EMPIRICAL AND THEORETICAL ANALYSES OF CORRECTION OF TIME-SERIES BIAS IN STOCK-RECRUITMENT RELATIONSHIPS OF SOCKEYE-SALMON (ONCORHYNCHUS-NERKA)

Using data from 30 sockeye salmon (Oncorhynchus nerka) stocks and Mont e Carlo simulations, we examined the importance of time-series bias on estimates of optimal harvest rate, optimal escapement, and sustainabl e yield. We compared the performance of the least-squares procedure fo r fitting a Ricker curve with an existing bias-correction method. Simu lations showed that the effect of time-series bias is greatest for low -productivity stocks that exhibit a high degree of autocorrelation amo ng residuals of the stock-recruitment relationship. A strong inverse e mpirical relationship between autocorrelation and stock productivity a mong the 30 stocks suggests that time-series bias is a more important concern for low-productivity northern stocks than for more productive southern stocks. The corrected method reduced bias in optimal escapeme nt estimates under a limited set of conditions but at the price of inc reased variance in the estimates. For a constant escapement goal polic y, using the bias correction thus resulted in sustainable yields sligh tly lower than or equal to expected values for 28 of the 30 stocks com pared with yields obtained using the standard least-squares estimation method. We demonstrate the value of using a decision theoretic approa ch to evaluate the performance of estimation methods.