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Life history and spatial traits predict extinction risk due to climate change

Author

Listed:
  • Richard G. Pearson

    (Centre for Biodiversity and Environment Research, Evolution and Environment, University College London, Gower Street London WC1E 6BT, UK
    American Museum of Natural History, Central Park West at 79th Street New York 10024, USA)

  • Jessica C. Stanton

    (Stony Brook University Stony Brook, New York 11794, USA)

  • Kevin T. Shoemaker

    (Stony Brook University Stony Brook, New York 11794, USA)

  • Matthew E. Aiello-Lammens

    (Stony Brook University Stony Brook, New York 11794, USA)

  • Peter J. Ersts

    (American Museum of Natural History, Central Park West at 79th Street New York 10024, USA)

  • Ned Horning

    (American Museum of Natural History, Central Park West at 79th Street New York 10024, USA)

  • Damien A. Fordham

    (The Environment Institute and School of Earth and Environmental Sciences, University of Adelaide South Australia 5005, Australia)

  • Christopher J. Raxworthy

    (American Museum of Natural History, Central Park West at 79th Street New York 10024, USA)

  • Hae Yeong Ryu

    (Stony Brook University Stony Brook, New York 11794, USA)

  • Jason McNees

    (NatureServe, 1101 Wilson Boulevard, 15th Floor Arlington, Virginia 22209, USA)

  • H. Reşit Akçakaya

    (Stony Brook University Stony Brook, New York 11794, USA)

Abstract

Climate change could be a game-changer for biodiversity conservation, potentially invalidating many established methods including those employed in vulnerability assessments. Now, a simulation study finds that extinction risk due to climate change can be predicted using measurable spatial and demographic variables. Interestingly, most of those variables identified as important are already used in species conservation assessment.

Suggested Citation

  • Richard G. Pearson & Jessica C. Stanton & Kevin T. Shoemaker & Matthew E. Aiello-Lammens & Peter J. Ersts & Ned Horning & Damien A. Fordham & Christopher J. Raxworthy & Hae Yeong Ryu & Jason McNees & , 2014. "Life history and spatial traits predict extinction risk due to climate change," Nature Climate Change, Nature, vol. 4(3), pages 217-221, March.
    • Handle: RePEc:nat:natcli:v:4:y:2014:i:3:d:10.1038_nclimate2113
    DOI: 10.1038/nclimate2113
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    Citations

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    Cited by:

    1. Chunrong Mi & Liang Ma & Mengyuan Yang & Xinhai Li & Shai Meiri & Uri Roll & Oleksandra Oskyrko & Daniel Pincheira-Donoso & Lilly P. Harvey & Daniel Jablonski & Barbod Safaei-Mahroo & Hanyeh Ghaffari , 2023. "Global Protected Areas as refuges for amphibians and reptiles under climate change," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    2. Tiphaine Guillet & Lauriane Mouysset, 2022. "Productive versus environmental objectives of agricultural policies dealing with climate change: a French case study," Post-Print hal-03919917, HAL.
    3. Graciá, Eva & Rodríguez-Caro, Roberto C. & Sanz-Aguilar, Ana & Anadón, José D. & Botella, Francisco & García-García, Angel Luis & Wiegand, Thorsten & Giménez, Andrés, 2020. "Assessment of the key evolutionary traits that prevent extinctions in human-altered habitats using a spatially explicit individual-based model," Ecological Modelling, Elsevier, vol. 415(C).
    4. Pilowsky, Julia A. & Manica, Andrea & Brown, Stuart & Rahbek, Carsten & Fordham, Damien A., 2022. "Simulations of human migration into North America are more sensitive to demography than choice of palaeoclimate model," Ecological Modelling, Elsevier, vol. 473(C).
    5. Patrik Byholm & Martin Beal & Natalie Isaksson & Ulrik Lötberg & Susanne Åkesson, 2022. "Paternal transmission of migration knowledge in a long-distance bird migrant," Nature Communications, Nature, vol. 13(1), pages 1-7, December.
    6. Peters, Ronny & Lin, Yue & Berger, Uta, 2016. "Machine learning meets individual-based modelling: Self-organising feature maps for the analysis of below-ground competition among plants," Ecological Modelling, Elsevier, vol. 326(C), pages 142-151.
    7. Chunyan Cao & Jun Tao, 2021. "Predicting the Areas of Suitable Distribution for Zelkova serrata in China under Climate Change," Sustainability, MDPI, vol. 13(3), pages 1-11, February.
    8. Ochoa-Ochoa, Leticia M. & Flores-Villela, Oscar A. & Bezaury-Creel, Juan E., 2016. "Using one vs. many, sensitivity and uncertainty analyses of species distribution models with focus on conservation area networks," Ecological Modelling, Elsevier, vol. 320(C), pages 372-382.
    9. Lucy R. Mason & Rhys E. Green & Christine Howard & Philip A. Stephens & Stephen G. Willis & Ainars Aunins & Lluís Brotons & Tomasz Chodkiewicz & Przemysław Chylarecki & Virginia Escandell & Ruud P. B., 2019. "Population responses of bird populations to climate change on two continents vary with species’ ecological traits but not with direction of change in climate suitability," Climatic Change, Springer, vol. 157(3), pages 337-354, December.
    10. Pliscoff, Patricio & Luebert, Federico & Hilger, Hartmut H. & Guisan, Antoine, 2014. "Effects of alternative sets of climatic predictors on species distribution models and associated estimates of extinction risk: A test with plants in an arid environment," Ecological Modelling, Elsevier, vol. 288(C), pages 166-177.
    11. Nathalie Butt & Rachael Gallagher, 2018. "Using species traits to guide conservation actions under climate change," Climatic Change, Springer, vol. 151(2), pages 317-332, November.

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