A statistical acoustics approach for estimating population-scale bowhead whale migration speed and direction

Bowhead whales vocalize during their annual fall migration from the Beaufort Sea to the Bering Sea, but the calling rates of individual animals are so low that tracking an individual trajectory is impractical using passive acoustic methods. However, the travel speed and direction of the migrating population can be inferred on a statistical basis by cross-correlating time sequences of call density measured at two locations spaced several kilometers apart. By using the triangulation abilities of a set of vector sensors deployed offshore the Alaskan North Slope between 2008 and 2014, call density time sequences were generated from 1-km wide and 40-km tall rectangular "zones" that were separated by distances ranging from 3.5 to 15 km. The cross-covariances between the two sequences generate a peak corresponding to the average time it takes for whales to travel between the zones. Consistent westward travel speeds of ∼5 km/h were obtained from four different locations on 6 of the 7 years of the study, independent of whether the zones were separated by 3.5, 7, or 15 km. Some sites, however, also revealed a less prominent eastern movement of whales, and shifts in migration speed were occasionally detectable over week-long time scales.

Diel spatio-temporal patterns of humpback whale singing on a high-density breeding ground

Humpback whale song chorusing dominates the marine soundscape in Hawai'i during winter months, yet little is known about spatio-temporal habitat use patterns of singers. We analysed passive acoustic monitoring data from five sites off Maui and found that ambient noise levels associated with song chorusing decreased during daytime hours nearshore but increased offshore. To resolve whether these changes reflect a diel offshore-onshore movement or a temporal difference in singing activity, data from 71 concurrently conducted land-based theodolite surveys were analysed. Non-calf pods (n = 3082), presumably including the majority of singers, were found further offshore with increasing time of the day. Separately, we acoustically localized 217 nearshore singers using vector-sensors. During the day, distances to shore and minimum distances among singers increased, and singers switched more between being stationary and singing while travelling. Together, these findings suggest that the observed diel trends in humpback whale chorusing off Maui represent a pattern of active onshore-offshore movement of singers. We hypothesize that this may result from singers attempting to reduce intraspecific acoustic masking when densities are high nearshore and avoidance of a loud, non-humpback, biological evening chorus offshore, creating a dynamic of movement of singers aimed at increasing the efficiency of their acoustic display.

Multi-target 2D tracking method for singing humpback whales using vector sensors

Acoustic vector sensors allow estimating the direction of travel of an acoustic wave at a single point by measuring both acoustic pressure and particle motion on orthogonal axes. In a two-dimensional plane, the location of an acoustic source can thus be determined by triangulation using the estimated azimuths from at least two vector sensors. However, when tracking multiple acoustic sources simultaneously, it becomes challenging to identify and link sequences of azimuthal measurements between sensors to their respective sources. This work illustrates how two-dimensional vector sensors, deployed off the coast of western Maui, can be used to generate azimuthal tracks from individual humpback whales singing simultaneously. Incorporating acoustic transport velocity estimates into the processing generates high-quality azimuthal tracks that can be linked between sensors by cross-correlating features of their respective azigrams, a particular time-frequency representation of sound directionality. Once the correct azimuthal track associations have been made between instruments, subsequent localization and tracking in latitude and longitude of simultaneous whales can be achieved using a minimum of two vector sensors. Two-dimensional tracks and positional uncertainties of six singing whales are presented, along with swimming speed estimates derived from a high-quality track.

Measurements of open-water arctic ocean noise directionality and transport velocity

Measurements from bottom-mounted acoustic vector sensors, deployed seasonally between 2008 and 2014 on the shallow Beaufort Sea shelf along the Alaskan North Slope, are used to estimate the ambient sound pressure power spectral density, acoustic transport velocity of energy, and dominant azimuth between 25 and 450 Hz. Even during ice-free conditions, this region has unusual acoustic features when compared against other U.S. coastal regions. Two distinct regimes exist in the diffuse ambient noise environment: one with high pressure spectral density levels but low directionality, and another with lower spectral density levels but high directionality. The transition between the two states, which is invisible in traditional spectrograms, occurs between 73 and 79 dB re 1 μPa²/Hz at 100 Hz, with the transition region occurring at lower spectral levels at higher frequencies. Across a wide bandwidth, the high-directionality ambient noise consistently arrives from geographical azimuths between 0° and 30° from true north over multiple years and locations, with a seasonal interquartile range of 40° at low frequencies and high transport velocities. The long-term stability of this directional regime, which is believed to arise from the dominance of wind-driven sources along an east-west coastline, makes it an important feature of arctic ambient sound.

Using anisotropic and narrowband ambient noise for continuous measurements of relative clock drift between independent acoustic recorders

Relative clock drift between instruments can be an issue for coherent processing of acoustic signals, which requires data to be time-synchronized between channels. This work shows how cross correlation of anisotropic narrowband ambient noise allows continuous estimation of the relative clock drift between independent acoustic recorders, under the assumption that the spatial distribution of the coherent noise sources is stationary. This method is applied to two pairs of commercial passive acoustic recorders deployed up to 14 m apart at 6 and 12 m depth, respectively, over a period of 10 days. Occasional calibration signals show that this method allows time-synchronizing the instruments to within ±1 ms. In addition to a large linear clock drift component on the order of tens of milliseconds per hour, the results reveal for these instruments non-linear excursions of up to 50 ms that cannot be measured by standard methods but are crucial for coherent processing. The noise field displays the highest coherence between 50 and 100 Hz, a bandwidth dominated by what are believed to be croaker fish, which are particularly vocal in the evenings. Both the passive and continuous nature of this method provide advantages over time-synchronization using active sources.

Estimating acoustic cue rates in bowhead whales, Balaena mysticetus, during their fall migration through the Alaskan Beaufort Sea

Eight years of passive acoustic data (2007-2014) from the Beaufort Sea were used to estimate the mean cue rate (calling rate) of individual bowhead whales (Balaena mysticetus) during their fall migration along the North Slope of Alaska. Calls detected on directional acoustic recorders (DASARs) were triangulated to provide estimates of locations at times of call production, which were then translated into call densities (calls/h/km²). Various assumptions were used to convert call density into animal cue rates, including the time for whales to cross the arrays of acoustic recorders, the population size, the fraction of the migration corridor missed by the localizing array system, and the fraction of the seasonal migration missed because recorders were retrieved before the end of the migration. Taking these uncertainties into account in various combinations yielded up to 351 cue rate estimates, which summarize to a median of 1.3 calls/whale/h and an interquartile range of 0.5-5.4 calls/whale/h.

Automated two-dimensional localization of underwater acoustic transient impulses using vector sensor image processing (vector sensor localization)

Detecting acoustic transients by signal-to-noise ratio (SNR) becomes problematic in nonstationary ambient noise environments characteristic of coral reefs. An alternate approach presented here uses signal directionality to automatically detect and localize transient impulsive sounds collected on underwater vector sensors spaced tens of meters apart. The procedure, which does not require precise time synchronization, first constructs time-frequency representations of both the squared acoustic pressure (spectrogram) and dominant directionality of the active intensity (azigram) on each sensor. Within each azigram, sets of time-frequency cells associated with transient energy arriving from a consistent azimuthal sector are identified. Binary image processing techniques then link sets that share similar duration and bandwidth between different sensors, after which the algorithm triangulates the source location. Unlike most passive acoustic detectors, the threshold criterion for this algorithm is bandwidth instead of pressure magnitude. Data collected from shallow coral reef environments demonstrate the algorithm's ability to detect SCUBA bubble plumes and consistent spatial distributions of somniferous fish activity. Analytical estimates and direct evaluations both yield false transient localization rates from 3% to 6% in a coral reef environment. The SNR distribution of localized pulses off Hawaii has a median of 7.7 dB and interquartile range of 7.1 dB.

Roaring and repetition: How bowhead whales adjust their call density and source level (Lombard effect) in the presence of natural and seismic airgun survey noise

Over 500 000 automated and manual acoustic localizations, measured over seven years between 2008 and 2014, were used to examine how natural wind-driven noise and anthropogenic seismic airgun survey noise influence bowhead whale call densities (calls/km²/min) and source levels during their fall migration in the Alaskan Beaufort Sea. Noise masking effects, which confound measurements of behavioral changes, were removed using a modified point transect theory. The authors found that mean call densities generally rose with increasing continuous wind-driven noise levels. The occurrence of weak airgun pulse sounds also prompted an increase in call density equivalent to a 10-15 dB change in natural noise level, but call density then dropped substantially with increasing cumulative sound exposure level (cSEL) from received airgun pulses. At low in-band noise levels the mean source level of the acoustically-active population changed to nearly perfectly compensate for noise increases, but as noise levels increased further the mean source level failed to keep pace, reducing the population's communication space. An increase of >40 dB cSEL from seismic airgun activity led to an increase in source levels of just a few decibels. These results have implications for bowhead acoustic density estimation, and evaluations of the masking impacts of anthropogenic noise.

Displaying bioacoustic directional information from sonobuoys using "azigrams"

The AN/SSQ-53 Directional Frequency Analysis and Recording (DIFAR) sonobuoy is an expendable device that can derive acoustic particle velocity along two orthogonal horizontal axes, along with acoustic pressure. This information enables computation of azimuths of low-frequency acoustic sources from a single compact sensor. The standard approach for estimating azimuth from these sensors is by conventional beamforming (i.e., adding weighted time series), but the resulting "cardioid" beampattern is imprecise, computationally expensive, and vulnerable to directional noise contamination for weak signals. Demonstrated here is an alternative multiplicative processing scheme that computes the "active intensity" of an acoustic signal to obtain the dominant directionality of a noise field as a function of time and frequency. This information is conveniently displayed as an "azigram," which is analogous to a spectrogram, but uses color to indicate azimuth instead of intensity. Data from several locations demonstrate this approach, which can be computed without demultiplexing the raw signal. Azigrams have been used to help diagnose sonobuoy issues, improve detectability, and estimate bearings of low signal-to-noise ratio signals. Azigrams may also enhance the detection and potential classification of signals embedded in directional noise fields.

A double-difference method for high-resolution acoustic tracking using a deep-water vertical array

Ray-tracing is typically used to estimate the depth and range of an acoustic source in refractive deep-water environments by exploiting multipath information on a vertical array. However, mismatched array inclination and uncertain environmental features can produce imprecise trajectories when ray-tracing sequences of individual acoustic events. "Double-difference" methods have previously been developed to determine fine-scale relative locations of earthquakes along a fault [Waldhauser and Ellsworth (2000). Bull. Seismolog. Soc. Am. 90, 1353-1368]. This technique translates differences in travel times between nearby seismic events, recorded at multiple widely separated stations, into precise relative displacements. Here, this method for acoustic multipath measurements on a single vertical array of hydrophones is reformulated. Changes over time in both the elevation angles and the relative arrival times of the multipath are converted into relative changes in source position. This approach is tested on data recorded on a 128-element vertical array deployed in 4 km deep water. The trajectory of a controlled towed acoustic source was accurately reproduced to within a few meters at nearly 50 km range. The positional errors of the double-difference approach for both the towed source and an opportunistically detected sperm whale are an order of magnitude lower than those produced from ray-tracing individual events.

Effects of tones associated with drilling activities on bowhead whale calling rates

During summer 2012 Shell performed exploratory drilling at Sivulliq, a lease holding located in the autumn migration corridor of bowhead whales (Balaena mysticetus), northwest of Camden Bay in the Beaufort Sea. The drilling operation involved a number of vessels performing various activities, such as towing the drill rig, anchor handling, and drilling. Acoustic data were collected with six arrays of directional recorders (DASARs) deployed on the seafloor over ~7 weeks in Aug-Oct. Whale calls produced within 2 km of each DASAR were identified and localized using triangulation. A "tone index" was defined to quantify the presence and amplitude of tonal sounds from industrial machinery. The presence of airgun pulses originating from distant seismic operations was also quantified. For each 10-min period at each of the 40 recorders, the number of whale calls localized was matched with the "dose" of industrial sound received, and the relationship between calling rates and industrial sound was modeled using negative binomial regression. The analysis showed that with increasing tone levels, bowhead whale calling rates initially increased, peaked, and then decreased. This dual behavioral response is similar to that described for bowhead whales and airgun pulses in earlier work. Increasing call repetition rates can be a viable strategy for combating decreased detectability of signals arising from moderate increases in background noise. Meanwhile, as noise increases, the benefits of calling may decrease because information transfer becomes increasingly error-prone, and at some point calling may no longer be worth the effort.

Decadal-scale frequency shift of migrating bowhead whale calls in the shallow Beaufort Sea

Automated and manual acoustic localizations of bowhead whale calls in the Beaufort Sea were used to estimate the minimum frequency attained by their highly variable FM-modulated call repertoire during seven westerly fall migrations. Analyses of 13 355 manual and 100 009 automated call localizations found that between 2008 and 2014 the proportion of calls that dipped below 75 Hz increased from 27% to 41%, shifting the mean value of the minimum frequency distribution from 94 to 84 Hz. Multivariate regression analyses using both generalized linear models and generalized estimating equations found that this frequency shift persisted even when accounting for ten other factors, including calling depth, call range, call type, noise level, signal-to-noise ratio, local water depth (site), airgun activity, and call spatial density. No single call type was responsible for the observed shift, but so-called "complex" calls experienced larger percentage downward shifts. By contrast, the call source level distribution remained stable over the same period. The observed frequency shift also could not be explained by migration corridor shifts, relative changes in call detectability between different frequency bands, long-term degradation in the automated airgun detector, physiological growth in the population, or behavioral responses to increasing population density (estimated via call density).

Source level and calling depth distributions of migrating bowhead whale calls in the shallow Beaufort Sea

Automated and manual acoustic localizations of migrating bowhead whales were used to estimate source level and calling depth distributions of their frequency-modulated-modulated calls over seven years between 2008 and 2014. Whale positions were initially triangulated using directional autonomous seafloor acoustic recorders, deployed between 25 and 55 m water depth near Kaktovik, Alaska, during the fall westward migration. Calling depths were estimated by minimizing the "discrepancy" between source level estimates from at least three recorders detecting the same call. Applying a detailed waveguide propagation model to the data yielded broadband source levels of 161 ± 9 dB re 1 μPa² s at 1 m (SEL) for calls received between 20 and 170 Hz. Applying a simpler 15 log₁₀(R) power-law propagation model yielded SEL source levels of 158 ± 10 dB. The most probable calling depths lay between 22 and 30 m: optimal depths for long-range acoustic signal transmission in this particular environment.

Humpback whale-generated ambient noise levels provide insight into singers' spatial densities

Baleen whale vocal activity can be the dominant underwater ambient noise source for certain locations and seasons. Previous wind-driven ambient-noise formulations have been adjusted to model ambient noise levels generated by random distributions of singing humpback whales in ocean waveguides and have been combined to a single model. This theoretical model predicts that changes in ambient noise levels with respect to fractional changes in singer population (defined as the noise "sensitivity") are relatively unaffected by the source level distributions and song spectra of individual humpback whales (Megaptera novaeangliae). However, the noise "sensitivity" does depend on frequency and on how the singers' spatial density changes with population size. The theoretical model was tested by comparing visual line transect surveys with bottom-mounted passive acoustic data collected during the 2013 and 2014 humpback whale breeding seasons off Los Cabos, Mexico. A generalized linear model (GLM) estimated the noise "sensitivity" across multiple frequency bands. Comparing the GLM estimates with the theoretical predictions suggests that humpback whales tend to maintain relatively constant spacing between one another while singing, but that individual singers either slightly increase their source levels or song duration, or cluster more tightly as the singing population increases.

Acoustic vector sensor beamforming reduces masking from underwater industrial noise during passive monitoring

Masking from industrial noise can hamper the ability to detect marine mammal sounds near industrial operations, whenever conventional (pressure sensor) hydrophones are used for passive acoustic monitoring. Using data collected from an autonomous recorder with directional capabilities (Directional Autonomous Seafloor Acoustic Recorder), deployed 4.1 km from an arctic drilling site in 2012, the authors demonstrate how conventional beamforming on an acoustic vector sensor can be used to suppress noise arriving from a narrow sector of geographic azimuths. Improvements in signal-to-noise ratio of up to 15 dB are demonstrated on bowhead whale calls, which were otherwise undetectable using conventional hydrophones.

The ambient acoustic environment in Laguna San Ignacio, Baja California Sur, Mexico

Each winter gray whales (Eschrichtius robustus) breed and calve in Laguna San Ignacio, Mexico, where a robust, yet regulated, whale-watching industry exists. Baseline acoustic environments in LSI's three zones were monitored between 2008 and 2013, in anticipation of a new road being paved that will potentially increase tourist activity to this relatively isolated location. These zones differ in levels of both gray whale usage and tourist activity. Ambient sound level distributions were computed in terms of percentiles of power spectral densities. While these distributions are consistent across years within each zone, inter-zone differences are substantial. The acoustic environment in the upper zone is dominated by snapping shrimp that display a crepuscular cycle. Snapping shrimp also affect the middle zone, but tourist boat transits contribute to noise distributions during daylight hours. The lower zone has three source contributors to its acoustic environment: snapping shrimp, boats, and croaker fish. As suggested from earlier studies, a 300 Hz noise minimum exists in both the middle and lower zones of the lagoon, but not in the upper zone.

Range estimation of bowhead whale (Balaena mysticetus) calls in the Arctic using a single hydrophone

Bowhead whales generate low-frequency calls in shallow-water Arctic environments, whose dispersive propagation characteristics are well modeled by normal mode theory. As each mode propagates with a different group speed, a call's range can be inferred by the relative time-frequency dispersion of the modal arrivals. Traditionally, at close ranges modal arrivals are separated using synchronized hydrophone arrays. Here a nonlinear signal processing method called "warping" is used to filter the modes on just a single hydrophone. The filtering works even at relatively short source ranges, where distinct modal arrivals are not separable in a conventional spectrogram. However, this warping technique is limited to signals with monotonically increasing or decreasing frequency modulations, a relatively common situation for bowhead calls. Once modal arrivals have been separated, the source range can be estimated using conventional modal dispersion techniques, with the original source signal structure being recovered as a by-product. Twelve bowhead whale vocalizations recorded near Kaktovik (Alaska) in 2010, with signal-to-noise ratios between 6 and 23 dB, are analyzed, and the resulting single-receiver range estimates are consistent with those obtained independently via triangulation from widely-distributed vector sensor arrays. Geoacoustic inversions for each call are necessary in order to obtain the correct ranges.

Ranging bowhead whale calls in a shallow-water dispersive waveguide

This paper presents the performance of three methods for estimating the range of broadband (50-500 Hz) bowhead whale calls in a nominally 55-m-deep waveguide: Conventional mode filtering (CMF), synthetic time reversal (STR), and triangulation. The first two methods use a linear vertical array to exploit dispersive propagation effects in the underwater sound channel. The triangulation technique used here, while requiring no knowledge about the propagation environment, relies on a distributed array of directional autonomous seafloor acoustics recorders (DASARs) arranged in triangular grid with 7 km spacing. This study uses simulations and acoustic data collected in 2010 from coastal waters near Kaktovik, Alaska. At that time, a 12-element vertical array, spanning the bottom 63% of the water column, was deployed alongside a distributed array of seven DASARs. The estimated call location-to-array ranges determined from CMF and STR are compared with DASAR triangulation results for 19 whale calls. The vertical-array ranging results are generally within ±10% of the DASAR results with the STR results providing slightly better agreement. The results also indicate that the vertical array can range calls over larger ranges and with greater precision than the particular distributed array discussed here, whenever the call locations are beyond the distributed array boundaries.

A comparison of acoustic and visual metrics of sperm whale longline depredation

Annual federal stock assessment surveys for Alaskan sablefish also attempt to measure sperm whale depredation by quantifying visual evidence of depredation, including lip remains and damaged fish. A complementary passive acoustic method for quantifying depredation was investigated during the 2011 and 2012 survey hauls. A combination of machine-aided and human analysis counted the number of distinct “creak” sounds detected on autonomous recorders deployed during the survey, emphasizing sounds that are followed by silence (“creak-pauses”), a possible indication of prey capture. These raw counts were then adjusted for variations in background noise levels between deployments. Both a randomized Pearson correlation analysis and a generalized linear model found that noise-adjusted counts of “creak-pauses” were highly correlated with survey counts of lip remains during both years (2012: r(10) = 0.89, p = 1e-3; 2011: r(39) = 0.72, p = 4e-3) and somewhat correlated with observed sablefish damage in 2011 [r(39) = 0.37, p = 0.03], but uncorrelated with other species depredation. The acoustic depredation count was anywhere from 10% to 80% higher than the visual counts, depending on the survey year and assumptions employed. The results suggest that passive acoustics can provide upper bounds on depredation rates; however, the observed correlation breaks down whenever three or more whales are present.

Acoustic tracking of sperm whales in the Gulf of Alaska using a two-element vertical array and tags

Between 15 and 17 August 2010, a simple two-element vertical array was deployed off the continental slope of Southeast Alaska in 1200 m water depth. The array was attached to a vertical buoy line used to mark each end of a longline fishing set, at 300 m depth, close to the sound-speed minimum of the deep-water profile. The buoy line also served as a depredation decoy, attracting seven sperm whales to the area. One animal was tagged with both a LIMPET dive depth-transmitting satellite and bioacoustic "B-probe" tag. Both tag datasets were used as an independent check of various passive acoustic schemes for tracking the whale in depth and range, which exploited the elevation angles and relative arrival times of multiple ray paths recorded on the array. Analytical tracking formulas were viable up to 2 km range, but only numerical propagation models yielded accurate locations up to at least 35 km range at Beaufort sea state 3. Neither localization approach required knowledge of the local bottom bathymetry. The tracking system was successfully used to estimate the source level of an individual sperm whale's "clicks" and "creaks" and predict the maximum detection range of the signals as a function of sea state.

Acoustic and diving behavior of sperm whales (Physeter macrocephalus) during natural and depredation foraging in the Gulf of Alaska

Sperm whales have depredated black cod (Anoplopoma fimbria) from demersal longlines in the Gulf of Alaska for decades, but the behavior has recently spread in intensity and geographic coverage. Over a three-year period 11 bioacoustic tags were attached to adult sperm whales off Southeast Alaska during both natural and depredation foraging conditions. Measurements of the animals' dive profiles and their acoustic behavior under both behavioral modes were examined for statistically significant differences. Two rough categories of depredation are identified: "deep" and "shallow." "Deep depredating" whales consistently surface within 500 m of a hauling fishing vessel, have maximum dive depths greater than 200 m, and display significantly different acoustic behavior than naturally foraging whales, with shorter inter-click intervals, occasional bouts of high "creak" rates, and fewer dives without creaks. "Shallow depredating" whales conduct dives that are much shorter, shallower, and more acoustically active than both the natural and deep depredating behaviors, with median creak rates three times that of natural levels. These results suggest that depredation efforts might be measured remotely with passive acoustic monitoring at close ranges.

Automated detection and localization of bowhead whale sounds in the presence of seismic airgun surveys

An automated procedure has been developed for detecting and localizing frequency-modulated bowhead whale sounds in the presence of seismic airgun surveys. The procedure was applied to four years of data, collected from over 30 directional autonomous recording packages deployed over a 280 km span of continental shelf in the Alaskan Beaufort Sea. The procedure has six sequential stages that begin by extracting 25-element feature vectors from spectrograms of potential call candidates. Two cascaded neural networks then classify some feature vectors as bowhead calls, and the procedure then matches calls between recorders to triangulate locations. To train the networks, manual analysts flagged 219 471 bowhead call examples from 2008 and 2009. Manual analyses were also used to identify 1.17 million transient signals that were not whale calls. The network output thresholds were adjusted to reject 20% of whale calls in the training data. Validation runs using 2007 and 2010 data found that the procedure missed 30%-40% of manually detected calls. Furthermore, 20%-40% of the sounds flagged as calls are not present in the manual analyses; however, these extra detections incorporate legitimate whale calls overlooked by human analysts. Both manual and automated methods produce similar spatial and temporal call distributions.

Relationship between visual counts and call detection rates of gray whales (Eschrichtius robustus) in Laguna San Ignacio, Mexico

Daily acoustic calling rates of Eastern North Pacific (ENP) gray whales were measured on 6 days during 1 mo of their 2008 breeding season in the sheltered coastal lagoon of Laguna San Ignacio in Baja California, Mexico. Visual counts of whales determined that the numbers of single animals in the lower lagoon more than tripled over the observation period. All call types showed production peaks in the early morning and evening with minimum rates generally detected in the early afternoon. For four of the five observation days, the daily number of "S1"-type calls increased roughly as the square of the number of the animals in the lower lagoon during both daytime and nighttime. This relationship persisted when raw call counts were adjusted for variations in background noise level, using a simple propagation law derived from empirical measurements. The one observation day that did not fit the square-law relationship occurred during a week when the group size in the lagoon increased rapidly. These results suggest that passive acoustic monitoring does not measure gray whale group size directly but monitors the number of connections in the social network, which rises as roughly M(2)/2 for a group size M.

Quantifying seismic survey reverberation off the Alaskan North Slope

Shallow-water airgun survey activities off the North Slope of Alaska generate impulsive sounds that are the focus of much regulatory attention. Reverberation from repetitive airgun shots, however, can also increase background noise levels, which can decrease the detection range of nearby passive acoustic monitoring (PAM) systems. Typical acoustic metrics for impulsive signals provide no quantitative information about reverberation or its relative effect on the ambient acoustic environment. Here, two conservative metrics are defined for quantifying reverberation: a minimum level metric measures reverberation levels that exist between airgun pulse arrivals, while a reverberation metric estimates the relative magnitude of reverberation vs expected ambient levels in the hypothetical absence of airgun activity, using satellite-measured wind data. The metrics are applied to acoustic data measured by autonomous recorders in the Alaskan Beaufort Sea in 2008 and demonstrate how seismic surveys can increase the background noise over natural ambient levels by 30-45 dB within 1 km of the activity, by 10-25 dB within 15 km of the activity, and by a few dB at 128 km range. These results suggest that shallow-water reverberation would reduce the performance of nearby PAM systems when monitoring for marine mammals within a few kilometers of shallow-water seismic surveys.

Three-dimensional localization of sperm whales using a single hydrophone

A three-dimensional localization method for tracking sperm whales with as few as one sensor is demonstrated. Based on ray-trace acoustic propagation modeling, the technique exploits multipath arrival information from recorded sperm whale clicks and can account for waveguide propagation physics like interaction with range-dependent bathymetry and ray refraction. It also does not require ray identification (i.e., direct, surface reflected) while utilizing individual ray arrival information, simplifying automation efforts. The algorithm compares the arrival pattern from a sperm whale click to range-, depth-, and azimuth-dependent modeled arrival patterns in order to estimate whale location. With sufficient knowledge of azimuthally dependent bathymetry, a three-dimensional track of whale motion can be obtained using data from a single hydrophone. Tracking is demonstrated using data from acoustic recorders attached to fishing anchor lines off southeast Alaska as part of efforts to study sperm whale depredation of fishing operations. Several tracks of whale activity using real data from one or two hydrophones have been created, and three are provided to demonstrate the method, including one simultaneous visual and acoustic localization of a sperm whale actively clicking while surfaced. The tracks also suggest that whales' foraging is shallower in the presence of a longline haul than without.

Source ranging with minimal environmental information using a virtual receiver and waveguide invariant theory

A method is presented for estimating the range of an unknown broadband acoustic source in a waveguide, using a vertical array and a signal sample from another broadband source at a known location relative to the array. The method requires no modeling of the acoustic field, and little to no environmental information for flat bathymetries. Waveguide invariant theory [e.g., D'Spain and Kuperman, J. Acoust. Soc. Am 106, 2454-2468 (1999)] is applied to the "virtual receiver" [Siderius et al., J. Acoust. Soc. Am. 102, 3439-3449 (1997)] to create a "virtual aperture" (VA). In effect, the method effectively converts a source at known range r(g) into a continuum of receivers lying between ranges (1 +/- alpha/beta)*r(g), where beta is a scalar parameter called the acoustic invariant, and alpha approximately 0.1. This effective displacement is achieved by correlating the known source field, measured at frequency component omega, with the unknown source field, measured at frequency component omega + omegas. When the VA output is plotted as a function of omega and omegas, the slope of the resulting correlation contours yields the unknown source range. The concept is illustrated via both simulation and analysis of data collected from a pseudo-random noise source with 75-150-Hz bandwidth during SWellEx-3, a shallow water experiment conducted off the San Diego coast. The virtual aperture can be reformulated for range-dependent environments, if adiabatic propagation assumptions are valid, and if the bathymetry surrounding the array is known.

Matched-field processing, geoacoustic inversion, and source signature recovery of blue whale vocalizations

Matched-field processing (MFP) and global inversion techniques have been applied to vocalizations from four whales recorded on a 48-element tilted vertical array off the Channel Islands in 1996. Global inversions from selected whale calls using as few as eight elements extracted information about the surrounding ocean bottom composition, array shape, and the animal's position. These inversion results were then used to conduct straightforward MFP on other calls. The sediment sound-speed inversion estimates are consistent with those derived from sediment samples collected in the area. In general, most animals swam from the east to west, but one animal remained within approximately 500 m of its original position over 45 min. All whales vocalized between 10 and 40 m depth. Three acoustic sequences are discussed in detail: the first illustrating a match between an acoustic track and visual sighting, the second tracking two whales to ranges out to 8 km, and the final sequence demonstrating high-resolution dive profiles from an animal that changed its course to avoid the research platform FLIP (floating instrument platform). This last whale displayed an unusual diversity of signals that include three strong frequency-modulated (FM) downsweeps which contain possible signs of an internal resonance. The arrival of this same whale coincided with a sudden change in oceanographic conditions.

Localization using Bartlett matched-field processor sidelobes

Ambiguity surface sidelobes generated by the Bartlett matched-field processor (MFP) shift location with frequency. This sidelobe shift can be viewed as a continuous trajectory in a range-frequency plane at a fixed depth, where the trajectories converge to the correct source range for a perfectly matched surface. In isovelocity or bottom-interacting environments the sidelobe trajectories are straight lines that converge to the true range at zero frequency, while environments with upward-refracting sound-speed profiles have trajectories that asymptotically converge as the frequency approaches infinity. This behavior can be explained by the theory of waveguide invariants, which predict the local behavior of interference maxima/minima of acoustic intensity in the frequency-range plane. As the ambiguity surface of the Bartlett matched-field processor has a physical interpretation in terms of a time-reversed acoustic field, with the sidelobes analogous to local interference maxima, these invariant concepts can be reformulated for application to MFP. These interference trajectories are demonstrated to exist in simulations, broadband source tows, and a type A blue whale vocalization. Sidelobe trajectories also exist in the range-depth plane, but they contain no information about the correct source depth. An appendix demonstrates how these sidelobe properties can be exploited when combining ambiguity surfaces through use of gradient and Radon transform information. The resulting range estimators demonstrate better peak-to-sidelobe ratios than a simple incoherent average.