CCAMLR

An accurate history of catch is an important input into the assessment of toothfish stocks, and uncertainty or bias in the amount of catch from an area must be taken into account in the assessment of a stock.

In 2013, Korea held a workshop on the anomalous CPUE data reported from some Korean vessels in data-poor exploratory fisheries (Delegation of Korea 2013). That paper requested that the data be analysed for the development and testing of plausible hypotheses to account for its inherent patterns.

One plausible hypothesis is that the catches were not reported proportionally from the areas where they were taken. For the purposes of developing an alternative catch history for these SSRUs, we use these data regarded as anomalous, along with that from other vessels fishing in the same area and season to illustrate a method for re-adjusting catches that may be area-misreported. We do this by using a standardised CPUE from these vessels to develop an estimate of the amount of catch that could plausibly be area-misreported on these vessel trips across the areas fished.

This allows the calculation of possible alternative catches in areas where reports may not reflect catches. In illustrating this approach to the vessels with anomalous CPUE, we can develop alternative catch histories that can be used to assess the sensitivity for assessments of toothfish.

We detail the procedure followed to check the Ross Sea CCAMLR fisheries data prior to using them in a stock assessment of Antarctic toothfish (Dissostichus mawsoni). The R codes used in this procedure have been made available to the Secretariat.

This paper proposes extending the trial of daytime setting of longlines between 15 and 30 April in the Patagonian toothfish longline fishery in CCAMLR Statistical Division 58.5.2 to encompass the 2013/14 and 2014/15 fishing seasons.  Extending the trial for a further two years will enable sufficient daytime fishing effort to occur in the trial period to ensure there is a proper basis for assessing whether to allow daytime fishing between 15 and 30 April on a permanent basis.

This paper proposes extending the fishing season in the Patagonian toothfish longline fishery in CCAMLR statistical division 58.5.2 on a trial basis during the 2013/14 and 2014/15 fishing seasons by a further two weeks. This would increase the fishing season to include the period from 1 to 14 November as part of the post-season extension with day/night setting allowed.

We have identified key uncertainties in the stock assessment of Antarctic toothfish in Subareas 88.1 ad 88.2 which could be addressed using specific research surveys and other dedicated voyages. Given the continued uncertainty arising from the relative paucity of abundance data, age and length composition data and gonad data for toothfish in some geographic areas and seasons, and from lack of sufficient data to understand toothfish movements and stock structure, we believe that research of this kind should be given a high priority by the Scientific Committee. We recommend the Scientific Committee invite members to submit proposals to address these uncertainties, and consider mechanisms by which coordinated research plans involving multiple Members could be generated either by the Scientific Committee or in its working groups.

We review tagging protocol changes made in 2012/13 and provide further recommendations to improve the quality of collected tagging programme data, and conduct research to improve effective tag releases and recoveries. We also provide a tagging training module to inform vessel observers and crew on tagging procedures.

We present a spatially explicit age-structured population dynamics operating model for Antarctic toothfish in the Ross Sea region, for a medium scale spatial resolution (189 spatial cells) covering the Ross Sea region. In this model run we spatially restrict the stock to cells where at least 5% of the depth is deemed suitable as habitat for toothfish (120 cells – semi-restricted model), and compare with previous models where the stock was either restricted to the fished cells only (65 cells – restricted model) or allowed to occupy the entire Ross Sea region including depths outside of those normally considered suitable habitat for toothfish (unrestricted model). The semi-restricted model provides a plausible distribution hypothesis in-between the two extreme bounding hypotheses represented by the previously presented restricted and unrestricted models (Mormede et al. 2013).

The most plausible model is the one that restricts toothfish distribution to depths which are known to provide suitable toothfish habitat. This is unsurprising because the model utilises fishery-dependent data and has no information about the distribution of toothfish in areas where no fishing has occurred, such that the unrestricted model estimates fish movements into cells outside of the fished area including those with implausible depths for toothfish.
 
Further data collection would be useful to improve the parameterisation of the model, in particular making collection of gonad weight measurements routine on all fishing vessels, surveying likely spawning grounds during winter, and obtaining fishery or survey data from areas not fished to date.

We propose that the modelling platform presented here can be used to test the likelihood and examine the consequences of alternative fish movement hypotheses given the data available. For a given movement scenario it can also be used to examine the likely effects on the toothfish stock assessment of alternate spatial management options affecting the distribution of fishing effort, data collection, and/or tagged fish releases.

This paper presents the Bayesian sex and age structured population stock assessment of Antarctic toothfish (Dissostichus mawsoni) in Subarea 88.2 covering SSRUs 88.2C, D, E, F, G, and H (SSRUs 88.2C–H). We examined several models including the 2013 implementation of the 2011 base case (R1), using the revised data selection method (R2), using a logistic selectivity for the northern fishery (R3), down-weighting the age data (R4), and having annual age length keys in the north (R5).

The stock assessment has strongly conflicting data: age frequency data push the biomass high, data from tags released in 2010, 2011 and 2012 suggest a much lower biomass, and data from tags released from 2004 to 2009 suggest an intermediate biomass.

The two models (R1 and R2) which estimate a higher biomass are those where the age data were more influential. However, these age data are not reliable because a single age length key has been applied. When annual age-length keys are applied there was a strong shift towards younger ages (R5) and lower biomass. The remaining two models (R4 and R5) suggest a substantially lower biomass than previously estimated, mainly due to the signal in the last three years of tag data. These are the data in which we have the highest degree of confidence for this fishery, due to improvements in tagging protocols and data collection.

We believe that there is sufficient conflicting information, and uncertainty in the age data, to warrant a decision to adopt the model which down-weights the age data in favour of the tag data as the base case. We therefore recommend that model R4 is used for providing management advice. In this model, the initial stock biomass is estimated at 6590 t (95% confidence interval 4800 – 9190 t), stock status is at 65%Bo (CI 52%–75%) and the yield based on the CCAMLR Decision Rules is 266 t. We also recommend that further ageing is carried out by fishing members involved in the fishery to allow annual full age length keys for all fisheries for future assessments.