Target sample sizes of n = 40/group represent a compromise between sampling effort (e.g. scanning capacity) and the ability to detect small-to-moderate effect sizes at a power of 0.8 in the case of univariate analyses (Cohen’s d = 0.25). For multivariate analyses (e.g. principal components analyses), target sample sizes of n = 40 with 50–68 landmarks produce highly repeatable covariance matrices (average RV coefficient of a sample’s Procrustes-adjusted covariance matrix with 1000 covariance matrices derived from bootstrapped data > 0.99).