Pay-walled
Article
2019
Renewable and Sustainable Energy Reviews
Pine, Matthew K., Schmitt Pál, Culloch Ross M., Lieber Lilian, and Kregting Louise T.
The deployment of tidal energy arrays is gaining momentum to provide marine renewable energy (MRE) to the global market. However, there are concerns over the potential impacts underwater noise emissions from operational devices may have on marine fauna. Auditory masking (the interference of important biological signals by anthropogenic noise) is a highly pervasive impact to marine fauna. We used a relatively new approach to evaluate the effects of noise from operational tidal energy devices on the listening space of marine mammals. Here, listening space reductions (LSR) for harbour porpoises (Phocoena phocoena) and harbour seals (Phoca vitulina) were assessed in winter and summer for two tidal energy devices of different designs. Results demonstrated that LSR was influenced by type of turbine, species, and season. For instance, LSRs for harbour seals were in excess of 80% within 60 m, whilst for harbour porpoises they were in excess of 55% within 10 m of the devices. For both species, LSRs were highest during winter, characterised by low ambient noise conditions. These findings highlight the importance of assessing masking over seasons, as masking effects are highly influenced by ambient noise conditions. Understanding the natural variation within seasons is also particularly relevant for tidal turbine noise assessments as devices are typically situated in highly dynamic environments. Since masking effects occur at the lower level of behavioural impacts in marine mammals, assessing the spatial extent of masking as part of environmental impact assessments is recommended. The listening space formula, which is largely based on measurable environmental factors (device and ambient noise), is transferable to any MRE device, or arrays, for any species (for which an audiogram can be assumed) and therefore provides an effective method to better inform MRE pre- and post-consenting processes.
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