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.
During the last decade vessel-position-recording devices, such as the Vessel Monitoring System and the Automatic Identification System, have increasingly given accurate spatial and quantitative ...information of industrial fisheries. On the other hand, small-scale fisheries (vessels below 12 m) remain untracked and largely unregulated even though they play an important socio-economic and cultural role in European waters and coastal communities and account for most of the total EU fishing fleet. The typically low-technological capacity of these small-scale fishing boats-for which space and power onboard are often limited-as well their reduced operative range encourage the development of efficient, low-cost, and low-burden tracking solutions. In this context, we designed a cost-effective and scalable prototypic architecture to gather and process positional data from small-scale vessels, making use of a LoRaWAN/cellular network. Data collected by our first installation are presented, as well as its preliminary processing. The emergence of a such low-cost and open-source technology coupled to artificial intelligence could open new opportunities for equipping small-scale vessels, collecting their trajectory data, and estimating their fishing effort (information which has historically not been present). It enables a new monitoring strategy that could effectively include small-scale fleets and support the design of new policies oriented to inform coastal resource and fisheries management.
Micro-plastic particles in the world's oceans represent a serious threat to both human health and marine ecosystems. Once released into the aquatic environment plastic litter is broken down to ...smaller pieces through photo-degradation and the physical actions of waves, wind, etc. The resulting particles may become so small that they are readily taken up by fish, crustaceans and mollusks. There is mounting evidence for the uptake of plastic particles by marine organisms that form part of the human food chain and this is driving urgent calls for further and deeper investigations into this pollution issue.
The present study aimed at investigating for the first time the occurrence, amount, typology of microplastic litter in the gastrointestinal tract of Solea solea and its spatial distribution in the northern and central Adriatic Sea. This benthic flatfish was selected as it is a species of high commercial interest within the FAO GFCM (General Fisheries Commission for the Mediterranean) area 37 (Mediterranean and Black Sea) where around 15% of the overall global Solea solea production originates.
The digestive tract contents of 533 individuals collected in fall during 2014 and 2015 from 60 sampling sites were examined for microplastics. These were recorded in 95% of sampled fish, with more than one microplastic item found in around 80% of the examined specimens. The most commonly found polymers were polyvinyl chloride, polypropylene, polyethylene, polyester, and polyamide, 72% as fragments and 28% as fibers. The mean number of ingested microplastics was 1.73 ± 0.05 items per fish in 2014 and 1.64 ± 0.1 in 2015. PVC and PA showed the highest densities in the northern Adriatic Sea, both inshore and off-shore while PE, PP and PET were more concentrated in coastal areas with the highest values offshore from the port of Rimini.
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•The characterization of microplastics in the stomach of common sole is investigated.•Investigations were oriented toward size and polymer composition.•The majority of plastics were fragments, only a limited amount of fibers was scored.
Occurrence and polymeric composition of microplastics in stomach content of wild S. solea is assessed. Spatial distribution is more influenced both by polymers chemical-physical properties and peculiarities in the oceanographic conditions rather than by the feeding strategy of the species.
Multibeam echosounders are widely used for 3D bathymetric mapping, and increasingly for water column studies. However, they rapidly collect huge volumes of data, which poses a challenge for water ...column data processing that is often still manual and time-consuming, or affected by low efficiency and high false detection rates if automated. This research describes a comprehensive and reproducible workflow that improves efficiency and reliability of target detection and classification, by calculating metrics for target cross-sections using a commercial software before feeding into a feature-based semi-supervised machine learning framework. The method is tested with data collected from an uncalibrated multibeam echosounder around an offshore gas platform in the Adriatic Sea. It resulted in more-efficient target detection, and, although uncertainties regarding user labelled training data need to be underlined, an accuracy of 98% in target classification was reached by using a final pre-trained stacking ensemble model.
The COVID-19 pandemic provides a major opportunity to study fishing effort dynamics and to assess the response of the industry to standard and remedial actions. Knowing a fishing fleet's capacity to ...compensate for effort reduction (i.e., its resilience) allows differentiating governmental regulations by fleet, i.e., imposing stronger restrictions on the more resilient and weaker restrictions on the less resilient. In the present research, the response of the main fishing fleets of the Adriatic Sea to fishing hour reduction from 2015 to 2020 was measured. Fleet activity per gear type was inferred from monthly Automatic Identification System data. Pattern recognition techniques were applied to study the fishing effort trends and barycentres by gear. The beneficial effects of the lockdowns on Adriatic endangered, threatened and protected (ETP) species were also estimated. Finally, fleet effort series were examined through a stock assessment model to demonstrate that every Adriatic fishing fleet generally behaves like a stock subject to significant stress, which was particularly highlighted by the pandemic. Our findings lend support to the notion that the Adriatic fleets can be compared to predators with medium-high resilience and a generally strong impact on ETP species.
Recent technological advancements have facilitated the extensive collection of movement data from large-scale fishing vessels, yet a significant data gap remains for small-scale fisheries. This gap ...hinders the development of consistent exploitation patterns and meeting the information needs for marine spatial planning in fisheries management. This challenge is specifically addressed in the Campania region of Italy, where several Marine Protected Areas support biodiversity conservation and fisheries management. The authors have created a spatially-explicit dataset that encompasses both large-scale (vessels exceeding 12 meters in length) and small-scale (below 12 meters) fishing efforts. This dataset (available at https://doi.org/10.6084/m9.figshare.23592006 ) is derived from vessel tracking data and participatory mapping. It offers insights into potential conflicts between different fishing segments and their interactions with priority species and habitats. The data can assist researchers and coastal management stakeholders in formulating policies that reduce resource competition and promote ecosystem-based fisheries management. Furthermore, the provided mapping approach is adaptable for other regions and decision-making frameworks, as we are committed to sharing the tools and techniques we employed.
Hydrocarbon seepage is overlooked in the marine environment, mostly due to the lack of high-resolution exploration data. This contribution is about the set-up of a relocatable and cost-effective ...monitoring system, which was tested on two seepages in the Central Adriatic Sea. The two case studies are an oil spill at a water depth of 10 m and scattered biogenic methane seeps at a water depth of 84 m. Gas plumes in the water column were detected with a multibeam system, tightened to sub-seafloor seismic reflection data. Dissolved benthic fluxes of nutrients, metals and Dissolved Inorganic Carbon (DIC) were measured by in situ deployment of a benthic chamber, which was used also for the first time to collect water samples for hydrocarbons characterization. In addition, the concentration of polycyclic aromatic hydrocarbons, as well as major and trace elements were analyzed to provide an estimate of hydrocarbon contamination in the surrounding sediment and to make further inferences on the petroleum system.
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.
Funding innovation requires knowledge on previous/on-going research and identification of gaps and synergies among actors, networks and projects, but targeted databases remain scattered, incomplete ...and scarcely searchable. Here we present the BlueBio database: a first comprehensive and robust compilation of internationally and nationally funded research projects active in the years 2003-2019 in Fisheries, Aquaculture, Seafood Processing and Marine Biotechnology. Based on the previous research projects' database realized in the framework of the COFASP ERA-NET, it was implemented within the ERA-NET Cofund BlueBio project through a 4-years data collection including 4 surveys and a wide data retrieval. After being integrated, data were harmonised, shared as open and disseminated through a WebGIS that was key for data entry, update and validation. The database consists of 3,254 "georeferenced" projects, described by 22 parameters that are clustered into textual and spatial, some directly collected while others deduced. The database is a living archive to inform actors of the Blue Bioeconomy sector in a period of rapid transformations and research needs and is freely available at: https://doi.org/10.6084/m9.figshare.21507837.v3 .
The combination of elevation data together with multispectral high-resolution images is a new methodology for obtaining land use/land cover classification. It represents a step forward for both the ...accuracy and automation of LULC applications and allows users to setup thematic assignments through rules based on feature attributes and human expert interpretation of land usage. The synergy between different types of information means that LiDAR can give new hints at both the segmentation and hybrid classification steps, leading to a joint use of multispectral, spatial and elevation data. The output is a thematic map characterized by a custom-designed legend that is able to discriminate between land cover classes with similar spectral characteristics (level 3 of the CLC legend). Experimental results from a hilly farmland area with some urban structures (Musone river basin, Ancona, Italy) are used to highlight how the proposed methodology enhances land cover classification in heterogeneous environments.
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