Yield-per-recruit modeling of two piscivores in a Midwestern reservoir: A Bayesian approach

Walleye Sander vitreus and hybrid striped bass Morone chrysops x M. saxatilis fisheries are supported by annual stockings in many US midwestern reservoirs. To maximize return to the angler, yield-per-recruit models are often used to evaluate expected yield and assist managers to determine which regulation to implement, generally length or bag limits. However, yield-per-recruit models are typically formulated with point estimates of life history parameters, which ignore uncertainty. Our objective was to estimate yield from yield-per-recruit models of walleye and hybrid striped bass under various harvest strategies (e.g., alternative minimum length limits and conditional fishing mortality rates) while incorporating uncertainty about the input model parameters. We estimated parameters of age and growth and weight-length models simultaneously using Bayesian inference. The full posterior distribution of these model parameter estimates were then used to estimate yield. We found that yield differed among length limits for both species at high conditional fishing mortality. We also found yield decreased for both species as minimum length limits increased for low conditional fishing mortality. Finally, we presented a probabilistic framework to determine how changing minimum length limits and conditional fishing mortality affects the probability of achieving 70-90% of the maximum yield. Our results provide insight on the expected yield under different minimum length limits and bag limits, while incorporating uncertainty in the model inputs, and add to the sparse literature on hybrid striped bass population dynamics.