Abstract
  1. The metric of functional evenness FEve is an example of how approaches to conceptualizing and measuring functional variability may go astray.
  2. The index of functional evenness FEve has critical conceptual and practical drawbacks:
  1. Different values of the FEve index for the same community can be obtained if the species have unequal species abundances; this result is highly likely if most of the traits are categorical.
  2. Very minor differences in even one pairwise distance can result in very different values of FEve.
  3. FEve uses only a fraction of the information contained in the matrix of species distances. Counterintuitively, this can cause very similar FEve scores for communities with substantially different patterns of species dispersal in trait space.
  4. FEve is a valid metric only if all species have exactly the same abundances. However, the meaning of FEve in such an instance is unclear as the purpose of the metric is to measure the variability of abundances in trait space.
  1. We recommend not using FEve metric in studies of functional variability. Given the wide usage of FEve index over the last decade, the validity of the conclusions based on those estimates are in question.
  2. Instead, we suggest three alternative metrics that combines variability in species distances in trait space with abundance in various ways, and more broadly recommend that researchers think about which community properties (e.g., trait-distances of a focus species to the nearest neighbor or all other species, variability of pairwise interactions between species) they want to measure and pick from among the appropriate metrics.
Functional trait variability is a component of biodiversity that for the species within a community measures variability in the traits that are assumed to play a role in organismal or ecosystem functions. Many aspects of ecosystem processes depend on the nature, distribution, and variation of organismal traits. Therefore, a proper assessment of functional trait variability is important, and numerous metrics and approaches have been developed since the 1990s to measure this key community attribute (many of them are listed in Scheiner, 2019).
Functional trait variability is a complex concept. To describe its different facets, Villéger, Mason, and Mouillot (2008) suggested three separate metrics: functional richness (FRic), functional evenness (FEve), and functional divergence (FDiv), which measure, respectively, the amount of trait space filled by the community, the evenness of species abundances as they are distributed in trait space, and how abundances are spread across trait space. Among the few commonly used approaches, these three metrics are some of the most complicated, but they are assumed to provide an exhaustive measure of functional variability within a community. Despite some criticisms of these indices, mainly focused on functional evenness (e.g. Ricotta, Bacaro, & Moretti, 2014; Legras & Gaertner, 2018), their usage has continually grown in recent years from 134 citations in 2015 to 288 in 2019, with a current total of over 1500 citations. In this paper, we demonstrate that functional evenness (FEve) has severe limitations in its applicability and interpretation. We concentrate on FEve as an example of how approaches to conceptualizing and measuring functional evenness may go astray.
A community can be characterized by its species and their abundances. Using additional information about those species, relationships among the species can be expressed in terms of pairwise distances, that in turn can be used to measure overall community variation. In particular, if each species is described by the same set of T traits (standardized trait values are assumed), a community of S species can be represented by S points in a T -dimensional trait space. While distances can be estimated with different metrics, relationships are completely predetermined by the species’ dispersion in the trait space. Functional trait diversity can be measured in a variety of ways; the differences in trait space among species can be measured using all pairwise distances, the mean distance of a given species from other species, or nearest-neighbor distances (Scheiner, 2019). Those distances can then be further weighted by the species abundances to provide a measure of abundance-weighted functional trait variation within this multi-trait space. FEve measures functional evenness based on abundance-weighted nearest-neighbor distances, so this metric might be relevant if the primary interactions within a community are among species that are most similar in trait values. While such types of interactions occur in many circumstances, there are many circumstances when this is not true for either species or types of interactions. However, the FEve metric has been widely used to analyze functional variation without consideration of the types of processes and entities being considered. We return to this issue in the final section of the paper when we discuss alternative measures of functional variation.