Latent Gaussian models to decide on spatial closures for bycatch management in the Barents Sea shrimp fishery

• Main Authors: Breivik, Olav Nikolai, Storvik, Geir, Nedreaas, Kjell
• Format: Article in Journal/Newspaper
• Language: unknown
• Published: NRC Research Press (a division of Canadian Science Publishing) 2015
• Subjects: Barents Sea; Laplace; atlantic cod; Gadus morhua; Pandalus borealis
• Online Access: http://hdl.handle.net/1807/72403; http://www.nrcresearchpress.com/doi/abs/10.1139/cjfas-2015-0322

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.