Letter | Published:

Amplified plant turnover in response to climate change forecast by Late Quaternary records

Nature Climate Change volume 6, pages 11151119 (2016) | Download Citation

Abstract

Conservation decisions are informed by twenty-first-century climate impact projections that typically predict high extinction risk1,2. Conversely, the palaeorecord shows strong sensitivity of species abundances and distributions to past climate changes3, but few clear instances of extinctions attributable to rising temperatures. However, few studies have incorporated palaeoecological data into projections of future distributions. Here we project changes in abundance and conservation status under a climate warming scenario for 187 European and North American plant taxa using niche-based models calibrated against taxa–climate relationships for the past 21,000 years. We find that incorporating long-term data into niche-based models increases the magnitude of projected future changes for plant abundances and community turnover. The larger projected changes in abundances and community turnover translate into different, and often more threatened, projected IUCN conservation status for declining tree taxa, compared with traditional approaches. An average of 18.4% (North America) and 15.5% (Europe) of taxa switch IUCN categories when compared with single-time model results. When taxa categorized as ‘Least Concern’ are excluded, the palaeo-calibrated models increase, on average, the conservation threat status of 33.2% and 56.8% of taxa. Notably, however, few models predict total disappearance of taxa, suggesting resilience for these taxa, if climate were the only extinction driver. Long-term studies linking palaeorecords and forecasting techniques have the potential to improve conservation assessments.

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References

  1. 1.

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

  2. 2.

    , , & Multiple dimensions of climate change and their implications for biodiversity. Science 344, 1247579 (2014).

  3. 3.

    & Long-term ecological records and their relevance to climate change predictions for a warmer world. Annu. Rev. Ecol. Evol. Syst. 42, 267–287 (2011).

  4. 4.

    Predicting the past distribution of species climatic niches. Glob. Ecol. Biogeogr. 18, 521–531 (2009).

  5. 5.

    & Conservation paleobiology: putting the dead to work. Trends Ecol. Evol. 26, 30–37 (2012).

  6. 6.

    , , , & Modeling species and community responses to past, present, and future episodes of climatic and ecological change. Annu. Rev. Ecol. Evol. Syst. 46, 343–368 (2015).

  7. 7.

    , , , & Beyond predictions: biodiversity conservation in a changing climate. Science 332, 53–58 (2010).

  8. 8.

    et al. The ice age ecologist: testing methods for reserve prioritization during the last global warming. Glob. Ecol. Biogeogr. 22, 289–301 (2012).

  9. 9.

    et al. Building the niche through time: using 13,000 years of data to predict the effects of climate change on three tree species in Europe. Glob. Ecol. Biogeogr. 22, 302–317 (2013).

  10. 10.

    & Biodiversity and climate change. Science 326, 806–807 (2009).

  11. 11.

    et al. Approaching a state shift in Earth’s biosphere. Nature 486, 52–58 (2012).

  12. 12.

    , , & Biodiversity baselines, thresholds and resilience: testing predictions and assumptions using palaeoecological data. Trends Ecol. Evol. 25, 583–591 (2010).

  13. 13.

    et al. Species-specific responses of Late Quaternary megafauna to climate and humans. Nature 479, 359–364 (2011).

  14. 14.

    , & Paleoecoinformatics: applying geohistorical data to ecological questions. Trends Ecol. Evol. 27, 104–112 (2012).

  15. 15.

    , & How much do we overestimate future local extinction rates when restricting the range of occurrence data in climate suitability models? Ecography 33, 878–886 (2010).

  16. 16.

    et al. No-analog climates and shifting realized niches during the late Quaternary: implications for 21st-century predictions by species distribution models. Glob. Change Biol. 18, 1698–1713 (2012).

  17. 17.

    Concluding remarks. Cold Spring Harb. Symp. Quant. Biol. 22, 415–427 (1957).

  18. 18.

    & Ensemble forecasting of species distributions. Trends Ecol. Evol. 22, 42–47 (2007).

  19. 19.

    IUCN Guidelines for using the IUCN Red List Categories and Criteria Version 10 (IUCN, 2013).

  20. 20.

    & Responses of plant populations and communities to environmental changes of the late quaternary. Paleobiology 26, 194–220 (2000).

  21. 21.

    , & The art of modelling range-shifting species. Methods Ecol. Evol. 1, 330–342 (2010).

  22. 22.

    & Biological responses to rapid climate change at the Younger Dryas-Holocene transition at Krákenes, western Norway. Holocene 18, 19–30 (2008).

  23. 23.

    & Late Quaternary extinction of a tree species in eastern North America. Proc. Natl Acad. Sci. USA 96, 13847–13852 (1999).

  24. 24.

    & Pollen percentages, tree abundances and the Fagerlind effect. J. Quat. Sci. 1, 35–43 (1986).

  25. 25.

    & Climatic and biotic velocities for woody taxa distributions over the last 16000 years in eastern North America. Ecol. Lett. 16, 773–781 (2013).

  26. 26.

    et al. Tree migration-rates: narrowing the gap between inferred post-glacial rates and projected rates. PLoS ONE 8, e71797 (2013).

  27. 27.

    , & Synergies among extinction drivers under global change. Trends Ecol. Evol. 23, 453–460 (2007).

  28. 28.

    et al. Population dynamics can be more important than physiological limits for determining range shifts under climate change. Glob. Change Biol. 19, 3224–3237 (2013).

  29. 29.

    et al. Impact of a century of climate change on small-mammal communities in Yosemite National Park, USA. Science 322, 261–264 (2008).

  30. 30.

    , , & Better forecasts of range dynamics using genetic data. Trends Ecol. Evol. 29, 436–443 (2014).

  31. 31.

    et al. The temperature of Europe during the Holocene reconstructed from pollen data. Quat. Sci. Rev. 22, 1701–1716 (2003).

Download references

Acknowledgements

D.N.-B. thanks det Frie Forskningsrads forskerkarriereprogram Sapere Aude. D.N.-B., B.G.H. and C.R. thank the Danish National Research Foundation for its support of the Center for Macroecology, Evolution, and Climate. J.W.W. was supported by the National Science Foundation (EAR-0844223, DEB-1257508) and the Climate, People, and Environment Program at the University of Wisconsin. J.S. and P.V. were supported by the British Broadcasting Corporation, BBC. B.G.H. also thanks the Marie Curie Actions under the Seventh Framework Programme (PIEF-GA-2009-252888) and B.G.H. and C.R. acknowledge the support of Imperial College London’s Grand Challenges in Ecosystems and the Environment Initiative.

Author information

Affiliations

  1. Center for Macroecology, Evolution and Climate, National Museum of Natural History, University of Copenhagen, 2100 Copenhagen, Denmark

    • D. Nogués-Bravo
    • , B. G. Holt
    •  & C. Rahbek
  2. Point Blue Conservation Science, Petaluma, California 94954, USA

    • S. Veloz
  3. Department of Life Sciences, Imperial College London, Silwood Park Campus, Ascot SL5 7PY, UK

    • B. G. Holt
    •  & C. Rahbek
  4. Department of Meteorology and Centre for Past Climate Change, University of Reading, Reading RG6 6BB, UK

    • J. Singarayer
  5. School of Geographical Sciences, University of Bristol, Bristol BS8 1SS, UK

    • J. Singarayer
    •  & P. Valdes
  6. Institut des Science de l’Environnement, Université de Genève, CH-1015 Lausanne, Switzerland

    • B. Davis
  7. Geography Department, University of Utah, 260 S. Central Campus Drive, Salt Lake City 84112, USA

    • S. C. Brewer
  8. Department of Geography and Center for Climatic Research, University of Wisconsin-Madison, Madison, Wisconsin 53706, USA

    • J. W. Williams

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Contributions

D.N.-B. conceived and headed the overall project. D.N.-B., S.V., B.G.H., S.C.B., J.W.W. and C.R. provided the main conceptual and methodological inputs. S.C.B. and J.W.W. provided the fossil pollen databases. J.S. and P.V. provided the palaeoclimatic simulations. B.G.H. performed the climate envelope model analysis. D.N.-B. performed the IUCN conservation status estimates and the model validation analysis. S.V. performed the niche-overlap and non-analogue climate analyses. D.N.-B. conducted the analysis on the differences of CO2 concentrations across time and the effect of abundance on the magnitude of change among IUCN categories. D.N.-B., S.V., B.G.H., S.C.B., J.W.W. and C.R. wrote most of the manuscript, with input from B.D., J.S. and P.V.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to D. Nogués-Bravo.

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DOI

https://doi.org/10.1038/nclimate3146

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