Most methods of multivariate analysis rely on a measure of proximity between individualcases or samples to quantify inter-sample differences. The choice of this measure is fundamental tothe method and its subsequent results. For example, when data are abundance counts of a set ofspecies at several sampling locations, some approaches rely on the Bray-Curtis dissimilaritymeasure between samples, while other approaches rely on the chi-square distance. A set ofobserved species abundances at a location has both size, in the form of the overall levels of thespecies counts, and shape, in the form of the relative values of the counts. The aim of this report isto clarify how much the chosen proximity measure is capturing differences in size between samplesas opposed to differences in shape. After motivating the idea using physical morphometric data, thestudy is extended to nonnegative data in general, with special focus on abundance counts andbiomass estimates, which are ubiquitous in ecological research.