Seabed plastic pollution seriously threatens marine biodiversity and ecosystem functioning by damaging marine organisms and disrupting ecosystems. Litter accumulation zones may overlap with fishing grounds for commercially important species, reducing productivity and yield. As studies have yet to be conducted on this topic, there is an urgent need to fill the knowledge gap on the impact of plastic pollution on fisheries and stock management. For these reasons, this study aimed to analyse the effect of seafloor plastic on fishing economic performance (as revenues) and commercially important species by mapping trawl areas and identifying litter hotspots on the seafloor. A model based on landing and Vessel Monitoring System data was employed to estimate the fishing grounds of the species, and a random forest machine-learning technique was used to identify seafloor litter hotspots. The findings demonstrate that seafloor plastic hotspots overlap with the fishing grounds, thus hurting economic productivity. The implications of this problem pose a significant threat to exposure and impact on certain species. Our findings indicate that seabed plastic pollution should be recognised as affecting fisheries administration and conservation approaches.
Sbrana, A., Galli, S., Russo, T. (2025). The effect of marine litter on fishery economic performance. FISHERIES RESEARCH, 285 [10.1016/j.fishres.2025.107346].
The effect of marine litter on fishery economic performance
Sbrana A.
;Galli S.;Russo T.
2025-01-01
Abstract
Seabed plastic pollution seriously threatens marine biodiversity and ecosystem functioning by damaging marine organisms and disrupting ecosystems. Litter accumulation zones may overlap with fishing grounds for commercially important species, reducing productivity and yield. As studies have yet to be conducted on this topic, there is an urgent need to fill the knowledge gap on the impact of plastic pollution on fisheries and stock management. For these reasons, this study aimed to analyse the effect of seafloor plastic on fishing economic performance (as revenues) and commercially important species by mapping trawl areas and identifying litter hotspots on the seafloor. A model based on landing and Vessel Monitoring System data was employed to estimate the fishing grounds of the species, and a random forest machine-learning technique was used to identify seafloor litter hotspots. The findings demonstrate that seafloor plastic hotspots overlap with the fishing grounds, thus hurting economic productivity. The implications of this problem pose a significant threat to exposure and impact on certain species. Our findings indicate that seabed plastic pollution should be recognised as affecting fisheries administration and conservation approaches.| File | Dimensione | Formato | |
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