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    Investigating the adherence of fisheries’ tagging data-sets to mark-recapture assumptions

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    Document Number:
    WG-SAM-2025/17
    Author(s):
    Masere, C., A. Coghlan, D. Maschette and P. Ziegler
    Submitted By:
    Dr Cara Masere (Australia)
    Approved By:
    Dr Philippe Ziegler (Australia)
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    Abstract

    Tagging studies can provide key insights into species’ growth, movement, and habitat preferences.  Most often such data is incorporated within mark-recapture models which enable estimation of parameters such as abundance, survival and sighting probability.  For all statistical analyses it is best practice to undertake appropriate data exploration to ensure the data-set is fit for purpose and in alignment with statistical assumptions of the given analysis.  The ability to meet all assumptions without reservation is typically not plausible.  Instead a clear understanding of which assumptions might be violated and how severely they affect your estimates is a useful approach.  However, when assumptions are strongly inconsistent and cannot be met, advanced models that relax specific assumptions should be considered.