This study focuses on the Chamsocephahus gunnari stock around South Georgia. The principle aims are, first, to assess current and past biomass and recruitment levels and, second, to analyse the relationship between the spawning stock and number of recruits. A conventional VPA and an ad hoc tuning method are used to estimate biomass levels and fishing mortality for the period 1971/72 to 1988/89. VPA-estimates of recruitment levels are used to investigate the degree of variability and the likely statistical distribution of recruitment. Data obtained during the UK/Polish survey around South Georgia in March 1989, were included in the study.
Results indicate that the current biomass level of the C. gunnari stock around South Georgia is only about 25% of the estimated peak biomass and that catch levels observed in recent years cannot be sustained. There is no clear relationship between the size of the spawning stock and recruitment, which is highly variable
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There is no abstract available for this document.
There is no abstract available for this document.
There is no abstract available for this document.
There is no abstract available for this document.
There is no abstract available for this document.
There is no abstract available for this document.
Abstract:
The AMLR hydroacoustic system used for surveys in the vicinity of Elephant Island and King George Island during 1987-1989 has hardware and software components. The method of analysis proceeds from the basic integration data (lm bins by 1min outputs) to the stratification of these data into blocks of area and finally a total estimate of abundance and statistical confidence limits about the block estimates and the total biomass in the surveyed area. The process depends on: 1) a calibrated, towed hydroacoustic system; 2) real-time analysis of data; and 3) using a structured database which ensures data integrity and repeatability of analytic results. The variability inherent in the distribution of krill mandates the use of covariance methods for the calculation of confidence intervals. This often requires post-cruise stratification of the survey data into statistical sub-areas. The intermediate and final results of these analyses may also be used to produce other data products for comparison with environmental or other biological data.