Fundamental to the careful management of fish stocks is information on mortality rates and other dynamic functions that characterize that stock. Prior to this work, such efforts for walleyes from the Saginaw Bay stock were conducted with a Brownie style analysis of jaw tag reports. Unlikely assumptions and limited participation by all fisheries in their report of tags, necessitated the elevation of stock assessment methods to state of the art methods. I developed a statistical catch-at-age model to accomplish this and evaluated four versions including three different treatments of natural mortality (M): a constant value, age-based M values, and time-varying M values. Deviance information criterion model selection procedures indicated that an age-based M model version was the optimal fit of the data. I also evaluated an integrated version that incorporated tag returns as auxiliary information for the recreational component. In this case, model selection was based on conformity between observed and predicted data and model convergence. The integrated version was ruled out due to poor agreement of the observed and predicted values, and predictions of abundance that were not reflected by the fisheries. It was concluded that the component of the population used for tagging may exhibit dynamics that differ from the rest of the stock. Total annual mortality of walleyes was greatest for older ages in all fisheries and ranged from 32% for age-2 fish to 39% for fish ages-10 and older. The recreational fishery accounted for the majority of fishing mortality but the commercial trapnet fishery in the main basin of Lake Huron and by-kill from other trapnets in the bay accounted for proportionally greater fishing mortality of younger ages of fish. Abundance peaked in 2007 at 4 million walleyes age 2 and older but estimates indicated a previous period of high abundance in the late 1980s, forcing the reconsideration of the past stock as depressed and dependent on stocking. Statistical catch-at-age methods characterize the dynamics of a stock from the past up to the present but do not project forward what the fish stock is likely to do in the future under various management scenarios. After consulting with fishery managers, I developed a stochastic simulation model and used it to evaluate management options for the recreational fishery in the form of a decision analysis and a value-of-information analysis for improved estimates of by-kill magnitude. This analysis was in light of two critical uncertain states of nature concerning the true magnitude (catchability) of the by-kill and the future of alewives in Lake Huron, the latter being a strong determinant of walleye recruitment. Management option evaluation indicated a greater harvestable surplus that could be allocated. Sustainable harvest was calculated as average harvest treating harvest in years when sustainability criteria were not met as zero. Sustainable harvest would be maximized if recreational fishing mortality were increased 50% from recent levels. Realizing this potential, however, would require more intensive management to ensure that desired levels of F occurred. Choices by managers as to how to allocate surplus harvest are a matter of policy, but concerns over maintaining predation pressure on alewives so as to suppress any resurgence may be reasons to manage conservatively by electing to instead maintain a higher predator abundance. The value of information analysis suggests that further research investment in the uncertainty over by-kill catchability might be justified on the basis of producing net-benefits from the recreational fishery.
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