Skip to main content

Thank you for visiting You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Evolutionary diversity is associated with wood productivity in Amazonian forests



Higher levels of taxonomic and evolutionary diversity are expected to maximize ecosystem function, yet their relative importance in driving variation in ecosystem function at large scales in diverse forests is unknown. Using 90 inventory plots across intact, lowland, terra firme, Amazonian forests and a new phylogeny including 526 angiosperm genera, we investigated the association between taxonomic and evolutionary metrics of diversity and two key measures of ecosystem function: aboveground wood productivity and biomass storage. While taxonomic and phylogenetic diversity were not important predictors of variation in biomass, both emerged as independent predictors of wood productivity. Amazon forests that contain greater evolutionary diversity and a higher proportion of rare species have higher productivity. While climatic and edaphic variables are together the strongest predictors of productivity, our results show that the evolutionary diversity of tree species in diverse forest stands also influences productivity. As our models accounted for wood density and tree size, they also suggest that additional, unstudied, evolutionarily correlated traits have significant effects on ecosystem function in tropical forests. Overall, our pan-Amazonian analysis shows that greater phylogenetic diversity translates into higher levels of ecosystem function: tropical forest communities with more distantly related taxa have greater wood productivity.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

Fig. 1: Location of plots.
Fig. 2: Bivariate relationships between aboveground wood productivity (AGWP) and the diversity variables included in the best-performing model.
Fig. 3: Standardized effect sizes for the best-fit model for both wood productivity and aboveground biomass.

Data availability

The permanently archived data package of the plot-level diversity, aboveground biomass, wood productivity and genus-level phylogeny are available from


  1. 1.

    Maherali, H. & Klironomos, J. N. Influence of phylogeny on fungal community assembly and ecosystem functioning. Science 316, 1746–1749 (2007).

    CAS  PubMed  Google Scholar 

  2. 2.

    Cadotte, M. W. Experimental evidence that evolutionarily diverse assemblages result in higher productivity. Proc. Natl Acad. Sci. USA 110, 8996–9000 (2013).

    CAS  PubMed  Google Scholar 

  3. 3.

    Cadotte, M. W., Cavender-Bares, J., Tilman, D. & Oakley, T. H. Using phylogenetic, functional and trait diversity to understand patterns of plant community productivity. PLoS ONE 4, e5695 (2009).

    PubMed  PubMed Central  Google Scholar 

  4. 4.

    Cadotte, M. W., Cardinale, B. J. & Oakley, T. H. Evolutionary history and the effect of biodiversity on plant productivity. Proc. Natl Acad. Sci. USA 105, 17012–17017 (2008).

    CAS  PubMed  Google Scholar 

  5. 5.

    Srivastava, D. S., Cadotte, M. W., Macdonald, A. A. M., Marushia, R. G. & Mirotchnick, N. Phylogenetic diversity and the functioning of ecosystems. Ecol. Lett. 15, 637–648 (2012).

    PubMed  Google Scholar 

  6. 6.

    Cadotte, M. W. Phylogenetic diversity and productivity: gauging interpretations from experiments that do not manipulate phylogenetic diversity. Funct. Ecol. 29, 1603–1606 (2015).

    Google Scholar 

  7. 7.

    Cadotte, M. W. Phylogenetic diversity–ecosystem function relationships are insensitive to phylogenetic edge lengths. Funct. Ecol. 29, 718–723 (2015).

    Google Scholar 

  8. 8.

    Davies, T. J., Urban, M. C., Rayfield, B., Cadotte, M. W. & Peres-Neto, P. R. Deconstructing the relationships between phylogenetic diversity and ecology: a case study on ecosystem functioning. Ecology 97, 2212–2222 (2016).

    PubMed  Google Scholar 

  9. 9.

    Venail, P. et al. Species richness, but not phylogenetic diversity, influences community biomass production and temporal stability in a re-examination of 16 grassland biodiversity studies. Funct. Ecol. 29, 615–626 (2015).

    Google Scholar 

  10. 10.

    Coelho de Souza, F. et al. Evolutionary heritage influences Amazon tree ecology. Proc. R. Soc. B Biol. Sci. 283, 20161587 (2016).

    Google Scholar 

  11. 11.

    Webb, C. O., Ackerly, D. D., Mcpeek, M. A. & Donoghue, M. J. Phylogenies and community ecology. Annu. Rev. Ecol. Syst. 33, 475–505 (2002).

    Google Scholar 

  12. 12.

    Webb, C. O. & Losos, A. E. J. B. Exploring the phylogenetic structure of ecological communities: an example for rain forest trees. Am. Nat. 156, 145–155 (2000).

    PubMed  Google Scholar 

  13. 13.

    Chave, J. et al. Regional and phylogenetic variation of wood density across 2456 neotropical tree species. Ecol. Appl. 16, 2356–2367 (2006).

    PubMed  Google Scholar 

  14. 14.

    Baraloto, C. et al. Decoupled leaf and stem economics in rain forest trees. Ecol. Lett. 13, 1338–1347 (2010).

    PubMed  Google Scholar 

  15. 15.

    Fauset, S. et al. Hyperdominance in Amazonian forest carbon cycling. Nat. Commun. 6, 6857 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  16. 16.

    Faith, D. P. Conservation evaluation and phylogenetic diversity. Biol. Conserv. 61, 1–10 (1992).

    Google Scholar 

  17. 17.

    Tucker, C. M. et al. A guide to phylogenetic metrics for conservation, community ecology and macroecology. Biol. Rev. 92, 698–715 (2016).

    PubMed  Google Scholar 

  18. 18.

    Cadotte, M., Albert, C. H. & Walker, S. C. The ecology of differences: assessing community assembly with trait and evolutionary distances. Ecol. Lett. 16, 1234–1244 (2013).

    PubMed  Google Scholar 

  19. 19.

    Swenson, N. G. Phylogenetic resolution and quantifying the phylogenetic diversity and dispersion of communities. PLoS ONE 4, e4390 (2009).

    PubMed  PubMed Central  Google Scholar 

  20. 20.

    Honorio Coronado, E. N. et al. Phylogenetic diversity of Amazonian tree communities. Divers. Distrib. 21, 1295–1307 (2015).

    Google Scholar 

  21. 21.

    Ter Steege, H. et al. Hyperdominance in the Amazonian tree flora. Science 342, 1243092 (2013).

    PubMed  Google Scholar 

  22. 22.

    Beer, C. et al. Terrestrial gross carbon dioxide uptake: global distribution and covariation with climate. Science 329, 834–838 (2010).

    CAS  PubMed  Google Scholar 

  23. 23.

    Malhi, Y. et al. The regional variation of aboveground live biomass in old-growth Amazonian forests. Glob. Change Biol. 12, 1107–1138 (2006).

    Google Scholar 

  24. 24.

    Forest, F. et al. Preserving the evolutionary potential of floras in biodiversity hotspots. Nature 445, 757–760 (2007).

    CAS  PubMed  Google Scholar 

  25. 25.

    Quesada, C. A. et al. Basin-wide variations in Amazon forest structure and function are mediated by both soils and climate. Biogeosciences 9, 2203–2246 (2012).

    Google Scholar 

  26. 26.

    Sullivan, M. J. P. et al. Diversity and carbon storage across the tropical forest biome. Sci. Rep. 7, 39102 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  27. 27.

    Hijmans, R. J., Cameron, S. E., Parra, J. L., Jones, P. G. & Jarvis, A. Very high resolution interpolated climate surfaces for global land areas. Int. J. Climatol. 25, 1965–1978 (2005).

    Google Scholar 

  28. 28.

    Quesada, C. A. et al. Variations in chemical and physical properties of Amazon forest soils in relation to their genesis. Biogeosciences 7, 1515–1541 (2010).

    CAS  Google Scholar 

  29. 29.

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

    PubMed  Google Scholar 

  30. 30.

    Voskamp, A., Baker, D. J., Stephens, P. A., Valdes, P. J. & Willis, S. G. Global patterns in the divergence between phylogenetic diversity and species richness in terrestrial birds. J. Biogeogr. 44, 709–721 (2017).

    Google Scholar 

  31. 31.

    Dexter, K. & Chave, J. Evolutionary patterns of range size, abundance and species richness in Amazonian angiosperm trees. PeerJ 4, e2402 (2016).

    PubMed  PubMed Central  Google Scholar 

  32. 32.

    Baraloto, C. et al. Using functional traits and phylogenetic trees to examine the assembly of tropical tree communities. J. Ecol. 100, 690–701 (2012).

    Google Scholar 

  33. 33.

    Magurran, A. E. Measuring Biological Diversity (Blackwell Science, 2004).

  34. 34.

    Reich, P. B. Key canopy traits drive forest productivity. Proc. R. Soc. B Biol. Sci. 279, 2128–2134 (2012).

    Google Scholar 

  35. 35.

    Williams, L. J., Paquette, A., Cavender-Bares, J., Messier, C. & Reich, P. B. Spatial complementarity in tree crowns explains overyielding in species mixtures. Nat. Ecol. Evol. 1, 0063 (2017).

    Google Scholar 

  36. 36.

    Jucker, T., Bouriaud, O. & Coomes, D. A. Crown plasticity enables trees to optimize canopy packing in mixed-species forests. Funct. Ecol. 29, 1078–1086 (2015).

    Google Scholar 

  37. 37.

    Pretzsch, H. Canopy space filling and tree crown morphology in mixed-species stands compared with monocultures. For. Ecol. Manage. 327, 251–264 (2014).

    Google Scholar 

  38. 38.

    Goodman, R. C., Phillips, O. L. & Baker, T. R. The importance of crown dimensions to improve tropical tree biomass estimates. Ecol. Appl. 24, 680–698 (2014).

    PubMed  Google Scholar 

  39. 39.

    Goodman, R. C., Phillips, O. L. & Baker, T. R. Dryad Data from: The importance of crown dimensions to improve tropical tree biomass estimates. Dryad Digital Repository (2013).

  40. 40.

    Parker, I. M. et al. Phylogenetic structure and host abundance drive disease pressure in communities. Nature 520, 542–544 (2015).

    CAS  PubMed  Google Scholar 

  41. 41.

    Gilbert, G. S. & Parker, I. M. The evolutionary ecology of plant disease: a phylogenetic perspective. Annu. Rev. Phytopathol. 54, 549–578 (2016).

    CAS  PubMed  Google Scholar 

  42. 42.

    Fine, P. V., Mesones, I. & Coley, P. D. Herbivores promote habitat specialization by trees in Amazonian forests. Science 305, 663–665 (2004).

    CAS  PubMed  Google Scholar 

  43. 43.

    Forrister, D. L., Endara, M.-J., Younkin, G. C., Coley, P. D. & Kursar, T. A. Herbivores as drivers of negative density dependence in tropical forest saplings. Science 363, 1213–1216 (2019).

    CAS  PubMed  Google Scholar 

  44. 44.

    Eichenberg, D. et al. Impacts of species richness on productivity in a large-scale subtropical forest experiment. Science 362, 80–83 (2018).

    PubMed  Google Scholar 

  45. 45.

    Satdichanh, M. et al. Phylogenetic diversity correlated with above-ground biomass production during forest succession: evidence from tropical forests in Southeast Asia. J. Ecol. 107, 1419–1432 (2018).

    Google Scholar 

  46. 46.

    Cavanaugh, K. C. et al. Carbon storage in tropical forests correlates with taxonomic diversity and functional dominance on a global scale. Glob. Ecol. Biogeogr. 23, 563–573 (2014).

    Google Scholar 

  47. 47.

    Poorter, L. et al. Diversity enhances carbon storage in tropical forests. Glob. Ecol. Biogeogr. 24, 1314–1328 (2015).

    Google Scholar 

  48. 48.

    Sande, M. T. et al. Biodiversity in species, traits, and structure determines carbon stocks and uptake in tropical forests. Biotropica 49, 593–603 (2017).

    Google Scholar 

  49. 49.

    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).

    Google Scholar 

  50. 50.

    Chao, K. J. et al. Growth and wood density predict tree mortality in Amazon forests. J. Ecol. 96, 281–292 (2008).

    Google Scholar 

  51. 51.

    Lopez-Gonzalez, G., Lewis, S. L., Burkitt, M. & Phillips, O. L. a web application and research tool to manage and analyse tropical forest plot data. J. Veg. Sci. 22, 610–613 (2011).

    Google Scholar 

  52. 52.

    Lopez-Gonzalez G., Simon L. L., Mark B., Baker P. J. & Oliver L. P. (2009);

  53. 53.

    Forrestel, E. J. et al. Different clades and traits yield similar grassland functional responses. Proc. Natl Acad. Sci. USA 114, 705–710 (2017).

    CAS  PubMed  Google Scholar 

  54. 54.

    Dexter, K. G. et al. Dispersal assembly of rain forest tree communities across the Amazon basin. Proc. Natl Acad. Sci. USA 114, 2645–2650 (2017).

    CAS  PubMed  Google Scholar 

  55. 55.

    Boyle, B. et al. The taxonomic name resolution service: an online tool for automated standardization of plant names. BMC Bioinformatics 14, 16 (2013).

    PubMed  PubMed Central  Google Scholar 

  56. 56.

    Gonzalez, M. A. et al. Identification of Amazonian trees with DNA barcodes. PLoS ONE 4, e7483 (2009).

    PubMed  PubMed Central  Google Scholar 

  57. 57.

    Lewis, S. L. et al. Tropical forest tree mortality, recruitment and turnover rates: calculation, interpretation and comparison when census intervals vary. J. Ecol. 92, 929–944 (2004).

    Google Scholar 

  58. 58.

    Talbot, J. et al. Methods to estimate aboveground wood productivity from long-term forest inventory plots. For. Ecol. Manage. 320, 30–38 (2014).

    Google Scholar 

  59. 59.

    Lewis, S. L. et al. Increasing carbon storage in intact African tropical forests. Nature 457, 1003–1006 (2009).

    CAS  PubMed  Google Scholar 

  60. 60.

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

    Google Scholar 

  61. 61.

    Zanne, A. E. et al. Dryad Data from: Towards a worldwide wood economics spectrum. Dryad Digital Repository (2009).

  62. 62.

    Feldpausch, T. R. et al. Height–diameter allometry of tropical forest trees. Biogeosciences 8, 1081–1106 (2011).

    Google Scholar 

  63. 63.

    Benjamini, Y. & Hochberg, Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. Ser. B 57, 289–300 (1995).

    Google Scholar 

  64. 64.

    Ter Steege, H. et al. Continental-scale patterns of canopy tree composition and function across Amazonia. Nature 443, 444–447 (2006).

    CAS  PubMed  Google Scholar 

  65. 65.

    Kutner, M., Nachtsheim, C., Neter, J. & Li, W. Applied Linear Statistical Models (McGraw-Hill/Irwin, 2004).

  66. 66.

    Kim, S. ppcor: An R package for a fast calculation to semi-partial correlation coefficients. Commun. Stat. Appl. Methods 22, 665–674 (2015).

    PubMed  PubMed Central  Google Scholar 

  67. 67.

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

  68. 68.

    Dixon, P. VEGAN, a package of R functions for community ecology. J. Veg. Sci. 14, 927–930 (2009).

    Google Scholar 

  69. 69.

    Kembel, S. W. et al. Picante: R tools for integrating phylogenies and ecology. Bioinformatics 26, 1463–1464 (2010).

    CAS  PubMed  Google Scholar 

  70. 70.

    Lopez-Gonzalez, G., Sullivan, M. & Baker, T. BiomasaFP: tools for analysing data downloaded from R package version 1.1 (2015).

  71. 71.

    Pinheiro, J. et al. nlme: linear and nonlinear mixed effects models. R package version 3.1-128 (2016).

  72. 72.

    Eva, H. D. et al. The land cover map for South America in the year 2000. GLC2000 Database (European Commission, Joint Research Centre, 2003);

Download references


This paper is a product of the project ‘Niche Evolution of South American Trees’ (funded by NERC; NE/I028122/1), RAINFOR (the Amazon Forest Inventory Network) and ( Phylogenetic data were generated by the Niche Evolution of South American Trees project; forest inventory data were generated by the RAINFOR network and curated by RAINFOR and have been supported by the Gordon and Betty Moore Foundation, the European Union’s Seventh Framework Programme projects 283080 (GEOCARBON) and 282664 (AMAZALERT), ERC grant ‘Tropical Forests in the Changing Earth System’, Natural Environment Research Council Urgency, Consortium and Standard grants ‘AMAZONICA’ (NE/F005806/1), ‘TROBIT’ (NE/D005590/1) and ‘Niche Evolution of South American Trees’ (NE/I028122/1), and ‘BIO-RED’ (NE/N012542/1). F.C.d.S. was supported by a PhD scholarship from the Coordination for the Improvement of Higher Education Personnel (Brazil; 117913-6). K.G.D. was supported by a Leverhulme International Academic Fellowship. O.L.P. was supported by an ERC Advanced Grant and is a Royal Society Wolfson Research Merit Award holder. R.T.B. acknowledges support from a Leverhulme Trust Research Fellowship (RF-2015-653). This paper is 772 in the Technical Series of the Biological Dynamics of Forest Fragments Project (BDFFP-INPA/STRI). We thank J. Lloyd and C. A. Quesada for comments on the manuscript. J. Lloyd helped conceived the RAINFOR forest census plot network. We also acknowledge A. Clark for laboratory work to generate new DNA sequences.

Author information




F.C.d.S., R.T.B. and K.G.D. conceived the study. F.C.d.S., R.T.B., O.L.P. and K.G.D. designed the study. F.C.d.S., K.G.D. and R.T.B. produced the phylogeny. F.C.d.S. analysed the data and wrote the paper. All co-authors collected field data or managed data. O.L.P. and Y.M. conceived the RAINFOR forest census plot network. K.G.D., O.L.P., R.T.P., D.N., M.J.P.S., E.Á.-D., A.Alves, I.A., A.Andrade, L.E.O.C.A., A.A.-M., E.J.M.M.A., L.A., G.A.A.C., O.B., C.B., J.G.B., R.G.A.B., R.J.W.B., F.B., J.L.C.C., W.C., J.C., A.C., J.A.C., F.C.-V., A.L.d.C., P.B.d.C., A.D.F., T.R.F., D.R.G., E.G., R.C.G., M.G., R.H., N.H., E.N.H.C., E.J.-R., T.J.K., S.L., W.F.L., G.L.-G., T.E.L., Y.M., B.S.M., B.H.M.-J., C.M., A.M.-M., D.A.N., P.N.V., M.C.P.M., G.C.P., J.J.P., N.C.A.P., L.P., A.P., F.R., A.Roopsind, A.Rudas, R.P.S., N.S., M.S., J.Singh, J.Stropp, H.t.S., J.T., R.T.-C., R.K.U., R.V.V., I.C.-V., S.A.V., V.A.V., R.J.Z. and R.T.B. commented and/or approved the manuscript.

Corresponding author

Correspondence to Fernanda Coelho de Souza.

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 Tables 1–6, Figs. 1–12, methods, results, discussion and Appendices 1–5.

Reporting summary

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Coelho de Souza, F., Dexter, K.G., Phillips, O.L. et al. Evolutionary diversity is associated with wood productivity in Amazonian forests. Nat Ecol Evol 3, 1754–1761 (2019).

Download citation

Further reading


Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing