Recruitment variability in Antarctic krill in Subarea 48.1 expressed as ‘proportional recruitment’
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Recruitment variability in Antarctic krill in Subarea 48.1 expressed as ‘proportional recruitment’

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  • Journal Title:
    CCAMLR Meetings, 2022
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  • Description:
    Proportional recruitment is a concept that summarizes the variability of new individuals entering a population over time. Two parameters characterizing proportional recruitment, the mean and standard deviation of the interannual proportion of juveniles in the population, are important inputs to the Generalised Yield Model in R (GRYM). The GRYM is a simulation framework that defines the amount of fisheries catch that is considered precautionary. It is currently under consideration by CCAMLR for managing catches of Antarctic krill. In this paper we calculate 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 are used to calculate proportional recruitment from each of these data sources using two alternative upper length bounds ('thresholds') for defining juveniles, 30 and 44 mm. Proportional recruitment parameters calculated using these 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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    CCAMLR Meetings; WG-EMM-2022/02
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    Accepted Manuscript
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