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    Monitoring the effects of environmental variability and climate change on toothfish assessments

    Solicitar acceso a documento de reunión
    Número de documento:
    WS-CC-2023/20
    Autor(es):
    Pinkerton, M., J. Devine, A. Dunn and S. Mormede
    Presentado por:
    Mr Nathan Walker (Nueva Zelandia)
    Aprobado por:
    Mr Nathan Walker (Nueva Zelandia)
    Resumen

    The effects of environmental variability and change on toothfish population dynamics and productivity are largely unknown and are difficult to predict given our current understanding of the Southern Ocean environment, species and ecosystems. In 2018 a preliminary method was endorsed by CCAMLR Scientific Committee whereby existing information from toothfish fisheries could be used to identify changes to key stock productivity parameters that have occurred or may currently be occurring as a consequence of environmental variability and change, including that due to global climate change. Since 2018, a number of Fishery Reports have included this information. The next step is to consider the impact of sustained changes (multi-year trends) in biological parameters on yield assessment to reduce uncertainty in management advice due to climate variability and change. The parameters that could be evaluated for the effects of environmental variability and change include: (1) mean recruitment (ȳ); (2) recruitment variability (σR); (3) mean length at age; (4) mean weight at length; (5) natural mortality (m); and (6) maturation ogives. Other factors that may impact assumptions underlying the assessments that could also be considered include stock distribution (for example, for its impact on tagged fish distribution or research survey interpretation), sex ratio in adults or recruits (indicating pre-recruitment processes, maturation or other sex specific changes) and the ages or lengths observed in the fishery (indicating changes in vulnerability patterns or mortality). We recommend that CCAMLR develop methods across finfish fisheries in the Convention Area to (1) consistently identify long-term changes in key parameters (as above) during characterisation and/or assessment stages; (2) test for long-term change through spatiotemporal analyses; (3) request WG-FSA develop a template for reporting; and (4) explore the effect of observed changes on stock size, productivity, distribution, and yield.