RESUMEN
Numerical models point to the south-east Bay of Biscay as a convergence area for floating particles, including plastics. The few existing studies on plastic abundance in the area mainly focus on open waters and yet information on the coastal area is limited. To fill this gap, neustonic samples were taken along the coastal waters of the south-east Bay of Biscay (2017-2020) to define the spatial distribution of plastic abundances and composition. Results show an average plastic abundance of 739,395 ± 2,625,271 items/km2 (998 ± 4338 g/km2). French waters were more affected, with five times higher plastic abundances than Spanish coasts. Microplastics represented 93 % of the total abundance of plastic items (28 % in weight), mesoplastics 7 % (26 %) and macroplastics 1 % (46 %). This study demonstrates that this area is a hotspot for plastic with levels in coastal waters similar to those in the Mediterranean Sea or other litter aggregation areas.
Asunto(s)
Plásticos , Contaminantes Químicos del Agua , Bahías , Monitoreo del Ambiente/métodos , Microplásticos , Contaminantes Químicos del Agua/análisisRESUMEN
In the Bay of Biscay, regional monitoring programmes and data on abundance and distribution of floating marine litter are scarce, contrary to many other European marine regions. Here, a joint analysis of multiyear observations (2017-2019) of floating micro and macrolitter and oceanographic conditions was conducted for the Bay of Biscay by combining microlitter samplings with neuston nets and vessel-based macrolitter observations. Results show spatiotemporal abundance and distribution patterns. The density of floating microlitter increased from 26,056 items/km2 in 2017 to 1,802,4611 items/km2 in 2019; floating macrolitter densities barely varied amongst year (2.52 items/km2 in 2017 and 3.70 items/km2 in 2019). No significant correlation was found between densities of micro and macrolitter, neither for the oceanographic variables. We conclude that longer micro and macrolitter monitoring periods and standardized datasets based on the cross-border cooperation are needed to collect more comparable information, evaluate trends, and support decision making in the area.