| Autor: |
Dugan HA; Center for Limnology, University of Wisconsin-Madison. 680 North Park Street Madison, Wisconsin 53706, United States., Skaff NK; Department of Fisheries and Wildlife, Michigan State University, 13 Natural Resources Building, East Lansing, Michigan 48824, United States., Doubek JP; School of Natural Resources & Environment and Center for Freshwater Research and Education, Lake Superior State University, Sault Sainte Marie, Michigan 49783, United States., Bartlett SL; NEW Water, 2231 North Quincy Street Green Bay, Wisconsin 54302, United States., Burke SM; University of Guelph, School of Environmental Sciences, Guelph, Ontario N1G 2W1, Canada.; Aquatic Contaminants Research Division, Environment & Climate Change Canada, Burlington, Ontario L7S 1A1, Canada., Krivak-Tetley FE; Department of Biological Sciences, Dartmouth College, 78 College Street, Hanover, New Hampshire 03768, United States., Summers JC; WSP Canada Incorporated, 2300 Yonge Street, Toronto, Ontario M4P 1E4, Canada., Hanson PC; Center for Limnology, University of Wisconsin-Madison. 680 North Park Street Madison, Wisconsin 53706, United States., Weathers KC; Cary Institute of Ecosystem Studies, Millbrook, New York 12545, United States. |
| Abstrakt: |
Lakes in the Midwest and Northeast United States are at risk of anthropogenic chloride contamination, but there is little knowledge of the prevalence and spatial distribution of freshwater salinization. Here, we use a quantile regression forest (QRF) to leverage information from 2773 lakes to predict the chloride concentration of all 49 432 lakes greater than 4 ha in a 17-state area. The QRF incorporated 22 predictor variables, which included lake morphometry characteristics, watershed land use, and distance to the nearest road and interstate. Model predictions had an r 2 of 0.94 for all chloride observations, and an r 2 of 0.86 for predictions of the median chloride concentration observed at each lake. The four predictors with the largest influence on lake chloride concentrations were low and medium intensity development in the watershed, crop density in the watershed, and distance to the nearest interstate. Almost 2000 lakes are predicted to have chloride concentrations above 50 mg L -1 and should be monitored. We encourage management and governing agencies to use lake-specific model predictions to assess salt contamination risk as well as to augment their monitoring strategies to more comprehensively protect freshwater ecosystems from salinization. |
