Biology

VMSbase is an R package devised to manage, process and visualize information about fishing vessels activity (provided by the vessel monitoring system-VMS) and catches/landings (as reported in the logbooks). VMSbase is primarily conceived to be user-friendly; to this end, a suite of state-of-the-art analyses is accessible via a graphical interface. In addition, the package uses a database platform allowing large datasets to be stored, managed and processed vey efficiently. Methodologies include data cleaning, that is removal of redundant or evidently erroneous records, and data enhancing, that is interpolation and merging with external data sources. In particular, VMSbase is able to estimate sea bottom depth for single VMS pings using an on-line connection to the National Oceanic and Atmospheric Administration (NOAA) database. It also allows VMS pings to be assigned to whatever geographic partitioning has been selected by users. Standard analyses comprise: 1) métier identification (using a modified CLARA clustering approach on Logbook data or Artificial Neural Networks on VMS data); 2) linkage between VMS and Logbook records, with the former organized into fishing trips; 3) discrimination between steaming and fishing points; 4) computation of spatial effort with respect to user-selected grids; 5) calculation of standard fishing effort indicators within Data Collection Framework; 6) a variety of mapping tools, including an interface for Google viewer; 7) estimation of trawled area. Here we report a sample workflow for the accessory sample datasets (available with the package) in order to explore the potentialities of VMSbase. In addition, the results of some performance tests on two large datasets (1610 5 and 1610 6 VMS signals, respectively) are reported to inform about the time required for the analyses. The results, although merely illustrative, indicate that VMSbase can represent a step forward in extracting and enhancing information from VMS/logbook data for fisheries studies.

A number of restrictions envisaged by Council Regulation 1967/2006 (Mediterranean Regulation, MR) have been introduced to reduce the fishing effort and the catch of juveniles in the Mediterranean Sea. A large proportion of the purse seiners of the Adriatic fleet that target small pelagic species may be using gear that does not comply with regulatory provisions. This study provides a thorough overview on Adriatic purse seine designs and fishing practices. Moreover, since no detailed information was available about their environmental impact, an ad hoc study was also performed to examine the issue in relation to Mediterranean Regulation provisions. Analysis of the technical data confirmed the vast majority of the nets used by the Adriatic purse seine fleet do not comply with regulatory provisions. However, data analysis highlighted that the technical features and operational characteristics of these fisheries do not justify the application of MR restrictions. In fact, i) spatial analysis of the fishing effort demonstrated that purse seiners operate more than 3 nautical miles off the coast, i.e. further than the area covered by the restrictions; and ii) data from sensors and video cameras documented that purse seines do not exert adverse impacts on critical habitats such as Posidonia meadows and that the groundrope impact on the seabed is so slight and short-lived as to be negligible. Moreover, the extensive changes required to make purse seines compliant with the MR would entail steep costs and would ultimately render the nets unsuitable for commercial fishing, thus involving highly negative socioeconomic consequences.

Analysis of data from vessel monitoring systems and automated identification systems in large-scale fisheries is used to describe the spatial distribution of effort, impact on habitats, and location of fishing grounds. To identify when and where fishing activities occur, analysis needs to take account of different fishing practices in different fleets. Small-scale fisheries (SSFs) vessels have generally been exempted from positional reporting requirements, but recent developments of compact low-cost systems offer the potential to monitor them effectively. To characterize the spatial distribution of fishing activities in SSFs, positions should be collected with sufficient frequency to allow detection of different fishing behaviours, while minimizing demands for data transmission, storage, and analysis. This study sought to suggest optimal rates of data collection to characterize fishing activities at appropriate spatial resolution. In a SSF case study, on-board observers collected Gl...

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The rationale applied for monitoring and managing fisheries is based on the implicit assumption that yield and stocks status is essentially determined by fisheries. Moreover, the fisheries yield is quantified and analyzed in terms of landings with respect to official management area of registration of vessels. In this way, the real area of activity of each fleet is not considered and this prevent an effective spatial analysis of the factors affecting fisheries yield and stocks status. This paper firstly presents a VMS-based reconstruction of the fishing effort and of the area of activity of the Italian trawlers in the Mediterranean Sea. The fishing area of each fleet is then used as a spatial reference to estimate primary productivity rate and gross primary production and to investigate, by using General Additive Models, the effects of trawling effort, primary production and time on fisheries yield, fisheries productivity and overexploitation rate for some key demersal species. The results evidence that the usage of satellite-based information of fishing activities and of primary production, when combined at the real spatial scale of fishing activities, could effectively improve our ability to analyze the response of the ecosystems to these driving forces and allow capturing the main trends of yield, productivity and overexploitation rate of demersal stocks.

Marine litter has significant ecological, social and economic impacts, ultimately raising welfare and conservation concerns. Assessing marine litter hotspots or inferring potential areas of accumulation are challenging topics of marine research. Nevertheless, models able to predict the distribution of marine litter on the seabed are still limited. In this work, a set of Artificial Neural Networks were trained to both model the effect of environmental descriptors on litter distribution and estimate the amount of marine litter in the Central Mediterranean Sea. The first goal involved the use of self-organizing maps in order to highlight the importance of environmental descriptors in affecting marine litter density. The second goal was achieved by developing a multilayer perceptron model, which proved to be an efficient method to estimate the regional quantity of seabed marine litter. Results demonstrated that machine learning could be a suitable approach in the assessment of the marine litter issues.

The increasing use of tracking devices, such as the Vessel Monitoring System (VMS) and the Automatic Identification System (AIS), have allowed, in the last decade, detailed spatial and temporal analyses of fishing footprints and of their effects on environments and resources. Nevertheless, tracking devices usually allow monitoring of the largest length classes composing different fleets, whereas fishing vessels below a regulatory threshold (i.e., 15 m in length-overall) are not mandatorily equipped with these tools. This issue is critical, since 36% of the vessels in the European Union (EU) fleets belong to these "hidden" length classes. In this study, a model [namely, a cascaded multilayer perceptron network (CMPN)] is devised to predict the annual fishing footprints of vessels without tracking devices. This model uses information about fleet structures, environmental characteristics, human activities, and fishing effort patterns of vessels equipped with tracking devices. Furthermore, the model is able to take into account the interactions between different components of the fleets (e.g., fleet segments), which are characterized by different operating ranges and compete for the same marine space. The model shows good predictive performance and allows the extension of spatial analyses of fishing footprints to the relevant, although still unexplored, fleet segments.

1. Overfishing or exploitation patterns with high juvenile mortalities often negatively impact demersal fish stocks. Meanwhile, the increased availability and diffusion of georeferenced information is propelling a revolution of marine spatial planning. 2. A spatial-explicit approach to the management of fishing effort should protect the Essential Fish Habitats and minimize the impact of trawlers on areas where juveniles of commercial species concentrate. 3. The smartR package is a data-driven model that implements the Spatially explicit bio-economic Model for Assessing and managing demeRsal Trawl fisheries to edit and format the raw data; construct and maintain coherent datasets; to numerically and visually inspect the generated metadata; to simulate management scenarios and forecast the possible effects in terms of resources status and economic performances of the fleets. 4. Explicit inclusion of the spatial dimension is essential to improve the understanding of the fishery system, and to enhance the ability of management plans to improve stocks statuses.

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 “slush” collected from fishing nets just after the end of hauling operations. 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 (reads counts generated by amplicon sequencing). We demonstrate that the assemblages identified using ...

The Working Group on Fisheries Benthic Impact and Trade-offs (WGFBIT) develops methods and performs assessments to evaluate benthic impact from fisheries at regional scale, while considering fisheries and seabed impact trade-offs. WGFBIT has attempted to perform these assessments for as many regions as possible, and for each region indicate, prioritize and execute (if feasible) potential improvements. In order to broadly anchor the assessment methodology, demonstrate its utility and flexibility and identify relevant data gaps and appropriate improvement potentials it was key that each assessment was performed and discussed by the regional experts at the meeting. The FBIT assessment framework was successfully applied in 5 ecoregions; the Arctic Sea, the Baltic Sea, the North Sea, the Celtic Sea and the Mediterranean Sea, with variable level of completeness and robustness. Standard structured regional outputs from the WGFBIT assessment workflow, in terms of pressure, sensitivity and impact estimates, were produced and presented for each region. This is a significant step towards the WGFBIT term of reference 'to produce a framework for MSFD D6/D1 assessment related to bottom abrasion of fishing activity at the regional scale'. An additional outcome from the assessments was an increased consensus and appreciation of the utility of the FBIT assessment framework. Each regional group identified where and how the assessment and methodology could be further improved; e.g. the need for updated and regionwide fishing pressure data and the inclusion of additional region-specific environmental variables in the estimation of habitat sensitivity. Moreover, a strategy was agreed on to further operationalize the current ecoregion assessments as well as bring in additional ecoregions. Four intersessional subgroups (trade-off, deep sea, data-script management, communication and advice) were established to facilitate future advances in the work of WGFBIT. These groups will be seeking to update and increase coverage of fishing pressure data (mainly for the Mediterranean), develop longevity estimation methods for deep-sea species and habitats, refine assessment approaches, integrate additional physical disturbance pressures, in addition to fishing, in the assessment and further develop communication material addressing dissemination of the methodological details, the actual assessment procedures and standardized workflow. ICES | WGFBIT 2019 | III ii Expert group information Expert group name Working group on Fishery Benthic impact and trade-off (WGFBIT) Expert group cycle Multiannual Year cycle started 2018 Reporting year in cycle 2/3 Chair(s) Gert Van Hoey, Belgium

Current fishing practices often do not allow adequate selection of species or sizes of fish, resulting in unwanted catches, subsequently discarded, with the consequent negative effects on both marine communities and fisheries profitability. The cross-analysis of density patches of potential unwanted catches and distribution of fishing effort can support the identification of spatial-temporal hot-spots in which the fishing pressure should be reduced to limit the amount of discards. The MinouwApp represents a technological and methodological framework to bring different, and structurally complex, sources of georeferenced data together into a simple visual interface aiming to interactively explore temporal ranges and areas of interest. The objective is to improve the understanding of fisheries dynamics, including discards, thus contributing to the implementation of discard management plans in a context of participative, ecosystem-based fisheries management strategies.

The recent establishment of the “landing obligation” under the reformed EU Common Fishery Policy has the twofold objective of reducing the excessive practice of discarding unwanted catch at sea and encouraging more selective and sustainable fisheries. Within this context, the awareness of the spatial distribution of potential unwanted catches is important for devising management measures aimed to decrease discards. This study analyzed the distribution of Hot Spot density areas of demersal fish and crustaceans below the Minimum Conservation Reference Size (MCRS) in four different southern European seas: continental Portuguese coast, Catalan Sea, South of Sicily, Liguria and northern Tyrrhenian Seas using both bottom trawl survey data and information on the spatial distribution of commercial fisheries. Critical areas for discarding were identified as zones where the highest densities of individuals below MCRS were consistently recorded throughout a series of years. Results clearly sho...