Selectivity curves of the capture of mangrove crab (Ucides cordatus) on the northern coast of Brazil using bayesian inference
Autor(a) principal: | |
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Data de Publicação: | 2016 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Brazilian Journal of Biology |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1519-69842016000200412 |
Resumo: | Abstract Fishing selectivity of the mangrove crab Ucides cordatus in the north coast of Brazil can be defined as the fisherman's ability to capture and select individuals from a certain size or sex (or a combination of these factors) which suggests an empirical selectivity. Considering this hypothesis, we calculated the selectivity curves for males and females crabs using the logit function of the logistic model in the formulation. The Bayesian inference consisted of obtaining the posterior distribution by applying the Markov chain Monte Carlo (MCMC) method to software R using the OpenBUGS, BRugs, and R2WinBUGS libraries. The estimated results of width average carapace selection for males and females compared with previous studies reporting the average width of the carapace of sexual maturity allow us to confirm the hypothesis that most mature individuals do not suffer from fishing pressure; thus, ensuring their sustainability. |
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Brazilian Journal of Biology |
repository_id_str |
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spelling |
Selectivity curves of the capture of mangrove crab (Ucides cordatus) on the northern coast of Brazil using bayesian inferencefisheries exploitationcapture probabilitysustainabilitybayesian inferencecoastal ecosystemAbstract Fishing selectivity of the mangrove crab Ucides cordatus in the north coast of Brazil can be defined as the fisherman's ability to capture and select individuals from a certain size or sex (or a combination of these factors) which suggests an empirical selectivity. Considering this hypothesis, we calculated the selectivity curves for males and females crabs using the logit function of the logistic model in the formulation. The Bayesian inference consisted of obtaining the posterior distribution by applying the Markov chain Monte Carlo (MCMC) method to software R using the OpenBUGS, BRugs, and R2WinBUGS libraries. The estimated results of width average carapace selection for males and females compared with previous studies reporting the average width of the carapace of sexual maturity allow us to confirm the hypothesis that most mature individuals do not suffer from fishing pressure; thus, ensuring their sustainability.Instituto Internacional de Ecologia2016-06-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1519-69842016000200412Brazilian Journal of Biology v.76 n.2 2016reponame:Brazilian Journal of Biologyinstname:Instituto Internacional de Ecologia (IIE)instacron:IIE10.1590/1519-6984.17714info:eu-repo/semantics/openAccessFurtado-Junior,I.Abrunhosa,F. A.Holanda,F. C. A. F.Tavares,M. C. S.eng2016-06-16T00:00:00Zoai:scielo:S1519-69842016000200412Revistahttps://www.scielo.br/j/bjb/https://old.scielo.br/oai/scielo-oai.phpbjb@bjb.com.br||bjb@bjb.com.br1678-43751519-6984opendoar:2016-06-16T00:00Brazilian Journal of Biology - Instituto Internacional de Ecologia (IIE)false |
dc.title.none.fl_str_mv |
Selectivity curves of the capture of mangrove crab (Ucides cordatus) on the northern coast of Brazil using bayesian inference |
title |
Selectivity curves of the capture of mangrove crab (Ucides cordatus) on the northern coast of Brazil using bayesian inference |
spellingShingle |
Selectivity curves of the capture of mangrove crab (Ucides cordatus) on the northern coast of Brazil using bayesian inference Furtado-Junior,I. fisheries exploitation capture probability sustainability bayesian inference coastal ecosystem |
title_short |
Selectivity curves of the capture of mangrove crab (Ucides cordatus) on the northern coast of Brazil using bayesian inference |
title_full |
Selectivity curves of the capture of mangrove crab (Ucides cordatus) on the northern coast of Brazil using bayesian inference |
title_fullStr |
Selectivity curves of the capture of mangrove crab (Ucides cordatus) on the northern coast of Brazil using bayesian inference |
title_full_unstemmed |
Selectivity curves of the capture of mangrove crab (Ucides cordatus) on the northern coast of Brazil using bayesian inference |
title_sort |
Selectivity curves of the capture of mangrove crab (Ucides cordatus) on the northern coast of Brazil using bayesian inference |
author |
Furtado-Junior,I. |
author_facet |
Furtado-Junior,I. Abrunhosa,F. A. Holanda,F. C. A. F. Tavares,M. C. S. |
author_role |
author |
author2 |
Abrunhosa,F. A. Holanda,F. C. A. F. Tavares,M. C. S. |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Furtado-Junior,I. Abrunhosa,F. A. Holanda,F. C. A. F. Tavares,M. C. S. |
dc.subject.por.fl_str_mv |
fisheries exploitation capture probability sustainability bayesian inference coastal ecosystem |
topic |
fisheries exploitation capture probability sustainability bayesian inference coastal ecosystem |
description |
Abstract Fishing selectivity of the mangrove crab Ucides cordatus in the north coast of Brazil can be defined as the fisherman's ability to capture and select individuals from a certain size or sex (or a combination of these factors) which suggests an empirical selectivity. Considering this hypothesis, we calculated the selectivity curves for males and females crabs using the logit function of the logistic model in the formulation. The Bayesian inference consisted of obtaining the posterior distribution by applying the Markov chain Monte Carlo (MCMC) method to software R using the OpenBUGS, BRugs, and R2WinBUGS libraries. The estimated results of width average carapace selection for males and females compared with previous studies reporting the average width of the carapace of sexual maturity allow us to confirm the hypothesis that most mature individuals do not suffer from fishing pressure; thus, ensuring their sustainability. |
publishDate |
2016 |
dc.date.none.fl_str_mv |
2016-06-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1519-69842016000200412 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1519-69842016000200412 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/1519-6984.17714 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Instituto Internacional de Ecologia |
publisher.none.fl_str_mv |
Instituto Internacional de Ecologia |
dc.source.none.fl_str_mv |
Brazilian Journal of Biology v.76 n.2 2016 reponame:Brazilian Journal of Biology instname:Instituto Internacional de Ecologia (IIE) instacron:IIE |
instname_str |
Instituto Internacional de Ecologia (IIE) |
instacron_str |
IIE |
institution |
IIE |
reponame_str |
Brazilian Journal of Biology |
collection |
Brazilian Journal of Biology |
repository.name.fl_str_mv |
Brazilian Journal of Biology - Instituto Internacional de Ecologia (IIE) |
repository.mail.fl_str_mv |
bjb@bjb.com.br||bjb@bjb.com.br |
_version_ |
1752129882904592384 |