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Windrow is a long-established term for the aggregations of seafoam, seaweeds, plankton and natural debris that appear on the ocean surface. Here, we define a “litter windrow” as any aggregation of floating litter at the submesoscale domain (<10 km horizontally), regardless of the force inducing the surface convergence, be it wind or other forces such as tides or density-driven currents. The marine litter windrows observed to date usually form stripes from tens up to thousands of meters long, with litter densities often exceeding 10 small items (<2 cm) per m2 or 1 large item (>2 cm) per 10 m2. Litter windrows are generally overlooked in research due to their dispersion, small size and ephemeral nature. However, applied research on windrows offers unique possibilities to advance on the knowledge and management of marine litter pollution. Litter windrows are hot spots of interaction with marine life. In addition, since the formation of dense litter windrows requires especially high loads of floating litter in the environment, their detection from space-borne sensors, aerial surveys or other platforms might be used to flag areas and periods of severe pollution. Monitoring and assessing of management plans, identification of pollution sources, or impact prevention are identified as some of the most promising fields of application for the marine litter windrows. In the present Perspective, we develop a conceptual framework and point out the main obstacles, opportunities and methodological approaches to address the study of litter windrows.

Search and rescue (SAR) modeling applications, mostly based on Lagrangian tracking particle algorithms, rely on the accuracy of met-ocean forecast models. Skill assessment methods are therefore required to evaluate the performance of ocean models in predicting particle trajectories. The Skill Score (SS), based on the Normalized Cumulative Lagrangian Separation (NCLS) distance between simulated and satellite-tracked drifter trajectories, is a commonly used metric. However, its applicability in coastal areas, where most of the SAR incidents occur, is difficult and sometimes unfeasible, because of the high variability that characterizes the coastal dynamics and the lack of drifter observations. In this study, we assess the performance of four models available in the Ibiza Channel (Western Mediterranean Sea) and evaluate the applicability of the SS in such coastal risk-prone regions seeking for a functional implementation in the context of SAR operations. We analyze the SS sensitivity to different forecast horizons and examine the best way to quantify the average model performance, to avoid biased conclusions. Our results show that the SS increases with forecast time in most cases. At short forecast times (i.e., 6 h), the SS exhibits a much higher variability due to the short trajectory lengths observed compared to the separation distance obtained at timescales not properly resolved by the models. However, longer forecast times lead to the overestimation of the SS due to the high variability of the surface currents. Findings also show that the averaged SS, as originally defined, can be misleading because of the imposition of a lower limit value of zero. To properly evaluate the averaged skill of the models, a revision of its definition, the so-called SS∗, is recommended. Furthermore, whereas drifters only provide assessment along their drifting paths, we show that trajectories derived from high-frequency radar (HFR) effectively provide information about the spatial distribution of the model performance inside the HFR coverage. HFR-derived trajectories could therefore be used for complementing drifter observations. The SS is, on average, more favorable to coarser-resolution models because of the double-penalty error, whereas higher-resolution models show both very low and very high performance during the experiments.

We analyzed strong events of coastal poleward along-shore currents above 10 cm s−1 and up to more than 50 cm s−1 on the inner shelf (50-80 m depth) of the Bay of Biscay (BoB) from the Spanish coast to the Brittany coast. We used data from four acoustic Doppler current profilers (ADCPs) deployed from July 2009 to August 2011. The goal of this study was to analyze current variability at meso-and subinertial scales and their generation mechanisms. These currents occurred all year long and were classified into three types. Events occurring principally in the southern part of the BoB were classified as southern events. Bay-scale events were defined when strong poleward currents were detected over all the shelf, typically stronger on the Spanish and the southern Brittany shelves. Strong events were characterized by depth averaged current velocities over 40 cm s−1 in the southern part of the BoB. At short time lags, the along-shore currents were clearly related to along-shore wind stress at upstream locations. An explanation is provided for longer time lags in terms of coastal trapped wave (CTW) dynamics. The first CTW mode phase speeds were in agreement with the propagation speeds of the fastest events (> 5 m s−1), while inner shelf modes could explain the slowest events (∼ 1-3 m s−1). The cross-shelf density gradient and the extension of the IPC were also associated with strong coastal poleward along-shore currents. The duration of the events, the vertical structure of the currents and the associated coastal trapped waves were studied in relation with the stratification.

Large scale convergence regions of floating marine litter are commonly observed in semi-enclosed seas as the Bay of Biscay. However, clean-up activities on such accumulation regions are limited by the spread of the large-size floating litter on the sea surface. Data gathered by a small-scale fishing vessel devoted to active fishing for floating litter activities during the spring and summer of 2018 reveals that the linear streaks of high concentration of floating litter (so-called litter "windrows") are common accumulation structures in the south-east coast of the Bay of Biscay. The random search of litter windrows for their collection through surface tows of macro-nets was proved to be an effective action for floating litter mitigation. A total of 196 tows collected 16.2 tons of floating marine litter in 68 working days. Most of the litter windrows were around 1 km length and, on average, accumulated 77.75 kg of floating marine litter. Fishing, shipping and aquaculture sectors were the source of 35% of the 4,130 litter items analyzed (55% in weight of the sourced items), and plastic was the most common type of material (96% in terms of items). A better understanding of the phenomenon of the litter windrows, capable to guide clean-up efforts in space and time, would provide a considerable improvement in the efficiency of mitigation actions to reduce the marine litter pollution. The observations of litter windrows in the coastal area of the south-east of the Bay of Biscay demonstrate the key role of submesoscale processes in the distribution of FML. The present work provides a thorough description of floating litter windrows in nature, which it was non-existent to date. The results are the kind of proof necessary to boost the research addressed on the submesoscale aggregations of FML. Coupling litter windrows observations with remote-sensing technology and high-resolution modeling techniques offer great opportunities for the mitigation actions against marine litter.

Identifying the role that environmental factors and biotic interactions play in species distribution can be essential to better understand and predict how ecosystems will respond to changing environmental conditions. This study aimed at disentangling the assemblage of the pelagic predator–prey community by identifying interspecific associations and their main drivers. For this purpose, we applied the joint species distribution modelling approach, JSDM, to the co-occurrence patterns of both prey and top predator communities obtained from JUVENA surveys during 2013–2016 in the Bay of Biscay. Results showed that the co-occurrence patterns of top predators and prey were driven by a combination of environmental and biotic factors, which highlighted the importance of considering both components to fully understand the community structure. In addition, results also revealed that many biotic interactions, such as schooling in prey (e.g. anchovy–sardine), local enhancement/facilitation in predators (e.g. Cory’s shearwater–fin whale), and predation between predator–prey species (e.g. northern gannet–horse mackerel), were led by positive associations, although predator avoidance behaviour was also suggested between negatively associated species (e.g. striped dolphin–blue whiting). The identification of interspecific associations can therefore provide insights on the functioning of predators–prey network and help advance towards an ecosystem-based management.