COS 84-7
A global, cross-taxa review of how we measure functional diversity

Wednesday, August 12, 2015: 3:40 PM
323, Baltimore Convention Center
Pamela L. Reynolds, Department of Environmental Science and Policy, University of California, Davis, CA
Marissa R. Lee, University Program in Ecology, Duke University, Durham, NC
Monica Granados, Department of Biology, McGill University, Montreal, QC, Canada
Kes Schroer, Neukom Institute for Computational Sciences, Dartmouth College
Background/Question/Methods

Functional diversity is increasingly recognized as an important dimension of biodiversity because of its links to ecosystem functioning, but researchers must make a number of difficult decisions about how to quantify functional diversity in their system. At a minimum, researchers must decide which traits to include, how many traits to include, and which diversity metric(s) to use to synthesize trait values. We conducted a systematic review of functional diversity measures across systems and taxa using Web of Science, Scopus, Google Scholar and Boolean search terms for “functional diversity” to a) determine whether there is consensus in the literature on how to calculate functional diversity and b) evaluate where ecosystem-specific and taxa-specific discrepancies in methodology occur. 

Results/Conclusions

Based on more than 120 studies, 5 traits and 50 species are the median number of traits and species, respectively, that researchers use to calculate functional diversity.  The most common metric for calculating functional diversity is Rao’s Q. While we found a large increase in the number of studies that measured functional diversity in the past 20 years, the majority of these studies have been conducted in terrestrial grasslands and located in either the US or China. Moreover, a paucity of functional diversity research exists where species richness is globally highest. By identifying how researchers measure functional diversity and the systems that are studied, this review illuminates which locations, systems, and taxa inform our understanding of functional diversity and highlights where gaps in our understanding exist.