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  • 1
    Online Resource
    Online Resource
    Oxford University Press (OUP) ; 2019
    In:  ICES Journal of Marine Science Vol. 76, No. 4 ( 2019-07-01), p. 837-847
    In: ICES Journal of Marine Science, Oxford University Press (OUP), Vol. 76, No. 4 ( 2019-07-01), p. 837-847
    Abstract: To assess fishing effects on data-poor species, impact can be derived from spatial overlap between species distribution and fishing effort and gear catchability. Here, we enhance the existing sustainability assessment for fishing effect method by estimating gear efficiency and heterogeneous density from sporadic catch data. We apply the method to two chondrichthyan bycatch species, Bight Skate and Draughtboard Shark in Australia, to assess cumulative fishing mortality (Fcum) from multiple fisheries. Gear efficiency is estimated from a Bayesian mixture distribution model and fish density is predicted by a generalized additive model. These results, combined with actual fishing effort, allow estimation of fishing mortality in each sector and subsequently, the Fcum. Risk is quantified by comparing Fcum with reference points based on life history parameters. When only the point estimates were considered, our result indicates that for the period 2009 and 2010 Bight Skate caught in 14 fisheries was at high cumulative risk (Fcum ≥ Flim) while Draughtboard Shark caught by 19 fisheries was at low cumulative risk (Fcum ≤ Fmsy). Because of the high cost of conducting cumulative risk assessments, we recommend examining the distribution of fishing effort across fisheries before carrying out the assessments.
    Type of Medium: Online Resource
    ISSN: 1054-3139 , 1095-9289
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2019
    detail.hit.zdb_id: 2463178-4
    detail.hit.zdb_id: 1468003-8
    detail.hit.zdb_id: 29056-7
    SSG: 12
    SSG: 21,3
    Location Call Number Limitation Availability
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  • 2
    Online Resource
    Online Resource
    Oxford University Press (OUP) ; 2018
    In:  ICES Journal of Marine Science Vol. 75, No. 3 ( 2018-05-01), p. 964-976
    In: ICES Journal of Marine Science, Oxford University Press (OUP), Vol. 75, No. 3 ( 2018-05-01), p. 964-976
    Type of Medium: Online Resource
    ISSN: 1054-3139 , 1095-9289
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2018
    detail.hit.zdb_id: 2463178-4
    detail.hit.zdb_id: 1468003-8
    detail.hit.zdb_id: 29056-7
    SSG: 12
    SSG: 21,3
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
  • 3
    In: ICES Journal of Marine Science, Oxford University Press (OUP), Vol. 78, No. 4 ( 2021-08-20), p. 1209-1216
    Abstract: This paper explores the possibility of using the ensemble modelling paradigm to fully capture assessment uncertainty and improve the robustness of advice provision. We identify and discuss advantages and challenges of ensemble modelling approaches in the context of scientific advice. There are uncertainties associated with every phase in the stock assessment process: data collection, assessment model choice, model assumptions, interpretation of risk, up to the implementation of management advice. Additionally, the dynamics of fish populations are complex, and our incomplete understanding of those dynamics and limited observations of important mechanisms, necessitate that models are simpler than nature. The aim is for the model to capture enough of the dynamics to accurately estimate trends and abundance, and provide the basis for robust advice about sustainable harvests. The status quo approach to assessment modelling has been to identify the “best” model and generate advice from that model, mostly ignoring advice from other model configurations regardless of how closely they performed relative to the chosen model. We discuss and make suggestions about the utility of ensemble models, including revisions to the formal process of providing advice to management bodies, and recommend further research to evaluate potential gains in modelling and advice performance.
    Type of Medium: Online Resource
    ISSN: 1054-3139 , 1095-9289
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2021
    detail.hit.zdb_id: 2463178-4
    detail.hit.zdb_id: 1468003-8
    detail.hit.zdb_id: 29056-7
    SSG: 12
    SSG: 21,3
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
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