Simulation Analysis of Tag-Integrated Catch-at-Age Models

Tag-integrated catch-at-age assessment models are increasingly being used in fisheries assessment and management. These models generally are spatially explicit and are used to estimate both mixing rates and population dynamics of stocks (e.g., abundances, mortality components). Tagging data can be modeled in various ways in an integrated assessment model. The first and most common way is to condition tag recoveries on the total number of tags released (release conditioned model). The second way is to condition tag recoveries on the total number of recoveries, thus ignoring tags that are never recovered (recapture conditioned model).  The recapture conditioned model formulation was originally used to estimate movement rates that would be unbiased by reporting rates and tag loss. This model has the advantage that under the limiting assumption of constancy over time and space these parameters cancel in the likelihood equations.  Although release conditioned and recapture conditioned tag-integrated models have been used empirically, simulation analyses of the performance of these two modeling approaches have not been widely conducted.  We conducted such simulations to compare the bias and precision of the two approaches under a range of scenarios.  We additionally evaluate the benefits that tagging data provide to catch-at-age models in general.