Special Feature: Functional Diversity
Which trait dissimilarity for functional diversity: trait means or trait overlap?
Version of Record online: 2 AUG 2013
© 2012 International Association for Vegetation Science
Journal of Vegetation Science
Volume 24, Issue 5, pages 807–819, September 2013
How to Cite
de Bello, F., Carmona, C. P., Mason, N. W. H., Sebastià, M.-T., Lepš, J. (2013), Which trait dissimilarity for functional diversity: trait means or trait overlap?. Journal of Vegetation Science, 24: 807–819. doi: 10.1111/jvs.12008
- Issue online: 2 AUG 2013
- Version of Record online: 2 AUG 2013
- Manuscript Accepted: 25 SEP 2012
- Manuscript Received: 30 MAR 2012
- Grant Agency of the Czech Republic
- GACR. Grant Numbers: P505/12/1296, P505/12/1390
- FPI scholarship. Grant Number: BES-2008-009821
- Community assembly;
- Environmental filtering;
- Functional traits;
- Intraspecific trait variability;
- Niche complementarity;
Many functional diversity indices require the calculation of functional trait dissimilarities between species. However, very little is known about how the dissimilarity measure used might affect conclusions about ecological processes drawn from functional diversity.
We simulated real applications of functional diversity, to illustrate the key properties of the two most common families of dissimilarity measures: (1) ‘Gower’ distance, using only ‘mean trait’ value per species and then standardizing each trait, e.g. relative to its range; (2) ‘trait overlap’ between species, which takes into account within-species trait variability. We then examine how these approaches could affect conclusions about ecological processes commonly assessed with functional diversity. We also propose a new R function (‘trova’, i.e. TRait OVerlAp) which performs computations to estimate species trait dissimilarity with different types of data.
The trait overlap approach generally produces a less context-dependent measure of functional dissimilarity. For example, the results are less dependent on the transformation of trait data (often required in empirical datasets) and on the particular pool of species considered (i.e. trait range, regularity and presence of outliers). The results therefore could be more easily compared across studies and biomes. Further, trait overlap more reliably reproduces patterns expected when niche differentiation structures communities. The Gower approach, on the contrary, more reliably detects environmental filtering effects.
The two approaches imply different conceptions of how species dissimilarities relate to niche differentiation. Trait overlap is suitable for testing the effect of species interactions on functional diversity within local communities, especially when relatively small differences in species traits are linked to different resource acquisition. Gower is better suited to detecting changes in functional diversity along environmental gradients, as greater differences in trait values reflect increased niche differentiation. Combining trait overlap and Gower approaches may provide a novel way to assess the joint effects of environmental filtering and niche complementarity on community assembly. We suggest that attention should be given not only to the index of functional diversity considered but also whether the dissimilarity used is appropriate for the study context.