Simultaneous Analysis of Genetic and Age Data to Estimate Spawning Population Contribution to Admixed Fisheries in the Great Lakes

Many Great Lake fisheries are admixed with individuals from different spawning populations occurring in the same area during periods of commercial and/or recreational exploitation. Examples of Great Lake fishes exploited through admixed fisheries include lake whitefish, walleye, lake trout, lake sturgeon, cisco, Chinook salmon, and yellow perch. Measuring spawning population contribution and, perhaps more importantly, inter-annual variability in contributions to admixed fisheries is not easy, but is important for preventing overharvest of low productivity populations. We are working to expand existing Bayesian-based genetic stock identification methods to include age or length data for the purpose of estimating inter-annual variability in spawning population contribution to admixed fisheries. To decrease the number of estimated parameters, time-varying spawning population contributions are modeled as a function of spawning population and year class effects. Two scenarios are considered: one in which year-class strength for baseline spawning populations changes consistently and another in which year-class strength fluctuates more dramatically. We demonstrate these estimation approaches and discuss associated assumptions using a combination of simulated data and actual genetic and age data for Great Lakes fish stocks.