Squared euclidean distance: A statistical test to evaluate plant community change. Forest Service research note (Final)

The concepts and a procedure for evaluating plant community change using the squared Euclidean distance (SED) resemblance function are described. Analyses are based on the concept that Euclidean distances constitute a sample from a population of distances between sampling units (SUs) for a specific number of times and SUs. With different times, the distances will be intracluster or intercluster. Intercluster distances represent a control treatment. If the communities differ between times, the population will contain clusters (regions of high density with short distances between SUs) that are separated by regions of low density (great distances between SUs). Within- and between-years mean squares from analyses of variance for each species (sp) in the data matrix can be used to compute the intracluster and intercluster mean distances. A multivariate ANOVA gives a test of the hypothesis that the intracluster mean distance is equal to the intercluster mean distance at an overall error rate. The confidence intervals may be examined and a decision made regarding any indicated change in the community. A simple example is provided to permit study of computational methods.