The Pygoscelis penguin colonies census in the Vernadsky Antarctic station area has been provided during 2017-2018 breeding season. The Pygoscelis penguins in the region of research are mainly gentoo penguin, which has formed 14 autonomous colonies with about 13320 of breeding pairs total and about 780 immature penguins. The Adelie specie is much less common in the area and formed 8 nesting colonies with 5300 nesting pairs and 800 immature penguins. Inside of the Adelie penguin specie family, there is significantly higher percentage of birds which not involved in the reproduction process. This fact, to some extent, probably explains the depression of the world population of the Adelie specie, which has been observed throughout the area during recent years. The nesting of the Antarctic penguin in the region of research should be considered a sporadic settlement at a considerable distance from the main range. The gentoo penguin colony at the Green Island possibly could be the southernmost points of the nesting habitat of this specie.

During the 2017 Scheme of International Scientific Observation workshop (WS-SISO), the data collection requirements for krill observers were discussed, with recommendations tabled in the WS-SISO Convener’s Report (SC-CAMLR-XXXVI/08) for amendments to the krill e-logbook used by SISO observers. This paper summarizes the changes to the e-logbook for proposed introduction in the 2019 season.

Antarctic krill Euphausia superba is an ecological key species in the Southern Ocean and a major fisheries resource. The winter survival of age class 0 (AC0) krill is susceptible to changes in the sea-ice environment due to their association with sea ice and their need to feed during their first winter. However, our understanding of their overwintering diet and its variability is limited. We studied the spatio-temporal variability of the diet in 4 cohorts of AC0 krill in the Northern Weddell Sea during late winter 2013 using stomach contents, fatty acids (FAs) and bulk stable isotope analysis (BSIA). Stomach contents were dominated by diatoms in numbers and occasionally contained large volumes of copepods. Many of the prey species found in the stomachs were sea ice-associated. Our results show that the diet of overwintering AC0 krill varies significantly in space and time. Variability in stomach content composition was related to environmental factors, including chlorophyll a concentration, copepod abundance and sea-ice cover. In contrast, FA composition mainly varied between cohorts, indicating variation in the long-term diet. The condition of the AC0 krill was reflected in FA and BSIA analysis, suggesting that the availability of sea ice-derived food sources over a long period may impact the condition of developing AC0 krill significantly. The spatio-temporal availability of sea-ice resources is a potentially important factor for AC0 krill winter survival.

Understanding the energy flux through food webs is important for estimating the capacity of marine ecosystems to support stocks of living resources. This paper provides a summary of a review on currently available Southern Ocean energetic density data. This review is a result of the Southern Ocean Diet and Energetics Database, an initiative of the SCAR Expert on Group Birds and Marine Mammals (EG-BAMM) and the SCAR Expert Group on Antarctic Biodiversity Informatics (EG-ABI), in which data on the diet and energetics of Southern Ocean species is collected to form a centralised database.

We provide a 2^nd update on the progress of our project “Tracking the overwinter habitat use of krill-dependent predators from Subarea 48.1”. The project was initiated with support from the CEMP Special Fund in 2015/16. Of 150 tags purchased in 2016, all have been deployed and the data collection phase has recently concluded. As of 28 May 2018, the last viable tags had ceased transmitting and, as of writing, final data collation is being completed. All valid data from tags that were released in 2017 have been collated and fit to state-space models, allowing estimation of habitat utilization distributions. Tracks for juvenile Adélie penguin deployed in 2018 remain to be analyzed. Preliminary assessments of environmental indices along tracked locations, suggest chinstraps used the warmest locations, while gentoo adults and Adélie juveniles shared similar distributions for SST in 2017. All tracked animals occupied mostly ice-free water during the period of tracking, but several gentoo and juvenile Adélie penguins locations occurred in ice-covered regions. When found in ice-covered regions, sea-ice conditions experienced by gentoo and Adélie penguins were similar. A script to automate extraction of satellite date for tracking data is provided.

The spatial variability of krill flux in the Scotia Sea calculated by using the geostrophic method, is analysed. For this, CCAMLR-2000 international survey data was used. The analysis was carried out in the 0-500 m depth ranges 50 m layers. Water mass geostrophic circulation, spatial distribution of krill density, water flow intensity (m³/s) and krill biomass (g/m3) transported by water flow to the Scotia Sea, were a subject of study.  It is clearly illustrated that the geostrophic krill flux in the Scotia Sea requires both favorable dynamic conditions and availability of krill transported by the water flow from the Pacific ocean Antarctic Area through the Antarctic Peninsula subarea. Calculations indicate that the krill drift through the Antarctic Peninsula area and the South Orkney area   in the Scotia Sea may be incomparably high than the annual catch of krill and the operating catch limits in Area 48.  The special attention was provided to a spatial variability of direction and intensity of krill flux through the Bransfield Strait and the Drake Passage. Results show that developments of krill resource management schemes require a study of the variability nature of its distribution under the influence of geostrophic flux at various space-time scales. The availability of such information is necessary to understand the competitive relationship between predators and fisheries for krill resources.

Baleen whales are important components of the Antarctic marine ecosystem as ‘sea-based’ top predators. Information on their distribution, movement and abundance trend is important as input data for ecosystem modelling studies. Genetic analyses were conducted to investigate the population identity as well the individual identity of southern right whales distributed in summer in the Antarctic Indian sector. The latter analysis was conducted to assess their site-fidelity, sex-specific ranges and abundance based on ‘mark-recapture’ methods in the Antarctic Indian sector (i.e., between 80°-135°E and south of 60°S). In total, 157 biopsy samples were collected as skin biopsies from free-ranging whales during fourteen summer surveys. The DNA was extracted from each biopsy sample, sequenced for 381 nucleotides of the mtDNA control region, genotyped at fourteen microsatellite loci, and the sex determined by the presence of a Y-chromosome specific locus. The mtDNA analysis suggested that whales in the Antarctic Indian sector in summer are closely related to the Australian calving ground. Eight incidences of individual matching (‘mark-recapture’) were detected (four males and four females). Individual matching by multi-locus genotypes was supported by mtDNA, sex determination, and in two cases where pictures were available, by photo-identification. These eight re-captures suggested that individual whales tended to return to the same location in the Antarctic Indian sector in subsequent years. The average longitudinal dispersal ranges were 13°06’ and 7°15’ in males and females, respectively. The time span between the ‘mark’ and the ‘recapture’ ranged from 3-13 years with an average at 7.3 years. Preliminary application of a ‘mark-recapture’ method based on an open population model, resulted in abundance estimate trend in the Antarctic Indian sector similar to those obtained using sighting survey data and the Line Transect Method in the same sector and similar period. However differences were observed in some years, which suggest that some of the assumptions used in the genetic ‘mark-recapture’ method should be further considered in future.

• Juvenile/larval fish taken as bycatch in the Antarctic krill fishery (CCAMLR subarea 48.1, 48.2 and 48.3) were identified by DNA barcoding and results compared with morphological identifications made on vessels by scientific observers.
• A total of 344 fish (primarily in the families Channichthyidae and Notothenidae) were identified using genetic barcoding markers.
• Species level identifications provided by observers were good for the common species Champsocephalus gunnari and Lepidonotothen larseni; however, DNA results show several less common Notothenidae species were identified as L. larseni.
• All of Chaenodraco wilsoni icefish (n=67) identified by an observer were actually Chionodraco rastrospinosus based on DNA barcoding.
• Many of the specimens (n=136) were recorded to family-level by observers; genetic barcoding markers allowed these specimens to be assigned to species level.
• The diversity of fish identified by observers (5 families; 8 species) was considerably lower than with DNA barcoding (7 families; 20 species).
• The impact of potential taxonomic misidentifications on fish bycatch datasets needs to be considered. Developing standardised field guides and additional observer training many improve the accuracy of observer taxonomic assignments.

A dedicated krill survey for CCAMLR Division 58.4.1 during 2018/19 season will be carried out by Japanese research vessel, Kaiyo-maru. No krill biomass has been estimated in the Division since 1996 when Australia conducted BROKE. There are two main objectives of our survey: (1) estimation of krill biomass to update B₀ in the division and (2) oceanographic observations in the area to detect long term changes if any. The krill survey (echosounder and RMT) and subsequent biomass estimation will follow the CCAMLR standard protocol. The survey is international oriented and a cumulative total of 34 researchers from 4 countries are expected to be engaged. An initial plan of the survey was presented to SG-ASAM-17 and WG-EMM-17 as SG-ASAM-17/01 and WG-EMM-17/05, respectively. A revised survey outline (SG-ASAM-18/03) and the details of narrowband (SG-ASAM-18/02) and broadband (SG-ASAM-18/05) acoustic survey methods were presented to SG-ASAM-18. The outcome of the previous discussion is reflected in this document. This revised proposal is presented to WG-EMM-18 with an intention to receive further comments from the participants. Every suggestion will be duly examined and incorporated where relevant in the final plan.

During the 2017 CCAMLR WG-EMM Norway was requested to act towards the industry to ensure catch reporting in accordance with the present conservation measure (CM 21-03) and to investigate potential errors in historical catch report data. As a response, the Norwegian delegation presented a list of actions that would facilitate further consideration and clarification of these technical issues, and these actions were endorsed by the Scientific Committee (SC-CAMLRXXXVI/11). This document presents the outcome of the action steps including onboard experiments and analyses of historical catch data.

Experiments on board ‘Saga Sea’ showed that there is an average delay of approximately 9 minutes between the time krill enters the trawl mouth and the time the same krill enters the holding tanks where catch weight can be first estimated and recorded. Further experiments onboard ‘Saga Sea’ and ‘Antarctic Sea’ to estimate variability in the conversion from krill holding tank volumes to krill biomass indicated that a relative standard deviation of 8-29% should be expected depending on vessel and specific holding tank features.

A previous working document indicated that there have likely been additional delays between the reported catch time and actual catch time since the krill catch is kept in holding tanks before being weighed on the flow scales. Our investigations of historical catch report data showed patterns which likely reflect reporting routines rather than true catch variability and also indicate that the reporting routines have varied between vessels and among officers on board.

The various historical reporting routines are difficult to retrace, and therefore, in order to get an idea about the uncertainty in reported catch weight and position from historical data, we used information about the maximum total capacity of the holding tanks and assumed that all catch records have been estimated based on flow scale measurements. We could then estimate a maximum residence time before the accumulated krill catch is recorded on the flow scales. The maximum residence time decreased with increasing catch rates, ranging from average values of ca. 18 hours for low catch rates to ca. 3 hours for high catch rates. The deviance in catch between original reports and reports reallocated according to estimated krill residence time was approximately normally distributed around a mean value of 1.6 tonnes with ca. 90% of the deviances contained within ±25 tonnes. These results suggest that the reporting delays cause additional uncertainty to any given reported catch value but not major bias. The geographical distribution of reported catch at different spatial scales showed only minor deviances between what was previously reported to CCAMLR and the catch reallocated in the present study using estimated krill residence times.

In summary, the results indicate that the uncertainty associated with the historical reports of catch from these fishing vessels with continuous pumping systems is higher than typically assumed. These data should therefore be used with caution, especially when conducting fine-scale retrospective analyses. When data are aggregated at temporal and spatial scales more pertinent to advisory processes and management, our results suggest that the impacts of the uncertainties in catch weight and spatial distribution are likely to be minor.