Exclusion of tidal influence on ambient sound measurements.

Growing concern about the impacts of anthropogenic noise on marine life has led to a global increase in the number of acoustic monitoring programmes aiming to quantify underwater soundscapes. However, low-frequency measurements in coastal sites may be affected by flow noise that is not actually present in the environment, but is caused by tidal flow turbulence around the hydrophone. At present, there is no standard way of removing this contaminating noise. This study presents an approach to exclude tidal influences (flow noise and other tidal-related acoustic self-noise) on ambient sound measurements, using data recorded at ten Scottish coastal sites between 2013 and 2017, and with a focus on the 63 and 125 Hz 1/3-octave bands. The annual ambient sound pressure levels (SPL) of the full and "tidal influence excluded" datasets of the three most tidally affected sites were compared against hypothetical noise thresholds. For the 63 Hz 1/3-octave band, results revealed: Site-specific patterns in the amount of data excluded (28.2%-89.2%), decreases in SPL (0.7-8.5 dB), and differences in the percentage of time that noise thresholds were exceeded. The described approach may serve as a standardised way of excluding tidal influence on soundscape descriptors.

Categorizing click trains to increase taxonomic precision in echolocation click loggers.

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.

Variation in harbour porpoise activity in response to seismic survey noise.

Animals exposed to anthropogenic disturbance make trade-offs between perceived risk and the cost of leaving disturbed areas. Impact assessments tend to focus on overt behavioural responses leading to displacement, but trade-offs may also impact individual energy budgets through reduced foraging performance. Previous studies found no evidence for broad-scale displacement of harbour porpoises exposed to impulse noise from a 10 day two-dimensional seismic survey. Here, we used an array of passive acoustic loggers coupled with calibrated noise measurements to test whether the seismic survey influenced the activity patterns of porpoises remaining in the area. We showed that the probability of recording a buzz declined by 15% in the ensonified area and was positively related to distance from the source vessel. We also estimated received levels at the hydrophones and characterized the noise response curve. Our results demonstrate how environmental impact assessments can be developed to assess more subtle effects of noise disturbance on activity patterns and foraging efficiency.

Short-term disturbance by a commercial two-dimensional seismic survey does not lead to long-term displacement of harbour porpoises.

Assessments of the impact of offshore energy developments are constrained because it is not known whether fine-scale behavioural responses to noise lead to broader-scale displacement of protected small cetaceans. We used passive acoustic monitoring and digital aerial surveys to study changes in the occurrence of harbour porpoises across a 2000 km(2) study area during a commercial two-dimensional seismic survey in the North Sea. Acoustic and visual data provided evidence of group responses to airgun noise from the 470 cu inch array over ranges of 5-10 km, at received peak-to-peak sound pressure levels of 165-172 dB re 1 µPa and sound exposure levels (SELs) of 145-151 dB re 1 µPa(2) s(-1). However, animals were typically detected again at affected sites within a few hours, and the level of response declined through the 10 day survey. Overall, acoustic detections decreased significantly during the survey period in the impact area compared with a control area, but this effect was small in relation to natural variation. These results demonstrate that prolonged seismic survey noise did not lead to broader-scale displacement into suboptimal or higher-risk habitats, and suggest that impact assessments should focus on sublethal effects resulting from changes in foraging performance of animals within affected sites.

Predictions from harbor porpoise habitat association models are confirmed by long-term passive acoustic monitoring.

Survey based habitat association models provide good spatial coverage, but only a snapshot in time of a species' occurrence in a particular area. A habitat association model for harbor porpoises was created using data from five visual surveys of the Moray Firth, Scotland. Its predictions were tested over broader temporal scales using data from static passive acoustic loggers, deployed in two consecutive years. Predictions of relative abundance (individuals per kilometer of survey transect) were obtained for each 4 km × 4 km grid cell, and compared with the median number of hours per day that porpoises were acoustically detected in those cells. There was a significant, but weak, correlation between predicted relative abundance and acoustic estimates of occurrence, but this was stronger when predictions with high standard errors were omitted. When grid cells were grouped into those with low, medium, and high predicted relative abundance, there were similarly significant differences in acoustic detections, indicating that porpoises were acoustically detected more often in cells where the habitat model predicted higher numbers. The integration of acoustic and visual data added value to the interpretation of results from each, allowing validation of patterns in relative abundance recorded during snapshot visual surveys over longer time scales.

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.

Seasonal and diel acoustic presence of North Atlantic minke whales in the North Sea.

Despite frequent records from other parts of the North Atlantic, minke whales have never been acoustically recorded in the North Sea. This study investigated the detectability of pulse trains previously associated with this species in other regions, in acoustic data from ten sites along the east coast of Scotland. Since preliminary results confirmed pulse train presence, subsequently, an automated detector was applied to these data to record the seasonal and diel presence of minke whale pulse trains. Minke whales were detected from May to November, with most detections occurring in June, July and October. No acoustic detections were made in December, January or in the month of April, whilst no data were available for February and March. This pattern of acoustic presence supports available visual data and suggested an absence of minke whales from the study area during winter. Minke whale acoustic presence showed a statistically significant diel pattern, with a detection peak during night time. This study established the acoustic detectability of minke whales in the North Sea and highlights the potential of using passive acoustic monitoring to study the seasonal presence and spatial distribution of minke whales in the North Sea and wider Northeast Atlantic.

Underwater noise levels in UK waters.

Underwater noise from human activities appears to be rising, with ramifications for acoustically sensitive marine organisms and the functioning of marine ecosystems. Policymakers are beginning to address the risk of ecological impact, but are constrained by a lack of data on current and historic noise levels. Here, we present the first nationally coordinated effort to quantify underwater noise levels, in support of UK policy objectives under the EU Marine Strategy Framework Directive (MSFD). Field measurements were made during 2013-2014 at twelve sites around the UK. Median noise levels ranged from 81.5-95.5 dB re 1 µPa for one-third octave bands from 63-500 Hz. Noise exposure varied considerably, with little anthropogenic influence at the Celtic Sea site, to several North Sea sites with persistent vessel noise. Comparison of acoustic metrics found that the RMS level (conventionally used to represent the mean) was highly skewed by outliers, exceeding the 97th percentile at some frequencies. We conclude that environmental indicators of anthropogenic noise should instead use percentiles, to ensure statistical robustness. Power analysis indicated that at least three decades of continuous monitoring would be required to detect trends of similar magnitude to historic rises in noise levels observed in the Northeast Pacific.

Assessing environmental impacts of offshore wind farms: lessons learned and recommendations for the future.

Offshore wind power provides a valuable source of renewable energy that can help reduce carbon emissions. Technological advances are allowing higher capacity turbines to be installed and in deeper water, but there is still much that is unknown about the effects on the environment. Here we describe the lessons learned based on the recent literature and our experience with assessing impacts of offshore wind developments on marine mammals and seabirds, and make recommendations for future monitoring and assessment as interest in offshore wind energy grows around the world. The four key lessons learned that we discuss are: 1) Identifying the area over which biological effects may occur to inform baseline data collection and determining the connectivity between key populations and proposed wind energy sites, 2) The need to put impacts into a population level context to determine whether they are biologically significant, 3) Measuring responses to wind farm construction and operation to determine disturbance effects and avoidance responses, and 4) Learn from other industries to inform risk assessments and the effectiveness of mitigation measures. As the number and size of offshore wind developments increases, there will be a growing need to consider the population level consequences and cumulative impacts of these activities on marine species. Strategically targeted data collection and modeling aimed at answering questions for the consenting process will also allow regulators to make decisions based on the best available information, and achieve a balance between climate change targets and environmental legislation.