Review of the Gulf of Mexico Golden Tilefish Stock Assessment: Data Inputs and Model Comparison

Data from the northern Gulf of Mexico golden tilefish fishery was fit to two statistical age structure stock assessment models to assess stock status and to investigate if differences in model structure would produce similar stock status results.  These models represent a stark contrast in terms of model complexity and data required amongst contemporary stock assessment approaches.  Stochastic Stock Reduction Analysis is a fairly simple (i.e. few model inputs and predicted parameters) model  that uses basic life history traits, catch history, and an index of abundance to best predict the current stock status.  Stock Synthesis is a more complex (i.e. numerous model inputs and predicted parameters) model widely used by NOAA Fisheries that uses incorporate time-varying life history patterns, complex size and age selectivities, multiple indices of abundance, and catch histories.  The available data for golden tilefish assessment is fairly typical for many deepwater species in the Gulf of Mexico with sporadic years of length composition, limited age composition data, and inconsistent, highly variable indices of abundance.  Both models agreed that stock status of golden tilefish was not overfished and not undergoing overfishing.  My results indicate that simple assessment models can provide similar results as more complex models that estimate large numbers of parameters and that these simple models may be more useful in modeling species with limited data and can corroborate the results of more complex models in less time.