Directional influence of stream habitat variables on modeling stream reaches in the greater Yellowstone ecosystem

Mapping of aquatic habitat by any method can be expensive due to costs of labor, sampling gear, massive data requirements, and limited time. Such pressures create fundamental changes in the roles of conservation scientists. Because of limited budgets and increasing duties, fisheries professionals need time- and cost-efficient methods for stream habitat mapping and assessments. Recent advances in river sampling strategy using natural neighbor based minimal data interpolative modeling in geographic information systems (GIS) have yielded success by reducing time required to produce accurate habitat maps. Minimal data interpolation methodology uses emerging value of information theory concepts, optimal sampling strategy, and statistical models to reduce data requirements (up to 95%) for fine scale aquatic habitat modeling. However, the concept of minimal data interpolation of streams is still in its infancy. This study furthers the practical use and knowledge state of minimal data interpolation of stream variables through exploration of directional influence, such as flow velocity, on optimal data collection strategy and its analysis using geographically weighted regression in GIS. Results indicate that incorporating directional influence of stream variables may further streamline the modeling process and reduce data collection requirements to produce accurate maps for varying purposes.