ABSTRACT
The U.S. Environmental Protection Agency (EPA) is required to issue regulations for implementing Section 316(b) of the Clean Water Act (CWA), 33 U.S.C. Section 1326(b). Section 316(b) provides that any standard established pursuant to Sections 301 or 306 of the CWA and applicable to a point source shall require that the location, design, construction, and capacity of the cooling-water intake structures reflect the best technology available (BTA) for minimizing adverse environmental impact (AEI). Early guidance provided by the EPA indicated that AEI occurs whenever there is entrainment or impingement of aquatic organisms resulting from the operation of a cooling-water intake structure[1]. However, this policy could require costly mitigation like a cooling tower that produces little benefit if an alternative definition of AEI is adopted, e.g., one based on populations. In such high-stakes cases, the degree of environmental protection and the associated cost should be reconciled with scientific data and methods[2]. Recently, the EPA began a process to update and formalize its early guidance for defining and assessing AEI. Factors that the EPA is considering include new approaches and tools developed since the early guidance was issued[3]. One of the tools being considered is ecological risk assessment. It is used to evaluate the likelihood that adverse ecological effects may occur or are occurring as a result of exposure to one or more stressors and includes an evaluation of uncertainty[4]. Two types of uncertainty affect risk assessments for populations[5]. One is intrinsic to the populations, reflecting natural variability in abundance. The other reflects variability in abundance due to sampling (i.e., measurement error). This distinction is not usually recognized in risk analyses of population extinction[6,7,8,9], but the distinction may be very important. Using very simplified and idealized numerical examples, Ferson and Ginzburg[5] demonstrated that failure to partition natural variability and measurement error could produce biased estimates of risk. Large measurement errors, which are present in most fisheries data, result in substantial uncertainty in abundance estimates[10], often overwhelming effects of density dependence in stock-recruitment relationships[11]. To improve the credibility of scientific advice and to provide better information, measurement error must be considered explicitly[12]. Analysis of the effects of measurement error usually involves bootstrapping simulation studies because multiple, independent estimates of specific parameters, needed to estimate measurement error, are rarely available. For the Hudson River stock of striped bass, multiple, independent indices of abundance are available and measurement error can be estimated. The effects of entraining fish, especially striped bass, at power plants operating on the Hudson River have been of considerable interest to regulators, electric utilities, and the public[13,14,15]. Currently, the New York State Department of Environmental Conservation (the Department) is reviewing applications to renew
the State Pollutant Discharge Elimination System (SPDES) permits for power plants operating on the Hudson River at the Bowline Point, Indian Point, and Roseton sites. In the review process, the Department will consider the level of uncertainty that can be accommodated in making a decision on the SPDES permit renewals (i.e., what level of risk to the fishery resource is acceptable)[16]. The Department will also consider issuing consecutive SPDES permits covering a time horizon of up to 15 years as an alternative to issuing a single permit for a 5-year period[17]. The choice of time horizon can strongly affect both the outcome and reliability of risk assessments[18]. For shorter time horizons, the risks of alternative actions may not differ appreciably. In such cases, having estimates of measurement error would be less critical than for longer time horizons where measurement error may hide real differences in risk. Our objectives were to identify a measure of risk for the Hudson River stock of striped bass that could be used to evaluate the effects of entrainment mortality at the Bowline, Indian Point, and Roseton power plants, assess the effects of measurement error and time on the risk estimates, and compare the risks due to entrainment mortality with those due to increased fishing mortality recommended under Amendment #5 to the Interstate Fishery Management Plan for Atlantic striped bass.
