This chapter will be concerned with the applications of multivariate analysis. First, general recommendations will be given for community ecology applications regarding data editing in preparation for multivariate analysis and selecting multivariate techniques appropriate for a given data set and purpose. These are based on the theory and evaluations presented in earlier chapters on direct gradient analysis, ordination, and classification. Then, representative literature references will be given for applications of multivariate analysis in applied community ecology and in related and distant fields.

General recommendations

First, general recommendations will be given for multivariate analysis in community ecology. Although presented in the context of community ecology, these recommendations, for the most part, concern common features of any kind of two-way individuals-by-attributes matrix and, consequently, apply to many kinds of data.

Especially for applied researchers, multivariate analysis is just one of many tools serving as a means to specific ends. An applied researcher's time for learning multivariate techniques and for analyzing a particular data set is limited, so it is necessary to provide straightforward, general recommendations that usually work. Given the greater robustness of recent multivariate techniques, such recommendations are now possible. As Williams (1976:28) notes, “Where a subject is ancillary to one's own discipline, the important thing is not how much, but how little, one needs to learn.”

Data editing

A samples-by-species community data matrix may be edited prior to multivariate analysis (Singer 1980).