The global spectrum of plant form and function

Journal name:
Nature
Volume:
529,
Pages:
167–171
Date published:
DOI:
doi:10.1038/nature16489
Received
Accepted
Published online

Abstract

Earth is home to a remarkable diversity of plant forms and life histories, yet comparatively few essential trait combinations have proved evolutionarily viable in today’s terrestrial biosphere. By analysing worldwide variation in six major traits critical to growth, survival and reproduction within the largest sample of vascular plant species ever compiled, we found that occupancy of six-dimensional trait space is strongly concentrated, indicating coordination and trade-offs. Three-quarters of trait variation is captured in a two-dimensional global spectrum of plant form and function. One major dimension within this plane reflects the size of whole plants and their parts; the other represents the leaf economics spectrum, which balances leaf construction costs against growth potential. The global plant trait spectrum provides a backdrop for elucidating constraints on evolution, for functionally qualifying species and ecosystems, and for improving models that predict future vegetation based on continuous variation in plant form and function.

At a glance

Figures

  1. The volume in trait space occupied by vascular plant species is strongly constrained compared to theoretical null models.
    Figure 1: The volume in trait space occupied by vascular plant species is strongly constrained compared to theoretical null models.

    The five diagrams are pictorial representations based on three out of the six trait dimensions forming the hypervolumes under scrutiny. The hypervolumes are constructed on the basis of log10- and z-transformed observed values of H, SSD, LA, LMA, Nmass and SM (observed hypervolume = hvobs), or on the bases of four different null models of multivariate variation of those traits (hvnm1 to hvnm4) (see Methods). Numbers adjacent to arrows indicate percentage reductions in size of hvobs compared to the null-model hypervolumes (all significant at P < 0.001).

  2. The global spectrum of plant form and function.
    Figure 2: The global spectrum of plant form and function.

    a, Projection of global vascular plant species (dots) on the plane defined by principal component axes (PC) 1 and 2 (details in Extended Data Table 1 and Extended Data Fig. 2). Solid arrows indicate direction and weighing of vectors representing the six traits considered; icons illustrate low and high extremes of each trait vector. Circled numbers indicate approximate position of extreme poles of whole-plant specialisation, illustrated by typical species (Extended Data Table 2). The colour gradient indicates regions of highest (red) to lowest (white) occurrence probability of species in the trait space defined by PC1 and PC2, with contour lines indicating 0.5, 0.95 and 0.99 quantiles (see Methods, kernel density estimation). Red regions falling within the limits of the 0.50 occurrence probability correspond to the functional hotspots referred to in main text. b, c, location of different growth-forms (b) and major taxa (c) in the global spectrum.

  3. Climatic and geographical coverage of the dataset.
    Extended Data Fig. 1: Climatic and geographical coverage of the dataset.

    ad, Green points, occurrence according to GBIF (http://www.gbif.org) of species with information on all six traits (a, c) and at least one trait (b, d). Upper panels (a, b) show distribution in major climatic regions of the world; grey, MAP and MAT as in CRU0.5 degree climatology261; Biome classification according to ref. 262. Lower panels (c, d) show distribution in the global map (Robinson projection); grey, land surface. Maps based on the R package ‘maps’, accessed at The Comprehensive R Archive Network (https://cran.r-project.org/web/packages/maps/index.html).

  4. Tests of the distribution of growth-forms (a) and major taxa (b) in trait space.
    Extended Data Fig. 2: Tests of the distribution of growth-forms (a) and major taxa (b) in trait space.

    Woody and non-woody species differed significantly in their positions along PC1 but not along PC2. Angiosperms differed significantly from gymnosperms and pteridophytes in their positions along both axes; gymnosperms and pteridophytes differed in their position along PC1 but not along PC2 (see Methods for details of PCA analysis and a posteriori tests). Whiskers denote ± 3 s.d. from mean; n woody = 1,001; n non-woody = 1,209; n angiosperms = 2,120; n gymnosperms = 80; n pteridophytes = 14). Horizontal bars and dots within boxes indicate mean and median, respectively. Means with the same letter are not significantly different (Fisher’s least significant difference; P > 0.01).

  5. Selected bivariate relationships underlying the global spectrum of plant form and function, showing herbaceous (green) and woody (black) species separately.
    Extended Data Fig. 3: Selected bivariate relationships underlying the global spectrum of plant form and function, showing herbaceous (green) and woody (black) species separately.

    See Extended Data Fig. 4 for standardized major axes statistics (slope, r2, sample size) of these and all other pairwise trait combinations.

  6. Bivariate relationships between the six traits that underlie the global spectrum of plant form and function.
    Extended Data Fig. 4: Bivariate relationships between the six traits that underlie the global spectrum of plant form and function.

    The lower left portion of the matrix shows two-dimensional probability density distributions of bivariate trait relationships derived through kernel density estimation (see Methods). The colour gradient indicates regions of highest (red) to lowest (white) occurrence probability of trait combinations with contour lines indicating 0.5, 0.95 and 0.99 quantiles. The upper right portion contains standardized major axis (SMA)263 statistics (slope, r2, sample size n, and statistical significance, NS, P > 0.05; *0.05 > P > 0.01; **0.01 > P > 0.001; ***P < 0.001) for the corresponding relationships for all species (a), and for herbaceous (h) and woody species (w) separately. The diagonal displays the total sample sizes for each trait. For traits showing a strongly bimodal distribution, the all-species slope and correlation should be treated with caution. Pteridophytes show a discontinuous distribution in SM, but otherwise fall well within the general distribution of points; they represent less than 1% of the dataset, therefore including or excluding them does not significantly alter any of the relationships. SMAs were fitted using SMATR v.2 (http://www.bio.mq.edu.au/ecology/SMATR/).

Tables

  1. Principal component analyses (PCAs) of global plant trait data
    Extended Data Table 1: Principal component analyses (PCAs) of global plant trait data
  2. Description and illustrative examples of species at different positions at the margin of the global spectrum of plant form and function
    Extended Data Table 2: Description and illustrative examples of species at different positions at the margin of the global spectrum of plant form and function

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Affiliations

  1. Instituto Multidisciplinario de Biología Vegetal (IMBIV), CONICET and FCEFyN, Universidad Nacional de Córdoba, Casilla de Correo 495, 5000 Córdoba, Argentina

    • Sandra Díaz,
    • Valeria Falczuk &
    • Lucas D. Gorné
  2. Max Planck Institute for Biogeochemistry, Hans-Knöll-Straße 10, 07745 Jena, Germany

    • Jens Kattge,
    • Christian Wirth,
    • Gerhard Bönisch,
    • Julia S. Joswig,
    • Angela Günther &
    • Miguel D. Mahecha
  3. German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Deutscher Platz 5e, 04103 Leipzig, Germany

    • Jens Kattge,
    • Christian Wirth,
    • Nadja Rüger &
    • Miguel D. Mahecha
  4. Systems Ecology, Department of Ecological Science, Vrije Universiteit, De Boelelaan 1085, 1081 HV Amsterdam, The Netherlands

    • Johannes H. C. Cornelissen
  5. Department of Biological Sciences, Macquarie University, Sydney, New South Wales 2109, Australia

    • Ian J. Wright,
    • I. Colin Prentice &
    • Mark Westoby
  6. Laboratoire d’Ecologie Alpine, UMR 5553, CNRS – Université Grenoble Alpes, 38041 Grenoble Cedex 9, France

    • Sandra Lavorel
  7. Laboratoire de Biométrie et Biologie Evolutive, UMR5558, Université Lyon 1, CNRS, F-69622 Villeurbanne, France

    • Stéphane Dray
  8. Institute of Biology, University of Leipzig, Johannisallee 21, 04103 Leipzig, Germany

    • Björn Reu
  9. Escuela de Biología, Universidad Industrial de Santander, Cra. 27 Calle 9, 680002 Bucaramanga, Colombia

    • Björn Reu
  10. Landscape Ecology Group, Institute of Biology and Environmental Sciences, University of Oldenburg, D-26111 Oldenburg, Germany

    • Michael Kleyer
  11. Department of Systematic Botany and Functional Biodiversity, University of Leipzig, Johannisallee 21, 04103 Leipzig, Germany

    • Christian Wirth
  12. AXA Chair in Biosphere and Climate Impacts, Grand Challenges in Ecosystems and the Environment and Grantham Institute – Climate Change and the Environment, Department of Life Sciences, Imperial College London, Silwood Park Campus, Buckhurst Road, Ascot SL5 7PY, UK

    • I. Colin Prentice
  13. Centre d’Ecologie Fonctionnelle et Evolutive (UMR 5175), CNRS-Université de Montpellier - Université Paul-Valéry Montpellier - EPHE, 34293 Montpellier Cedex 5, France

    • Eric Garnier
  14. Plant Sciences (IBG-2), Forschungszentrum Jülich GmbH, D-52425 Jülich, Germany

    • Hendrik Poorter
  15. Department of Forest Resources, University of Minnesota, St Paul, Minnesota 55108, USA

    • Peter B. Reich
  16. Hawkesbury Institute for the Environment, University of Western Sydney, Penrith New South Wales 2751, Australia

    • Peter B. Reich
  17. Evolution & Ecology Research Centre, School of Biological, Earth and Environmental Sciences, UNSW Australia, Sydney, New South Wales 2052, Australia

    • Angela T. Moles
  18. Collections , The Royal Botanic Gardens Kew, Wakehurst Place, Ardingly, West Sussex, RH17 6TN, UK

    • John Dickie
  19. Center for Biodiversity Management, P.O. Box 120, Yungaburra, Queensland 4884, Australia

    • Andrew N. Gillison
  20. Department of Biological Sciences, George Washington University, Washington DC 20052, USA

    • Amy E. Zanne
  21. Center for Conservation and Sustainable Development, Missouri Botanical Garden, St Louis, Missouri 63121, USA

    • Amy E. Zanne
  22. UMR 5174 Laboratoire Evolution et Diversité Biologique, CNRS & Université Paul Sabatier, Toulouse 31062, France

    • Jérôme Chave
  23. Smithsonian Tropical Research Institute, Apartado 0843-03092, Balboa, Ancón, Panama

    • S. Joseph Wright &
    • Nadja Rüger
  24. Komarov Botanical Institute, Prof. Popov Street 2, St Petersburg 197376, Russia

    • Serge N. Sheremet’ev
  25. INRA, UMR1202 BIOGECO, F-33610 Cestas, France

    • Hervé Jactel
  26. Université de Bordeaux, BIOGECO, UMR 1202, F-33600 Pessac, France

    • Hervé Jactel
  27. International Center for Tropical Botany, Department of Biological Sciences, Florida International University, Miami, Florida 33199, USA

    • Christopher Baraloto
  28. INRA, UMR Ecologie des Forêts de Guyane, 97310 Kourou, French Guiana

    • Christopher Baraloto
  29. Department of Theoretical and Applied Sciences, University of Insubria, Via J.H. Dunant 3, I-21100 Varese, Italy

    • Bruno Cerabolini
  30. Department of Agricultural and Environmental Sciences (DiSAA), University of Milan, Via G. Celoria 2, I-20133 Milan, Italy

    • Simon Pierce
  31. Département de biologie, Université de Sherbrooke, Sherbrooke, Quebec J1K 2R1, Canada

    • Bill Shipley
  32. Biodiversity Informatics and Spatial Analysis, Jodrell Building, The Royal Botanic Gardens Kew, Richmond TW9 3AB, UK

    • Donald Kirkup
  33. Unidad de Bioestadística, Centro Agronómico Tropical de Investigación y Enseñanza (CATIE), 7170 Turrialba, 30501, Costa Rica

    • Fernando Casanoves

Contributions

Order in list of authors reflects overall participation in this article. S.Di., J.K. and S.L. designed the study. S.Di., J.K., J.H.C.C., I.J.W., S.L., M.K., C.W., E.G., I.C.P , M.W., H.P., P.B.R., A.T.M., J.D, A.N.G., A.E.Z., J.C., S.J.W., S.N.S., H.J., C.B., B.C., S.P., B. S. and D.K. contributed substantial amounts of data. S.Di., J.K., G.B., A.G. and V.F. constructed the database. S.Di., J.K., J.H.C.C., I.J.W., S.L., S.Dr., B.R., M.K., C.W., E.G., F.C., J.S.J., N.R., M.D.M. and L.D.G. carried out analyses. S.Di., J.K., J.H.C.C., I.J.W., S.L., M.K., C.W., I.C.P., M.W. and P.B.R. wrote the article with contributions from S.Dr., B.R., E.G., H.P., A.T.M., J.D., A.N.G., A.E.Z., J.C., S.J.W., S.N.S., H.J., C.B., B.C., S.P., B.S., DK, F.C., M.D.M. and L.D.G.

Competing financial interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to:

Author details

Extended data figures and tables

Extended Data Figures

  1. Extended Data Figure 1: Climatic and geographical coverage of the dataset. (379 KB)

    ad, Green points, occurrence according to GBIF (http://www.gbif.org) of species with information on all six traits (a, c) and at least one trait (b, d). Upper panels (a, b) show distribution in major climatic regions of the world; grey, MAP and MAT as in CRU0.5 degree climatology261; Biome classification according to ref. 262. Lower panels (c, d) show distribution in the global map (Robinson projection); grey, land surface. Maps based on the R package ‘maps’, accessed at The Comprehensive R Archive Network (https://cran.r-project.org/web/packages/maps/index.html).

  2. Extended Data Figure 2: Tests of the distribution of growth-forms (a) and major taxa (b) in trait space. (62 KB)

    Woody and non-woody species differed significantly in their positions along PC1 but not along PC2. Angiosperms differed significantly from gymnosperms and pteridophytes in their positions along both axes; gymnosperms and pteridophytes differed in their position along PC1 but not along PC2 (see Methods for details of PCA analysis and a posteriori tests). Whiskers denote ± 3 s.d. from mean; n woody = 1,001; n non-woody = 1,209; n angiosperms = 2,120; n gymnosperms = 80; n pteridophytes = 14). Horizontal bars and dots within boxes indicate mean and median, respectively. Means with the same letter are not significantly different (Fisher’s least significant difference; P > 0.01).

  3. Extended Data Figure 3: Selected bivariate relationships underlying the global spectrum of plant form and function, showing herbaceous (green) and woody (black) species separately. (315 KB)

    See Extended Data Fig. 4 for standardized major axes statistics (slope, r2, sample size) of these and all other pairwise trait combinations.

  4. Extended Data Figure 4: Bivariate relationships between the six traits that underlie the global spectrum of plant form and function. (540 KB)

    The lower left portion of the matrix shows two-dimensional probability density distributions of bivariate trait relationships derived through kernel density estimation (see Methods). The colour gradient indicates regions of highest (red) to lowest (white) occurrence probability of trait combinations with contour lines indicating 0.5, 0.95 and 0.99 quantiles. The upper right portion contains standardized major axis (SMA)263 statistics (slope, r2, sample size n, and statistical significance, NS, P > 0.05; *0.05 > P > 0.01; **0.01 > P > 0.001; ***P < 0.001) for the corresponding relationships for all species (a), and for herbaceous (h) and woody species (w) separately. The diagonal displays the total sample sizes for each trait. For traits showing a strongly bimodal distribution, the all-species slope and correlation should be treated with caution. Pteridophytes show a discontinuous distribution in SM, but otherwise fall well within the general distribution of points; they represent less than 1% of the dataset, therefore including or excluding them does not significantly alter any of the relationships. SMAs were fitted using SMATR v.2 (http://www.bio.mq.edu.au/ecology/SMATR/).

Extended Data Tables

  1. Extended Data Table 1: Principal component analyses (PCAs) of global plant trait data (133 KB)
  2. Extended Data Table 2: Description and illustrative examples of species at different positions at the margin of the global spectrum of plant form and function (345 KB)

Supplementary information

PDF files

  1. Supplementary Information (136 KB)

    This file contains links to Supplementary Applications 1 and 2 and Supplementary Tables 1-2.

Additional data