CCAMLR

We present the results of an alternative method of estimating krill abundance, and producing maps of krill distribution, from the data collected during the 2000 CCAMLR survey of the Scotia Sea. Using a probabilistic Bayesian Maximum Entropy (MaxEnt) technique, density values for the unsurveyed off-transect portions of the survey area were found by interpolation, and thus values for total biomass across the survey area, and within individual small-scale management units (SSMUs), can be inferred. The MaxEnt formalism allows an objective choice of the parameters of the interpolation, and hence an objective choice of the most probable reconstruction of krill distribution, given the data. The Bayesian framework also allows an intrinsic calculation of the error in any resulting density estimate. During the survey, data were integrated at approximately 1 nm intervals, resulting in 9,586 observed data points. We therefore inferred the krill density on a 1 nm × 1 nm grid of pixels. Density values (g m-2) were calculated for all 1,726,332 pixels in the reconstructed area. The MaxEnt maps of the density distribution of krill across the survey area are presented. The resulting total biomass inferred for the survey area was 207.98 million tonnes, with a standard deviation of 10.08 million tonnes. The inferred biomass of krill in each of the SSMUs was: Antarctic Peninsula Pelagic Area (APPA) 65.192 Mt; Antarctic Peninsula West (APW) 0.753 Mt; Drake Passage West (APDPW) 35.874 Mt; Drake Passage East (APDPE) 0.397 Mt; Bransfield Strait West (APBSW) 0.167 Mt; Bransfield Strait East (APBSE) 1.381 Mt; Elephant Island (APEI) 10.496 Mt; Antarctic Peninsula East (APE) 0.003 Mt; South Orkney Pelagic Area (SOPA) 30.799 Mt; South Orkney West (SOW) 0.988 Mt; South Orkney North East (SONE) 0.005 Mt; South Orkney South East (SOSE) 0.243 Mt; South Georgia Pelagic Area (SGPA) 57.194 Mt; South Georgia West (SGW) 1.742 Mt; South Georgia East (SGE) 1.742 Mt.

In this work the characteristics of krill transport across the SSMUs determined on the basis of long-term Russian research in Area 48 are considered. Estimates of mean current velocities based on the long-term data from 3012 stations and respective time intervals when the water mass in the study area was totally replaced are presented. It is shown that in SSMUs the multiple total replacement of water masses is possible during one fishing season. These processes of water mass replacement will be accompanied with krill biomass transport across the boundaries of the SSMUs. Our estimates of krill flux out SSMU during fishing season appeared incomparable neither with the historical annual catch within SSMU, nor with the total catch from the Scotia Sea for any fishing season during the latest 20 years. It is shown that total krill biomass of 3.392 mln.t. transported by water mass out three SSMUs is comparable to the total precautionary yield value in the Scotia Sea comprising 3.17 mln.t. It is concluded that krill transport estimates should be taken into consideration in the scheme for allocating the krill catch limit among SSMUs in the Scotia Sea developing by CCMLR. This is primarily referred to the fourth option of the schemes (Hewitt, et al, 2004)

In 2004, the Commission tasked the Secretariat to discuss with the Committee on Environmental Protection (CEP) the nature of available data from the Antarctic Site Inventory, and to invite consideration by appropriate Working Groups of whether the data would be of value to CCAMLR. Information about the data is presented for consideration by WG-EMM.

At Marion Island, there was considerable correlation in numbers of adults breeding at study colonies for both Macaroni Eudyptes chrysolophus and Eastern Rockhopper E. chrysocome filholi Penguins, over 26 and 22 years respectively, suggesting over-wintering conditions may influence the proportions of birds breeding. For both species the time of arrival of females for breeding, and for Rockhopper Penguins the mass of females on arrival, was significantly related to breeding success. Therefore, over-wintering conditions may also affect breeding success. Trends in breeding success at study colonies were more strongly correlated for Macaroni Penguins than Rockhopper Penguins. Macaroni Penguins have a greater foraging range than Rockhopper Penguins when breeding, and may be more influenced at this stage by wider-scale environmental phenomena. For Macaroni Penguins, breeding success was significantly correlated with mass of chicks at fledging. For both species, mass on arrival of males was significantly correlated with that of females. Although both species had low weights on arrival after the El Niño Southern Oscillation event of 1997/98, there was no significant correlation in mass on arrival between the two species. It is likely that at Marion Island their over-wintering grounds are different.