CCAMLR

The Third Meeting of the ACAP’s Advisory Committee was held in Valdivia, Chile from 19 – 22 June 2007. It was preceded by meetings of the Status and Trends Working Group on 16 June and the Seabird Bycatch Working Group on 17-18 June 2007. This paper provides a summary of the major outcomes of the meeting.

Australia’s sub-Antarctic and Antarctic fisheries observer program is administered by the Australian Fisheries Management Authority (AFMA), with technical and data management support from the Australian Antarctic Division (AAD). Australian observers work on both trawl and longline vessels targeting finfish in the CCAMLR area. As the assessments and conservation measures employed by CCAMLR increase in sophistication, the tasks required to be completed by observers are increasing in number and complexity. Such a set of qualities is rarely available ‘off the shelf’. To ensure that observers in these fisheries are able to complete the broad range of task required under the CCAMLR System of International Scientific Observation (SISO) and under domestic legislation, a system of performance management and data quality assurance has been developed. This system covers all aspects of the observers’ experience in the work place, from initial recruitment through training, accreditation and ongoing performance assessment. Australia considers the use of such a performance management system to be essential in ensuring that high quality data continues to be collected by SISO.

This paper describes French fishery targeting Patagonian Toothfish inside CCAMLR area, what are the data collected and how they are checked, a short description of prioritisation of observer’s task is given.

SeaBird is a generalised age- and/or stage-structured seabird population dynamics model that allows a great deal of flexibility in specifying the population dynamics, parameter estimation, and model outputs. The manual provides information on how to use SeaBird, including how to run it, how to set up the input files, descriptions of the population dynamics and estimation methods, and how to generate outputs. It also contains a brief overview of the technical specifications of the software, and examples of models using SeaBird. SeaBird is designed for flexibility. It allows the user to structure the modelled population in the way that best suits the available data. Depending on these data the user may which to specify the population structure using some or all of the following characteristics: age, life stage (e.g., immature or mature), sex, or behaviour (e.g., in any year mature birds may be classified as breeders or non-breeders). Interactions with fisheries can be modelled and the user can choose the sequence of events in a model year. A wide variety of types of data can be used. Estimation can be by maximum likelihood or Bayesian. As well as generating point estimates of the parameters of interest, SeaBird can calculate likelihood or posterior profiles and can generate Bayesian posterior distributions using Monte Carlo Markov Chain methods. SeaBird can project population status into the future under various alternative scenarios. SeaBird was designed to share many features and concepts with the fishery stock assessment model CASAL (Bull et al. 2005) and users of the latter program will find it easy to adapt to SeaBird. However, there are some important differences between the programs that are described.

ic life is developed in accordance with the rules of metrology, mathematical statistics and using the biocenological regularities of water objects. The basis of evaluating the stocks of water life was investigated through biocenotic conditionality in the areas of their equal probability in concentrations. The traditional method of squares in evaluating the stocks of water life was modernized with the use of probabilistic approach, the required knowledge of rules of statistical distributions of its specific concentration. Allocation of borders in the areas of probably equal concentrations of aquatic life applied in the proposed technique offer the mean integral values of probabilities. It is recommended to minimize errors of evaluation of the aquatic life resources using the statistical method of producing the average values if it is stated that casual component is more than two times higher of the regular component in a resulting error of evaluation of the average specific concentration of water life.

Quantitative method for describing krill mass congestions based on perennial observations using trawling and hydroacoustic data is proposed. Reliable evaluation of krill resources is provided with probability methods and spatial analyses requiring knowledge of statistical distribution rules applicable for natural habitat and equal probability concentrations. Spatial analyses of krill population densities have shown mixed rules of statistical distribution over its natural habitat. Data analyses procedures applied for trawling and hydro-acoustic sampling have to in compliance with the rules of statistical distribution and principles of metrology. Division of natural habitat of the Antarctic krill into regions is based on a principle of equal probability applied for congestions instead of the principle of equal proportions. Metrological features of evaluating population densities of krill are revealed. Standard measures for the population densities of krill in natural habitat are not available, thus it is principally impossible to structure systems and random errors in evaluating process, to define their impact on final evaluation of the resource. Special metrological principles are required and proposed for the correct evaluations based on reproducibility of statistic distribution parameters for krill and minimizing miscalculations in evaluations of congestions. Evaluations regime applied for the population density of krill should be defined by reliability and admissible error of estimated resource. Traditional concepts of observation system concerning the resources of krill should be further developed with applications of rules and parameters dealing with statistical distributions of population density, information about sources of errors, tools and methods of evaluation, standard techniques of minimizing errors in evaluations taking into account biological features of krill development. Methodical standards and uniform evaluation criteria for parameter evaluations of statistical distributions should be proposed to the Countries participating in the Antarctic Treaty as proceedings regarding minimal errors in the evaluation procedure. Reliable evaluation of krill resources requires advanced technical tools and observation systems. Population density values for krill should be calculated using Aitchison delta distribution. Primary statements regarding the krill in strategic planning for fisheries should include relevant biologically valid evaluations of population numbers for krill with the maintained reliability requirements and reasonable errors in evaluating the density of populations.