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Long-distance migratory birds threatened by multiple independent risks from global change

Abstract

Many species migrate long distances annually between their breeding and wintering areas1. Although global change affects both ranges, impact assessments have generally focused on breeding ranges and ignored how environmental changes influence migrants across geographical regions and the annual cycle2,3. Using range maps and species distribution models, we quantified the risk of summer and winter range loss and migration distance increase from future climate and land cover changes on long-distance migratory birds of the Holarctic (n = 715). Risk estimates are largely independent of each other and magnitudes vary geographically. If seasonal range losses and increased migration distances are not considered, we strongly underestimate the number of threatened species by 18–49% and the overall magnitude of risk for 17–50% species. Many of the analysed species that face multiple global change risks are not listed by International Union for Conservation of Nature as threatened or near threatened. To neglect seasonal migration in impact assessments could thus seriously misguide species’ conservation.

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Fig. 1: Three proposed global change risks for migratory birds.
Fig. 2: Seasonal species richness of long-distance migratory birds and projected changes in species richness for 2050.
Fig. 3: Projected changes in the summer and winter range sizes and in migratory distances.
Fig. 4: Overlap in global change risks for different IUCN categories.

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Data availability

All data except the GLOBIO land cover data are publicly available; bird range maps at www.birdlife.org, climate data at www.worldclim.org, bird trait data at https://doi.org/10.6084/m9.figshare.c.3306933, and bird phylogenetic data at www.birdtree.org. The GLOBIO land cover scenarios were provided by courtesy of M. Bakkenes and are not publicly available.

References

  1. Newton, I. The Migration Ecology of Birds (Academic, London, 2007).

    Chapter  Google Scholar 

  2. Small-Lorenz, S. L., Culp, L. A., Ryder, T. B., Will, T. C. & Marra, P. P. A blind spot in climate change vulnerability assessments. Nat. Clim. Change 3, 91–93 (2013).

    Article  Google Scholar 

  3. Hewson, C. M., Thorup, K., Pearce-Higgins, J. W. & Atkinson, P. W. Population decline is linked to migration route in the Common Cuckoo. Nat. Commun. 7, 12996 (2016).

    Article  Google Scholar 

  4. Chen, I. C., Hill, J. K., Ohlemüller, R., Roy, D. B. & Thomas, C. D. Rapid range shifts of species associated with high levels of climate warming. Science 333, 1024–1026 (2011).

    Article  CAS  Google Scholar 

  5. Urban, M. C. Accelerating extinction risk from climate change. Science 348, 571–573 (2015).

    Article  CAS  Google Scholar 

  6. Sillett, T. S., Holmes, R. T. & Sherry, T. W. Impacts of a global climate cycle on population dynamics of a migratory songbird. Science 288, 2040–2042 (2000).

    Article  CAS  Google Scholar 

  7. Kirby, J. S. et al. Key conservation issues for migratory land- and waterbird species on the world’s major flyways. Bird Conserv. Int. 18, S49–S73 (2008).

    Article  Google Scholar 

  8. Sanderson, F. J., Donald, P. F., Pain, D. J., Burfield, I. J. & van Bommel, F. P. J. Long-term population declines in Afro-Palearctic migrant birds. Biol. Conserv. 131, 93–105 (2006).

    Article  Google Scholar 

  9. Teitelbaum, C. S. et al. Experience drives innovation of new migration patterns of whooping cranes in response to global change. Nat. Commun. 7, 12793 (2016).

    Article  CAS  Google Scholar 

  10. Rushing, C. S., Ryder, T. B. & Marra, P. P. Quantifying drivers of population dynamics for a migratory bird throughout the annual cycle. Proc. R. Soc. B. 283, 20152846 (2016).

    Article  Google Scholar 

  11. La Sorte, F. A. et al. Global change and the distributional dynamics of migratory bird populations wintering in Central America. Glob. Change Biol. 23, 5284–5296 (2017).

    Article  Google Scholar 

  12. Both, C. et al. Avian population consequences of climate change are most severe for long-distance migrants in seasonal habitats. Proc. R. Soc. B. 277, 1259–1266 (2009).

    Article  Google Scholar 

  13. Marra, P. P., Cohen, E. B., Loss, S. R., Rutter, J. E. & Tonra, C. M. A call for full annual cycle research in animal ecology. Biol. Lett. 11, 20150552 (2015).

    Article  Google Scholar 

  14. Guisan, A., Thuiller, W. & Zimmermann, N. E. Habitat Suitability and Distribution Models With Applications in R (Cambridge Univ. Press, Cambridge, 2017).

  15. Thuiller, W. et al. Consequences of climate change on the tree of life in Europe. Nature 470, 531–534 (2011).

    Article  CAS  Google Scholar 

  16. Pereira, H. M. et al. Scenarios for global biodiversity in the 21st century. Science 330, 1496–1501 (2010).

    Article  CAS  Google Scholar 

  17. Barbet-Massin, M., Walther, B. A., Thuiller, W., Rahbek, C. & Jiguet, F. Potential impacts of climate change on the winter distribution of Afro-Palaearctic migrant passerines. Biol. Lett. 5, 248–251 (2009).

    Article  Google Scholar 

  18. Doswald, N. et al. Potential impacts of climatic change on the breeding and non-breeding ranges and migration distance of European Sylvia warblers. J. Biogeogr. 36, 1194–1208 (2009).

    Article  Google Scholar 

  19. Reese, G. C. & Skagen, S. K. Modeling nonbreeding distributions of shorebirds and waterfowl in response to climate change. Ecol. Evol. 7, 1497–1513 (2017).

    Article  Google Scholar 

  20. Culp, L. A., Cohen, E. B., Scarpignato, A. L., Thogmartin, W. E. & Marra, P. P. Full annual cycle climate change vulnerability assessment for migratory birds. Ecosphere 8, e01565 (2017).

    Article  Google Scholar 

  21. Jetz, W., Wilcove, D. S. & Dobson, A. P. Projected impacts of climate and land-use change on the global diversity of birds. PLoS Biol. 5, e157 (2007).

    Article  Google Scholar 

  22. IPCC Climate Change 2013: The Physical Science Basis (eds Stocker, T. F. et al.) (Cambridge Univ. Press, 2013).

  23. Barbet-Massin, M., Thuiller, W. & Jiguet, F. The fate of European breeding birds under climate, land-use and dispersal scenarios. Glob. Change Biol. 18, 881–890 (2012).

    Article  Google Scholar 

  24. IUCN Standards and Petitions Subcommittee Guidelines for Using the IUCN Red List Categories and Criteria V ersion 13 (IUCN, 2017).

  25. La Sorte, F. A. & Fink, D. Projected changes in prevailing winds for transatlantic migratory birds under global warming. J. Anim. Ecol. 86, 273–284 (2017).

    Article  Google Scholar 

  26. Lindström, Å. & Alerstam, T. Optimal fat loads in migrating birds: a test of the time-minimization hypothesis. Am. Nat. 140, 477–491 (1992).

    Article  Google Scholar 

  27. Schmaljohann, H. & Both, C. The limits of modifying migration speed to adjust to climate change. Nat. Clim. Change 7, 573–576 (2017).

    Article  Google Scholar 

  28. Schaefer, M., Menz, S., Jeltsch, F. & Zurell, D. sOAR: A tool for modelling optimal animal life-history strategies in cyclic environments. Ecography 41, 551–557 (2018).

    Article  Google Scholar 

  29. Faurby, S. & Araújo, M. B. Anthropogenic range contractions bias species climate change forecasts. Nature Clim. Change 8, 252–256 (2018).

    Article  Google Scholar 

  30. Zurell, D. et al. Benchmarking novel approaches for modelling species range dynamics. Glob. Change Biol. 22, 2651–2664 (2016).

    Article  Google Scholar 

  31. Bird Species Distribution Maps of the World (BirdLife International and NatureServe, Cambridge, 2014).

  32. Schleuning, M. et al. Ecological networks are more sensitive to plant than to animal extinction under climate change. Nat. Commun. 7, 13965 (2016).

    Article  CAS  Google Scholar 

  33. Krosby, M. et al. Climate-induced range overlap among closely related species. Nat. Clim. Change 5, 883–886 (2015).

    Article  Google Scholar 

  34. Jetz, W., Thomas, G. H., Joy, J. B., Hartmann, K. & Mooers, A. O. The global diversity of birds in space and time. Nature 491, 444–448 (2012).

    Article  CAS  Google Scholar 

  35. Wilman, H. et al. EltonTraits 1.0: Species-level foraging attributes of the world’s birds and mammals. Ecology 95, 2027 (2014).

    Article  Google Scholar 

  36. Hijmans, R. J., Cameron, S. E., Parra, J. L., Jones, P. G. & Jarvis, A. Very high resolution interpolated climate surfaces for global land areas. Int. J. Clim. 25, 1965–1978 (2005).

    Article  Google Scholar 

  37. Laube, I., Graham, C. H. & Böhning-Gaese, K. Niche availability in space and time: migration in Sylvia warblers. J. Biogeogr. 42, 1896–1906 (2015).

    Article  Google Scholar 

  38. Zurell, D., Gallien, L., Graham, C. H. & Zimmermann, N. E. Do long-distance migratory birds track their niche through seasons?. J. Biogeogr. 45, 1459–1468 (2018).

    Article  Google Scholar 

  39. Alkemade, R. et al. GLOBIO3: A Framework to Investigate Options for Reducing Global Terrestrial Biodiversity Loss. Ecosystems 12, 374–390 (2009).

    Article  Google Scholar 

  40. van Vuuren, D. P. & Carter, T. R. Climate and socio-economic scenarios for climate change research and assessment: reconciling the new with the old. Clim. Change 122, 415–429 (2013).

    Article  Google Scholar 

  41. Dormann, C. F. et al. Collinearity: a review of methods to deal with it and a simulation study evaluating their performance. Ecography 36, 27–46 (2013).

    Article  Google Scholar 

  42. Thuiller, W., Lafourcade, B., Engler, R. & Araújo, M. B. BIOMOD – a platform for ensemble forecasting of species distributions. Ecography 32, 369–373 (2009).

    Article  Google Scholar 

  43. R Development Core Team R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2014); https://www.R-project.org/

  44. Barbet-Massin, M., Jiguet, F., Albert, C. H. & Thuiller, W. Selecting pseudo-absences for species distribution models: how, where and how many? Methods Ecol. Evol. 3, 327–338 (2012).

    Article  Google Scholar 

  45. Allouche, O., Tsoar, A. & Kadmon, R. Assessing the accuracy of species distribution models: prevalence, kappa and the true skill statistic (TSS). J. Appl. Ecol. 43, 1223–1232 (2006).

    Article  Google Scholar 

  46. Bjornstad, O. N. ncf: Spatial Nonparametric Covariance Functions R package version 1.1-7 (R Foundation for Statistical Computing, 2016).

  47. Hurlbert, A. H. & Jetz, W. Species richness, hotspots, and the scale dependence of range maps in ecology and conservation. Proc. Natl Acad. Sci. USA 104, 13384–13389 (2007).

    Article  CAS  Google Scholar 

  48. Cardoso, P. red: IUCN Redlisting Tools R package version 1.3.3 (R Foundation for Statistical Computing, 2018).

  49. Barbet-Massin, M. & Jetz, W. The effect of range changes on the functional turnover, structure and diversity of bird assemblages under future climate scenarios. Glob. Change Biol. 21, 2917–2928 (2015).

    Article  Google Scholar 

  50. Paradis, E., Baillie, S. R., Sutherland, W. J. & Gregory, R. D. Patterns of natal and breeding dispersal in birds. J. Anim. Ecol. 67, 518–536 (1998).

    Article  Google Scholar 

  51. VanDerWal, J., Falconi, L., Januchowski, S., Shoo, L. & Storlie, C. SDMTools: Species Distribution Modelling Tools: Tools for Processing Data Associated with Species Distribution Modelling Exercises R package version 1.1-221 (R Foundation for Statistical Computing, 2014).

  52. Thuiller, W. et al. Does probability of occurrence relate to population dynamics? Ecography 37, 1155–1166 (2014).

    Article  Google Scholar 

  53. Ho, L. S. T. & Ane, C. A linear-time algorithm for Gaussian and non-Gaussian trait evolution models. Syst. Biol. 63, 397–408 (2014).

    Article  Google Scholar 

  54. Paradis, E. & Claude, J. Analysis of comparative data using generalized estimating equations. J. Theor. Biol. 218, 175–185 (2002).

    Article  Google Scholar 

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Acknowledgements

D.Z. received funding from the Swiss National Science Foundation (SNF, grant no. PZ00P3_168136/1) and from the German Science Foundation (DFG, grant: ZU 361/1-1). N.E.Z. and C.H.G. acknowledge support from SNF (grant nos 31003A_149508/1 and 310030L_170059 to N.E.Z., grant no. 31003A_173342 to C.H.G.). We are indebted to M. Bakkenes for providing the global land cover scenarios.

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D.Z. and N.E.Z. conceived the general idea and designed the study with the help of all authors. D.Z. ran the analyses and led the writing. All authors interpreted results and significantly contributed to writing and editing the manuscript.

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Correspondence to Damaris Zurell.

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Zurell, D., Graham, C.H., Gallien, L. et al. Long-distance migratory birds threatened by multiple independent risks from global change. Nature Clim Change 8, 992–996 (2018). https://doi.org/10.1038/s41558-018-0312-9

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