Using Expert Knowledge to Develop Fuzzy Habitat Suitability Models for Steelhead and Chinook Salmon in the Interior Columbia River Basin

Strategic restoration actions for threatened and endangered species require accurate estimates of available habitat.  In this study, we developed habitat suitability models using a fuzzy inference system (FIS) approach.  Relative to traditional habitat suitability modeling approaches, the FIS approach is beneficial in that it is conceptually easy to understand (e.g., rooted in language vs. numbers), flexible in parameterization, accommodating to imprecise data and capable of incorporating expert knowledge.  Models were developed for two life stages (juveniles, spawners) of two species of concern (steelhead and spring Chinook) in the interior Columbia River Basin (CRB).  Expert opinion from numerous fish biologists were used to define the ‘IF-THEN’ rules that relate the model inputs, or physical factors, to the model output, habitat suitability.  Metrics derived from the models include weighted usable area and reach-level capacity estimates.  We applied the model at over 400 stream reaches in 8 subbasins of the interior CRB using output from Delft 3D hydraulic model runs and field substrate estimates and compared predictions to alternative estimates of habitat capacity and use.  This study highlights the utility of FIS modeling approaches when funding and logistics limit the ability to produce river-specific fish preference curves.