Location
UMass Amherst
Start Date
27-6-2011 10:20 AM
End Date
27-6-2011 10:40 AM
Description
The York Haven hydroelectric Project is fourth in a series of hydroelectric dams on the lower Susquenhanna River with upstream passage facilities for American shad. As part of relicensing at York Haven, resource agencies have requested that a statistically valid estimate of American shad upstream passage efficiency be developed for the Project fish ladder. A statistical true mean was adopted. Radio telemetry tracking was determined to be the best method of generating data to estimate passage efficiency. Sample size is a critical design component due to the transmitter costs, availability of fish for tagging, and logistics of tracking large numbers of fish at the same time. Historical fish passage records from 1997 through 2009 were examined to evaluate the appropriate radio telemetry sample size necessary to achieve the statistical precision target. Year to year variation in passage numbers and proportion of fish passed is substantial in the record. Regression analyses indicate that approximately 90% of the total annual, variability in the number of shad passing the lower dam. Further, the proportion of fish passed varies year to year as a function of downstream population density, measured by passage at the lower dam. A bootstrap analysis and logistic regression analysis was used to estimate variation and the appropriate sample size for the radio telemetry study. The results of this analysis indicate that it will take a minimum of 5 years studying 250 tagged shad per year or 10 years of more studying 100 tagged shad per year at York Haven Dam to be 95% certain of estimating the true mean efficiency of upstream fish passage within +/- 25%.
Session B1- Sample size and statistical considerations for the estimation of American shad upstream fish passage efficiency
UMass Amherst
The York Haven hydroelectric Project is fourth in a series of hydroelectric dams on the lower Susquenhanna River with upstream passage facilities for American shad. As part of relicensing at York Haven, resource agencies have requested that a statistically valid estimate of American shad upstream passage efficiency be developed for the Project fish ladder. A statistical true mean was adopted. Radio telemetry tracking was determined to be the best method of generating data to estimate passage efficiency. Sample size is a critical design component due to the transmitter costs, availability of fish for tagging, and logistics of tracking large numbers of fish at the same time. Historical fish passage records from 1997 through 2009 were examined to evaluate the appropriate radio telemetry sample size necessary to achieve the statistical precision target. Year to year variation in passage numbers and proportion of fish passed is substantial in the record. Regression analyses indicate that approximately 90% of the total annual, variability in the number of shad passing the lower dam. Further, the proportion of fish passed varies year to year as a function of downstream population density, measured by passage at the lower dam. A bootstrap analysis and logistic regression analysis was used to estimate variation and the appropriate sample size for the radio telemetry study. The results of this analysis indicate that it will take a minimum of 5 years studying 250 tagged shad per year or 10 years of more studying 100 tagged shad per year at York Haven Dam to be 95% certain of estimating the true mean efficiency of upstream fish passage within +/- 25%.
Comments
Steve Arnold is a Senior Aquatic Scientist and Professional Associate at HDR I DTA in Portland Maine. He obtained an MS in Biology from Michigan Technological University, in 1981. He has worked as a fisheries consultant for 28 years and has provided services exclusively to the hydropower industry for 21 years. Steve's professional interests include upstream and downstream passage of anadromous and catadromous fish, fish population dynamics, instream flow and associated habitat for aquatic organisms, and multiple-use resource conservation principles.