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Shifts in Arctic vegetation and associated feedbacks under climate change

Nature Climate Change volume 3, pages 673677 (2013) | Download Citation



Climate warming has led to changes in the composition, density and distribution of Arctic vegetation in recent decades1,2,3,4. These changes cause multiple opposing feedbacks between the biosphere and atmosphere5,6,7,8,9, the relative magnitudes of which will have globally significant consequences but are unknown at a pan-Arctic scale10. The precise nature of Arctic vegetation change under future warming will strongly influence climate feedbacks, yet Earth system modelling studies have so far assumed arbitrary increases in shrubs (for example, +20%; refs 6, 11), highlighting the need for predictions of future vegetation distribution shifts. Here we show, using climate scenarios for the 2050s and models that utilize statistical associations between vegetation and climate, the potential for extremely widespread redistribution of vegetation across the Arctic. We predict that at least half of vegetated areas will shift to a different physiognomic class, and woody cover will increase by as much as 52%. By incorporating observed relationships between vegetation and albedo, evapotranspiration and biomass, we show that vegetation distribution shifts will result in an overall positive feedback to climate that is likely to cause greater warming than has previously been predicted. Such extensive changes to Arctic vegetation will have implications for climate, wildlife and ecosystem services.

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We thank G. Arnesen, J. Elith, A. Elvebakk, P. J. Ersts, N. Horning, M. C. Mack, J. Silverman and Y. Ryu. Supported by NSF grants IPY 0732948 to R.G.P., IPY 0732954 to S.J.G., and Expeditions 0832782 to T.D.

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Author notes

    • Sarah J. Knight

    Present address: Food and Environment Research Agency, Sand Hutton, York YO41 1LZ, UK


  1. Center for Biodiversity and Conservation, American Museum of Natural History, New York, New York 10024, USA

    • Richard G. Pearson
    •  & Sarah J. Knight
  2. AT&T Labs-Research, 180 Park Avenue, Florham Park, New Jersey 07932, USA

    • Steven J. Phillips
  3. Woods Hole Research Center, 149 Woods Hole Road, Falmouth, Massachusetts 02540, USA

    • Michael M. Loranty
    • , Pieter S. A. Beck
    •  & Scott J. Goetz
  4. Department of Geography, Colgate University, Hamilton, New York 13346, USA

    • Michael M. Loranty
  5. Department of Computer Science, Cornell University, Ithaca, New York 14853, USA

    • Theodoros Damoulas
  6. Department of Biology, University of York, York YO10 5DD, UK

    • Sarah J. Knight


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R.G.P. and S.J.G. conceived the study; R.G.P. analysed data; S.J.P. analysed data and ran Random Forests models; M.M.L. led albedo and evapotranspiration analyses; P.S.A.B. led biomass and SN analyses; T.D. ran multi-kernel Relevance Vector Machines models; S.J.K. ran preliminary analyses; R.G.P., M.M.L. and P.S.A.B. wrote the paper with contributions from all authors.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Richard G. Pearson.

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