Habitat use of a coastal delphinid population investigated using passive acoustic monitoring

Funding: Marine Scotland Science and the Marine Alliance for Science and Technology for Scotland (MASTS) pooling initiative, and their support is gratefully acknowledged. MASTS is funded by the Scottish Funding Council (grant reference HR09011) and contributing institutions.1. The population of bottlenose dolphins in eastern Scotland has undergone significant range expansion since the 1990s, when a Special Area of Conservation was established for the population. 2. Distribution of this population is well described within areas of its range where intensive work has been carried out, such as the inner Moray Firth, St Andrews Bay and the Tay estuary area. However, elsewhere in their range, habitat use is less well understood. 3. In this study, a large‐scale and long‐term passive acoustic array was used to gain a better understanding of bottlenose dolphin habitat use in eastern Scottish waters, complementing and augmenting existing visual surveys. 4. Data from the array were analysed using a three‐stage approach. First, acoustic occupancy results were reported; second, temporal trends were modelled; and third, a spatial–temporal‐habitat model of acoustic occupancy was created. 5. Results from the acoustic occupancy are in agreement with visual studies that found that areas near known foraging locations were consistently occupied. Results from the temporal trend analysis were inconclusive. Habitat modelling showed that, throughout their range, bottlenose dolphins are most likely to be detected closer to shore, and at a constant distance from shore, in deeper water.PostprintPeer reviewe

Echolocation detections and digital video surveys provide reliable estimates of the relative density of harbour porpoises

Acknowledgements We would like to thank Erik Rexstad and Rob Williams for useful reviews of this manuscript. The collection of visual and acoustic data was funded by the UK Department of Energy & Climate Change, the Scottish Government, Collaborative Offshore Wind Research into the Environment (COWRIE) and Oil & Gas UK. Digital aerial surveys were funded by Moray Offshore Renewables Ltd and additional funding for analysis of the combined datasets was provided by Marine Scotland. Collaboration between the University of Aberdeen and Marine Scotland was supported by MarCRF. We thank colleagues at the University of Aberdeen, Moray First Marine, NERI, Hi-Def Aerial Surveying Ltd and Ravenair for essential support in the field, particularly Tim Barton, Bill Ruck, Rasmus Nielson and Dave Rutter. Thanks also to Andy Webb, David Borchers, Len Thomas, Kelly McLeod, David L. Miller, Dinara Sadykova and Thomas Cornulier for advice on survey design and statistical approache. Data Accessibility Data are available from the Dryad Digital Repository: http://dx.doi.org/10.5061/dryad.cf04gPeer reviewedPublisher PD

Spatiotemporal variation in harbor porpoise distribution and foraging across a landscape of fear

Funding information: Marine Alliance for Science and Technology for Scotland; Marine Scotland Science; University of AberdeenPeer reviewedPublisher PD

Comparing distribution of harbour porpoise using Generalized Additive Models and hierarchical Bayesian models with Integrated Nested Laplace Approximation

Open Access via Elsevier agreement Acknowledgments We thank colleagues at the University of Aberdeen, Moray First Marine, NERI, Hi-Def Aerial Surveying Ltd and Ravenair for essential support in the field, particularly Tim Barton, Bill Ruck, Rasmus Nielson and Dave Rutter. L.D.W. was supported by the Marine Alliance for Science and Technology for Scotland (MASTS), the University of Aberdeen and Marine Scotland Science. Collaboration between the University of Aberdeen and Marine Scotland was supported by the Marine Collaboration Research Forum (MarCRF). Digital aerial surveys in 2010 were funded by Moray Offshore Renewables Ltd and 2014 by Marine Scotland. Additional funding for analysis of the combined datasets was provided by Marine Scotland. Collaboration between the University of Aberdeen and Marine Scotland was supported by MarCRF.Peer reviewedPublisher PD

Categorizing click trains to increase taxonomic precision in echolocation click loggers

L.R. and K.J.P. were supported by Marine Scotland Science and the Marine Alliance for Science and Technology for Scotland (MASTS) pooling initiative and their support is gratefully acknowledged. MASTS is funded by the Scottish Funding Council (grant reference HR09011) and contributing institutions.Passive acoustic monitoring is an efficient way to study acoustically active animals but species identification remains a major challenge. C-PODs are popular logging devices that automatically detect odontocete echolocation clicks. However, the accompanying analysis software does not distinguish between delphinid species. Click train features logged by C-PODs were compared to frequency spectra from adjacently deployed continuous recorders. A generalized additive model was then used to categorize C-POD click trains into three groups: broadband click trains, produced by bottlenose dolphin (Tursiops truncatus) or common dolphin (Delphinus delphis), frequency-banded click trains, produced by Risso's (Grampus griseus) or white beaked dolphins (Lagenorhynchus albirostris), and unknown click trains. Incorrect categorization rates for broadband and frequency banded clicks were 0.02 (SD 0.01), but only 30% of the click trains met the categorization threshold. To increase the proportion of categorized click trains, model predictions were pooled within acoustic encounters and a likelihood ratio threshold was used to categorize encounters. This increased the proportion of the click trains meeting either the broadband or frequency banded categorization threshold to 98%. Predicted species distribution at the 30 study sites matched well to visual sighting records from the region.PostprintPeer reviewe

Spatiotemporal variation in harbor porpoise distribution and foraging across a landscape of fear

Understanding spatiotemporally varying animal distributions can inform ecological understanding of species' behavior (e.g., foraging and predator/prey interactions) and support development of management and conservation measures. Data from an array of echolocation‐click detectors (C‐PODs) were analyzed using Bayesian spatiotemporal modeling to investigate spatial and temporal variation in occurrence and foraging activity of harbor porpoises (Phocoena phocoena) and how this variation was influenced by daylight and presence of bottlenose dolphins (Tursiops truncatus). The probability of occurrence of porpoises was highest on an offshore sandbank, where the proportion of detections with foraging clicks was relatively low. The porpoises' overall distribution shifted throughout the summer and autumn, likely influenced by seasonal prey availability. Probability of porpoise occurrence was lowest in areas close to the coast, where dolphin detections were highest and declined prior to dolphin detection, leading potentially to avoidance of spatiotemporal overlap between porpoises and dolphins. Increased understanding of porpoises' seasonal distribution, key foraging areas, and their relationship with competitors can shed light on management options and potential interactions with offshore industries

Validation of the Bluebelle Wound Healing questionnaire (WHQ) for assessment of surgical site infection in primary surgical wounds after hospital discharge

Background Accurate assessment of surgical‐site infection (SSI) is crucial for surveillance and research. Self‐reporting patient measures are needed because current SSI tools are limited for assessing patients after leaving hospital. The Bluebelle Wound Healing Questionnaire (WHQ) was developed for patient or observer completion; this study tested its acceptability, scale structure, reliability and validity in patients with closed primary wounds after abdominal surgery. Methods Patients completed the WHQ (self‐assessment) within 30 days after leaving hospital and returned it by post. Healthcare professionals completed the WHQ (observer assessment) by telephone or face‐to‐face. Questionnaire response rates and patient acceptability were assessed. Factor analysis and Cronbach's α examined scale structure and internal consistency. Test–retest and self‐ versus observer reliability assessments were performed. Sensitivity and specificity for SSI discrimination against a face‐to‐face reference diagnosis (using Centers for Disease Control and Prevention criteria) were examined. Results Some 561 of 792 self‐assessments (70·8 per cent) and 597 of 791 observer assessments (75·5 per cent) were completed, with few missing data or problems reported. Data supported a single‐scale structure with strong internal consistency (α greater than 0·8). Reliability between test–retest and self‐ versus observer assessments was good (κ 0·6 or above for the majority of items). Sensitivity and specificity for SSI discrimination was high (area under the receiver operating characteristic (ROC) curve 0·91). Conclusion The Bluebelle WHQ is acceptable, reliable and valid with a single‐scale structure for postdischarge patient or observer assessment of SSI in closed primary wounds

The impact of a team-based intervention on the lifestyle risk factor management practices of community nurses: outcomes of the community nursing SNAP trial

BackgroundLifestyle risk factors like smoking, nutrition, alcohol consumption, and physical inactivity (SNAP) are the main behavioural risk factors for chronic disease. Primary health care is an appropriate setting to address these risk factors in individuals. Generalist community health nurses (GCHNs) are uniquely placed to provide lifestyle interventions as they see clients in their homes over a period of time. The aim of the paper is to examine the impact of a service-level intervention on the risk factor management practices of GCHNs.MethodsThe trial used a quasi-experimental design involving four generalist community nursing services in NSW, Australia. The services were randomly allocated to either an intervention group or control group. Nurses in the intervention group were provided with training and support in the provision of brief lifestyle assessments and interventions. The control group provided usual care. A sample of 129 GCHNs completed surveys at baseline, 6 and 12 months to examine changes in their practices and levels of confidence related to the management of SNAP risk factors. Six semi-structured interviews and four focus groups were conducted among the intervention group to explore the feasibility of incorporating the intervention into everyday practice.ResultsNurses in the intervention group became more confident in assessment and intervention over the three time points compared to their control group peers. Nurses in the intervention group reported assessing physical activity, weight and nutrition more frequently, as well as providing more brief interventions for physical activity, weight management and smoking cessation. There was little change in referral rates except for an improvement in weight management related referrals. Nurses’ perception of the importance of ‘client and system-related’ barriers to risk factor management diminished over time.ConclusionsThis study shows that the intervention was associated with positive changes in self-reported lifestyle risk factor management practices of GCHNs. Barriers to referral remained. The service model needs to be adapted to sustain these changes and enhance referral

The NightLife study — the clinical and cost-effectiveness of thrice-weekly, extended, in-centre nocturnal haemodialysis versus daytime haemodialysis using a mixed methods approach: study protocol for a randomised controlled trial

Background: In-centre nocturnal haemodialysis (INHD) offers extended-hours haemodialysis, 6 to 8 h thrice-weekly overnight, with the support of dialysis specialist nurses. There is increasing observational data demonstrating potential benefits of INHD on health-related quality of life (HRQoL). There is a lack of randomised controlled trial (RCT) data to confirm these benefits and assess safety. Methods: The NightLife study is a pragmatic, two-arm, multicentre RCT comparing the impact of 6 months INHD to conventional haemodialysis (thrice-weekly daytime in-centre haemodialysis, 3.5–5 h per session). The primary outcome is the total score from the Kidney Disease Quality of Life tool at 6 months. Secondary outcomes include sleep and cognitive function, measures of safety, adherence to dialysis and impact on clinical parameters. There is an embedded Process Evaluation to assess implementation, health economic modelling and a QuinteT Recruitment Intervention to understand factors that influence recruitment and retention. Adults (≥ 18 years old) who have been established on haemodialysis for > 3 months are eligible to participate. Discussion: There are 68,000 adults in the UK that need kidney replacement therapy (KRT), with in-centre haemodialysis the treatment modality for over a third of cases. HRQoL is an independent predictor of hospitalisation and mortality in individuals on maintenance dialysis. Haemodialysis is associated with poor HRQoL in comparison to the general population. INHD has the potential to improve HRQoL. Vigorous RCT evidence of effectiveness is lacking. The NightLife study is an essential step in the understanding of dialysis therapies and will guide patient-centred decisions regarding KRT in the future. Trial registration: Trial registration number: ISRCTN87042063. Registered: 14/07/2020

Validated shipping noise maps of the Northeast Atlantic

Underwater noise pollution from shipping is globally pervasive and has a range of adverse impacts on species which depend on sound, including marine mammals, sea turtles, fish, and many invertebrates. International bodies including United Nations agencies, the Arctic Council, and the European Union are beginning to address the issue at the policy level, but better evidence is needed to map levels of underwater noise pollution and the potential benefits of management measures such as ship-quieting regulations. Crucially, corroboration of noise maps with field measurements is presently lacking, which undermines confidence in their application to policymaking. We construct a computational model of underwater noise levels in the Northeast Atlantic using Automatic Identification System (AIS) ship-tracking data, wind speed data, and other environmental parameters, and validate this model against field measurements at 4 sites in the North Sea. Overall, model predictions of the median sound level were within ±3 dB for 93% of the field measurements for one-third octave frequency bands in the range 125 Hz-5 kHz. Areas with median noise levels exceeding 120 dB re 1 μPa and 20 dB above modelled natural background sound were predicted to occur in the Dover Strait, the Norwegian trench, near to several major ports, and around offshore infrastructure sites in the North Sea. To our knowledge, this is the first study to quantitatively validate large-scale modelled noise maps with field measurements at multiple sites. Further validation will increase confidence in deeper waters and during winter months. Our results highlight areas where anthropogenic pressure from shipping noise is greatest and will inform the management of shipping noise in the Northeast Atlantic. The good agreement between measurements and model gives confidence that models of shipping noise can be used to inform future policy and management decisions to address shipping noise pollution