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Modelling fish growth with imperfect data: The case of Trachurus picturatus

2022Journal article Open access
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dc.contributor.authorNeves, Ana
dc.contributor.authorVieira, Ana Rita
dc.contributor.authorSequeira, Vera
dc.contributor.authorSilva, Elisabete
dc.contributor.authorSilva, Frederica
dc.contributor.authorDuarte, Ana Marta
dc.contributor.authorMendes, Susana
dc.contributor.authorGanhão, Rui
dc.contributor.authorAssis, Carlos
dc.contributor.authorRebelo, Rui
dc.contributor.authorMagalhães, Maria Filomena
dc.contributor.authorGil, Maria Manuel
dc.contributor.authorGordo, Leonel Serrano
dc.date.accessioned2022-08-22T12:46:25Z
dc.date.available2022-08-22T12:46:25Z
dc.date.issued2022
dc.descriptionFunding: This publication was funded by the European Maritime and Fisheries Fund MAR2020 project “VALOREJET: Valorização de espécies rejeitadas e de baixo valor comercial”, MAR-01.03.01-FEAMP-0003 and by Fundação para a Ciência e Tecnologia through research contracts attributed to Vera Sequeira (CEECIND/02705/2017) and Ana Rita Vieira (CEECIND/01528/2017) and strategic project UIBD/04292/2020.pt_PT
dc.description.abstractGrowth modelling is essential to inform fisheries management but is often hampered by sampling biases and imperfect data. Additional methods such as interpolating data through backcalculation may be used to account for sampling bias but are often complex and time-consuming. Here, we present an approach to improve plausibility in growth estimates when small individuals are under-sampled, based on Bayesian fitting growth models using Markov Chain Monte Carlo (MCMC) with informative priors on growth parameters. Focusing on the blue jack mackerel, Trachurus picturatus, which is an important commercial fish in the southern northeast Atlantic, this Bayesian approach was evaluated in relation to standard growth model fitting methods, using both direct readings and back-calculation data. Matched growth parameter estimates were obtained with the von Bertalanffy growth function applied to back-calculated length at age and the Bayesian fitting, using MCMC to direct age readings, with both outperforming all other methods assessed. These results indicate that Bayesian inference may be a powerful addition in growth modelling using imperfect data and should be considered further in age and growth studies, provided relevant biological information can be gathered and included in the analyses.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationNeves, A.; Vieira, A.R.; Sequeira, V.; Silva, E.; Silva, F.; Duarte, A.M.; Mendes, S.; Ganhão, R.; Assis, C.; Rebelo, R.; et al. Modelling Fish Growth with Imperfect Data: The Case of Trachurus picturatus. Fishes 2022, 7, 52. https://doi.org/10.3390/fishes7010052pt_PT
dc.identifier.doi10.3390/fishes7010052pt_PT
dc.identifier.issn2410-3888
dc.identifier.urihttp://hdl.handle.net/10400.8/7566
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherMDPIpt_PT
dc.relationNot Available
dc.relationNot Available
dc.relationMarine and Environmental Sciences Centre
dc.relation.publisherversionhttps://www.mdpi.com/2410-3888/7/1/52pt_PT
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectBayesianpt_PT
dc.subjectCarangidaept_PT
dc.subjectFisheriespt_PT
dc.subjectMortalitypt_PT
dc.titleModelling fish growth with imperfect data: The case of Trachurus picturatuspt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleNot Available
oaire.awardTitleNot Available
oaire.awardTitleMarine and Environmental Sciences Centre
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/CEEC IND 2017/CEECIND%2F02705%2F2017%2FCP1387%2FCT0042/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/CEEC IND 2017/CEECIND%2F01528%2F2017%2FCP1387%2FCT0040/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F04292%2F2020/PT
oaire.citation.issue1pt_PT
oaire.citation.titleFishespt_PT
oaire.citation.volume7pt_PT
oaire.fundingStreamCEEC IND 2017
oaire.fundingStreamCEEC IND 2017
oaire.fundingStream6817 - DCRRNI ID
person.familyNameNeves
person.familyNameSequeira
person.familyNameSilva
person.familyNameCardoso Duarte
person.familyNameMENDES
person.familyNameManeta Ganhão
person.familyNameBorges Sampaio e Rebelo
person.familyNameMagalhães
person.familyNameGil
person.familyNameGordo
person.givenNameAna
person.givenNameVera
person.givenNameFrederica
person.givenNameAna Marta
person.givenNameSUSANA
person.givenNameRui Manuel
person.givenNameRui Miguel
person.givenNameMaria Filomena
person.givenNameMaria M
person.givenNameLeonel
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project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
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