Abstract

Global warming is forcing many species to shift their distributions upward, causing consequent changes in the compositions of species that occur at specific locations. This prediction remains largely untested for tropical trees. Here we show, using a database of nearly 200 Andean forest plot inventories spread across more than 33.5° latitude (from 26.8° S to 7.1° N) and 3,000-m elevation (from 360 to 3,360 m above sea level), that tropical and subtropical tree communities are experiencing directional shifts in composition towards having greater relative abundances of species from lower, warmer elevations. Although this phenomenon of ‘thermophilization’ is widespread throughout the Andes, the rates of compositional change are not uniform across elevations. The observed heterogeneity in thermophilization rates is probably because of different warming rates and/or the presence of specialized tree communities at ecotones (that is, at the transitions between distinct habitats, such as at the timberline or at the base of the cloud forest). Understanding the factors that determine the directions and rates of compositional changes will enable us to better predict, and potentially mitigate, the effects of climate change on tropical forests.

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Data availability

The plot data that support the findings of this study are available from the Red de Bosques (https://redbosques.condesan.org/) upon reasonable request. The list of species included in the analysis with their number of GBIF records after filtering and their estimated thermal optima is available in Supplementary Table 2.

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Acknowledgements

We thank the many individuals and institutions (including the Red de Bosques Andinos, CODESAN, APECO, CONICET and RAINFOR) who are working to protect and understand Andean forests; GBIF and contributing institutions for making collection data publicly available and E. Ortíz for creating the map of plot locations. B.F. and K.J.F. were supported by the US NSF (DEB-1350125) and the Swiss Agency for Development and Cooperation. M.R.S. and W.F.R. were supported by the US NSF (DEB-1754647, DEB-1258112, and EAR-1338694). J.H. was supported by DFG Grants HO3296/2 and HO3296/4. Peruvian plot monitoring was supported by the Blue Moon Fund and the Gordon and Betty Moore Foundation’s Andes to Amazon Program and RAINFOR grant 1656 (coordinated by O. Phillips). A complete list of acknowledgments and funding sources can be found in the Supplementary Information.

Reviewer information

Nature thanks A. M. Latimer, J. Lenoir, H. Pauli and the other anonymous reviewer(s) for their contribution to the peer review of this work.

Author information

Affiliations

  1. Department of Biology, University of Miami, Coral Gables, FL, USA

    • Belén Fadrique
    •  & Kenneth J. Feeley
  2. Departamento de Biología, Escuela Politécnica Nacional, Quito, Ecuador

    • Selene Báez
  3. Consortium for the Sustainable Development of the Andean Ecoregion (CONDESAN), Quito, Ecuador

    • Selene Báez
    • , Francisco Cuesta C.
    • , Manuel Peralvo
    •  & Esteban Pinto
  4. Departamento de Ciencias Forestales, Universidad Nacional de Colombia–Sede Medellín, Medellín, Colombia

    • Álvaro Duque
  5. Instituto de Ecología Regional (IER), Universidad Nacional de Tucumán (UNT) & Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Yerba Buena, Argentina

    • Agustina Malizia
    • , Cecilia Blundo
    • , Julieta Carilla
    •  & Oriana Osinaga-Acosta
  6. Facultad de Ciencias Agrarias, Universidad Nacional de Jujuy, Jujuy, Argentina

    • Lucio Malizia
  7. Department of Biology and Center for Energy, Environment and Sustainability, Wake Forest University, Winston-Salem, NC, USA

    • Miles Silman
    •  & William Farfán-Ríos
  8. Herbario Vargas (CUZ), Universidad Nacional de San Antonio Abad del Cusco, Cusco, Peru

    • William Farfán-Ríos
  9. Environmental Change Institute, School of Geography and the Environment, University of Oxford, Oxford, UK

    • Yadvinder Malhi
  10. Department of Geography & the Environment, University of Texas at Austin, Austin, TX, USA

    • Kenneth R. Young
  11. Paleoecology & Landscape Ecology, Institute for Biodiversity and Ecosystem Dynamics (IBED), University of Amsterdam, Amsterdam, Netherlands

    • Francisco Cuesta C.
  12. Plant Ecology, University of Göttingen, Göttingen, Germany

    • Jurgen Homeier
  13. Universidad de Cuenca, Facultad de Ciencias Agropecuarias, Cuenca, Ecuador

    • Oswaldo Jadan
  14. Programa de Investigación Biodiversidad y Servicios Ecosistémicos, Universidad Nacional de Loja, Loja, Ecuador

    • Nikolay Aguirre
    •  & Zhofre Aguirre
  15. Fairchild Tropical Botanic Garden, Coral Gables, FL, USA

    • Kenneth J. Feeley

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Contributions

B.F. and K.J.F. designed the study, carried out the analysis and wrote the Article. S.B., A.D., A.M., C.B., J.C., O.O.-A., L.M., M.S., W.F.-R., Y.M., K.R.Y., F.C.C., J.H., M.P., E.P., O.J., N.A. and Z.A. provided data and assistance with writing.

Competing interests

The authors declare no competing interests.

Corresponding author

Correspondence to Kenneth J. Feeley.

Extended data figures and tables

  1. Extended Data Fig. 1 CTI, MAT and elevation of study plots.

    a, The relationship between the mean CTI for each of the Andean forest plots (averaged across all censuses) and the MAT at the plot locations. n = 186, slope = 0.71, R = 0.92, 95% confidence interval = 0.88–0.93, P < 0.001. b, The relationship between the mean plot CTI and plot elevation. n = 186, R = −0.77, 95% confidence interval = −0.82 to −0.7, P < 0.001. c, The relationship between plot MAT and plot elevation. n = 186, R = −0.92, 95% confidence interval = −0.93 to −0.88, P < 0.001. All analyses are two-sided Spearman correlations.

  2. Extended Data Fig. 2 Regression-based thermophilization rates of repeatedly censused plots.

    TRplot was compared to the MAT for the Andean forest plots with multiple censuses (n = 64). Each point represents one plot and the size of the point is proportional to the number of censuses. Error bars are 95% confidence intervals based on the linear least-square regressions of the CTI versus census year of each plot. Grey points represent plots with non-significant TRplot values and filled, coloured points represent plots with significant TRplot values; hollow points are plots with only two censuses and for which the significance of the TRplot could therefore not be determined. Positive and negative TRplot are coloured red and blue, respectively.

  3. Extended Data Fig. 3 Thermophilization rates for areas with different warming rates.

    The thermophilization rates in areas with different warming rates (TRwarm; the annualized change in the mean CTI of all plots within a band of equitable warming rate) were compared to the warming rate. n = 283 plot censuses, assigned to 20 warming bands. The dashed line indicates the mean TRwarm and the coloured shaded area indicates the 95% confidence interval of TRwarm. Positive and negative TRwarm is coloured red and blue, respectively.

  4. Extended Data Fig. 4 Species richness of repeatedly censused 1-ha plots.

    Species richness versus MAT in the 1-ha Andean forest plots with multiple censuses. n = 61. Each point represents one plot and the red and blue colours indicate positive and negative TRplot values, respectively. The line shows the linear regression between MAT and species richness. R2 = 0.10, P < 0.05.

  5. Extended Data Fig. 5 Range of the thermal optima in study plots.

    The range of thermal optima of co-occurring species versus TRplot in the plots with multiple censuses. n = 64. Each point represents one plot and the red and blue colours represent positive and negative TRplot values, respectively. The line shows the linear regression between the range of the thermal optima of the plots and TRplot. R2 = 0.19, P < 0.001.

  6. Extended Data Fig. 6 Basal area change in species composition.

    Percentage change in absolute basal area per plot for more-thermophilic (species thermal optimum > plot CTI) and less-thermophilic (species thermal optimum < plot CTI) species versus MAT in plots with multiple censuses (n = 64). The more- and less-thermophilic species are coloured red and blue, respectively. Lines show loess regression fits between the percentage change in basal area and MAT, and the shaded areas represent the 95% confidence intervals around the loess regressions.

  7. Extended Data Table 1 Results for alternative calculations of TRMAT and TRplot

Supplementary information

  1. Supplementary Information

    This file contains extended Acknowledgments

  2. Reporting Summary

  3. Supplementary Tables

    Supplementary Table 1 in pdf format contains detailed information of the plots included in the analysis such as coordinates, plot size, MAT and CTI. Supplementary Table 2 in pdf format shows the list of the 1720 species included in the analysis, number of GBIF records available after filtering and their estimated Thermal Optima.

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https://doi.org/10.1038/s41586-018-0715-9

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