Bayesian spatio-temporal discard model in a demersal trawl fishery

Grazia Pennino Maria, Munoz Facundo, Conesa David, López-Quıílez Antonio, Bellido José María. 2014. Bayesian spatio-temporal discard model in a demersal trawl fishery. Journal of Sea Research, 90 : pp. 44-53.

Journal article ; Article de recherche ; Article de revue à facteur d'impact
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Quartile : Q2, Sujet : MARINE & FRESHWATER BIOLOGY / Quartile : Q2, Sujet : OCEANOGRAPHY

Abstract : Spatial management of discards has recently been proposed as a useful tool for the protection of juveniles, by reducing discard rates and can be used as a buffer against management errors and recruitment failure. In this study Bayesian hierarchical spatial models have been used to analyze about 440 trawl fishing operations of two different metiers, sampled between 2009 and 2012, in order to improve our understanding of factors that influence the quantity of discards and to identify their spatio-temporal distribution in the study area. Our analysis showed that the relative importance of each variable was different for each metier, with a few similarities. In particular, the random vessel effect and seasonal variability were identified as main driving variables for both metiers. Predictive maps of the abundance of discards and maps of the posterior mean of the spatial component show several hot spots with high discard concentration for each metier. We argue how the seasonal/spatial effects, and the knowledge about the factors influential to discarding, could potentially be exploited as potential mitigation measures for future fisheries management strategies. However, misidentification of hotspots and uncertain predictions can culminate in inappropriate mitigation practices which can sometimes be irreversible. The proposed Bayesian spatial method overcomes these issues, since it offers a unified approach which allows the incorporation of spatial random-effect terms, spatial correlation of the variables and the uncertainty of the parameters in the modeling process, resulting in a better quantification of the uncertainty and accurate predictions.

Mots-clés Agrovoc : Chalutage, Pêche démersale, Théorie bayésienne, Ressource marine, Ressource halieutique, Perte

Mots-clés complémentaires : Modélisation Bayésienne, Analyse spatiale

Mots-clés libres : Bayesian analysis, Spatial analysis, Ecology, Marine resources

Classification Agris : M11 - Fisheries production
M40 - Aquatic ecology
U10 - Computer science, mathematics and statistics

Champ stratégique Cirad : Hors axes (2014-2018)

Auteurs et affiliations

  • Grazia Pennino Maria, Instituto Español de Oceanografía (ESP) - auteur correspondant
  • Munoz Facundo, Universidad de Valencia (ESP) ORCID: 0000-0002-5061-4241
  • Conesa David, Universitat de Valencia (ESP)
  • López-Quıílez Antonio, Universitat de Valencia (ESP)
  • Bellido José María, Instituto Español de Oceanografía (ESP)

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