Latent Gaussian models to decide on spatial closures for bycatch management in the Barents Sea shrimp fishery
In the Barents Sea and adjacent water, fishing grounds are closed for shrimp fishing by the Norwegian Directorate of Fisheries Monitoring and Surveillance Service (MSS) if the expected number of juvenile fish caught are predicted to exceed a certain limit per kilogram shrimp (Pandalus borealis). Tod...
Main Authors: | , , |
---|---|
Format: | Article in Journal/Newspaper |
Language: | unknown |
Published: |
NRC Research Press (a division of Canadian Science Publishing)
2015
|
Subjects: | |
Online Access: | http://hdl.handle.net/1807/72403 http://www.nrcresearchpress.com/doi/abs/10.1139/cjfas-2015-0322 |
id |
ftunivtoronto:oai:localhost:1807/72403 |
---|---|
record_format |
openpolar |
spelling |
ftunivtoronto:oai:localhost:1807/72403 2023-05-15T15:27:42+02:00 Latent Gaussian models to decide on spatial closures for bycatch management in the Barents Sea shrimp fishery Breivik, Olav Nikolai Storvik, Geir Nedreaas, Kjell 2015-12-22 http://hdl.handle.net/1807/72403 http://www.nrcresearchpress.com/doi/abs/10.1139/cjfas-2015-0322 unknown NRC Research Press (a division of Canadian Science Publishing) 0706-652X http://hdl.handle.net/1807/72403 http://www.nrcresearchpress.com/doi/abs/10.1139/cjfas-2015-0322 Article 2015 ftunivtoronto 2020-06-17T11:59:16Z In the Barents Sea and adjacent water, fishing grounds are closed for shrimp fishing by the Norwegian Directorate of Fisheries Monitoring and Surveillance Service (MSS) if the expected number of juvenile fish caught are predicted to exceed a certain limit per kilogram shrimp (Pandalus borealis). Today, a simple ratio estimator, which do not fully utilize all data available, is in use. In this research we construct a Bayesian hierarchical spatio-temporal model for improved prediction of the bycatch ratio in the Barents Sea shrimp fishery. More predictable bycatch will be an advantage for the MSS due to more correct decisions and better resource allocation, and for the fishermen due to more predictable fishing grounds. The model assumes that the occurrence of shrimp and juvenile cod can be modeled by linked regression models containing several covariates (including 0-group abundance estimates) and random effects modeled as Gaussian fields. Integrated Nested Laplace Approximations (INLA) is applied for fast calculation. The method is applied to prediction of the bycatch ratio for Atlantic cod (Gadus morhua). The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author. Article in Journal/Newspaper atlantic cod Barents Sea Gadus morhua Pandalus borealis University of Toronto: Research Repository T-Space Barents Sea Laplace ENVELOPE(141.467,141.467,-66.782,-66.782) |
institution |
Open Polar |
collection |
University of Toronto: Research Repository T-Space |
op_collection_id |
ftunivtoronto |
language |
unknown |
description |
In the Barents Sea and adjacent water, fishing grounds are closed for shrimp fishing by the Norwegian Directorate of Fisheries Monitoring and Surveillance Service (MSS) if the expected number of juvenile fish caught are predicted to exceed a certain limit per kilogram shrimp (Pandalus borealis). Today, a simple ratio estimator, which do not fully utilize all data available, is in use. In this research we construct a Bayesian hierarchical spatio-temporal model for improved prediction of the bycatch ratio in the Barents Sea shrimp fishery. More predictable bycatch will be an advantage for the MSS due to more correct decisions and better resource allocation, and for the fishermen due to more predictable fishing grounds. The model assumes that the occurrence of shrimp and juvenile cod can be modeled by linked regression models containing several covariates (including 0-group abundance estimates) and random effects modeled as Gaussian fields. Integrated Nested Laplace Approximations (INLA) is applied for fast calculation. The method is applied to prediction of the bycatch ratio for Atlantic cod (Gadus morhua). The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author. |
format |
Article in Journal/Newspaper |
author |
Breivik, Olav Nikolai Storvik, Geir Nedreaas, Kjell |
spellingShingle |
Breivik, Olav Nikolai Storvik, Geir Nedreaas, Kjell Latent Gaussian models to decide on spatial closures for bycatch management in the Barents Sea shrimp fishery |
author_facet |
Breivik, Olav Nikolai Storvik, Geir Nedreaas, Kjell |
author_sort |
Breivik, Olav Nikolai |
title |
Latent Gaussian models to decide on spatial closures for bycatch management in the Barents Sea shrimp fishery |
title_short |
Latent Gaussian models to decide on spatial closures for bycatch management in the Barents Sea shrimp fishery |
title_full |
Latent Gaussian models to decide on spatial closures for bycatch management in the Barents Sea shrimp fishery |
title_fullStr |
Latent Gaussian models to decide on spatial closures for bycatch management in the Barents Sea shrimp fishery |
title_full_unstemmed |
Latent Gaussian models to decide on spatial closures for bycatch management in the Barents Sea shrimp fishery |
title_sort |
latent gaussian models to decide on spatial closures for bycatch management in the barents sea shrimp fishery |
publisher |
NRC Research Press (a division of Canadian Science Publishing) |
publishDate |
2015 |
url |
http://hdl.handle.net/1807/72403 http://www.nrcresearchpress.com/doi/abs/10.1139/cjfas-2015-0322 |
long_lat |
ENVELOPE(141.467,141.467,-66.782,-66.782) |
geographic |
Barents Sea Laplace |
geographic_facet |
Barents Sea Laplace |
genre |
atlantic cod Barents Sea Gadus morhua Pandalus borealis |
genre_facet |
atlantic cod Barents Sea Gadus morhua Pandalus borealis |
op_relation |
0706-652X http://hdl.handle.net/1807/72403 http://www.nrcresearchpress.com/doi/abs/10.1139/cjfas-2015-0322 |
_version_ |
1766358112659308544 |