CCAMLR

A descriptive analysis of the toothfish tagging programme carried out in the Ross Sea since 2001 is presented for the first time. Tag-release and tag-recapture data are presented for both toothfish species for Subareas 88.1 and 88.2 for New Zealand vessels only. This is because data from non-New Zealand vessels were unavailable at the time of the analysis. A total of 4903 Antarctic toothfish have been released and 89 recaptured, and 443 Patagonian toothfish released and 9 recaptured. For the last two years, when tagging has been part of the Conservation Measure, New Zealand vessels have tagged between 1.0 and 1.37 toothfish per tonne of catch. Tagging rates by area over the past three years have been in the same proportion as the catch by area. However, recapture rates have tended to be higher in the northern and eastern SSRUs 88.1C and 88.2E.
The maximum movement of Antarctic toothfish from the New Zealand data set has been about 200 km. However, most (80%) Antarctic toothfish have moved less than 50 km. Consequently, nearly all fish have been recaptured from the same SSRU where they were released. The mean size of tagged Antarctic toothfish has increased since 2001, but is still smaller than the mean size of fish taken in the commercial catch. Larger toothfish (>35 kg) are difficult to tag without significant damage to fish, and there appears to be a trade-off between maximising size of released fish and minimising tagging mortality. Growth rates of Antarctic toothfish that have been at liberty for 2–3 years have averaged 5– 7 cm per year, which is consistent with growth rates predicted from the von Bertalanffy growth curve. The preliminary estimate of tag loss from double tagging experiments is 13% per year.

This paper describes an approach, using CASAL, to undertake operating model/estimation model experiments for Dissostichus spp., and methods for calculating CCAMLR yields using CASAL. We present an example model for the fictitious fishery on a fictitious species Dissostichus spurious (Everson, 2004) and investigate model performance from alternative types of observations. In general, most models were fitted with an expected percent root mean squared error (%RMSE) of less than 20%. The inclusion of additional data (i.e., more observation types) assisted in providing better estimates.
Further research on the expected performance of integrated models is required that investigates a range of alternative “true” states with data that includes bias and variance in observations, as well as the robustness of the estimation model to alternative operating model assumptions. In addition, the expected uncertainty that may arise from an MCMC approach has not been considered here.
In general, operating/estimation modelling experiments provide a means of evaluating alternative approaches to the assessment of stocks, however it should be noted that simulation studies often under-estimate the uncertainty that would be found in a real assessment.

This paper presents a new approach to the stratification of catch-at-length data of Antarctic toothfish (D. mawsoni) in the Ross Sea.
Tree based regression techniques were used to stratify the sampled catch based on the median length of Antarctic toothfish for each set using the observer length frequency data. The median lengths were weighted within the regression by the inverse of the variance, rather than giving equal weights to all tows. Two variables (depth and SSRU) were used by the tree regression model to determine the strata.
The resulting stratification effectively split the fishery into 4 regions, consisting of shallow inshore regions where predominantly smaller fish were found, to deeper offshore regions where only larger fish were found. The paper presents the new estimates of Antarctic toothfish catch-at-length and catch-at-age from the Ross Sea up to the end of the 2003–04 fishing season.

The mark-recapture method of estimating toothfish population size described last year, which uses a modification of the Petersen estimator to take account of mortality and selectivity, is implemented here in Splus code.

This paper investigates the influence of mixing of fish, and the uneven distribution of tag placements and recapture effort, on bias in the Petersen estimate. It does so by constructing a linear model of the South Georgia toothfish fishery, simulating fish movements within this system and overlaying various combinations of tagging and recapture effort to investigate bias. The fishable grounds around South Georgia were divided into 77 very small scale boxes lying along the 1000m contour. The uneven distribution of animals was simulated by adjusting an average movement rate downwards when animals encountered a high CPUE box and upwards in a low CPUE box so that they were retained in high CPUE boxes. The model incorporates the facility for releases by box over a number of years.
The model performed as expected with test situations. It produced a near-perfect estimate of stock size when there was an ideal distribution of tags and/or fishing effort; by ideal we mean that either tagging or fishing effort was in direct proportion to CPUE. When both tagging and fishing effort were non-ideal, eg when effort was concentrated away from tag concentrations, or overly concentrated in them, the Petersen estimator either over-estimated or underestimated (respectively) the true population size. When run on the real tag release data, and using CPUE from 2002-2004 and recapture effort in 2003 and 2004, the model indicated that the Petersen equation produced an under-estimate of true population size. Although we do not advocate using the magnitude of the estimated bias to correct the tagging estimate made last year for 48.3, we do conclude that the particular distribution of tag releases and recapture effort at South Georgia is likely to lead to an under-estimate of the true population size rather than an over-estimate of it.

ASPM have been proposed and applied for Patagonian toothfish stock assessment at CCAMLR Subarea 48.3. Last results obtained from this model, discussed at WG-FSA (2004), do not show acceptable fit with standardized CPUE series and observed length proportions in the catches.
In this paper, we discuss some of the problems related with available CPUE data and estimate new vulnerability patterns to produce a good fit of the model both, to CPUE series and proportion-at-length data from CCAMLR dataset.

Quantifying the catch rates and biomass of by-catch species on CCAMLR’s fishing grounds is an essential component of the assessment advice prepared by WG-FSA. However, such analyses are problematic because the CCAMLR datasets are incomplete and have a high occurrence of ‘missing catch values’.
A method to treat ‘missing catch values’ using estimates derived from the mean weights of by-catch species by fishing gear, region and period is outlined. This method would improve the consistency of the CCAMLR datasets and allow quantitative analyses of by-catch to be based on the best, scientific data available.