Special Feature: Functional Diversity
Functional and phylogenetic community assembly linked to changes in species diversity in a long-term resource manipulation experiment
Article first published online: 2 AUG 2013
© 2013 International Association for Vegetation Science
Journal of Vegetation Science
Volume 24, Issue 5, pages 843–852, September 2013
How to Cite
Gerhold, P., Price, J. N., Püssa, K., Kalamees, R., Aher, K., Kaasik, A., Pärtel, M. (2013), Functional and phylogenetic community assembly linked to changes in species diversity in a long-term resource manipulation experiment. Journal of Vegetation Science, 24: 843–852. doi: 10.1111/jvs.12052
- Issue published online: 2 AUG 2013
- Article first published online: 2 AUG 2013
- Manuscript Accepted: 9 JAN 2013
- Manuscript Received: 5 APR 2012
- Estonian Science Foundation. Grant Numbers: 8039, 8323, 8613, SF0180119
- European Regional Development Fund (Center of Excellence FIBIR), European Social Fund through MOBILITAS post-doctoral grant. Grant Number: MJD47
- European Union 7th framework project SCALES. Grant Number: FP7-226852
Appendix S1. The relationship between the change in mean FD and PD in experimental plots from 2002 to 2011.
Appendix S2. A modified version of the function ´mpd´ (mean pair-wise distance) in package ´picante´ (v. 1.5-2) in R with the option ´abundance.weighted = TRUE´ which does not include the diagonal in the dissimilarity matrix between species (which is always 0), and is hence intrinsically independent of the number of species in the matrix.
Appendix S3. Raw data set of the number of experimental plots, net species gain and loss, the mean and SD of species diversity, FD and PD at the beginning and at the end of the experiment.
Appendix S4. Results of GLMM using Markov chain Monte Carlo techniques for the relationships between annual changes in species diversity (calculated as Simpson's reciprocal index; log-transformed) and annual changes in trait mean values in the experimental plots.
Appendix S5. Results of GLMM using Markov chain Monte Carlo techniques for the relationship between annual changes in species diversity and changes in the abundance of single species in the experimental plots.
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