Quantifying the Effects of Aging Bias in Atlantic Striped Bass Stock Assessment

Abstract

AbstractThe effects of aging bias on stock assessment have been evaluated in many simulation studies. However, simulated data cannot be used to quantify the magnitude of aging biases in a real data set and thus their effects on an ongoing stock assessment. In this study, we validated scale and otolith aging using Striped Bass Morone saxatilis of known age collected from the Chesapeake Bay between 1997 and 2006. Otoliths provided more accurate (74% agreement) and precise (average CV = 1.9%) age estimates than scales, which overestimated the ages of young fish and underestimated the ages of old fish (22% agreement; average CV = 9.8%). Based on their accuracy, otolith ages were subsequently used to quantify aging biases in the scale ages and effects of bias in the stock assessment of Atlantic Striped Bass. We converted scale‐age to otolith‐age input using paired scale and otolith ages of Striped Bass collected by commercial fisheries in Virginia waters of the Chesapeake Bay and the mid‐Atlantic from 1999 to 2010. A statistical catch‐at‐age model was run with the scale‐ and otolith‐age input data and the results were compared. We found that aging biases from scale ages resulted in underestimates of population abundance (15%) and female spawning stock biomass (19%) and overestimates of fishing mortality in the terminal year (19%) and made strong age‐1 recruitment years appear weaker and weak ones stronger. Our study demonstrates how aging bias in a large scale‐age sample can be corrected with a relatively small sample of paired scale–otolith ages and provides fisheries management with a quantitative evaluation of aging bias and its effects on the assessment of the Atlantic Striped Bass stock.