CCAMLR

A survey was conducted in order to collect information for the stock status and biology of toothfish in the Division 58.4.3b (BANZARE Bank), using a commercial bottom longline vessel Shinsei Maru No. 3, from 24th May to 5th June, 2012. Due to unexpected bad weather and sea condition, the vessel and some equipments on board were frozen, the operations were delayed and the fuel oil for the stability of the vessel was wasted. Unexpected low fish catches in the preceding survey in Ob-Lena Bank during the same cruise and the wasteful use of baits also lead to the decline of the stability of the vessel. The above mentioned situation forced the vessel to interrupt the survey halfway to ensure the safety of voyage. Shinsei Maru Trot line system with modified configurations was used as fishing gear for 16 hauls. Mean CPUE of Dissostichus spp. was 52.2 kg / km (CV = 107 %). This was identical with the mean CPUE of 51.8 kg / km in the 2010/11 survey. Total of 51 individuals of toothfish with good physical condition and single-hooked were tagged and released during the survey. No toothfish was recaptured. Fish with good physical condition and single-hooked contributed 26-39 % to the total fish caught by the two kinds of modified trotline configurations recommended by WG-FSA in 2011. 

We propose to continue the survey focusing mark-recapture experiment in the 2012/13 season with slightly modified spatial designs. An approximate stock biomass level of Dissostichus spp. in the target stock area was estimated to be 8 444 tonnes, using CPUE comparison method. This was lower than the estimate of 13 592 tonnes using the mean CPUE from 2007/08 to 2009/10. However, the survey area in 2011/12 overlapped well with that in the 2010/11 and the CPUE was identical between the two years nevertheless the numbers of hooks for the trotline configuration for the 2011/12 survey were reduced to 60 % of normal configuration. Thus the existing catch limit of 40 tonnes seems to be appropriate for the 2012/13 survey. We would examine the appropriate scheme to complete the survey in 2012/13 such as changing the survey season, separating the cruise between the surveys in Ob-Lena Bank and BANZARE Bank for securing enough ship-time, etc.

Picking up the calling of the ATCM XXXIV to the Treaty Parties to intensify their efforts in using remote sensing techniques for improved monitoring of environment and climate changes in the Antarctic, Germany currently carries out a feasibility study on penguin monitoring using such techniques. Additionally, CEP representatives and scientists discuss on an informal level the need and the general possibilities of a penguin monitoring in the Antarctic Treaty area based on remote sensing techniques. In order to stimulate and formalize this discussion, Germany proposes to open an Intersessional Contact Group (ICG) on penguin monitoring via remote sensing on the CEP Discussion Forum on the Secretariat website and invites CCAMLR to participate in this process.

To estimate optimal relative sample size of scientific observer data collected on Antarctic krill commercial fishing vessels, we estimated the relationship between statistical precision and sample size by using variance component analysis. Observer datasets on Japanese krill fishery from 1995–2008 were analysed by using a hierarchical Bayesian model. The models were composed of multistage cluster units (i.e., year, sub-area, vessel, cruise, and haul) based on a state-space model, separating biological process error in the population dynamics from fishery process as observation error. In both krill length and bycatch fish number, the parameters estimated by MCMC hardly show difference among years, sub-areas, and vessels. The potent interaction effect between year and sub-area suggests large spatio-temporal variability in size structure of krill population, which is presumably derived from large variability of recruitment causing difficulty in predicting krill population dynamics. Variances of observer datasets were calculated by the multistage sampling formula with the variance terms derived from the Bayesian model. For both krill length and bycatch fish number, vessel sample size show marked effects on CV, although haul sample size affect CV for only krill length data up to 10% haul coverage. These results suggest that data collection by scientific observers onboard commercial vessels provide an important information for the management of krill resources and Antarctic ecosystem, while we need further discussion about the optimal relative sample size to ensure the statistical precision required for the specific objective of a study with considering the cost of observer deployment.

The authors   analyzed the influence of climate changes on space-time dynamic of Antarctic krill fishery in the Area 48 using the CCAMLR fishery data and time series of ААО induces (Antarctic Oscillation Index) as the indication of climate variability.   Here we used the methods of the integrated ecosystem assessment used by ICES and the modern de-nosing data methods. The influence of climate variability was traced across long-term dynamic of fleet operation including standardized CPUE indices, monthly and daily catches.  The important evidence of ongoing climate variability is the fishery regimes switching observed in long-term fishery. Standardized CPUE index was used as an indicator of probable fishing regime switching.   The peculiarity of such switching in the entire Area 48 and its Subareas 48.2, 48.2 and 48.3 is considered.  It was found that the significant switching of fishery regime occurred in 2006, when fishery transferred to the state «high CPUE» retained during 2006-2010.  This period is characterized by the highest values of CPUE index and AAO index   reached in the Area 48 for the whole 1986-2011 observation period.  It was shown that over 2006-2011years the observed shift of the fishing seasons towards fall-winter months of the Southern hemisphere are accompanied by the shrinking of the fishing season itself. The ongoing climate variability demonstrates the possibility of new fishing regimes switching which can impact on fishery structure in years to come.   Climate changes can become the reason for the changes in abundance, distribution and life cycle of krill affecting space-time variability of fishery strategy and performance. Therefore   to support developing the approaches for management of krill fishery the following factors seem to be urgent: availability of information sufficient to detect and understand regularities and trends in krill distribution in the Area 48; forecasting methods to predict possible fishery regime switching in the years to come.

This paper briefly outlines the key scientific issues that should be resolved for providing sufficient information with the aim of quantitative understanding regularities and trends of krill spatial distribution in the Area 48 being the important information for developing management strategy for krill stock. It is proposed to developing a long-term-strategy for conducting synoptic surveys focused to the tasks outlined here. Some requirements to the design of such synoptic surveys are shown.

Practical implementation of these proposals will contribute to attaining CCAMLR goals in krill stocks management.