Abstract
Impingement rates for young-of-the-year white perch (Morone americana) in the Hudson River were analyzed to address two questions: (1) assuming a specified number of years of additional data, what is the minimum fractional reduction in mean year-class strength that could be detected, and (2) assuming a specified fractional reduction in mean year-class strength, how many additional years of impingement data would be required to detect the reduction. Our results indicate that the variability in the baseline data is so great that 10 more years of data are not adequate for detecting even substantial (>50%) reductions in mean year-class strength and that more than 50 years of data would be required to detect an actual 50% reduction in mean year-class strength, given a Type II error of 50%. Our methodology offers a generic tool for establishing bounds on reductions in fish stocks and for estimating the number of additional years of data required to detect such reductions.Key words: fractional reduction, impingement, power plant, statistical power, Type I and Type II errors, white perch, year-class strength
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