The issue of observer coverage in krill fisheries has been the subject of extensive discussion at the Commission for a number of years, as the krill fishery is the only CCAMLR fishery that does not require 100% observer coverage. The Secretariat analysed the level of observer coverage for the past five years comparing the number of days of fishing conducted by vessels in the krill fleet, with the number of days observers were present on vessels as this is a consistent metric that can be applied fleet wide, regardless of fishing method. The results show a 90% level  of observer coverage across the krill fleet, spanning all subareas and seasons.

The reproductive success of southern right whale (Eubalaena australis) depends on body condition and, therefore, on foraging success. This, in turn, might be affected by climatically driven change in the abundance of the species main prey, krill (Euphausia superba), on the feeding grounds. Annual data on southern right whale number of calves were obtained from aerial surveys carried out between 1997 and 2013 in southern Brazil, where the species concentrate during their breeding season. The number of calves recorded each year varied from 7 to 43 (x = 21.11 ± 11.88). Using cross-correlation analysis we examined the response of the species to climate anomalies and krill densities. Significant correlations were found with krill densities (r = 0.69, p = 0.002, lag 0 years), Oceanic Niño Index (r = −0.65, p = 0.03, lag 6 years), Antarctic Oscillation (r = 0.76, p = 0.01, lag 7 years) and Antarctic sea ice area (r = −0.68, p = 0.002, lag 0 years). Our results suggest that global climate indices influence southern right whale breeding success in southern Brazil by determining variation in food (krill) availability for the species. Therefore, increased frequency of years with reduced krill abundance, due to global warming, is likely to reduce the current rate of recovery of southern right whales from historical overexploitation.

Announcement and details of the Third International Symposium on Krill to be held at the  University of St Andrews, Scotland, between June 12 and 16, 2017.

This study aims to provide consistent information to explain the steady declining trend in the number of breeding pairs of Antarctic shag Phalacrocorax bransfieldensis in two colonies on Nelson Island, South Shetland Islands, southern Atlantic sector of Antarctica, which was observed during the 1990s up to the mid 2000s over an overall monitoring period of over two decades. It addresses correspondence between long-term population trends of inshore demersal fish and inshore-feeding Antarctic shags of this area, where an intensive commercial fishery for shag prey once operated. The analysis also includes comparable information on diet (by examination of regurgitated pellets), foraging patterns, and breeding output of shags from the Danco Coast, western Antarctic Peninsula, an area where no commercial finfish fishery has ever existed. Integral study of these parameters there showed that, in Antarctic shags, low breeding success and high foraging effort might imply low recruitment and high adult mortality, respectively, with both factors adversely affecting the population trends of this bird. In line with these premises, the declining trend observed in shag colonies on the South Shetland Islands appears to have been influenced by the concomitant decrease in abundance of two of their main prey, the nototheniids Notothenia rossii and Gobionotothen gibberifrons, due to intensive industrial fishing in the area in the late 1970s. In comparison, no such pattern occurred for the Danco Coast colonies.

This paper summarises progress by WG-EMM-STAPP in estimating krill consumption by air-breathing predators in CCAMLR management units. There have been significant advances in estimating krill consumption by pack-ice seals and penguins since the last update in 2011. Estimates of pack-ice seal abundance are now available for Areas 48, 88 and 58. Krill consumption by crabeater seals, the most important krill-consuming seal species, has been estimated in Areas 48 and 58. Large-scale estimates of breeding penguin abundance are now available for Areas 48, 88 and 58, and a large-scale estimate of non-breeder abundance is now available for Adélie penguins in Area 58. Parametising a bio-energetics model recently developed for breeding Adélie penguins to other species, to non-breeders, and to other regions will allow estimates of krill consumption by penguins to be developed in all Areas in the near future. Work to partition krill consumption by penguins into small-scale management units by developing foraging habitat models is well advanced.

We describe current work to obtain krill consumption estimates for flying seabirds in CCAMLR Divisions 58.4.1 and 58.4.2. We are currently compiling a database of search and count effort for flying seabirds to assess the extent and rigour of existing data, and conducting a large-scale abundance survey of snow petrels. We plan to adapt a bio-energetics model developed for breeding Adélie penguins and apply it to flying seabird species by extending and generalising the code to make it suitable for other species, and searching the literature, or where necessary collecting new data, to estimate parameter input values. We have conducted tracking work on four species in two regions over two years to determine the foraging distribution and to develop predictive foraging-environment models to partition consumption estimates over space.

As a contribution to the work program of WG-EMM-STAPP to estimate krill consumption by predators, this paper presents estimates of krill consumption by crabeater seals off East Antarctica between 64ºE-150ºE, which includes all of Division 58.4.1 and part of Division 58.4.2. Krill consumption by crabeater seals in this region in 1999/00 was estimated to be 3.8 (95% CI 2.4-6.0) million tonnes per year. This represents approximately 20% of the krill biomass estimated from acoustic surveys.

We estimate the total abundance of Adélie penguins foraging in Divisions 58.4.1 and 58.4.2 and provide preliminary estimates of krill consumed by breeding Adélie penguins in these Divisions using a newly developed bio-energetics model.  Our estimate of ~6 million Adélie penguins substantially revises known abundance upwards by including the large non-breeding population and estimating a larger breeding population than was evident from previous work. The population of breeding Adélie penguins was estimated to consume 193,300 (57,700 – 313,700) tonnes of krill during a breeding season (November (arrival) to March (end of moult)). We are currently extending the prey consumption model to estimate the amount of krill consumed by non-breeding Adélie penguins and consumption for the entire population including breeders and non-breeders outside the breeding season.

We developed a bioenergetics model to estimate prey consumption by the Adelie penguin. The model predicts prey consumption throughout the breeding season and incorporates uncertainty in model parameters using Monte Carlo simulation. The model was parametised with data obtained from the CEMP site at Bechervaise Island using 13 years of data, a year when penguins successfully reared chicks, and a year with low breeding success. On the basis of variable breeding success and the proportion of krill and fish in their diet, we estimate that this population consumes 78-406 t of krill and 4-46 t of fish each breeding season.

CEMP data from different sites in Area 48 were used to compare patterns of inter-annual variability as a function of the site location to examine the spatial scale over which CEMP data that have been collected at an individual site reflect changes in the marine ecosystem. Correlations between combined standardised indices (CSI) of summer CEMP parameters were generally positive and the patterns of inter-annual variability of sites in Subreas 48.1 showed an increased level of concordance in the period since 2008. Further expert review of the CSIs from individual sites would be helpful in further clarifying the appropriate spatial scale monitoring data collected as part of CEMP.