the onset of fuelling. Energy stores at departure are the same and later departure is not compensated with faster travel between departure and arrival, still resulting in the same total time spent fuelling (through later arrival). Our results support hypothesis a, with departure date being largely compensated with subsequent en route fuelling time across the study species (except brent goose), resulting in similar arrival among early- and late-departing migrations and individuals (Fig. 4a, b; main text).

Supplementary information

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Source Data Fig. 4

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Source Data Extended Data Fig. 1

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Linssen, H., Lameris, T.K., Boom, M.P. et al. Scope for waterfowl to speed up migration to a warming Arctic. Nat. Clim. Chang. 15, 1107–1114 (2025). https://doi.org/10.1038/s41558-025-02419-6

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