Including intraspecific trait variability to avoid distortion of functional diversity and ecological inference: Lessons from natural assemblages

Functional diversity assessments are crucial and increasingly used for understanding ecological processes and managing ecosystems. The functional diversity of a community is assessed by sampling traits at one or more scales (individuals, populations and species) and calculating a summary index of the variation in trait values. However, it remains unclear how the scales at which traits are sampled and the indices used to estimate functional diversity may alter the patterns observed and inferences about ecological processes. For 40 plant and 61 ant communities, we assess functional diversity using six methods—spanning various mean‐based and probabilistic methods—that reflect common scenarios where different levels of detail are available in trait data. We test whether including trait variability at different scales (from individuals to species) alters functional diversity values calculated using the volume‐based and dissimilarity‐based indices, Functional Richness (FRic) and Rao, respectively. We further test whether such effects alter functional diversity patterns observed across communities and their relationships with environmental drivers such as abiotic gradients and occurrences of invasive species. Intraspecific trait variability strongly determined FRic and Rao. Methods using only species' mean trait values to calculate FRic (convex hulls) and Rao (Gower‐based dissimilarity) distorted the patterns observed when intraspecific trait variability was considered. These distortions generated Type I and Type II errors for the effects of environmental factors structuring the plant and ant communities. A high sensitivity of FRic to individuals with extreme trait values was revealed in comparisons of different probabilistic methods including among‐individual and among‐population trait variability in functional diversity. In contrast, values of and ecological patterns in Rao were consistent among methods including different scales of intraspecific trait variability. Our results show empirically that decisions about where traits are sampled and how trait variability is included in functional diversity can drastically change the patterns observed and conclusions about ecological processes. We recommend sampling the traits of multiple individuals per species and capturing their intraspecific trait variability using probabilistic methods. We discuss how intraspecific trait variability can be reasonably estimated and included in functional diversity in the common cir