Antarctic krill (Euphausia superba) are considered to be one of the key species in the Antarctic marine food web, being prey to a wide variety of dependent species as well as being commercially harvested. The commercial exploitation of krill is managed under the direction of CCAMLR (Commission for the Conservation of Antarctic Marine Living Resources), utilising results derived from the CCAMLR generalised yield model and krill yield model (Constable and de la Mare, 1996; Butterworth et al. 1994). A key parameter of the krill yield model is an estimate of the pre-exploitation biomass of krill (B₀). The current estimate of B₀ which is used by CCAMLR in the model is derived from the CCAMLR-2000 synoptic acoustic survey (hereafter CCAMLR-2000) in the Food and Agriculture Organisation (FAO) statistical subareas 48.1, 48.2, 48.3 and 48.4 (Hewitt et al. 2004; Watkins et al. 2004). The design, planning, implementation and subsequent first analysis of the CCAMLR-2000 B₀ estimate were initiated in 1995 and documented within the CCAMLR WG-EMM reports (SC-CAMLR-XIV, Annex 4, Paragraph 4.61;  SC-CAMLR-XV, Annex 4, Paragraphs 3.72 to 3.75, 8.8; SC-CAMLR-XVI, Annex 4, Paragraphs 8.109 to 8.129; SC-CAMLR-XVII, Annex 4, Paragraphs 9.49 to 9.90; SC-CAMLR-XVIII, Annex 4, paragraphs 8.41 to 8.49) as well as papers tabled at those meetings (CCAMLR 1995; 1996; 1997; 1998; 1999). In particular two workshops, one planning (SC-CAMLR-XVIII, Annex 4, Appendix D) and one analysis (SC-CAMLR-XIX, Annex 4, Appendix G), provide background and detail to the survey design, implementation and original analysis (CCAMLR 1999; 2000). Since 2000 a number of re-analyses, improvements and corrections to the acoustic protocol to determine krill density have been tabled at the CCAMLR WG-EMM and SG-ASAM meetings. This document aims to summarise those changes and their rationale.

For ease of reading, this document has been separated into nine sections: Survey design; Acoustic data collection; Acoustic data processing; Target strength (TS) model and implementation; Target identification; Echo integration; Conversion of acoustic backscatter to areal biomass; Estimation of total biomass from areal biomass; and Estimation of uncertainty. Key methods and their derivations are highlighted in bold. This document does not describe a re-design of the CCAMLR synoptic survey, but details changes to the initial analysis, and the procedures (Table 1) which lead to the current estimate of B₀.

We report on preliminary analyses to estimate macaroni penguin consumption of prey in Subarea 48.3 during the period when penguins are constrained by breeding. We show that the greatest levels of consumption occur during incubation and pre-moult, but that there are also evident increases towards the end of guard and the end of crèche. Our initial results indicate that levels of krill consumption are comparable with some previously reported estimates, but with some important differences. This work represents a collaborative study by scientists working through WG-EMM-STAPP. We propose that similar such analyses should be undertaken for the other krill-eating penguin species breeding in Area 48, and that such analyses are best undertaken collaboratively.

The authors present to the Working Group on Ecosystem Monitoring and Management (WG EMM) the scientific background and justification for the development of a marine protected area (MPA) in the Weddell Sea planning area. In accordance with the recommendations by WG-EMM-14 (SC-CAMLR-XXIII, Annex 6), this was done in three separate documents (Part A-C). WG-EMM-16/01 (Part A) sets out the general context of the establishment of CCAMLR-MPAs and provides the background information on the Weddell Sea MPA (WSMPA) planning area; WG-EMM-16/02 (Part B) informs on the data retrieval process and WG-EMM-16/03 (Part C) describes the methods and the results of the scientific analyses as well as the development of the objectives and finally of the borders for the WSMPA.

Earlier versions of Parts A-C were already presented at the meetings of EMM and SC-CAMLR in 2015. The Scientific Committee did recognise that the body of science of the background documents (SC-CAMLR-XXXIV/BG/15, BG/16, BG/17) provides the necessary foundation for developing a WSMPA proposal (SC-CAMLR-XXXIV, § 5.11).

Here, the authors present the final version of Part A to WG EMM. Part A has undergone final editorial corrections in the 2015/16 intersessional period and contains (i) a synopsis in terms of the establishment of MPAs (chapter 1); (ii) a description of the boundaries of the WSMPA planning area (chapter 2); (iii) a comprehensive, yet succinct, general description of the Weddell Sea ecosystem (chapter 3); (iv) and finally a guidance regarding the future work beyond the development of the scientific basis for the evaluation of a WSMPA (chapter 4).

In April 2016 Southern Ocean Network of Acoustics (SONA) hosted a workshop of its partners and invited guests to discuss acoustic processing methods and future directions. Five agenda items were discussed: Acoustic data/data coverage and availability; Data processing techniques and comparison; Metrics of data quality and DOIs; Summary statistics and a way forward for regional comparison; and Current and future collaboration and opportunities. This report is a summary of those agenda items.

This study used a Marxan approach to identify important benthic areas within MPA Planning Domain 1 (Western Antarctic Peninsula and Southern Scotia Sea). The results do not constitute any proposal for candidate MPAs, however they may be useful in contributing additional information towards the Domain 1 MPA planning process. Several core areas important for benthic conservation are described according to habitat-forming features such as geomorphology and bathymetry. The core areas are primarily located west of the Antarctic Peninsula in the Bransfield Strait and north of the South Shetland Islands, and around the South Orkney Islands. Data layers shared with all CCAMLR Members as part of the Domain 1 planning process were used in this study (under the CCAMLR data use and access rules). This study demonstrates the value of shared datasets in facilitating additional, supporting analyses for MPA planning. The range of available data also has relevance to a wide variety of other CCAMLR work, in addition to MPA planning. We therefore recommend that such data should continue to be made available through the CCAMLR website as far as possible, to provide for their use by any Member in MPA-related or other analyses.

The authors considered the inter-annual variability of krill transport factors in the Scotia Sea analysing data from available meso-scale surveys covered the Scotia Sea. The subject of analysis were the geostrophic water masses circulation and krill transport factors, including variability of water masses  (kg / m³) and krill biomass (g / m3) transporting across the survey area.  Obtained estimates were compared with those from CCAMLR 2000 Survey.  It was shown that the presence or absence of krill in subareas/SSMUs in the Scotia Sea is in a greater degree a reflection of the dynamics of krill geostrophic transport, and is not determined by the krill stock state or not determined by the influence of krill fishery.

Analysis of spatial-temporal variability of the CPUE indices for the krill fishery in Area 48 (2006-2015) with using fishery index anomalies, method “Semaphore” and cluster analysis with option“Сoniss” was provided.   Results of this analysis detailed by Subarea 48.1, 48.2 and 48.3 and SSMUs and fishery techniques are considered.

Analysis of the krill spatial distribution characteristics as the important factor for the krill fishery management in Area was performed by Sytov A. being   the CCAMLR Scholarship recipient (mentor Kasatkina S.). The data obtained  from the multiannual Russian observations in the Area 48, including acoustic surveys data, fishery statistics (haul by haul), the data obtained during scientific observation on board fishing vessels (including acoustic and biological observations) were  analyzed for the period from 1980 to 2002. The main results of this analysis are shown.

We analyzed the sea-ice concentration for the southern ice-shelf areas of 48.6 during the latest four seasons using two satellite data, LANCE-MODIS data and AMSR2 of “Shizuku” processed byUniversity Bremen.

Figure 1 shows the overall of the topography and ice condition with Shinsei maru No. 3 trace in 2015/16 season (the detailed trace will be presented at the PowerPoint slide in the WG-SAM-16 meeting).

Figure 2 shows the sea-ice dynamics during the last four seasons (2013-2016) for the two research blocks, 48.6_4 and 48.6_5. The sea-ice concentration during January-March for block 48.6_4 was lowest in 2016, and Japan and South Africa vessels has conducted fishing operation as they scheduled and completed almost all the catch limit allocated.

Figure 3 focused the sea-ice dynamics in and around block 48.6_5 during the latest four seasons. As for 2015/16 season, the fast sea-ice had still occupied the block except for the southern part near the continent in February 1st (Figure 3). Shinsei maru No. 3 had conducted the operations in block 48.6_4 almost all the time in January following the operations in block 48.6_3, then moved to block 48.6_5 in February 4th. However, there had been no appropriate route for her to enter the block, thus she left for the northern part of Subarea 48.6 in February 8th. However, the sea-ice disappeared in the eastern part of the block in February 21st after she left. The sea-ice was becoming thick around whole block in March 11th, but disappeared in the eastern part of the block again in March 21st.

Figure 4 shows the time series of sea-ice concentration during January-March for the latest four seasons in the two research blocks. The sea-ice concentration for block 48.6_4 was much lower throughout the period in 2016 (red line in the upper figure) than the preceding three seasons. The sea-ice concentration for block 48.6_5 stayed at averaged level of the latest seasons during January-February but showed the lowest level in March in 2016 (red line in the lower figure).

As Figures 3 and 4, the sea-ice condition in 2015/16 season was the most favorable to enter 48.6_5 during the latest four seasons. It was however unfortunate that Shinsei maru No. 3 could not enter the research block 48.6_5 because she missed the opportunity to go into the block even though there were apparently free of ice for some part in some timing after late February.

We try to analyze the sea-ice dynamics in relation to environmental factors such as wind and ocean currents to predict the sea-ice condition for the following seasons, which will enable the vessels to conduct the effective research toward the robust stock assessment. We will develop the research plan and make the presentation on that in the coming WG-FSA meeting.

It is important to study its structure because plankton community changes by the environmental changes in the Antarctic Ocean ecosystem. We here applied the metabarcoding method to analyze the biodiversity of zooplankton in the Indian Ocean of Antarctica, Division 58.4.1 in 2014/15. Compared with the previous method, next generation sequencing (NGS) using Miseq platform produces the large amount of reliable data with relatively low cost. Resulting NGS sequencing two different sized zooplankton populations, 40,376 (56 OTUs and 12 species) and 16,525 (62 OTUs and 16 species) contigs were obtained from large-sized (>1 mm) and small-sized (< 1mm) fractions, respectively. Based on the low numbers of “unknown” OTUs, we were able to know that metabarcoding strategy can be possible in the zooplankton survey only if additional barcode data of small-sized zooplankton or those with soft tissue are supplemented. In both fractions, copepods occupied the highest proportions and Calanoides acutus was the major species among them. Although there were a lot of commonly identified species in both fractions, we were also able to identify several fraction-specific species, which provide several useful ecological information examined zooplanktons. The reproduction of spawning grounds may be estimated by the fish OTS originated from the egg or larvae. From this result, we showed the possibility about the large scale zooplankton survey using the NGS technology for its low cost and time for the analysis.