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  • CCAMLR Science, Volume 24 (2023):1-18

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CCAMLR Science, Volume 24 (2023):1-18

Journal Volume:
CCAMLR Science, Volume 24
Page Numbers:
1-18
Auteur(s):
D. Kinzey, J.T. Hinke, C.S. Reiss and G.M. Watters
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Recruitment variability of Antarctic krill in Subarea 48.1 expressed as ‘proportional recruitment’: length threshold effects

Abstract / Description: 

Proportional recruitment summarises the variability of new individuals entering a population over time. Two parameters characterising proportional recruitment, the mean and standard deviation of the interannual proportion of juveniles in the population, are important inputs to the generalised yield model (Grym) when the proportional recruitment option is being used to set fishery catches. The Grym is a simulation framework that can define the amount of fisheries catch that is considered precautionary as defined by decision rules. It is currently under consideration by CCAMLR for managing catches of Antarctic krill. This study calculated proportional recruitment of krill from seven data sources in Subarea 48.1 representing research trawl surveys, fishery observer data and predator diets. Krill length-frequency distributions provided values of proportional recruitment from each of these data sources using a range of alternative upper length bounds (‘thresholds’) from 30 to 44 mm for defining juveniles. All datasets tracked the same interannual peaks and troughs in proportional recruitment. Proportional recruitment parameters calculated using the alternative thresholds from the same datasets varied widely. Across all data sources and thresholds, the interannual mean proportional recruitment of krill varied from 0.02 to 0.76 with standard deviations varying from 0.03 to 0.3. The choice of length threshold had a larger effect on the proportional recruitment parameters than differences among datasets. The potential importance of size selectivity in krill samples, especially if smaller bounds on the juvenile length threshold are assigned, could require adjusting observed frequencies for the lower selectivity of smaller individuals. These results highlight the importance of deciding which upper length bound and which data source(s) to use to identify juveniles in calculating the parameters to be supplied to the Grym.

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