Technical Abstract: Distance-based methods have been a valuable tool for ecologists for decades. Ordination and cluster analysis in particular have been widely practiced because they allow the visualization of a multivariate dataset in a few dimensions. The Mantel test and its relatives add hypothesis testing to the distance-based toolbox, but no information is available on when to combine data vectors into a single multivariate dissimilarity or when to treat them independently. For Euclidean distances on scaled data, the correlation of a pair of multivariate distance matrices can be calculated from the correlations between the two sets of individual distance matrices, demonstrating a clear link between univariate and multivariate distances. This relationship also provides a means for understanding the maximum possible value of the Mantel statistic, which can be considerably less than 1 for a given analysis. Scaling of the data, whether standardization or other means, is an essential component of any dissimilarity analysis where multiple variables are used to calculate one coefficient.