Abstract
- The metric of functional evenness FEve is an example of how approaches
to conceptualizing and measuring functional variability may go astray.
- The index of functional evenness FEve has critical conceptual and
practical drawbacks:
- 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.
- Very minor differences in even one pairwise distance can result in
very different values of FEve.
- 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.
- 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.
- 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.
- 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.