Spatial Scale and Appropriate Aquatic Habitat Modeling Approaches

Stream habitat data are often collected across spatial scales because relationships among habitat, species occurrence, and management plans are linked at multiple spatial scales. Unfortunately, scale is often a limiting factor to gaining insight from spatial analysis of stream habitat data. Considerable cost is often expended to collect data at several spatial scales to gain accurate evaluation of spatial relationships in streams. To address utility of single set of data when used at varying scales, accuracy loss, and potential to lower data collection needs in stream habitat studies, we examined the influence of scale on accuracy of natural neighbor predicted depth, flow, and substrate maps. We measured two streams at 0.1 m2 cell size over an area of 797 m2 to create baseline for natural neighbor interpolated maps at 12 incremental scales ranging from a raster size of 0.1 m2 to 13.38 m2. Predictive maps exposed a logarithmic linear decay in r2 and RMSE values for map accuracy for variables as scale departed from the original. Proportional accuracy of models was maintained up to 78% at scales 11 times more coarse than the original collection scale. Therefore, accuracy retention was suitable for assessment and management purposes at scales many times removed from the data collection scale. Our study is relevant to spatial modeling, fish habitat assessment, and stream habitat management because it highlights the potential of a single dataset to fulfill analysis needs otherwise requiring several scaled datasets at an increased cost of time and money.