Investigating agreement between different data sources using Bayesian state-space model: an application to estimating NE Atlantic mackerel catch and stock abundance
Bayesian Markov chain Monte Carlo methods are ideally suited to analyses of situations where there are a variety of data sources, particularly where the uncertainties differ markedly among the data and the estimated parameters can be correlated. The example of Northeast Atlantic (NEA) mackerel is us...
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ftunivwagenin:oai:library.wur.nl:wurpubs/395198 2024-01-21T10:08:55+01:00 Investigating agreement between different data sources using Bayesian state-space model: an application to estimating NE Atlantic mackerel catch and stock abundance Simmonds, E.J. Portilla, E. Skagen, D. Beare, D.J. Reid, D.G. 2010 application/pdf https://research.wur.nl/en/publications/investigating-agreement-between-different-data-sources-using-baye https://doi.org/10.1093/icesjms/fsq013 en eng https://edepot.wur.nl/146773 https://research.wur.nl/en/publications/investigating-agreement-between-different-data-sources-using-baye doi:10.1093/icesjms/fsq013 info:eu-repo/semantics/restrictedAccess Wageningen University & Research ICES Journal of Marine Science 67 (2010) 6 ISSN: 1054-3139 age data egg mortality indexes management parameters info:eu-repo/semantics/article Article/Letter to editor info:eu-repo/semantics/publishedVersion 2010 ftunivwagenin https://doi.org/10.1093/icesjms/fsq013 2023-12-27T23:15:19Z Bayesian Markov chain Monte Carlo methods are ideally suited to analyses of situations where there are a variety of data sources, particularly where the uncertainties differ markedly among the data and the estimated parameters can be correlated. The example of Northeast Atlantic (NEA) mackerel is used to evaluate the agreement between available data from egg surveys, tagging, and catch-at-age using multiple models within the Bayesian framework WINBUGS. The errors in each source of information are dealt with independently, and there is extensive exploration of potential sources of uncertainty in both the data and the model. Model options include variation by age and over time of both selectivity in the fishery and natural mortality, varying the precision and calculation method for spawning-stock biomass derived from an egg survey, and the extent of missing catches varying over time. The models are compared through deviance information criterion and Bayesian posterior predictive p-values. To reconcile mortality estimated from the different datasets the landings and discards reported would have to have been between 1.7 and 3.6 times higher than the recorded catches. Article in Journal/Newspaper Northeast Atlantic Wageningen UR (University & Research Centre): Digital Library ICES Journal of Marine Science 67 6 1138 1153 |
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Open Polar |
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Wageningen UR (University & Research Centre): Digital Library |
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ftunivwagenin |
language |
English |
topic |
age data egg mortality indexes management parameters |
spellingShingle |
age data egg mortality indexes management parameters Simmonds, E.J. Portilla, E. Skagen, D. Beare, D.J. Reid, D.G. Investigating agreement between different data sources using Bayesian state-space model: an application to estimating NE Atlantic mackerel catch and stock abundance |
topic_facet |
age data egg mortality indexes management parameters |
description |
Bayesian Markov chain Monte Carlo methods are ideally suited to analyses of situations where there are a variety of data sources, particularly where the uncertainties differ markedly among the data and the estimated parameters can be correlated. The example of Northeast Atlantic (NEA) mackerel is used to evaluate the agreement between available data from egg surveys, tagging, and catch-at-age using multiple models within the Bayesian framework WINBUGS. The errors in each source of information are dealt with independently, and there is extensive exploration of potential sources of uncertainty in both the data and the model. Model options include variation by age and over time of both selectivity in the fishery and natural mortality, varying the precision and calculation method for spawning-stock biomass derived from an egg survey, and the extent of missing catches varying over time. The models are compared through deviance information criterion and Bayesian posterior predictive p-values. To reconcile mortality estimated from the different datasets the landings and discards reported would have to have been between 1.7 and 3.6 times higher than the recorded catches. |
format |
Article in Journal/Newspaper |
author |
Simmonds, E.J. Portilla, E. Skagen, D. Beare, D.J. Reid, D.G. |
author_facet |
Simmonds, E.J. Portilla, E. Skagen, D. Beare, D.J. Reid, D.G. |
author_sort |
Simmonds, E.J. |
title |
Investigating agreement between different data sources using Bayesian state-space model: an application to estimating NE Atlantic mackerel catch and stock abundance |
title_short |
Investigating agreement between different data sources using Bayesian state-space model: an application to estimating NE Atlantic mackerel catch and stock abundance |
title_full |
Investigating agreement between different data sources using Bayesian state-space model: an application to estimating NE Atlantic mackerel catch and stock abundance |
title_fullStr |
Investigating agreement between different data sources using Bayesian state-space model: an application to estimating NE Atlantic mackerel catch and stock abundance |
title_full_unstemmed |
Investigating agreement between different data sources using Bayesian state-space model: an application to estimating NE Atlantic mackerel catch and stock abundance |
title_sort |
investigating agreement between different data sources using bayesian state-space model: an application to estimating ne atlantic mackerel catch and stock abundance |
publishDate |
2010 |
url |
https://research.wur.nl/en/publications/investigating-agreement-between-different-data-sources-using-baye https://doi.org/10.1093/icesjms/fsq013 |
genre |
Northeast Atlantic |
genre_facet |
Northeast Atlantic |
op_source |
ICES Journal of Marine Science 67 (2010) 6 ISSN: 1054-3139 |
op_relation |
https://edepot.wur.nl/146773 https://research.wur.nl/en/publications/investigating-agreement-between-different-data-sources-using-baye doi:10.1093/icesjms/fsq013 |
op_rights |
info:eu-repo/semantics/restrictedAccess Wageningen University & Research |
op_doi |
https://doi.org/10.1093/icesjms/fsq013 |
container_title |
ICES Journal of Marine Science |
container_volume |
67 |
container_issue |
6 |
container_start_page |
1138 |
op_container_end_page |
1153 |
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1788699791461449728 |