Skip to main content

    UPDATE OF THE INTEGRATED STOCK ASSESSMENT FOR THE PATAGONIAN TOOTHFISH (DISSOSTICHUS ELEGINOIDES) FOR THE HEARD AND MCDONALD ISLANDS (DIVISION 58.5.2)

    Request Meeting Document
    Document Number:
    WG-FSA-09/20
    Author(s):
    S.G. Candy and D.C. Welsford (Australia)
    Abstract

    The integrated assessment of Patagonian toothfish, Dissostichus eleginoides, for the Heard and McDonald Islands (Division 58.5.2) was updated by replacing catch-at-length proportions from commercial catches with catch-at-age proportions by applying age length keys (ALKs) to gear- type/ground (i.e. sub-fishery) and year-specific length frequency (LF) data. A Poisson log-linear (contingency-type) analysis of the age-length frequency data suggested that ALKs could be pooled across sub-fisheries without significant loss of information. Pooling the ALKs in this way meant that all commercial catch data could be input to CASAL as catch-at-age proportions except for the 2009 catches. For 2006 and 2007 random stratified trawl surveys, ALKs were used to convert abundance-at-length to abundance-at-age data. Effective sample sizes for the commercial catch-at-age proportions, assuming a multinomial distribution, and the coefficient of variation (CV) for the abundance-at-age, assuming a lognormal distribution, each took into account uncertainty due to haul-level variability in catch-at-length proportions, ALK sampling error and random ageing error. CASAL allows a single ageing error matrix to be defined and applies this matrix to predictions of numbers-at-age and proportions-at-age. In other work, this matrix was found to depend on the readability score of the otoliths used for ageing, so the ageing error matrix was calculated as a weighted average of elements across nearest integer average readability scores for sub-fishery by year aged otoliths where the weights were the effective sample size for proportions-at-age. Compared to the assessment that did not incorporate catch-at-age or abundance-at-age data, the aged-based assessment dramatically lowered the CV for the recruitment series, from around 1.8 down to approximately 0.6. The other major differences to the a2-ess model of Candy and Constable (2007, CCAMLR Science 15, 1-34) were that catches and catch-at-age data for additional sub-fisheries (2 longline, 1 trawl) and pot fishing in the 2006 season were included since catches in these cases have become significant in recent years, and the CV of mean length-at-age was fixed at 0.1 and not estimated since the inclusion of age data has reduced the ability to successfully estimate this parameter. The long-term yield that satisfies the CCAMLR decision rules, using a split of the catch by sub-fishery corresponding to actual catches in 2008, was 2 565 t.