The effects of ship noise on marine mammals - a review

viii, 174 hlm, 23 c

Racehorse welfare across a training season

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

Predicting the exposure of diving grey seals to shipping noise.

There is high spatial overlap between grey seals and shipping traffic, and the functional hearing range of grey seals indicates sensitivity to underwater noise emitted by ships. However, there is still very little data regarding 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 a three-dimensional 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-h sound exposure levels (10-1000 Hz) (SELw). Median predicted 24-h SELw was 128 and 142 dB re 1 μPa2s 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

Correction to: Cluster identification, selection, and description in Cluster randomized crossover trials: the PREP-IT trials

An amendment to this paper has been published and can be accessed via the original article

Implementing stakeholder engagement to explore alternative models of consent: An example from the PREP-IT trials

Introduction: Cluster randomized crossover trials are often faced with a dilemma when selecting an optimal model of consent, as the traditional model of obtaining informed consent from participant's before initiating any trial related activities may not be suitable. We describe our experience of engaging patient advisors to identify an optimal model of consent for the PREP-IT trials. This paper also examines surrogate measures of success for the selected model of consent. Methods: The PREP-IT program consists of two multi-center cluster randomized crossover trials that engaged patient advisors to determine an optimal model of consent. Patient advisors and stakeholders met regularly and reached consensus on decisions related to the trial design including the model for consent. Patient advisors provided valuable insight on how key decisions on trial design and conduct would be received by participants and the impact these decisions will have. Results: Patient advisors, together with stakeholders, reviewed the pros and cons and the requirements for the traditional model of consent, deferred consent, and waiver of consent. Collectively, they agreed upon a deferred consent model, in which patients may be approached for consent after their fracture surgery and prior to data collection. The consent rate in PREP-IT is 80.7%, and 0.67% of participants have withdrawn consent for participation. Discussion: Involvement of patient advisors in the development of an optimal model of consent has been successful. Engagement of patient advisors is recommended for other large trials where the traditional model of consent may not be optimal