Simulation testing the robustness of stock assessment models to error:some results from the ICES Strategic Initiative on Stock Assessment Methods

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dc.contributor.authorDeroba, J J
dc.contributor.authorButterworth, Doug S
dc.contributor.authorMethot, R D Jr
dc.contributor.authorDe Oliveira, J
dc.contributor.authorFernandez, C
dc.contributor.authorNielsen, A
dc.contributor.authorCadrin, S X
dc.contributor.authorDickey-Collas, M
dc.contributor.authorLegault, C M
dc.contributor.authorIanelli, J
dc.contributor.authorValero, J L
dc.contributor.authorNeedle, C
dc.contributor.authorO\'Malley, J M
dc.contributor.authorChang, Y-J
dc.contributor.authorThompson, G G
dc.contributor.authorCanales, C
dc.contributor.authorSwain, D P
dc.contributor.authorMiller, D C M
dc.contributor.authorHintzen, N T
dc.contributor.authorBertignac, M
dc.contributor.authorIbaibarriaga, L
dc.contributor.authorSilva, A
dc.contributor.authorMurta, A
dc.contributor.authorKell, L T
dc.contributor.authorDe Moor, Carryn L
dc.contributor.authorParma, A M
dc.contributor.authorDichmont, C M
dc.contributor.authorRestrepo, V R
dc.contributor.authorYe, Y
dc.contributor.authorJardim, E
dc.contributor.authorSpencer, P D
dc.contributor.authorHanselman, D H
dc.contributor.authorBlaylock, J
dc.contributor.authorMood, M
dc.contributor.authorHulson, P -J F
dc.date.accessioned2016-03-10T10:25:09Z
dc.date.available2016-03-10T10:25:09Z
dc.date.issued2015
dc.date.updated2016-03-10T10:13:00Z
dc.description.abstractThe World Conference on Stock Assessment Methods (July 2013) included a workshop on testing assessment methods through simulations. The exercise was made up of two steps applied to datasets from 14 representative fish stocks from around the world. Step 1 involved applying stock assessments to datasets with varying degrees of effort dedicated to optimizing fit. Step 2 was applied to a subset of the stocks and involved characteristics of given model fits being used to generate pseudo-data with error. These pseudo-data were then provided to assessment modellers and fits to the pseudo-data provided consistency checks within (self-tests) and among (cross-tests) assessment models. Although trends in biomass were often similar across models, the scaling of absolute biomass was not consistent across models. Similar types of models tended to perform similarly (e.g. age based or production models). Self-testing and cross-testing of models are a useful diagnostic approach, and suggested that estimates in the most recent years of time-series were the least robust. Results from the simulation exercise provide a basis for guidance on future large-scale simulation experiments and demonstrate the need for strategic investments in the evaluation and development of stock assessment methodsen_ZA
dc.identifierhttp://dx.doi.org/10.1093/icesjms/fst237
dc.identifier.apacitationDeroba, J. J., Butterworth, D. S., Methot, R. D. J., De Oliveira, J., Fernandez, C., Nielsen, A., ... Hulson, P. -. F. (2015). Simulation testing the robustness of stock assessment models to error:some results from the ICES Strategic Initiative on Stock Assessment Methods. <i>ICES Journal of Marine Science</i>, http://hdl.handle.net/11427/17626en_ZA
dc.identifier.chicagocitationDeroba, J J, Doug S Butterworth, R D Jr Methot, J De Oliveira, C Fernandez, A Nielsen, S X Cadrin, et al "Simulation testing the robustness of stock assessment models to error:some results from the ICES Strategic Initiative on Stock Assessment Methods." <i>ICES Journal of Marine Science</i> (2015) http://hdl.handle.net/11427/17626en_ZA
dc.identifier.citationDeroba, J. J., Butterworth, D. S., Methot, R. D., De Oliveira, J. A. A., Fernandez, C., Nielsen, A., ... & Valero, J. L. (2015). Simulation testing the robustness of stock assessment models to error: some results from the ICES strategic initiative on stock assessment methods. ICES Journal of Marine Science: Journal du Conseil, 72(1), 19-30.en_ZA
dc.identifier.issn1054-3139en_ZA
dc.identifier.ris TY - Journal Article AU - Deroba, J J AU - Butterworth, Doug S AU - Methot, R D Jr AU - De Oliveira, J AU - Fernandez, C AU - Nielsen, A AU - Cadrin, S X AU - Dickey-Collas, M AU - Legault, C M AU - Ianelli, J AU - Valero, J L AU - Needle, C AU - O'Malley, J M AU - Chang, Y-J AU - Thompson, G G AU - Canales, C AU - Swain, D P AU - Miller, D C M AU - Hintzen, N T AU - Bertignac, M AU - Ibaibarriaga, L AU - Silva, A AU - Murta, A AU - Kell, L T AU - De Moor, Carryn L AU - Parma, A M AU - Dichmont, C M AU - Restrepo, V R AU - Ye, Y AU - Jardim, E AU - Spencer, P D AU - Hanselman, D H AU - Blaylock, J AU - Mood, M AU - Hulson, P -J F AB - The World Conference on Stock Assessment Methods (July 2013) included a workshop on testing assessment methods through simulations. The exercise was made up of two steps applied to datasets from 14 representative fish stocks from around the world. Step 1 involved applying stock assessments to datasets with varying degrees of effort dedicated to optimizing fit. Step 2 was applied to a subset of the stocks and involved characteristics of given model fits being used to generate pseudo-data with error. These pseudo-data were then provided to assessment modellers and fits to the pseudo-data provided consistency checks within (self-tests) and among (cross-tests) assessment models. Although trends in biomass were often similar across models, the scaling of absolute biomass was not consistent across models. Similar types of models tended to perform similarly (e.g. age based or production models). Self-testing and cross-testing of models are a useful diagnostic approach, and suggested that estimates in the most recent years of time-series were the least robust. Results from the simulation exercise provide a basis for guidance on future large-scale simulation experiments and demonstrate the need for strategic investments in the evaluation and development of stock assessment methods DA - 2015 DB - OpenUCT DP - University of Cape Town J1 - ICES Journal of Marine Science LK - https://open.uct.ac.za PB - University of Cape Town PY - 2015 SM - 1054-3139 T1 - Simulation testing the robustness of stock assessment models to error:some results from the ICES Strategic Initiative on Stock Assessment Methods TI - Simulation testing the robustness of stock assessment models to error:some results from the ICES Strategic Initiative on Stock Assessment Methods UR - http://hdl.handle.net/11427/17626 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/17626
dc.identifier.vancouvercitationDeroba JJ, Butterworth DS, Methot RDJ, De Oliveira J, Fernandez C, Nielsen A, et al. Simulation testing the robustness of stock assessment models to error:some results from the ICES Strategic Initiative on Stock Assessment Methods. ICES Journal of Marine Science. 2015; http://hdl.handle.net/11427/17626.en_ZA
dc.languageengen_ZA
dc.publisherOxford University Pressen_ZA
dc.publisher.departmentMarine Resource Assessment and Management Groupen_ZA
dc.publisher.facultyFaculty of Scienceen_ZA
dc.publisher.institutionUniversity of Cape Town
dc.sourceICES Journal of Marine Scienceen_ZA
dc.source.urihttp://icesjms.oxfordjournals.org/
dc.subject.othercross-test
dc.subject.othermodel comparison
dc.subject.otherpseudo data
dc.subject.otherself-test
dc.subject.othertime-series analysis
dc.subject.othervpa
dc.titleSimulation testing the robustness of stock assessment models to error:some results from the ICES Strategic Initiative on Stock Assessment Methodsen_ZA
dc.typeJournal Articleen_ZA
uct.type.filetypeText
uct.type.filetypeImage
uct.type.publicationResearchen_ZA
uct.type.resourceArticleen_ZA
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