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

被引：4
作者：
Soto, M. [1 ]
Fernandez-Peralta, L. [1 ]
Rey, J. [1 ]
Czerwisnki, I. [2 ]
Garcia-Cancela, R. [1 ]
Llope, M. [2 ]
Cabrera-Busto, J. [2 ]
Liebana, M. [1 ]
Pennino, M. G. [3 ]
机构：
[1] Ctr Oceanog Malaga, Inst Espanol Oceanog IEO CSIC, Puerto Pesquero S-N, Malaga 29640, Spain
[2] Ctr Oceanog Cadiz, Inst Espanol Oceanog IEO CSIC, Muelle Levante S-N, Cadiz 11006, Spain
[3] Ctr Oceanog Madrid, Inst Espanol Oceanog IEO CSIC, C Corazon Maria 8, Madrid 28002, Spain
来源：
FISHERIES RESEARCH | 2023年 / 268卷
关键词：
Bayesian hierarchical modelling; INLA; Spatial management tool; Ecosystem-based fisheries management; Random forest; Discards; Mauritania; MANAGEMENT; VARIABILITY; REGRESSION; RATES;
D O I：
10.1016/j.fishres.2023.106830
中图分类号：
S9 [水产、渔业];
学科分类号：
0908 ;
摘要：
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 spatiotemporal 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.
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页数：11
相关论文
共 67 条
[1]   Sub-regional ecosystem variability in the Canary Current upwelling [J].
Aristegui, Javier ;
Barton, Eric D. ;
Alvarez-Salgado, Xose A. ;
Santos, A. Miguel P. ;
Figueiras, Francisco G. ;
Kifani, Souad ;
Hernandez-Leon, Santiago ;
Mason, Evan ;
Machu, Eric ;
Demarcq, Herve .
PROGRESS IN OCEANOGRAPHY, 2009, 83 (1-4) :33-48
[2]   Understanding discarding in trawl fisheries: A model based demersal case study with implications for mitigating and assessing impacts [J].
Barnes, Thomas C. ;
Candy, Steven G. ;
Morris, Stephen ;
Johnson, Daniel D. .
PLOS ONE, 2022, 17 (02)
[3]  
Bellido J. M., 2007, Boletin Instituto Espanol de Oceanografia, V23, P73
[4]  
Bellido JM, 2019, EUROPEAN LANDING OBLIGATION: REDUCING DISCARDS IN COMPLEX, MULTI-SPECIES AND MULTI-JURISDICTIONAL FISHERIES, P239, DOI 10.1007/978-3-030-03308-8_12
[5]   Fishery discards and bycatch: solutions for an ecosystem approach to fisheries management? [J].
Bellido, Jose M. ;
Begona Santos, M. ;
Grazia Pennino, M. ;
Valeiras, Xulio ;
Pierce, Graham J. .
HYDROBIOLOGIA, 2011, 670 (01) :317-333
[6]   Discards of cod (Gadus morhua) in the Norwegian coastal fisheries: improving past and future estimates [J].
Berg, Hilde Sofie Fantoft ;
Clegg, Thomas Laurence ;
Blom, Geir ;
Kolding, Jeppe ;
Ono, Kotaro ;
Nedreaas, Kjell .
ICES JOURNAL OF MARINE SCIENCE, 2022, 79 (05) :1548-1560
[7]   Random forests [J].
Breiman, L .
MACHINE LEARNING, 2001, 45 (01) :5-32
[8]   Modelling trawling discards of the Alboran fisheries in the Mediterranean Sea [J].
Carbonell, Aina ;
Garcia, Teresa ;
Gonzalez, Maria ;
Alvarez-Berastegui, Diego ;
Mallol, Sandra ;
Miguel de la Serna, Jose ;
Bulto, Cristina ;
Maria Bellido, Jose ;
Barcala, Elena ;
Baro, Jorge .
REGIONAL STUDIES IN MARINE SCIENCE, 2018, 23 :73-86
[9]   Inclusion of discards in stock assessment models [J].
Cook, Robin M. .
FISH AND FISHERIES, 2019, 20 (06) :1232-1245
[10]   Spatial and temporal seasonal trends in coastal upwelling off Northwest Africa, 1981-2012 [J].
Cropper, Thomas E. ;
Hanna, Edward ;
Bigg, Grant R. .
DEEP-SEA RESEARCH PART I-OCEANOGRAPHIC RESEARCH PAPERS, 2014, 86 :94-111
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