Form or Shape? Examining the Effect of Size Adjustment on Evolutionary Analyses of Catarrhine Appendicular Morphology

Objective: Morphometric analyses of primate skeletal evolution frequently employ data scaling to reduce or eliminate the variable of size. However, multiple methods of scaling may be employed that may alter the variance–covariance (VCV) matrix describing relationships between traits. Here, we aim to better understand how different scaling methods may impact results of analyses using the VCV matrix by applying common scaling methods to a dataset and comparing results. Materials and Methods: 39 interlandmark distances from eight postcranial elements were taken from a sample of six primate species. Five datasets—raw, one log-scaled, two isometrically scaled, and one allometrically scaled—were then analyzed for matrix similarity, magnitude of integration, and whether trait covariation matched patterns expected under a model of purely neutral evolution. Results: Choice of scaling method employed may alter results of some analyses, or, when the impact of specific traits are considered, may alter which traits are most impactful to results. Inter- and intra-specific variation in size may drive these differences in results. Conclusion: Data scaling can impact the results of analyses using a VCV matrix, indicating that studies using different methodologies may not be reasonably comparable. While the choice of scaling method depends on the aims of the study, the method employed should be carefully considered prior to analysis. As primate body size varies across the phylogeny, applying multiple scaling methods could further our understanding of how size has impacted skeletal evolution, particularly in studies incorporating species with high intra- or interspecific body size variation.