A River Valley Segment Classification of Michigan Streams Based on Fish and Physical Attributes

Abstract

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 two-level, river valley segment-scale classification system of rivers and streams throughout Michigan. Regression tree analyses distinguished 10 segment types based on mean July temperature and network catchment area and 26 segment types when channel gradient was also 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. A test of classification strength using fish assemblage data from an additional 77 river valley segments indicated that the classification system performed significantly better than random groupings of river valley segments. Our classification system for river valley segments overcomes several weaknesses of the classifications previously used in Michigan, and our approach may prove beneficial for developing classifications elsewhere.