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.

Early analyses of CPUE in the krill fishery concluded that it was not a useful index of krill abundance. However, understanding the factors effecting the operation of the krill fishery and the extent to which these reflect changes in krill abundance are key elements of developing feedback management of the krill fishery. This analysis reviewed catch and effort data from the krill fishery for the period 2001 – 2016 (up to 26/5/2016) in Subareas 48.1, 48.2 and 48.3 to determine whether CPUE might be used to produce a fishery-scale performance index. The vessels-specific mean CPUE (log catch (kg) per minute fishing) was estimated using all data for each vessel; an annual index was calculated as the difference between this overall mean and the mean for each year in which the vessel fished. An overall fishery performance index (FPI) was derived from the sum of the vessel-specific indices for each year. The annual FPI for each of the three subareas showed no synchronous relationship with each other and showed differing relationship with the total catch in the same subarea. Comparison of the annual FPI with the krill biomass (from research surveys) and the CSIs from CEMP data suggests (at least qualitatively) some concordance between the performance of the fishery and krill abundance.

The CCAMLR Ecosystem Monitoring Program (CEMP) was established to detect changes in krill-based ecosystems to provide a basis for regulating harvesting of Antarctic living marine resources in accordance with the ‘ecosystem approach’.  This report:

1. summarises CEMP data submissions for the 2015/16 season,

2. presents a CEMP data inventory and metadata overview for Area 48, and

3. outlines the process and methods used to provide data extracts for analyses by Members as part of the development of approaches to feedback management.

This report also includes a number of issues for consideration in relation to the clarification of the format for submitting data on penguin breeding population size and breeding chronology (parameters A3 and A9) as well as the utility of Members providing a site description and relevant details of operational constraints when submitting CEMP data. 

The northern regions of the Scotia Sea demonstrate notable variability in environmental conditions, particularly in the location of the Polar Front. This has a strong influence on patterns of productivity and distribution of plankton, with implications to higher trophic levels, including harvested species. The long-term impact of environmental variability on plankton species composition and abundance has been monitored through conducting a series of Continuous Plankton Recorder (CPR) tows in the South Atlantic Ocean since 2005. The tows were carried out as a collaboration between the British Antarctic Survey (BAS) and the Sir Alister Hardy Foundation for Ocean Science (SAHFOS). This report documents the series of tows that have been carried out to date, which comprises more than 2000 samples from 78 successful tows. Of these, 715 samples have been analysed.  A total of 245 taxa have been recorded, with abundance being far more variable than species composition within and between tows.  In general, phytoplankton were most abundant in the tows taken in November and December but sharp declines occur by April. Diatoms dominated the phytoplankton together with coccolithophores and silicoflagellates. The most commonly recorded copepod was Calanus simillimus, while Thysanoessa spp. was the most abundant euphausiid. An analysis considering the relationship between satellite-derived dynamic height (from which frontal positions may be approximated) and abundance of biomass-dominant species indicated varying affinities, implying that major faunal shifts will accompany any changes to frontal locations in this region.

Increased awareness about the present status of marine systems, including those where fisheries target the prey of natural predators, has led to recommendations about how information on the status of marine predators might be used to inform ecosystem-based management approaches. In the Antarctic, sustained ecological research has generated long-term data on the performance of marine predators, coupled with data that describe the density of their principal prey, Antarctic krill. Here we explore some of the longest time series of such data yet available, using records that were closely matched with consistent ecological time periods. Our results show that: (i) at the larger scale, some predator variables are correlated across sites and they therefore probably reflect common regional ecological conditions; (ii) at smaller scales, other variables depend upon local biological conditions, requiring that managers must evaluate the applicable scale of these predator indices if they are to be used in management decisions; (iii) variability in the krill population is evident at different spatial and temporal scales, some of which is important for predators, indeed when krill density is low, spatial variability and patchiness is probably a more important determinant of foraging success than density per se; (iv) previously documented relationships between predators and krill density are not apparent, suggesting that correlative relationships may break down as data series change in duration. We note that relationships that describe critical density thresholds for prey might not provide adequate management information, particularly at low krill densities. We suggest that a programme of work is needed to better characterise predator requirements, if ecosystem-based approaches are to be reliably implemented.