The number of marine watercraft is on the rise-from private boats in coastal areas to commercial ships crossing oceans. A concomitant increase in underwater noise has been reported in several regions around the globe. Given the important role sound plays in the life functions of marine mammals, research on the potential effects of vessel noise has grown-in particular since the year 2000. We provide an overview of this literature, showing that studies have been patchy in terms of their coverage of species, habitats, vessel types, and types of impact investigated. The documented effects include behavioral and acoustic responses, auditory masking, and stress. We identify knowledge gaps: There appears a bias to more easily accessible species (i.e., bottlenose dolphins and humpback whales), whereas there is a paucity of literature addressing vessel noise impacts on river dolphins, even though some of these species experience chronic noise from boats. Similarly, little is known about the potential effects of ship noise on pelagic and deep-diving marine mammals, even though ship noise is focused in a downward direction, reaching great depth at little acoustic loss and potentially coupling into sound propagation channels in which sound may transmit over long ranges. We explain the fundamental concepts involved in the generation and propagation of vessel noise and point out common problems with both physics and biology: Recordings of ship noise might be affected by unidentified artifacts, and noise exposure can be both under-and over-estimated by tens of decibel if the local sound propagation conditions are not considered. The lack of anthropogenic (e.g., different vessel types), environmental (e.g., different sea states or presence/absence of prey), and biological (e.g., different demographics) controls is a common problem, as is a lack of understanding what constitutes the 'normal' range of behaviors. Last but not least, the biological significance of observed responses is mostly unknown. Moving forward, standards on study design, data analysis, and reporting are badly needed so that results are comparable (across space and time) and so that data can be synthesized to address the grand unknowns: the role of context and the consequences of chronic exposures.

Underwater noise pollution from shipping is a significant ecological concern. Acoustic propagation models are essential to predict noise levels and inform management activities to safeguard ecosystems. However, these models can be computationally expensive to execute. To increase computational efficiency, ships are spatially partitioned using grids but the cell size is often arbitrary. This work presents an adaptive grid where cell size varies with distance from the receiver to increase computational efficiency and accuracy. For a case study in the Celtic Sea, the adaptive grid represented a 2 to 5 fold increase in computational efficiency in August and December respectively, compared to a high resolution 1 km grid. A 5 km grid increased computational efficiency 5 fold again. However, over the first 25 km, the 5 km grid produced errors up to 13.8 dB compared to the 1 km grid, whereas, the adaptive grid generated errors of less than 0.5 dB.

There is high spatial overlap between grey seals and shipping traffic, and their functional hearing range indicates they are sensitive to underwater noise emitted by ships. However, there is still very little data about the exposure of grey seals to shipping noise, constraining effective policy decisions. Particularly, there are few predictions that consider the at-sea movement of seals. Consequently, this study aimed to predict the exposure of adult grey seals and pups to shipping noise along their threedimensional movement track, and assess the influence of shipping characteristics on sound exposure levels. Using ship location data, a ship source model and the acoustic propagation model RAMSurf, this study estimated weighted 24-hr sound exposure levels (10-1000 Hz) (SEL w ). Median predicted 24-hr SEL w was 128 dB re 1µP a 2 s and 142 dB re 1µP a 2 s for the pups and adults respectively. The predicted exposure of seals to shipping noise did not exceed best evidence thresholds for temporary threshold shift. Exposure was mediated by the number of ships, ship source level, the distance between seals and ships, and the at-sea behaviour of the seals. The results can inform regulatory planning related to anthropogenic pressures on seal populations.a This paper is part of a special issue on The Effects of Noise on Aquatic Life.

The development of exertional heat illness (EHI) is a health, welfare and performance concern for racehorses. However, there has been limited multivariable assessment of the possible risk factors for EHI in racehorses, despite such information being vital for regulators to effectively manage the condition. Consequently, this study aimed to identify the risk factors associated with the occurrence of EHI in Thoroughbred racehorses and assess the ability of the risk factor model to predict the occurrence of EHI in racehorses to assist in early identification. Runners at British racecourses recorded in the British Horseracing Authority database between 1st July 2010 and 30th April 2018 were used to model the probability that a horse would present with EHI as a function of a suite of environmental, horse level and race level factors. EHI was reported in 0.1% of runners. Race distance, wet bulb globe temperature, preceding 5-day temperature average, occurrence of a previous EHI incident, going, year and race off time were identified as risk factors for EHI. The model performed better than chance in classifying incidents with a mean area under the receiver operating characteristic curve score of 0.884 (SD = 0.02) but had a large number of false positives. The results provide vital evidence for industry on the need to provide appropriate cool down facilities, identify horses that have repeated EHI incidents for early intervention, and collect new data streams such as on course wet bulb globe temperature measurements. The results are especially relevant as the sport is operating in a changing climate and must mitigate against more extreme and longer spells of hot weather.

Racehorse welfare is gaining increasing public attention, however scientific evidence in this area is lacking. In order to develop a better understanding of racehorse welfare, it must be measured and monitored. This is the first study to assess racehorse welfare using scientific objective methods across a training season. The aim of this study was threefold, firstly to investigate welfare measures which could be used in the first welfare assessment protocol for racehorses. Secondly, to understand the effect that a racing and training season had on individual racehorses and thirdly to identify risk factors for both good and poor welfare. Thirteen racehorse training yards were visited at the beginning and the peak of the racing season in England. Behavioral observations along with individual environmental and animal-based welfare measures were carried out on 353 horses in 13 training yards selected for variability. In our sample the horses were generally in good physical health: 94% of horses recorded as an ideal body condition score, no horses had signs of hoof neglect and 77.7% had no nasal discharge. The overall prevalence of external Mouth Corner Lesions was 12.9% and was significantly higher for Flat racing than Jump racing horses. The majority of horses (67.5%) showed positive horse human interactions. When stabled 54.1% horses had physical social contact and nasal discharge was not associated with increased physical contact. The training season significantly affected Human Reactivity Tests, Horse Grimace Scale scores and time spent resting and feeding. A total of 14.5% of horses displayed stereotypic behavior on at least two occasions. Horses with windows in their stables spent more time surveying their surroundings. Overall, in this population of racehorses, horses spent around a third of their daytime feeding (33.7%) followed by time spent standing resting (22.6%). The welfare assessment protocol used in this study is suitable for use in industry to collect welfare data on racehorses.