An Ecological Climatic Classification of Michigan: A Quantitative Approach

Abstract

Abstract An ecological climatic classification method that emphasizes variables important to tree growth and survival was developed for Michigan. Separate classifications of weather station data were made for winter variables, growing season temperature variables, and growing season water balance variables. Each classification was based on the combined results of 6 cluster analysis procedures and principal component analysis. Hierarchical agglomerative average link cluster analysis using a modified Canberra metric as a distance measure (CANA) was generally most effective in reflecting the underlying structure of the climatic data. A single unified classification was then made combining the climatic information with physiographic patterns. Three regions and 20 districts were identified. The final classification was evaluated with canonical discriminant analysis and analyses of variance. The importance of such classifications for forest management and relationships with other climatic classification methods were discussed. For. Sci. 34(1):119-138.