Alec J. Duncan

The marine soundscape, whether in coastal areas or the deepest ocean, in the tropics or at the poles, contains a myriad of sounds. Sounds may be grouped by their origin into geophony (e.g., wind, precipitation, waves, earthquakes, volcanoes, and ice), biophony (e.g., invertebrates, fishes, and marine mammals), and anthropophony (e.g., port construction, mineral and hydrocarbon exploration and production, renewable energy installation, and shipping). This chapter gives a brief overview of the geophony and biophony, and then focuses on the anthropophony. The sounds of boats and ships of various types, marine seismic surveys, drilling, dredging, pile driving, windfarms, geotechnical site investigations, sonars, echosounders, explosions, and acoustic mitigation devices are presented, along with their characteristic source levels and spectra. Approaches to modeling, in particular, the sounds emitted by ships, seismic airguns, and pile driving are discussed.

The 2019 crash of an F35 fighter aircraft off the east coast of Japan was detected at a range of approximately 3000 km by a hydroacoustic station of the Comprehensive Nuclear Test Ban Treaty Organisation’s International Monitoring System. In this paper we compare the acoustic propagation conditions relating to that detection to those relating to the crash of Malaysian Airlines flight MH370 in the Indian Ocean in 2014 with a view to reassessing the likelihood that acoustic signals detected on a similar hydroacoustic station could have been related to the loss of MH370. Possible differences in source levels due to different assumptions about impact parameters are also considered. Despite several extensive searches, the location of the wreckage of MH370 remains unknown.

This chapter presents an introduction to acoustics and explains the basic quantities and concepts relevant to terrestrial and aquatic animal bioacoustics. Specific terminology that is introduced includes sound pressure, sound exposure, particle velocity, sound speed, longitudinal and transverse waves, frequency-modulation, amplitude-modulation, decibel, source level, near-field, far-field, frequency weighting, power spectral density, and one-third octave band level, amongst others. The chapter then introduces basic signal sampling and processing concepts such as sampling frequency, Nyquist frequency, aliasing, windowing, and Fourier transform. The chapter concludes with an introductory treatise of sound localization and tracking, including time difference of arrival and beamforming.

Sound propagation under water is a complex process. Sound does not propagate along straight-line transmission paths. Rather, it reflects, refracts, and diffracts. It scatters off rough surfaces (such as the sea surface and the seafloor) and off reflectors within the water column (e.g., gas bubbles, fish swim bladders, and suspended particles). It is transmitted into the seafloor and partially lost from the water. It is converted into heat by exciting molecular vibrations. There are common misconceptions about sound propagation in water, such as “low-frequency sound does not propagate in shallow water,” “over hard seafloors, all sound is reflected, leading to cylindrical spreading,” and “over soft seafloors, sound propagates spherically.” This chapter aims to remove common misconceptions and empowers the reader to comprehend sound propagation phenomena in a range of environments and appreciate the limitations of widely used sound propagation models. The chapter begins by deriving the sonar equation for a number of scenarios, including animal acoustic communication, communication masking by noise, and acoustic surveying of animals. It introduces the concept of the layered ocean, presenting temperature, salinity, and resulting sound speed profiles. These are needed to develop the most common concepts of sound propagation under water: ray tracing and normal modes. This chapter explains Snell’s law, reflection and transmission coefficients, and Lloyd’s mirror. It provides an overview of publicly available sound propagation software (including wavenumber integration and parabolic equation models). It concludes with a few practical examples of modeling propagation loss for whale song and a seismic airgun array.

Sea noise collected over 2003 to 2017 from the Perth Canyon, Western Australia was analysed for variation in the South Eastern Indian Ocean pygmy blue whale song structure. The primary song-types were: P3, a three unit phrase (I, II and III) repeated with an inter-song interval (ISI) of 170–194 s; P2, a phrase consisting of only units II & III repeated every 84–96 s; and P1 with a phrase consisting of only unit II repeated every 45–49 s. The different ISI values were approximate multiples of each other within a season. When comparing data from each season, across seasons, the ISI value for each song increased significantly through time (all fits had p << 0.001), at 0.30 s/Year (95%CI 0.217–0.383), 0.8 s/Year (95%CI 0.655–1.025) and 1.73 s/Year (95%CI 1.264–2.196) for the P1, P2 and P3 songs respectively. The proportions of each song-type averaged at 21.5, 24.2 and 56% for P1, P2 and P3 occurrence respectively and these ratios could vary by up to ± 8% (95% CI) amongst years. On some occasions animals changed the P3 ISI to be significantly shorter (120–160 s) or longer (220–280 s). Hybrid song patterns occurred where animals combined multiple phrase types into a repeated song. In recent years whales introduced further complexity by splitting song units. This variability of song-type and proportions implies abundance measure for this whale sub population based on song detection needs to factor in trends in song variability to make data comparable between seasons. Further, such variability in song production by a sub population of pygmy blue whales raises questions as to the stability of the song types that are used to delineate populations. The high level of song variability may be driven by an increasing number of background whale callers creating ‘noise’ and so forcing animals to alter song in order to ‘stand out’ amongst the crowd.

Naturally constrained environments like bays and lakes are frequently used for water sports activities. While the sound of motorized vessels is rather well understood, non-motorized activities have received less investigation. Ten water sports activities (swimming backstroke, breaststroke, butterfly, and freestyle; snorkelling with fins; kicking a boogie board with fins; paddling with alternating or simultaneous arms while lying on a surfboard; scuba-diving; kayaking and jumping into the water) were recorded in a controlled yet even more constrained environment: an Olympic-sized pool. Activities that occurred at the surface involved repeatedly piercing the surface and hence creating the bubble clouds which were the strongest sound generators. Received levels were 110–131 dB re 1μPa (10–16,000 Hz) for all of the activities at the closest point of approach (1 m). All activities produced a characteristic spectro-temporal pattern in all the quantities measured (sound pressure, particle displacement, velocity, and acceleration) by which they could be identified. Applicability of the results to security monitoring of pools, performance assessments of professional or competitive swimmers, and studies of the distances at which humans may be detectable by marine animals in the sea will be discussed.