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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.

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Vessel traffic management systems can be employed for environmental management where vessel activity may be of concern. One such location is in San Francisco Bay where a variety of vessel types transit a highly developed urban estuary. We analyzed vessel presence and speed across space and time using vessel data from the Marine Monitor, a vessel tracking system that integrates data from the Automatic Identification System and a marine-radar sensor linked to a high-definition camera. In doing so, we provide data that can inform collision risk to cetaceans who show an increased presence in the Bay and evaluation of the value in incorporating data from multiple sources when observing vessel traffic. We found that ferries traveled the greatest distance of any vessel type. Ferries and other commercial vessels (e.g., cargo and tanker ships and tug boats) traveled consistently in distinct paths while recreational traffic (e.g., motorized recreational craft and sailing vessels) was more dispersed. Large shipping vessels often traveled at speeds greater than 10 kn when transiting the study area, and ferries traveled at speeds greater than 30 kn. We found that distance traveled and speed varied by season for tugs, motorized recreational and sailing vessels. Distance traveled varied across day and night for cargo ships, tugs, and ferries while speed varied between day and night only for ferries. Between weekdays and weekends, distance traveled varied for cargo ships, ferries, and sailing vessels, while speed varied for ferries, motorized recreational craft, and sailing vessels. Radar-detected vessel traffic accounted for 33.9% of the total track distance observed, highlighting the need to include data from multiple vessel tracking systems to fully assess and manage vessel traffic in a densely populated urban estuary.

Ship strikes are a widespread conservation issue for many cetacean species globally. Population level impacts depend on the occurrence and severity of collisions, which may lead to life altering injuries or fatalities. Such impacts are a major concern for large, long-lived, and reproductively slow species like the fin whale. Since 2014, a seasonal feeding aggregation of fin whales has been monitored from February to June off the Catalan coast (Spain), in the northwest Mediterranean Sea. Oceanographical factors influence the occurrence and high density of krill within submarine canyons along the continental shelf, resulting in high whale abundance within a small spatial area. The study area extends 37 km offshore across a 1,944 km2 marine strip situated between the towns of Torredembarra and Castelldefels. This fin whale feeding ground is exposed to high density marine vessel traffic, given its location between the northern Mediterranean shipping lane, which links Barcelona and Tarragona Ports to the Atlantic Ocean and wider Mediterranean Basin. Ship strikes represent the greatest conservation threat for fin whales in the Mediterranean Sea. At least four fin whales have been found dead in Barcelona Port since 1986 due to ship strikes and seven live whales have been documented with injuries in the study area since 2018. Fin whale distribution was mapped with known high-risk marine vessels' (cargo, tanker and passenger vessels) shipping lanes. Vessel density and shipping lanes characterised by speed were considered. Collision risk was estimated monthly based on the predicted fin whale occurrence and traffic density. Several shipping lanes crossed the fin whale feeding habitat every month with an average speed of 15 kn. Cargo vessels displayed the highest ship-strike risk during April, overlapping with the peak of fin whale sightings in the critical feeding area. Slower vessel speeds (8 kn) in waters <200 m depth or along the continental shelf should be implemented al

China, as a major maritime nation, the China Containerized Freight Index (CCFI) serves as an objective reflection of the Chinese shipping market and an important indicator for understanding China's shipping industry globally. The shipping market is a complex ecosystem influenced by various factors, including vessel supply and demand, cargo supply and demand relationships and prices, fuel prices, and competition from substitute and complementary markets. To analyze and study the state of the Chinese shipping market, we selected the CCFI as an indicator and collected data on six factors that may affect the overall shipping market. These factors include "the China Coastal Bulk Freight Index(CCBFI)", "the Baltic Dry Index(BDI)", "the Yangtze River Container Freight Index", "Global: Aluminum (minimum purity of 99.5%, London Metal Exchange (LME) spot price): UK landed price", "Major Ports: Container Throughput", and "Coal Price: US Central Appalachia: Coal Spot Price Index". Then, we constructed an analyticaland predictive framework using Deep Neural Network (DNN), CatBoost regression model, and robust regression model to study the CCFI. Based on the R2 results of the three models, it is evident that DNN provides the best analytical and predictive performance for the CCFI, accurately forecasting its changes. Additionally, the robust regression model indicates that "Global: Aluminum (minimum purity of 99.5%, LME spot price): UK landed price" has the greatest impact on the CCFI. Finally, from a business perspective, we provide some suggestions for China's container shipping industry.

1 - Before the 2020 COVID-19 pandemic, cruise ship tourism had been one of the fastest growing segments of global tourism, presenting a range of potential impacts. At Akaroa Harbour, Aotearoa New Zealand, the number of annual cruise ship visits more than quadrupled following earthquake damage to Ōtautahi Christchurch's Lyttelton Port in 2011. Akaroa Harbour is an area of core use for endangered and endemic HECTOR's dolphins (Cephalorhynchus hectori). Dolphins here are exposed to some of the highest levels of cetacean tourism in Aotearoa New Zealand. 2 - Relationships were examined between growth in cruise ship visits, as well as tours focused specifically on dolphins, and long-term trends in summer distribution of HECTOR's dolphins at Akaroa Harbour, from 2000 to 2020. Core use areas for HECTOR's dolphins within the harbour were quantified via kernel density estimation using data from 2,335 sightings from over 8,000 km of standardized survey effort. Data were allocated into four periods based on varying levels of tourism. 3 - Dolphin habitat preference varied over time, with the greatest change occurring between 2005-2011 and 2012-2015. When comparing these periods, the spatial overlap of core habitat was less than 24%. Dolphin distribution shifted towards the outer harbour after 2011 and has remained relatively consistent since. 4 - The observed shift in distribution coincided with the more than fourfold increase in annual cruise ship visits to Akaroa Harbour. Several pressures related to cruise ship tourism are likely to have influenced habitat preferences of dolphins. Further investigation into causal factors of the observed shift is warranted. 5 - In the wake of the COVID-19 pandemic, the future of cruise ship and wildlife tourism is in flux. Our findings suggest that the future re-development of this industry should follow a precautionary approach, with the onus on industry to provide evidence of sustainability before proceeding.

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