CCAMLR

Antarctic and sub-Antarctic seabirds, marine mammals, and human fisheries concentrate their foraging efforts on a single species, Antarctic krill (Euphausia superba). Because these predators may have a significant effect on krill abundance, we estimated the energy and prey requirements of Adelie (Pygoscelis adeliae), chinstrap (Pygoscelis antarctica), and gentoo (Pygoscelis papua) penguins and female Antarctic fur seals (Arctocephalus gazella) breeding on the South Shetland Islands, Antarctica and compared these estimates with catch statistics from the Antarctic krill fishery. Published data on field metabolic rate, population size, diet, prey energy content, and metabolic efficiency were used to estimate prey requirements of these breeding adult, land-based predators and their dependent offspring. Due to their large population size, chinstrap penguins were the most significant krill predators during the period examined, consuming an estimated 7.8 x 108 kg krill, followed by Adelie penguins (3.1 x 107 kg), gentoo penguins (1.2 x 107 kg), and Antarctic fur seals (3.6 x 106 kg). Total consumption of all land-based predators on the South Shetland Islands was estimated at 8.3 x 108 kg krill. The commercial krill fishery harvest m the South Shetland Island region (1.0 x 108 kg) was approximately 12% of this. Commercial harvest coincides seasonally and spatially with peak penguin and fur seal prey demands, and may affect prey availability to penguins and fur seals. This differs from the conclusions of Ichii et al. who asserted that the potential for competition between South Shetland predators and the commercial krill fishery is low.

The current long-term estimates of mean recruitment rates suggest that the population is unsustainable, as they are too low to maintain the estimated mortality rate. The variable annual estimates of recruitment to the population can be used to model in detail interannual variation in the population dynamics of krill and estimate the expected mortality rates. A number of models of the population dynamics of krill are used to assess to what extent they can explain the observed changes in the density of the population in the Antarctic Peninsula region. Two approaches have been explored: the first uses the bulk density estimates and uses a non-linear regression method to estimate the mortality rate. The second method develops a fully age-structured population model and uses only the recruitment data to develop a model of the long-term dynamics. Data on the recruitment of the first and second age groups were used to derive different estimates of mortality rates. Both model approaches applied to the recruitment data for the first age class produced an instantaneous mortality rate estimate of approximately 0.6 (?43% per annum). In both cases however the mortality rate estimate is poorly constrained in a range from about 0.3 to 1.0 (26%-63%) and the long-term trajectories of density estimated by the models give a relatively poor fit to the observed data. Using the recruitment data for the second age class produced higher mortality rate estimates of between 0.8-1.0 (59-63%) and produced better fits to the observed density changes. The need for caution in interpreting the model results was emphasized by an analysis of the sensitivity, which showed that the density data strongly constrain the model trajectories, which are less sensitive to changes in the recruitment rates.

An assessment of the environmental processes influencing variability in the recruitment and density of Antarctic krill (Euphausia superba) is important, as variability in krill stocks affects the Antarctic marine ecosystem as a whole. We have assessed variability in krill recruitment and density with hypothesized environmental factors, including strength of westerly winds (westerlies) determined from sea level pressure differences across the Drake Passage, sea ice cover, and ozone depletion. We found a significant positive correlation between krill recruitment in the Antarctic Peninsula area and the strength of westerlies during 1982–1998. Years with strong westerlies during the austral summer season resulted in high krill recruitment in 1987/1988, 1990/1991, and 1994/1995, while the years of weak westerlies resulted in low krill recruitment in 1982/1983, 1988/1989, 1992/1993, and 1996/1997. The strength of westerlies was significantly related to recruitment of 1-year-old krill (1' = 0.57) and 2-year-old krill (r = 0.69) with a level of significance of 5%. In addition, the strength of westerlies also had a strong correlation with chlorophyll a (r = 0.63) and sea ice cover with a 1-year time lag (r = 0.67). The strength of westerlies is considered to be a key environmental factor. We also found significant correlations between krill density in the Antarctic Peninsula area and the Antarctic ozone depletion parameters during 1977–1997 (e.g., total ozone in October at Faraday/Vernadsky Station of r = 0.76 with a level of significance of 1 %). We suspect that ozone depletion impacts directly and/or indirectly on the variability in krill density.

A krill density model suggested during WG-EMM at Kochi ( Dy?(1-Rl)-Dy-1?e-M=0) still involved uncertainties of age 1 krill. Present document improves the model by taking the uncertainties in to account, and assuming a reasonable mortality. The model suggested that if we expect the currently accepted values of mortality M (0.8-1.0), the potential proportional recruitment should be larger than the observed values. Although potential recruitments were incorporated, and also reasonable mortality was used in the model, dramatic variation of densities after 1994/95 season could not be clearly explained.

An index of per capita recruitment (PCR) is proposed such that Ri PCRy–1 = R1y/(1–R1y)eM where R1 is the proportion of age-1 animals sampled in year y and M is the post-recruit mortality rate. The intent of the index is to facilitate investigation of reproductive success and the factors postulated to affect it. The formulation of PCR is based on the assumptions that: 1) post-recruit mortality does not vary over age or between years; 2) 100% of age-1 animals spawn; 3) a representative sample of the population is available; and 4) the proportion of age-1 animals in the sample can be determined unambiguously. Normal, log-normal and uniform probability distributions of R1, and three levels of M, were assumed in order to investigate the resulting distributions of PCR. Distributions of PCR are skewed toward higher values such that the dynamic range of PCR is largest with high values of R1; increasing M tends to offset this effect but only slightly. A simple population model was then constructed to test the sensitivity of PCR to relaxation of its underlying assumptions. PCR is not biased relative to recruits per spawner when mortality is constant over all ages and years, and when all age-1 animals spawn. These conclusions are insensitive to changes in the shape of the functional relationship between spawners and recruits. PCR is biased low with age-specific decline in mortality and reduction in the proportion of age-1 spawners. Introducing year to year random variability in both mortality and proportion of age age-1 spawners resulted in broader distributions of PCR relative to recruits per spawner but did not appear to introduce additional bias. On average, PCR will under estimate recruits per spawner by 30% if reasonable assumptions are made regarding the variability of mortality and the proportion of age-1 spawners. The effectiveness of PCR to track changes in recruits per spawner over time was confirmed by introducing cycles in the shape of the functional relationship between spawners and recruits. PCR was also able to track cycles in recruits per spawner after a 20% random sampling error was added to the value of R1 used in the calculation of PCR and year to year random variability in mortality and proportion of age-1 spawners was introduced, although errors were larger. A time series of PCR for Antarctic krill sampled in the vicinity of the South Shetland Islands from 1979 through 1998 is presented.