Climate sensitive size-dependent survival in tropical trees

Article metrics


Survival rates of large trees determine forest biomass dynamics. Survival rates of small trees have been linked to mechanisms that maintain biodiversity across tropical forests. How species survival rates change with size offers insight into the links between biodiversity and ecosystem function across tropical forests. We tested patterns of size-dependent tree survival across the tropics using data from 1,781 species and over 2 million individuals to assess whether tropical forests can be characterized by size-dependent life-history survival strategies. We found that species were classifiable into four ‘survival modes’ that explain life-history variation that shapes carbon cycling and the relative abundance within forests. Frequently collected functional traits, such as wood density, leaf mass per area and seed mass, were not generally predictive of the survival modes of species. Mean annual temperature and cumulative water deficit predicted the proportion of biomass of survival modes, indicating important links between evolutionary strategies, climate and carbon cycling. The application of survival modes in demographic simulations predicted biomass change across forest sites. Our results reveal globally identifiable size-dependent survival strategies that differ across diverse systems in a consistent way. The abundance of survival modes and interaction with climate ultimately determine forest structure, carbon storage in biomass and future forest trajectories.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

Fig. 1: Schematic of the workflow for this analysis.
Fig. 2: Survival probability as a function of DBH for each of the four identified survival modes.
Fig. 3: Mean annual aboveground carbon loss to mortality.
Fig. 4: In general, traits do not map strongly onto the four survival modes.
Fig. 5: Average annual individual growth rate by survival mode.
Fig. 6: Observed versus predicted biomass.


  1. 1.

    Bonan, G. B. Forests and climate change: forcings, feedbacks, and the climate benefits of forests. Science 320, 1444–1449 (2008).

  2. 2.

    Pan, Y. et al. A large and persistent carbon sink in the world’s forests. Science 333, 988–993 (2011).

  3. 3.

    Wright, S. J. The carbon sink in intact tropical forests. Glob. Change Biol. 19, 337–339 (2013).

  4. 4.

    Brienen, R. J. W. et al. Long-term decline of the Amazon carbon sink. Nature 519, 344–348 (2015).

  5. 5.

    Allen, C. D., Breshears, D. D. & McDowell, N. G. On underestimation of global vulnerability to tree mortality and forest die-off from hotter drought in the Anthropocene. Ecosphere 6, 1–55 (2015).

  6. 6.

    Friend, A. D. et al. Carbon residence time dominates uncertainty in terrestrial vegetation responses to future climate and atmospheric CO2. Proc. Natl Acad. Sci. USA 111, 3280–3285 (2014).

  7. 7.

    McMahon, S. M., Parker, G. G. & Miller, D. R. Evidence for a recent increase in forest growth. Proc. Natl Acad. Sci. USA 107, 3611–3615 (2010).

  8. 8.

    van der Sande, M. T. et al. Abiotic and biotic drivers of biomass change in a Neotropical forest. J. Ecol. 105, 1223–1234 (2017).

  9. 9.

    Johnson, M. O. et al. Variation in stem mortality rates determines patterns of above-ground biomass in Amazonian forests: implications for dynamic global vegetation models. Glob. Change Biol. 22, 3996–4013 (2016).

  10. 10.

    Chesson, P. Mechanisms of maintenance of species diversity. Annu. Rev. Ecol. Syst. 31, 343–366 (2000).

  11. 11.

    Adler, P. B., Ellner, S. P. & Levine, J. M. Coexistence of perennial plants: an embarrassment of niches. Ecol. Lett. 13, 1019–1029 (2010).

  12. 12.

    Purves, D. & Pacala, S. Predictive models of forest dynamics. Science 320, 1452–1453 (2008).

  13. 13.

    Coomes, D. A. & Allen, R. B. Mortality and tree-size distributions in natural mixed-age forests. J. Ecol. 95, 27–40 (2007).

  14. 14.

    Rees, M., Condit, R., Crawley, M., Pacala, S. & Tilman, D. Long-term studies of vegetation dynamics. Science 293, 650–655 (2001).

  15. 15.

    Cobb, R. C., Filipe, J. A. N., Meentemeyer, R. K., Gilligan, C. A. & Rizzo, D. M. Ecosystem transformation by emerging infectious disease: loss of large tanoak from California forests. J. Ecol. 100, 712–722 (2012).

  16. 16.

    Bennett, A. C., McDowell, N. G., Allen, C. D. & Anderson-Teixeira, K. J. Larger trees suffer most during drought in forests worldwide. Nat. Plants 1, 15139 (2015).

  17. 17.

    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).

  18. 18.

    McDowell, N. et al. Drivers and mechanisms of tree mortality in moist tropical forests. New Phytol. 219, 851–869 (2018).

  19. 19.

    Hennig, C. Dissolution point and isolation robustness: robustness criteria for general cluster analysis methods. J. Multivar. Anal. 99, 1154–1176 (2008).

  20. 20.

    McFadden, D. in Frontiers in Economics (ed. Zarembka, P.) 105–142 (Academic Press, New York, 1973).

  21. 21.

    Vanclay, J. K. Mortality functions for North Queensland rain forests. J. Trop. For. Sci. 4, 15–36 (1991).

  22. 22.

    Rüger, N., Huth, A., Hubbell, S. P. & Condit, R. Response of recruitment to light availability across a tropical lowland rain forest community. J. Ecol. 97, 1360–1368 (2009).

  23. 23.

    Eichhorn, M. P., Nilus, R., Compton, S. G., Hartley, S. E. & Burslem, D. F. R. P. Herbivory of tropical rain forest tree seedlings correlates with future mortality. Ecology 91, 1092–1101 (2010).

  24. 24.

    Bell, T., Freckleton, R. P. & Lewis, O. T. Plant pathogens drive density-dependent seedling mortality in a tropical tree. Ecol. Lett. 9, 569–574 (2006).

  25. 25.

    Packer, A. & Clay, K. Soil pathogens and spatial patterns of seedling mortality in a temperate tree. Nature 404, 278–281 (2000).

  26. 26.

    Chambers, J. Q., dos Santos, J., Ribeiro, R. J. & Higuchi, N. Tree damage, allometric relationships, and above-ground net primary production in central Amazon forest. For. Ecol. Manag. 152, 73–84 (2001).

  27. 27.

    Silver, E. J., Fraver, S., D’Amato, A. W., Aakala, T. & Palik, B. J. Long-term mortality rates and spatial patterns in an old-growth Pinus resinosa forest. Can. J. For. Res. 43, 809–816 (2013).

  28. 28.

    McDowell, N. G. & Allen, C. D. Darcy’s law predicts widespread forest mortality under climate warming. Nat. Clim. Change 5, 669–672 (2015).

  29. 29.

    Meakem, V. et al. Role of tree size in moist tropical forest carbon cycling and water deficit responses. New Phytol. 219, 947–958 (2018).

  30. 30.

    Kraft, N. J. B., Metz, M. R., Condit, R. S. & Chave, J. The relationship between wood density and mortality in a global tropical forest data set. New Phytol. 188, 1124–1136 (2010).

  31. 31.

    Poorter, L. The relationships of wood-, gas- and water fractions of tree stems to performance and life history variation in tropical trees. Ann. Bot. 102, 367–375 (2008).

  32. 32.

    Wright, S. J. et al. Functional traits and the growth–mortality trade-off in tropical trees. Ecology 91, 3664–3674 (2010).

  33. 33.

    Poorter, H., Niinemets, Ü., Poorter, L., Wright, I J. & Villar, R. Causes and consequences of variation in leaf mass per area (LMA): a meta-analysis. New Phytol. 182, 565–588 (2009).

  34. 34.

    Westoby, M., Falster, D. S., Moles, A. T., Vesk, P. A. & Wright, I. J. Plant ecological strategies: some leading dimensions of variation between species. Annu. Rev. Ecol. Syst. 33, 125–159 (2002).

  35. 35.

    Kraft, N. J. B., Godoy, O. & Levine, J. M. Plant functional traits and the multidimensional nature of species coexistence. Proc. Natl Acad. Sci. USA 112, 797–802 (2015).

  36. 36.

    Kramer-Schadt, S., Revilla, E., Wiegand, T. & Grimm, V. Patterns for parameters in simulation models. Ecol. Model. 204, 553–556 (2007).

  37. 37.

    Dietze, M. C. et al. A quantitative assessment of a terrestrial biosphere model’s data needs across North American biomes. J. Geophys. Res. Biogeosci. 119, 286–300 (2014).

  38. 38.

    Fisher, R. A. et al. Vegetation demographics in Earth System Models: a review of progress and priorities. Glob. Change Biol. 24, 35–54 (2018).

  39. 39.

    Condit, R. Tropical Forest Census Plots: Methods and Results from Barro Colorado Island, Panama and a Comparison with Other Plots (Springer Science & Business Media, New York, 1998).

  40. 40.

    R Development Core Team R: A language and Environment for Statistical Computing (R Foundation for Statistical Computing, Vienna, 2015).

  41. 41.

    Stan Development Team Stan: A C++ Library for Probability and Sampling v.2.10.0 (2015).

  42. 42.

    Marod, D., Kutintara, U., Yarwudhi, C., Tanaka, H. & Nakashisuka, T. Structural dynamics of a natural mixed deciduous forest in western Thailand. J. Veg. Sci. 10, 777–786 (1999).

  43. 43.

    Metcalf, C. J. E., Horvitz, C. C., Tuljapurkar, S. & Clark, D. A. A time to grow and a time to die: a new way to analyze the dynamics of size, light, age, and death of tropical trees. Ecology 90, 2766–2778 (2009).

  44. 44.

    Miura, M., Manabe, T., Nishimura, N. & Yamamoto, S. Forest canopy and community dynamics in a temperate old-growth evergreen broad-leaved forest, south-western Japan: a 7-year study of a 4-ha plot. J. Ecol. 89, 841–849 (2001).

  45. 45.

    Needham, J., Merow, C., Chang-Yang, C. H., Caswell, H. & McMahon, S. M. Inferring forest fate from demographic data: from vital rates to population dynamic models. Proc. R. Soc. B 285, 2017–2050 (2018).

  46. 46.

    Lê, S., Josse, J. & Husson, F. FactoMineR: An R package for multivariate analysis. J. Stat. Softw. 25, 1–18 (2008).

  47. 47.

    Husson, F., Josse, J. & Pages, J. Principal Component Methods-Hierarchical Clustering-Partitional Clustering: Why Would We Need to Choose for Visualizing Data Technical Report of the Applied Mathematics Department (Agrocampus Quest, Rennes, 2010).

  48. 48.

    Chave, J. et al. Improved allometric models to estimate the aboveground biomass of tropical trees. Glob. Change Biol. 20, 3177–3190 (2014).

  49. 49.

    Chave, J. et al. Towards a worldwide wood economics spectrum. Ecol. Lett. 12, 351–366 (2009).

  50. 50.

    Swenson, N. G. et al. Temporal turnover in the composition of tropical tree communities: functional determinism and phylogenetic stochasticity. Ecology 93, 490–499 (2012).

  51. 51.

    Zanne, A. E. et al. Global Wood Density Database (Dyrad Digital Repository, 2009);

  52. 52.

    Katabuchi, M., Kurokawa, H., Davies, S. J., Tan, S. & Nakashizuka, T. Soil resource availability shapes community trait structure in a species-rich dipterocarp forest. J. Ecol. 100, 643–651 (2012).

  53. 53.

    Stephenson, N. L. Climatic control of vegetation distribution: the role of the water balance. Am. Nat. 135, 649–670 (1990).

  54. 54.

    Yee, T. W. The VGAM package for categorical data analysis. J. Stat. Softw. 32, 1–34 (2010).

Download references


The authors thank the many people involved in establishing and maintaining all the plots utilized in these analyses. A detailed list of funding sources for each plot is available in the Supplementary Information. The development of this project benefited from ForestGEO workshops in 2015, 2016 and 2017 (NSF DEB-1046113 to S.J.D.). Contributions by C.X., J.Q.C., S.J.D. and N.M. were supported by the Next-Generation Ecosystem Experiments (NGEE-Tropics) project, funded by the US Department of Energy, Office of Biological and Environmental Research. S.M.M. was partially funded by NSF - EF1137366. D.J.J. was supported by Los Alamos National Laboratory (Director’s Post-doctoral Fellowship).

Author information

D.J.J., J.N., C.X., N.M. and S.M.M. conceived and designed the analyses, D.J.J. and J.N. performed the analyses, D.J.J., C.X., S.J.D., N.M., J.N., S.M.M. wrote the initial draft. E.C.M. and C.X. provided FATES simulations. K.J.A.-T., S.B., C.H.C.-Y., J.Q.C., J.-M.C., G.B.C., R.C., S.C., C.F., F.I.-N., C.P.G., S.G., N.G., T.W.G., C.-F.H., S.H., A.R.K., M.K., D.K., C.M.L., S.L., E.C.M., M.M., N.G.M., P.S.O., R.O., L.S., N.G.S., I.F.S., S.T., D.W.T., J.T., M.N.U., M.U., R.V., S.Y. and J.K.Z. contributed data, provided site-specific information and helped revise the manuscript. All authors contributed to the final version of the manuscript.

Correspondence to Daniel J. Johnson.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

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

Supplementary information

Supplementary Information

Supplementary figures and tables

Reporting Summary

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Johnson, D.J., Needham, J., Xu, C. et al. Climate sensitive size-dependent survival in tropical trees. Nat Ecol Evol 2, 1436–1442 (2018) doi:10.1038/s41559-018-0626-z

Download citation

Further reading