When are model-based stock assessments rejected for use in management and what happens then?

André E. Punt, Geoffrey N. Tuck, Jemery Day, Cristian M. Canales, Jason M. Cope, Carryn L. de Moor, José A.A. De Oliveira, Mark Dickey-Collas, Bjarki Þ. Elvarsson, Melissa A. Haltuch, Owen S. Hamel, Allan C. Hicks, Christopher M. Legault, Patrick D. Lynch, Michael J. Wilberg

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

Model-based stock assessments form a key component of the management advice for fish and invertebrate stocks worldwide. It is important for such assessments to be peer-reviewed and to pass scientific scrutiny before they can be used to inform management decision making. While it is desirable for management decisions to be based on quantitative assessments that use as much of the available data as possible, this is not always the case. A proposed assessment may be found to be unsatisfactory during the peer-review process (even if it utilizes all of the available data), leading to decisions being made using simpler approaches. This paper provides a synthesis across seven jurisdictions of the types of diagnostic statistics and plots that can be used to evaluate whether a proposed assessment is ‘best available science’, summarizes several cases where a proposed assessment was not accepted for use in management, and how jurisdictions are able to provide management advice when a stock assessment is ‘rejected.’ The paper concludes with recommended general practices for reducing subjectivity when deciding whether to accept an assessment and how to provide advice when a proposed assessment is rejected.
Original languageEnglish
Article number105465
JournalFisheries Research
Volume224
ISSN0165-7836
DOIs
Publication statusPublished - 2020

Keywords

  • Peer review
  • Retrospective analysis
  • Stock assessment
  • Uncertainty

Cite this

Punt, A. E., Tuck, G. N., Day, J., Canales, C. M., Cope, J. M., de Moor, C. L., ... Wilberg, M. J. (2020). When are model-based stock assessments rejected for use in management and what happens then? Fisheries Research, 224, [105465]. https://doi.org/10.1016/j.fishres.2019.105465
Punt, André E. ; Tuck, Geoffrey N. ; Day, Jemery ; Canales, Cristian M. ; Cope, Jason M. ; de Moor, Carryn L. ; De Oliveira, José A.A. ; Dickey-Collas, Mark ; Elvarsson, Bjarki Þ. ; Haltuch, Melissa A. ; Hamel, Owen S. ; Hicks, Allan C. ; Legault, Christopher M. ; Lynch, Patrick D. ; Wilberg, Michael J. / When are model-based stock assessments rejected for use in management and what happens then?. In: Fisheries Research. 2020 ; Vol. 224.
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abstract = "Model-based stock assessments form a key component of the management advice for fish and invertebrate stocks worldwide. It is important for such assessments to be peer-reviewed and to pass scientific scrutiny before they can be used to inform management decision making. While it is desirable for management decisions to be based on quantitative assessments that use as much of the available data as possible, this is not always the case. A proposed assessment may be found to be unsatisfactory during the peer-review process (even if it utilizes all of the available data), leading to decisions being made using simpler approaches. This paper provides a synthesis across seven jurisdictions of the types of diagnostic statistics and plots that can be used to evaluate whether a proposed assessment is ‘best available science’, summarizes several cases where a proposed assessment was not accepted for use in management, and how jurisdictions are able to provide management advice when a stock assessment is ‘rejected.’ The paper concludes with recommended general practices for reducing subjectivity when deciding whether to accept an assessment and how to provide advice when a proposed assessment is rejected.",
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author = "Punt, {Andr{\'e} E.} and Tuck, {Geoffrey N.} and Jemery Day and Canales, {Cristian M.} and Cope, {Jason M.} and {de Moor}, {Carryn L.} and {De Oliveira}, {Jos{\'e} A.A.} and Mark Dickey-Collas and Elvarsson, {Bjarki {\TH}.} and Haltuch, {Melissa A.} and Hamel, {Owen S.} and Hicks, {Allan C.} and Legault, {Christopher M.} and Lynch, {Patrick D.} and Wilberg, {Michael J.}",
year = "2020",
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Punt, AE, Tuck, GN, Day, J, Canales, CM, Cope, JM, de Moor, CL, De Oliveira, JAA, Dickey-Collas, M, Elvarsson, BÞ, Haltuch, MA, Hamel, OS, Hicks, AC, Legault, CM, Lynch, PD & Wilberg, MJ 2020, 'When are model-based stock assessments rejected for use in management and what happens then?', Fisheries Research, vol. 224, 105465. https://doi.org/10.1016/j.fishres.2019.105465

When are model-based stock assessments rejected for use in management and what happens then? / Punt, André E.; Tuck, Geoffrey N.; Day, Jemery; Canales, Cristian M.; Cope, Jason M.; de Moor, Carryn L.; De Oliveira, José A.A.; Dickey-Collas, Mark; Elvarsson, Bjarki Þ.; Haltuch, Melissa A.; Hamel, Owen S.; Hicks, Allan C.; Legault, Christopher M.; Lynch, Patrick D.; Wilberg, Michael J.

In: Fisheries Research, Vol. 224, 105465, 2020.

Research output: Contribution to journalJournal articleResearchpeer-review

TY - JOUR

T1 - When are model-based stock assessments rejected for use in management and what happens then?

AU - Punt, André E.

AU - Tuck, Geoffrey N.

AU - Day, Jemery

AU - Canales, Cristian M.

AU - Cope, Jason M.

AU - de Moor, Carryn L.

AU - De Oliveira, José A.A.

AU - Dickey-Collas, Mark

AU - Elvarsson, Bjarki Þ.

AU - Haltuch, Melissa A.

AU - Hamel, Owen S.

AU - Hicks, Allan C.

AU - Legault, Christopher M.

AU - Lynch, Patrick D.

AU - Wilberg, Michael J.

PY - 2020

Y1 - 2020

N2 - Model-based stock assessments form a key component of the management advice for fish and invertebrate stocks worldwide. It is important for such assessments to be peer-reviewed and to pass scientific scrutiny before they can be used to inform management decision making. While it is desirable for management decisions to be based on quantitative assessments that use as much of the available data as possible, this is not always the case. A proposed assessment may be found to be unsatisfactory during the peer-review process (even if it utilizes all of the available data), leading to decisions being made using simpler approaches. This paper provides a synthesis across seven jurisdictions of the types of diagnostic statistics and plots that can be used to evaluate whether a proposed assessment is ‘best available science’, summarizes several cases where a proposed assessment was not accepted for use in management, and how jurisdictions are able to provide management advice when a stock assessment is ‘rejected.’ The paper concludes with recommended general practices for reducing subjectivity when deciding whether to accept an assessment and how to provide advice when a proposed assessment is rejected.

AB - Model-based stock assessments form a key component of the management advice for fish and invertebrate stocks worldwide. It is important for such assessments to be peer-reviewed and to pass scientific scrutiny before they can be used to inform management decision making. While it is desirable for management decisions to be based on quantitative assessments that use as much of the available data as possible, this is not always the case. A proposed assessment may be found to be unsatisfactory during the peer-review process (even if it utilizes all of the available data), leading to decisions being made using simpler approaches. This paper provides a synthesis across seven jurisdictions of the types of diagnostic statistics and plots that can be used to evaluate whether a proposed assessment is ‘best available science’, summarizes several cases where a proposed assessment was not accepted for use in management, and how jurisdictions are able to provide management advice when a stock assessment is ‘rejected.’ The paper concludes with recommended general practices for reducing subjectivity when deciding whether to accept an assessment and how to provide advice when a proposed assessment is rejected.

KW - Peer review

KW - Retrospective analysis

KW - Stock assessment

KW - Uncertainty

U2 - 10.1016/j.fishres.2019.105465

DO - 10.1016/j.fishres.2019.105465

M3 - Journal article

VL - 224

JO - Fisheries Research

JF - Fisheries Research

SN - 0165-7836

M1 - 105465

ER -