Heriberto A. Garcia

Vast assembly of vocal marine mammals from diverse species on fish spawning ground

Observing marine mammal (MM) populations continuously in time and space over the immense ocean areas they inhabit is challenging but essential for gathering an unambiguous record of their distribution, as well as understanding their behaviour and interaction with prey species. Here we use passive ocean acoustic waveguide remote sensing (POAWRS) in an important North Atlantic feeding ground to instantaneously detect, localize and classify MM vocalizations from diverse species over an approximately 100,000 km2 region. More than eight species of vocal MMs are found to spatially converge on fish spawning areas containing massive densely populated herring shoals at night-time and diffuse herring distributions during daytime. We find the vocal MMs divide the enormous fish prey field into species-specific foraging areas with varying degrees of spatial overlap, maintained for at least two weeks of the herring spawning period. The recorded vocalization rates are diel (24 h)-dependent for all MM species, with some significantly more vocal at night and others more vocal during the day. The four key baleen whale species of the region: fin, humpback, blue and minke have vocalization rate trends that are highly correlated to trends in fish shoaling density and to each other over the diel cycle. These results reveal the temporospatial dynamics of combined multi-species MM foraging activities in the vicinity of an extensive fish prey field that forms a massive ecological hotspot, and would be unattainable with conventional methodologies. Understanding MM behaviour and distributions is essential for management of marine ecosystems and for accessing anthropogenic impacts on these protected marine species.

Vocalization Source Level Distributions and Pulse Compression Gains of Diverse Baleen Whale Species in the Gulf of Maine

The vocalization source level distributions and pulse compression gains are estimated for four distinct baleen whale species in the Gulf of Maine: fin, sei, minke and an unidentified baleen whale species. The vocalizations were received on a large-aperture densely-sampled coherent hydrophone array system useful for monitoring marine mammals over instantaneous wide areas via the passive ocean acoustic waveguide remote sensing technique. For each baleen whale species, between 125 and over 1400 measured vocalizations with significantly high Signal-to-Noise Ratios (SNR > 10 dB) after coherent beamforming and localized with high accuracies (<10% localization errors) over ranges spanning roughly 1 km–30 km are included in the analysis. The whale vocalization received pressure levels are corrected for broadband transmission losses modeled using a calibrated parabolic equation-based acoustic propagation model for a random range-dependent ocean waveguide. The whale vocalization source level distributions are characterized by the following means and standard deviations, in units of dB re 1 μ Pa at 1 m: 181.9 ± 5.2 for fin whale 20-Hz pulses, 173.5 ± 3.2 for sei whale downsweep chirps, 177.7 ± 5.4 for minke whale pulse trains and 169.6 ± 3.5 for the unidentified baleen whale species downsweep calls. The broadband vocalization equivalent pulse-compression gains are found to be 2.5 ± 1.1 for fin whale 20-Hz pulses, 24 ± 10 for the unidentified baleen whale species downsweep calls and 69 ± 23 for sei whale downsweep chirps. These pulse compression gains are found to be roughly proportional to the inter-pulse intervals of the vocalizations, which are 11 ± 5 s for fin whale 20-Hz pulses, 29 ± 18 for the unidentified baleen whale species downsweep calls and 52 ± 33 for sei whale downsweep chirps. The source level distributions and pulse compression gains are essential for determining signal-to-noise ratios and hence detection regions for baleen whale vocalizations received passively on underwater acoustic sensing systems, as well as for assessing communication ranges in baleen whales.

Continental Shelf-Scale Passive Acoustic Detection and Characterization of Diesel-Electric Ships Using a Coherent Hydrophone Array

The passive ocean acoustic waveguide remote sensing (POAWRS) technique is employed to detect and characterize the underwater sound radiated from three scientific research and fishing vessels received at long ranges on a large-aperture densely-sampled horizontal coherent hydrophone array. The sounds radiated from the research vessel (RV) Delaware II in the Gulf of Maine, and the RV Johan Hjort and the fishing vessel (FV) Artus in the Norwegian Sea are found to be dominated by distinct narrowband tonals and cyclostationary signals in the 150 Hz to 2000 Hz frequency range. The source levels of these signals are estimated by correcting the received pressure levels for transmission losses modeled using a calibrated parabolic equation-based acoustic propagation model for random range-dependent ocean waveguides. The probability of the detection region for the most prominent signal radiated by each ship is estimated and shown to extend over areas spanning roughly 200 km in diameter when employing a coherent hydrophone array. The current standard procedure for quantifying ship-radiated sound source levels via one-third octave bandwidth intensity averaging smoothes over the prominent tonals radiated by a ship that can stand 10 to 30 dB above the local broadband level, which may lead to inaccurate or incorrect assessments of the impact of ship-radiated sound.

Temporal-spatial and source level distributions for a repertoire of fin whale vocalizations in the Norwegian Sea observed with a coherent hydrophone array

The vocalizations of the fin whale are detected, characterized and localized over instantaneous wide areas of the Norwegian and Barents Seas using a large-aperture densely-sampled coherent hydrohone array via the passive ocean acoustic waveguide remote sensing (POAWRS) technique from observations in late winter to early spring 2014. The fin whale vocalizations are comprised of their characteristic 20 Hz pulses, interspersed by 130 Hz upsweeps, less abundant 30-100 Hz downsweep chirps and 18-19 Hz centered backbeats. The time-frequency characteristics of these vocalization types and their diel occurrence rate time-series are quantified in three distinct regions of the Norwegian Sea, off the coasts of Alesund, Lofoten, and the Northern Finnmark. Their vocalization rates are a factor of roughly 5 times and 17 times larger respectively for the 20 Hz and 130 Hz centered vocalizations off Northern Finnmark than the other regions. The vocalization rate spatial density distributions, source level distributions an...

Passive acoustic detection of surface ships at ranges exceeding 100 kilometers and mechanisms for ship noise generation

The passive ocean acoustic waveguide remote sensing technique is employed to detect diesel-electric vehicles at ranges exceeding 100 kilometers. The underwater sounds radiated from these vessels are received at long ranges on a large-aperture densely-sampled horizontal coherent hydrophone array. The source levels of these signals are estimated by correcting the received pressure levels for transmission losses modeled using a calibrated parabolic equation-based acoustic propagation model for random range-dependent ocean waveguides. Here we find spectra of ship-radiated sound that is extremely dynamic containing both broadband signals and narrowband tonals at discrete frequencies with source levels that vary depending on ship conditions. We track a vessel with increasing range to find range dependence on broadband signals at close range and tonal signals at long range. Machinery noise generated from engines, propellers, flow noise and other cavitation sources are found to vary depending on ship conditions and are unique to each vessel. Our analysis indicates these vessels can be instantaneously tracked over wide areas spanning more than 300 kilometers in diameter.

Identification of fin whale 20-Hz pulses and other vocalizations from passive monitoring with a coherent hydrophone array

A large variety of sound sources in the ocean, including biological, geophysical and man-made activities can be simultaneously monitored over instantaneous continental-shelf scale regions via the passive ocean acoustic waveguide remote sensing (POAWRS) technique by employing a large-aperture densely-sampled coherent hydrophone array. Millions of acoustic signals received on the POAWRS system per day can make it challenging to identify individual sound sources. An automated classification system is necessary to enable sound sources to be recognized. Here each detected acoustic signal is represented by an amplitude weighted pitch track which describes its fundamental frequency-time and amplitude variation. Multiple features are extracted from the pitch track including mean, minimum and maximum frequencies, bandwidth, signal duration, frequency-time slope and curvature, as well as several amplitude weighted features. A large training data set of fin whale 20-Hz pulses and other vocalizations are gathered after manual inspection and labeling. Next, multiple classifiers including logistic regression and decision tree are built and tested for identifying the fin whale 20-Hz pulses and other vocalizations from the enormous amounts of acoustic signals detected per day. The performance of the classifiers are evaluated and comparedA large variety of sound sources in the ocean, including biological, geophysical and man-made activities can be simultaneously monitored over instantaneous continental-shelf scale regions via the passive ocean acoustic waveguide remote sensing (POAWRS) technique by employing a large-aperture densely-sampled coherent hydrophone array. Millions of acoustic signals received on the POAWRS system per day can make it challenging to identify individual sound sources. An automated classification system is necessary to enable sound sources to be recognized. Here each detected acoustic signal is represented by an amplitude weighted pitch track which describes its fundamental frequency-time and amplitude variation. Multiple features are extracted from the pitch track including mean, minimum and maximum frequencies, bandwidth, signal duration, frequency-time slope and curvature, as well as several amplitude weighted features. A large training data set of fin whale 20-Hz pulses and other vocalizations are gathered aft...

Comparing neural networks with conventional classifiers for fin whale vocalizations in beamformed spectrograms of coherent hydrophone array

A large variety of sound sources in the ocean, including biological, geophysical and man-made activities can be simultaneously monitored over instantaneous continental-shelf scale regions via the passive ocean acoustic waveguide remote sensing (POAWRS) technique by employing a large-aperture densely-sampled coherent hydrophone array. Millions of acoustic signals received on the POAWRS system per day can make it challenging to identify individual sound sources. An automated classification system is necessary to enable sound sources to be recognized. Here a large training data set of fin whale and other vocalizations are gathered after manual inspection and labelling. Next, multiple classifiers including neural networks, logistic regression, support vector machine (SVM) and decision tree are built and tested for identifying the fin whale and other vocalizations from the enormous amounts of acoustic signals detected per day. The neural network classifier will use beamformed spectrograms to classify acoustic ...

Temporal–spatial, spectral, and source level distributions of fin whale vocalizations in the Norwegian Sea observed with a coherent hydrophone array

&NA; To better understand fin whale vocalization behaviour in the Norwegian and Barents Seas, a large‐aperture densely sampled coherent hydrophone array was deployed in late winter 2014 to monitor their vocalizations instantaneously over wide areas via passive ocean acoustic waveguide remote sensing (POAWRS). Here, we (i) provide a time‐frequency characterization for different call types observed (20 Hz pulses, 130 Hz upsweeps, 30‐100 Hz downsweep chirps, and 18‐19 Hz backbeats); (ii) compare their relative abundances in three different coastal regions off Alesund, Lofoten, and Northern Finnmark; (iii) estimate the temporal and spatial distributions; (iv) source level distributions; and (v) probability of detection (PoD) regions for the more abundant 20 Hz pulse and 130 Hz upsweep call types. The fin whale vocalizations received over the diel cycle (24 h) were significantly more abundant by a factor of roughly seven off Northern Finnmark than the other two regions, associated with fish feeding activities. The source levels are estimated to be 190.5±7.4 dB for the fin whale 20 Hz pulses and 170.3 ± 5.2 dB for the 130 Hz upsweeps. We find that fin whales are capable of producing each vocalization type either independently or simultaneously with other types, and the 20 Hz sound production in the fin whales involves a mechanism that generates a significantly less‐intense second‐order harmonic of the fundamental.

Instantaneous wide-area passive acoustic monitoring of surface ships and submerged vehicles using a coherent hydrophone array

The ability to monitor surface ships and other ocean vehicles continuously over instantaneous wide areas is essential for a wide range of applications including defense and ocean environmental assessment. Here, we employ a large-aperture coherent hydrophone array system to detect, localize, and classify several surface ships and other ocean vehicles from their sounds radiated underwater using the passive ocean acoustic waveguide remote sensing (POAWRS) technique. The approach is calibrated for four distinct research and fisheries survey vessels with accurately known locations obtained from global positioning systems (GPS). Acoustic signals passively recorded on the coherent hydrophone array are first beamformed for their azimuthal dependencies. The sounds radiated by ocean vehicles are automatically detected using a threshold detector from the beamformed spectrograms. The bearing versus time trajectories of sequences of detections are used to localize the ocean vehicles by employing the moving array trian...

Temporal-spatial distributions for a repertoire of fin whale vocalizations from directional sensing with a coherent hydrophone array

The ability to monitor and differentiate vocalizations from a given marine mammal species can be challenging with single sensor measurements when there are multiple marine mammal species vocalizing in close proximity and when the vocalizations have not been observed or documented previously. Here we employ a large-aperture coherent hydrophone array system with directional sensing to detect, localize, and classify a repertoire of fin whale vocalizations using the passive ocean acoustic waveguide remote sensing (POAWRS) technique. The fin whale vocalizations are comprised of their characteristic 20 Hz centered pulses, interspersed by 130 Hz centered upsweep calls, and other vocalizations with frequencies ranging between 40 and 80 Hz. The directional sensing ability of POAWRS is essential for associating various call types to fin whales after long term tracking of the vocalization bearing-time trajectories and localizations over multiple diel cycles. Here, we quantify the relative diel occurrence of the thre...