A Multimetric Assessment of Stream Condition in the Northern Lakes and Forests Ecoregion Using Spatially Explicit Statistical Modeling and Regional Normalization

Abstract

AbstractWe sampled fish communities, water temperature, water chemistry, physical habitat, and catchment characteristics for 94 stream sites selected randomly throughout the Northern Lakes and Forests ecoregion and used those data to explicitly model reference conditions and assess ecological stream condition at each site via a regional normalization framework. The streams we sampled were first order through fourth order, and the catchments ranged from 0.9 to 458 km2. We developed multiple linear regression (MLR) models that predicted fish community metrics, water chemistry characteristics, and local physical habitat from catchment characteristics; we used these models to compare existing conditions with the conditions that would be expected based on the regression models. Our results indicated that the fish communities were relatively unimpaired because the catchment variables associated with human‐induced land use change were important in only 1 of the 10 fish metric models. Agricultural land use was a significant variable in the MLR equation for species of Lepomis (sunfish). Agricultural land use and urban land use were both significant variables in all of the MLR models predicting water chemistry variables; urban land use was a significant variable in the MLR model predicting the percent coverage of all instream cover types. Regional normalization indicated that none of the sites were impaired based on fish community attributes. However, our analysis based on water chemistry metrics indicated that 22– 35% of the sites were impaired and that, based on physical habitat, 6–14% of the sites were impaired. A comparison with other published studies of the ecoregion suggested that the regional normalization process correctly characterized stream condition.