Abstract
The functional diversity of a community can influence ecosystem functioning and reflects assembly processes. The large number of disparate metrics used to quantify functional diversity reflects the range of attributes underlying this concept, generally summarized as functional richness, functional evenness, and functional divergence. However, in practice, we know very little about which attributes drive which ecosystem functions, due to a lack of field-based tests. Here we test the association between eight leading functional diversity metrics (Rao’s Q, FD, FDis, FEve, FDiv, convex hull volume, and species and functional group richness) that emphasize different attributes of functional diversity, plus 11 extensions of these existing metrics that incorporate heterogeneous species abundances and trait variation. We assess the relationships among these metrics and compare their performances for predicting three key ecosystem functions (above- and belowground biomass and light capture) within a long-term grassland biodiversity experiment. Many metrics were highly correlated, although unique information was captured in FEve, FDiv, and dendrogram-based measures (FD) that were adjusted by abundance. FD adjusted by abundance outperformed all other metrics in predicting both above- and belowground biomass, although several others also performed well (e.g. Rao’s Q, FDis, FDiv). More generally, trait-based richness metrics and hybrid metrics incorporating multiple diversity attributes outperformed evenness metrics and single-attribute metrics, results that were not changed when combinations of metrics were explored. For light capture, species richness alone was the best predictor, suggesting that traits for canopy architecture would be necessary to improve predictions. Our study provides a comprehensive test linking different attributes of functional diversity with ecosystem function for a grassland system.
Highlights
Functional diversity, commonly referred to as the value, range, and distribution of functional traits of organisms in a community [1,2], is hypothesized to reflect many processes in community and ecosystem ecology
The question becomes, and the one which we focus on in this study, which attribute(s) of functional diversity has a stronger influence on which ecosystem processes and under which conditions [26]? Mason et al (2005) suggested that functional diversity can be generally deconstructed into three components: functional richness, functional evenness, and functional divergence
Associations among Predictors All metrics except functional divergence (FDiv), FEve, FDabun, and FDcv.abun tended to be highly correlated with other metrics, and all except FDabun and FDcv.abun were significantly correlated with species richness
Summary
Functional diversity, commonly referred to as the value, range, and distribution of functional traits of organisms in a community [1,2], is hypothesized to reflect many processes in community and ecosystem ecology. Research over the past decade has considerably advanced the field, with at least 10 traitbased functional diversity metrics being proposed far (reviewed in [13,14,15]). These include the unadjusted sum (Functional Attribute Diversity, FAD; [16]) or average [17] of pair-wise distances between species in trait-space (functional dissimilarity), the abundance-weighted variance in traits using multiple traits (Rao’s quadratic entropy, Q; [18,19]), the abundance-weighted variance of traits using a single trait (FDvar; [20]), the regularity of trait distribution (Functional Regularity Index, FRO; [21]), the sum of branch lengths following cluster analysis of traits in a community (FD,; [22]), the volume of trait space occupied (Convex Hull Volume, Hull; [23]), the evenness of the abundance distribution in the minimum spanning tree linking all species (FEve, [24]), the divergence of abundance distributions relative to the community centroid (FDiv, [24]), as well as the mean distance of species from the community centroid after adjusting for abundances (FDis, [25])
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