The current uncertainties with regards to the Antarctic krill biomass stock status still do not allow scientists to provide the management advice on a SSMU krill catch limit allocation subdivision in Area 48. These uncertainties are enhanced by inconsistent state of exact krill catch data in fishing operations - so called "green weight issue". Due to the need to distribute the krill catch limit in Statistical Area 48 so as to ensure that land-based predators are not affected by fishing activity, the Commission has adopted the interim Conservation Measure 51-07(2009) last year. For comprehensive consideration and revision CM51-07(2009) in the 2011 CCAMLR Meeting the Commission should remind Members to provide appropriate efforts for collection data on the resource requirements of land-based predators in Statistical Area 48.
Abstract:
The Secretariat has been developing Fishery Plans under the Regulatory Framework established by the Scientific Committee and Commission. In recent years, Plans have been drafted for the krill fishery in Area 48 (see WG-EMM-01/7, 02/6 and 03/28) and other fisheries (see WAMI-01/5, WGFSA-02/9 and 03/6). Each Fishery Plan draws together the history of management measures and fishery requirements agreed by the Commission, as well as key operational information for each fishery.
In 2004, the Secretariat undertook a major re-organisation and re-construction of the database which holds the time series of information used in the Fishery Plans. This information includes:
• management measures and fishery requirements reported in the ‘Schedule of Conservation Measures in Force’;
• other management information reported in the reports of the Scientific Committee and Commission; and
• operational and catch information derived from data submitted to the CCAMLR.
In addition, the layout of the Fishery Plan was revised and the information is now presented under 3 sections:
1. management measures and fishery requirements;
2. operational aspect (i.e. “what really happened”); and
3. catches (STATLANT, fine-scale and in-season datasets).
This paper outlines these further developments.
