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Funded by Department of Energy and Climate Change (UK), BES, ASAB, Greenpeace, Environmental Trust, Scottish Natural Heritage, Scottish Government, Whale and Dolphin Conservation, Talisman Energy (UK) Ltd., DECC, Chevron, Natural Environment Research Council Acknowledgments Funding for this work was provided by the Department of Energy and Climate Change (UK). Photo-identification data were collected during a series of grants and contracts from the BES, ASAB, Greenpeace Environmental Trust, Scottish Natural Heritage, Scottish Government, Whale and Dolphin Conservation, Talisman Energy (UK) Ltd., DECC, Chevron, and the Natural Environment Research Council. All survey work was carried out under Scottish Natural Heritage Animal Scientific Licences. The authors have no conflict of interest to declare. We thank Mark Bravington for his helpful advice at the early stages of this work and two anonymous reviewers for their useful comments on the manuscript. ; Peer reviewed ; Publisher PDF

Funding for this work was provided by the Department of Energy and Climate Change (UK). Photo-identification data were collected during a series of grants and contracts from the BES, ASAB, Greenpeace Environmental Trust, Scottish Natural Heritage, Scottish Government, Whale and Dolphin Conservation, Talisman Energy (UK) Ltd., DECC, Chevron, and the Natural Environment Research Council. ; Accurate estimates of fecundity rate are key to population assessments and effectively direct conservation efforts. We present a new approach to estimate fecundity rate based on the probability of a female giving birth, conditional on a previous birth t years ago, from which an expected inter-birth interval (IBI) can be estimated. We use generalized linear mixed-effects models to account for individual and temporal variability and apply the approach to individual reproductive histories of bottlenose dolphins (Tursiops truncatus) from the east coast of Scotland. We estimate a fecundity rate of 0.222 (95% CI = 0.218–0.253) and an expected IBI of 4.49 yr (95% CI = 3.94–4.93 yr). We use simulated data samples to show that the approach produces estimates with a minimum bias of <3%. Simulations are also used to investigate the effect of the most common data-driven biases in the estimates of birth intervals and fecundity rate; we recommend longitudinal studies of at least 10 yr and capture probabilities of at least 0.3 when using this methodology. The approach may be modified to incorporate other parameters of interest and should be applicable to any population with comprehensive data on birth intervals. ; Publisher PDF ; Peer reviewed

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 data sets was provided by Marine Scotland. Collaboration between the University of Aberdeen and Marine Scotland was supported by MarCRF. ; 1. Robust estimates of the density or abundance of cetaceans are required to support a wide range of ecological studies and inform management decisions. Considerable effort has been put into the development of line-transect sampling techniques to obtain estimates of absolute density from aerial- and boat-based visual surveys. Surveys of cetaceans using acoustic loggers or digital cameras provide alternative methods to estimate relative density that have the potential to reduce cost and provide a verifiable record of all detections. However, the ability of these methods to provide reliable estimates of relative density has yet to be established. 2. These methodologies were compared by conducting aerial visual line-transect surveys (n = 10 days) and digital video strip-transect surveys (n = 4 days) in the Moray Firth, Scotland. Simultaneous acoustic data were collected from moored echolocation detectors (C-PODs) at 58 locations across the study site. Density surface modelling (DSM) of visual survey data was used to estimate spatial variation in relative harbour porpoise density on a 4 × 4 km grid. DSM was also performed on the digital survey data, and the resulting model output compared to that from visual survey data. Estimates of relative density from visual surveys around acoustic monitoring sites were compared with several metrics previously used to characterise variation in acoustic detections of echolocation clicks. 3. There was a strong correlation between estimates of relative density from visual surveys and digital video surveys (Spearman's ρ = 0·85). A correction to account for animals missed on the transect line [previously calculated for visual aerial surveys of harbour porpoise in the North Sea was used to convert relative density from the visual surveys to absolute density. This allowed calculation of the first estimate of a proxy for detection probability in digital video surveys, suggesting that 61% (CV = 0·53) of harbour porpoises were detected. There was also a strong correlation between acoustic detections and density with Spearman's ρ = 0·73 for detection positive hours. 4. These results provide confidence in the emerging use of digital video and acoustic surveys for studying the density of small cetaceans and their responses to environmental and anthropogenic change. ; Publisher PDF ; Peer reviewed

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.cf04g ; Peer reviewed ; Publisher PDF

DJFR, GH, VMJ and BM were funded by the UK Department of Energy and Climate Change (DECC) as part of their Offshore Energy Strategic Environmental Assessment programme. DT and GH were also funded by NERC/Defra EBAO NE/J004243/1. ELJ was funded under Scottish Government grant MMSS001/01. This work was also supported by National Capability funding from the Natural Environment Research Council to SMRU (grant no. SMRU1001). Tags and their deployment in the Thames in 2006 and The Wash were funded by DECC. Tags and their deployment in the Thames in 2012 were commissioned by Zoological Society London, with funding from BBC Wildlife Fund and Sita Trust. ; 1. As part of global efforts to reduce dependence on carbon-based energy sources there has been a rapid increase in the installation of renewable energy devices. The installation and operation of these devices can result in conflicts with wildlife. In the marine environment, mammals may avoid wind farms that are under construction or operating. Such avoidance may lead to more time spent travelling or displacement from key habitats. A paucity of data on at-sea movements of marine mammals around wind farms limits our understanding of the nature of their potential impacts. 2. Here, we present the results of a telemetry study on harbour seals Phoca vitulina in The Wash, south-east England, an area where wind farms are being constructed using impact pile driving. We investigated whether seals avoid wind farms during operation, construction in its entirety, or during piling activity. The study was carried out using historical telemetry data collected prior to any wind farm development and telemetry data collected in 2012 during the construction of one wind farm and the operation of another. 3. Within an operational wind farm, there was a close-to-significant increase in seal usage compared to prior to wind farm development. However, the wind farm was at the edge of a large area of increased usage, so the presence of the wind farm was unlikely to be the cause. 4. There was no significant displacement during construction as a whole. However, during piling, seal usage (abundance) was significantly reduced up to 25 km from the piling activity; within 25 km of the centre of the wind farm, there was a 19 to 83% (95% confidence intervals) decrease in usage compared to during breaks in piling, equating to a mean estimated displacement of 440 individuals. This amounts to significant displacement starting from predicted received levels of between 166 and 178 dB re 1 μPa(p·p). Displacement was limited to piling activity; within 2 h of cessation of pile driving, seals were distributed as per the non-piling scenario. 5. Synthesis and applications. Our spatial and temporal quantification of avoidance of wind farms by harbour seals is critical to reduce uncertainty and increase robustness in environmental impact assessments of future developments. Specifically, the results will allow policymakers to produce industry guidance on the likelihood of displacement of seals in response to pile driving; the relationship between sound levels and avoidance rates; and the duration of any avoidance, thus allowing far more accurate environmental assessments to be carried out during the consenting process. Further, our results can be used to inform mitigation strategies in terms of both the sound levels likely to cause displacement and what temporal patterns of piling would minimize the magnitude of the energetic impacts of displacement. ; Publisher PDF ; Peer reviewed