Abstract
Information gained from tagging programs can be incorporated into stock assessments to reduce uncertainty in the current stock status. A spatially explicit Bayesian was used to analyze historical Atlantic conventional tag data and showed that the tagging data available provide information on regional movements within the Eastern Atlantic Ocean, but due to fewer tag releases and returns in the Western Atlantic, basin-wide parameters are not estimable. Catch and effort data suggest that these movements are seasonal. A large scale tagging program is currently being implemented in the Atlantic by the International Commission for the Conservation of Atlantic Tunas (ICCAT). A simulation framework was developed to model ICCAT’s Atlantic Ocean Tuna Tagging Program (AOTTP) and provide recommendations for the program. This simulation framework was used to simulate the release of two types of electronic tags, data storage tags and popup satellite archival tags on yellowfin and bigeye tuna. A Bayesian space-state model was used to estimate movement rates, fishing, and natural mortality from the simulated electronic data and conventional tags. Fishing and natural mortality parameter estimates were very similar from both types of electronic tags. Using conventional tag data simulated using an age-specific fishing and natural mortality in a spatially-explicit simulation framework, mortality was estimated as age-specific parameters and age-constant parameters. Model results indicated that when the underlying population dynamics have significant age structure, assuming parameters were constant across age classes resulted in significantly biased estimates. The simulations provided several recommendations to help the AOTTP meet the goals of the program.