Climate-driven changes in the composition of New World plant communities

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A Publisher Correction to this article was published on 10 September 2020

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Abstract

Climate change is altering the distributions of species, which in turn causes shifts in the composition of plant communities. Specifically, rising temperatures should cause increasing relative abundances of heat-loving or heat-tolerant species (that is, ‘thermophilization’) and changes in precipitation should cause altered abundances of water-demanding species. We analysed millions of records of thousands of species and found that the plant communities in most ecoregions in North, Central and South America have experienced thermophilization over the past four decades (1970–2011). Thermophilization was fastest in ecoregions with intermediate temperatures and was positively correlated with warming rates within many biomes. Changes in the relative abundances of water-demanding species were less consistent and were not correlated with changes in precipitation, meaning that the drought sensitivity of some ecoregions may be increasing despite decreasing rainfall and increasing probabilities of drought. Climate-driven changes in plant community composition will affect the function and stability of New World ecoregions.

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Fig. 1: The relationships between climate and floristic composition of New World ecoregions.
Fig. 2: The thermophilization and mesophilization rates of 191 New World ecoregion plant communities.
Fig. 3: Maps showing the geographic patterns in climate change and changes in plant community composition.
Fig. 4: Differences in the climate compositions of lost, recruiting and surviving species.
Fig. 5: The relationships between changes in the floristic composition of 191 New World ecoregions and their climate.
Fig. 6: The relationships between changes in the floristic composition of 191 New World ecoregions and changes in climate.

Data availability

The project was based entirely on data that are publicly available through CHELSA (http://chelsa-climate.org/), Ecoregions2017 (https://ecoregions2017.appspot.com/) and BIEN (http://bien.nceas.ucsb.edu/bien/). A list of data providers contributing plant collection and observation records to BIEN is included in the Supplementary Information.

Change history

  • 10 September 2020

    An amendment to this paper has been published and can be accessed via a link at the top of the paper.

References

  1. 1.

    Zhang, T., Niinemets, Ü., Sheffield, J. & Lichstein, J. W. Shifts in tree functional composition amplify the response of forest biomass to climate. Nature 556, 99–102 (2018).

    CAS  Google Scholar 

  2. 2.

    Parmesan, C. & Yohe, G. A globally coherent fingerprint of climate change impacts across natural systems. Nature 421, 37–42 (2003).

    CAS  Google Scholar 

  3. 3.

    Parmesan, C. & Hanley, M. E. Plants and climate change: complexities and surprises. Ann. Bot. 116, 849–864 (2015).

    Google Scholar 

  4. 4.

    Telwala, Y., Brook, B. W., Manish, K. & Pandit, M. K. Climate-induced elevational range shifts and increase in plant species richness in a Himalayan biodiversity epicentre. PLoS ONE 8, e57103 (2013).

    CAS  Google Scholar 

  5. 5.

    Jump, A. S., Huang, T. J. & Chou, C. H. Rapid altitudinal migration of mountain plants in Taiwan and its implications for high altitude biodiversity. Ecography 35, 204–210 (2012).

    Google Scholar 

  6. 6.

    Angelo, C. L. & Daehler, C. C. Upward expansion of fire‐adapted grasses along a warming tropical elevation gradient. Ecography 36, 551–559 (2013).

    Google Scholar 

  7. 7.

    Morueta-Holme, N. et al. Strong upslope shifts in Chimborazo’s vegetation over two centuries since Humboldt. Proc. Natl Acad. Sci. USA 112, 12741–12745 (2015).

    CAS  Google Scholar 

  8. 8.

    Parolo, G. & Rossi, G. Upward migration of vascular plants following a climate warming trend in the Alps. Basic Appl. Ecol. 9, 100–107 (2008).

    Google Scholar 

  9. 9.

    Chen, I.-C., Hill, J. K., Ohlemüller, R., Roy, D. B. & Thomas, C. D. Rapid range shifts of species associated with high levels of climate warming. Science 333, 1024–1026 (2011).

    CAS  Google Scholar 

  10. 10.

    Moret, P., Muriel, P., Jaramillo, R. & Dangles, O. Humboldt’s tableau physique revisited. Proc. Natl Acad. Sci. USA 116, 12889–12894 (2019).

    CAS  Google Scholar 

  11. 11.

    Lenoir, J. & Svenning, J. C. Climate-related range shifts—a global multidimensional synthesis and new research directions. Ecography 38, 15–28 (2015).

    Google Scholar 

  12. 12.

    Lenoir, J., Gegout, J. C., Marquet, P. A., de Ruffray, P. & Brisse, H. A significant upward shift in plant species optimum elevation during the 20th century. Science 320, 1768–1771 (2008).

    CAS  Google Scholar 

  13. 13.

    Feeley, K. J. Distributional migrations, expansions, and contractions of tropical plant species as revealed in dated herbarium records. Glob. Change Biol. 18, 1335–1341 (2012).

    Google Scholar 

  14. 14.

    Fei, S. et al. Divergence of species responses to climate change. Sci. Adv. 3, e1603055 (2017).

    Google Scholar 

  15. 15.

    Zhu, K., Woodall, C. W. & Clark, J. S. Failure to migrate: lack of tree range expansion in response to climate change. Glob. Change Biol. 18, 1042–1052 (2012).

    Google Scholar 

  16. 16.

    Crimmins, S. M., Dobrowski, S. Z., Greenberg, J. A., Abatzoglou, J. T. & Mynsberge, A. R. Changes in climatic water balance drive downhill shifts in plant species’ optimum elevations. Science 331, 324–327 (2011).

    CAS  Google Scholar 

  17. 17.

    Kelly, A. E. & Goulden, M. L. Rapid shifts in plant distribution with recent climate change. Proc. Natl Acad. Sci. USA 105, 11823–11826 (2008).

    CAS  Google Scholar 

  18. 18.

    Wieczynski, D. J. et al. Climate shapes and shifts functional biodiversity in forests worldwide. Proc. Natl Acad. Sci. USA 116, 587–592 (2019).

    CAS  Google Scholar 

  19. 19.

    Bertrand, R. et al. Changes in plant community composition lag behind climate warming in lowland forests. Nature 479, 517–520 (2011).

    CAS  Google Scholar 

  20. 20.

    Blonder, B. et al. Linking environmental filtering and disequilibrium to biogeography with a community climate framework. Ecology 96, 972–985 (2015).

    Google Scholar 

  21. 21.

    Gottfried, M. et al. Continent-wide response of mountain vegetation to climate change. Nat. Clim. Change 2, 111–115 (2012).

    Google Scholar 

  22. 22.

    Duque, A., Stevenson, P. & Feeley, K. J. Thermophilization of adult and juvenile tree communities in the northern tropical Andes. Proc. Natl Acad. Sci. USA 112, 10744–10749 (2015).

    CAS  Google Scholar 

  23. 23.

    Fadrique, B. et al. Widespread but heterogeneous responses of Andean forests to climate change. Nature 564, 207–212 (2018).

    CAS  Google Scholar 

  24. 24.

    Feeley, K. J., Hurtado, J., Saatchi, S., Silman, M. R. & Clark, D. B. Compositional shifts in Costa Rican forests due to climate-driven species migrations. Glob. Change Biol. 19, 3472–3480 (2013).

    Google Scholar 

  25. 25.

    Feeley, K. J. et al. Upslope migration of Andean trees. J. Biogeogr. 38, 783–791 (2011).

    Google Scholar 

  26. 26.

    Esquivel‐Muelbert, A. et al. Compositional response of Amazon forests to climate change. Glob. Change Biol. 25, 39–56 (2019).

    Google Scholar 

  27. 27.

    Feeley, K. J. & Silman, M. R. Biotic attrition from tropical forests correcting for truncated temperature niches. Glob. Change Biol. 16, 1830–1836 (2010).

    Google Scholar 

  28. 28.

    Title, P. O. & Bemmels, J. B. ENVIREM: an expanded set of bioclimatic and topographic variables increases flexibility and improves performance of ecological niche modeling. Ecography 41, 291–307 (2018).

    Google Scholar 

  29. 29.

    Santiago, L. S. et al. Coordination and trade-offs among hydraulic safety, efficiency and drought avoidance traits in Amazonian rainforest canopy tree species. New Phytol. 218, 1015–1024 (2018).

    Google Scholar 

  30. 30.

    Strzepek, K., Yohe, G., Neumann, J. & Boehlert, B. Characterizing changes in drought risk for the United States from climate change. Environ. Res. Lett. 5, 044012 (2010).

    Google Scholar 

  31. 31.

    Sheffield, J. & Wood, E. F. Projected changes in drought occurrence under future global warming from multi-model, multi-scenario, IPCC AR4 simulations. Clim. Dynam. 31, 79–105 (2008).

    Google Scholar 

  32. 32.

    Duffy, P. B., Brando, P., Asner, G. P. & Field, C. B. Projections of future meteorological drought and wet periods in the Amazon. Proc. Natl Acad. Sci. USA 112, 13172–13177 (2015).

    CAS  Google Scholar 

  33. 33.

    Conradi, T., Van Meerbeek, K., Ordonez, A. & Svenning, J. C. Biogeographic historical legacies in the net primary productivity of Northern Hemisphere forests. Ecol. Lett. 23, 800–810 (2020).

  34. 34.

    Dinerstein, E. et al. An ecoregion-based approach to protecting half the terrestrial realm. BioScience 67, 534–545 (2017).

    Google Scholar 

  35. 35.

    Olson, D. M. et al. Terrestrial ecoregions of the world: a new map of life on Earth. BioScience 51, 933–938 (2001).

    Google Scholar 

  36. 36.

    Anderson-Teixeira, K. J. et al. CTFS-ForestGEO: a worldwide network monitoring forests in an era of global change. Glob. Change Biol. 21, 528–549 (2015).

    Google Scholar 

  37. 37.

    Dauby, G. et al. RAINBIO: a mega-database of tropical African vascular plants distributions. PhytoKeys 74, 1–18 (2016).

    Google Scholar 

  38. 38.

    DeWalt, S. J., Bourdy, G., de Michel, L. R. & Quenevo, C. Ethnobotany of the Tacana: quantitative inventories of two permanent plots of Northwestern Bolivia. Econ. Bot. 53, 237–260 (1999).

    Google Scholar 

  39. 39.

    Enquist, B. & Boyle, B. SALVIAS—the SALVIAS vegetation inventory database. Biodivers. Ecol. 4, 288 (2012).

    Google Scholar 

  40. 40.

    Enquist, B. J., Condit, R., Peet, R. K., Schildhauer, M. & Thiers, B. M. Cyberinfrastructure for an integrated botanical information network to investigate the ecological impacts of global climate change on plant biodiversity. Preprint at https://peerj.com/preprints/2615/ (2016).

  41. 41.

    Fegraus, E. Tropical Ecology Assessment and Monitoring Network (TEAM Network). Biodivers. Ecol. 4, 287 (2012).

    Google Scholar 

  42. 42.

    Maitner, B. S. et al. The BIEN R package: a tool to access the Botanical Information and Ecology Network (BIEN) database. Methods Ecol. Evol. 9, 373–379 (2018).

    Google Scholar 

  43. 43.

    Peet, R. K. et al. Vegetation-plot database of the Carolina Vegetation Survey. Biodivers. Ecol. 4, 243–253 (2012).

    Google Scholar 

  44. 44.

    Peet, R. K., Lee, M. T., Jennings, M. D. & Faber-Langendoen, D. VegBank: a permanent, open-access archive for vegetation plot data. Biodivers. Ecol. 4, 233–241 (2012).

    Google Scholar 

  45. 45.

    Sosef, M. S. M. et al. Exploring the floristic diversity of tropical Africa. BMC Biol. 15, 15 (2017).

    Google Scholar 

  46. 46.

    König, C. et al. Biodiversity data integration—the significance of data resolution and domain. PLoS Biol. 17, e3000183 (2019).

    Google Scholar 

  47. 47.

    Karger, D. N. et al. Climatologies at high resolution for the earth’s land surface areas. Sci. Data 4, 170122 (2017).

    Google Scholar 

  48. 48.

    Enquist, B. J. et al. The commonness of rarity: global and future distribution of rarity across land plants. Sci. Adv. 5, eaaz0414 (2019).

    Google Scholar 

  49. 49.

    Feeley, K. J., Davies, S. J., Perez, R., Hubbell, S. P. & Foster, R. B. Directional changes in the species composition of a tropical forest. Ecology 92, 871–882 (2011).

    Google Scholar 

  50. 50.

    Gosselin, F. Putting floristic thermophilization in forests into a conservation biology perspective: beyond mean trait approaches. Ann. For. Sci. 73, 215–218 (2016).

    Google Scholar 

  51. 51.

    De Frenne, P. et al. Microclimate moderates plant responses to macroclimate warming. Proc. Natl Acad. Sci. USA 110, 18561–18565 (2013).

    Google Scholar 

  52. 52.

    Stevens, J. T., Safford, H. D., Harrison, S. & Latimer, A. M. Forest disturbance accelerates thermophilization of understory plant communities. J. Ecol. 103, 1253–1263 (2015).

    Google Scholar 

  53. 53.

    Bush, M. B., Silman, M. R. & Urrego, D. H. 48,000 years of climate and forest change in a biodiversity hot spot. Science 303, 827–829 (2004).

    CAS  Google Scholar 

  54. 54.

    R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2014).

  55. 55.

    Bates, D., Mächler, M., Bolker, B. & Walker, S. Fitting linear mixed-effects models using lme4. J. Stat. Soft. 67, 1–48 (2015).

    Google Scholar 

  56. 56.

    Nakagawa, S. & Schielzeth, H. A general and simple method for obtaining R2 from generalized linear mixed‐effects models. Methods Ecol. Evol. 4, 133–142 (2013).

    Google Scholar 

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Acknowledgements

This project was funded through the US National Science Foundation grant no. DEB-1350125 to K.J.F.; D.Z. was supported by the National Doctoral Scholarship COLCIENCIAS-Colombia grant no. 647, 2015-II.

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Contributions

K.J.F. conceived and designed the project and led manuscript writing. K.J.F., C.B., B.F., T.M.P. and D.Z. analysed the data and interpreted results. K.J.F. led manuscript writing and preparation. C.B., B.F., T.M.P. and D.Z. assisted in manuscript writing and preparation.

Corresponding author

Correspondence to K. J. Feeley.

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Extended data

Extended Data Fig. 1 The relationships between temperature and precipitation at the species, ecosystem and community levels.

The relationships between a, species’ optimal temperature (MATopt, oC) and optimal precipitation (TAPopt, mm) as based on the distribution of observation records from 1970–1985 (Pearson’s R = 0.55; d.f. = 17241; P < 0.0001), b, the average Mean Annual Temperature (MAT, oC) and Total Annual Precipitation (TAP, mm) of ecoregions from 1979–2012 (Pearson’s correlation, R = 0.58; d.f. = 189; P < 0.0001), and c) the initial (1970–1985) Community Temperature Index (CTI, oC) and Community Precipitation Index (CPI, mm) of ecoregions (Pearson’s R = 0.72; d.f. = 189; P < 0.0001). In a, each point represents a species; in b and c, each point represents an ecoregion and points are coloured according to their biome designation (see Fig. 1).

Supplementary information

Supplementary Information

Supplementary text and Figs. 1–9.

Supplementary Data

Supplementary Data 1a–f.

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Feeley, K.J., Bravo-Avila, C., Fadrique, B. et al. Climate-driven changes in the composition of New World plant communities. Nat. Clim. Chang. 10, 965–970 (2020). https://doi.org/10.1038/s41558-020-0873-2

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