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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Veröffentlicht in:Fisheries research 2023-12, Vol.268, p.106830, Article 106830
Hauptverfasser: Soto, M., Fernández-Peralta, L., Rey, J., Czerwisnki, I., García-Cancela, R., Llope, M., Cabrera-Busto, J., Liébana, M., Pennino, M.G.
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Sprache:eng
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Zusammenfassung: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.
ISSN:0165-7836
1872-6763
DOI:10.1016/j.fishres.2023.106830