Given the large scale and hostile condition of the Southern Ocean, which accounts for almost 10% of the world ocean, the collection of scientific data and information in support of effective decision-making process is particularly challenging. To fulfill its obligation to provide scientific recommendations and advice for management, the SC-CAMLR is mandated to encourage and promote cooperation in the field of scientific research in order to extend knowledge of the marine living resources of the Antarctic marine ecosystem. As an important component of the Antarctic marine ecosystem, the vast marine area around east Antarctica is generally recognized as data-poor region. During the discussion in the SC-CAMLR on the marine living resources and the ecosystem in this region, including in the process of development of East Antarctic Marine Protected Areas proposal, the paucity of time-series biotic data that can be used to describe the structure and process of the ecosystem, particularly those relevant to the quantitative assessment of some important fish and krill stocks, has been reiterated by members. For example, WG-EMM-10/26, and SC-CAMLR-XXX/11, etc. 

The Regional Fishery Body Secretariats' Network (RSN)  is a unique coordination mechanism consisting of Regional Fishery Advisory Bodies (RFABs) and Regional Fishery Management Organizations (RFMOs) from around the world. The paper provides a brief overview of RSN, its scope and activities that have the ultimate goal of promoting and highlighting the essential role of regional cooperation for fishery and aquaculture development and sustainability. CCAMLR Members are invited to note the scope and work of RSN and consider the benefit of CCAMLR participation in RSN.

A preliminary integrated stock assessment model was constructed for Dissostichus mawsoni at the research block 48.6_2, as a test run for integrated assessment model for stock assessment of D. mawsoni at Subarea 48.6. Our preliminary analysis is problematic as a stock assessment, but indicates future tasks for improvement: further sensitivity analysis of IUU, addition of ageing data and modeling of migration.

This document is based on the Research proposal for Dissostichus spp. in Subarea 48.1 by the Ukraine (WG-SAM-2019/28), which was presented and discussed at the meeting of the Working Group on Statistics on Statistics, Assessments and Modelling (Concarneau, France, 17 to 21 June 2019).

One of the outcomes of the Capacity-Building Workshop hosted by South Africa was the development of the applicable pro-forma and draft Deed of Funding. These documents are attached.

Information available in the CCEP on incidents of non-compliance with CM 26-01 paragraph 6, that prohibits dumping or discharging offal and discards south of 60°S, appear to be the result of mechanical failure. The information on offal management practices from other organisations relate to how and when offal should be discharged and largely reflects the provisions of CCAMLR’s CM 25-02, CM 25-03. The lack of a common theme in the relatively small (and declining) number of such reports do not indicate a specific action required to improve the implementation of CM 26-01 paragraph 6.

Electronic Monitoring on fishing vessels is increasing globally and is seen as an efficient method of assisting reliable reporting in commercial fisheries. These systems have been traditionally focused on the need to independently meet regulatory and market demands for transparency and accountability, but an increasingly important consideration is the contribution such systems can make to effective management by increasing the amount and quality of scientific research data that can be supplied from commercial fishing vessels.

This paper describes initial development work and presents several examples demonstrating the use of EM to collect research data in the CCAMLR managed Ross Sea toothfish fishery by New Zealand. Following the success of this work and other trials undertaken by other New Zealand vessels, we suggest that EM is further used to help provide better scientific research and monitoring data.

The Amundsen Sea region toothfish fishery has been operating since 2003. The biological characterisation of the fishery showed a truncation of the right-hand limb of the age distribution between 2004 and 2014. Few age data are currently available after 2014. We recommend that further ageing of toothfish in the ASR be made a priority to develop annual age-length keys and age frequencies. We further recommend that catch limits in the ASR be calculated following the trend analysis rules developed by WG-FSA for research blocks (CAMLR-XXXVI 2017, Annex 7 paragraph 4.33). The estimated catch limits, based on the one-year Chapman estimates and allowing a maximum of 20% in the catch limit for 88.2H and research block 882_2 are:

• 882H: 240 t catch and allowing a maximum of 20% change in the catch limit from 200 t.
• Research block 882_2: 288 t catch and allowing a maximum of 20% change in the catch limit from 240 t.

We note that research blocks 882_1, 3 and 4 used the CPUE by seabed area analogy in the past, which has been calculated by the CCAMLR Secretariat previously using the agreed method for research blocks in other areas. We have not updated the calculations in this report.

The reconciliation of CDS data with monthly fine-scale catch and effort data has demonstrated the effectiveness of the CDS to trace the catch of toothfish caught in the CCAMLR Convention Area. Whilst some variability has been observed amongst vessels, members have been contacted and dialogue is ongoing.

We update the estimates of the growth and length-weight parameters for Antarctic toothfish (Dissostichus mawsoni) in the Ross Sea region (Subareas 88.1 and SSRUs 88.2AB). We present revised estimates of the von Bertalanffy growth curves, estimates of mean length at age using maximum likelihood estimation (MLE), and the length-weight relationship based on available CCAMLR SISO data collected from fishing operations in the Ross Sea region.

Estimates of growth and length-weight were similar to those previously used, however there was some suggestion that the shape of the growth curve may be better approximated by the MLE mean length at age relationship rather than by the von Bertalanffy equation. Stock assessment model estimates of B₀ and 2017 spawning stock biomass (B₂₀₁₇) and stock status (%SSB₂₀₁₇) were lower than with the previous von Bertalanffy relationship. But estimates of %SSB₂₀₁₇ were very similar between the revised von Bertalanffy and the MLE mean length at age model. In this case, the model conclusions were very similar and either of the updated relationships may be adequate parameterisations in the Ross Sea region stock assessment model.

Investigation of residual patterns in the fits to the relationships showed no evidence of systematic change in these parameters over time.