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Persistent Quaternary climate refugia are hospices for biodiversity in the Anthropocene


Climate stability leads to high levels of speciation and reduced extinction rates, shaping species richness patterns1,2,3. Hotspots of species diversity often overlap with regions that experienced stable temperatures and, perhaps, variable rates of precipitation during the late Quaternary4,5. These hotspots potentially harbour many species with low vagility and small geographical ranges6, making them more vulnerable to future ecoclimatic change4,7,8. By comparing global and regional patterns of climate stability during short periods of unusually large and widespread climate changes since the Last Glacial Maximum with twenty-first-century patterns, we show that human-driven climate change will disproportionally affect biodiversity in late Quaternary climate refugia, ultimately affecting the species, communities and ecosystems that are most vulnerable to climate change. Moreover, future changes in absolute temperature will probably erode the mechanisms that are theorized to sustain biodiversity hotspots across time. These impending shifts from stable to unstable temperatures—projected for the majority of the world’s biodiversity regions—threaten to reduce the size and extent of important climatic safe havens for diversity. Where climate refugia are forecast to persist until the end of this century, temperatures in these refuges are likely to exceed the acclimation capacity of many species, making them short-term hospices for biodiversity at best7,8,9.

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Fig. 1: Classified median trend and variability during periods of rapid change in global mean temperature.
Fig. 2: Areas of overlap in stable surface temperature (≤25th percentile) and unstable precipitation (≥75th percentile) conditions over land.
Fig. 3: The relationship between contemporary species richness and past temperature trend and precipitation variability.
Fig. 4: A comparison of past and future signal-to-noise ratios.
Fig. 5: The regional changes in SNR for Wallace zoogeographic regions.

Data availability

The source data used for the analysis of preindustrial control and future RCP scenarios are available through the Earth System Grid Federation data portals (for example, with scripts to download the data available at Data used for the analysis of climates from the LGM to preindustrialization are available through the PaleoView software ( Data used to recreate the figures is available from the corresponding authors on request.

Code availability

The code used to generate the outputs (trends, variability, SNR) is available from the corresponding authors on request.


  1. Dynesius, M. & Jansson, R. Evolutionary consequences of changes in species’ geographical distributions driven by Milankovitch climate oscillations. Proc. Natl Acad. Sci. USA 97, 9115–9120 (2000).

    Article  CAS  Google Scholar 

  2. Hewitt, G. The genetic legacy of the Quaternary ice ages. Nature 405, 907–913 (2000).

    Article  CAS  Google Scholar 

  3. Fine, P. V. A. Ecological and evolutionary drivers of geographic variation in species diversity. Annu. Rev. Ecol. Evol. Syst. 46, 369–392 (2015).

    Article  Google Scholar 

  4. Fjeldså, J. & Lovett, J. C. Geographical patterns of old and young species in African forest biota: the significance of specific montane areas as evolutionary centres. Biodiv. Conserv. 6, 325–346 (1997).

    Article  Google Scholar 

  5. Haffer, J. Speciation in amazonian forest birds. Science 165, 131–137 (1969).

    Article  CAS  Google Scholar 

  6. Fjeldså, J., Bowie, R. C. K. & Rahbek, C. The role of mountain ranges in the diversification of birds. Annu. Rev. Ecol. Evol. Syst. 43, 249–265 (2012).

    Article  Google Scholar 

  7. Jansson, R. Global patterns in endemism explained by past climatic change. Proc. R. Soc. B 270, 583–590 (2003).

    Article  Google Scholar 

  8. Sandel, B. et al. The influence of Late Quaternary climate-change velocity on species endemism. Science 334, 660–664 (2011).

    Article  CAS  Google Scholar 

  9. Harrison, S. & Noss, R. Endemism hotspots are linked to stable climatic refugia. Ann. Bot. 119, 207–214 (2017).

    Article  Google Scholar 

  10. Araújo, M. B. et al. Quaternary climate changes explain diversity among reptiles and amphibians. Ecography 31, 8–15 (2008).

    Article  Google Scholar 

  11. Dalsgaard, B. et al. Specialization in plant-hummingbird networks is associated with species richness, contemporary precipitation and Quaternary climate-change velocity. PLoS ONE 6, e25891 (2011).

    Article  CAS  Google Scholar 

  12. Carnaval, A. C., Hickerson, M. J., Haddad, C. F., Rodrigues, M. T. & Moritz, C. Stability predicts genetic diversity in the Brazilian Atlantic forest hotspot. Science 323, 785–789 (2009).

    Article  CAS  Google Scholar 

  13. Hughes, A. R., Inouye, B. D., Johnson, M. T., Underwood, N. & Vellend, M. Ecological consequences of genetic diversity. Ecol. Lett. 11, 609–623 (2008).

    Article  Google Scholar 

  14. Tzedakis, P. C., Lawson, I. T., Frogley, M. R., Hewitt, G. M. & Preece, R. C. Buffered tree population changes in a Quaternary refugium: evolutionary implications. Science 297, 2044–2047 (2002).

    Article  CAS  Google Scholar 

  15. Fordham, D. A., Saltre, F., Brown, S. C., Mellin, C. & Wigley, T. M. L. Why decadal to century timescale palaeoclimate data are needed to explain present-day patterns of biological diversity and change. Glob. Change Biol. 24, 1371–1381 (2018).

    Article  Google Scholar 

  16. Cooper, A. et al. Abrupt warming events drove Late Pleistocene Holarctic megafaunal turnover. Science 349, 602–606 (2015).

    Article  CAS  Google Scholar 

  17. Fordham, D. A., Brown, S. C., Wigley, T. M. L. & Rahbek, C. Cradles of diversity are unlikely relics of regional climate stability. Curr. Biol. 29, R356–R357 (2019).

    Article  CAS  Google Scholar 

  18. Wallace, A. R. Tropical Nature, and Other Essays (Macmillan and Company, 1878).

  19. Mittermeier, R. A., Turner, W. R., Larsen, F. W., Brooks, T. M. & Gascon, C. in Biodiversity Hotspots: Distribution and Protection of Conservation Priority Areas (eds Zachos, F. E. & Habel, J. C.) 3–22 (Springer, 2011).

  20. Connell, J. H. Diversity in tropical rain forests and coral reefs. Science 199, 1302–1310 (1978).

    Article  CAS  Google Scholar 

  21. Johnson, D. J., Condit, R., Hubbell, S. P. & Comita, L. S. Abiotic niche partitioning and negative density dependence drive tree seedling survival in a tropical forest. Proc. R. Soc. B 284, 20172210 (2017).

    Article  Google Scholar 

  22. Barlow, J. et al. The future of hyperdiverse tropical ecosystems. Nature 559, 517–526 (2018).

    Article  CAS  Google Scholar 

  23. Burke, K. D. et al. Pliocene and Eocene provide best analogs for near-future climates. Proc. Natl Acad. Sci. USA 115, 13288 (2018).

    Article  CAS  Google Scholar 

  24. Stillman, J. H. Acclimation capacity underlies susceptibility to climate change. Science 301, 65–65 (2003).

    Article  CAS  Google Scholar 

  25. Frieler, K. et al. Limiting global warming to 2 °C is unlikely to save most coral reefs. Nature Clim. Change 3, 165–170 (2012).

    Google Scholar 

  26. Tewksbury, J. J., Huey, R. B. & Deutsch, C. A. Putting the heat on tropical animals. Science 320, 1296–1297 (2008).

    Article  CAS  Google Scholar 

  27. Sniderman, J. M. K. et al. Southern Hemisphere subtropical drying as a transient response to warming. Nat. Clim. Change 9, 232–236 (2019).

  28. Lohman, D. J. et al. Biogeography of the Indo-Australian archipelago. Annu. Rev. Ecol. Evol. Syst. 42, 205–226 (2011).

    Article  Google Scholar 

  29. Pellissier, L. et al. Quaternary coral reef refugia preserved fish diversity. Science 344, 1016–1019 (2014).

    Article  CAS  Google Scholar 

  30. Mora, C. et al. Biotic and human vulnerability to projected changes in ocean biogeochemistry over the 21st century. PLoS Biol. 11, e1001682 (2013).

    Article  CAS  Google Scholar 

  31. van Vuuren, D. P. et al. The representative concentration pathways: an overview. Climatic Change 109, 5–31 (2011).

    Article  Google Scholar 

  32. Liu, Z. et al. Transient simulation of last deglaciation with a new mechanism for Bolling–Allerod warming. Science 325, 310–314 (2009).

    Article  CAS  Google Scholar 

  33. Zhang, X. et al. Indices for monitoring changes in extremes based on daily temperature and precipitation data. WIREs Clim. Change 2, 851–870 (2011).

    Article  Google Scholar 

  34. Wood, S. N. Generalized Additive Models: An Introduction with R (Chapman and Hall/CRC, 2017).

  35. Ver Hoef, J. M. & Boveng, P. L. Quasi-poisson vs. negative binomial regression: how should we model overdispersed count data? Ecology 88, 2766–2772 (2007).

    Article  Google Scholar 

  36. Grueber, C. E., Nakagawa, S., Laws, R. J. & Jamieson, I. G. Multimodel inference in ecology and evolution: challenges and solutions. J. Evol. Biol. 24, 699–711 (2011).

    Article  CAS  Google Scholar 

  37. Holt, B. G. et al. An update of wallace’s zoogeographic regions of the world. Science 339, 74–78 (2013).

    Article  CAS  Google Scholar 

  38. Jetz, W. & Rahbek, C. Geographic range size and determinants of avian species richness. Science 297, 1548–1551 (2002).

    Article  Google Scholar 

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This research was funded by an Australian Research Council Future Fellowships awarded to D.A.F. (grant no. FT140101192) and a Discovery Grant (grant no. DP130103261) awarded to T.M.L.W.

Author information

Authors and Affiliations



D.A.F conceived and led the project. S.C.B and T.M.L.W. did the analysis. B.L.O.-B. and C.R. guided the analysis of climate and macroecological datasets. S.C.B drafted the manuscript and all authors commented on the paper.

Corresponding authors

Correspondence to Stuart C. Brown or Damien A. Fordham.

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Competing interests

The authors declare no competing interests.

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Peer review information Nature Climate Change thanks Glenn Yannic and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Classified median trend and variability during periods of rapid change in global mean temperature.

Panels show the past (a, b) and the future for RCP 4.5 (c, d) for surface temperature (a, c) and precipitation (b, d). The six classes map median trend and variability (s.d. of residuals from the trend) calculated separately for land and ocean: ≤ 25th (P25); > 25th and ≤ 50th (Low–Low); ≤ 50th for trend and ≥ 50th for variability (Low–High); > 50th for trend and ≤ 50th for variability (High–Low); > 50th and ≤ 75th (High–High); > 75th (P75). The hatched overlays in c and d show climatic conditions that are considered as either stable (≤ P25, surface temperature) or unstable (≥ P75, precipitation) at a global scale in both the past and future.

Extended Data Fig. 2 Areas of overlap in stable surface temperature (≤ 25th percentile) and unstable precipitation (≥ 75th percentile) conditions over land.

Panels show the past (a), and the future under RCP 4.5 (b). Areas of overlap - regions where climate conditions are hypothesized to drive higher contemporary species richness – are shown in blue. Areas in orange in b, show differences between the past and the future (i.e., areas of overlap that are lost). The transparent green regions overlaid on the maps are biodiversity hotspots19.

Extended Data Fig. 3 Comparison of past and future signal-to-noise ratios.

Grid cell differences (ΔSNR) in signal-to-noise ratio (SNR = trend/variability) for centuries of rapid change in global-mean temperature since 21,000 BP and for RCP 4.5 calculated for air temperature (a) and precipitation (b).

Extended Data Fig. 4 Regional changes in SNR for Wallace Zoogeographic regions.

Map of percent overlap between empirical kernel density estimates (KDE) for temperature SNR (a) and precipitation SNR (b) calculated during past rapid shifts in global-mean temperature and under an RCP 4.5 scenario.

Supplementary information

Supplementary Information

Supplementary methods, Figs. 1–9, Tables 1–5 and refs. 1–49.

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Brown, S.C., Wigley, T.M.L., Otto-Bliesner, B.L. et al. Persistent Quaternary climate refugia are hospices for biodiversity in the Anthropocene. Nat. Clim. Chang. 10, 244–248 (2020).

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