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The Importance of Matching the Spatial Scales of Probabilistic Monitoring Designs with Management Questions
Philip R. Trowbridge 1 and Stephen H. Jones 2
1 New Hampshire Department of Environmental Services, Concord, New Hampshire
2 Jackson Estuarine Laboratory, University of New Hampshire, Durham, New Hampshire
Probabilistic monitoring designs offer attractive cost efficiencies to States who are charged with assessing all of their waters in Section 305(b) Water Quality Reports. Rather than sampling every lake, river, and estuary, States can test a random sample of each water body and use this sample to make inferences about the condition of all water bodies. However, the accuracy of the assessment depends on the number of stations in the random sample. Therefore, States need to make a value judgment on how many stations are needed to assess their waters accurately with respect to the management questions being asked.
The N.H. Department of Environmental Services and the University of New Hampshire researched the effect of different spatial scales on the outcomes of probabilistic monitoring. Three overlapping spatial scales were compared. At the smallest scale, four small areas of NH's estuaries were randomly sampled. These four areas were subsets of the study area for the USEPA's National Coastal Assessment, which covered all of NH's estuarine waters. Finally, NH's estuaries are a subset of the U.S. portion of the Gulf of Maine, the whole extent of which was tested for the National Coastal Assessment.
Mercury concentrations in sediment were measured for each of these studies. This paper compares the results of the three studies to determine the ability of probabilistic monitoring at different spatial scales to discern the true scales of environmental disturbance. The results are useful to managers who are planning to implement probabilistic monitoring to resolve specific management questions.
Keywords: monitoring design, probabilistic, spatial scales, mercury, sediment