scholarly journals Lockdown: How the COVID-19 Pandemic Affected the Fishing Activities in the Adriatic Sea (Central Mediterranean Sea)

2021 ◽  
Vol 8 ◽  
Author(s):  
Elisabetta Russo ◽  
Marco Anelli Monti ◽  
Giacomo Toninato ◽  
Claudio Silvestri ◽  
Alessandra Raffaetà ◽  
...  
Keyword(s):  
Venice Lagoon ◽  
Fishing Effort ◽  
Otter Trawl ◽  
Small Scale ◽  
Automatic Identification ◽  
Identification System ◽  
Strong Reduction ◽  
Central Mediterranean ◽  
Containment Measures ◽  
Almost All

The coronavirus disease 2019 (COVID-19) has brought a global socio-economic crisis to almost all sectors including the fishery. To limit the infection, governments adopted several containment measures. In Italy, Croatia, and Slovenia, a lockdown period was imposed from March to May 2020, during which many activities, including restaurants had to close or limit their business. All of this caused a strong reduction in seafood requests and consequently, a decrease in fishing activities. The aim of this study is to investigate the effects of the COVID-19 in the Northern and Central Adriatic fleet, by comparing the fishing activities in three periods (before, during, and after the lockdown) of 2019 and 2020. The use of the Automatic Identification System (AIS) data allowed us to highlight the redistribution of the fishing grounds of the trawlers, mainly located near the coasts during the 2020 lockdown period, as well as a reduction of about 50% of fishing effort. This reduction resulted higher for the Chioggia trawlers (−80%) and, in terms of fishing effort decrease, the large bottom otter trawl was the fishing segment mainly affected by the COVID-19 event. Moreover, by analysing the landings of the Chioggia fleet and the Venice lagoon fleets, it was possible to point out a strong reduction both in landings and profits ranging from −30%, for the small-scale fishery operating at sea, to −85%, for the small bottom otter trawl.

scholarly journals Global Fisheries Responses to Culture, Policy and COVID-19 from 2017 to 2020

2021 ◽  
Vol 13 (22) ◽  
pp. 4507
Author(s):  
Bin He ◽  
Fengqin Yan ◽  
Hao Yu ◽  
Fenzhen Su ◽  
Vincent Lyne ◽  
...  
Keyword(s):  
Large Data ◽  
Fishing Effort ◽  
Coastal Areas ◽  
Decision Makers ◽  
Small Scale ◽  
Automatic Identification ◽  
Identification System ◽  
Political Events ◽  
Open Source Data ◽  
The Us

Global Fishing Watch (GFW) provides global open-source data collected via automated monitoring of vessels to help with sustainable management of fisheries. Limited previous global fishing effort analyses, based on Automatic Identification System (AIS) data (2017–2020), suggest economic and environmental factors have less influence on fisheries than cultural and political events, such as holidays and closures, respectively. As such, restrictions from COVID-19 during 2020 provided an unprecedented opportunity to explore added impacts from COVID-19 restrictions on fishing effort. We analyzed global fishing effort and fishing gear changes (2017–2019) for policy and cultural impacts, and then compared impacts of COVID-19 lockdowns across several countries (i.e., China, Spain, the US, and Japan) in 2020. Our findings showed global fishing effort increased from 2017 to 2019 but decreased by 5.2% in 2020. We found policy had a greater impact on monthly global fishing effort than culture, with Chinese longlines decreasing annually. During the lockdown in 2020, trawling activities dropped sharply, particularly in the coastal areas of China and Spain. Although Japan did not implement an official lockdown, its fishing effort in the coastal areas also decreased sharply. In contrast, fishing in the Gulf of Mexico, not subject to lockdown, reduced its scope of fishing activities, but fishing effort was higher. Our study demonstrates, by including the dimensions of policy and culture in fisheries, that large data may materially assist decision-makers to understand factors influencing fisheries’ efforts, and encourage further marine interdisciplinary research. We recommend the lack of data for small-scale Southeast Asian fisheries be addressed to enable future studies of fishing drivers and impacts in this region.

A Cloud Computing Architecture to Map Trawling Activities Using Positioning Data

2019 ◽  
Author(s):  
A. Galdelli ◽  
A. Mancini ◽  
A. N. Tassetti ◽  
C. Ferrà Vega ◽  
E. Armelloni ◽  
...  
Keyword(s):  
Integrated Management ◽  
Low Cost ◽  
Sustainable Use ◽  
Fishing Effort ◽  
Small Scale ◽  
Automatic Identification ◽  
Identification System ◽  
Small Vessels ◽  
Small Scale Fisheries ◽  
Major Development

Abstract Descriptive and spatially-explicit information on fisheries plays a key role for an efficient integrated management of the maritime activities and the sustainable use of marine resources. However, this information is today still hard to obtain and, consequently, is a major issue for implementing Marine Spatial Planning (MSP). Since 2002, the Automatic Identification System (AIS) has been undergoing a major development allowing now for a real time geo-tracking and identification of equipped vessels of more than 15m in length overall (LOA) and, if properly processed, for the production of adequate information for MSP. Such monitoring systems or other low-cost and low-burden solutions are still missing for small vessels (LOA < 12m), whose catches and fishing effort remain spatially unassessed and, hence, unregulated. In this context, we propose an architecture to process vessel tracking data, understand the behaviour of trawling fleets and map related fishing activities. It could be used to process not only AIS data but also positioning data from other low cost systems as IoT sensors that share their position over LoRa and 2G/3G/4G links. Analysis gives back important and verified data (overall accuracy of 92% for trawlers) and opens up development perspectives for monitoring small scale fisheries, helping hence to fill fishery data gaps and obtain a clearer picture of the fishing grounds as a whole.

scholarly journals The global network of ports supporting high seas fishing

2021 ◽  
Vol 7 (9) ◽  
pp. eabe3470
Author(s):  
Jorge P. Rodríguez ◽  
Juan Fernández-Gracia ◽  
Carlos M. Duarte ◽  
Xabier Irigoien ◽  
Víctor M. Eguíluz
Keyword(s):  
Fishing Effort ◽  
Global Network ◽  
Automatic Identification ◽  
Identification System ◽  
Middle Income ◽  
Middle Income Countries ◽  
Fishing Vessels ◽  
National Jurisdiction ◽  
The Commons ◽  
High Seas

Fisheries in waters beyond national jurisdiction (“high seas”) are difficult to monitor and manage. Their regulation for sustainability requires critical information on how fishing effort is distributed across fishing and landing areas, including possible border effects at the exclusive economic zone (EEZ) limits. We infer the global network linking harbors supporting fishing vessels to fishing areas in high seas from automatic identification system tracking data in 2014, observing a modular structure, with vessels departing from a given harbor fishing mostly in a single province. The top 16% of these harbors support 84% of fishing effort in high seas, with harbors in low- and middle-income countries ranked among the top supporters. Fishing effort concentrates along narrow strips attached to the boundaries of EEZs with productive fisheries, identifying a free-riding behavior that jeopardizes efforts by nations to sustainably manage their fisheries, perpetuating the tragedy of the commons affecting global fishery resources.

scholarly journals Defining high-resolution dredge fishing grounds with Automatic Identification System (AIS) data

2017 ◽  
Vol 30 ◽  
pp. 39 ◽  
Author(s):  
Damien Le Guyader ◽  
Cyril Ray ◽  
Françoise Gourmelon ◽  
David Brosset
Keyword(s):  
High Resolution ◽  
Data Access ◽  
Relevant Information ◽  
Fishing Effort ◽  
Automatic Identification ◽  
Identification System ◽  
Automatic Identification System ◽  
Local Decision ◽  
Bay Of Brest ◽  
Maritime Spatial Planning

High resolution estimates of bottom towed fishing gears are needed to provide relevant information for natural resource management, impact assessment and maritime spatial planning. The use of satellite-based vessel monitoring system (VMS) data is constrained by data access restrictions as well as rather coarse data resolution. This study focuses on mapping dredge gear fishing grounds using fishing effort estimates at the métier level based on automatic identification system (AIS) data. The performance of the approach was evaluated in terms of correct discrimination between fishing and non-fishing activities for known fishing positions as well as appropriate error propagation. The test was conducted in the Bay of Brest (France) in partnership with a committee of local fishers. The results identified dredge fishing grounds for great scallop (Pecten maximus) in the western part of the Bay of Brest and provided high-resolution information for scientists and local decision makers on the spatial and temporal seasonal variability of fishing effort. The proposed method is semi-automatic and generic making it suitable for other applications.

scholarly journals Sensing the Same Fishing Fleet with AIS and VIIRS: A Seven-Year Assessment of Squid Jiggers in FAO Major Fishing Area 41

2019 ◽  
Vol 12 (1) ◽  
pp. 32
Author(s):  
Javier Ruiz ◽  
Isabel Caballero ◽  
Gabriel Navarro
Keyword(s):  
Infrared Imaging ◽  
Spatial Scales ◽  
Fishing Effort ◽  
Automatic Identification ◽  
Identification System ◽  
Sources Of Information ◽  
Food And Agriculture ◽  
Food And Agriculture Organization ◽  
High Degree ◽  
Fishing Area

Global Fishing Watch and VIIRS-DNB (visible infrared imaging radiometer suite day/night band) signals are compared for the jigger fleet in FAO (Food and Agriculture Organization of the United Nations) Major Fishing Area 41 during the maximum feasible time span (2012–2018). Both signals have shown a high degree of consistency at all temporal and spatial scales analyzed, including seasonal cycles, lack of signal for some years and interannual tendencies. This indicates that both signals are a fair representation of the fishing effort exerted by the jigger fleet in this zone. The high degree of consistency does not support views questioning satellite AIS (automatic identification system) as a reliable tool to survey fishing activities. Instead, our results add evidence supporting the value of remote sensing, in particular, when independent sources of information (such as VIIRS-DNB and AIS) are combined, as a relevant tool to add transparency and support compliance of fishing activities in vast and distant regions of the ocean.

scholarly journals AIS and VMS Ensemble Can Address Data Gaps on Fisheries for Marine Spatial Planning

2021 ◽  
Vol 13 (7) ◽  
pp. 3769
Author(s):  
Pascal Thoya ◽  
Joseph Maina ◽  
Christian Möllmann ◽  
Kerstin S. Schiele
Keyword(s):  
Case Studies ◽  
Spatial Planning ◽  
Fishing Effort ◽  
Rapid Expansion ◽  
Automatic Identification ◽  
Identification System ◽  
Marine Spatial Planning ◽  
The North ◽  
Address Data ◽  
The Baltic

Spatially explicit records of fishing activities’ distribution are fundamental for effective marine spatial planning (MSP) because they can help to identify principal fishing areas. However, in numerous case studies, MSP has ignored fishing activities due to data scarcity. The vessel monitoring system (VMS) and the automatic identification system (AIS) are two commonly known technologies used to observe fishing activities. However, both technologies generate data that have several limitations, making them ineffective when used in isolation. Here, we evaluate both datasets’ limitations and strengths, measure the drawbacks of using any single dataset and propose a method for combining both technologies for a more precise estimation of the distribution of fishing activities. Using the Baltic Sea and the North Sea–Celtic Sea regions as case studies, we compare the spatial distribution of fishing effort from International Council for the Exploration of the Seas (ICES) VMS data and global fishing watch AIS data. We show that using either dataset in isolation can lead to a significant underestimation of fishing effort. We also demonstrate that integrating both datasets in an ensemble approach can provide more accurate fisheries information for MSP. Given the rapid expansion of MSP activities globally, our approach can be utilised in data-limited regions to improve cross border spatial planning.

scholarly journals COVID-19 Impact on Global Maritime Mobility

2020 ◽  
Author(s):  
Leonardo M. Millefiori ◽  
Paolo Braca ◽  
Dimitris Zissis ◽  
Giannis Spiliopoulos ◽  
Stefano Marano ◽  
...  
Keyword(s):  
Composite Index ◽  
Global Network ◽  
Automatic Identification ◽  
Identification System ◽  
Shipping Industry ◽  
Mobility Patterns ◽  
Economic Activities ◽  
Mobility Index ◽  
The World ◽  
Containment Measures

Abstract To prevent the outbreak of the Coronavirus disease (COVID-19), numerous countries around the world went into lockdown and imposed unprecedented containment measures. These restrictions progressively produced changes to social behavior and global mobility patterns, evidently disrupting social and economic activities. Here, using maritime traffic data, collected via a global network of Automatic Identification System (AIS) receivers, we analyze the effects that the COVID-19 pandemic and the containment measures had on the shipping industry, which accounts alone for more than 80% of the world trade. We introduce the notion of a “maritime mobility index”, a synthetic composite index, to quantitatively assess ship mobility in a given unit of time. The mobility index calculation used in this study, has a worldwide extent and is based on the computation of Cumulative Navigated Miles (CNM) of all ships reporting their position and navigational status via AIS. We compare 2020 mobility levels to those of previous years assuming that an unchanged growth rate would have been achieved, if not for COVID-19. Following the outbreak, we find an unprecedented drop in maritime mobility, across all categories of commercial shipping. The reduced activity is observable from March to June, when the most severe restrictions were in force, producing a variation of mobility quantified between -5.62% and -13.77% for container ships, between 2.28% and -3.32% for dry bulk, between -0:22% and -9.27% for wet bulk, and between -19.57% and -42.77% for passenger shipping. The presented study is unprecedented for the uniqueness and completeness of the employed AIS dataset, which comprises a trillion AIS messages broadcast worldwide by 50,000 ships, a figure that closely parallels the documented size of the world merchant fleet.

A Feature Encoding Approach and a Cloud Computing Architecture to Map Fishing Activities

2021 ◽  
Author(s):  
A. Galdelli ◽  
A. Mancini ◽  
E. Frontoni ◽  
A. N. Tassetti
Keyword(s):  
Spatial Planning ◽  
Low Cost ◽  
Small Scale ◽  
Automatic Identification ◽  
Identification System ◽  
Marine Spatial Planning ◽  
Fishing Activity ◽  
Feature Encoding ◽  
Encoding Method ◽  
New Policies

Abstract Monitoring fish stocks and fleets’ activities is key for Marine Spatial Planning. In recent years Vessel Monitoring System and Automatic Identification System have been developed for vessels longer than 12 and 15m in length, respectively, while small scale vessels (< 12m in length) remain untracked and largely unregulated, even though they account for 83% of all fishing activity in the Mediterranean Sea. In this paper we present an architecture that makes use of a low-cost LoRa/cellular network to acquire and process positioning data from small scale vessels, and a feature encoding approach that can be easily extended to process and map small scale fisheries. The feature encoding method uses a Markov chain to model transitions between successive behavioural states (e.g., fishing, steaming) of each vessel and classify its activity. The approach is evaluated using k-fold and Leave One Boat Out cross-validations and, in both cases, it results in significant improvements in the classification of fishing activities. The use of a such low-cost and open source technology coupled to artificial intelligence could open up potential for more integrated and transparent platforms to inform coastal resource and fisheries management, and cross-border marine spatial planning. It enables a new monitoring strategy that could effectively include small-scale fleets and support the design of new policies oriented to the optimal use of marine resources.

scholarly journals Trends in Vessel Atmospheric Emissions in the Central Mediterranean over the Last 10 Years and during the COVID-19 Outbreak

2021 ◽  
Vol 9 (7) ◽  
pp. 762
Author(s):  
Martin Saliba ◽  
Francelle Azzopardi ◽  
Rebecca Muscat ◽  
Marvic Grima ◽  
Alexander Smyth ◽  
...  
Keyword(s):  
Air Quality ◽  
Active Volcano ◽  
Assessment Model ◽  
Automatic Identification ◽  
Identification System ◽  
Ship Emissions ◽  
Central Mediterranean ◽  
Traffic Emission ◽  
Ship Traffic ◽  
Gas Measurements

Giordan Lighthouse, located on the island of Gozo in the Malta-Sicily Channel within the central Mediterranean region, is ideally located to study the primary sources of atmospheric pollution. A total of 10 years of data have been accumulated from the reactive gas and greenhouse gas detectors and the aerosol analyzers found at this Global Atmosphere Watch (GAW) regional station. The data has been evaluated, resulting in trends in emissions from shipping recorded within the same region coming to the fore. The other source of emissions that was evident within the recorded data originated from Mt. Etna, located on the island of Sicily and representing the highest active volcano in Europe. The aim of this paper is to investigate the effect of ship emissions on trace gases and aerosol background measurements at Giordan Lighthouse, including the putative influence of COVID-19 on the same emissions. The model used to evaluate ship emissions was the Ship Traffic Emission Assessment Model (STEAM). From trace gas measurements at Giordan Lighthouse, a slowly decreasing trend in sulfur oxide (SOx) and nitrogen oxide (NOx) emissions was noted. To better understand the air quality results obtained, the STEAM model was fed, as an input, an Automatic Identification System (AIS) dataset to describe the vessel activity in the area concerned. This study also investigates the effects of the COVID19 pandemic on marine traffic patterns within the area and any corresponding changes in the air quality. Such an analysis was carried out through the use of SENTINEL 5 data.

Assessing Grounding Frequency using Ship Traffic and Waterway Complexity

2014 ◽  
Vol 68 (1) ◽  
pp. 89-106 ◽  
Author(s):  
Arsham Mazaheri ◽  
Jakub Montewka ◽  
Pentti Kotilainen ◽  
Otto-Ville Edvard Sormunen ◽  
Pentti Kujala
Keyword(s):  
Expert Elicitation ◽  
Traffic Density ◽  
Automatic Identification ◽  
Identification System ◽  
Factors Affecting ◽  
Ship Traffic ◽  
Maritime Traffic ◽  
Statistical Dependency ◽  
Almost All ◽  
Sea Area

Ship traffic is the factor that presents in almost all of the existing grounding risk models. It is considered to be one of the main factors affecting the expected frequency of ship groundings. This is mostly accepted by experts as common sense. However, there is no research available on the actual dependency between ship traffic and grounding accidents. In this paper, we conduct a study aimed at determining the statistical dependency between the density and distribution of traffic, the number and frequency of grounding accidents and the dependency between the complexity of waterways and an actual accident. For this purpose we utilise statistical analysis of maritime traffic, obtained from Automatic Identification System (AIS) data and grounding accidents, enhanced with the expert elicitation techniques delivering the waterway complexity index. The sea area under investigation is the Gulf of Finland. The results show statistical dependency between frequency of grounding and waterway complexity as well as the traffic distribution. However, the study does not reveal any significant dependency between grounding and traffic density.

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