CCAMLR

We tuned four parameterizations of Foosa to provide predictions that are consistent with the agreed calendar, as specified by the WG-SAM, that describes changes in the abundances of krill and their predators in the Scotia Sea. First, we compiled a set of base parameterizations from information in the literature and following specifications laid out by the WG-SAM. These base parameterizations cover a combinatorial framework that considers krill movement (or lack thereof) and the shape of a relationship determining how the effective abundance of breeding predators depends on foraging success during the breeding season. We also added a new functional relationship to Foosa: a relationship that determines the degrees to which the survival of juvenile predators depends on foraging success in their first winter of life. The dynamics predicted by our base parameterizations were loosely consistent with the direction and timing of changes in predator abundance specified by the numerical calendar from Hill et al. (2008). This indicated that our base parameterizations were reasonable and that tuning to the numerical calendar would be feasible. Second, we tuned, via sums of squares, one stock-recruitment parameter for each predator population in each parameterization to the “empirical abundance estimates” for predators reported by Hill et al. (2008). Tuning the peak recruitment by all 19 predator populations was sufficient to predict the empirical abundance estimates almost exactly for all predators by all parameterizations. The dynamics predicted by these tuned parameterizations often had trends and changes in magnitude that were roughly consistent with those in the numerical calendar, lending additional support to the validity of the initial conditions, un-tuned parameters, and functional forms used in this application of Foosa. Finally, we tuned, via an objective function that minimizes the sum of absolute proportional differences in abundance, one or two stock-recruitment parameters for each predator population to the numerical calendar itself. Parameterizations tuned in this last step constitute our reference set and predict plausible dynamics by reasonably matching the timing of events and magnitude of changes that are specified in numerical calendar. This reference set encapsulates hypotheses that go beyond the basic contrasts between krill movement and predator response to foraging success in the breeding season, implying a diverse set of hypotheses that includes SSMU-specific views about the productivities of individual predator populations and the effects of winter foraging conditions on juvenile survival. All four parameterizations in our reference set imply ongoing trends in predator populations, and, in forward simulations, changes in abundance predicted from these ongoing trends will likely need to be separated from changes caused by krill fishing. Although we believe that all four parameterizations in our reference set are plausible to some degree, we do not think that they are equally plausible. We suggest plausibility ranks for these four parameterizations that might be useful for synthesizing the output of future modeling efforts and simplifying communications with decision makers. After completing our analytical work and writing most of this paper, we found a small error in the initial conditions used in one of our four parameterizations. We discuss why this error does not affect the conclusions presented here or in our follow-on effort to conduct a risk assessment using the reference set.

Over the past few years WG-EMM has been developing a management procedure for the krill fishery in Statistical Area 48. This procedure will involve, inter alia, subdivision of the precautionary catch limit among a set of small-scale management units. So far the Working Group has identified six candidate methods for subdividing the catch limit and rejected one of them as unsuitable (Option 1 - subdivision based on the distribution of historical catches). In recognising the need for a “staged development” of the management procedure, the Working Group has agreed to defer the development and evaluation of two further options (Option 5 - adjustable catch limits within SSMUs and Option 6 - structured fishing) until a future date. The remaining three options propose subdividing the catch limit according to the distribution of predator demand (Option 2), krill standing stock (Option 3), or the difference between these two (Option 4). In this paper we review the uncertainties relating to the spatial distribution of predator demand and krill standing stock and assess their potential implications. We consider that a strong case can be made against Option 4, which is likely to increase ecosystem risk when the underlying estimates of consumption and/or standing stock are uncertain, especially when they are biased. We suggest that the data documenting the distribution of krill standing stock are likely to be more reliable than those documenting the distribution of predator demand, leading us to favour the use of Option 3. However, we note that though Option 3 appears to be the most favourable, there is little documentary information about temporal variability in the spatial distribution of krill biomass, emphasising the need for monitoring and model-based risk assessments. Finally, we conclude that WG-EMM cannot delay the subdivision of the precautionary catch limit without incurring some risk.

Relatively little ecological information is available for the South Sandwich Islands, so the diversity of information available to determine potential SSMU boundaries is limited. Nevertheless, a suggested SSMU is proposed, based on the foraging distance of the most abundant land-based consumer of krill breeding on the islands, the chinstrap penguin. The proposed SSMU represents a single ecological entity with no internal boundaries. It is based on the best information currently available.

In 2007 WG-SAM defined a set of reference observations for validating and tuning proposed models to evaluate krill catch allocation options for Area 48 (the SAM calendar). The observations, which were endorsed by WG-EMM, were largely qualitative and relative. We used available data to translate these observations into numerical terms (the numerical calendar). We provide spatially-resolved reference points for the density of krill, and the abundance of “generic” seals, penguins and whales in 1970, 2007 and at least one intermediate year. Recent work on baleen whales indicates a higher growth rate than that suggested by WG-SAM, so the numerical calendar for this taxon deviates from the SAM calendar. The numerical calendar is a partly subjective interpretation of limited data and should not be considered a definitive description of the relevant dynamics. This exercise resulted in population sizes for several taxa that are adjusted for asynchronous observations and are potentially more suitable for initialising models than those published in Hill et al (2007).

Dr Rachel Fewster (Department of Statistics, Faculty of Science, University of Auckland) participated in the WG-EMM Predator Survey Workshop as Invited Expert. The terms of reference for her participation were as follows: 1. Participate in the Workshop on Predator Abundance in June 2008 2. Provide consultation and advice on procedures for: (i) estimating abundance of important krill predators for Small Scale Management Units in CCAMLR Convention Area 48 (ii) estimating uncertainty around abundance estimates (iii) identifying gaps in existing data that constrain estimation of status and advising on how best to fill those gaps 3. Assist in the preparation of a workshop report 4. Submit a post-workshop report to CCAMLR. Dr Fewster’s post-workshop report is enclosed. (This report was submitted to WG-EMM by the Secretariat, in consultation with the Convener of the Predator Survey Workshop)

A standardized krill net sampling survey was conducted in the Lazarev Sea (CCAMLR Subarea 48.6) in austral summer during December/January 2007/08 (LAKRIS, Lazarev Krill Study) as a German contribution to CCAMLR-IPY 2008. At the start of the survey period the entire survey area was completely covered with seasonal pack-ice, but rapidly retreating until the end of the survey in late January. 52 samples were taken by RMT 8 and RMT 1 along three transects south of 60°S. Krill and other Antarctic Euphausiacea species densities were estimated from both RMT net samples. Length and maturity stage composition and seasonal development of maturity stages were analysed. Distribution and density of krill larvae are provided for the Lazarev Sea.

This paper summarises the notifications received from Members intending to participate in krill fisheries in the CCAMLR Convention Area in the 2008/09 season.

As reported to the CCAMLR Secretariat, 6 vessels from 5 Contracting Parties are fishing for krill in Area 48 in the 2007/08 season, and these vessels have taken 84110 t of krill to date. The preliminary estimate of the total catch of krill for the season is approximately 108343 t. This compares with 104586 t of krill reported in the STATLANT data for 2006/07. With the exception of Poland, all Contracting Parties have submitted complete sets of haul-by-haul data for 2006/07. The report includes: Availability of fishery and observer data; Time series of catch by season, Contracting Party and small-scale management unit; Species composition of by-catch; Occurrence of incidental catches of seabirds and mammals; Consideration of the Conservation Measures in force in the fishery. Reference information on stock and areas, and parameters used in stock assessment are also included.

The CCAMLR Ecosystem Monitoring Program (CEMP) uses indices derived from data on indicator species collected by standard methods in the three Integrated Study Regions of the Convention Area. Each year the Secretariat updates the standardised index values and provides a summary of trends and anomalies in these data. This report covers predator indices only. Data were submitted by 7 Members for 10 sites and 13 different CEMP parameters for the 2007/08 season. No data was submitted from Edmonson Point and Ross Island; however counts from aerial photographs taken at Ross Island for the previous five seasons are being undertaken. There has been a general decline in the number of parameters submitted from the monitoring sites.