In the report we inform shortly on the activity in the Ukrainian Vernadsky Antarctic Station area on service of CEMP cameras and installation ARGOS satellite tags in penguin colonies as part of the CEMP projects run by USA, Argentina, Poland and Ukraine 'Establishing a CEMP Camera Network in Subarea 48.1' and 'Tracking the overwinter habitat use of krill dependent predators from Subarea 48.1'. In season 2016/17 biologists winteres made service for nine cameras and downloaded pictures of 2015/16 and 2016/17 seasons from cameras installed in penguine colonies at Petermann, Yalour and Galindez Islands. Cameras overwintered succesfully and data for full breeding cycle of penguin in 2016/17 season have been collected. Fifteen ARGOS satellite tags have been installed in the adult gentoo penguins in Galindez Island colony. Photo sequences for all breeding activity at three sites have been processd partly only due to late arrival of Ukraine expedition to Kyiv. The training of new winterers-biologists who will work at Vernadsky in 2017/18 season has been provided for CEMP methods and for visual observations in Galindez colony for future camera validation

Antarctic krill (Euphausia superba) and salps are major macroplankton contributors to Southern Ocean food webs and krill are also fished commercially. Managing this fishery sustainably, against a backdrop of rapid regional climate change, requires information on distribution and time trends. Many data on the abundance of both taxa have been obtained from net sampling surveys since 1926, but much of this is stored in national archives, sometimes only in notebooks. In order to make these important data accessible we have collated available abundance data (numerical density, no.m−2) of postlarval E. superba and salp individual (multiple species, and whether singly or in chains). These were combined into a central database, KRILLBASE, together with environmental information, standardisation and metadata. The aim is to provide a temporal-spatial data resource to support a variety of research such as biogeochemistry, autecology, higher predator foraging and food web modelling in addition to fisheries management and conservation. Previous versions of KRILLBASE have led to a series of papers since 2004 which illustrate some of the potential uses of this database. With increasing numbers of requests for these data we here provide an updated version of KRILLBASE that contains data from 15194 net hauls, including 12758 with krill abundance data and 9726 with salp abundance data. These data were collected by 10 nations and span 56 seasons in two epochs (1926–1939 and 1976–2016). Here, we illustrate the seasonal, inter-annual, regional and depth coverage of sampling, and provide both circumpolar- and regional-scale distribution maps. Krill abundance data have been standardised to accommodate variation in sampling methods, and we have presented these as well as the raw data. Information is provided on how to screen, interpret and use KRILLBASE to reduce artefacts in interpretation, with contact points for the main data providers.

This study aims to improve understanding of spatial and temporal variability in krill fishing activity in MPA Planning Domain 1, towards the development of a ‘cost layer’ and additional information for use in Marxan analyses and subsequent MPA planning activities. We provide further detail on the location of areas of high concentration of krill catches or ‘hotspots’ in current fishing activities, by examining variability in catch locations and magnitude across an 11-year period from 2005/2006 to 2015/2016.We also analyze the distribution of fishing hotspots at different time scales in Domain 1 and investigate whether these could be incorporated into a single cost layer that adequately accounts for the variability in fishing dynamics, to assist in the MPA planning process. We conclude that the development of a single cost layer that adequately represents fishery patternsfor Domain 1 is not feasible; however, krill fishing catch and effort information is an integral part of the Domain 1 MPA planning process and should be incorporated into the consideration ofrequired management provisions once priority areas for conservation have been identified.   

This report summarizes the results of a series of international workshops specifically develop to assist in the Domain 1 MPA planning process, including the 2012 - First International Workshop held in Valparaiso, Chile, (WG-EMM 12/69); the 2013 – Binational Workshop (Chile-Argentina) held in La Serena, Chile (WG-EMM 14/40), the 2015 - Second International Workshop for identifying Marine Protected Areas (MPAs) in Domain 1 of CCAMLR held in Buenos Aires, Argentina (WG-EMM 15/42); and the 2016 - Informal Workshop on Domain 1 MPA held in Bologna, Italy (WG-EMM 16/73).

This report has been compiled by the authors based on expert discussions held during the above workshops. The list of participants for these Workshops can be found in Annex 3.

This draft is aimed to describe the process for the designation of an MPA in Domain 1 led by Argentina and Chile. The process has resulted in the compilation, analysis, integration and display of a large amount of information, not only contributing to the best science available but also providing a platform for the sharing and visualization of information. We highlight the multinational approach in all stages of the decision making process towards identifying Priority Areas for Conservation (PAC) in Domain 1. A technical description of the software and analyses used for the identification of the PAC is provided. Thereafter, considerations of both ecological and management components are described to finally arrive to a Domain 1 MPA model to be discussed among members during the EMM-2017. The MPA management will be done in accordance with the Objectives of the Convention. Having in consideration all the issues mentioned above, a multinational Research Steering Committee is proposed in order to engage all interested Members in the discussion and development of a Research and Monitoring Plan, thus reaching the best available solution for the management of the proposed MPA, one that takes into account conservation objectives, as well as other ecosystem services, such as krill fishing.

With the recommencement of commercial krill (Euphausia superba) fishing in CCAMLR Divisions 58.4.1 and 58.4.2, off the coast of East Antarctica, Australia is adapting the risk assessment framework used in Area 48 to assess the risks involved in any redevelopment of a krill fishery and evaluate whether the current management procedure has a high likelihood of achieving CCAMLR’s objectives in this region. This paper describes the first steps to populating the risk assessment framework with the best available scientific data on abundance of krill predators, foraging activity and the historical distribution of krill catch and effort. We have pulled together an initial collection of existing krill predator distribution models and have produced new preliminary models for krill and various predator species. We request the Working Group review this work, prioritise data sets and further analyses, and consider a process to allow the completion of a first risk assessment for the krill fishery in this region in the near future.

The Antarctic krill fisheries have evolved to operate in ever more concentrated geographical areas of predictable high krill densities, and knowledge about trends and variability in krill biomass, distribution and swarm structure on these local scales seems critical for assessing the three-way interactions between krill, krill-dependent predators and the krill fishery. Acoustic data collected from the fishing vessels might help provide such insight. In the present work, the dynamics of krill with regards to abundance and distribution as well as swarm characteristics and diel vertical migration were studied using acoustic data from the Chinese krill fishing vessel ‘Fu Rong Hai’ operating in the Bransfield Strait from late austral summer (February) to autumn (March to May), and its potential impact on the fishing efficiency were also examined. Only detected and delineated swarms were included in the integration assuming they constituted the bulk of krill biomass. Our results indicated a major shift in mid-April which included increased biomass, increased vertical distribution of swarms, a shift in diel vertical migration from upward migration during daytime in February-March to downward migration during daytime in May, and also a shift in the length distribution of krill. The results strongly support recent findings of an inshore krill migration from summer to winter, and indicates that the migration is also followed by a gradual shift in swarming behavior. Our results further showed that the fishing vessel operated in areas of very high swarm encounter rates, and that the trawling occurred on the highest krill concentrations, indicating that the fishing strategy of this vessel was to target krill swarms of maximum density. In addition, the functional relationships between the catch per unit effort (CPUE) and potential impact factors showed that the catching efficiency increased over the season and was positively related to both krill packing density and acoustic biomass, but negatively related to the center depth of gravity. The results demonstrate that new understanding of krill seasonal dynamics and its influence on fishing efficiency can be gained based on data collected from a fishing vessel under operation, and underlines the utility of a full implementation of the SG-ASAM plans for data collection from fishing vessels.

The analysis of euphausiid larvae collected during summer 2011 in the Weddell Scotia Confluence región, in 2012 on the WAP and Scotia Sea and 2014 on the South Orkneys Platform show a strong decrease in the abundance of Euphausia superba larvae and an increase in Thysanoessa macrura in 2011 and 2012 and a strong increase in the abundance of E. superba in 2014. Oceanographic conditions didn’t show any significant variations respect historical information. The analysis was conducted using cluster analysis finding that the associations of the different larvae and especies correspond to the available information. The densities observed during the cruises were compared with densities obtained in 1981 and 1995 calculating expected values at a fixed grid of points. The significance of the differences was established using a binomial test on their signs.

The usability of CPUE data as Antarctic krill abundance index was a widely discussed issue. Many studies suggested the CPUE data should be standardized before using as abundance/biomass index. We tried to develop general additive models to standardize the CPUE data collected from Chinese fishing vessels during 2009/10 -2013/14 seasons. We also compared the CPUE data and acoustic data collected by Chinese fishing vessel Furonghai in 2015/16 season. The result showed that the CPUE data could be impacted by fishing activity, environmental and spatial and temporal factors. Ten days and monthly could be fine temporal scales for CPUE statistic. Catch per hour data could be more close to the acoustic data than catch per day data. The veridical distribution and movement of krill could be important source of differences between CPUE and acoustic data. The uncertainties and biases of CPUE data implied that CPUE used to indicate the krill stock abundance should be very caution. However, the dynamics of CPUE could indicate the changing trends of the density of krill in the water close to sea surface, which may be concerned by krill feedback management.

The attached draft Climate Change Response Work Program addresses the remaining Terms of Reference of the Intersessional Correspondence Group (ICG) to develop approaches for integrating considerations of the impacts of climate change into the work of CCAMLR (components of TORs 7 and 8). It aims to build on related work of the Commission, SC-CAMLR and its working groups, and to link with related work being undertaken by the Committee for Environmental Protection (CEP).