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Most species of whales are vulnerable to vessel collisions, and the probability of lethality increases logistically with vessel speed. An Automatic Identification System (AIS) can provide valuable vessel activity data, but terrestrial-based AIS has a limited spatial range. As the need for open ocean monitoring increases, AIS broadcasts relayed over earth-orbiting satellites, satellite AIS (SAIS), provides a method for expanding the range of AIS broadcast reception. We used SAIS data from 2013 and 2014 to calculate vessel density and speed over ground around the coast of Washington state in the northwestern United States. Nearby shipping lanes connecting the Ports of Seattle, Tacoma, Portland, and in Canada, Vancouver, have the greatest density of vessel traffic arriving and departing. Knowledge of shipping activity is important in this area due to the nearby presence of NOAA designated Cetacean Density and Distribution Working Group's Biologically Important Areas (BIA) for large whale species vulnerable to vessel collisions. We quantified density and speed for each vessel type that transits through BIA's. We found that cargo and tanker vessels traveled the farthest distance at the greatest speeds. As ship-strike risk assessments have traditionally relied on terrestrial AIS, we explored issues in the application of SAIS data. Temporal gaps in SAIS data led to a resulting systematic underestimation of vessel speed in calculated speed over ground. However, SAIS can be helpful in documenting minimum vessel speeds across large geographic areas and across national boundaries, especially beyond the reach of terrestrial AIS receivers. SAIS data can also be useful in examining vessel density at broad scales and could be used to assess basin-wide open ocean routes. Future use of additional satellite platforms with AIS receivers and technological advances will help rectify this issue and improve data coverage and quality.

The Automatic Identification System (AIS) is a real-time network of transmitters and receivers that allow vessel movements to be broadcast, tracked, and recorded. Though traditionally used for real-time maritime applications related to keeping track of vessel traffic for collision avoidance, there is increasing interest in using AIS data and the AIS platform for maritime safety planning, resource management, and weather forecasting. AIS data are being made tractable for alternative non-real-time applications like determining trends and patterns in vessel traffic and helping to prioritize where modern bathymetric surveys are needed to ensure safe maritime transit. The AIS is also being used for widespread transmission of critical environmental conditions information, such as sea state and weather, to mariners, forecasters, and emergency response providers. Several pilot projects are underway that demonstrate the capacity and promise of AIS data and the AIS platform to serve multiple purposes, providing overall maritime domain awareness while maintaining its most important objective of tracking vessels to aid safe, secure, efficient and environmentally sound maritime operations.

Invasive species are spreading into northern latitudes and threatening food and water security. Alaska's aquatic environments support some of the world's most productive wild salmon fisheries. Yet, the influx of invasive species increases the strain on the ecosystems, cultures, and economies that depend on these fisheries. Especially worrisome is the potential transmission of aquatic invasive species (AIS) such as zebra mussels (Dreissena polymorpha), quagga mussels (Dreissena bugensis), or Asian clams (Corbicula fluminea) through the trade and traffic of recreational watercraft from AIS-infested regions. Since neither invasive mussels nor clams have been found in Alaska waters, there is opportunity to prevent introductions of invasive molluscs and avoid catastrophic impacts to some of the world's last intact ecosystems. To date little data are available to guide human response to reducing the risk of transmitting freshwater AIS that affect critical natal habitat for Alaska's salmon fisheries. This study triangulated existing data on watercraft registrations and inspections with key informant interviews to establish a first estimate of introduction rates for watercraft-related AIS. Results show that at least 129 used and motorized watercraft are estimated to enter Alaska annually from dreissenid-infested regions with an estimated 47 reaching Alaska freshwater uninspected. These watercraft are entering Alaska through both land and marine pathways. The study points toward the need for a collaborative response among state, federal, tribal, and local agencies, and watercraft owners to devise effective prevention. Response opportunities include inspections and decontaminations at critical control points, and an increased outreach and education campaign for watercraft users. Policy implications for salmon fisheries are discussed should AIS become established in Alaska. Also, the costs, and the long-term sustainability of a prevention program are discussed.

The growing concerns about the negative effects caused by whale watching on wild cetacean populations are evincing the need to measure whale watching effort more precisely. The current alternatives do not provide sufficient information or imply time-consuming and staff-intensive tasks that limit their effectiveness to establish the maximum carrying capacity for this tourist activity. A methodology based on big data analysis, using Automatic Identification System (AIS) messages can provide valuable vessel activity information, which is necessary to estimate whale watching effort in areas with cetacean populations. We used AIS data to automatically detect whale watching operations and quantify whale watching effort with high spatial and temporal resolution in the Canary Islands off the west African coast. The results obtained in this study are very encouraging, proving that the methodology can estimate seasonal and annual trends in the whale watching effort. The methodology has also proved to be effective in providing detailed spatial information about the whale watching effort, which makes an interesting tool to manage spatial regulations and enforce exclusion zones. The widespread use of AIS devices in maritime navigation provides an enormous potential to easily extend this methodology to other regions worldwide. Any public strategy aimed at the sustainable use of marine resources should enhance the use of this kind of information technologies, collecting and archiving detailed information on the activity of all the vessels, especially in marine protected areas.

The Panama Canal Authority has been monitoring AIS messages and have encountered that many vessels were transmitting incomplete or incorrect data.

AI System Tested by Tokyo Bay Vessel Traffic Controllers.

Watch: AI-Project Successfully Saves Fuel On Stena Line Vessels.

Artificial Intelligence (AI) will enable ships navigating in polar ocean conditions to be more efficient using a new route planning tool created by British Antarctic Survey (BAS) researchers. The tool aims to reduce carbon emissions and optimise science.

The escalating greenhouse gas (GHG) emissions from maritime trade present a serious environmental and biological threat. With increasing emission reduction initiatives, such as the European Union's incorporation of the maritime sector into the emissions trading system, both challenges and opportunities emerge for maritime transport and associated industries. To address these concerns, this study presents a model specifically designed for estimating and projecting the spatiotemporal GHG emission inventory of ships, particularly when dealing with incomplete automatic identification system datasets. In the computational aspect of the model, various data processing techniques are employed to rectify inaccuracies arising from incomplete or erroneous AIS data, including big data cleaning, ship trajectory aggregation, multi-source spatiotemporal data fusion and missing data complementation. Utilizing a bottom-up ship dynamic approach, the model generates a high-resolution GHG emission inventory. This inventory contains key attributes such as the types of ships emitting GHGs, the locations of these emissions, the time periods during which emissions occur, and emissions. For predictive analytics, the model utilizes temporal fusion transformers equipped with the attention mechanism to accurately forecast the critical emission parameters, including emission locations, time frames, and quantities. Focusing on the sea area around Tianjin port-a region characterized by high shipping activity-this study achieves fine-grained emission source tracking via detailed emission inventory calculations. Moreover, the prediction model achieves a promising loss function of approximately 0.15 under the optimal parameter configuration, obtaining a better result than recurrent neural network (RNN) and long short-term memory network (LSTM) in the comparative experiments. The proposed method allows for a comprehensive understanding of emission patterns across diverse vessel types under vari

With technology advancing so quickly, it can be hard to keep up with the choice of calling-for-help gadgets. Here we outline the options, so you'll be able to tell your AIS from your PLB.

Researchers develop an autonomous ship guidance system using probabilistic modeling and AI

A voluntary commercial vessel slowdown trial was conducted through 16 nm of shipping lanes overlapping critical habitat of at-risk southern resident killer whales (SRKW) in the Salish Sea. From August 7 to October 6, 2017, the trial requested piloted vessels to slow to 11 knots speed-through-water. Analysis of AIS vessel tracking data showed that 350 of 951 (37%) piloted transits achieved this target speed, 421 of 951 (44%) transits achieved speeds within one knot of this target (i.e., ≤12 knots), and 55% achieved speeds ≤ 13 knots. Slowdown results were compared to 'Baseline' noise of the same region, matched across lunar months. A local hydrophone listening station in Lime Kiln State Park, 2.3 km from the shipping lane, recorded 1.2 dB reductions in median broadband noise (10-100,000 Hz, rms) compared to the Baseline period, despite longer transit. The median reduction was 2.5 dB when filtering only for periods when commercial vessels were within 6 km radius of Lime Kiln. The reductions were highest in the 1st decade band (-3.1 dB, 10-100 Hz) and lowest in the 4th decade band (-0.3 dB reduction, 10-100 kHz). A regional vessel noise model predicted noise for a range of traffic volume and vessel speed scenarios for a 1133 km2 'Slowdown region' containing the 16 nm of shipping lanes. A temporally and spatially explicit simulation model evaluated the changes in traffic volume and speed on SRKW in their foraging habitat within this Slowdown region. The model tracked the number and magnitude of noise-exposure events that impacted each of 78 (simulated) SRKW across different traffic scenarios. These disturbance metrics were simplified to a cumulative effect termed 'potential lost foraging time' that corresponded to the sum of disturbance events described by assumptions of time that whales could not forage due to noise disturbance. The model predicted that the voluntary Slowdown trial achieved 22% reduction in 'potential lost foraging time' for SRK

Low-frequency sound from large vessels is a major, global source of ocean noise that can interfere with acoustic communication for a variety of marine animals. Changes in vessel activity provide opportunities to quantify relationships between vessel traffic levels and soundscape conditions in biologically important habitats. Using continuous deep-sea (890 m) recordings acquired ∼20 km (closest point of approach) from offshore shipping lanes, we observed reduction of low-frequency noise within Monterey Bay National Marine Sanctuary (California, United States) associated with changes in vessel traffic during the onset of the COVID-19 pandemic. Acoustic modeling shows that the recording site receives low-frequency vessel noise primarily from the regional shipping lanes rather than via the Sound Fixing and Ranging (SOFAR) channel. Monthly geometric means and percentiles of spectrum levels in the one-third octave band centered at 63 Hz during 2020 were compared with those from the same months of 2018-2019. Spectrum levels were persistently and significantly lower during February through July 2020, although a partial rebound in ambient noise levels was indicated by July. Mean spectrum levels during 2020 were more than 1 dB re 1 μPa2 Hz-1 below those of a previous year during 4 months. The lowest spectrum levels, in June 2020, were as much as 1.9 (mean) and 2.4 (25% exceedance level) dB re 1 μPa2 Hz-1 below levels of previous years. Spectrum levels during 2020 were significantly correlated with large-vessel total gross tonnage derived from economic data, summed across all California ports (r = 0.81, p < 0.05; adjusted r2 = 0.58). They were more highly correlated with regional presence of large vessels, quantified from Automatic Identification System (AIS) vessel tracking data weighted according to vessel speed and modeled acoustic transmission loss (r = 0.92, p < 0.01; adjusted r2 = 0.81). Within the 3-year study period, February-June 2020 exhibited persistentl

Over the past two years, researchers at Fisheries and Oceans Canada have been running an acoustic monitoring project at multiple study sites throughout Nova Scotia, Canada to investigate baleen whale presence and levels of underwater noise. At the onset of the COVID-19 pandemic, a passive acoustic monitor (PAM) was in place in the study site located in the approaches to Halifax Harbor, a major Canadian port. This provided a unique opportunity to determine if changes in vessel noise levels occurred after pandemic restrictions were put in place. To investigate this, we analyzed and compared acoustic data collected from March 28 to April 28 and August 6 to October 22 in both 2019 and 2020. We also investigated possible changes in vessel traffic from February 1 through April 28 and July 1 through July 28 in 2019 and 2020 using terrestrial-based automatic identification system (AIS) data provided by the Canadian Coast Guard and cargo information provided by the Port of Halifax. The acoustic data were analyzed in 1/3 octave frequency bands. For the 89.1-112 Hz frequency band, we found an 8.4 dB increase in the daily minimum sound pressure level (SPL) in April 2020 compared to April 2019 due the presence of a large crane vessel stationed near the mooring site. For the period of August to October, we found an approximately 1.7 dB reduction in the same metric from 2019 to 2020. The most noticeable change in vessel composition was the dramatic decrease in the number and occurrence of pleasure craft in July 2020 compared to the same period in 2019. While this analysis looked at only a single PAM and a limited amount of data, we observed changes in sound levels in the frequency band known to be associated with shipping as well as changes in vessel traffic; we conclude that these observed changes may be related to pandemic restrictions.

Vessel strikes have been documented around the world and frequently figure as a top human cause of large whale mortality. The shipping lanes in the Santa Barbara Channel, California and nearby waters have some of the highest predicted whale mortality from vessel strikes in the United States waters of the eastern Pacific. Beginning in 2007, National Oceanographic and Atmospheric Administration requested voluntary vessel speed reductions (VSRs) for vessels greater than 300 GT traveling in the Santa Barbara Channel shipping routes to decrease whale mortality from ship strikes. We employed a ship strike model using whale density data and automatic identification system (AIS) vessel data to estimate mortality under several management scenarios. To assess the effect of the VSR on strike mortality, we bootstrapped speeds from vessels greater than 19 m long that transited when no VSR was in place. Finally, we calculated the predicted mortality for hypothetical cooperation scenarios by artificially adding speed caps post-hoc to real vessel transits. For 2012-2018, we estimated that in our study area on average during summer/fall (June-November) 8.9 blue, 4.6 humpback, and 9.7 fin whales were killed from ship strikes each year (13-26% greater than previously estimated). We evaluated winter/spring (January-April) humpback mortality for the first time, resulting in an estimate of 5.7 deaths on average per year. Poor cooperation with the VSR led to low (5% maximum) to no reductions in the estimated number of strike mortalities. Evaluating potential scenarios showed that if 95% cooperation occurred in the lanes, whale deaths there would decrease by 22-26%. Adding VSRs with similar cooperation levels at the northern end of the Santa Barbara Channel and south of Channel Islands National Marine Sanctuary could decrease estimated strike mortalities in those areas by 30%. If VSRs were added and cooperation reached 95% there and in the lanes, we estimate a 21-29% decrease i

As underwater noise from ship traffic increases, profound effects on the marine environment highlight the need for improved mitigation measures. One measure, reduction in ship speed, has been shown to be one of the key drivers in reducing sound source levels of vessels. In 2017, a study began to assess the impacts of increasing commercial shipping traffic on sperm whales in Northwest Providence Channel, northern Bahamas, an international trade route that primarily serves the southeast US. Ship data were collected from an Automatic Identification System (AIS) station combined with recordings from an acoustic recorder to measure underwater sound levels and to detect the presence of sperm whales. Here we analyze a subset of these data to opportunistically investigate potential changes in ship traffic before and during the COVID-19 pandemic. These data span one calendar year from October 2019 to October 2020. A pre-COVID-19 dataset of 121 days, from a recorder approximately 2 km from the shipping route was compared to a 134-day dataset collected during COVID-19 from the same site, comprising 2900 and 3181 ten-minute recordings, respectively. A dramatic decrease in ocean noise levels concurrent with changes in shipping activity occurred during the pandemic. The mean pre-COVID-19 power density level in the 111-140 Hz 1/3-octave band was 88.81 dB re 1 μPa (range 81.38-100.90) and decreased to 84.27 dB re 1 μPa (range 78.60-99.51) during COVID-19, equating to a 41% reduction in sound pressure levels (SPL). After differences in seasonal changes in wind speed were accounted for, SPL decreased during the pandemic by 3.98 dB (37%). The most notable changes in ship activity were significantly reduced vessel speeds for all ship types and fewer ships using the area during the pandemic. Vessel speed was highly correlated to SPL and the only ship-based variable that predicted SPLs. Despite the opportunistic nature [i.e., not a standard before-after-control-impact (BACI) stud