|Title||A technique for establishing reference nutrient concentrations across watersheds impacted by humans|
|Publication Type||Journal Article|
|Year of Publication||2004|
|Authors||Dodds, WK, Oakes, R|
|Journal||Limnology and Oceanography Methods|
Establishing reference nutrient conditions for rivers and streams is necessary to assess human impact on aquatic ecosystems and protect water quality and biotic integrity. Several methods have been proposed: (1) percentiles from statistical distributions of all rivers and streams in a region or dataset, (2) reference stream approaches, and (3) modeling river networks from existing reference streams. We propose an additional statistical method to estimate the influence of anthropogenic land uses on lotic nutrient concentrations. First, we quantify regional variation by using analysis of covariance, where total nitrogen or total phosphorus is the dependent variable, region is the categorical predictor, and percentage of anthropogenic land use (e.g., cropland, urban land) is the covariate. This allows for the aggregation of regions if there is not a significant regional effect, or if there is a significant regional effect, identifies the need to analyze regions separately. Second, we develop multiple linear regression models with best-model techniques in which anthropogenic land-use classifications are the independent variables, and the logarithms of in-stream nutrient concentrations are the dependent variables. The intercept of these regression models (i.e., expected nutrient concentration in the absence of human activities assuming linear extrapolation to the origin) represents the reference nutrient concentrations. This analysis suggests that larger percentages of cropland and urban land have strong positive influences on in-stream nutrient concentrations, both in eastern Kansas and across the conterminous United States. The most appropriate method for regions may depend on the relative availability of reference sites and other data sources. The covariance/reference approach offers a potential method for regions with limited numbers of reference sites.