Abstract
Plant communities are composed of species that differ both in functional traits and evolutionary histories. As species’ functional traits partly result from their individual evolutionary history, we expect the functional diversity of communities to increase with increasing phylogenetic diversity. This expectation has only been tested at local scales and generally for specific growth forms or specific habitat types, for example, grasslands. Here we compare standardized effect sizes for functional and phylogenetic diversity among 1,781,836 vegetation plots using the global sPlot database. In contrast to expectations, we find functional diversity and phylogenetic diversity to be only weakly and negatively correlated, implying a decoupling between these two facets of diversity. While phylogenetic diversity is higher in forests and reflects recent climatic conditions (1981 to 2010), functional diversity tends to reflect recent and past climatic conditions (21,000 years ago). The independent nature of functional and phylogenetic diversity makes it crucial to consider both aspects of diversity when analysing ecosystem functioning and prioritizing conservation efforts.
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Data availability
All calculated biodiversity indices necessary to reproduce the results of this paper are available at https://doi.org/10.25829/idiv.3574-mpmk21 (ref. 95). The vegetation plot raw data for sPlotOpen are available at https://www.idiv.de/de/splot/splotopen.html. The vegetation plot raw data contained in the sPlot database are available upon request by submitting a project proposal to the sPlot Steering Committee. The proposals should follow the Governance and Data Property Rules of the sPlot Working Group available on the sPlot website (www.idiv.de/splot). Source data are provided with this paper.
Code availability
All R scripts used for this study can be found in our GitHub repository at https://github.com/georghaehn/Haehn-et-al-2024-FD-PD-coupling.
References
O’Connor, B., Bojinski, S., Röösli, C. & Schaepman, M. E. Monitoring global changes in biodiversity and climate essential as ecological crisis intensifies. Ecol. Inform. 55, 101033 (2020).
Anwar, M. R., Liu, D. L., Macadam, I. & Kelly, G. Adapting agriculture to climate change: a review. Theor. Appl. Climatol. 113, 225–245 (2013).
Benevolenza, M. A. & DeRigne, L. The impact of climate change and natural disasters on vulnerable populations: a systematic review of literature. J. Hum. Behav. Soc. Environ. 29, 266–281 (2019).
IPCC Climate Change 2023: Synthesis Report (eds Core Writing Team, Lee, H. & Romero, J.) (IPCC, 2023).
Fahad, S. et al. Climate Change and Plants: Biodiversity, Growth and Interactions (CRC, 2021).
Corlett, R. T. & Westcott, D. A. Will plant movements keep up with climate change? Trends Ecol. Evol. 28, 482–488 (2013).
Cavender-Bares, J., Kozak, K. H., Fine, P. V. A. & Kembel, S. W. The merging of community ecology and phylogenetic biology. Ecol. Lett. 12, 693–715 (2009).
Götzenberger, L. et al. Ecological assembly rules in plant communities—approaches, patterns and prospects. Biol. Rev. 87, 111–127 (2012).
Rieseberg, L. H., Wood, T. E. & Baack, E. J. The nature of plant species. Nature 440, 524–527 (2006).
Verdú, M. & Pausas, J. G. Fire drives phylogenetic clustering in Mediterranean Basin woody plant communities. J. Ecol. 95, 1316–1323 (2007).
Ackerly, D. D., Schwilk, D. W. & Webb, C. O. Niche evolution and adaptive radiation: testing the order of trait divergence. Ecology 87, 50–61 (2006).
Pillar, V. D., Duarte, L. d. S., Sosinski, E. E. & Joner, F. Discriminating trait-convergence and trait-divergence assembly patterns in ecological community gradients. J. Veg. Sci. 20, 334–348 (2009).
Pillar, V. D., Sabatini, F. M., Jandt, U., Camiz, S. & Bruelheide, H. Revealing the functional traits linked to hidden environmental factors in community assembly. J. Veg. Sci. 32, e12976 (2021).
Pillar, V. D. Trait divergence in plant community assembly is generated by environmental factor interactions. J. Veg. Sci. 35, e13259 (2024).
Ackerly, D. Conservatism and diversification of plant functional traits: evolutionary rates versus phylogenetic signal. Proc. Natl Acad. Sci. USA 106, 19699–19706 (2009).
Ávila-Lovera, E., Winter, K. & Goldsmith, G. R. Evidence for phylogenetic signal and correlated evolution in plant–water relation traits. New Phytol. 237, 392–407 (2023).
Münkemüller, T. et al. How to measure and test phylogenetic signal. Methods Ecol. Evol. 3, 743–756 (2012).
Molina-Venegas, R. & Rodríguez, M. Á. Revisiting phylogenetic signal; strong or negligible impacts of polytomies and branch length information? BMC Evol. Biol. 17, 53 (2017).
Melzer, R., Wang, Y.-Q. & Theißen, G. The naked and the dead: the ABCs of gymnosperm reproduction and the origin of the angiosperm flower. Semin. Cell Dev. Biol. 21, 118–128 (2010).
Cavender-Bares, J., Ackerly, D. D., Baum, D. A. & Bazzaz, F. A. Phylogenetic overdispersion in Floridian oak communities. Am. Nat. 163, 823–843 (2004).
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).
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).
Webb, C. O. Exploring the phylogenetic structure of ecological communities: an example for rain forest trees. Am. Nat. 156, 145–155 (2000).
Flynn, D. F. B., Mirotchnick, N., Jain, M., Palmer, M. I. & Naeem, S. Functional and phylogenetic diversity as predictors of biodiversity—ecosystem–function relationships. Ecology 92, 1573–1581 (2011).
Tucker, C. M., Davies, T. J., Cadotte, M. W. & Pearse, W. D. On the relationship between phylogenetic diversity and trait diversity. Ecology 99, 1473–1479 (2018).
Večeřa, M. et al. Decoupled phylogenetic and functional diversity in European grasslands. Preslia 95, 413–445 (2023).
Prinzing, A. et al. Less lineages—more trait variation: phylogenetically clustered plant communities are functionally more diverse. Ecol. Lett. 11, 809–819 (2008).
Kluge, J. & Kessler, M. Phylogenetic diversity, trait diversity and niches: species assembly of ferns along a tropical elevational gradient. J. Biogeogr. 38, 394–405 (2011).
Bruelheide, H. et al. sPlot—a new tool for global vegetation analyses. J. Veg. Sci. 30, 161–186 (2019).
Castagneyrol, B., Jactel, H., Vacher, C., Brockerhoff, E. G. & Koricheva, J. Effects of plant phylogenetic diversity on herbivory depend on herbivore specialization. J. Appl. Ecol. 51, 134–141 (2014).
Qian, H., Hao, Z. & Zhang, J. Phylogenetic structure and phylogenetic diversity of angiosperm assemblages in forests along an elevational gradient in Changbaishan, China. J. Plant Ecol. 7, 154–165 (2014).
Honorio Coronado, E. N. et al. Phylogenetic diversity of Amazonian tree communities. Divers. Distrib. 21, 1295–1307 (2015).
Mastrogianni, A., Kallimanis, A. S., Chytrý, M. & Tsiripidis, I. Phylogenetic diversity patterns in forests of a putative refugial area in Greece: a community level analysis. For. Ecol. Manag. 446, 226–237 (2019).
Klimeš, A., Šímová, I., Zizka, A., Antonelli, A. & Herben, T. The ecological drivers of growth form evolution in flowering plants. J. Ecol. 110, 1525–1536 (2022).
Chai, Y. et al. Patterns of taxonomic, phylogenetic diversity during a long-term succession of forest on the Loess Plateau, China: insights into assembly process. Sci. Rep. 6, 27087 (2016).
Díaz, S. et al. The global spectrum of plant form and function. Nature 529, 167–171 (2016).
Weigelt, A. et al. An integrated framework of plant form and function: the belowground perspective. New Phytol. 232, 42–59 (2021).
Carta, A., Peruzzi, L. & Ramírez-Barahona, S. A global phylogenetic regionalization of vascular plants reveals a deep split between Gondwanan and Laurasian biotas. New Phytol. 233, 1494–1504 (2022).
Sabatini, F. M. et al. sPlotOpen—an environmentally balanced, open-access, global dataset of vegetation plots. Glob. Ecol. Biogeogr. 30, 1740–1764 (2021).
Reich, P. B. et al. The evolution of plant functional variation: traits, spectra, and strategies. Int. J. Plant Sci. 164, 143–164 (2003).
Mayfield, M. M. & Levine, J. M. Opposing effects of competitive exclusion on the phylogenetic structure of communities. Ecol. Lett. 13, 1085–1093 (2010).
Pigot, A. L. & Etienne, R. S. A new dynamic null model for phylogenetic community structure. Ecol. Lett. 18, 153–163 (2015).
Godoy, O., Kraft, N. J. B. & Levine, J. M. Phylogenetic relatedness and the determinants of competitive outcomes. Ecol. Lett. 17, 836–844 (2014).
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).
de Bello, F. et al. Handbook of Trait-Based Ecology: From Theory to R Tools (Cambridge Univ. Press, 2021).
Owen, N. R., Gumbs, R., Gray, C. L. & Faith, D. P. Global conservation of phylogenetic diversity captures more than just functional diversity. Nat. Commun. 10, 859 (2019).
Kraft, N. J. B. et al. Community assembly, coexistence and the environmental filtering metaphor. Funct. Ecol. 29, 592–599 (2015).
Zuo, X. et al. Functional diversity response to geographic and experimental precipitation gradients varies with plant community type. Funct. Ecol. 35, 2119–2132 (2021).
Massante, J. C. et al. Contrasting latitudinal patterns in phylogenetic diversity between woody and herbaceous communities. Sci. Rep. 9, 6443 (2019).
Cai, H. et al. Geographical patterns in phylogenetic diversity of Chinese woody plants and its application for conservation planning. Divers. Distrib. 27, 179–194 (2021).
Tietje, M. et al. Global hotspots of plant phylogenetic diversity. New Phytol. 240, 1636–1646 (2023).
Qian, H., Zhang, J. & Jiang, M. Global patterns of taxonomic and phylogenetic diversity of flowering plants: biodiversity hotspots and coldspots. Plant Divers. 45, 265–271 (2023).
De Pauw, K. et al. Taxonomic, phylogenetic and functional diversity of understorey plants respond differently to environmental conditions in European forest edges. J. Ecol. 109, 2629–2648 (2021).
Kambach, S. et al. Climate–trait relationships exhibit strong habitat specificity in plant communities across Europe. Nat. Commun. 14, 712 (2023).
Pryer, K. M. et al. Horsetails and ferns are a monophyletic group and the closest living relatives to seed plants. Nature 409, 618–622 (2001).
Rothfels, C. J. et al. The evolutionary history of ferns inferred from 25 low-copy nuclear genes. Am. J. Bot. 102, 1089–1107 (2015).
De Frenne, P. et al. Forest microclimates and climate change: importance, drivers and future research agenda. Glob. Change Biol. 27, 2279–2297 (2021).
Kovács, B., Tinya, F. & Ódor, P. Stand structural drivers of microclimate in mature temperate mixed forests. Agric. For. Meteorol. 234–235, 11–21 (2017).
Swenson, N. Phylogenetic resolution and quantifying the phylogenetic diversity and dispersion of communities. PLoS ONE 4, e4390 (2009).
Sessa, E. B. et al. Community assembly of the ferns of Florida. Am. J. Bot. 105, 549–564 (2018).
Kattge, J. et al. TRY plant trait database—enhanced coverage and open access. Glob. Change Biol. 26, 119–188 (2020).
Shan, H. et al. Gap filling in the plant kingdom: trait prediction using hierarchical probabilistic matrix factorization. Preprint at https://arxiv.org/abs/1206.6439 (2012).
Fazayeli, F., Banerjee, A., Kattge, J., Schrodt, F. & Reich, P. B. Uncertainty quantified matrix completion using bayesian hierarchical matrix factorization. In 2014 13th International Conference on Machine Learning and Applications (eds Chen, X.-w. et al.) 312–317 (IEEE, 2014).
Schrodt, F. et al. BHPMF—a hierarchical Bayesian approach to gap-filling and trait prediction for macroecology and functional biogeography. Glob. Ecol. Biogeogr. 24, 1510–1521 (2015).
Rao, C. R. Diversity and dissimilarity coefficients: a unified approach. Theor. Popul. Biol. 21, 24–43 (1982).
Laliberté, E. & Legendre, P. A distance-based framework for measuring functional diversity from multiple traits. Ecology 91, 299–305 (2010).
Laliberté, E., Legendre, P. & Shipley, B. FD: measuring functional diversity from multiple traits, and other tools for functional ecology. R package version 1.0-12 (2014).
Walker, A. P., McCormack, M. L., Messier, J., Myers-Smith, I. H. & Wullschleger, S. D. Trait covariance: the functional warp of plant diversity? New Phytol. 216, 976–980 (2017).
Kembel, S. W. et al. picante: integrating phylogenies and ecology. R package version 1.8.2 (2020).
Jin, Y. & Qian, H. V. PhyloMaker: an R package that can generate very large phylogenies for vascular plants. Ecography 42, 1353–1359 (2019).
Smith, S. A. & Brown, J. W. Constructing a broadly inclusive seed plant phylogeny. Am. J. Bot. 105, 302–314 (2018).
Zanne, A. E. et al. Three keys to the radiation of angiosperms into freezing environments. Nature 506, 89–92 (2014).
Qian, H. & Jin, Y. An updated megaphylogeny of plants, a tool for generating plant phylogenies and an analysis of phylogenetic community structure. J. Plant Ecol. 9, 233–239 (2016).
Revell, L. J. phytools: phylogenetic tools for comparative biology (and other things). R package version 2.1-1 (2023).
Letten, A. D. & Cornwell, W. K. Trees, branches and (square) roots: why evolutionary relatedness is not linearly related to functional distance. Methods Ecol. Evol. 6, 439–444 (2015).
de Bello, F., Carmona, C. P., Lepš, J., Szava-Kovats, R. & Pärtel, M. Functional diversity through the mean trait dissimilarity: resolving shortcomings with existing paradigms and algorithms. Oecologia 180, 933–940 (2016).
Petchey, O. L. & Gaston, K. J. Extinction and the loss of functional diversity. Proc. R. Soc. Lond. B 269, 1721–1727 (2002).
Cadotte, M. W. et al. Phylogenetic diversity metrics for ecological communities: integrating species richness, abundance and evolutionary history. Ecol. Lett. 13, 96–105 (2010).
Gotelli, N. J. & McCabe, D. J. Species co-occurrence: a meta-analysis of J. M. Diamond’s assembly rules model. Ecology 83, 2091–2096 (2002).
Schultz, J. The Ecozones of the World: The Ecological Division of the Geosphere (Springer Nature, 2005).
Karger, D. N. et al. Climatologies at high resolution for the Earth’s land surface areas. Sci. Data 4, 170122 (2017).
Karger, D. N. et al. Data from: Climatologies at high resolution for the Earth’s land surface areas. Dryad https://doi.org/10.5061/DRYAD.KD1D4 (2018).
Brown, S. C., Wigley, T. M. L., Otto-Bliesner, B. L. & Fordham, D. A. StableClim, continuous projections of climate stability from 21000 BP to 2100 CE at multiple spatial scales. Sci. Data 7, 335 (2020).
Renssen, H. & Isarin, R. F. B. The two major warming phases of the last deglaciation at ∼14.7 and ∼11.5 ka cal BP in Europe: climate reconstructions and AGCM experiments. Glob. Planet. Change 30, 117–153 (2001).
Hijmans, R. J. Raster: Geographic data analysis and modeling. R package version 3.6-30 (2023).
Wood, S. mgcv: Mixed GAM computation vehicle with automatic smoothness estimation. R package version 1.9-1 (2023).
Wood, S. N. Fast stable restricted maximum likelihood and marginal likelihood estimation of semiparametric generalized linear models. J. R. Stat. Soc. B 73, 3–36 (2011).
Wood, S. N. Stable and efficient multiple smoothing parameter estimation for generalized additive models. J. Am. Stat. Assoc. 99, 673–686 (2004).
Wood, S. N. Generalized Additive Models: An Introduction with R (Chapman and Hall/CRC, 2017).
Wood, S. N. Thin-plate regression splines. J. R. Stat. Soc. B 65, 95–114 (2003).
Wood, S. N., Pya, N. & Säfken, B. Smoothing parameter and model selection for general smooth models. J. Am. Stat. Assoc. 111, 1548–1563 (2016).
Hijmans, R. J., Phillips, S., Leathwick, J. & Elith, J. dismo: species distribution modeling. R package version 1.3-14 (2022).
Arel-Bundock, V. marginaleffects: predictions, comparisons, slopes, marginal means, and hypothesis tests. R package version 0.18.0 (2023).
R Core Team R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2022).
Hähn, G. J. A., Damasceno, G., Sabatini, F. M. & Bruelheide, H. Global decoupling of functional and phylogenetic diversity in plant communities (version 1.0). iDiv https://doi.org/10.25829/idiv.3574-mpmk21 (2024).
Acknowledgements
We are thankful for the efforts of thousands of vegetation scientists sampling and digitalizing vegetation data and making them available in regional, national or international databases. We appreciate the support of the German Research Foundation for funding sPlot as one of the iDiv research platforms (DFG FZT 118, 202548816). The scientific results have (in part) been computed at the High-Performance Computing Cluster EVE, a joint effort of both the Helmholtz Centre for Environmental Research—UFZ (http://www.ufz.de/) and the German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig (http://www.idiv-biodiversity.de/). We thank the administration and support staff of EVE who keep the system running and support us with our scientific computing needs: T. Schnicke, B. Langenberg, G. Schramm, T. Harzendorf, T. Strempel and L. Schurack from the UFZ and C. Krause from iDiv. We thank the iDiv Data & Code Unit for assistance with curation (done by L. Figueiredo) and archiving of the dataset. F.M.S. gratefully acknowledges financial support from the Rita Levi Montalcini (2019) programme, funded by the Italian Ministry of University and Research (MUR). J.-C.S. considers this work a contribution to Center for Ecological Dynamics in a Novel Biosphere (ECONOVO), funded by Danish National Research Foundation (grant no. DNRF173) and his VILLUM Investigator project ‘Biodiversity Dynamics in a Changing World’, funded by VILLUM FONDEN (grant no. 16549). V.D.P. received support from Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq, Brazil, grant no. 313315/2022-1). I.B. and J.A.C. were funded by the Basque Government (IT1487-22). A.D.B was supported by the Knut and Alice Wallenberg Foundation (WAF KAW 2019.0202) and the Swedish Foundation for Strategic Research (FFL21-0194). A.G.-d.-M. has been supported by National Forestry and Wildlife Service (SERFOR) of Peru (AUT-IFL-2023-017) and Fundación Universitaria San Pablo-CEU, grant nos. GNRI 2023 and GNRI 2024. A.Č., F.K. and U. Šilc were supported by the Slovenian Research and Innovation Agency (P1-0236).
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G.J.A.H., F.M.S. and H.B. conceived the idea. G.J.A.H. performed the analysis with substantial input from F.M.S., G.D. and H.B. G.J.A.H. drafted the first version of the paper with support by F.M.S., G.D., M. Sporbert and H.B. E.A.-D., I.A., M.B., E.B., I.B., A.D.B., G.B., Z.B.-D., J.A.C., A.Č., M.C., R.Ć., A.L.d.G, M.D.S., J. Dengler, J. Dolezal, M.A.E.-S., M.F., A.G.-d.-M., E.G., H.G., V.G., S.H., M.Z.H., B.H., J.H., U.J., F.J., A.J., J.K., M.K., L.K., H.K., F.K., J.L., J.E.M., L.M., A.N., J.N., A.P.-H., O.L.P., V.D.P., G.R.-T., E.R., B. Sandel, M. Schmidt, U.S., S.S., F.S., U.Š., B. Sparrow, M. Sporbert, Z.S., B. Strohbach, J.-C.S., C.Q.T., Z.T., A.C.V., C.V., D. Waller, D. Wana, H.-F.W., T.W. and G.Z. provided parts of the data. All co-authors edited the paper and provided suggestions on how to improve the analyses.
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Hähn, G.J.A., Damasceno, G., Alvarez-Davila, E. et al. Global decoupling of functional and phylogenetic diversity in plant communities. Nat Ecol Evol 9, 237–248 (2025). https://doi.org/10.1038/s41559-024-02589-0
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DOI: https://doi.org/10.1038/s41559-024-02589-0