Geographical limits to species-range shifts are suggested by climate velocity (original) (raw)

Change history

Two labels in Fig. 1b, bottom part, were incorrect and have been fixed.

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Acknowledgements

This work was conducted as a part of the Towards Understanding Marine Biological Impacts of Climate Change Working Group supported by the National Center for Ecological Analysis and Synthesis, a center funded by the NSF (grant no. EF-0553768), the University of California, Santa Barbara and the State of California. M.T.B., P.J.M. and J.G.M. were supported by the UK Natural Environment Research Council grant NE/J024082/1. D.S. was supported by the Australian Research Council’s Collaborative Research Network. J.P. thanks the Australian Research Council Centre of Excellence for Coral Reef Studies for additional support, and A.J.R. was supported by the Australian Research Council Discovery Grant DP0879365 and Future Fellowship Grant FT0991722.

Author information

Authors and Affiliations

  1. Department of Ecology, Scottish Association for Marine Science, Scottish Marine Institute, Oban, Argyll, PA37 1QA, Scotland, UK,
    Michael T. Burrows & Jorge García Molinos
  2. School of Science and Engineering, University of the Sunshine Coast, Maroochydore, Queensland QLD 4558, Australia,
    David S. Schoeman
  3. Climate Adaptation Flagship, CSIRO Marine and Atmospheric Research, Ecosciences Precinct, GPO Box 2583, Brisbane, Queensland 4001, Australia,
    Anthony J. Richardson & Elvira S. Poloczanska
  4. Centre for Applications in Natural Resource Mathematics (CARM), School of Mathematics and Physics, The University of Queensland, St Lucia, Queensland 4072, Australia,
    Anthony J. Richardson
  5. Department of Genetics, University of Melbourne, 30 Flemington Road, Parkville, Victoria 3010, Australia,
    Ary Hoffmann
  6. Department of Biology, The University of North Carolina at Chapel Hill, Chapel Hill, 27599-3280, North Carolina, USA
    Lauren B. Buckley & John F. Bruno
  7. Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Aberystwyth SY23 3DA, UK,
    Pippa J. Moore
  8. Centre for Marine Ecosystems Research, Edith Cowan University, Perth 6027, Australia,
    Pippa J. Moore
  9. The Global Change Institute, The University of Queensland, Brisbane, Queensland 4072, Australia,
    Christopher J. Brown & Ove Hoegh-Guldberg
  10. The UWA Oceans Institute, University of Western Australia, 35 Stirling Highway, Crawley 6009, Australia,
    Carlos M. Duarte
  11. Department of Global Change Research, IMEDEA (UIB-CSIC), Instituto Mediterráneo de Estudios Avanzados, Esporles 07190, Spain,
    Carlos M. Duarte
  12. Department of Marine Biology, Faculty of Marine Sciences, King Abdulaziz University, PO Box 80207, Jeddah 21589, Saudi Arabia,
    Carlos M. Duarte
  13. Bren School of Environmental Science and Management, University of California, Santa Barbara, 93106, California, USA
    Benjamin S. Halpern & Carrie V. Kappel
  14. Imperial College London, Silwood Park Campus, Buckhurst Road, Ascot SL5 7PY, UK,
    Benjamin S. Halpern
  15. GeoZentrum Nordbayern, Paläoumwelt, Universität Erlangen-Nürnberg, Loewenichstrasse 28, 91054 Erlangen, Germany,
    Wolfgang Kiessling
  16. Museum für Naturkunde, Invalidenstr asse 43, 10115 Berlin, Germany,
    Wolfgang Kiessling
  17. Department of Zoology and Biodiversity Research Centre, University of British Columbia, Vancouver V6T 1Z4, Canada,
    Mary I. O’Connor
  18. School of Biological Sciences, Australian Research Council Centre of Excellence for Coral Reef Studies, The University of Queensland, Brisbane, Queensland 4072, Australia,
    John M. Pandolfi
  19. Integrative Biology, University of Texas, Austin, 78712, Texas, USA
    Camille Parmesan
  20. Marine Institute, Drake Circus, University of Plymouth, Devon PL4 8AA, UK,
    Camille Parmesan
  21. Farallon Institute for Advanced Ecosystem Research, 101 H Street, Suite Q, Petaluma, California 94952, USA,
    William J. Sydeman
  22. Climate Adaptation Flagship, CSIRO Ecosystem Sciences, GPO Box 1700, Canberra, Australian Capital Territory 2601, Australia,
    Simon Ferrier & Kristen J. Williams

Authors

  1. Michael T. Burrows
  2. David S. Schoeman
  3. Anthony J. Richardson
  4. Jorge García Molinos
  5. Ary Hoffmann
  6. Lauren B. Buckley
  7. Pippa J. Moore
  8. Christopher J. Brown
  9. John F. Bruno
  10. Carlos M. Duarte
  11. Benjamin S. Halpern
  12. Ove Hoegh-Guldberg
  13. Carrie V. Kappel
  14. Wolfgang Kiessling
  15. Mary I. O’Connor
  16. John M. Pandolfi
  17. Camille Parmesan
  18. William J. Sydeman
  19. Simon Ferrier
  20. Kristen J. Williams
  21. Elvira S. Poloczanska

Contributions

M.T.B., D.S.S., A.J.R. and E.S.P. conceived the research. M.T.B., J.G.M. and D.S.S. analysed the data. M.T.B., D.S.S., A.J.R., E.S.P., J.G.M. and M.I.O. wrote the first draft. M.T.B., D.S.S., A.J.R., J.G.M., A.H., L.B.B., P.J.M., C.J.B., J.F.B., C.M.D., B.S.H., O.H.G., C.V.K.,W.K., M.I.O., J.M.P., C.P., W.J.S., S.F., K.J.W. and E.S.P. contributed equally to discussion of ideas and analyses, and all authors commented on the manuscript.

Corresponding author

Correspondence toMichael T. Burrows.

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Competing interests

The authors declare no competing financial interests.

Additional information

Data used in analyses are available from the University of East Anglia Climate Research Unit and the UK Meteorological Office Hadley Centre, with online access at the British Atmospheric Data Centre. Maps are available as Google Earth files on http://www.figshare.com.

Extended data figures and tables

Extended Data Figure 1 Ternary plots containing the trajectory classes.

a–d, Plots are based on the proportions of trajectories starting from (_N_st), ending in (_N_end), and flowing through (_N_FT) a cell. In a ternary plot three-dimensional cell coordinates (adding up to a 100%) are projected in a two-dimensional space. The arrows by the axes indicate the direction in which each variable is projected into the trajectory space. Point clouds represent global 1° resolution cell coordinate projections into the trajectory space based on 50-year climate trajectory simulations for land (a) and sea surface temperature (b) (1960–2009), and 2006–2100 RCP 8.5 (c) and RCP 4.5 (d) climate scenarios for ocean temperatures. CON, convergence; DIV, divergence; SK, relative sink.

Extended Data Figure 2 Uncertainty associated with the proposed trajectory classification.

a, Mean standard error of the trend. b, Standard deviation in magnitude of spatial gradient. c, Angular deviation of the spatial gradient associated to bootstrapped (n = 500) mean annual surface temperature series. d, e, Bootstrap-derived uncertainty associated with the proposed trajectory classification (d) and after collapsing slow/non-moving and convergence/divergence areas into a single category each (e). rad, radians.

Extended Data Figure 3 Frequency distribution of the uncertainty associated with the trajectory-based classification of land and ocean.

a, Frequency histogram of the proportion of coincident categories between the proposed 1960–2009 trajectory classification and classifications resulting from 500 bootstrapped surface temperature climate series (see Methods for details). b, c, Cumulative frequency plots of the mean distribution of bootstrapped trajectory categories contained in each category of the proposed trajectory classification for land (b) and ocean regions (c).

Extended Data Figure 4 Global patterns of climate-velocity trajectory classes for ocean and land surface temperatures.

a–d, Ocean surface temperatures (a, c) and land surface temperatures (b, d). Uncertainty in classification of areas is shown by the cross hatching on areas of original global patterns with 500 bootstrap class maps that are classified as ‘very likely’ (a, b; <90% consistency) and ‘likely’ (c, d; <66% consistency).

Extended Data Table 1 Summary of trajectory classes, with implications for species range shifts if species distributions track shifting climatic niches

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Burrows, M., Schoeman, D., Richardson, A. et al. Geographical limits to species-range shifts are suggested by climate velocity.Nature 507, 492–495 (2014). https://doi.org/10.1038/nature12976

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