HOW DO DIFFERENT MEASURES OF FUNCTIONAL DIVERSITY PERFORM?

TLDR

Biodiversity influences ecosystem functioning by altering resource‑use complementarity among species, and functional diversity metrics aim to quantify this complementarity to explain and predict ecosystem performance. The study compares the explanatory power of four functional diversity measures—species richness, functional group richness, functional attribute diversity, and FD—and demonstrates novel methods for computing the latter two. The authors evaluate the calculation methods for functional attribute diversity and FD, focusing on how to select the information used and discussing the opportunities and limitations of these approaches. Species richness and functional group richness explain the least variation in aboveground biomass, whereas functional attribute diversity and FD explain more, likely because they incorporate more information and fewer assumptions.

Abstract

Biodiversity can influence ecosystem functioning through changes in the amount of resource use complementary among species. Functional diversity is a measure of biodiversity that aims to quantify resource use complementarity and thereby explain and predict ecosystem functioning. The primary goal of this article is to compare the explanatory power of four measures of functional diversity: species richness, functional group richness, functional attribute diversity, and FD. The secondary goal is to showcase the novel methods required for calculating functional attribute diversity and FD. We find that species richness and functional group richness explain the least variation in aboveground biomass production within and across grassland biodiversity manipulations at six European locations; functional attribute diversity and FD explain greater variation. Reasons for differences in explanatory power are discussed, such as the relatively greater amount of information and fewer assumptions included in functional attribute diversity and FD. We explore the opportunities and limitations of the particular methods we used to calculate functional attribute diversity and FD. These mainly concern how best to select the information used to calculate them.