Resolving environmental disputes: A statistical method for choosing among competing cluster models

The protection of whole assemblages of species requires that such assemblag es be identified in some nonarbitrary, quantitative manner. Clustering meth ods can be used to identify groups or clusters of observations (i.e., sites , transects, quadrats, etc.) on the basis of multivariate assemblage data, where each species is a variable. There are many kinds of cluster analyses, all potentially providing different outcomes, that is, different clusters of the multivariate observations. The wide choice of clustering methods and the necessarily subjective choice of which method and measure of similarit y to use for a particular data set. is problematic. It can lead (and has le d) to disputes about the way multivariate observations should be grouped, c ausing conflicts in making environmental decisions. We present a statistica l test for choosing among competing cluster models and demonstrate its use with a case in point. The method provides an objective way to discriminate among competing models in order to determine the model that best fits the a vailable data. Provided each party in a dispute identifies and articulates the cluster model it supports, the method can give a nonarbitrary judgment concerning the best model. This method provides an important tool for the r esolution of environmental disputes concerning the presence of a particular community at a particular place and time, which may be impacted by a propo sed development.