Choosing the Right Tool for the Job: Comparing Stream Classification Frameworks

Geomorphic stream classification provides a means to stratify monitoring of fish and their habitat, allows extrapolation of habitat quality to areas that are not directly monitored, and informs restoration design. While numerous classification frameworks are available to managers, little information exists about how frameworks compare with regard to data, time, and expertise requirements. The reasons for agreement or disagreement between classification outputs also remain largely unexplored. Here we apply four frameworks within the Middle Fork John Day River, Oregon, USA. We compare the results of the River Styles Framework, Natural Channel Classification, the Rosgen Classification System, and channel form-based statistical classification. We find that the frameworks classified reach types consistently, and where divergence occurred, differences resulted from (a) spatial scale of input data used, (b) the requisite metrics and their order in completing a framework’s decision tree and/or (c) whether the framework classified current or historic channel form. We additionally explored the relative effort, time, and disciplinary expertise required to complete each classification. The results of this research emphasize that selection of a particular geomorphic stream classification framework for use fisheries management should be tailored to the driving questions and disturbance processes at hand.