Laura Varone

Local homogeneity, in ecology, is the often undisclosed assumption that variability within populations is negligible or mostly distributed evenly. In large areas, this can lead to the aggregation of different populations without regard for their unique needs and characteristics, such as drought sensitivity and functional trait distributions. Here, we discuss whether this assumption can be justified, and we hypothesize that discerning the source of variation between plasticity and adaptation could be a feasible approach to formulate an informed decision. We test this hypothesis on plants, resorting to a common garden experiment to determine the source of variation of several plant functional traits at a local scale (~60 km) of three wild species: Quercus ilex , Pistacia lentiscus , and Cistus salviifolius . Individuals of each species were sourced from three key sites chosen along a local aridity gradient. Our approach led to the rejection of the local homogeneity assumption for Q. ilex and C. salviifolius at this scale due to the adaptive divergence observed among neighboring populations. This case study provides evidence that addressing local homogeneity can highlight diverging populations in a relatively simple way. We conclude that gathering empirical evidence on intraspecific variability is a feasible approach that can provide researchers with solid bases to decide whether to adopt the local homogeneity assumption or not.

In trait‐based ecology, phenotypic variation (PVar) is often quantified with measures expressing average differences between populations standardized in the range 0–1. However, these measures disregard the within‐population trait variability. In addition, some of them cannot be partitioned between populations. These aspects can either alter their interpretation or limit their applicability. To overcome these problems, we propose a new measure, the phenotypic dissimilarity (PhD) index, to quantify PVar between populations in scenarios of varying within‐population interindividual trait variability. PhD can also quantify within‐population PVar while accounting for intraindividual trait variability. Using simulated and real data, we show that using the PhD index becomes important when the within‐population trait variability is not negligible, as in all ecological studies. By accounting for within‐population trait variability, the PhD index does not overestimate PVar across an environmental gradient compared to other estimators. Traits inherently vary within species. Accounting for such variability is essential to understanding species’ phenotypic responses to environmental cues. The proposed PhD index will provide ecologists with a tool for quantifying PVar within species and compare it between species at different levels of biological organization. We provide an R function to calculate the PhD index.