CCAMLR

Target strength measurements of free swimming krill at 120kHz were made using a single beam monostatic system in a 10 m3 laboratory tank. Krill (grouped according to length classes) swam freely in the tank triggering the data acquisition system when generating a back scattered signal larger than a threshold, determined by the system noise level. Dorsal and ventral target strength estimates were calculated indirectly by deconvolution of the cumulative probability function of echo ensembles of single animal insonifications. For mean length classes in the range [29.6, 36.2] mm the median single-animal target strengths are in the range [-76.7,-71.8] dB. Monte Carlo computer simulations were used to evaluate the effects of varying the ratio of largest to smallest echo amplitudes for a given ensemble, thus enabling the estimation of threshold induced bias in the target strength estimates. The threshold induced bias was then determined for each ensemble of experimental data and used to determine corrections which were in the range of [-0.84, -0.33] dB. An error analysis of the target strength estimates detailing the components due to measurement accuracy and precision, and the indirect signal processing techniques used is also presented.

The results of acoustic surveys, especially in low signal-to-noise regimes, are sensitive to the method used to exclude the contribution of background noise from the acoustic data. The use of thresholds to reject weak signals during data collection is inappropriate because the noise contribution to the above-threshold-signal cannot later be removed in post processing. The only solution is to log unthresholded data and to correct for noise in post processing. Integrated data collected at 120 kHz with a Simrad EK500 are presented to demonstrate the highly variable nature of background noise. A dynamic method to determine background noise for individual integration intervals was found to be better than several methods that apply a single background noise level to a data set. The dynamic technique requires that logged data have high resolution in both depth and distance. It can be applied so long as some integration layers in each integration intervals include only noise. Further, it is recommended that the physically meaningful quantity "noise power", being the apparent received power (dB/ 1 W) at the transducer due to noise, is used to describe background noise levels.

Krill (Euphausia superba) provide a direct link between primary producers and higher trophic levels in the Antarctic marine food web. The pelagic tunicate Salpa thompsoni can also be important during spring and summer through the formation of extensive and dense blooms. Although salps are not a major dietary item for Antarctic vertebrate predators, their blooms can affect adult krill reproduction and survival of krill larvae. Here we provide data from 1995 and 1996 that support hypothesized relationships between krill, salps and region-wide sea-ice conditions. We have assessed salp consumption as a proportion of net primary production, and found correlations between herbivore densities and integrated chlorophyll-a that indicate that there is a degree of competition between krill and salps. Our analysis of the relationship between annual sea-ice cover and a longer time series of air temperature measurements indicates a decreased frequency of winters with extensive sea-ice development over the last five decades. Our data suggest that decreased krill availability may affect the levels of their vertebrate predators. Regional warming and reduced krill abundance therefore affect the marine food web and krill resource management.

Scientific observations on fishes incidentally caught during krill fisheries by F/V Niitaka Maru were made from 1 to 23 February, 1997 to the north of the South Shetland Islands. Among 80 hauls examined, a total of 61 specimens belonging to 4 families and 7 species, Electrona antarctica (50 specimens), Electrona carlsbergi (4), Protomyctophum tenisoni (1), Gymnoscopelus opisthopterus (1), Notolepis coatsi (3), Benthalbella elongata (1) and Neopagetopsis ionah (1), were captured as by-catch in 16 hauls. Except for one channichthyid juvenile of Neopagetopsis ionah, by-catch fishes were referred to the bathypelagic families, the Myctophidae, Paralepididae and Scopelarchidae. Among by-catch fishes, Electrona antarctica of the Myctophidae was the most abundant. This species was found in 12 hauls, and its estimated value was 20 to 380 ind./t. The present by-catch data did not provide clear relationship between the abundance of by-catch fish and the krill CPUE. This observation is different from by-catch data made in previous studies. In the present survey, the abundance of by-catch was well correlated to the time zone of trawling, which is thought to depend on a large amount of bathypelagic fishes in the catches.

Thomson and Butterworth (1996) developed a krill-predator model and applied this to an Antarctic fur seal dataset. These calculations are extended here. The level of krill fishing intensity required to halve the fur seal population (γhalf) is between 0.08 and 0.09, slightly lower than that estimated previously. Tests of the estimation procedure indicate that γhalf estimates are likely to be biased upwards. The estimator is not robust to incorrect specification of the form of the functional relationship assumed between krill availability and survival rates, and especially not to the assumption of the size of the maximum growth rate which the population can achieve. Refinements are introduced to the process of applying this approach to the black-browed albatross dataset, but calculations to estimate γhalf for this species have yet to be completed. The results quoted above are for the deterministic models; stochastic calculations await finalisation.

Polynyas accelerate oceanic and atmospheric processes. We additionally think polynyas influence biological activity. We pursued daily transition of coastal polynyas in the Antarctic Peninsula area from 1978 through 1995 using images of sea ice concentrations by the satellite microwave observations. A typical polynya existed off the tip of the Peninsula in 1987 and 1991. In the such years, sea ice cover developed extensively. Inversely, the years of the narrow sea ice cover were 1988, 1989,1990 and 1993. In the such years, polynyas did not existed. The typical polynya (nearly 500 x 200 km) in 1987 was pursed from beginning on August 1 to end on October 20. The shape of the polynya changed remarkably in several days. We speculated that annual variability of sea ice cover and consequently polynyas is mainly caused by the Westerly winds.