Papers in the Biological Sciences

 

Authors

C. E. Timothy Paine, University of StirlingFollow
Lucy Amissah, Wageningen University
Harald Auge, Helmholtz Center for Environmental Research
Christopher Baraloto, INRA, UMR
Martin Baruffol, University of Zurich
Nils Bourland, University of Liege
Helge Bruelheide, German Centre for Integrative Biodiversity Research
Kasso Dainou, University of Liege
Roland C. de Gouvenain, Rhode Island College
Jean-Louis Doucet, University of Liege
Susan Doust, Australian Antarctic Division
Paul V. A. Fine, University of California - Berkeley
Claire Fortunel, INRA, UMR
Josephine Haase, University of Freiburg
Karen D. Holl, University of California, Santa Cruz
Herve Jactel, INRA
Xuefei Li, University of Zurich
Kaoru Kitajima, Florida International University
Julia Koricheva, Royal Holloway, University of London
Cristina Martinez-Garza, Universidad Autonoma del Estado de Morelos
Christian Messier, Université du Québec à Montréal et Université du Québec en Outaouais
Alain Paquette, Université du Québec à Montréal
Christopher Philipson, Institute of Terrestrial Ecosystems
Daniel Piotto, Universidade Federal do Sul da Bahia
Lourens Poorter, Wageningen University
Juan M. Posada, Universidad del Rosario
Catherine Potvin, Smithsonian Tropical Research Institute
Kalle Rainio, University of Turku
Sabrina E. Russo, University of Nebraska - LincolnFollow
Mariacarmen Ruiz-Jaen, McGill University
Michael Scherer-Lorenzen, University of Freiburg
Campbell O. Webb, Arnold Arboretum of Harvard University
S. Joseph Wright, Smithsonian Tropical Research Institute
Rakan A. Zahawi, Las Cruces Biological Station
Andy Hector, University of Oxford

Date of this Version

2015

Citation

Journal of Ecology 2015, 103, 978–989

Comments

© 2015 The Authors.

doi: 10.1111/1365-2745.12401

Abstract

1. Plant functional traits, in particular specific leaf area (SLA), wood density and seed mass, are often good predictors of individual tree growth rates within communities. Individuals and species with high SLA, low wood density and small seeds tend to have faster growth rates. 2. If community-level relationships between traits and growth have general predictive value, then similar relationships should also be observed in analyses that integrate across taxa, biogeographic regions and environments. Such global consistency would imply that traits could serve as valuable proxies for the complex suite of factors that determine growth rate, and, therefore, could underpin a new generation of robust dynamic vegetation models. Alternatively, growth rates may depend more strongly on the local environment or growth–trait relationships may vary along environmental gradients. 3. We tested these alternative hypotheses using data on 27 352 juvenile trees, representing 278 species from 27 sites on all forested continents, and extensive functional trait data, 38% of which were obtained at the same sites at which growth was assessed. Data on potential evapotranspiration (PET), which summarizes the joint ecological effects of temperature and precipitation, were obtained from a global data base. 4. We estimated size-standardized relative height growth rates (SGR) for all species, then related them to functional traits and PET using mixed-effect models for the fastest growing species and for all species together. 5. Both the mean and 95th percentile SGR were more strongly associated with functional traits than with PET. PET was unrelated to SGR at the global scale. SGR increased with increasing SLA and decreased with increasing wood density and seed mass, but these traits explained only 3.1% of the variation in SGR. SGR–trait relationships were consistently weak across families and biogeographic zones, and over a range of tree statures. Thus, the most widely studied functional traits in plant ecology were poor predictors of tree growth over large scales. 6. Synthesis. We conclude that these functional traits alone may be unsuitable for predicting growth of trees over broad scales. Determining the functional traits that predict vital rates under specific environmental conditions may generate more insight than a monolithic global relationship can offer.

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