CCAMLR

This paper explains the background and scientific rationale behind New Zealand’s decision to send two separate research voyages to the Balleny Islands, located north of the Ross Sea, in the Antarctic summer of early 2006. The first of these voyages involved a dedicated research expedition to the Balleny Islands exclusively, utilizing R/V Tiama, a 15 m expedition yacht. The second voyage included supplemental sampling in the Balleny Islands area as part of a larger Ross Sea expedition utilizing R/V Tangaroa. The successful completion of these voyages represents a considerable step forward for New Zealand’s approach to the Balleny Islands. This paper provides a preliminary summary of the scientific sampling activities carried out by each expedition, and discusses how the resulting data will likely inform the design of subsequent research activities in the area.

We describe the compilation and derivation of parameters for use in krill-fishery-predator models of the Scotia Sea – Antarctic Peninsula region. The primary aim is to provide input for the model developed by Watters et al. (2006), which we use to define the required parameters. However, these parameters should be applicable to other models of the system. Our methods include the use of weighted averages to derive “generic” parameters from multiple species in a taxonomic group, and the derivation of potential krill transport rates from the OCCAM global ocean circulation model. This parameter set, like most others, is associated with considerable uncertainty, which must be taken into account when it is used. We have therefore documented our sources, assumptions and calculations at every stage of the compilation process. Our calculations suggest that myctophid fish are the major consumers of Antractic krill in the Scotia Sea –Antarctic Peninsula region.

We summarize three types of data in order to increase appreciation among fishery managers of the close spatial and temporal ecological overlaps among top predators in the Ross Sea Shelf Ecosystem (RSShE). This includes data on diet, foraging behavior, and habitat use. Murphy (1995) demonstrated that space-time overlap is critical to predicting the degree to which a fishery might affect a food web. The fisheries that we contemplate are those for Antarctic toothfish and the Antarctic minke whale, though other species might also soon be exploited in the Ross Sea region. In addition to those two predators we also include other trophic competitors and (and in two cases predatory species): killer whale (type C), Weddell seal, Emperor penguin, Adélie penguin, and 4 species of flighted birds.
Using data from satellite tags attached to top predators that occur at colonies and haul outs along the coast of Victoria Land from 1990 through 2004, we summarize the foraging ranges from these sites and the habitats used for foraging. We also summarize data on diet and overlaps in foraging behavior among these predators from analyses of scats and stomach contents and time-depth-recorders collected from 1976 through 2002. Finally, we present results of ship-based surveys of birds and cetaceans made from 1976 through 1981. Though many of those species have not yet been studied using satellite telemetry, their diets have been investigated.
Most top predators in the Ross Sea feed at relatively great depths, perhaps because this affords them access to waters under sea ice, which persists in this region except for late summer. Three of them are able to exploit the entire water column of the shelf, with others foraging from near surface to mid-depths. The major geographic habitats used include waters that are or were part of the marginal ice zone that rings the Ross Sea Polynya during spring and summer when primary production is in full swing. Waters over shallow banks, especially in the western region, also appear to be important habitats. Even for colonies of these predators that are near the shelfbreak, their foraging efforts appear to be restricted to waters overlying the upper slope and shelf although deeper waters are well within range. In the RSShE, the main prey species eaten by most of the listed predators is the Antarctic silverfish, which is a major predator of ice krill. Based on frequency of occurrence in the diet, the prevalence of silverfish among diving predators averages 70% (range 45-95%) and among near-to-surface predators averages 31% (range 4-53%). The other main prey species of RSShE top predators is ice krill. Antarctic krill replaces ice krill in the predators’ diets over the Ross Sea continental slope and outer shelf waters.
The key, and perhaps critical, foraging habitats of the seals and penguins from the colonies and haul-outs studied so far along the Victoria Land coast occur almost entirely within CCAMLR statistical area SSRU 88.1J and the southern third of 88.1H, one of the main SSRUs for harvests of Antarctic toothfish. We make recommendations for research needs related to top predators, including further assessments of population size and diet (including studies of fatty acid composition) from autumn through early spring when sea ice is most extensive, and simultaneous tracking of toothfish and cetaceans, especially the toothfish-eating killer whale.

A Management Procedure (MP) approach is proposed to assist in advising 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-breeding predators. The Spatial Multi-species Operating Model (SMOM) developed in Plaganyi and Butterworth (2006) is used as an operating model which simulates the “true” dynamics of the resource with tests across a wide range of scenarios for the underlying dynamics of the resource. Unlike static catch allocation options, the illustrative MPs developed here have a feedback structure, and hence are able to react and self-correct. It is important, as with the static allocation options, to ensure that the likely performances of these MPs in terms of low risk to predators within each SSMU are reasonably robust to the primary uncertainties about such dynamics. A MP module separate from the operating model contains the methods and rules that are used to subdivide the krill catch between SSMUs. Different MPs are then simulation tested with their performances being evaluated on the basis of a set of performance statistics which essentially compare the risks of reducing the abundances of predators (and krill) below certain levels, as well as the variability in future average krill catches per SSMU associated with each MP. The key assumption made here is that data will be regularly available in future to monitor the impact/s of different krill catch limits. For illustrative purposes, it is assumed that two main sources of data will be available for use in a MP: (1) indices of absolute or relative abundance, or performance of the various predators (i.e. the CEMP series), and (2) survey estimates of krill absolute or relative abundance per SSMU. The approach proposed is readily modified if, for example, no krill abundance indices are available. Given that “future” data are required as inputs to test a MP including feedback, these data are generated with random variation about their underlying values and assuming the same variance as estimated from the past data.

It was shown that potential increase in krill fishery in the immediate future, accompanied by introduction of highly intensive fishing and processing technologies call for studying the fishery influence on ecosystem components beyond the framework of traditional investigations of predator-krill- fishery interactions. In this case, apart from traditional commercial statistics (vessels location, fishing effort, etc.), the trawl design and fishing method should be considered as a constituent of studying the krill fishing technology. It is just trawl design and fishing method that will determine catchability, selectivity and ecological compatibility of the gear during the fishery and, accordingly, form the fishing process influence on ecosystem components, such as juvenile fish, larvae, immature and adult krill and other small pelagic species. Obviously, ecological compatibility of krill processing technology, including waste recovery, may become a constituent part of fishery influence on ecosystem components beginning from the water, phyto- and zooplankton, krill, and further through trophic relationships to fish, birds and mammals.
It was discussed the potential major sources and scenarios of ecological influence of continuous krill fishing technology with “air-bubbling suspension system”(CFS), which is compared with a conventional fishing method. It was shown that not only hydrobionts, which are in close contact with the trawl, will be exposed to ecosystem influence of CFS, but also marine animals (seals, fish, for instance), though not fished by trawl, can be exposed to ecological pressing at a distance through the influence on environmental conditions. Therefore we conceive it to be expedient that introduction of fishing technology with the use of air-bubbling suspension systems is forestalled with planning and conduction of special investigations. Some proposals on such investigations were outlined.

ICED is a multidisciplinary, international initiative recently launched in response to the increasing need to develop integrated circumpolar analyses of Southern Ocean ecosystems. The long-term goal of ICED is to develop a coordinated circumpolar approach to understand climate interactions in the Southern Ocean, the implications for ecosystem dynamics, the impacts on biogeochemical cycles, and the development of management procedures. CCAMLR community scientists have been instrumental in developing this initiative, and a key aim of ICED is to link with CCAMLR scientists to develop management procedures that include relevant aspects of the wider operation of ocean ecosystems. This document describes the current status of ICED and is aimed at further developing links with the CCAMLR scientific community in order to maximise the impact of science on the management of Southern Ocean ecosystems.

Upward-looking acoustic Doppler current profilers (300 kHz, ADCP) and echosounders (125 kHz) were deployed on moorings on- and off-shelf to the northwest of South Georgia to measure abundance of Antarctic krill continuously between 14 October 2002 and 29 December 2005. A distinct seasonal pattern in krill abundance was detected that recurred consistently over all 3 years. Krill densities in winter were predominantly low (mean = 18.7 g m-2 SD 24.3) but rose substantially by summer in each year (mean = 89.5 g m-2 SD 64.2). A simple polynomial regression model with time as the independent variable explained 71% of the observed week-week variation. Mooring estimates of krill abundance were not statistically different (P>0.05) from estimates derived from standard ship-based krill surveys in adjacent periods suggesting that the mooring point estimates had relevance in a wider spatial context (ship surveys cover c. 100 x 100 km). Mooring data were used to explore whether high frequency temporal variation (i.e. within-year) could have led to the perceived between-year variation from previous summer surveys in the South Georgian western core box region between 1990 and 2005. Comparison of these ‘snap-shot’ ship survey estimates with the observed pattern of within-year variability showed that some of the alleged ‘year-to-year’ variation could be attributed just to sampling at different dates of year. However, there were some survey estimates that were significantly different (P

Antarctic krill has been studied for many decades, but we are still long way from understanding their biology to be able to make reliable predictions about the reaction of their populations to environmental change. This is partly due to certain difficulties in relation to logistics, operations and survey design associated with scientific surveys that have been obstacles for us to better understand krill biology. The krill fishery is the largest fishery in the Southern Ocean, continuously operating since early 1970s. Recent studies revealed its potential to be used as a unique source for scientific discussions to understand krill biology. In this paper, after a brief overview of krill fishery operation and krill biology, we examine how current data collection through the fishery operation could contribute to a greater understanding of krill biology, and then suggest future priorities for fisheries-related research in relation to recent changes in the Southern Ocean environment.

A long term study on the maturity cycle of Antarctic krill was conducted in a research aquarium. Antarctic krill were either kept individually or in a batch for 8 months under different temperature and food conditions, and the succession of female maturity stages and intermoult periods were observed. In all cases regression and re-maturation of external sexual characteristics were observed, but there were differences in length of the cycle and intermoult periods between the experimental conditions. Based on these results, and information available from previous studies, we suggest a conceptual model describing seasonal cycle of krill physiology which provides a framework for future studies and highlight the importance of its link to the timings of the environmental conditions.

We have substantially revised the krill-predator-fishery model that was presented to the WG-EMM in 2005. The new version of our model is called KPFM2, and we have addressed all four of the changes which the WG-EMM indicated would be required to use the model for providing advice on the allocation of catch among the SSMUs (i.e., add seasonality, consider alternative movement hypotheses, add thresholds in krill density that cause fishing to cease, and compute a performance measure that compares the distribution of simulated catch to the distribution of historical catch). We have added a substantial number of other features to the model as well. Many of these features were suggested to us at the 2005 meeting of the WG-EMM but not recorded as requirements; we have made a serious attempt to address most suggestions. These additional, features include
• predators that can forage outside their natal SSMUs;
• predators whose survival is a function of their foraging performance;
• differential competitive strengths among predators and the fishery;
• control over the seasonal timing of fishing and predator breeding that allows fishing and breeding to overlap or be disjunct;
• a facility for conducting simplified management strategy evaluations; and
• general improvements to the flexibility, performance, and usability of the model.
In our opinion, KPFM2 can be a useful tool for evaluating the outcomes of the six management procedures that are candidates for allocating the precautionary krill catch among SSMUs.