CCAMLR

This paper addresses work conducted on the Mori-Butterworth multi-species model of the Antarctic ecosystem subsequent to the Ulsan meeting of the IWC Scientific Committee. Points raised about the model during that meeting are addressed in turn. Results are quoted that suggest that krill is indeed unable to fully utilise the primary production available. The precision of parameters estimated when fitting the model to abundance and trend data is reported. The model is extended to include an “other predators” variable (reflecting squid, fish and seabirds) so that the crabeater seal variable does not have to act as a surrogate for these in addition to the seals themselves. This results in an improved fit of the model to available abundance estimates for crabeater seals. A list of topics for possible further work on the model is presented. The development of an improved set of abundance and trend estimates for the various krill predators is seen as a priority for improving the reliability of current models, and it is suggested that this should be a key focus of the proposed joint IWC-CCAMLR workshop on this topic.

At the 2005 Scientific Committee (the Committee) Meeting (CCAMLR), Norway indicated that a Norwegian-flagged vessel, “Saga Sea” would be fishing for krill in the 2005/06 fishing season using modified gear and trawl system. The Committee agreed that this new technology would not be considered a ‘new and exploratory fishery’ if a monitoring system was implemented that provided adequate information on effort, catch characteristic and the broader ecosystem impacts of this new technology. In response to these concerns a monitoring system has been developed in collaboration between Norway’s Institute of Marine Research (IMR) and the UK’s Marine Resources Assessment Group and will be implemented onboard by a UK CCAMLR Scientific and National Observers.

Satellite telemetry was used to determine the winter movements and distributions of eight chinstrap penguins known to breed at one of two colonies in the South Shetland Islands, Antarctic Peninsula region during the 2000 and 2004 austral winters. Six birds from a breeding site in Admiralty Bay on King George Island (620 10’ S, 580 27’ W) were instrumented with satellite tags following their annual molt; similarly, two birds were tagged at their breeding site on Cape Shirreff, Livingston Island (620 28’ S, 600 46’ W). Chinstrap penguins were tracked successfully for one to six months following dispersal from their respective breeding colonies using the ARGOS satellite system. Data analyses revealed that 4 of the birds instrumented in the 2000 winter, two from each colony, foraged largely on the shelf to the north and northeast of the South Shetland Islands. Similarly, two birds tagged at Admiralty Bay in 2004 also dispersed to the Drakes Passage side of the South Shetland Islands. In contrast to the inshore locations utilized by all the penguins in 2000, both of the 2004 winter birds foraged well offshore, 350 to 500 km north of the Islands. Bathymetry and hydrological data, including SST and geostrophic velocities, suggest that the chinstrap penguins used markedly different winter foraging habitats in the 2000 and 2004 winters. The final two chinstrap penguins from Admiralty Bay, one from each winter, proceeded directly to the Elephant Island area and spent the next 2-5 months continually migrating eastward. Both of these penguins followed the Scotia Arc with the chinstrap penguin tagged in 2004 tracked to the vicinity of the South Orkney Islands where its signal was lost in April, a distance of 800 km from its breeding colony. The bird tagged in the 2000 winter continued towards the South Sandwich Islands until its signal was lost at 580 30’ S, 360 10’ W in late July, over 1300 km from its breeding colony. The migration path of both these birds was remarkably similar to the only other record of a chinstrap penguin’s winter migration reported by Wilson et al. (1998). Our results suggest that chinstrap penguins breeding in the same colonies during the summer have different migratory routes and winter habitats. The different migratory routes may reflect individual ties to different ancestral epicenters of chinstrap populations; one older and local in the South Shetland Islands and one relatively recent, arising from the emigration of chinstrap penguins that occurred during the expansion of this species in numbers and range in the middle of the past century.

A multidisciplinary, single-ship survey of CCAMLR Division 58.4.2 was conducted in January-March 2006, during which time multifrequency echosounder data were collected for the purposes of estimating the biomass (B₀) of Antarctic krill (Euphausia superba). The mean density of E. superba, integrated to 250 m depth across the survey area (1,566,157 km²), was 10.15 g m^-2. The total biomass was estimated to be 15.89 million tonnes with a CV of 47.93%. Most of the E. superba detected (80%) were in relatively weak aggregations (s_A <100 m² nmi^-2 for each 2 km-alongtrack integration interval), with 50% of integration intervals containing backscattering values <10 m² nmi^-2. Half of the biomass was found within 100 km of the 1000 m isobath, although aggregations often extended to the Northern ends of the transects at 62°S. The majority of acoustic detections were in the top 100m of the water column, centred around 50 m depth.

This document outlines the preliminary results of an Australian survey of CCAMLR Division 58.4.2 (the South West Indian Ocean Sector of the Southern Ocean 30-80°E) in January-March 2006, which was designed around an acoustic biomass survey for krill and a large-scale oceanographic survey. The survey is intended to produce a new estimate of krill biomass (B0) for this Division so that a revised precautionary catch limit can be established by CCAMLR. The survey utilised a standardised design as adopted in previous B0 surveys in the CCAMLR Area and was designed so that the results would be compatible with the 1996 BROKE (Baseline Research on Oceanography, Krill and the Environment) survey of the adjacent CCAMLR Division 58.4.1 which collected information on a wide range of ecological parameters. The survey was conducted from a single ship, the RSV Aurora Australis, and consisted of 11 meridional transects, between 30° and 80°E. On each transect a range of underway data were obtained and on six transects detailed sampling was conducted at predetermined stations. This background paper provides an overview of what was achieved by this survey; the detailed results are currently being analysed and are being prepared for a special Issue of Deep-Sea Research for publication in 2008.

We report on the further development of a carbon-budget trophic-model of the Ross Sea with which to investigate effects of the fishery for Antarctic toothfish (Dissostichus mawsoni). The Ross Sea is a low primary production system, with production being localised in space and time. In the relative absence of krill, Antarctic silverfish (Pleuragramma antarctica) are probably the major middle-trophic level link between primary production and the larger predators. Mesozooplankton (mainly copepods), and demersal fish (especially, Macrourus whitsoni, Bathyraja eatonii, Chionodraco hamatus, C. antarcticus) are other key linking species. The trophic model presented here is not complete and should be considered a work in progress. Overall, the model is close to balance, with total exports of organic carbon (mainly respiration) exceeding primary production by 7%. However, individual groups are generally not balanced, due in part to limited information on diet fractions of Ross Sea organisms. Methods to adjust diet fractions to take into account the relative abundances of prey items are suggested but not applied. The current version of the trophic model suggests that Antarctic toothfish have the potential to exert considerable predation pressure on some species of demersal fish. The significance of toothfish in the diets of predators (especially Weddell seal, type-C killer whale, sperm whale) cannot be tested reliably by the current version of the model, which is not spatially or seasonally resolved, and does not consider sub-populations of predators. More complete information on the abundances and diets of top predators in the Ross Sea are needed, especially with regard to the spatial, seasonal and interannual variability of these properties, and the population structures. Other recommendations for fieldwork, and work currently underway or planned by New Zealand scientists in the Ross Sea, are given.

An assessment of the environmental processes influencing variability in the recruitment and density of Antarctic krill (Euphausia superba DANA) is important as variability in krill stocks affects the Antarctic marine ecosystem as a whole. Naganobu et al. (1999) had assessed variability in krill recruitment and density in the Antarctic Peninsula area with an environmental factor; strength of westerly winds (westerlies) determined from sea-level pressure differences across the Drake Passage, between Rio Gallegos, Argentina, and Base Esperanza, at the tip of the Antarctic Peninsula during 1982-1998. Fluctuations in the westerlies across the Drake Passage were referred to as the Drake Passage Oscillation Index (DPOI). They found significant correlations between krill recruitment and DPOI. Additionally, we calculated a new time series of DPOI from January 1952 to March 2006. We also tried to making comparison between DPOI and oceanic condition of the surface layer around the South Shetland Islands, and suggested response from DPOI to the oceanic condition.

A Spatial Multi-species Operating Model (SMOM) of the underlying krill-predator-fishery dynamics is developed in response to requests for scientific advice regarding the subdivision of the precautionary catch limit for krill among 15 small-scale management units (SSMUs) in the Scotia Sea to reduce the potential impact of fishing on land-based predators. The model is intended to complement the outputs from the KPFM. The model includes all 15 SSMUs and uses an annual timestep to update the numbers of krill in each of the SSMUs, as well as the numbers of predator species in each of these areas. The model currently includes only two predator groups (penguins and seals) but is configured so that there is essentially no upper limit on the number of predator species which can be included. Given the numerous uncertainties regarding the choice of parameter values, a Reference Set is used in preference to a single Reference Case operating model. The initial Reference Set used comprises 12 alternative combinations that essentially try to bound the uncertainty in the choice of survival estimates as well as the breeding success relationship. The model is coded in AD Model Builder and quickly generates large numbers of stochastic replicates to explore different hypotheses such as that related to the transport of krill. The SMOM developed here is intended for use as an operating model in a formal MP framework described in an accompanying paper. Different MPs are simulation tested with their performances being compared on the basis of an agreed set of performance statistics which essentially compare the risks of reducing the abundance of predators below certain levels, as well as comparing the variability in future average krill catches per SSMU associated with each MP.

This report presents results from a pilot study to investigate the use of acoustics to estimate middle trophic level prey organisms (e.g., krill and mesopelagic fish) in the Ross Sea. Single frequency (38 kHz) acoustic data were available from New Zealand longline vessels participating in the exploratory fishery for toothfish in 2002–03 and 2005–06, and multifrequency (12, 38, and 120 kHz) acoustic data were collected from the research vessel Tangaroa during a voyage to the western Ross Sea in February–March 2006. Analyses were carried out to assess data quality, describe different mark types, and quantify spatial and vertical distribution of acoustic backscatter in the upper 1000 m of the water column.
There were clear spatial patterns in the amount and type of mesopelagic backscatter observed. There was much more backscatter in the upper 1000 m and a wider variety of mark types north of 67° S. Common mark types in the northern region included a surface layer at less than 50 m depth, schools and layers centred on about 200 m and 400 m depth, and a diffuse deep scattering layer centred at 750 m depth. Average acoustic density was lower south of 70º S, and most of the backscatter was from schools and layers shallower than 100 m. Near bottom marks were associated with areas shallower than 1000 m on the Ross Sea shelf edge. In general, the amount of backscatter observed in the Ross Sea was much lower than that observed in shelf areas off New Zealand (Chatham Rise and Campbell Plateau).
Little direct information is available on the species composition of different mark types in the Ross Sea. However, different acoustic responses across the three frequencies available on Tangaroa provided some clues about the likely identity of the key scatterers. Marks shallower than 100 m depth were typically much stronger on 120 kHz than on 38 kHz, and weak on 12 kHz. This type of acoustic response is typical of krill or other large zooplankton. Schools and layers at 200–400 m depth showed a more consistent response across all three frequencies and may have been associated with small fish. This study identified key areas and mark types for further research, including directed sampling, and showed how fishing vessels could be used to opportunistically collect acoustic data.

A standardized krill net sampling survey was conducted in the Lazarev Sea (Subarea 48.6) in December 2005. Krill densities were low in the Lazarev Sea. No substantial day/night differences were observed in the catches. Spatial distribution of krill density and size/age classes is discussed for the Lazarev Sea. Recruitment indices were calculated for one-year-old (R1) and two-year-old krill (R2), showing high values for both recruitment indices. New information is given on the development of maturity stages in the early phase of the spawning season.