An updated framework to account for inter-individual variability when quantifying phenotypic variation

In trait-based ecology, phenotypic variation (PVar) is often quantified with measures that express average differences between populations standardized in the range 0-1. A major problem with these measures is that they disregard the within-population trait variability. In addition, most of these measures cannot be decomposed across scales. This can alter their interpretation, thus limiting their applicability. To overcome these problems, we propose a new measure, the Phenotypic Dissimilarity Index (PhD) that is insensitive to the within-population interindividual trait variability. Likewise, PhD can be used to quantify PVar between individuals in a population while accounting for the PVar within individuals. Using simulated and real data, we showed that PhD index correctly quantifies PVar when the within-population trait variability is not negligible, as in many ecological studies. By accounting for within-population trait variability, the PhD index generally provides a more parsimonious quantification of PVar across an environmental gradient compared to other estimators. Traits sampled within a species have an inherent variability. Accounting for such variability is essential to understand species phenotypic responses to environmental cues. As such, the PhD index will provide ecologists with an asset to reliably quantify and compare PVar within and between species across environmental gradients at different scales. We also provide an R function to calculate the PhD index.