Validation of a vulnerability index of exposure to chemicals of emerging concern in surface water and sediment of Great Lakes tributaries of the United States.

Widespread occurrence of emerging contaminants in Great Lakes tributaries led to the development and publication of a vulnerability index (VI) to assess the potential exposure of aquatic communities to chemicals of emerging concern (CEC) in the Great Lakes basin. The robust nature of the VI was tested to evaluate the underlying statistical model and expand the spatial domain of the index. Data collected at 131 new sampling sites (Test 1) and published data from independent studies (Test 2) were used to test the model predictions. Test 1 water and sediment samples were analyzed for the same classes of CEC chemicals and compared to the predictions for the original VI. Concentrations and numbers of unique CECs detected in water and sediment samples were similar between the original data and the two test datasets, although CECs tended to have higher detection frequencies in the original dataset compared to the Test 1 and Test 2 datasets. For example, 69 CECs were detected in ≥30% of water samples in the original dataset compared with 17 CECs in the Test 1 data and 59 in the Test 2 data. Predicted vulnerability for test sites agreed with actual vulnerability 64% of the time for water and 71% of the time for sediment. Agreement percentage results were greater when individual sites were grouped by river, with 82% agreement between predictions and actual vulnerability for water and 78% agreement for sediment. For the entire dataset, the VI ranks correlated with an independent estimate of potential biological impact. Agreement percentage was the greatest for low or high vulnerability index values but highly variable for sites that are classified as having medium vulnerability. Despite the underlying variability, there is a significant correlation (R2 = 0.26; p < 0.01) between the VI ranking of tributaries and the independent ranking of potential negative biological impact.

Predicting the occurrence of chemicals of emerging concern in surface water and sediment across the U.S. portion of the Great Lakes Basin.

Chemicals of emerging concern (CECs) are introduced into the aquatic environment via various sources, posing a potential risk to aquatic organisms. Previous studies have identified relationships between the presence of CECs in water and broad-scale watershed characteristics. However, relationships between the presence of CECs and source-related watershed characteristics have not been explored across the Great Lakes basin. Boosted regression tree (BRT) analyses were used to develop predictive models of CEC occurrence in water and sediment throughout 24 U.S. tributaries to the Great Lakes. Models were based on the distribution of both broad-scale and source-related watershed characteristics. Twenty-one upstream watershed characteristics, including land cover, number of permitted point sources, and distance to point sources were used to develop models predicting the probability of CEC occurrence in surface water and bottom sediment. Total accuracy of BRT models ranged from 66% to 94% for both matrices. All 21 watershed characteristics were important predictor variables in at least one surface-water model; twenty were important in at least one bottom-sediment model. Among the model variables, developed land use and distance to point sources were important predictors of the presence of CEC classes in both water and sediment. Although limitations exist, BRT models are one tool available for assessing vulnerability of fisheries and aquatic resources to CEC occurrences.