Influence of data quality and quantity from a multiyear tagging program on an integrated fish stock assessment

Using a modeling framework for toothfish (Dissostichus spp.) population dynamics, fishing, and data collection, this study investigated how the bias and precision of biomass estimates from an integrated tag-based assessment are influenced by various aspects of a multiyear tagging program, particularly the effects of the size of tagged fish compared with the size of fish in the catch (tag size-overlap), numbers of tagged fish, duration of the tagging program, using catch-at-length or catch-at-age data as auxiliary data, and stock depletion levels. Biomass estimates generally improved with more and better-quality tagging data. The results showed that even when tag releases were distributed over a relatively large number of size classes, low recapture numbers collected in short tagging programs with a 100% tag size-overlap were sufficient for robust and unbiased assessments. Particularly in the early stages of the tagging program, a high tag size-overlap was imperative to maximize the likelihood of a robust assessment. Biomass estimates were largely unaffected by the stock depletion level; however, using catch-at-age compared with catch-at-length improved recruitment estimates and resulted in more conservative biomass estimates.