Environmental factors predict community functional composition in Amazonian forests
Version of Record online: 31 OCT 2013
© 2013 The Authors. Journal of Ecology © 2013 British Ecological Society
Journal of Ecology
Volume 102, Issue 1, pages 145–155, January 2014
How to Cite
Fortunel, C., Paine, C. E. T., Fine, P. V. A., Kraft, N. J. B., Baraloto, C. (2014), Environmental factors predict community functional composition in Amazonian forests. Journal of Ecology, 102: 145–155. doi: 10.1111/1365-2745.12160
- Issue online: 16 DEC 2013
- Version of Record online: 31 OCT 2013
- Accepted manuscript online: 28 AUG 2013 07:23AM EST
- Manuscript Accepted: 23 AUG 2013
- Manuscript Received: 30 NOV 2012
- NSF. Grant Number: DEB-0743103/0743800
- INRA Package
- Investissement d'Avenir
- Agence Nationale de la Recherche
- CEBA. Grant Number: ANR-10-LABX-0025
Table S1. Individual and species sampling in each plot in each habitat in French Guiana and Peru.
Table S2. List of the 800 studied species ordered alphabetically by family based on APG3 classification.
Table S3. Effect of environmental filtering on community-weighted and community-unweighted mean, range and variance for 15 leaf and wood traits in the 13 studied plots.
Table S4. Estimates of the best linear model between observed community-weighted and community-unweighted mean traits and environmental data across 13 plots.
Table S5. Model-averaged estimates of the best linear models between observed community-weighted and community-unweighted mean traits and environmental data across 13 plots.
Figure S1. Environmental filtering on community trait clouds integrating species abundances and built in leaf and wood dimensions.
Figure S2. Environmental filtering on community trait clouds integrating species presence–absence and built in leaf and wood dimensions.
Figure S3. Community-unweighted functional dissimilarity and environmental dissimilarity between plot pairs in French Guiana and Peru.
Figure S4. Calculation vs. prediction of community-weighted and community-unweighted mean traits in 61 plots.
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