2019
DOI: 10.1016/j.fishres.2019.105320
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Exploring the utility of different tag-recovery experimental designs for use in spatially explicit, tag-integrated stock assessment models

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Cited by 10 publications
(26 citation statements)
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“…Additionally, many of the tag parameters (e.g. tag mixing and tag reporting rates) are estimable within IPMs (Figures S14-S15; Goethel et al, 2019;Vincent et al, 2017Vincent et al, , 2020, particularly if auxiliary data are available and fit directly in the model (e.g. adding an objective function component for high reward tagging data as in Polacheck, Eveson, Laslett, Pollock, & Hearn, 2006).…”
Section: Discussionmentioning
confidence: 99%
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“…Additionally, many of the tag parameters (e.g. tag mixing and tag reporting rates) are estimable within IPMs (Figures S14-S15; Goethel et al, 2019;Vincent et al, 2017Vincent et al, , 2020, particularly if auxiliary data are available and fit directly in the model (e.g. adding an objective function component for high reward tagging data as in Polacheck, Eveson, Laslett, Pollock, & Hearn, 2006).…”
Section: Discussionmentioning
confidence: 99%
“…Although the limitations must be carefully considered when using tagging data, simulation studies have increasingly demonstrated that issues with tagging data can be overcome through carefully chosen assumptions and well‐designed tagging studies (Brenden et al., 2010; Goethel et al., 2015, 2019; Saunders et al., 2019; Vincent et al., 2017, 2020). Therefore, in many instances, the benefits of including tagging data often outweigh the pitfalls for spatial IPMs (Goethel et al., 2019; Vincent et al., 2017, 2020). When only limited tag releases are possible, precision of spatial IPMs will likely decrease, but accuracy is not usually impacted (assuming that the dynamics of the tagged individuals, including movement, adequately reflect the overall population; Goethel et al., 2015b, 2019; Vincent et al., 2017).…”
Section: Discussionmentioning
confidence: 99%
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