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Abstract

Bringing together leaf trait data spanning 2,548 species and 175 sites we describe, for the first time at global scale, a universal spectrum of leaf economics consisting of key chemical, structural and physiological properties. The spectrum runs from quick to slow return on investments of nutrients and dry mass in leaves, and operates largely independently of growth form, plant functional type or biome. Categories along the spectrum would, in general, describe leaf economic variation at the global scale better than plant functional types, because functional types overlap substantially in their leaf traits. Overall, modulation of leaf traits and trait relationships by climate is surprisingly modest, although some striking and significant patterns can be seen. Reliable quantification of the leaf economics spectrum and its interaction with climate will prove valuable for modelling nutrient fluxes and vegetation boundaries under changing land-use and climate.

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Acknowledgements

All authors contributed (mostly unpublished) data and intellectual input to the project. The first three authors took the lead in the organization, analysis and writing-up of this work, and contributed 8% of the data, with 223 species from 11 sites. We also thank the many other researchers who provided additional information about their study sites and published data.

Author information

Affiliations

  1. Department of Biological Sciences, Macquarie University, New South Wales 2109, Australia

    • Ian J. Wright
    •  & Mark Westoby
  2. Department of Forest Resources, University of Minnesota, St Paul, Minnesota 55108, USA

    • Peter B. Reich
    •  & Jacek Oleksyn
  3. Department of Biological Sciences, Stanford University, Stanford, California 94305, USA

    • David D. Ackerly
  4. Departamento de Estudios Ambientales, Universidad Simón Bolivar, Caracas 1080, Venezuela

    • Zdravko Baruch
  5. Forest Ecology and Forest Management Group, Department of Environmental Sciences, Wageningen University, PO Box 342, 6700 AH Wageningen, The Netherlands

    • Frans Bongers
  6. Smithsonian Environmental Research Center, PO Box 28, 647 Contees Wharf Road, Edgewater, Maryland 21037, USA

    • Jeannine Cavender-Bares
  7. Institute of Arctic Biology, University of Alaska, Fairbanks, Alaska 99775, USA

    • Terry Chapin
  8. Institute of Ecological Science, Department of Systems Ecology, Vrije Universiteit, De Boelelaan 1087, 1081 HV, Amsterdam, The Netherlands

    • Johannes H. C. Cornelissen
  9. Institute für Umweltwissensch, University of Zurich, Zurich, Switzerland

    • Matthias Diemer
  10. Departament de Biologia, Laboratori de Fisiologia Vegetal, Universidad de Illes Balears, 07122 Palma de Mallorca, Illes Balears (Spain)

    • Jaume Flexas
    •  & Javier Gulias
  11. Centre d'Ecologie Fonctionnelle et Evolutive, CNRS, UMR 5175, 1919, Route de Mende, 34293 Montpellier cedex 5, France

    • Eric Garnier
    • , Marie-Laure Navas
    •  & Catherine Roumet
  12. Department of Environmental Biology, Curtin University of Technology, Perth, Western Australia 6845, Australia

    • Philip K. Groom
    •  & Byron B. Lamont
  13. Graduate School of Life Sciences, Tohoku University, Aoba, Sendai 980-8578, Japan

    • Kouki Hikosaka
  14. Department of Biology, University of Wisconsin-Eau Claire, Eau Claire, Wisconsin 54702-4004, USA

    • Tali Lee
  15. Landcare Research, Private Bag 1930, Dunedin, New Zealand

    • William Lee
  16. Departamento de Botánica, Universidad de Concepción, Casilla 160-C, Concepción, Chile

    • Christopher Lusk
  17. Department of Botany, University of Cape Town, ZA-7701 Rondebosch, South Africa

    • Jeremy J. Midgley
  18. Department of Plant Physiology, University of Tartu, Riia 23, Tartu 51011, Estonia

    • Ülo Niinemets
  19. Polish Academy of Sciences, Institute of Dendrology, Parkowa 5, 62-035 Kornik, Poland

    • Jacek Oleksyn
  20. Nikko Botanical Garden, Graduate School of Science, University of Tokyo, 1842 Hanaishi, Nikko, Tochigi 321-1435, Japan

    • Noriyuki Osada
  21. Plant Ecophysiology, Utrecht University, PO Box 800.84, 3508 TB, Utrecht, The Netherlands

    • Hendrik Poorter
  22. School of Plant Biology, University of Western Australia, Crawley, Western Australia 6009, Australia

    • Pieter Poot
    •  & Erik J. Veneklaas
  23. Key Centre for Tropical Wildlife Management, Charles Darwin University, Darwin, Northern Territory 0909, Australia

    • Lynda Prior
  24. Ural State University, Yekaterinburg, Russia

    • Vladimir I. Pyankov
  25. Faculty of Forestry, University of Toronto, 33 Willcocks St, Toronto, Ontario M5S 3B3, Canada

    • Sean C. Thomas
  26. Department of Forest Science, Texas A&M University, 2135 TAMU, College Station, Texas 77843-2135, USA

    • Mark G. Tjoelker
  27. Area de Ecología, Campus de Rabanales, Universidad de Córdoba, 14071 Córdoba, Spain

    • Rafael Villar

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Competing interests

The authors declare that they have no competing financial interests.

Corresponding author

Correspondence to Ian J. Wright.

Supplementary information

Word documents

  1. 1.

    Supplementary Information

    This consists of: 1. a list of published literature sources; 2. further details of bivariate trait relationships allowing formulation of predictive regression equations; 3. details of multiple regression analyses mentioned in the text; 4. PCA loadings for the area-based 5 trait analysis.

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    Supplementary Data

    Glopnet dataset

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DOI

https://doi.org/10.1038/nature02403

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