Transmission loss patterns from acoustic harassment and deterrent devices do not always follow geometrical spreading predictions

Author Posting. © The Author(s), 2009. This is the author's version of the work. It is posted here by permission of John Wiley & Sons for personal use, not for redistribution. The definitive version was published in Marine Mammal Science 25 (2009): 53-67, doi:10.1111/j.1748-7692.2008.00243.x.Acoustic harassment and deterrent devices have become increasingly popular mitigation tools for negotiating the impacts of marine mammals on fisheries. The rationale for their variable effectiveness remains unexplained but high variability in the surrounding acoustic field may be relevant. In the present study, the sound fields of one acoustic harassment device and three acoustic deterrent devices were measured at three study sites along the Scandinavian coast. Superimposed onto an overall trend of decreasing sound exposure levels with increasing range were large local variations in sound level for all sources in each of the environments. This variability was likely caused by source directionality, inter-ping source level variation and multi-path interference. Rapid and unpredictable variations in the sound level as a function of range deviated from expectations derived from spherical and cylindrical spreading models and conflicted with the classic concept of concentric zones of increasing disturbance with decreasing range. Under such conditions, animals may encounter difficulties when trying to determine the direction to and location of a sound source, which may complicate or jeopardize avoidance responses.The project was funded by the Swedish Fishermen Association, the Swedish Board of Fisheries, Aage V. Jensen Foundations, Danish Forest and Nature Agency, The Nordic Research Council and the Carlsberg Foundation. Additional logistical support was furnished by the Oticon Foundation and Reson A/S. A.D. Shapiro received financial support from the National Defense Science and Engineering Graduate Fellowship and the WHOI Academic Programs Office. 35

Echolocation activity of harbour porpoises, Phocoena phocoena, shows seasonal artificial reef attraction despite elevated noise levels close to oil and gas platforms

Abstract Harbour porpoises frequently alter their behaviour in response to underwater sound from shipping, seismic surveys, drilling and marine renewables. Less well understood is the response of porpoises to sounds emitted from oil and gas (O&G) platforms during routine operations. The responses are not easily predicted as platforms can act simultaneously and to varying degree as a source of disturbance through noise and attraction through an artificial reef effect with increased prey abundance and diversity. To investigate the presence and feeding behaviour of harbour porpoises around platforms, autonomous acoustic loggers were placed for up to 2 years, at 21 stations 0–25.6 km from the largest platform in the Danish North Sea. Harbour porpoises were detected at all distances year round in two distinct seasonal activity patterns. During July–January, porpoises were attracted to the platform as indicated by high foraging activity within 800 m of the platform. Echolocation activity levels were up to twofold higher than those observed at 3.2–9.6 km from the platform. Similar high echolocation activity was observed 200 m from neighbouring offshore installations located within 15 km, regardless of their size, during May–July. This study shows that porpoises may be attracted to offshore O&G platforms despite confirmed elevated underwater noise and are likely exploiting higher prey abundance in the vicinity of such structures. This is possibly due to increased prey availability created by the combined effect of the artificial reef formed by the underwater structure and the local protected area around all platforms where fishery is banned. Hard substrate and untouched seabed are rare and valuable habitats to many organisms in heavily trawled waters like the North Sea, and the ecological importance of these structures should be considered in the development of decommissioning strategies

residual_data_horizontal_movements

Contains the residuals of the GAM analyses on the horizontal movement data, which was used in the piecewise regression analyses. It is the underlying data used to produce figure 3 in the main article and contains 5 variables: “id” gives the name of the harbor porpoise individual “hour_since_release” is the time (hours) since the individual was released into the water after GPS tagging “residuals_steplength” are the residuals of the Euclidian distance (m) between GPS locations “residuals_speed” are the residuals of the speed (m/sec) between GPS locations “residuals_turing_angle” are the residuals of the turning angle (degrees) between GPS location

Data from: Fine-scale movement responses of free-ranging harbour porpoises to capture, tagging, and short-term noise pulses from a single airgun

Knowledge about the impact of anthropogenic disturbances on the behavioural responses of cetaceans is constrained by lack of data on fine-scale movements of individuals. We equipped five free-ranging harbour porpoises (Phocoena phocoena) with high-resolution location and dive loggers and exposed them to a single 10 in3 underwater airgun producing high-intensity noise pulses (2−3 second intervals) for one minute. All five porpoises responded to capture and tagging with longer, faster and more directed movements as well as with shorter, shallower, less wiggly dives immediately after release, with natural behaviour resumed in ≤24 hours. When we exposed porpoises to airgun pulses at ranges of 420−690 m with noise level estimates of 135−147 dB re 1µPa2s (SEL), one individual displayed rapid and directed movements away from the exposure site and two individuals used shorter and shallower dives compared to natural behaviour immediately after exposure. Noise-induced movement typically lasted for ≤8 hours with an additional 24-hour recovery period until natural behaviour was resumed. The remaining individuals did not show any quantifiable responses to the noise exposure. Changes in natural behaviour following anthropogenic disturbances may reduce feeding opportunities and evaluating potential population-level consequences should be a priority research area

Exposed porpoise dive data

This is the full dataset collected by dive-loggers fitted on four harbor porpoise individuals. Impossible values were removed as described in the article. It is the underlying data used to produce figures in the Supplementary material and contains 6 variables: “id” gives the name of the harbor porpoise individual “datetime” gives the date and time of the start of each dive “dive_duration” gives the difference in time (sec) between the start and end of each dive “max_depth” provides the maximum depth (m) reached during each dive “wiggliness” provides the sum of absolute depth differences (m) while at the bottom of each dive; measure of amount of “wiggling” while at bottom “post_dive_duration” provides the time (sec) spent at the surface after each div

residual_data_vertical_movements

Contains the residuals of the GAM analyses on the vertical movement data, which was used in the piecewise regression analyses. It is the underlying data used to produce figure 4 in the main article and contains 6 variables: “id” gives the name of the harbor porpoise individual “hour_since_release” is the time (hours) since the individual was released into the water after GPS tagging “dive_duration” are the residuals of the difference in time (sec) between the start and end of each dive “max_depth” are the residuals of the maximum depth (m) reached during each dive “wiggliness” are the residuals of the sum of absolute depth differences (m) while at the bottom of each dive “post_dive_duration” are the residuals of the time (sec) spent at the surface after each div

Exposed porpoise GPS data

This is the full dataset collected by GPS tags fitted on four harbor porpoise individuals. Large positional errors were removed as described in the article. The data also contains the calculated horizontal movement parameters and distance variables to produce figure 1 in the main article and the figures in the Supplementary material. The data contains 10 variables: “id” gives the name of the harbor porpoise individual “datetime” gives the date and time of the GPS location columns “x” and “y” are the coordinates of the GPS location in the projection CRS("+proj=utm +zone=32 +ellps=intl +towgs84=-87,-98,-121,0,0,0,0 +units=m +no_defs") “steplength” is the Euclidian distance (m) between GPS locations “speed” is the speed (m/sec) between GPS locations “turing_angle” is the turning angle (degrees) between GPS locations “hour_since_release” is the time (hours) since the individual was released into the water after GPS tagging “dist_to_exposure_site” is the Euclidian distance (m) of the individual porpoise relative to the airgun exposure site “dist_to_release_site” is the Euclidian distance (m) of the individual porpoise relative to the GPS tagging and release sit

R-code

The file contains the R-code for the piecewise linear regression analyses and model selection used to assess capture/tagging and airgun noise-induced movement responses in harbour porpoise

Supporting figures, tables and detailed field protocol from Fine-scale movement responses of free-ranging harbour porpoises to capture, tagging and short-term noise pulses from a single airgun

THE ESM consists of the following: Figure S1. Horizontal movement trajectory of four harbour porpoises exposed to short-term noise pulses from a single airgun noise in the inner Danish waters. A detailed description of harbour porpoise capture, handling, and tagging procedure. Figure S2. Overview of fieldwork protocol. Figure S3. Complete dive profile of four harbour porpoises exposed to airgun pulses in the inner Danish waters. Figure S4. Results of generalized additive mixed model (GAMM) analyses showing predicted effects of hour of the day on three horizontal movement parameters of four harbour porpoises captured in the inner Danish waters and fitted with a GPS-unit. Figure S5. Results of generalized additive mixed model (GAMM) analyses showing predicted effects of hour of the day on four vertical movement parameters of four harbour porpoises captured in the inner Danish waters, and fitted with TDR-units. Figure S6. Overview of the full dataset for each horizontal movement parameters. Figure S7. Overview of the full dataset for each vertical movement parameter. Figure S8: Overview of the temporal autocorrelation in piecewise regression model residuals of each horizontal movement parameter. Figure S9: Overview of the temporal autocorrelation in piecewise regression model residuals of each vertical movement parameter. Table S1: The mean (SE) values of breakpoints (h since release) as estimated by the best piecewise-regression models used to quantify timing of behavioural alterations in horizontal and vertical movement parameters of five harbour porpoises captured and tagged in the inner Danish waters and exposed to short-term noise pulses from a single airgun. Table S2: The coefficient (SE) of each regression line as estimated by the piecewise-regression models to quantify timing of behavioural alterations in horizontal and vertical movement parameters of five harbour porpoises captured and tagged in the inner Danish waters and exposed to short-term noise pulses from a single airgun