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    Estimating future krill catches that meet the CCAMLR and alternative decision rules for FAO Subarea 48.1 using an integrated assessment model

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    Номер документа:
    WG-EMM-15/51 Rev. 1
    D. Kinzey, G.M. Watters and C.S. Reiss (USA)
    Представлено (имя):
    Dr Doug Kinzey (Соединенные Штаты Америки)
    Утверждено (имя):
    Admin Admin (Секретариат АНТКОМ)
    Пункт(ы) повестки дня

    An integrated assessment model for Antarctic krill in FAO Subarea 48.1 that incorporates catch and length-composition data from the krill fishery with biomass indices and length-compositions from research surveys has been developed. The model uses statistical fits to these data to estimate the effects of the fishery on the krill population. The model estimates parameters representing krill population biology and the fishery during the period with data (1976 to 2014 in these models) and then applies these parameter values to future projections (2015-2034) at pre-specified levels of future catches. The model can compare predicted krill spawning biomass expected with projected future catches to the CCAMLR decision rules. An alternative pair of decision rules to those currently employed by CCAMLR are also applied to the projections. The alternative rules are based on comparing krill spawning biomass expected under projected future catch levels to spawning biomass expected without any fishing during the same future period. The CCAMLR rules are based on comparisons to estimated pre-exploitation spawning biomass instead of to projections with no fishing. Catch levels that meet the various decision criteria are identified and compared. Arbitrary time-series of future annual recruitments may be supplied to the model. Example estimates of spawning biomass for different future levels of catch, assuming recruitment in the future will be the same as recruitment estimated during the period for which survey and fishery data were available, are reported. The effects of using different data sources and weightings on the estimates of stock status during the estimation period are explored.