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Predicting and mitigating future biodiversity loss using long-term ecological proxies

Nature Climate Change volume 6, pages 909–916 (2016)Cite this article

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Abstract

Uses of long-term ecological proxies in strategies for mitigating future biodiversity loss are too limited in scope. Recent advances in geochronological dating, palaeoclimate reconstructions and molecular techniques for inferring population dynamics offer exciting new prospects for using retrospective knowledge to better forecast and manage ecological outcomes in the face of global change. Opportunities include using fossils, genes and computational models to identify ecological traits that caused species to be differentially prone to regional and range-wide extinction, test if threatened-species assessment approaches work and locate habitats that support stable ecosystems in the face of shifting climates. These long-term retrospective analyses will improve efforts to predict the likely effects of future climate and other environmental change on biodiversity, and target conservation management resources most effectively.

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Figure 1: Approaches for integrating long-term historical knowledge into ecological models.
Figure 2: Change in mean annual temperature in the UK for the past 21 kyr and for the twentieth and twenty-first century.
Figure 3: Validating predictions from range dynamics models using fossil and genetic data.
Figure 4: Identifying the traits most likely to influence extinction risk and range dynamics using a robust coverage of a multi-dimensional parameter space.

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Acknowledgements

The Australian Research Council (ARC) supported D.A.F., F.S., T.M.L.W and B.W.B. (FT140101192, DP130103842, DP130103261); NSF DEB-1146198 supported H.R.A. B. Otto-Bliesner helped with the climate analysis. D. Nogués-Bravo and J. Gill provided useful ideas and comments.

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Authors and Affiliations

  1. The Environment Institute and School of Biological Sciences, The University of Adelaide, 5005, South Australia, Australia

    Damien A. Fordham, Frédérik Saltré & Tom M. L. Wigley

  2. Department of Ecology and Evolution, Stony Brook University, Stony Brook, 11794, New York, USA

    H. Resit Akçakaya

  3. Department of Biological Sciences, Macquarie University, 2109, New South Wales, Australia

    John Alroy

  4. National Center for Atmospheric Research, Boulder, 80307, Colorado, USA

    Tom M. L. Wigley

  5. School of Biological Sciences, Private Bag 55, University of Tasmania, Hobart, 7001, Tasmania, Australia

    Barry W. Brook

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The ideas in this paper are the result of discussions involving all authors. D.A.F. wrote the initial draft of the manuscript and all authors contributed to the writing of the final version of the paper.

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Correspondence to Damien A. Fordham.

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Fordham, D., Akçakaya, H., Alroy, J. et al. Predicting and mitigating future biodiversity loss using long-term ecological proxies. Nature Clim Change 6, 909–916 (2016). https://doi.org/10.1038/nclimate3086

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