Modelling drivers of trawl fisheries discards using Bayesian spatio-temporal models

Effective spatial fisheries management requires a proper understanding of the spatial distribution of both target species and discards. Also, spatial modelling of fishery-dependent data is an effective tool to capture uncertainties in data-limited situations. This study analyses the drivers behind d...

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Detalles Bibliográficos
Autores: Soto-Ruiz, María, Fernández-Peralta, Lourdes, Rey-Sanz, Javier, Czerwinski, Ivone A., García-Cancela, Ramón, Llope, Marcos, Liébana, María, Pennino, Maria Grazia
Tipo de recurso: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2023
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/344330
Acceso en línea:http://hdl.handle.net/10261/344330
https://api.elsevier.com/content/abstract/scopus_id/85169038459
Access Level:acceso abierto
Palabra clave:Bayesian hierarchical modelling
Discards
Ecosystem-based fisheries management
Spatial management tool
INLA
Mauritania
Random forest
Descripción
Sumario:Effective spatial fisheries management requires a proper understanding of the spatial distribution of both target species and discards. Also, spatial modelling of fishery-dependent data is an effective tool to capture uncertainties in data-limited situations. This study analyses the drivers behind discarding by comparing the standardising properties of three different components: Total Discards, Discards Per Unit of Effort and Total Discard Ratio. These metrics were analysed by means of Bayesian hierarchical spatio-temporal Gamma regression models to correctly to identify areas with high discards values that are characterized as discards hotspots. Our results showed that Total Discards is the component which better quantified the aggregated ecological impact of discarding practices, whereas Total Discard Ratio and Discards Per Unit of Effort identify complementary issues of benefits versus loss of biomass. Spatial maps obtained by combining these three approaches are a powerful tool for the spatial management of discards.