A river valley segment classification of Michigan streams based on fish and physical attributes

Water resource managers are frequently interested in river and stream classification systems to generalize stream conditions and establish management policies over large spatial scales.  We used fish assemblage data from 745 river valley segments to develop a bi-level, segment-scale classification system for rivers and streams in Michigan.  Regression tree analyses distinguished 10 segment types based on July mean temperature and network catchment area, and classified 26 segment types when channel gradient was additionally considered.  Nonmetric multidimensional scaling analyses suggested that fish assemblages differed among segment types, but were only slightly influenced by channel gradient.  Species that were indicative of specific segment types generally had habitat requirements that matched segment attributes.  Fish assemblage data from an additional 77 river valley segments verified the precision of the classification system.  Our classification system for river valley segments overcomes several weaknesses of classification approaches previously used in Michigan and our approach may be applicable elsewhere.