Code and data from: Measuring the overall functional diversity by aggregating its multiple facets: functional richness, biomass evenness, trait evenness, and dispersion

Human activities induce environmental changes, which can affect
individuals' traits and then lead to changes in functional diversity
and finally in ecosystem functioning. Measuring functional diversity is
thus of utmost importance to understand the consequences of such
activities on ecosystem functioning. Functional diversity is composed of
several facets, but these facets are almost always measured individually
and we lack a metric capturing the overall, multifaceted functional
diversity. We consequently developed an index K of the overall
functional diversity defined as the geometric mean of four independent
facets: functional richness (the classic measure of the coverage over the
trait axis), biomass evenness, and trait evenness (quantifying how evenly
filled the biomass and trait distributions, separately) and dispersion
(quantifying the spread around the biomass-weighted mean trait, which is
maximised for uniform and bimodal distributions). K and each of its
underlying facets take values between 0 and 1 and assume the uniform
distribution to yield maximal diversity. We compared K to other, more
classic metrics measuring a single facet of functional diversity by
calculating all these indices for randomly and non-randomly generated
communities. We showed that K overcomes several limitations of other
indices (e.g. lack of accuracy, not computable for simple communities,
unclear ecological interpretation), and was well correlated with ecosystem
functions in simulated predator-prey communities. In addition, decomposing
K into its underlying facets revealed that ecosystem functions can be
driven by different facets of K on different trophic levels. The
strength of our index K lies in being the only index that measures the
overall functional diversity by combining several facets and providing the
option to decompose K into them. This notably yields mechanistic insights
about which facets are more important for driving changes in functional
diversity and ecosystem functioning.