Special Feature: Functional Diversity
A guide for using functional diversity indices to reveal changes in assembly processes along ecological gradients
Article first published online: 20 NOV 2012
© 2013 International Association for Vegetation Science
Journal of Vegetation Science
Volume 24, Issue 5, pages 794–806, September 2013
How to Cite
Mason, N. W.H., de Bello, F., Mouillot, D., Pavoine, S., Dray, S. (2013), A guide for using functional diversity indices to reveal changes in assembly processes along ecological gradients. Journal of Vegetation Science, 24: 794–806. doi: 10.1111/jvs.12013
- Issue published online: 2 AUG 2013
- Article first published online: 20 NOV 2012
- Manuscript Accepted: 24 SEP 2012
- Manuscript Received: 29 MAR 2012
- Environmental filtering;
- Functional divergence;
- Functional evenness;
- Functional richness;
- Functional trait;
- Limiting similarity;
- Niche complementarity;
- Null models;
- Species richness
Which functional diversity indices have the power to reveal changes in community assembly processes along abiotic stress gradients? Is their power affected by stochastic processes and variations in species richness along stress gradients?
We used a simple community assembly model to explore the power of functional diversity indices across a wide range of ecological contexts. The model assumes that with declining stress the influence of niche complementarity on species fitness increases while that of environmental filtering decreases. We separately incorporated two trait-independent stochastic processes – mass and priority effects – in simulating species occurrences and abundances along a hypothetical stress gradient. We ran simulations where species richness was constant along the gradient, or increased, decreased or varied randomly with declining stress. We compared observed values for two indices of functional richness – total functional dendrogram length (FD) and convex hull volume (FRic) – with a matrix-swap null model (yielding indices SESFD and SESFRic) to remove any trivial effects of species richness. We also compared two indices that measure both functional richness and functional divergence – Rao quadratic entropy (Rao) and functional dispersion (FDis) – with a null model that randomizes abundances across species but within communities. This converts them to pure measures of functional divergence (SESRao and SESFDis).
When mass effects operated, only SESRao and SESFDis gave reasonable power, irrespective of how species richness varied along the stress gradient. FD, FRic, Rao and FDis had low power when species richness was constant, and variation in species richness greatly influenced their power. SESFRic and SESFD were unaffected by variation in species richness. When priority effects operated, FRic, SESFRic, Rao and FDis had good power and were unaffected by variation in species richness. Variation in species richness greatly affected FD and SESFD. SESRao and SESFDis had low power in the priority effects model but were unaffected by variation in species richness.
Our results demonstrate that a reliable test for changes in assembly processes along stress gradients requires functional diversity indices measuring either functional richness or functional divergence. We recommend using SESFRic as a measure of functional richness and either SESRao or SESFDis (which are very closely related mathematically) as a measure of functional divergence. Used together, these indices of functional richness and functional divergence provide good power to test for increasing niche complementarity with declining stress across a broad range of ecological contexts.