Spatio-temporal patterns of beaked whale echolocation signals in the North Pacific

Ziphius cavirostris presence relative to the vertical and temporal variability of oceanographic conditions in the Southern California Bight

The oceanographic conditions of the Southern California Bight (SCB) dictate the distribution and abundance of prey resources and therefore the presence of mobile predators, such as goose-beaked whales (Ziphius cavirostris). Goose-beaked whales are deep-diving odontocetes that spend a majority of their time foraging at depth. Due to their cryptic behavior, little is known about how they respond to seasonal and interannual changes in their environment. This study utilizes passive acoustic data recorded from two sites within the SCB to explore the oceanographic conditions that goose-beaked whales appear to favor. Utilizing optimum multiparameter analysis, modeled temperature and salinity data are used to identify and quantify these source waters: Pacific Subarctic Upper Water (PSUW), Pacific Equatorial Water (PEW), and Eastern North Pacific Central Water (ENPCW). The interannual and seasonal variability in goose-beaked whale presence was related to the variability in El Niño Southern Oscillation events and the fraction and vertical distribution of the three source waters. Goose-beaked whale acoustic presence was highest during the winter and spring and decreased during the late summer and early fall. These seasonal increases occurred at times of increased fractions of PEW in the California Undercurrent and decreased fractions of ENPCW in surface waters. Interannual increases in goose-beaked whale presence occurred during El Niño events. These results establish a baseline understanding of the oceanographic characteristics that correlate with goose-beaked whale presence in the SCB. Furthering our knowledge of this elusive species is key to understanding how anthropogenic activities impact goose-beaked whales.

Machine learning with taxonomic family delimitation aids in the classification of ephemeral beaked whale events in passive acoustic monitoring

Passive acoustic monitoring is an essential tool for studying beaked whale populations. This approach can monitor elusive and pelagic species, but the volume of data it generates has overwhelmed researchers' ability to quantify species occurrence for effective conservation and management efforts. Automation of data processing is crucial, and machine learning algorithms can rapidly identify species using their sounds. Beaked whale acoustic events, often infrequent and ephemeral, can be missed when co-occurring with signals of more abundant, and acoustically active species that dominate acoustic recordings. Prior efforts on large-scale classification of beaked whale signals with deep neural networks (DNNs) have approached the class as one of many classes, including other odontocete species and anthropogenic signals. That approach tends to miss ephemeral events in favor of more common and dominant classes. Here, we describe a DNN method for improved classification of beaked whale species using an extensive dataset from the western North Atlantic. We demonstrate that by training a DNN to focus on the taxonomic family of beaked whales, ephemeral events were correctly and efficiently identified to species, even with few echolocation clicks. By retrieving ephemeral events, this method can support improved estimation of beaked whale occurrence in regions of high odontocete acoustic activity.

Odontocete spatial patterns and temporal drivers of detection at sites in the Hawaiian islands

Successful conservation and management of marine top predators rely on detailed documentation of spatiotemporal behavior. For cetacean species, this information is key to defining stocks, habitat use, and mitigating harmful interactions. Research focused on this goal is employing methodologies such as visual observations, tag data, and passive acoustic monitoring (PAM) data. However, many studies are temporally limited or focus on only one or few species. In this study, we make use of an existing long-term (2009-2019), labeled PAM data set to examine spatiotemporal patterning of at least 10 odontocete (toothed whale) species in the Hawaiian Islands using compositional analyses and modeling techniques. Species composition differs among considered sites, and this difference is robust to seasonal movement patterns. Temporally, hour of day was the most significant predictor of detection across species and sites, followed by season, though patterns differed among species. We describe long-term trends in species detection at one site and note that they are markedly similar for many species. These trends may be related to long-term, underlying oceanographic cycles that will be the focus of future study. We demonstrate the variability of temporal patterns even at relatively close sites, which may imply that wide-ranging models of species presence are missing key fine-scale movement patterns. Documented seasonal differences in detection also highlights the importance of considering season in survey design both regionally and elsewhere. We emphasize the utility of long-term, continuous monitoring in highlighting temporal patterns that may relate to underlying climatic states and help us predict responses to climate change. We conclude that long-term PAM records are a valuable resource for documenting spatiotemporal patterns and can contribute many insights into the lives of top predators, even in highly studied regions such as the Hawaiian Islands.

Silbido profundo: An open source package for the use of deep learning to detect odontocete whistles

This work presents an open-source matlab software package for exploiting recent advances in extracting tonal signals from large acoustic data sets. A whistle extraction algorithm published by Li, Liu, Palmer, Fleishman, Gillespie, Nosal, Shiu, Klinck, Cholewiak, Helble, and Roch [(2020). Proceedings of the International Joint Conference on Neural Networks, July 19-24, Glasgow, Scotland, p. 10] is incorporated into silbido, an established software package for extraction of cetacean tonal calls. The precision and recall of the new system were over 96% and nearly 80%, respectively, when applied to a whistle extraction task on a challenging two-species subset of a conference-benchmark data set. A second data set was examined to assess whether the algorithm generalized to data that were collected across different recording devices and locations. These data included 487 h of weakly labeled, towed array data collected in the Pacific Ocean on two National Oceanographic and Atmospheric Administration (NOAA) cruises. Labels for these data consisted of regions of toothed whale presence for at least 15 species that were based on visual and acoustic observations and not limited to whistles. Although the lack of per whistle-level annotations prevented measurement of precision and recall, there was strong concurrence of automatic detections and the NOAA annotations, suggesting that the algorithm generalizes well to new data.

Echolocation click discrimination for three killer whale ecotypes in the Northeastern Pacific

Three killer whale ecotypes are found in the Northeastern Pacific: residents, transients, and offshores. These ecotypes can be discriminated in passive acoustic data based on distinct pulsed call repertoires. Killer whale acoustic encounters for which ecotypes were assigned based on pulsed call matching were used to characterize the ecotype-specific echolocation clicks. Recordings were made using seafloor-mounted sensors at shallow (∼120 m) and deep (∼1400 m) monitoring locations off the coast of Washington state. All ecotypes' echolocation clicks were characterized by energy peaks between 12 and 19 kHz, however, resident clicks featured sub peaks at 13.7 and 18.8 kHz, while offshore clicks had a single peak at 14.3 kHz. Transient clicks were rare and were characterized by lower peak frequencies (12.8 kHz). Modal inter-click intervals (ICIs) were consistent but indistinguishable for resident and offshore killer whale encounters at the shallow site (0.21-0.22 s). Offshore ICIs were longer and more variable at the deep site, and no modal ICI was apparent for the transient ecotype. Resident and offshore killer whale ecotype may be identified and distinguished in large passive acoustic datasets based on properties of their echolocation clicks, however, transient echolocation may be unsuitable in isolation as a cue for monitoring applications.

Discriminating and classifying odontocete echolocation clicks in the Hawaiian Islands using machine learning methods

Passive acoustic monitoring (PAM) has proven a powerful tool for the study of marine mammals, allowing for documentation of biologically relevant factors such as movement patterns or animal behaviors while remaining largely non-invasive and cost effective. From 2008-2019, a set of PAM recordings covering the frequency band of most toothed whale (odontocete) echolocation clicks were collected at sites off the islands of Hawai'i, Kaua'i, and Pearl and Hermes Reef. However, due to the size of this dataset and the complexity of species-level acoustic classification, multi-year, multi-species analyses had not yet been completed. This study shows how a machine learning toolkit can effectively mitigate this problem by detecting and classifying echolocation clicks using a combination of unsupervised clustering methods and human-mediated analyses. Using these methods, it was possible to distill ten unique echolocation click 'types' attributable to regional odontocetes at the genus or species level. In one case, auxiliary sightings and recordings were used to attribute a new click type to the rough-toothed dolphin, Steno bredanensis. Types defined by clustering were then used as input classes in a neural-network based classifier, which was trained, tested, and evaluated on 5-minute binned data segments. Network precision was variable, with lower precision occurring most notably for false killer whales, Pseudorca crassidens, across all sites (35-76%). However, accuracy and recall were high (>96% and >75%, respectively) in all cases except for one type of short-finned pilot whale, Globicephala macrorhynchus, call class at Kaua'i and Pearl and Hermes Reef (recall >66%). These results emphasize the utility of machine learning in analysis of large PAM datasets. The classifier and timeseries developed here will facilitate further analyses of spatiotemporal patterns of included toothed whales. Broader application of these methods may improve the efficiency of global multi-species PAM data processing for echolocation clicks, which is needed as these datasets continue to grow.

A machine learning pipeline for classification of cetacean echolocation clicks in large underwater acoustic datasets

Machine learning algorithms, including recent advances in deep learning, are promising for tools for detection and classification of broadband high frequency signals in passive acoustic recordings. However, these methods are generally data-hungry and progress has been limited by challenges related to the lack of labeled datasets adequate for training and testing. Large quantities of known and as yet unidentified broadband signal types mingle in marine recordings, with variability introduced by acoustic propagation, source depths and orientations, and interacting signals. Manual classification of these datasets is unmanageable without an in-depth knowledge of the acoustic context of each recording location. A signal classification pipeline is presented which combines unsupervised and supervised learning phases with opportunities for expert oversight to label signals of interest. The method is illustrated with a case study using unsupervised clustering to identify five toothed whale echolocation click types and two anthropogenic signal categories. These categories are used to train a deep network to classify detected signals in either averaged time bins or as individual detections, in two independent datasets. Bin-level classification achieved higher overall precision (>99%) than click-level classification. However, click-level classification had the advantage of providing a label for every signal, and achieved higher overall recall, with overall precision from 92 to 94%. The results suggest that unsupervised learning is a viable solution for efficiently generating the large, representative training sets needed for applications of deep learning in passive acoustics.

Acoustic classification of false killer whales in the Hawaiian islands based on comprehensive vocal repertoire

Use of underwater passive acoustic datasets for species-specific inference requires robust classification systems to identify encounters to species from characteristics of detected sounds. A suite of routines designed to efficiently detect cetacean sounds, extract features, and classify the detection to species is described using ship-based, visually verified detections of false killer whales (Pseudorca crassidens). The best-performing model included features from clicks, whistles, and burst pulses, which correctly classified 99.6% of events. This case study illustrates use of these tools to build classifiers for any group of cetacean species and assess classification confidence when visual confirmation is not available.

Decadal Assessment of Sperm Whale Site-Specific Abundance Trends in the Northern Gulf of Mexico Using Passive Acoustic Data

Passive acoustic monitoring has been successfully used to study deep-diving marine mammal populations. To assess regional population trends of sperm whales in the northern Gulf of Mexico (GoM), including impacts of the Deepwater Horizon platform oil spill in 2010, the Littoral Acoustic Demonstration Center-Gulf Ecological Monitoring and Modeling (LADC-GEMM) consortium collected broadband acoustic data in the Mississippi Valley/Canyon area between 2007 and 2017 using bottom-anchored moorings. These data allow the inference of short-term and long-term variations in site-specific abundances of sperm whales derived from their acoustic activity. A comparison is made between the abundances of sperm whales at specific sites in different years before and after the oil spill by estimating the regional abundance density. The results show that sperm whales were present in the region throughout the entire monitoring period. A habitat preference shift was observed for sperm whales after the 2010 oil spill with higher activities at sites farther away from the spill site. A comparison of the 2007 and 2015 results shows that the overall regional abundance of sperm whales did not recover to pre-spill levels. The results indicate that long-term spatially distributed acoustic monitoring is critical in characterizing sperm whale population changes and in understanding how environmental stressors impact regional abundances and the habitat use of sperm whales.

Acoustic Presence of Dolphins through Whistles Detection in Mediterranean Shallow Waters

The evaluation of acoustic temporal rhythms in wide-ranging cetaceans can reveal patterns in animal spatial presence and the occurrence of periodical phenomena. Here, we aimed at assessing the temporal patterns of dolphin’s acoustic presence in a shallow-water area in the Sicily Strait (Mediterranean Sea). Whistles were collected continuously for 14 months from an acoustic monitoring station installed aboard of an elastic seamark. Over a total of 6955 h of recording, 14,048 signals were identified using both automatic and visual methods. Three parameters were analyzed: hourly presence (HP), used as a proxy of the presence of dolphins in the area; detection rate (DR), indicating the acoustic activity rate of dolphins measured per hour in the entire dataset; and detection rate in presence of dolphins (DRD), indicating the acoustic activity rate of dolphins considering only the hours when whistles were recorded. The highest values of both HP and DR were reached during the night, and the Autumn and Winter months, suggesting an increase in the dolphin’s occurrence and a possible moving away and towards the monitoring station potentially following prey. DRD, instead, showed an almost uniform distribution throughout the day implying that when the animals are close to the monitoring station, the acoustic activity does not show any pattern. However, possible changes in the communication exchange along the seasons were suggested. This study complements other work on this subject, improving the knowledge of dolphins’ acoustic activity in the area.

The effect of two 12 kHz multibeam mapping surveys on the foraging behavior of Cuvier's beaked whales off of southern California

The impact of multibeam echosounder (MBES) operations on marine mammals has been less studied compared to military sonars. To contribute to the growing body of MBES knowledge, echolocation clicks of foraging Cuvier's beaked whales were detected on the Southern California Antisubmarine Warfare Range (SOAR) hydrophones during two MBES surveys and assembled into foraging events called group vocal periods (GVPs). Four GVP characteristics were analyzed Before, During, and After 12 kHz MBES surveys at the SOAR in 2017 and 2019 to assess differences in foraging behavior with respect to the mapping activity. The number of GVP per hour increased During and After MBES surveys compared with Before. There were no other differences between non-MBES and MBES periods for the three other characteristics: the number of clicks per GVP, GVP duration, and click rate. These results indicate that there was not a consistent change in foraging behavior during the MBES surveys that would suggest a clear response. The animals did not leave the range nor stop foraging during MBES activity. These results are in stark contrast to those of analogous studies assessing the effect of Naval mid-frequency active sonar on beaked whale foraging, where beaked whales stopped echolocating and left the area.

Co-occurrence of beaked whale strandings and naval sonar in the Mariana Islands, Western Pacific

Mid-frequency active sonar (MFAS), used for antisubmarine warfare (ASW), has been associated with multiple beaked whale (BW) mass stranding events. Multinational naval ASW exercises have used MFAS offshore of the Mariana Archipelago semi-annually since 2006. We report BW and MFAS acoustic activity near the islands of Saipan and Tinian from March 2010 to November 2014. Signals from Cuvier's (Ziphius cavirostris) and Blainville's beaked whales (Mesoplodon densirostris), and a third unidentified BW species, were detected throughout the recording period. Both recorders documented MFAS on 21 August 2011 before two Cuvier's beaked whales stranded on 22–23 August 2011. We compared the history of known naval operations and BW strandings from the Mariana Archipelago to consider potential threats to BW populations. Eight BW stranding events between June 2006 and January 2019 each included one to three animals. Half of these strandings occurred during or within 6 days after naval activities, and this co-occurrence is highly significant. We highlight strandings of individual BWs can be associated with ASW, and emphasize the value of ongoing passive acoustic monitoring, especially for beaked whales that are difficult to visually detect at sea. We strongly recommend more visual monitoring efforts, at sea and along coastlines, for stranded cetaceans before, during and after naval exercises.

Characteristics of vocalisations recorded from free-ranging Shepherd's beaked whales, Tasmacetus shepherdi

Beaked whales (family Ziphiidae) are among the least studied of all the large mammals. This is especially true of Shepherd's beaked whale (Tasmacetus shepherdi), which until recently had been very rarely sighted alive, with nothing known about the species' acoustic behaviour. Vocalisations of Shepherd's beaked whales were recorded using a hydrophone array on two separate days during marine mammal surveys of the Otago submarine canyons in New Zealand. After carefully screening the recordings, two distinct call types were found; broadband echolocation clicks, and burst pulses. Broadband echolocation clicks (n = 476) had a median inter-click-interval (ICI) of 0.46 s and median peak frequency of 19.2 kHz. The burst pulses (n = 33) had a median peak frequency of constituent clicks (n = 1741) of 14.7 kHz, and median ICI of 11 ms. These results should be interpreted with caution due to the limited bandwidth used to record the signals. To the authors' knowledge, this study presents the first analysis of the characteristics of Shepherd's beaked whale sounds. It will help with identification of the species in passive acoustic monitoring records, and future efforts to further analyse this species' vocalisations.

A description of echolocation clicks recorded in the presence of True's beaked whale (Mesoplodon mirus)

True's beaked whales (Mesoplodon mirus) were encountered on two separate shipboard surveys on 24 July 2016 and 16 September 2017 in the western North Atlantic Ocean. Recordings were made using a hydrophone array towed 300 m behind the ship. In 2016, three different groups were sighted within 1500 m of the ship; clicks were recorded for 26 min. In 2017, a single group of five whales was tracked over the course of five hours in which the ship maintained a distance <4000 m from the group. A total of 2938 frequency-modulated (FM) clicks and 7 buzzes were recorded from both encounters. Plausible inter-click-intervals (ICIs) were calculated from 2763 clicks, and frequency and duration measurements were calculated from 2150 good quality FM clicks. The median peak frequencies were 43.1 kHz (2016, n = 718) and 43.5 kHz (2017, n = 1432). Median ICIs were 0.17 s (2016) and 0.19 s (2017). The spectra and measurements of the recorded clicks closely resemble Gervais's beaked whale clicks (Mesoplodon europaeus) and distinguishing between the two species in acoustic data sets proves difficult. The acoustic behavior of True's beaked whales was previously unknown; this study provides a description of echolocation clicks produced by this species.

Diving behavior of Cuvier's beaked whales inferred from three-dimensional acoustic localization and tracking using a nested array of drifting hydrophone recorders

Echolocation pulses from Cuvier's beaked whales are used to track the whales' three-dimensional diving behavior in the Catalina Basin, California. In 2016, five 2-element vertical hydrophone arrays were suspended from the surface and drifted at ∼100-m depth. Cuvier's beaked whale pulses were identified, and vertical detection angles were estimated from time-differences-of-arrival of either direct-path signals received on two hydrophones or direct-path and surface-reflected signals received on the same hydrophone. A Bayesian state-space model is developed to track the diving behavior. The model is fit to these detection angle estimates from at least four of the drifting vertical arrays. Results show that the beaked whales were producing echolocation pulses and are presumed to be foraging at a mean depth of 967 m (standard deviation = 112 m), approximately 300 m above the bottom in this basin. Some whales spent at least some time at or near the bottom. Average swim speed was 1.2 m s^-1, but swim direction varied during a dive. The average net horizontal speed was 0.6 m s^-1. Results are similar to those obtained from previous tagging studies of this species. These methods may allow expansion of dive studies to other whale species that are difficult to tag.

Cadhla O, Berrow S. Signals from the deep: Spatial and temporal acoustic occurrence of beaked whales off western Ireland

Little is known of the spatio-temporal occurrence of beaked whales off western Ireland, limiting the ability of Regulators to implement appropriate management and conservation measures. To address this knowledge gap, static acoustic monitoring was carried out using eight fixed bottom-mounted autonomous acoustic recorders: four from May to December 2015 on Ireland’s northern slope and four from March to November 2016 on the western and southern slopes. Recorders ran for 205 to 230 days, resulting in 4.09 TB of data sampled at 250 kHz which could capture beaked whale acoustic signals. Zero-crossing-based automated detectors identified beaked whale clicks. A sample of detections was manually validated to evaluate and optimize detector performance. Analysis confirmed the occurrence of Sowerby’s and Cuvier’s beaked whales and Northern bottlenose whales. Northern bottlenose whale clicks occurred in late summer and autumn, but were too few to allow further analysis. Cuvier’s and Sowerby’s clicks occurred at all stations throughout the monitoring period. There was a significant effect of month and station (latitude) on the mean daily number of click detections for both species. Cuvier’s clicks were more abundant at lower latitudes while Sowerby’s were greater at higher latitudes, particularly in the spring, suggesting a spatial segregation between species, possibly driven by prey preference. Cuvier’s occurrence increased in late autumn 2015 off northwest Porcupine Bank, a region of higher relative occurrence for each species. Seismic airgun shots, with daily sound exposure levels as high as 175 dB re 1 μPa²·s, did not appear to impact the mean daily number of Cuvier’s or Sowerby’s beaked whale click detections. This work provides insight into the significance of Irish waters for beaked whales and highlights the importance of using acoustics for beaked whale monitoring.

Unknown beaked whale echolocation signals recorded off eastern New Zealand

The echolocation signals of most beaked whale species are still unknown. In fact, out of the 22 species comprising the family Ziphiidae, only the echolocation pulses for 7 species have been clearly described. This study describes two distinct beaked whale echolocation signals recorded in the Cook Strait region using passive acoustic technology. These signals differ from previously described Ziphiid species clicks. A description of the time-frequency characteristics of the two signals is provided. Understanding the characteristics of these signals is necessary to correctly identify species from their echolocation signals and enables future monitoring of beaked whales using passive acoustics techniques.

Limited trophic partitioning among sympatric delphinids off a tropical oceanic atoll

Understanding trophic relationships among marine predators in remote environments is challenging, but it is critical to understand community structure and dynamics. In this study, we used stable isotope analysis of skin biopsies to compare the isotopic, and thus, trophic niches of three sympatric delphinids in the waters surrounding Palmyra Atoll, in the Central Tropical Pacific: the melon-headed whale (Peponocephala electra), Gray’s spinner dolphin (Stenella longirostris longirostris), and the common bottlenose dolphin (Tursiops truncatus). δ¹⁵N values suggested that T. truncatus occupied a significantly higher trophic position than the other two species. δ¹³C values did not significantly differ between the three delphinds, potentially indicating no spatial partitioning in depth or distance from shore in foraging among species. The dietary niche area—determined by isotopic variance among individuals—of T. truncatus was also over 30% smaller than those of the other species taken at the same place, indicating higher population specialization or lower interindividual variation. For P. electra only, there was some support for intraspecific variation in foraging ecology across years, highlighting the need for temporal information in studying dietary niche. Cumulatively, isotopic evidence revealed surprisingly little evidence for trophic niche partitioning in the delphinid community of Palmyra Atoll compared to other studies. However, resource partitioning may happen via other behavioral mechanisms, or prey abundance or availability may be adequate to allow these three species to coexist without any such partitioning. It is also possible that isotopic signatures are inadequate to detect trophic partitioning in this environment, possibly because isotopes of prey are highly variable or insufficiently resolved to allow for differentiation.

Precision and bias in estimating detection distances for beaked whale echolocation clicks using a two-element vertical hydrophone array

Detection distances are critical for cetacean density and abundance estimation using distance sampling methods. Data from a drifting buoy system consisting of an autonomous recorder and a two-element vertical hydrophone array at ∼100-m depth are used to evaluate three methods for estimating the horizontal distance (range) to beaked whales making echolocation clicks. The precision in estimating time-differences-of-arrival (TDOA) for direct- and surface-reflected-path clicks is estimated empirically using repeated measures over short time periods. A Teager-Kaiser energy detector is used to improve estimates of TDOA for surface-reflected signals. Simulations show that array tilt in the direction of the source cannot be reliably estimated given this array geometry and these measurements of TDOA error, which means that range cannot be reliably estimated. If array tilt can be reduced to less than 0.5°, range can be reliably estimated up to ∼3000 m. If array depth is increased to 200 m and array tilt is less than 1°, range can be reliably estimated up to ∼5000 m. Prior information on the depth of vocalizing beaked whales and estimates of declination angle can be used to precisely estimate range, but different analytical methods are required to avoid bias and to treat distributions of depth probabilistically.

Cetacean acoustic detections from free-floating vertical hydrophone arrays in the southern California Current

Drifting acoustic recorders were deployed in the southern California Current during Fall 2014. Two hydrophones configured as a 2-m vertical array at 100 m depth recorded using a 192 kHz sample rate on a 10% duty cycle (2 min/20 min). Beaked whales were detected in 33 of 8618 two-minute recordings. Sperm whales were detected in 185 recordings, and dolphins in 2291 recordings. Many beaked whales detected were over an abyssal plain and not associated with slope or seamount features. Results show the feasibility of using free-floating recording systems to detect a variety of cetacean species over periods of several months.

Shifts in frequency-modulated pulses recorded during an encounter with Blainville's beaked whales (Mesoplodon densirostris)

Echolocation signals produced by beaked whales (family: Ziphiidae) include frequency-modulated (FM) pulses that appear to have species-specific characteristics. To date there has been no established evidence that a single species of beaked whale might produce more than one type of FM pulse. In 2014 a group of Blainville's beaked whales (Mesoplodon densirostris) were sighted off of Southern California; recordings included FM pulses with significant increases in peak frequency, center frequency, and -10 dB bandwidth relative to FM pulses previously attributed to this species. This research suggests there may be greater variation in received beaked whale FM pulses than previously understood.

Effects of duty-cycled passive acoustic recordings on detecting the presence of beaked whales in the northwest Atlantic

This study investigated the effects of using duty-cycled passive acoustic recordings to monitor the daily presence of beaked whale species at three locations in the northwest Atlantic. Continuous acoustic records were subsampled to simulate duty cycles of 50%, 25%, and 10% and cycle period durations from 10 to 60 min. Short, frequent listening periods were most effective for assessing the daily presence of beaked whales. Furthermore, subsampling at low duty cycles led to consistently greater underestimation of Mesoplodon species than either Cuvier's beaked whales or northern bottlenose whales, leading to a potential bias in estimation of relative species occurrence.

Passive acoustic monitoring of beaked whale densities in the Gulf of Mexico

Beaked whales are deep diving elusive animals, difficult to census with conventional visual surveys. Methods are presented for the density estimation of beaked whales, using passive acoustic monitoring data collected at sites in the Gulf of Mexico (GOM) from the period during and following the Deepwater Horizon oil spill (2010-2013). Beaked whale species detected include: Gervais' (Mesoplodon europaeus), Cuvier's (Ziphius cavirostris), Blainville's (Mesoplodon densirostris) and an unknown species of Mesoplodon sp. (designated as Beaked Whale Gulf - BWG). For Gervais' and Cuvier's beaked whales, we estimated weekly animal density using two methods, one based on the number of echolocation clicks, and another based on the detection of animal groups during 5 min time-bins. Density estimates derived from these two methods were in good general agreement. At two sites in the western GOM, Gervais' beaked whales were present throughout the monitoring period, but Cuvier's beaked whales were present only seasonally, with periods of low density during the summer and higher density in the winter. At an eastern GOM site, both Gervais' and Cuvier's beaked whales had a high density throughout the monitoring period.

Three-dimensional tracking of Cuvier's beaked whales' echolocation sounds using nested hydrophone arrays

Cuvier's beaked whales (Ziphius cavirostris) were tracked using two volumetric small-aperture (∼1 m element spacing) hydrophone arrays, embedded into a large-aperture (∼1 km element spacing) seafloor hydrophone array of five nodes. This array design can reduce the minimum number of nodes that are needed to record the arrival of a strongly directional echolocation sound from 5 to 2, while providing enough time-differences of arrivals for a three-dimensional localization without depending on any additional information such as multipath arrivals. To illustrate the capabilities of this technique, six encounters of up to three Cuvier's beaked whales were tracked over a two-month recording period within an area of 20 km(2) in the Southern California Bight. Encounter periods ranged from 11 min to 33 min. Cuvier's beaked whales were found to reduce the time interval between echolocation clicks while alternating between two inter-click-interval regimes during their descent towards the seafloor. Maximum peak-to-peak source levels of 179 and 224 dB re 1 μPa @ 1 m were estimated for buzz sounds and on-axis echolocation clicks (directivity index = 30 dB), respectively. Source energy spectra of the on-axis clicks show significant frequency components between 70 and 90 kHz, in addition to their typically noted FM upsweep at 40-60 kHz.