Maritime traffic and fishing activities have accelerated considerably over the last decade, with a consequent impact on the environment and marine resources. Meanwhile, a growing number of ship-reporting technologies and remote-sensing systems are generating an overwhelming amount of spatio-temporal and geographically distributed data related to large-scale vessels and their movements. Individual technologies have distinct limitations but, when combined, can provide a better view of what is happening at sea, lead to effectively monitor fishing activities, and help tackle the investigations of suspicious behaviors in close proximity of managed areas. The paper integrates non-cooperative Synthetic Aperture Radar (SAR) Sentinel-1 images and cooperative Automatic Identification System (AIS) data, by proposing two types of associations: (i) point-to-point and (ii) point-to-line. They allow the fusion of ship positions and highlight “suspicious” AIS data gaps in close proximity of managed areas that can be further investigated only once the vessel—and the gear it adopts—is known. This is addressed by a machine-learning approach based on the Fast Fourier Transform that classifies single sea trips. The approach is tested on a case study in the central Adriatic Sea, automatically reporting AIS-SAR associations and seeking ships that are not broadcasting their positions (intentionally or not). Results allow the discrimination of collaborative and non-collaborative ships, playing a key role in detecting potential suspect behaviors especially in close proximity of managed areas.

In the past decades, the Automatic Identification System (AIS) has been employed in numerous research fields as a valuable tool for, among other things, Maritime Domain Awareness and Maritime Spatial Planning. In contrast, its use in fisheries management is hampered by coverage and transmission gaps. Transmission gaps may be due to technical limitations (e.g., weak signal or interference with other signals) or to deliberate switching off of the system, to conceal fishing activities. In either case such gaps may result in underestimating fishing effort and pressure. This study was undertaken to map and analyze bottom trawler transmission gaps in terms of duration and distance from the harbor with a view to quantifying unobserved fishing and its effects on overall trawling pressure. Here we present the first map of bottom trawler AIS transmission gaps in the Mediterranean Sea and a revised estimate of fishing effort if some gaps are considered as actual fishing.

Temperature is often an important variable influencing the vertical position of fish larvae in the water column. The same species may show different vertical distributions in areas with a strong near-surface seasonal thermocline compared to isothermal near-surface regions. In areas with a strong surface thermocline, tuna larvae show a significant preference for the near-surface warmer layers. Little is known regarding larval tuna vertical distribution in isothermal waters and on the vertical distribution of the associated larval fish assemblages. We conducted vertical stratified sampling using the same methodology and fishing device (MOCNESS) in the two major spawning areas of Atlantic bluefin tuna (BFT): western Mediterranean Sea (MED), characterized by a surface thermocline, and the Gulf of Mexico (GOM) which lacks thermal stratification. Tuna larvae occupied the upper 30 m in both areas, but the average larval depth distribution was consistently deeper in the GOM. In the MED, vertical distribution of larval fish assemblages was explained by temperature, and species such as BFT, Thunnus alalunga, and Ceratoscopelus maderensis, among others, coexist above the thermocline and are separated from species such as Cyclothone braueri and Hygophum spp. (found below the thermocline). In the GOM, the environmental correlates of the vertical distribution of the larvae were salinity and fluorescence. Mesopelagic taxa such as Ceratoscopelus spp. and Cyclothone spp., among others, had a shallower average distribution than Lampanyctus spp., Hygophum spp., and Myctophum spp.