Plant functional traits have globally consistent effects on competition

Abstract

Phenotypic traits and their associated trade-offs have been shown to have globally consistent effects on individual plant physiological functions1,2,3, but how these effects scale up to influence competition, a key driver of community assembly in terrestrial vegetation, has remained unclear4. Here we use growth data from more than 3 million trees in over 140,000 plots across the world to show how three key functional traits—wood density, specific leaf area and maximum height—consistently influence competitive interactions. Fast maximum growth of a species was correlated negatively with its wood density in all biomes, and positively with its specific leaf area in most biomes. Low wood density was also correlated with a low ability to tolerate competition and a low competitive effect on neighbours, while high specific leaf area was correlated with a low competitive effect. Thus, traits generate trade-offs between performance with competition versus performance without competition, a fundamental ingredient in the classical hypothesis that the coexistence of plant species is enabled via differentiation in their successional strategies5. Competition within species was stronger than between species, but an increase in trait dissimilarity between species had little influence in weakening competition. No benefit of dissimilarity was detected for specific leaf area or wood density, and only a weak benefit for maximum height. Our trait-based approach to modelling competition makes generalization possible across the forest ecosystems of the world and their highly diverse species composition.

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Figure 1: Assessing competitive interactions at global scale.
Figure 2: Trait-dependent and trait-independent effects on maximum growth and competition across the globe, and their variation among biomes.
Figure 3: Variation of maximum growth, competitive effects and competitive tolerance with wood density and SLA predicted by global traits models.

References

  1. 1

    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. Evol. Syst. 33, 125–159 (2002)

    Google Scholar 

  2. 2

    Wright, I. J. et al. The worldwide leaf economics spectrum. Nature 428, 821–827 (2004)

    ADS  CAS  Google Scholar 

  3. 3

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

    PubMed  Google Scholar 

  4. 4

    Keddy, P. A. Competition (Springer Netherlands, 1989)

  5. 5

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

    CAS  PubMed  Google Scholar 

  6. 6

    Adler, P. B., Fajardo, A., Kleinhesselink, A. R. & Kraft, N. J. B. Trait-based tests of coexistence mechanisms. Ecol. Lett. 16, 1294–1306 (2013)

    Google Scholar 

  7. 7

    MacArthur, R. & Levins, R. The limiting similarity, convergence, and divergence of coexisting species. Am. Nat. 101, 377–385 (1967)

    Google Scholar 

  8. 8

    Uriarte, M. et al. Trait similarity, shared ancestry and the structure of neighbourhood interactions in a subtropical wet forest: implications for community assembly. Ecol. Lett. 13, 1503–1514 (2010)

    PubMed  Google Scholar 

  9. 9

    Kunstler, G. et al. Competitive interactions between forest trees are driven by species’ trait hierarchy, not phylogenetic or functional similarity: implications for forest community assembly. Ecol. Lett. 15, 831–840 (2012)

    PubMed  PubMed Central  Google Scholar 

  10. 10

    HilleRisLambers, J., Adler, P., Harpole, W., Levine, J. & Mayfield, M. Rethinking community assembly through the lens of coexistence theory. Annu. Rev. Ecol. Evol. Syst. 43, 227–248 (2012)

    Google Scholar 

  11. 11

    Lasky, J. R., Uriarte, M., Boukili, V. K. & Chazdon, R. L. Trait-mediated assembly processes predict successional changes in community diversity of tropical forests. Proc. Natl Acad. Sci. USA 111, 5616–5621 (2014)

    ADS  CAS  PubMed  Google Scholar 

  12. 12

    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)

    ADS  CAS  Google Scholar 

  13. 13

    Mayfield, M. M. & Levine, J. M. Opposing effects of competitive exclusion on the phylogenetic structure of communities: phylogeny and coexistence. Ecol. Lett. 13, 1085–1093 (2010)

    PubMed  Google Scholar 

  14. 14

    Kraft, N. J. B., Crutsinger, G. M., Forrestel, E. J. & Emery, N. C. Functional trait differences and the outcome of community assembly: an experimental test with vernal pool annual plants. Oikos 123, 1391–1399 (2014)

    Google Scholar 

  15. 15

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

    PubMed  Google Scholar 

  16. 16

    Goldberg, D. E. Competitive ability: definitions, contingency and correlated traits. Phil. Trans. R. Soc. Lond. B 351, 1377–1385 (1996)

    ADS  Google Scholar 

  17. 17

    Gaudet, C. L. & Keddy, P. A. A comparative approach to predicting competitive ability from plant traits. Nature 334, 242–243 (1988)

    ADS  Google Scholar 

  18. 18

    Kattge, J. et al. TRY – a global database of plant traits. Glob. Change Biol. 17, 2905–2935 (2011)

    ADS  Google Scholar 

  19. 19

    Uriarte, M., Canham, C. D., Thompson, J. & Zimmerman, J. K. A neighborhood analysis of tree growth and survival in a hurricane-driven tropical forest. Ecol. Monogr. 74, 591–614 (2004)

    Google Scholar 

  20. 20

    Poorter, L. et al. Are functional traits good predictors of demographic rates? Evidence from five neotropical forests. Ecology 89, 1908–1920 (2008)

    CAS  PubMed  Google Scholar 

  21. 21

    Poorter, L., Bongers, L. & Bongers, F. Architecture of 54 moist-forest tree species: traits, trade-offs, and functional groups. Ecology 87, 1289–1301 (2006)

    PubMed  Google Scholar 

  22. 22

    Aiba, M. & Nakashizuka, T. Architectural differences associated with adult stature and wood density in 30 temperate tree species. Funct. Ecol. 23, 265–273 (2009)

    Google Scholar 

  23. 23

    Niinemets, Ü. A review of light interception in plant stands from leaf to canopy in different plant functional types and in species with varying shade tolerance. Ecol. Res. 25, 693–714 (2010)

    Google Scholar 

  24. 24

    Adams, T. P., Purves, D. W. & Pacala, S. W. Understanding height-structured competition in forests: is there an R* for light? Proc. R. Soc. B 274, 3039–3047 (2007)

    PubMed  Google Scholar 

  25. 25

    Sapijanskas, J., Paquette, A., Potvin, C., Kunert, N. & Loreau, M. Tropical tree diversity enhances light capture through crown plasticity and spatial and temporal niche differences. Ecology 95, 2479–2492 (2014)

    Google Scholar 

  26. 26

    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 

  27. 27

    Bagchi, R. et al. Pathogens and insect herbivores drive rainforest plant diversity and composition. Nature 506, 85–88 (2014)

    ADS  CAS  PubMed  Google Scholar 

  28. 28

    Wang, P., Stieglitz, T., Zhou, D. W. & Cahill, J. F. Jr. Are competitive effect and response two sides of the same coin, or fundamentally different? Funct. Ecol. 24, 196–207 (2010)

    Google Scholar 

  29. 29

    Canham, C. D. et al. Neighborhood analyses of canopy tree competition along environmental gradients in New England forests. Ecol. Appl. 16, 540–554 (2006)

    PubMed  Google Scholar 

  30. 30

    Rüger, N., Wirth, C., Wright, S. J. & Condit, R. Functional traits explain light and size response of growth rates in tropical tree species. Ecology 93, 2626–2636 (2012)

    PubMed  Google Scholar 

  31. 31

    Schielzeth, H. Simple means to improve the interpretability of regression coefficients: Interpretation of regression coefficients. Methods Ecol. Evol. 1, 103–113 (2010)

    Google Scholar 

  32. 32

    Bates, D., Maechler, M., Bolker, B. & Walker, S. Fitting linear mixed-effects models using lme4. J. Stat. Soft. 67, 1–48 (2014)

    Google Scholar 

  33. 33

    R Development Core Team. R: A Language and Environment for Statistical Computing http://www.R-project.org/ (R Foundation for Statistical Computing, 2014)

  34. 34

    Kriticos, D. J. et al. CliMond: global high-resolution historical and future scenario climate surfaces for bioclimatic modelling. Methods Ecol. Evol. 3, 53–64 (2012)

    Google Scholar 

  35. 35

    Connell, J. H. On the prevalence and relative importance of interspecific competition: Evidence from field experiments. Am. Nat. 122, 661–696 (1983)

    Google Scholar 

  36. 36

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

    Google Scholar 

  37. 37

    Chesson, P. in Ecological Systems (ed. Leemans, R. ) 223–256 (Springer, 2012)

  38. 38

    Godoy, O. & Levine, J. M. Phenology effects on invasion success: insights from coupling field experiments to coexistence theory. Ecology 95, 726–736 (2014)

    PubMed  Google Scholar 

  39. 39

    IGN Inventaire Forestier; http://inventaire-forestier.ign.fr/spip/spip.php?rubrique153

  40. 40

    Kooyman, R., Rossetto, M., Allen, C. & Cornwell, W. Australian tropical and subtropical rain forest community assembly: phylogeny, functional biogeography, and environmental gradients. Biotropica 44, 668–679 (2012)

    Google Scholar 

  41. 41

    New Zealand National Vegetation Survey Databank; https://nvs.landcareresearch.co.nz/

  42. 42

    Wiser, S. K., Bellingham, P. J. & Burrows, L. E. Managing biodiversity information: development of New Zealand’s National Vegetation Survey databank. N. Z. J. Ecol. 25, 1–17 (2001)

    Google Scholar 

  43. 43

    Ministerio de Agricultura, Alimentación y Medio Ambiente. Inventario Forestal Nacional; http://www.magrama.gob.es/es/desarrollo-rural/temas/politica-forestal/inventario-cartografia/inventario-forestal-nacional/default.aspx

  44. 44

    Villaescusa, R. & Diaz, R. Segundo Inventario Forestal Nacional (1986–1996) (Ministerio de Medio Ambiente, 1998)

  45. 45

    Villanueva, J. Tercer Inventario Forestal Nacional (1997–2007) (Ministerio de Medio Ambiente, 2004)

  46. 46

    Fridman, J. & Stahl, G. A three-step approach for modelling tree mortality in swedish forests. Scand. J. For. Res. 16, 455–466 (2001)

    Google Scholar 

  47. 47

    Swiss National Forest Inventory (NFI); http://www.lfi.ch/index-en.php

  48. 48

    USDA Forest Inventory and Analysis National Program; http://www.fia.fs.fed.us/tools-data/

  49. 49

    Condit, R., Engelbrecht, B. M. J ., Pino, D., Perez, R. & Turner, B. L. Species distributions in response to individual soil nutrients and seasonal drought across a community of tropical trees. Proc. Natl Acad. Sci. USA 110, 5064–5068 (2013)

    ADS  CAS  PubMed  Google Scholar 

  50. 50

    Condit, R., Hubbell, S. P. & Foster, R. B. Mortality and growth of a commercial hardwood ‘el cativo’, Prioria copaifera, in Panama. For. Ecol. Manage. 62, 107–122 (1993)

    Google Scholar 

  51. 51

    Lasky, J. R., Sun, I., Su, S.-H., Chen, Z.-S. & Keitt, T. H. Trait-mediated effects of environmental filtering on tree community dynamics. J. Ecol. 101, 722–733 (2013)

    Google Scholar 

  52. 52

    Ishihara, M. I. et al. Forest stand structure, composition, and dynamics in 34 sites over japan. Ecol. Res. 26, 1007–1008 (2011)

    Google Scholar 

  53. 53

    Thompson, J. et al. Land use history, environment, and tree composition in a tropical forest. Ecol. Appl. 12, 1344–1363 (2002)

    Google Scholar 

  54. 54

    Ouédraogo, D.-Y., Mortier, F., Gourlet-Fleury, S., Freycon, V. & Picard, N. Slow-growing species cope best with drought: evidence from long-term measurements in a tropical semi-deciduous moist forest of Central Africa. J. Ecol. 101, 1459–1470 (2013)

    Google Scholar 

  55. 55

    Herault, B., Ouallet, J., Blanc, L., Wagner, F. & Baraloto, C. Growth responses of neotropical trees to logging gaps. J. Appl. Ecol. 47, 821–831 (2010)

    Google Scholar 

  56. 56

    Hérault, B. et al. Functional traits shape ontogenetic growth trajectories of rain forest tree species. J. Ecol. 99, 1431–1440 (2011)

    Google Scholar 

  57. 57

    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 

  58. 58

    Ricklefs, R. E. The Economy of Nature (WH Freeman, 2001)

  59. 59

    Whittaker, R. H. Communities and Ecosystems (Macmillan, 1970)

  60. 60

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

    PubMed  Google Scholar 

  61. 61

    Gourlet-Fleury, S. et al. Environmental filtering of dense-wooded species controls above-ground biomass stored in African moist forests. J. Ecol. 99, 981–990 (2011)

    Google Scholar 

  62. 62

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

    PubMed  Google Scholar 

  63. 63

    Ackerly, D. D. & Cornwell, W. K. A trait-based approach to community assembly: partitioning of species trait values into within- and among-community components. Ecol. Lett. 10, 135–145 (2007)

    CAS  Google Scholar 

  64. 64

    Castro-Díez, P., Puyravaud, J., Cornelissen, J. & Villar-Salvador, P. Stem anatomy and relative growth rate in seedlings of a wide range of woody plant species and types. Oecologia 116, 57–66 (1998)

    ADS  PubMed  Google Scholar 

  65. 65

    Cornelissen, J. An experimental comparison of leaf decomposition rates in a wide range of temperate plant species and types. J. Ecol. 84, 573–582 (1996)

    Google Scholar 

  66. 66

    Cornelissen, J., Diez, P. C. & Hunt, R. Seedling growth, allocation and leaf attributes in a wide range of woody plant species and types. J. Ecol. 84, 755–765 (1996)

    Google Scholar 

  67. 67

    Cornelissen, J., Werger, M., Castro-Diez, P., Van Rheenen, J. & Rowland, A. Foliar nutrients in relation to growth, allocation and leaf traits in seedlings of a wide range of woody plant species and types. Oecologia 111, 460–469 (1997)

    ADS  CAS  PubMed  Google Scholar 

  68. 68

    Cornelissen, J. et al. Leaf digestibility and litter decomposability are related in a wide range of subarctic plant species and types. Funct. Ecol. 18, 779–786 (2004)

    Google Scholar 

  69. 69

    Cornelissen, J. et al. Functional traits of woody plants: correspondence of species rankings between field adults and laboratory-grown seedlings? J. Veg. Sci. 14, 311–322 (2003)

    Google Scholar 

  70. 70

    Cornwell, W. K. & Ackerly, D. D. Community assembly and shifts in plant trait distributions across an environmental gradient in coastal California. Ecol. Monogr. 79, 109–126 (2009)

    Google Scholar 

  71. 71

    Cornwell, W. K., Schwilk, L. D. W. & Ackerly, D. D. A trait-based test for habitat filtering: convex hull volume. Ecology 87, 1465–1471 (2006)

    PubMed  Google Scholar 

  72. 72

    Cornwell, W., Bhaskar, R., Sack, L. & Cordell, S. Adjustment of structure and function of Hawaiian Metrosideros polymorpha at high vs. low precipitation. Funct. Ecol. 21, 1063–1071 (2007)

    Google Scholar 

  73. 73

    Cornwell, W. K. et al. Plant species traits are the predominant control on litter decomposition rates within biomes worldwide. Ecol. Lett. 11, 1065–1071 (2008)

    PubMed  Google Scholar 

  74. 74

    Diaz, S. et al. The plant traits that drive ecosystems: evidence from three continents. J. Veg. Sci. 15, 295–304 (2004)

    Google Scholar 

  75. 75

    Fonseca, C. R., Overton, J. M., Collins, B. & Westoby, M. Shifts in trait-combinations along rainfall and phosphorus gradients. J. Ecol. 88, 964–977 (2000)

    Google Scholar 

  76. 76

    Fortunel, C. et al. Leaf traits capture the effects of land use changes and climate on litter decomposability of grasslands across Europe. Ecology 90, 598–611 (2009)

    PubMed  Google Scholar 

  77. 77

    Freschet, G. T., Cornelissen, J. H., Van Logtestijn, R. S. & Aerts, R. Evidence of the ‘plant economics spectrum’ in a subarctic flora. J. Ecol. 98, 362–373 (2010)

    Google Scholar 

  78. 78

    Freschet, G. T., Cornelissen, J. H., van Logtestijn, R. S. & Aerts, R. Substantial nutrient resorption from leaves, stems and roots in a subarctic flora: what is the link with other resource economics traits? New Phytol. 186, 879–889 (2010)

    CAS  PubMed  Google Scholar 

  79. 79

    Garnier, E. et al. Assessing the effects of land-use change on plant traits, communities and ecosystem functioning in grasslands: a standardized methodology and lessons from an application to 11 European sites. Ann. Bot. (Lond.) 99, 967–985 (2007)

    ADS  Google Scholar 

  80. 80

    Green, W. USDA PLANTS compilation, version 1, 09-02-02; http://bricol.net/downloads/data/PLANTSdatabase/ (2009)

  81. 81

    Han, W., Fang, J., Guo, D. & Zhang, Y. Leaf nitrogen and phosphorus stoichiometry across 753 terrestrial plant species in China. New Phytol. 168, 377–385 (2005)

    CAS  PubMed  Google Scholar 

  82. 82

    He, J.-S. et al. A test of the generality of leaf trait relationships on the Tibetan Plateau. New Phytol. 170, 835–848 (2006)

    PubMed  Google Scholar 

  83. 83

    He, J.-S. et al. Leaf nitrogen: phosphorus stoichiometry across Chinese grassland biomes. Oecologia 155, 301–310 (2008)

    ADS  PubMed  Google Scholar 

  84. 84

    Hoof, J., Sack, L., Webb, D. T. & Nilsen, E. T. Contrasting structure and function of pubescent and glabrous varieties of Hawaiian Metrosideros polymorpha (Myrtaceae) at high elevation. Biotropica 40, 113–118 (2008)

    Google Scholar 

  85. 85

    Kattge, J., Knorr, W., Raddatz, T. & Wirth, C. Quantifying photosynthetic capacity and its relationship to leaf nitrogen content for global-scale terrestrial biosphere models. Glob. Change Biol. 15, 976–991 (2009)

    ADS  Google Scholar 

  86. 86

    Kleyer, M. et al. The LEDA traitbase: a database of life-history traits of the Northwest European flora. J. Ecol. 96, 1266–1274 (2008)

    Google Scholar 

  87. 87

    Kurokawa, H. & Nakashizuka, T. Leaf herbivory and decomposability in a malaysian tropical rain forest. Ecology 89, 2645–2656 (2008)

    PubMed  Google Scholar 

  88. 88

    Laughlin, D. C., Leppert, J. J., Moore, M. M. & Sieg, C. H. A multi-trait test of the leaf-height-seed plant strategy scheme with 133 species from a pine forest flora. Funct. Ecol. 24, 493–501 (2010)

    Google Scholar 

  89. 89

    Martin, R. E., Asner, G. P. & Sack, L. Genetic variation in leaf pigment, optical and photosynthetic function among diverse phenotypes of Metrosideros polymorpha grown in a common garden. Oecologia 151, 387–400 (2007)

    ADS  PubMed  Google Scholar 

  90. 90

    McDonald, P., Fonseca, C., Overton, J. & Westoby, M. Leaf-size divergence along rainfall and soil-nutrient gradients: is the method of size reduction common among clades? Funct. Ecol. 17, 50–57 (2003)

    Google Scholar 

  91. 91

    Medlyn, B. E. et al. Effects of elevated [CO2] on photosynthesis in European forest species: a meta-analysis of model parameters. Plant Cell Environ. 22, 1475–1495 (1999)

    CAS  Google Scholar 

  92. 92

    Medlyn, B. E. & Jarvis, P. G. Design and use of a database of model parameters from elevated [CO2] experiments. Ecol. Modell. 124, 69–83 (1999)

    CAS  Google Scholar 

  93. 93

    Medlyn, B. et al. Stomatal conductance of forest species after long-term exposure to elevated CO2 concentration: a synthesis. New Phytol. 149, 247–264 (2001)

    Google Scholar 

  94. 94

    Messier, J., McGill, B. J. & Lechowicz, M. J. How do traits vary across ecological scales? A case for trait-based ecology. Ecol. Lett. 13, 838–848 (2010)

    PubMed  Google Scholar 

  95. 95

    Moles, A. T. et al. Factors that shape seed mass evolution. Proc. Natl Acad. Sci. USA 102, 10540–10544 (2005)

    ADS  CAS  PubMed  Google Scholar 

  96. 96

    Moles, A. T. et al. A brief history of seed size. Science 307, 576–580 (2005)

    ADS  CAS  PubMed  Google Scholar 

  97. 97

    Moles, A. T., Falster, D. S., Leishman, M. R. & Westoby, M. Small-seeded species produce more seeds per square metre of canopy per year, but not per individual per lifetime. J. Ecol. 92, 384–396 (2004)

    Google Scholar 

  98. 98

    Niinemets, Ü. Global-scale climatic controls of leaf dry mass per area, density, and thickness in trees and shrubs. Ecology 82, 453–469 (2001)

    Google Scholar 

  99. 99

    Niinemets, Ü. Research review. components of leaf dry mass per area–thickness and density–alter leaf photosynthetic capacity in reverse directions in woody plants. New Phytol. 144, 35–47 (1999)

    Google Scholar 

  100. 100

    Ogaya, R. & Peñuelas, J. Experimental drought in a holm oak forest: different photosynthetic response of the two dominant species, Quercus ilex and Phillyrea latifolia. Environ. Exp. Bot. 50, 137–148 (2003)

    Google Scholar 

  101. 101

    Ogaya, R. & Penuelas, J. Contrasting foliar responses to drought in Quercus ilex and Phillyrea latifolia. Biol. Plant. 50, 373–382 (2006)

    Google Scholar 

  102. 102

    Ogaya, R. & Peñuelas, J. Tree growth, mortality, and above-ground biomass accumulation in a holm oak forest under a five-year experimental field drought. Plant Ecol. 189, 291–299 (2007)

    Google Scholar 

  103. 103

    Ogaya, R. & Peñuelas, J. Tree growth, mortality, and above-ground biomass accumulation in a holm oak forest under a five-year experimental field drought. Plant Ecol. 189, 291–299 (2007)

    Google Scholar 

  104. 104

    Onoda, Y. et al. Global patterns of leaf mechanical properties. Ecol. Lett. 14, 301–312 (2011)

    PubMed  Google Scholar 

  105. 105

    Ordoñez, J. C. et al. Plant strategies in relation to resource supply in mesic to wet environments: does theory mirror nature? Am. Nat. 175, 225–239 (2010)

    PubMed  Google Scholar 

  106. 106

    Ordoñez, J. C. et al. Leaf habit and woodiness regulate different leaf economy traits at a given nutrient supply. Ecology 91, 3218–3228 (2010)

    PubMed  Google Scholar 

  107. 107

    Pakeman, R. J. et al. Impact of abundance weighting on the response of seed traits to climate and land use. J. Ecol. 96, 355–366 (2008)

    Google Scholar 

  108. 108

    Pakeman, R. J., Lepš, J., Kleyer, M., Lavorel, S. & Garnier, E. Relative climatic, edaphic and management controls of plant functional trait signatures. J. Veg. Sci. 20, 148–159 (2009)

    Google Scholar 

  109. 109

    Peñuelas, J. et al. Faster returns on ‘leaf economics’ and different biogeochemical niche in invasive compared with native plant species. Glob. Change Biol. 16, 2171–2185 (2010)

    ADS  Google Scholar 

  110. 110

    Peñuelas, J. et al. Higher allocation to low cost chemical defenses in invasive species of Hawaii. J. Chem. Ecol. 36, 1255–1270 (2010)

    PubMed  Google Scholar 

  111. 111

    Poorter, L. & Bongers, F. Leaf traits are good predictors of plant performance across 53 rain forest species. Ecology 87, 1733–1743 (2006)

    PubMed  Google Scholar 

  112. 112

    Poorter, L. Leaf traits show different relationships with shade tolerance in moist versus dry tropical forests. New Phytol. 181, 890–900 (2009)

    PubMed  Google Scholar 

  113. 113

    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)

    PubMed  Google Scholar 

  114. 114

    Preston, K. A., Cornwell, W. K. & DeNoyer, J. L. Wood density and vessel traits as distinct correlates of ecological strategy in 51 California coast range angiosperms. New Phytol. 170, 807–818 (2006)

    PubMed  Google Scholar 

  115. 115

    Pyankov, V. I., Kondratchuk, A. V. & Shipley, B. Leaf structure and specific leaf mass: the alpine desert plants of the Eastern Pamirs, Tadjikistan. New Phytol. 143, 131–142 (1999)

    Google Scholar 

  116. 116

    Quested, H. M. et al. Decomposition of sub-arctic plants with differing nitrogen economies: a functional role for hemiparasites. Ecology 84, 3209–3221 (2003)

    Google Scholar 

  117. 117

    Reich, P. B. et al. Scaling of respiration to nitrogen in leaves, stems and roots of higher land plants. Ecol. Lett. 11, 793–801 (2008)

    PubMed  Google Scholar 

  118. 118

    Reich, P. B., Oleksyn, J. & Wright, I. J. Leaf phosphorus influences the photosynthesis–nitrogen relation: a cross-biome analysis of 314 species. Oecologia 160, 207–212 (2009)

    ADS  PubMed  Google Scholar 

  119. 119

    Sack, L. Responses of temperate woody seedlings to shade and drought: do trade-offs limit potential niche differentiation? Oikos 107, 110–127 (2004)

    Google Scholar 

  120. 120

    Sack, L., Tyree, M. T. & Holbrook, N. M. Leaf hydraulic architecture correlates with regeneration irradiance in tropical rainforest trees. New Phytol. 167, 403–413 (2005)

    PubMed  Google Scholar 

  121. 121

    Sack, L., Melcher, P. J., Liu, W. H., Middleton, E. & Pardee, T. How strong is intracanopy leaf plasticity in temperate deciduous trees? Am. J. Bot. 93, 829–839 (2006)

    PubMed  Google Scholar 

  122. 122

    Sardans, J., Peñuelas, J. & Ogaya, R. Drought-induced changes in C and N stoichiometry in a Quercus ilex Mediterranean forest. For. Sci. 54, 513–522 (2008)

    Google Scholar 

  123. 123

    Sardans, J., Peñuelas, J., Prieto, P. & Estiarte, M. Changes in Ca, Fe, Mg, Mo, Na, and S content in a Mediterranean shrubland under warming and drought. J. Geophys. Res. 113, G03039 (2008)

    ADS  Google Scholar 

  124. 124

    Shipley, B. & Vu, T.-T. Dry matter content as a measure of dry matter concentration in plants and their parts. New Phytol. 153, 359–364 (2002)

    Google Scholar 

  125. 125

    Soudzilovskaia, N. A. et al. Functional traits predict relationship between plant abundance dynamic and long-term climate warming. Proc. Natl Acad. Sci. USA 110, 18180–18184 (2013)

    ADS  CAS  PubMed  Google Scholar 

  126. 126

    Willis, C. G. et al. Phylogenetic community structure in minnesota oak savanna is influenced by spatial extent and environmental variation. Ecography 33, 565–577 (2010)

    Google Scholar 

  127. 127

    Wilson, K. B., Baldocchi, D. D. & Hanson, P. J. Spatial and seasonal variability of photosynthetic parameters and their relationship to leaf nitrogen in a deciduous forest. Tree Physiol. 20, 565–578 (2000)

    PubMed  Google Scholar 

  128. 128

    Wright, I. J. et al. Relationships among ecologically important dimensions of plant trait variation in seven neotropical forests. Ann. Bot. (Lond.) 99, 1003–1015 (2007)

    Google Scholar 

  129. 129

    Wright, I. J. et al. Irradiance, temperature and rainfall influence leaf dark respiration in woody plants: evidence from comparisons across 20 sites. New Phytol. 169, 309–319 (2006)

    CAS  PubMed  Google Scholar 

  130. 130

    Zanne, A. E. et al. Angiosperm wood structure: global patterns in vessel anatomy and their relation to wood density and potential conductivity. Am. J. Bot. 97, 207–215 (2010)

    PubMed  Google Scholar 

  131. 131

    South, A. rworldmap. a new r package for mapping global data. Rem. J. 3, 35–43 (2011)

    Google Scholar 

  132. 132

    Nakagawa, S. & Hanson, P. J. A general and simple method for obtaining R2 from generalized linear mixed-effects models. Methods Ecol. Evol. 4, 133–142 (2013)

    Google Scholar 

  133. 133

    Johnson, P. C. D. Extension of Nakagawa and Schielzeth’s R2GLMM to random slopes models. Methods Ecol. Evol. 5, 944–946 (2014)

    PubMed  PubMed Central  Google Scholar 

  134. 134

    Burnham, K. P. & Anderson, D. R. Model Selection and Multimodel Inference: a Practical Information-Theoretic Approach (Springer-Verlag, 2002)

Download references

Acknowledgements

We are especially grateful to the researchers whose long-term commitment to establish and maintain forest plots and their associated databases made this study possible, and to those who granted us data access: forest inventories and permanent plots of New Zealand, Spain (MAGRAMA), France, Switzerland, Sweden, US and Canada (for the provinces of Quebec provided by the Ministère des Ressources Naturelles du Québec, Ontario provided by OnTAP’s Growth and Yield Program of the Ontario Ministry of Natural Resources, Saskatchewan, Manitoba, New Brunswick, Newfoundland and Labrador), CTFS (BCI and LTER-Luquillo), Taiwan (Fushan), Cirad (Paracou with funding by CEBA, ANR-10-LABX-25-01), Cirad, MEFCP and ICRA (M’Baïki) and Japan. We thank MPI-BGC Jena, who host TRY, and the international funding networks supporting TRY (IGBP, DIVERSITAS, GLP, NERC, QUEST, FRB and GIS Climate). G.K. was supported by a Marie Curie International Outgoing Fellowship within the 7th European Community Framework Program (Demo-Traits project, no. 299340). The working group that initiated this synthesis was supported by Macquarie University and by Australian Research Council through a fellowship to M.W.

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Contributions

G.K. and M.W. conceived the study, and with D.F. led a workshop with the participation of D.A.C., F.H., R.M.K., D.C.L., L.P., M.V., G.V. and S.J.W. G.K. wrote the manuscript with key inputs from all workshop participants and help from all authors. G.K., D.F. and F.H. wrote the computer code and processed the data. G.K. devised the main analytical approach and performed analyses with assistance from D.F. for the figures. G.K., D.A.C., D.F., F.H., R.M.K., D.C.L., M.V., G.V., S.J.W., M.A., C.B., J.C., J.H.C.C., S.G.-F., M.H., B.H., J.K., H.K., Y.O., J.P., H.P., M.U., S.R., P.R.-B., I.-F.S., G.S., N.G.S., J.T., B.W., C.W., M.A.Z., H.Z., J.K.Z. and N.E.Z. collected and processed the raw data.

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Correspondence to Georges Kunstler.

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The authors declare no competing financial interests.

Extended data figures and tables

Extended Data Figure 1 Map of the plot locations of all data sets analysed.

LPP plots are represented with a large points and NFI plots with small points (the Panama data set comprises both a 50 ha plot and a network of 1 ha plots). The world map is from the R package rworldmap131 using Natural Earth data.

Extended Data Figure 2 Average difference between interspecific and intraspecific competition predicted with estimates of trait-independent and trait-dependent processes influencing competition for models fitted for each trait.

ac, Models were fitted for wood density (a), SLA (b) or maximum height (c). The average differences between interspecific and intraspecific competition are influenced by α0intra, α0inter and αd coefficients (see Methods for details). Negative values indicate that intraspecific competition is stronger than interspecific competition.

Extended Data Figure 3 Variation of trait-independent inter and intraspecific competition, trait dissimilarity (|tf − tc| × αd), competitive effect (tc × αe), tolerance to competition (tf × αt) and maximum growth (tf × m1) with wood density, SLA and maximum height.

ao, Wood density (ae), SLA (fj) and maximum height (ko). Trait varied from their quantile at 5% to their quantile at 95%. The shaded area represents the 95% confidence interval of the prediction (including uncertainty associated with α0 or m0). α0intra and α0inter, which do not vary with traits, are represented with their associated confidence intervals.

Extended Data Figure 4 Trait-dependent and trait-independent effects on maximum growth and competition across the globe and their variation among biomes for models without separation of α0 between intra and interspecific competition for wood density, SLA and maximum height.

a, Wood density. b, SLA. c, Maximum height. See Fig. 2 in the main text for parameters description, and see Fig. 1a in the main text for biome definition.

Extended Data Table 1 Standardized coefficient estimates from models fitted for each trait
Extended Data Table 2 Trees data description
Extended Data Table 3 Traits data description
Extended Data Table 4 Species traits pairwise correlations

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Kunstler, G., Falster, D., Coomes, D. et al. Plant functional traits have globally consistent effects on competition. Nature 529, 204–207 (2016). https://doi.org/10.1038/nature16476

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