Skip to main content

    Assessment models for Antarctic toothfish (Dissostichus mawsoni) in Subarea 88.2 SSRUs 88.2C–G for the years 2002–03 to 2010–11

    Request Meeting Document
    Document Number:
    WG-FSA-11/43
    Author(s):
    S. Mormede, A. Dunn and S.M. Hanchet (New Zealand)
    Abstract

    This paper describes the first Bayesian sex and age structured population stock assessment model of Antarctic toothfish (Dissostichus mawsoni) in Subarea 88.2 covering SSRUs 88.2C, D, E, F, and G (SSRUs 88.2C–G). For modelling purpose, we split the region into two fisheries: south of 70.2° S where smaller fish are typically caught and effort has been light; and north of 70.2° S where larger fish are caught and most of the effort has been concentrated. For our reference case we used a selected trips data set and fitted to tag and fishery data from the northern fishery only.
    Model fits to the data were adequate, with the tag-release and recapture data providing the most information on stock size. Estimated initial equilibrium mid-season spawning stock biomass (B0) for model R1 (2011 reference case) ranged from 9820 to 13 350 t, with the initial biomass estimated to be 11 420 t. The yield was estimated at 544 t, slightly lower than the combined current catch limits for the region of 575 t.
    We examined several sensitivities including (i) unaccounted mortality due to lost gear, (ii) catch and tag data from the southern fishery, and (iii) tag data from all trips. The inclusion of the unaccounted mortality from lost gear had little impact on estimates of biomass. The inclusion of tag data from the south fishery led to a 10% increase of biomass, due to the low numbers of tags there, whilst including tag data from all vessels led to a 20% increase in biomass.
    We believe that the SSRU 88.2C–G model provides a more realistic representation of the observations and catch data for the area than the SSRU 88.2E only model. The SSRU 88.2C–G area included tags that may move between SSRU 88.2E and adjacent SSRUs, and it better accounts for the age frequency structure of the north and south areas.