Nonmetric multidimensional scaling (MDS, also NMDS and NMS) is an ordination technique that differs in several ways from nearly all other ordination methods. In most ordination methods, many axes are calculated, but only a few are viewed, owing to graphical limitations. In MDS, a small number of axes are explicitly chosen prior to the analysis and the data are fitted to those dimensions; there are no hidden axes of variation. Second, most other ordination methods are analytical and therefore result in a single unique solution to a set of data. In contrast, MDS is a numerical technique that iteratively seeks a solution and stops computation when an acceptable solution has been found, or it stops after some pre-specified number of attempts. As a result, an MDS ordination is not a unique solution and a subsequent MDS analysis on the same set of data and following the same methodology will likely result in a somewhat different ordination. Third, MDS is not an eigenvalue-eigenvector technique like principal components analysis or correspondence analysis that ordinates the data such that axis 1 explains the greatest amount of variance, axis 2 explains the next greatest amount of variance, and so on. As a result, an MDS ordination can be rotated, inverted, or centered to any desired configuration. … Nonmetric Multi-Dimensional Scaling (NMDS)