Effects of duty cycle on passive acoustic monitoring metrics: The case of blue whale songs.

Long-term fixed passive acoustic monitoring of cetacean populations is a logistical and technological challenge, often limited by the battery capacity of the autonomous recorders. Depending on the research scope and target species, temporal subsampling of the data may become necessary to extend the deployment period. This study explores the effects of different duty cycles on metrics that describe patterns of seasonal presence, call type richness richness, and daily call rate of three blue whale acoustics populations in the Southern Indian Ocean. Detections of blue whale calls from continuous acoustic data were subsampled with three different duty cycles of 50%, 33%, and 25% within listening periods ranging from 1 min to 6 h. Results show that reducing the percentage of recording time reduces the accuracy of the observed seasonal patterns as well as the estimation of daily call rate and call call type richness. For a specific duty cycle, short listening periods (5-30 min) are preferred to longer listening periods (1-6 h). The effects of subsampling are greater the lower the species' vocal activity or the shorter their periods of presence. These results emphasize the importance of selecting a subsampling scheme adapted to the target species.

Fin whale song evolution in the North Atlantic.

Animal songs can change within and between populations as the result of different evolutionary processes. When these processes include cultural transmission, the social learning of information or behaviours from conspecifics, songs can undergo rapid evolutions because cultural novelties can emerge more frequently than genetic mutations. Understanding these song variations over large temporal and spatial scales can provide insights into the patterns, drivers and limits of song evolution that can ultimately inform on the species' capacity to adapt to rapidly changing acoustic environments. Here, we analysed changes in fin whale (Balaenoptera physalus) songs recorded over two decades across the central and eastern North Atlantic Ocean. We document a rapid replacement of song INIs (inter-note intervals) over just four singing seasons, that co-occurred with hybrid songs (with both INIs), and a clear geographic gradient in the occurrence of different song INIs during the transition period. We also found gradual changes in INIs and note frequencies over more than a decade with fin whales adopting song changes. These results provide evidence of vocal learning in fin whales and reveal patterns of song evolution that raise questions on the limits of song variation in this species.

Numerical modeling and observations of seismo-acoustic waves propagating as modes in a fluid-solid waveguide.

This paper discusses the nature of the low-frequency seismo-acoustic waves generated by submarine earthquakes in the ocean. In a finite-depth homogeneous ocean over a semi-infinite solid crust, the derivation of the acoustic equations shows that waves propagate as modes. The waves propagating with the speed of sound in water (T waves) are preceded by waves with frequencies below the Airy phase. Furthermore, the group speeds of these modes are sensitive to the environmental setting. As a test, we applied the spectral finite-element code SPECFEM2D in a simplified configuration with an ocean layer overlaying a solid crust, and a seismic source below a Gaussian seamount surrounded by a flat seafloor. The simulations confirm that the generated T waves and their precursors follow the theoretical dispersion curves. A more realistic environment with a seismically-layered crust and a sound-speed profile in the ocean is then used to predict the expected acoustic modes. Although noisy, recordings by ocean bottom seismometers from the southwest Indian Ocean show T waves preceded by ultra-low frequency waves, which display two modes comparable to the theoretical ones. They are in good agreement for mode 1, whereas, for mode 0, a slight offset in frequency has yet to be explained.

Detecting, classifying, and counting blue whale calls with Siamese neural networks.

The goal of this project is to use acoustic signatures to detect, classify, and count the calls of four acoustic populations of blue whales so that, ultimately, the conservation status of each population can be better assessed. We used manual annotations from 350 h of audio recordings from the underwater hydrophones in the Indian Ocean to build a deep learning model to detect, classify, and count the calls from four acoustic song types. The method we used was Siamese neural networks (SNN), a class of neural network architectures that are used to find the similarity of the inputs by comparing their feature vectors, finding that they outperformed the more widely used convolutional neural networks (CNN). Specifically, the SNN outperform a CNN with 2% accuracy improvement in population classification and 1.7%-6.4% accuracy improvement in call count estimation for each blue whale population. In addition, even though we treat the call count estimation problem as a classification task and encode the number of calls in each spectrogram as a categorical variable, SNN surprisingly learned the ordinal relationship among them. SNN are robust and are shown here to be an effective way to automatically mine large acoustic datasets for blue whale calls.

Multiple pygmy blue whale acoustic populations in the Indian Ocean: whale song identifies a possible new population.

Blue whales were brought to the edge of extinction by commercial whaling in the twentieth century and their recovery rate in the Southern Hemisphere has been slow; they remain endangered. Blue whales, although the largest animals on Earth, are difficult to study in the Southern Hemisphere, thus their population structure, distribution and migration remain poorly known. Fortunately, blue whales produce powerful and stereotyped songs, which prove an effective clue for monitoring their different 'acoustic populations.' The DGD-Chagos song has been previously reported in the central Indian Ocean. A comparison of this song with the pygmy blue and Omura's whale songs shows that the Chagos song are likely produced by a distinct previously unknown pygmy blue whale population. These songs are a large part of the underwater soundscape in the tropical Indian Ocean and have been so for nearly two decades. Seasonal differences in song detections among our six recording sites suggest that the Chagos whales migrate from the eastern to western central Indian Ocean, around the Chagos Archipelago, then further east, up to the north of Western Australia, and possibly further north, as far as Sri Lanka. The Indian Ocean holds a greater diversity of blue whale populations than thought previously.

Three-dimensional modeling of earthquake generated acoustic waves in the ocean in simplified configurations.

The low-frequency (4-40 Hz) acoustic waves generated by undersea earthquakes are of great importance to monitor the low-level seismic activity associated with seafloor spreading ridges. To better understand the near-source interaction of seismic waves with the seafloor and the resulting generation of low-frequency acoustic waves, the wave propagation in a solid medium (the Earth's crust) and in the overlaying fluid medium (the ocean) were jointly simulated using a three-dimensional (3D) spectral finite-element code (SPECFEM3D). Due to numerical limitations of 3D simulations, the focus was on simple model configurations with a 1 Hz source located below a Gaussian seamount or ridge. The simulated acoustic waves (0-2.5 Hz) propagate as Rayleigh modes and are affected by modal dispersion; their horizontal speed increases away from the source and reaches the sound speed about 140 km away. The amplitude of the generated acoustic waves is affected by the shape of the seafloor topography above the seismic source, as well as their travel times to hydrophones. Consequently, localization of the acoustic sources by trilateration from arrival times may be biased by 3D-effects, and thus the seismic/acoustic conversion zone may not match the epicenter.

Interseismic strain build-up on the submarine North Anatolian Fault offshore Istanbul.

Using offshore geodetic observations, we show that a segment of the North Anatolian Fault in the central Sea of Marmara is locked and therefore accumulating strain. The strain accumulation along this fault segment was previously extrapolated from onshore observations or inferred from the absence of seismicity, but both methods could not distinguish between fully locked or fully creeping fault behavior. A network of acoustic transponders measured crustal deformation with mm-precision on the seafloor for 2.5 years and did not detect any significant fault displacement. Absence of deformation together with sparse seismicity monitored by ocean bottom seismometers indicates complete fault locking to at least 3 km depth and presumably into the crystalline basement. The slip-deficit of at least 4 m since the last known rupture in 1766 is equivalent to an earthquake of magnitude 7.1 to 7.4 in the Sea of Marmara offshore metropolitan Istanbul.

On the reliability of acoustic annotations and automatic detections of Antarctic blue whale calls under different acoustic conditions.

Evaluation of the performance of computer-based algorithms to automatically detect mammalian vocalizations often relies on comparisons between detector outputs and a reference data set, generally obtained by manual annotation of acoustic recordings. To explore the reproducibility of these annotations, inter- and intra-analyst variability in manually annotated Antarctic blue whale (ABW) Z-calls are investigated by two analysts in acoustic data from two ocean basins representing different scenarios in terms of call abundance and background noise. Manual annotations exhibit strong inter- and intra-analyst variability, with less than 50% agreement between analysts. This variability is mainly caused by the difficulty of reliably and reproducibly distinguishing single calls in an ABW chorus made of overlaying distant calls. Furthermore, the performance of two automated detectors, based on spectrogram correlation or subspace-detection strategy, is evaluated by comparing detector output to a "conservative" manually annotated reference data set, which comprises only analysts' matching events. This study highlights the need for a standardized approach for human annotations and automatic detections, including a quantitative description of their performance, to improve the comparability of acoustic data, which is particularly relevant in the context of collaborative approaches in collecting and analyzing large passive acoustic data sets.

Identification of two potential whale calls in the southern Indian Ocean, and their geographic and seasonal occurrence.

Since passive acoustic monitoring is widely used, unidentified acoustic signals from marine mammals are commonly reported. The signal characteristics and emission patterns are the main clues to identify the possible sources. In this study, the authors describe two previously unidentified sounds, recorded at up to five widely-spaced sites (30 × 30 degree area) in the southern Indian Ocean, in 2007 and between 2010 and 2015. The first reported signal (M-call) consists of a single tonal unit near 22 Hz and lasting about 10 s, repeated with an interval longer than 2 min. This signal is only detected in 2007. The second signal (P-call) is also a tonal unit of 10 s, repeated every 160 s, but at a frequency near 27 Hz. Its yearly number increased greatly between 2007 and 2010, and moderately since then. Based on their characteristics and seasonal patterns, this study shows that both signals are clearly distinct from any known calls of blue whale subspecies and populations dwelling in the southern Indian Ocean. However, they display similarities with blue whale vocalizations. More particularly, the P-call can be mistaken for the first tonal unit of the Antarctic blue whale Z-call.

Seasonal and Diel Vocalization Patterns of Antarctic Blue Whale (Balaenoptera musculus intermedia) in the Southern Indian Ocean: A Multi-Year and Multi-Site Study.

Passive acoustic monitoring is an efficient way to provide insights on the ecology of large whales. This approach allows for long-term and species-specific monitoring over large areas. In this study, we examined six years (2010 to 2015) of continuous acoustic recordings at up to seven different locations in the Central and Southern Indian Basin to assess the peak periods of presence, seasonality and migration movements of Antarctic blue whales (Balaenoptera musculus intermedia). An automated method is used to detect the Antarctic blue whale stereotyped call, known as Z-call. Detection results are analyzed in terms of distribution, seasonal presence and diel pattern of emission at each site. Z-calls are detected year-round at each site, except for one located in the equatorial Indian Ocean, and display highly seasonal distribution. This seasonality is stable across years for every site, but varies between sites. Z-calls are mainly detected during autumn and spring at the subantarctic locations, suggesting that these sites are on the Antarctic blue whale migration routes, and mostly during winter at the subtropical sites. In addition to these seasonal trends, there is a significant diel pattern in Z-call emission, with more Z-calls in daytime than in nighttime. This diel pattern may be related to the blue whale feeding ecology.

Automated detection of Antarctic blue whale calls.

This paper addresses the problem of automated detection of Z-calls emitted by Antarctic blue whales (B. m. intermedia). The proposed solution is based on a subspace detector of sigmoidal-frequency signals with unknown time-varying amplitude. This detection strategy takes into account frequency variations of blue whale calls as well as the presence of other transient sounds that can interfere with Z-calls (such as airguns or other whale calls). The proposed method has been tested on more than 105 h of acoustic data containing about 2200 Z-calls (as found by an experienced human operator). This method is shown to have a correct-detection rate of up to more than 15% better than the extensible bioacoustic tool package, a spectrogram-based correlation detector commonly used to study blue whales. Because the proposed method relies on subspace detection, it does not suffer from some drawbacks of correlation-based detectors. In particular, it does not require the choice of an a priori fixed and subjective template. The analytic expression of the detection performance is also derived, which provides crucial information for higher level analyses such as animal density estimation from acoustic data. Finally, the detection threshold automatically adapts to the soundscape in order not to violate a user-specified false alarm rate.

Low-frequency sound level in the Southern Indian Ocean.

This study presents long-term statistics on the ambient sound in the Southern Indian Ocean basin based on 2 years of data collected on six widely distributed autonomous hydrophones from 47°S to 4°S and 53°E to 83°E. Daily mean power spectra (10-100 Hz) were analyzed in order to identify the main sound sources and their space and time variability. Periodic signals are principally associated with the seasonal presence of three types of blue whales and fin whales whose signatures are easily identified at specific frequencies. In the low frequencies, occurrence of winter lows and summer highs in the ambient noise levels are well correlated with iceberg volume variations at the southern latitudes, suggesting that icebergs are a major sound source, seasonally contributing to the ambient noise, even at tropical latitudes (26°S). The anthropogenic contribution to the noise spectrum is limited. Shipping sounds are only present north and west of the study area in the vicinity of major traffic lanes. Acoustic recordings from the southern sites may thus be representative of the pristine ambient noise in the Indian Ocean.

A numerical model for ocean ultra-low frequency noise: wave-generated acoustic-gravity and Rayleigh modes.

The generation of ultra-low frequency acoustic noise (0.1 to 1 Hz) by the nonlinear interaction of ocean surface gravity waves is well established. More controversial are the quantitative theories that attempt to predict the recorded noise levels and their variability. Here a single theoretical framework is used to predict the noise level associated with propagating pseudo-Rayleigh modes and evanescent acoustic-gravity modes. The latter are dominant only within 200 m from the sea surface, in shallow or deep water. At depths larger than 500 m, the comparison of a numerical noise model with hydrophone records from two open-ocean sites near Hawaii and the Kerguelen islands reveal: (a) Deep ocean acoustic noise at frequencies 0.1 to 1 Hz is consistent with the Rayleigh wave theory, in which the presence of the ocean bottom amplifies the noise by 10 to 20 dB; (b) in agreement with previous results, the local maxima in the noise spectrum support the theoretical prediction for the vertical structure of acoustic modes; and (c) noise level and variability are well predicted for frequencies up to 0.4 Hz. Above 0.6 Hz, the model results are less accurate, probably due to the poor estimation of the directional properties of wind-waves with frequencies higher than 0.3 Hz.

T-wave generation and propagation: a comparison between data and spectral element modeling.

T-waves are underwater acoustic waves generated by earthquakes. Modeling of their generation and propagation is a challenging problem. Using a spectral element code-SPECFEM2D, this paper presents the first realistic simulations of T-waves taking into account major aspects of this phenomenon: The radiation pattern of the source, the propagation of seismic waves in the crust, the seismic to acoustic conversion on a non-planar seafloor, and the propagation of acoustic waves in the water column. The simulated signals are compared with data from the mid-Atlantic Ridge recorded by an array of hydrophones. The crust/water interface is defined by the seafloor bathymetry. Different combinations of water sound-speed profiles and sub-seafloor seismic velocities, and frequency content of the source are tested. The relative amplitudes, main arrival-times, and durations of simulated T-phases are in good agreement with the observed data; differences in the spectrograms and early arrivals are likely due to too simplistic source signals and environmental model. These examples demonstrate the abilities of the SPECFEM2D code for modeling earthquake generated T-waves.

Seasonal and geographic variation of southern blue whale subspecies in the Indian Ocean.

Understanding the seasonal movements and distribution patterns of migratory species over ocean basin scales is vital for appropriate conservation and management measures. However, assessing populations over remote regions is challenging, particularly if they are rare. Blue whales (Balaenoptera musculus spp) are an endangered species found in the Southern and Indian Oceans. Here two recognized subspecies of blue whales and, based on passive acoustic monitoring, four "acoustic populations" occur. Three of these are pygmy blue whale (B.m. brevicauda) populations while the fourth is the Antarctic blue whale (B.m. intermedia). Past whaling catches have dramatically reduced their numbers but recent acoustic recordings show that these oceans are still important habitat for blue whales. Presently little is known about the seasonal movements and degree of overlap of these four populations, particularly in the central Indian Ocean. We examined the geographic and seasonal occurrence of different blue whale acoustic populations using one year of passive acoustic recording from three sites located at different latitudes in the Indian Ocean. The vocalizations of the different blue whale subspecies and acoustic populations were recorded seasonally in different regions. For some call types and locations, there was spatial and temporal overlap, particularly between Antarctic and different pygmy blue whale acoustic populations. Except on the southernmost hydrophone, all three pygmy blue whale acoustic populations were found at different sites or during different seasons, which further suggests that these populations are generally geographically distinct. This unusual blue whale diversity in sub-Antarctic and sub-tropical waters indicates the importance of the area for blue whales in these former whaling grounds.