CCAMLR

Between november and february of the years 1993/94, 1995/96, 1996/97, 1997/98, 1998/99 and 1999/2000, one hundred and fifty three specimens of southern elephant seals, Mirounga leonina, were stomach lavaged at King George Island in order to analyse their diet. The two major prey types were cephalopods and fish which ocurred respectively in 98,1% and 14% of stomachs containing prey remains. The aim of the present paper was to report data on fish prey obtained from seal stomachs throughout the whole study period. One hundred and forty five sagittal otoliths were removed from 16 stomachs containing fish remains. Of these stomachs, 9 belonged to adult females, 6 to juvenile males and 1 to a subadult male. The identification of otoliths revealed the predominance of myctophids as fish prey of seals, representing 76,5% of the fish predated. The most frequent (75%) and abundant prey species was Gymnoscopelus nicholsi which constituted in number 69% of the otoliths found. This species was followed by the nototheniid Pleuragramma antarcticum which represented 11,7% in number and 31,3% in frequency of occurrence. Based on the great distances travelled by seals from their foraging grounds to their hauling sites and the differential rate of passage of fish and cephalopod remains through their gastrointestinal tract, an underrepresentation of the consumption of fish is highly probable. Moreover, according to the movements at sea of southern elephant seals tracked from King George Island we suggest that while myctophids may be their dominant fish prey in areas close to their hauling sites, they are probably replaced by the Antarctic silverfish P. antarcticum as seals migrate southward towards higher latitudes where this species is highly abundant.

The data on Soviet krill fishery in i977-1992 are presented. The fishing effort (FE) developed in 1977-1991 was 50086 fishing days in total. According to the pictures presented FE was distributed between subareas 48.1, 48.2 and 48.3. Monthly FE distribution between subareas revealed the three types of FE distribution in subsequent groups of years: Type I: 1981 and 1982, partly 1979/1980: FE was concentrated in subarea 48.1 in January-April, then moved to 48.3 via 48.2. Type II: 1983, 1984, 1985, and 1986: FE was developed mostly in subarea 48.2, since 1985 the role of 48.3 is increasing. Type III: 1987, 1988 and 1989. FE was developed mostly in 48.3, from March-April to September-November. There are discussed several groups of factors influencing FE distribution, it is very difficult to determine the key one between them. However, it was revealed that the determined types of FE distribution well correspond to spatial and temporal variability of the zonal and meridional atmospheric processes. The prerequisites for the main fishing effort development exist in the subarea where Southern transfers are maximally developed for the moment. The phenomena occur in subareas 48.1 and 48.2 under increase of the zonal western transfers and in subarea 48.3 under their decrease.

The study aimed to test the utility of instruments deployed on marine mammals for measuring physical oceanographic variation and, using this method, to examine temperature variation in the coastal waters around South Georgia. There was a significant correlation between temperature measurements made using a towed undulating oceanographic recorder (UOR) and concurrent measurements from time-depth recorders (TDRs) fitted to lactating Antarctic fur seals foraging from the coast of South Georgia. Congruence was found at horizontal spatial scales from 0.01° X 0.01° to 0.5° X 0.5° (degrees of latitude and longitude), and at a vertical scale of 10 m. However, there was no significant correlation between temperature measured by TDRs in the top 5 m and sea surface temperature (SST) measured by satellite remote sensing. TDR data provided information about temperature variation vertically through the water column, and through time. The UOR data were used to recalibrate the TDR data in order to correct for the slow response time of the TDR thermistor relative to the speed of seal movements through the water column. Seasonal temperature variation was apparent, and temperatures also varied between regions, and with bathymetry. These results were consistent with the current interpretation of the coastal oceanography around South Georgia. In particular, the relationship between on- and off-shelf waters showed larger amounts of warmer surface water in a region in which more run-off was to be expected. The study also showed that Antarctic fur seals concentrate their activity in regions of colder, and presumably oceanic, water. Such instrumented animals could provide near real time data for assimilation into ocean models.

At last year’s meetings WG-EMM and Scientific Committee expressed an interest in summarized information on seabird demography, particularly in relation to generation time and productivity. this represents a substantial task with not inconsiderable resource implications. However, as an initial step, this paper attaches a tabulated review of most of the relevant data up to 1981 (Croxall, 1982). The most important subsequent demographic studies are referenced in the recent report of the SCAR Bird Biology Subcommittee (WGEMM- 00/16). The meeting is invited to consider how it wishes to proceed in respect of such data.

GOOS (Global Ocean Observing System) is a permanent global system for observations, modelling and analysis of marine and ocean variables to support operational ocean services worldwide. It is sponsored by IOC, WMO, UEP and ICSU (see website is http://ioc.unesco.org/goos/).
In December 2000, Dr Angus McEwan, GOOS representative, met with the Data Manager and Science Officer to briefly discuss possible collaboration between GOOS and CCAMLR. It was agreed that any proposals for collaboration received from GOOS would need to be considered by WG-EMM and SC-CAMLR.
This document presents the follow-up letter from Dr McEwan, together with extracts from GOOS’s strategic plan for tracking changes in marine ecosystems.

Variability is a key feature of the pelagic ecosystems of the Southern Ocean and an important aspect of the variation is fluctuation in the abundance of krill, the major prey item of many of the higher predators. Direct impacts of variability in the large-scale physical environment, such as changes in ocean circulation, have been suggested as the main factor generating the observed fluctuations. So far, however, there has been little quantitative assessment of the importance of krill population dynamics in the observed variation. Here, analyses of a model of krill population development and predator diet data from South Georgia were used to examine seasonal changes in the population structure of krill. The krill population model was combined with a size-based selection function and used to generate expected length-frequency distributions in the predator diet through a summer season. Comparison of the model solutions with the predator diet data indicates that the model can reproduce the observed pattern of variation and emphasizes that adult population changes are a key aspect of the interannual fluctuations observed during some years. Low krill abundance was associated with reduced representation of the 3+ age group, whereas when krill were abundant the 3+ age class was the major age group present. The seasonal changes in the population structure in the predator diet involve a complex interaction of relative year class strength, timing of immigration, fluctuations in growth rates and dynamic predator selective effects. Development of the model to examine the interactive effects of changing krill growth and mortality rates will be a valuable next step. The dominance of the changes in krill population age structure underlines the fact that to understand the variability of the South Georgia ecosystem we must identify the major factors generating variability in population dynamics throughout the Scotia Sea.

This paper discusses the principles required to develop of small-scale management units and highlights a work program in this development. It provides the theoretical foundation for considering the scales of management units involving the integration of local populations of harvested species, foraging areas of predators, fishing grounds and the potential influences of the environment, including oceanography and metapopulation structure of the harvest species. The integration of these three components requires two different units: the “harvesting unit”, which is at the scale of the metapopulation of the harvested species, and the “predator unit”, which does not have to be a relatively self-contained ecosystem but should be sufficiently self-contained such that fishing in that unit does not inadvertently affect predators being monitored in other units. Harvesting units are defined and a number of additional divisions of CCAMLR statistical areas are proposed on ecological grounds to complete the division of the CCAMLR area. The South Atlantic region (Area 48) is used to illustrate how to define predator units. The derived conceptual model is then used to formulate a work program for the development of fisheries on prey species, notably krill, in other harvesting units. The manner in which predator units can be used to help the CCAMLR Ecosystem Monitoring Program provide strategic advice on the effects of fishing is discussed. In general, the early acquisition of information from within a harvesting unit on the distribution of local populations of krill, the potential foraging density of predators (i.e. abundance of predators, distribution of colonies and foraging range) and the potential fishing grounds will provide the means for circumscribing predator units as well as undertaking an assessment of long-term annual yield. It is proposed that the early development of the fishery could be concentrated in a small number of units to the extent that the fishing intensity in those units is equivalent to the intensity expected across all units once the TAC had been reached. Other units in which fishing was not occurring could be monitored as well. This process could help predetermine whether or not the TAC is likely to cause undesirable effects on predators in any of the predator units. In this way, the need for whether or not local restrictions on harvesting are necessary can be determined well in advance of the TAC being reached as well as the overall requirements for the monitoring program.

A proposal to arrange a CCAMLR course in survey design and execution at KMRS is put forward to propagate the experiences gained in planning and executing the CCAMLR 2000 krill survey. The proposed course would recruit teachers and students from member countries and illustrate both theoretical and practical aspects of krill survey work by planning and performing a “miniature survey” in Gullmarsfjorden with the Nordic Krill Meganyctiphanes norvegica as a model organism. It is argued that such an international course would help to assure that the collective wisdom of CCAMLR is maintained, developed and disseminated to younger scientist.

Scientific observations on fishes incidentally caught during commercial krill fisheries by F/V Niitaka Maru (3910t) were made from 16 December 2000 to 26 January 2001 in the vicinity of the South Shetland Islands. Among 103 net hauls quantitatively examined, by-catch fishes were found in 41 trawl catches. Lepidonotothen larseni was the most abundant in number and weight and occurred in 20.4% of hauls sampled for by-catch and 51.2% of those contained fish. P. antarcticum and C. gunnari were the second in abundance in number and weight respectively. Most hauls were dominated by one species which constitute 63.4% of hauls contained by-catch fish and a high degree of spatotemporal dissociation among juveniles of different species was recognized. The by-catch data of the present survey provided a clear picture of the negative correlation between abundance of by-catch fish and the krill CPUE. The relationship between towing time and estimated individual number of by-catch fish in each haul was obscure.

Cape Shirreff and San Telmo Islets (SSSI Nº32) shelter the largest breeding population of Antarctic fur seals, Arctocephalus gazella, in the South Shetland Archipelago. Since all censuses up to date have been single counts and do not allow the calculation of confidence limits, a protocol was developed for assessing uncertainties in the estimates of the counts (inter and intra-observer error) and put into practice during the 2000/2001 field season. Intra-observer error was between 0,15-1,74%CV, while inter-observer error was within 3% of the overall mean. The relationship between census error and pup numbers show a linear trend, however, some outliers (outside the 95%CI) could be identified and corresponded to beaches in which variation cannot be entirely attributed to inter-observer error. It can be suggested that topography, density, tides and meteorological conditions can affect pup censuses in a considerable way. These factors should all be assessed and taken into account when undertaking regional surveys of land-based predators in the future. Censuses developed at the SSSI have proved to be quite precise and this suggests that previously reported trends are not an artifact of counting error, thus supporting the hypothesis that the A. gazella population at SSSI Nº32 is reaching stability since more than 87% of K has already been attained.