Explore the vast range of titles available.

Bottom trawlers land around 19 million tons of fish and invertebrates annually, almost one-quarter of wild marine landings. The extent of bottom trawling footprint (seabed area trawled at least once in a specified region and time period) is often contested but poorly described. We quantify footprints using high-resolution satellite vessel monitoring system (VMS) and logbook data on 24 continental shelves and slopes to 1,000-m depth over at least 2 years. Trawling footprint varied markedly among regions: from < 10% of seabed area in Australian and New Zealand waters, the Aleutian Islands, East Bering Sea, South Chile, and Gulf of Alaska to > 50% in some European seas. Overall, 14% of the 7.8 million-km2 study area was trawled, and 86% was not trawled. Trawling activity was aggregated; the most intensively trawled areas accounting for 90% of activity comprised 77% of footprint on average. Regional swept area ratio (SAR; ratio of total swept area trawled annually to total area of region, a metric of trawling intensity) and footprint area were related, providing an approach to estimate regional trawling footprints when highresolution spatial data are unavailable. If SAR was =0.1, as in 8 of 24 regions, therewas > 95% probability that > 90%of seabed was not trawled. If SAR was 7.9, equal to the highest SAR recorded, there was > 95% probability that >70% of seabed was trawled. Footprints were smaller and SAR was =0.25 in regions where fishing rates consistently met international sustainability benchmarks for fish stocks, implying collateral environmental benefits from sustainable fishing. © 2018 National Academy of Sciences. All rights reserved.

Several research initiatives have been undertaken to map fishing effort at high spatial resolution using the Vessel Monitoring System (VMS). An alternative to the VMS is represented by the Automatic Identification System (AIS), which in the EU became compulsory in May 2014 for all fishing vessels of length above 15 meters. The aim of this paper is to assess the uptake of the AIS in the EU fishing fleet and the feasibility of producing a map of fishing effort with high spatial and temporal resolution at European scale. After analysing a large AIS dataset for the period January-August 2014 and covering most of the EU waters, we show that AIS was adopted by around 75% of EU fishing vessels above 15 meters of length. Using the Swedish fleet as a case study, we developed a method to identify fishing activity based on the analysis of individual vessels' speed profiles and produce a high resolution map of fishing effort based on AIS data. The method was validated using detailed logbook data and proved to be sufficiently accurate and computationally efficient to identify fishing grounds and effort in the case of trawlers, which represent the largest portion of the EU fishing fleet above 15 meters of length. Issues still to be addressed before extending the exercise to the entire EU fleet are the assessment of coverage levels of the AIS data for all EU waters and the identification of fishing activity in the case of vessels other than trawlers.

A key challenge in contemporary ecology and conservation is the accurate tracking of the spatial distribution of various human impacts, such as fishing. While coastal fisheries in national waters are closely monitored in some countries, existing maps of fishing effort elsewhere are fraught with uncertainty, especially in remote areas and the High Seas. Better understanding of the behavior of the global fishing fleets is required in order to prioritize and enforce fisheries management and conservation measures worldwide. Satellite-based Automatic Information Systems (S-AIS) are now commonly installed on most ocean-going vessels and have been proposed as a novel tool to explore the movements of fishing fleets in near real time. Here we present approaches to identify fishing activity from S-AIS data for three dominant fishing gear types: trawl, longline and purse seine. Using a large dataset containing worldwide fishing vessel tracks from 2011-2015, we developed three methods to detect and map fishing activities: for trawlers we produced a Hidden Markov Model (HMM) using vessel speed as observation variable. For longliners we have designed a Data Mining (DM) approach using an algorithm inspired from studies on animal movement. For purse seiners a multi-layered filtering strategy based on vessel speed and operation time was implemented. Validation against expert-labeled datasets showed average detection accuracies of 83% for trawler and longliner, and 97% for purse seiner. Our study represents the first comprehensive approach to detect and identify potential fishing behavior for three major gear types operating on a global scale. We hope that this work will enable new efforts to assess the spatial and temporal distribution of global fishing effort and make global fisheries activities transparent to ocean scientists, managers and the public.

The fishing sector is faced with emission problems arising from the extensive use of diesel engines as prime movers. Energy efficiency, environmental performance, and minimization of operative costs through the reduction of fuel consumption are key research topics across the whole maritime sector. Ship emissions can be determined at different levels of complexity and accuracy, i.e., by analyzing ship technical data and assuming its operative profile, or by direct measurements of key parameters. This paper deals with the analysis of the environmental footprint of a fishing trawler operating in the Adriatic Sea, including three phases of the Life-Cycle Assessment (manufacturing, Well-to-Pump (WTP), and Pump-to-Wake (PTW)). Based on the data on fuel consumption, the viability of replacing the conventional diesel-powered system with alternative options is analyzed. The results showed that fuels such as LNG and B20 represent the easiest solution that would result in a reduction of harmful gases and have a positive impact on overall costs. Although electrification and hydrogen represent one of the cleanest forms of energy, due to their high price and complex application in an obsolete fleet, they do not present an optimal solution for the time being. The paper showed that the use of alternative fuels would have a positive effect on the reduction of harmful emissions, but further work is needed to find an environmentally acceptable and economically profitable pathway for redesigning the ship power system of fishing trawlers.

Il 17 febbraio 2024, dodici esemplari di Champsodon nudivittis sono stati catturati da un peschereccio commerciale a strascico per la pesca dei gamberi nelle acque costiere di Karabiga, nella provincia di Çanakkale, a una profondità compresa tra i 45 e i 65 m. 11 presente lavoro presenta le segnalazioni aggiornate di C. nudivittis nei Mediterraneo, compresa la recente presenza nei Mar di Marmara, in Turchia.

Monitoring marine resource exploitation is a key activity in fisheries science and biodiversity conservation. Since research surveys are time consuming and costly, fishery-dependent data (i.e., derived directly from fishing vessels) are increasingly credited with a key role in expanding the reach of ocean monitoring. Fishing vessels may be seen as widely ranging data-collecting platforms, which could act as a fleet of sentinels for monitoring marine life, in particular exploited stocks. Here, we investigate the possibility of assessing catch composition of single hauls carried out by trawlers by applying DNA metabarcoding to the dense water draining from fishing nets just after the end of hauling operations (hereafter “slush”). We assess the performance of this approach in portraying β-diversity and examining the quantitative relationship between species abundances in the catch and DNA amount in the slush (read counts generated by amplicon sequencing). We demonstrate that the assemblages identified using DNA in the slush satisfactorily mirror those returned by visual inspection of net content (about 71% of species and 86% of families of fish) and detect a strong relationship between read counts and species abundances in the catch. We therefore argue that this approach could be upscaled to serve as a powerful source of information on the structure of demersal assemblages and the impact of fisheries.

Common bottlenose dolphins (Tursiops truncatus) rely on whistles for group cohesion and coordination and on echolocation for prey detection and capture. In Texas bays, dolphins recurrently feed near shrimp trawlers and along seawalls, where they encounter different anthropogenic noises and prey availabilities. We used passive acoustic monitoring to compare whistles and click trains produced by dolphins foraging in these two human-modified habitats in the Texas Coastal Bend. Whistle sequences near trawlers exhibited greater contour diversity and complexity than those near seawalls, likely reflecting developmental and social influences within large mixed-age aggregations that included calves and young-of-year. Elevated group-level click and buzz activity near trawlers primarily reflected large group sizes rather than increased clicking by individuals, indicating collective echolocation effort. Higher proportions of buzz clicks and buzz-containing trains near trawlers indicate increased foraging effort and repeated prey-capture attempts when exploiting trawler-aggregated prey. Short, sparse, and more variable click trains near seawalls are consistent with exploratory echolocation in a less predictable foraging environment where the benefits of eavesdropping are reduced. The data show that social structure, prey resources, and habitat-specific noise shape communication and echolocation across the two foraging contexts.

Aim To examine the utility of local ecological knowledge (LEK) and fishing effort data in revealing bycatch patterns of marine threatened species in small‐scale fisheries to inform their conservation and management. Location Northern Haizhou Bay, China (35° to 37° N, 119° to 122° E). Methods We conducted semi‐structured interviews on fishers (N = 97) in small‐scale fisheries to derive LEK about bycatch of 20 threatened species (12 sharks, one mammal, one seahorse and six seabirds). We analysed the bycatch/sighting occurrence seasonality, gear‐specific bycatch risk, perceived bycatch levels and trends of these species. We compared the qualitative description with quantitative data of bycatch levels using Hellinger Distances. We identified fishery‐wildlife conflict hotspots based on fishing effort data from the Global Fishing Watch and LEK‐elicited species distributions. Results Our results revealed that the fishers could provide occurrences of 12 threatened fauna (excluding seabirds) which peaked in spring and autumn; their perceived bycatch levels were generally very low. Overall, fishers couldn't discriminate seabird species and suggested that bycatch of seabirds was extremely rare. Trawlers imposed the highest bycatch risk to almost all focal species. Of the six species with available data, only two had qualitative categorisations of perceived bycatch levels that aligned with quantitative estimates. Perceived bycatch levels of all species declined, but only three had quantitative estimations (a decline rate of 80%–89% over past decade). Additionally, bycatch of threatened species largely occurred in a coastal area (34°30′–36°30′ N and 119°0′–121°30′ E) that was heavily fished. Main Conclusions The threatened marine bycatch fauna in the Northern Haizhou Bay demand urgent population assessment and precautionary management measures. Fishers' quantitative and qualitative knowledge provides useful data on bycatch levels and their trends for these fauna. Our study provides a cost‐effective approach to inform bycatch management of threatened marine species in small‐scale fisheries of developing countries.

Human beings are the dominant top predator in the marine ecosystem. Throughout most of the global ocean this predation is carried out by industrial fishing vessels, that can now be observed in unprecedented detail via satellite monitoring of Automatic Identification System (AIS) messages. The spatial and temporal distribution of this fishing effort emerges from the coupled interaction of ecological and socio-economic drivers and can therefore yield insights on the dynamics of both the ecosystem and fishers. Here we analyze temporal variability of industrial fishing effort from 2015-2017 as recorded by global AIS coverage, and differentiated by fishing gear type. The strongest seasonal signal is a reduction of total deployed effort during the annual fishing moratorium on the numerically-dominant Chinese fleet, which occurs during boreal summer. An additional societally-controlled reduction of effort occurs during boreal winter holidays. After accounting for these societal controls, the total deployed effort is relatively invariant throughout the year for all gear types except squid jiggers and coastal purse seiners. Despite constant deployment levels, strong seasonal variability occurs in the spatial pattern of fishing effort for gears targeting motile pelagic species, including purse seiners, squid jiggers and longliners. Trawlers and fixed gears target bottom-associated coastal prey and show very little overall seasonality, although they exhibit more seasonal variation at locations that are further from port. Our results suggest that societal controls dominate the total deployment of fishing effort, while the behavior of pelagic fish, including seasonal migration and aggregation, is likely the most prominent driver of the spatial seasonal variations in global fishing effort.