Abordagem bayesiana para modelos dinâmicos de biomassa
Autor(a) principal: | |
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Data de Publicação: | 2018 |
Tipo de documento: | Tese |
Idioma: | por |
Título da fonte: | Biblioteca Digital de Teses e Dissertações da UFRPE |
Texto Completo: | http://www.tede2.ufrpe.br:8080/tede2/handle/tede2/7237 |
Resumo: | Tuna and tuna-like species represent a great attraction for companies and fishers in general, due to their meat quality, their high commercial value and their extensive distribution in the oceans. Appropriate management is fundamental to the survival of some species, and to the sustainability of fi sheries. In this way, knowledge about abundance estimates and population biomass variations is paramount for sheries management. Dynamic models of biomass are essential techniques for calculating the estimates. This study proposed the use of Bayesian analysis for the models of Fox, Schaefer and Pella-Tomlinson. Initially, the objective was to evaluate the accuracy and precision of the information acquired about the parameters of the models. For this, catch and catch per unit effort data of the South Atlantic sword sh (Xiphias gladius) were used. It was concluded that there was no progress on precision and accuracy, taking as true "values" for the parameters the estimates of the last report of The International Commission for the Conservation of Atlantic Tunas (ICCAT). Sequentially, the objective was to evaluate the dynamic model of the biomass of Pella and Tomlinson, considering the variation and the fixation of the shape parameter in a scalar value. In this case, were used catch and catch per unit effort data of bigeye tuna (Thunnus obesus) of Atlantic. It was concluded that the model of Pella and Tomlinson with estimation of the shape parameter through of a prior distribution is more susceptible to in influences of non informative data and with discrepant points, and produces estimates more imprecise than when the form parameter is set as a scalar value, in the models of Schaefer and Fox. |
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ANDRADE, Humber Agrelli deDUARTE NETO, Paulo JoséSTOSIC, TatijanaSILVA, Antonio Samuel Alves daOLINDA, Ricardo Alves dehttp://lattes.cnpq.br/0565638399131481XAVIER, Érika Fialho Morais2018-05-09T13:31:41Z2018-02-23XAVIER, Érika Fialho Morais. Abordagem bayesiana para modelos dinâmicos de biomassa. 2018. 86 f. Tese (Programa de Pós-Graduação em Biometria e Estatística Aplicada) - Universidade Federal Rural de Pernambuco, Recife.http://www.tede2.ufrpe.br:8080/tede2/handle/tede2/7237Tuna and tuna-like species represent a great attraction for companies and fishers in general, due to their meat quality, their high commercial value and their extensive distribution in the oceans. Appropriate management is fundamental to the survival of some species, and to the sustainability of fi sheries. In this way, knowledge about abundance estimates and population biomass variations is paramount for sheries management. Dynamic models of biomass are essential techniques for calculating the estimates. This study proposed the use of Bayesian analysis for the models of Fox, Schaefer and Pella-Tomlinson. Initially, the objective was to evaluate the accuracy and precision of the information acquired about the parameters of the models. For this, catch and catch per unit effort data of the South Atlantic sword sh (Xiphias gladius) were used. It was concluded that there was no progress on precision and accuracy, taking as true "values" for the parameters the estimates of the last report of The International Commission for the Conservation of Atlantic Tunas (ICCAT). Sequentially, the objective was to evaluate the dynamic model of the biomass of Pella and Tomlinson, considering the variation and the fixation of the shape parameter in a scalar value. In this case, were used catch and catch per unit effort data of bigeye tuna (Thunnus obesus) of Atlantic. It was concluded that the model of Pella and Tomlinson with estimation of the shape parameter through of a prior distribution is more susceptible to in influences of non informative data and with discrepant points, and produces estimates more imprecise than when the form parameter is set as a scalar value, in the models of Schaefer and Fox.Espécies de atuns e afins representam um grande atrativo para empresas e pescadores em geral, em virtude da qualidade da carne, do alto valor comercial e da ampla distribuição nos oceanos. Uma gestão adequada é fundamental para a sobrevivência de algumas espécies e para a sustentabilidade da pesca, e o conhecimento sobre estimativas de abundância e variações da biomassa das populações é primordial para a gestão de pesca. Os modelos dinâmicos de biomassa são importantes técnicas para o cálculo destas estimativas. Este estudo propôs o uso da análise bayesiana para os modelos de Fox, Schaefer e Pella-Tomlinson. Inicialmente, objetivou-se avaliar a acurácia e a precisão da informação adquirida ao longo dos anos sobre os parâmetros dos modelos. Para isto, utilizaram-se dados de captura e captura por unidade de esforço do espadarte (Xiphias gladius) do Atlântico Sul. Concluiu-se que não houve avanço quanto à precisão e acurácia, tomando como valores "verdadeiros" para os parâmetros as estimativas do último relatatório da International Commission for the Conservation of Atlantic Tunas (ICCAT). Sequencialmente, objetivou-se avaliar o modelo dinâmico de biomassa de Pella e Tomlinson, considerando a variação e a fixação do parâmetro de forma em um valor escalar. Neste caso, utilizaram-se dados de captura por unidade de esforço e captura da albacora bandolim (Thunnus obesus) do Atlântico. Concluiu-se que o modelo de Pella e Tomlinson com estimação do parâmetro de forma por meio de uma priori é mais susceptível às Influências de dados pouco informativos e com pontos discrepantes e produz estimativas mais imprecisas do que quando se fi xa o parâmetro de forma em um valor escalar, nos modelos de Schaefer e Fox.Submitted by Mario BC (mario@bc.ufrpe.br) on 2018-05-09T13:31:41Z No. of bitstreams: 1 Erika Fialho Morais Xavier.pdf: 2058672 bytes, checksum: c940d090f0c0320e8f1d36bc1e912cf9 (MD5)Made available in DSpace on 2018-05-09T13:31:41Z (GMT). No. of bitstreams: 1 Erika Fialho Morais Xavier.pdf: 2058672 bytes, checksum: c940d090f0c0320e8f1d36bc1e912cf9 (MD5) Previous issue date: 2018-02-23Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPESapplication/pdfporUniversidade Federal Rural de PernambucoPrograma de Pós-Graduação em Biometria e Estatística AplicadaUFRPEBrasilDepartamento de Estatística e InformáticaAnálise bayesianaModelo de produçãoBiomassaEspadarteAlbacora bandolimCIENCIAS EXATAS E DA TERRA::PROBABILIDADE E ESTATISTICAAbordagem bayesiana para modelos dinâmicos de biomassainfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesis768382242446187918600600600600-6774555140396120501-58364078281851435172075167498588264571info:eu-repo/semantics/openAccessreponame:Biblioteca Digital de Teses e Dissertações da UFRPEinstname:Universidade Federal Rural de Pernambuco (UFRPE)instacron:UFRPEORIGINALErika Fialho Morais Xavier.pdfErika Fialho Morais Xavier.pdfapplication/pdf2058672http://www.tede2.ufrpe.br:8080/tede2/bitstream/tede2/7237/2/Erika+Fialho+Morais+Xavier.pdfc940d090f0c0320e8f1d36bc1e912cf9MD52LICENSElicense.txtlicense.txttext/plain; charset=utf-82165http://www.tede2.ufrpe.br:8080/tede2/bitstream/tede2/7237/1/license.txtbd3efa91386c1718a7f26a329fdcb468MD51tede2/72372018-05-09 10:31:41.652oai:tede2: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Biblioteca Digital de Teses e Dissertaçõeshttp://www.tede2.ufrpe.br:8080/tede/PUBhttp://www.tede2.ufrpe.br:8080/oai/requestbdtd@ufrpe.br ||bdtd@ufrpe.bropendoar:2024-05-28T12:35:23.279204Biblioteca Digital de Teses e Dissertações da UFRPE - Universidade Federal Rural de Pernambuco (UFRPE)false |
dc.title.por.fl_str_mv |
Abordagem bayesiana para modelos dinâmicos de biomassa |
title |
Abordagem bayesiana para modelos dinâmicos de biomassa |
spellingShingle |
Abordagem bayesiana para modelos dinâmicos de biomassa XAVIER, Érika Fialho Morais Análise bayesiana Modelo de produção Biomassa Espadarte Albacora bandolim CIENCIAS EXATAS E DA TERRA::PROBABILIDADE E ESTATISTICA |
title_short |
Abordagem bayesiana para modelos dinâmicos de biomassa |
title_full |
Abordagem bayesiana para modelos dinâmicos de biomassa |
title_fullStr |
Abordagem bayesiana para modelos dinâmicos de biomassa |
title_full_unstemmed |
Abordagem bayesiana para modelos dinâmicos de biomassa |
title_sort |
Abordagem bayesiana para modelos dinâmicos de biomassa |
author |
XAVIER, Érika Fialho Morais |
author_facet |
XAVIER, Érika Fialho Morais |
author_role |
author |
dc.contributor.advisor1.fl_str_mv |
ANDRADE, Humber Agrelli de |
dc.contributor.referee1.fl_str_mv |
DUARTE NETO, Paulo José |
dc.contributor.referee2.fl_str_mv |
STOSIC, Tatijana |
dc.contributor.referee3.fl_str_mv |
SILVA, Antonio Samuel Alves da |
dc.contributor.referee4.fl_str_mv |
OLINDA, Ricardo Alves de |
dc.contributor.authorLattes.fl_str_mv |
http://lattes.cnpq.br/0565638399131481 |
dc.contributor.author.fl_str_mv |
XAVIER, Érika Fialho Morais |
contributor_str_mv |
ANDRADE, Humber Agrelli de DUARTE NETO, Paulo José STOSIC, Tatijana SILVA, Antonio Samuel Alves da OLINDA, Ricardo Alves de |
dc.subject.por.fl_str_mv |
Análise bayesiana Modelo de produção Biomassa Espadarte Albacora bandolim |
topic |
Análise bayesiana Modelo de produção Biomassa Espadarte Albacora bandolim CIENCIAS EXATAS E DA TERRA::PROBABILIDADE E ESTATISTICA |
dc.subject.cnpq.fl_str_mv |
CIENCIAS EXATAS E DA TERRA::PROBABILIDADE E ESTATISTICA |
description |
Tuna and tuna-like species represent a great attraction for companies and fishers in general, due to their meat quality, their high commercial value and their extensive distribution in the oceans. Appropriate management is fundamental to the survival of some species, and to the sustainability of fi sheries. In this way, knowledge about abundance estimates and population biomass variations is paramount for sheries management. Dynamic models of biomass are essential techniques for calculating the estimates. This study proposed the use of Bayesian analysis for the models of Fox, Schaefer and Pella-Tomlinson. Initially, the objective was to evaluate the accuracy and precision of the information acquired about the parameters of the models. For this, catch and catch per unit effort data of the South Atlantic sword sh (Xiphias gladius) were used. It was concluded that there was no progress on precision and accuracy, taking as true "values" for the parameters the estimates of the last report of The International Commission for the Conservation of Atlantic Tunas (ICCAT). Sequentially, the objective was to evaluate the dynamic model of the biomass of Pella and Tomlinson, considering the variation and the fixation of the shape parameter in a scalar value. In this case, were used catch and catch per unit effort data of bigeye tuna (Thunnus obesus) of Atlantic. It was concluded that the model of Pella and Tomlinson with estimation of the shape parameter through of a prior distribution is more susceptible to in influences of non informative data and with discrepant points, and produces estimates more imprecise than when the form parameter is set as a scalar value, in the models of Schaefer and Fox. |
publishDate |
2018 |
dc.date.accessioned.fl_str_mv |
2018-05-09T13:31:41Z |
dc.date.issued.fl_str_mv |
2018-02-23 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/doctoralThesis |
format |
doctoralThesis |
status_str |
publishedVersion |
dc.identifier.citation.fl_str_mv |
XAVIER, Érika Fialho Morais. Abordagem bayesiana para modelos dinâmicos de biomassa. 2018. 86 f. Tese (Programa de Pós-Graduação em Biometria e Estatística Aplicada) - Universidade Federal Rural de Pernambuco, Recife. |
dc.identifier.uri.fl_str_mv |
http://www.tede2.ufrpe.br:8080/tede2/handle/tede2/7237 |
identifier_str_mv |
XAVIER, Érika Fialho Morais. Abordagem bayesiana para modelos dinâmicos de biomassa. 2018. 86 f. Tese (Programa de Pós-Graduação em Biometria e Estatística Aplicada) - Universidade Federal Rural de Pernambuco, Recife. |
url |
http://www.tede2.ufrpe.br:8080/tede2/handle/tede2/7237 |
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por |
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por |
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600 600 600 600 |
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info:eu-repo/semantics/openAccess |
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openAccess |
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application/pdf |
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Universidade Federal Rural de Pernambuco |
dc.publisher.program.fl_str_mv |
Programa de Pós-Graduação em Biometria e Estatística Aplicada |
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UFRPE |
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Universidade Federal Rural de Pernambuco |
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