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    A feasibility study for stock assessment of D. mawsoni in the Ross Sea (Subares 88.1 and 88.2) using a tag and recapture experiment

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    Document Number:
    WG-FSA-SAM 03/10
    Author(s):
    K.J. Sullivan, N.W.McL. Smith, J. McKenzie and S.M. Hanchet (New Zealand)
    Abstract

    This paper reports on a feasibility study into a tag and recapture experiment for the purpose of stock assessment of the Antarctic toothfish (Dissostichus mawsoni) in the Ross Sea. An exploratory fishery for D. mawsoni has been operating since 1997-98. Catches have increased from ~40 t in 1997-98 to nearly 1800 t in 2002-03. Although some Patagonian toothfish (D. eleginoides) are taken in the more northern areas, catches have been predominantly D. mawsoni.
    To date nearly 2000 toothfish (about 90% D. mawsoni) have been tagged and released in the area, from vessels operating in the exploratory fishery during the last 3 seasons. A good number of tag recoveries have been reported, mainly within the same season but also between successive seasons, which indicates that fish are surviving the tagging event.
    It is proposed to continue tag releases each season as part of the exploratory fishery for the purpose of determining the stock size of D. mawsoni and sustainable yields for the fishery. Ongoing annual tagging will provide data suitable for estimating natural survival, abundance and recruitment using the Jolly-Seber or variant estimators. The utility of this approach is investigated here by applying a Jolly-Seber estimator to simulated tagging data generated by an operating model over a range of assumed population sizes and tagging strategies. The study indicates the number of releases required to achieve various levels of precision of the population estimate based on:
    • assumed survival rates of released fish;
    • current exploitation rates in the fishery; and
    • known growth and natural mortality parameters.
    Although this initial attempt considers the simplest population structure (a homogeneous stock and fishery), further complexity can be added to the model to explore the heterogeneity in the population using length and spatial strata.