An age structured model for assessment and management of Copper River chinook salmon

Abstract

Chinook salmon in Alaska support human uses through a variety of fisheries. Age-structured assessment models are rarely used for estimating the abundance of exploited stocks. This thesis develops a model for the Copper River chinook salmon population to show its advantages over typical assessment models. Information consists of catch-age data from three fisheries (commercial, recreational, subsistence), and two sources of auxiliary data (escapement index, spawner-recruit relationship). Four approaches utilizing different information sources are explored. Results suggest that an approach utilizing pooled catch-age data with time-varying brood-year proportions produces the best estimates, although retrospective and sensitivity analyses suggest that all four approaches explored are robust. The model should assist managers when making management decisions, because it integrates all sources of information, accounts for uncertainty, and provides estimates of optimal escapement. The model shows promise as a method for assessing and forecasting chinook salmon populations.