Species-specific beaked whale echolocation signals

Identification of the enigmatic Deraniyagala's beaked whale

It is essential to discover and identify animals in species level in the wild to achieve the collection of baseline data and benefit better understanding and conservation of the rare species. However, this is far from being realized for many beaked whales in the deep sea, including the Deraniyagala's beaked whale (Mesoplodon hotaula), which is one of the least-known whales with no confirmed live sightings at sea yet all over the world. Here, we provide the first robust field identification of M. hotaula, by integrating DNA sequencing of skin biopsies, acoustic data, and photographs. Our discovery illustrates that M. hotaula has distinguishing acoustic and morphological characteristics, enabling us to distinguish it from other mesoplodonts in the wild. The identification of M. hotaula in species level is rapidly advancing our knowledge on its distribution range, habitat characteristics, behavior, ontogenetic color pattern development, group size and structure, and potential threats.

Acoustic signature of plastic marine debris mimics the prey items of deep-diving cetaceans

It is largely assumed that odontocetes voluntarily ingest plastic marine debris because they visually mistake it for prey. However, deep-diving whales do not rely on visual systems to forage and instead employ echolocation. Whether or not these whales misinterpret acoustic signals that lead to the accidental ingestion of plastic is unknown. We examined this question by measuring the target strength of prey items (squid, squid beaks) and various naturally weathered and fouled plastics sourced from the North Carolina coastline in situ at sea at 38, 70 and 120 kHz. Here we show that 100 % of plastic marine debris tested (plastics commonly found in the stomachs of stranded whales such as plastic bags, rope, and bottles) have either similar or stronger acoustic target strengths compared with that of whale prey items. These finding supports the hypothesis that consumption of plastic by deep-diving odontocetes is driven by a misperception of acoustic signals.

Sounds as taxonomic indicators in Holocentrid fishes

The species-specific character of sounds in the animal kingdom has been extensively documented, yet research on fishes has predominantly focused on a limited number of species, overlooking the potential of acoustic signals to reflect broader taxonomic ranks. In this study, we analyzed acoustic data of hand-held sounds from 388 specimens spanning 5 genera and 33 species within the family Holocentridae, with the objective of evaluating the use of sound characteristics for taxonomic discrimination across various levels (subfamily, genus, species). Sounds could be indicative of grouping. Taxa discriminability depends on taxonomic level; the higher the taxonomic level, the better the discrimination of taxa based on sounds. Analogous to the role of morphological traits in taxonomic delineation, this research corroborates the utility of acoustic features in identifying fish taxa across multiple hierarchical levels. Remarkably, certain holocentrid species have evolved complex sound patterns characterized by unique temporal arrangements where pulses are not continuous but emitted in blocks, facilitating the exploitation of the acoustic space.

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.

Where's Whaledo: A software toolkit for array localization of animal vocalizations

Where's Whaledo is a software toolkit that uses a combination of automated processes and user interfaces to greatly accelerate the process of reconstructing animal tracks from arrays of passive acoustic recording devices. Passive acoustic localization is a non-invasive yet powerful way to contribute to species conservation. By tracking animals through their acoustic signals, important information on diving patterns, movement behavior, habitat use, and feeding dynamics can be obtained. This method is useful for helping to understand habitat use, observe behavioral responses to noise, and develop potential mitigation strategies. Animal tracking using passive acoustic localization requires an acoustic array to detect signals of interest, associate detections on various receivers, and estimate the most likely source location by using the time difference of arrival (TDOA) of sounds on multiple receivers. Where's Whaledo combines data from two small-aperture volumetric arrays and a variable number of individual receivers. In a case study conducted in the Tanner Basin off Southern California, we demonstrate the effectiveness of Where's Whaledo in localizing groups of Ziphius cavirostris. We reconstruct the tracks of six individual animals vocalizing concurrently and identify Ziphius cavirostris tracks despite being obscured by a large pod of vocalizing dolphins.

Navigating the unknown: assessing anthropogenic threats to beaked whales, family Ziphiidae

This review comprehensively evaluates the impacts of anthropogenic threats on beaked whales (Ziphiidae)-a taxonomic group characterized by cryptic biology, deep dives and remote offshore habitat, which have challenged direct scientific observation. By synthesizing information published in peer-reviewed studies and grey literature, we identified available evidence of impacts across 14 threats for each Ziphiidae species. Threats were assessed based on their pathways of effects on individuals, revealing many gaps in scientific understanding of the risks faced by beaked whales. By applying a comprehensive taxon-level analysis, we found evidence that all beaked whale species are affected by multiple stressors, with climate change, entanglement and plastic pollution being the most common threats documented across beaked whale species. Threats assessed as having a serious impact on individuals included whaling, military sonar, entanglement, depredation, vessel strikes, plastics and oil spills. This review emphasizes the urgent need for targeted research to address a range of uncertainties, including cumulative and population-level impacts. Understanding the evidence and pathways of the effects of stressors on individuals can support future assessments, guide practical mitigation strategies and advance current understanding of anthropogenic impacts on rare and elusive marine species.

Hector's dolphins (Cephalorhynchus hectori) produce both narrowband high-frequency and broadband acoustic signals

Odontocetes produce clicks for echolocation and communication. Most odontocetes are thought to produce either broadband (BB) or narrowband high-frequency (NBHF) clicks. Here, we show that the click repertoire of Hector's dolphin (Cephalorhynchus hectori) comprises highly stereotypical NBHF clicks and far more variable broadband clicks, with some that are intermediate between these two categories. Both NBHF and broadband clicks were made in trains, buzzes, and burst-pulses. Most clicks within click trains were typical NBHF clicks, which had a median centroid frequency of 130.3 kHz (median -10 dB bandwidth = 29.8 kHz). Some, however, while having only marginally lower centroid frequency (median = 123.8 kHz), had significant energy below 100 kHz and approximately double the bandwidth (median -10 dB bandwidth = 69.8 kHz); we refer to these as broadband. Broadband clicks in buzzes and burst-pulses had lower median centroid frequencies (120.7 and 121.8 kHz, respectively) compared to NBHF buzzes and burst-pulses (129.5 and 130.3 kHz, respectively). Source levels of NBHF clicks, estimated by using a drone to measure ranges from a single hydrophone and by computing time-of-arrival differences at a vertical hydrophone array, ranged from 116 to 171 dB re 1 μPa at 1 m, whereas source levels of broadband clicks, obtained from array data only, ranged from 138 to 184 dB re 1 μPa at 1 m. Our findings challenge the grouping of toothed whales as either NBHF or broadband species.

Bayesian detection and tracking of odontocetes in 3-D from their echolocation clicks

Localization and tracking of marine animals can reveal key insights into their behaviors underwater that would otherwise remain unexplored. A promising nonintrusive approach to obtaining location information of marine animals is to process their bioacoustic signals, which are passively recorded using multiple hydrophones. In this paper, a data processing chain that automatically detects and tracks multiple odontocetes (toothed whales) in three dimensions (3-D) from their echolocation clicks recorded with volumetric hydrophone arrays is proposed. First, the time-difference-of-arrival (TDOA) measurements are extracted with a generalized cross-correlation that whitens the received acoustic signals based on the instrument noise statistics. Subsequently, odontocetes are tracked in the TDOA domain using a graph-based multi-target tracking (MTT) method to reject false TDOA measurements and close gaps of missed detections. The resulting TDOA estimates are then used by another graph-based MTT stage that estimates odontocete tracks in 3-D. The tracking capability of the proposed data processing chain is demonstrated on real acoustic data provided by two volumetric hydrophone arrays that recorded echolocation clicks from Cuvier's beaked whales (Ziphius cavirostris). Simulation results show that the presented MTT method using 3-D can outperform an existing approach that relies on manual annotation.

Acoustic identification and classification of four dolphin species in the Brazilian marine area affected by the largest tailings dam failure disaster

Passive acoustic monitoring (PAM) is an increasingly used technique to access the occurrence, distribution, and abundance of cetaceans that may be visually unavailable most of the time. The largest tailings dam failure disaster occurred on 5 November 2015, when the Fundão dam collapsed, releasing over 50 million cubic meters of tailings into the Doce River basin; 14 days later, the tailings plume reached the Atlantic Ocean. PAM was implemented in the concerned area and cetacean species were acoustically identified. Whistles and clicks of visual and acoustic matches were used to predict and classify exclusive acoustic records through random forest models. The identified species were Guiana, rough-toothed, and bottlenose dolphins. Additionally, the franciscana, the most threatened cetacean in the western South Atlantic Ocean, was also acoustically identified. The whistle classifier had 86.9% accuracy with final frequency, duration, and maximum frequency ranked as the most important parameters. The clicks classifier had 86.7% accuracy with peak frequency and 3 dB bandwidth as the most important parameters for classifying species. Considering the potential effect of the increase in turbidity on sound transmission, such as attenuation, the presented classifier should be continuously improved with novel data collected from long-term acoustic monitoring.

Acoustic and visual cetacean surveys reveal year-round spatial and temporal distributions for multiple species in northern British Columbia, Canada

Cetaceans spend most of their time below the surface of the sea, highlighting the importance of passive acoustic monitoring as a tool to facilitate understanding and mapping their year-round spatial and temporal distributions. To increase our limited knowledge of cetacean acoustic detection patterns for the east and west coasts of Gwaii Haanas, a remote protected area on Haida Gwaii, BC, Canada, acoustic datasets recorded off SG̱ang Gwaay (Sep 2009-May 2011), Gowgaia Slope (Jul 2017-Jul 2019), and Ramsay Island (Aug 2018-Aug 2019) were analyzed. Comparing overlapping periods of visual surveys and acoustic monitoring confirmed presence of 12 cetacean species/species groups within the study region. Seasonal patterns were identified for blue, fin, humpback, grey and sperm whale acoustic signals. Killer whale and delphinid acoustic signals occurred year-round on both coasts of Haida Gwaii and showed strong diel variation. Cuvier's, Baird's, beaked whale and porpoise clicks, were identified in high-frequency recordings on the west coast. Correlations between environmental factors, chlorophyll-a and sea surface temperature, and cetacean acoustic occurrence off Gwaii Haanas were also examined. This study is the first to acoustically monitor Gwaii Haanas waters for an extended continuous period and therefore serves as a baseline from which to monitor future changes.

Ultrasonic antifouling devices negatively impact Cuvier's beaked whales near Guadalupe Island, México

Widespread use of unregulated acoustic technologies in maritime industries raises concerns about effects on acoustically sensitive marine fauna worldwide. Anthropogenic noise can disrupt behavior and may cause short- to long-term disturbance with possible population-level consequences, particularly for animals with a limited geographic range. Ultrasonic antifouling devices are commercially available, installed globally on a variety of vessel types, and are marketed as an environmentally-friendly method for biofouling control. Here we show that they can be an acoustic disturbance to marine wildlife, as seasonal operation of these hull-mounted systems by tourist vessels in the marine protected area of Guadalupe Island, México resulted in the reduced presence of a potentially resident population of Cuvier's beaked whales (Ziphius cavirostris). Human activities are rapidly altering soundscapes on local and global scales, and these findings highlight the need to identify key noise sources and assess their impacts on marine life to effectively manage oceanic ecosystems.

Identification of western North Atlantic odontocete echolocation click types using machine learning and spatiotemporal correlates

A combination of machine learning and expert analyst review was used to detect odontocete echolocation clicks, identify dominant click types, and classify clicks in 32 years of acoustic data collected at 11 autonomous monitoring sites in the western North Atlantic between 2016 and 2019. Previously-described click types for eight known odontocete species or genera were identified in this data set: Blainville's beaked whales (Mesoplodon densirostris), Cuvier's beaked whales (Ziphius cavirostris), Gervais' beaked whales (Mesoplodon europaeus), Sowerby's beaked whales (Mesoplodon bidens), and True's beaked whales (Mesoplodon mirus), Kogia spp., Risso's dolphin (Grampus griseus), and sperm whales (Physeter macrocephalus). Six novel delphinid echolocation click types were identified and named according to their median peak frequencies. Consideration of the spatiotemporal distribution of these unidentified click types, and comparison to historical sighting data, enabled assignment of the probable species identity to three of the six types, and group identity to a fourth type. UD36, UD26, and UD28 were attributed to Risso's dolphin (G. griseus), short-finned pilot whale (G. macrorhynchus), and short-beaked common dolphin (D. delphis), respectively, based on similar regional distributions and seasonal presence patterns. UD19 was attributed to one or more species in the subfamily Globicephalinae based on spectral content and signal timing. UD47 and UD38 represent distinct types for which no clear spatiotemporal match was apparent. This approach leveraged the power of big acoustic and big visual data to add to the catalog of known species-specific acoustic signals and yield new inferences about odontocete spatiotemporal distribution patterns. The tools and call types described here can be used for efficient analysis of other existing and future passive acoustic data sets from this region.

Changes in the acoustic activity of beaked whales and sperm whales recorded during a naval training exercise off eastern Canada

Experimental research has shown that beaked whales exhibit strong avoidance reactions to naval active sonars used during antisubmarine warfare training exercises, including cessation of echolocation and foraging activity. Behavioural responses to sonar have also been linked to strandings and mortality. Much of the research on the responses of beaked whales and other cetaceans to naval active sonar has occurred on or near U.S. naval training ranges, and the impacts of sonar in other regions remain poorly understood, particularly as these impacts, including mortality, are likely to go unobserved in offshore areas. In September 2016 the multinational naval exercise 'CUTLASS FURY 2016' (CF16) was conducted off eastern Canada. We used passive acoustic recordings collected in the region to quantify the occurrence and characteristics of sonar signals, measure ambient noise levels, and assess changes in the acoustic activity of beaked and sperm whales. The number of hours per day with echolocation clicks from Cuvier's beaked whales and sperm whales were significantly reduced during CF16, compared to the pre-exercise period in 2016 (sperm whales) and to control data from 2015 (both species). Clicks from an unidentified Mesoplodont beaked whale species, sporadically detected prior to CF16, were absent during the exercise and for 7 days afterward. These results suggest that beaked and sperm whales ceased foraging in the vicinity of CF16 and likely avoided the affected area. Such disturbance may have energetic, health, and fitness consequences.

Performance metrics for marine mammal signal detection and classification

Automatic algorithms for the detection and classification of sound are essential to the analysis of acoustic datasets with long duration. Metrics are needed to assess the performance characteristics of these algorithms. Four metrics for performance evaluation are discussed here: receiver-operating-characteristic (ROC) curves, detection-error-trade-off (DET) curves, precision-recall (PR) curves, and cost curves. These metrics were applied to the generalized power law detector for blue whale D calls [Helble, Ierley, D'Spain, Roch, and Hildebrand (2012). J. Acoust. Soc. Am. 131(4), 2682-2699] and the click-clustering neural-net algorithm for Cuvier's beaked whale echolocation click detection [Frasier, Roch, Soldevilla, Wiggins, Garrison, and Hildebrand (2017). PLoS Comp. Biol. 13(12), e1005823] using data prepared for the 2015 Detection, Classification, Localization and Density Estimation Workshop. Detection class imbalance, particularly the situation of rare occurrence, is common for long-term passive acoustic monitoring datasets and is a factor in the performance of ROC and DET curves with regard to the impact of false positive detections. PR curves overcome this shortcoming when calculated for individual detections and do not rely on the reporting of true negatives. Cost curves provide additional insight on the effective operating range for the detector based on the a priori probability of occurrence. Use of more than a single metric is helpful in understanding the performance of a detection algorithm.

Scale-free distribution of silences

Soundscape studies help us understand ecological processes, biodiversity distribution, anthropic influences, and even urban quality, across a wide variety of places and time periods. In this work, instead of looking for differences, we ask if there are common characteristics shared by all soundscapes. Based on our results, we propose a universal distribution of quiet-time (background noise) and sound-time (acoustic energy bursts) in audio recordings. We analyzed one continuous hour during daylight and one at night, from ten randomly selected days in each environment: urban, dry forest, savanna, rupestrian field, Atlantic forest, marine, and freshwater. We found that the histograms of the quiet-time followed a power law for all scenarios analyzed, they present fractal events or scale-free distributions. This distribution covers up to four orders of magnitude, with an exponent of 1.6≤α≤2.0 for all soundscapes. By contrast, the sound-time distribution in all environments followed a log-normal or timescale dependence, with a typical time for the duration of sounds (0.06-0.12 s). Such time duration limitation can be related to the physiology of sound emission in animals.

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.

Model-based localization of deep-diving cetaceans using towed line array acoustic data

Passive acoustic monitoring using a towed line array of hydrophones is a standard method for localizing cetaceans during line-transect cetacean abundance surveys. Perpendicular distances estimated between localized whales and the trackline are essential for abundance estimation using acoustic data. Uncertainties in the acoustic data from hydrophone movement, sound propagation effects, errors in the time of arrival differences, and whale depth are not accounted for by most two-dimensional localization methods. Consequently, location and distance estimates for deep-diving cetaceans may be biased, creating uncertainty in abundance estimates. Here, a model-based localization approach is applied to towed line array acoustic data that incorporates sound propagation effects, accounts for sources of error, and localizes in three dimensions. The whale's true distance, ship trajectory, and whale movement greatly affected localization results in simulations. The localization method was applied to real acoustic data from two separate sperm whales, resulting in three-dimensional distance and depth estimates with position bounds for each whale. By incorporating sources of error, this three-dimensional model-based approach provides a method to address and integrate the inherent uncertainties in towed array acoustic data for more robust localization.

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.

Recommended snapshot length for acoustic point-transect surveys of intermittently available Cuvier's beaked whales

Acoustic point-transect distance-sampling surveys have recently been used to estimate the density of beaked whales. Typically, the fraction of short time "snapshots" with detected beaked whales is used in this calculation. Beaked whale echolocation pulses are only intermittently available, which may affect the best choice of snapshot length. The effect of snapshot length on density estimation for Cuvier's beaked whale (Ziphius cavirostris) is investigated by sub-setting continuous recordings from drifting hydrophones deployed off southern and central California. Snapshot lengths from 20 s to 20 min are superimposed on the time series of detected beaked whale echolocation pulses, and the components of the density estimation equation are estimated for each snapshot length. The fraction of snapshots with detections, the effective area surveyed, and the snapshot detection probability all increase with snapshot length. Due to compensatory changes in these three components, density estimates show very little dependence on snapshot length. Within the range we examined, 1-2 min snapshots are recommended to avoid the potential bias caused by animal movement during the snapshot period and to maximize the sample size for estimating the effective area surveyed.

Using context to train time-domain echolocation click detectors

This work demonstrates the effectiveness of using humans in the loop processes for constructing large training sets for machine learning tasks. A corpus of over 57 000 toothed whale echolocation clicks was developed by using a permissive energy-based echolocation detector followed by a machine-assisted quality control process that exploits contextual cues. Subsets of these data were used to train feed forward neural networks that detected over 850 000 echolocation clicks that were validated using the same quality control process. It is shown that this network architecture performs well in a variety of contexts and is evaluated against a withheld data set that was collected nearly five years apart from the development data at a location over 600 km distant. The system was capable of finding echolocation bouts that were missed by human analysts, and the patterns of error in the classifier consist primarily of anthropogenic sources that were not included as counter-training examples. In the absence of such events, typical false positive rates are under ten events per hour even at low thresholds.

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.

Cetacean distribution models based on visual and passive acoustic data

Distribution models are needed to understand spatiotemporal patterns in cetacean occurrence and to mitigate anthropogenic impacts. Shipboard line-transect visual surveys are the standard method for estimating abundance and describing the distributions of cetacean populations. Ship-board surveys provide high spatial resolution but lack temporal resolution and seasonal coverage. Stationary passive acoustic monitoring (PAM) employs acoustic sensors to sample point locations nearly continuously, providing high temporal resolution in local habitats across days, seasons and years. To evaluate whether cross-platform data synthesis can improve distribution predictions, models were developed for Cuvier’s beaked whales, sperm whales, and Risso’s dolphins in the oceanic Gulf of Mexico using two different methods: generalized additive models and neural networks. Neural networks were able to learn unspecified interactions between drivers. Models that incorporated PAM datasets out-performed models trained on visual data alone, and joint models performed best in two out of three cases. The modeling results suggest that, when taken together, multiple species distribution models using a variety of data types may support conservation and management of Gulf of Mexico cetacean populations by improving the understanding of temporal and spatial species distribution trends.

Echolocation click parameters and biosonar behaviour of the dwarf sperm whale (Kogia sima)

Dwarf sperm whales (Kogia sima) are small toothed whales that produce narrow-band high-frequency (NBHF) echolocation clicks. Such NBHF clicks, subject to high levels of acoustic absorption, are usually produced by small, shallow-diving odontocetes, such as porpoises, in keeping with their short-range echolocation and fast click rates. Here, we sought to address the problem of how the little-studied and deep-diving Kogia can hunt with NBHF clicks in the deep sea. Specifically, we tested the hypotheses that Kogia produce NBHF clicks with longer inter-click intervals (ICIs), higher directionality and higher source levels (SLs) compared with other NBHF species. We did this by deploying an autonomous deep-water vertical hydrophone array in the Bahamas, where no other NBHF species are present, and by taking opportunistic recordings of a close-range Kogia sima in a South African harbour. Parameters from on-axis clicks (n=46) in the deep revealed very narrow-band clicks (root mean squared bandwidth, BW_RMS, of 3±1 kHz), with SLs of up to 197 dB re. 1 µPa peak-to-peak (μPa_pp) at 1 m, and a half-power beamwidth of 8.8 deg. Their ICIs (mode of 245 ms) were much longer than those of porpoises (<100 ms), suggesting an inspection range that is longer than detection ranges of single prey, perhaps to facilitate auditory streaming of a complex echo scene. On-axis clicks in the shallow harbour (n=870) had ICIs and SLs in keeping with source parameters of other NBHF cetaceans. Thus, in the deep, dwarf sperm whales use a directional, but short-range echolocation system with moderate SLs, suggesting a reliable mesopelagic prey habitat.

Echolocation click parameters of short-finned pilot whales (Globicephala macrorhynchus) in the wild

Short-finned pilot whales (Globicephala macrorhynchus) are large, deep-diving predators with diverse foraging strategies, but little is known about their echolocation. To quantify the source properties of short-finned pilot whale clicks, we made 15 deployments off the coast of Tenerife of a deep-water hydrophone array consisting of seven autonomous time-synced hydrophone recorders (SoundTraps), enabling acoustic localization and quantification of click source parameters. Of 8185 recorded pilot whale clicks, 47 were classified as being recorded on-axis, with a mean peak-to-peak source level (SL) of 181 ± 7 dB re 1 μPa, a centroid frequency of 40 ± 4 kHz, and a duration of 57 ± 23 μs. A fit to a piston model yielded an estimated half-power (-3 dB) beam width of 13.7° [95% confidence interval (CI) 13.2°-14.5°] and a mean directivity index (DI) of 22.6 dB (95% CI 22.5-22.9 dB). These measured SLs and DIs are surprisingly low for a deep-diving toothed whale, suggesting we sampled the short-finned pilot whales in a context with little need for operating a long-range biosonar. The substantial spectral overlap with beaked whale clicks emitted in similar deep-water habitats implies that pilot whale clicks may constitute a common source of false detections in beaked whale passive acoustic monitoring efforts.

Acoustic detection range and population density of Cuvier's beaked whales estimated from near-surface hydrophones

The population density of Cuvier's beaked whales is estimated acoustically with drifting near-surface hydrophone recorders in the Catalina Basin. Three empirical approaches (trial-based, distance-sampling, and spatially explicit capture-recapture) are used to estimate the probability of detecting the echolocation pulses as a function of range. These detection functions are used with two point-transect methods (snapshot and dive-cue) to estimate density. Measurement errors result in a small range of density estimates (3.9-5.4 whales per 1000 km²). Use of multiple approaches and methods allows comparison of the required information and assumptions of each. The distance-sampling approach with snapshot-based density estimates has the most stringent assumptions but would be the easiest to implement for large scale surveys of beaked whale density. Alternative approaches to estimating detection functions help validate this approach. The dive cue method of density estimation has promise, but additional work is needed to understand the potential bias caused by animal movement during a dive. Empirical methods are a viable alternative to the theoretical acoustic modeling approaches that have been used previously to estimate beaked whale density.

First live sighting of Deraniyagala's beaked whale (Mesoplodon hotaula) or ginkgo-toothed beaked whale (Mesoplodon ginkgodens) in the western Pacific (South China Sea) with preliminary data on coloration, natural markings, and surfacing patterns

Beaked whales represent around 25% of known extant cetacean species, yet they are the least known of all marine mammals. Identification of many Mesoplodon species has relied on examination of a few stranded individuals. Particularly, the ginkgo-toothed beaked whale (Mesoplodon ginkgodens) and Deraniyagala's beaked whale (Mesoplodon hotaula) are among the least-known of beaked whale species, without confirmed sightings of living individuals to date. We present a sighting of 3 free-ranging individuals of M. ginkgodens/hotaula whale from a dedicated marine mammal vessel survey carried out in the South China Sea in April and May 2019. Photographic data (301 photographs) from the sighting were compared to photos of fresh stranded ginkgo-toothed beaked whale and Deraniyagala's beaked whale from both historical and unpublished records. We found that free-ranging M. ginkgodens and M. hotaula individuals can be easily distinguished from other Mesoplodon species due to differences in melon and gape shapes and coloration patterns. However, accurate at-sea differentiation of M. ginkgodens and M. hotaula may not be possible due to high similarity in both coloration and scarring patterns. In addition to our photo-identification data, we collected what we believe to be the first preliminary descriptions of surfacing behavior and diving patterns of one of these species. Finally, the presence of scars possibly caused by fishing gear or marine litter raises concerns about anthropogenic impacts and conservation of these poorly known species.

Listening forward: approaching marine biodiversity assessments using acoustic methods

Ecosystems and the communities they support are changing at alarmingly rapid rates. Tracking species diversity is vital to managing these stressed habitats. Yet, quantifying and monitoring biodiversity is often challenging, especially in ocean habitats. Given that many animals make sounds, these cues travel efficiently under water, and emerging technologies are increasingly cost-effective, passive acoustics (a long-standing ocean observation method) is now a potential means of quantifying and monitoring marine biodiversity. Properly applying acoustics for biodiversity assessments is vital. Our goal here is to provide a timely consideration of emerging methods using passive acoustics to measure marine biodiversity. We provide a summary of the brief history of using passive acoustics to assess marine biodiversity and community structure, a critical assessment of the challenges faced, and outline recommended practices and considerations for acoustic biodiversity measurements. We focused on temperate and tropical seas, where much of the acoustic biodiversity work has been conducted. Overall, we suggest a cautious approach to applying current acoustic indices to assess marine biodiversity. Key needs are preliminary data and sampling sufficiently to capture the patterns and variability of a habitat. Yet with new analytical tools including source separation and supervised machine learning, there is substantial promise in marine acoustic diversity assessment methods.

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.

Modeling the acoustic repertoire of Cuvier's beaked whale clicks

This paper investigates the evolution of spectral properties observed in Cuvier's beaked whale (Ziphius cavirostris) click trains recorded by fixed hydrophones in the Gulf of Mexico. In the context of deep water and high-frequency sounds and observed inter-click intervals, the authors assumed that the main effect responsible for the modification of the spectral content between adjacent clicks in the same click train is the source beam pattern. The spectral structure is studied by using the Wigner-Ville time-frequency distribution and is compared with the conventional Fourier spectrogram. The results show that the observed Cuvier's beaked whale clicks are a superposition of upsweep and downsweep chirps, unlike the currently accepted upsweep only structure of beaked whale clicks in bioacoustics literature. The spectral structure variations simulated by using a flat circular piston model as a beam pattern transmission model are consistent with the evolution of spectral click properties observed in experimental data. A better understanding of the properties of observed echolocation clicks of Cuvier's beaked whales will provide useful information for click annotations and, therefore, will contribute to improving accuracy of detecting, classifying, tracking, and estimating the density of Cuvier's beaked whales.

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.

Click characteristics of northern bottlenose whales (Hyperoodon ampullatus) and Sowerby's beaked whales (Mesoplodon bidens) off eastern Canada

Passive acoustic monitoring (PAM) is crucial to expanding the knowledge of beaked whales, including the northern bottlenose whale (Hyperoodon ampullatus) and Sowerby's beaked whale (Mesoplodon bidens). Existing descriptions of clicks produced by these species are limited by sample size, number of individuals recorded, and geographic scope. Data from multiple encounters in the western North Atlantic are used to provide a quantitative description of clicks produced by these species. Recordings from nine encounters with northern bottlenose whales in Nova Scotia and Newfoundland were analyzed (N = 2239 clicks). The click type described had a median peak frequency of 25.9 kHz (10th-90th percentile range: 22.9-29.3 kHz), and a median inter-click interval (ICI) of 402 ms (N = 1917, 10th-90th percentile range: 290-524 ms). Recordings from 18 Sowerby's beaked whale encounters from Nova Scotia were analyzed (N = 762 clicks). The click type described had a median peak frequency of 65.8 kHz (10th-90th percentile range: 61.5-76.5 kHz), and a median ICI of 237 ms (N = 677, 10th-90th percentile range: 130-315 ms). These results will contribute to the development of methods to detect and classify beaked whale clicks to the species level, improving the effectiveness of PAM and enhancing scientific understanding and conservation efforts for cryptic and at-risk cetaceans.

Integrative bioacoustics discrimination of eight delphinid species in the western South Atlantic Ocean

This study presents an integrative bioacoustics approach to discriminate eight species of odontocetes found on the outer continental shelf and slope of the western South Atlantic Ocean. Spinner, Atlantic spotted, rough-toothed, Risso's, bottlenose, short-beaked common dolphins, killer and long-finned pilot whales were visually confirmed during recordings with a 3-element omnidirectional hydrophone array. Spectral and time parameters of whistles and echolocation clicks were used in a discriminant function analysis and a classification tree model. As a first step, whistles and clicks were analysed separately; a further analysis consisted of both vocalisations jointly classified. All species showed species-specific properties in their vocalisations. Whistles had greater misclassification rates when compared to clicks. The correct classification was enhanced by the joint step, given the 5.8% error in the discriminant function analysis and a misclassification rate of 18.8% in the tree model. In addition, Receiver Operating Characteristic curves resulting from the tree algorithm analysis exhibited better model efficiency for all species in the joint classification. These findings on acoustical discrimination of such abundant and cosmopolitan species contribute to delphinid classification systems.

Automatic detection, classification, and quantification of sciaenid fish calls in an estuarine soundscape in the Southeast United States

In the Southeast USA, major contributors to estuarine soundscapes are the courtship calls produced by fish species belonging to the family Sciaenidae. Long-term monitoring of sciaenid courtship sounds may be valuable in understanding reproductive phenology, but this approach produces massive acoustic datasets. With this in mind, we designed a feature-based, signal detector for sciaenid fish calls and tested the efficacy of this detector against manually reviewed data. Acoustic recorders were deployed to collect sound samples for 2 min every 20 min at four stations in the May River estuary, South Carolina, USA from February to November, 2014. Manual analysis of acoustic files revealed that four fish species, belonging to the family Sciaenidae, were the major sound producers in this estuarine soundscape, and included black drum (Pogonias cromis), silver perch (Bairdiella chrysoura), spotted seatrout (Cynoscion nebulosus), and red drum (Sciaenops ocellatus). Recorded calls served as an acoustic library of signature features that were used to create a signal detector to automatically detect, classify, and quantify the number of calls in each acoustic file. Correlation between manual and automatic detection was significant and precision varied from 61% to 100%. Automatic detection provided quantitative data on calling rates for this long-term data set. Positive temperature anomalies increased calling rates of black drum, silver perch, and spotted seatrout, while negative anomalies increased calling rates of red drum. Acoustic monitoring combined with automatic detection could be an additional or alternative method for monitoring sciaenid spawning and changes in phenology associated with climate change.

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.

Species-level classification of beaked whale echolocation signals detected in the northern Gulf of Mexico

This study presents and evaluates several methods for automated species-level classification of echolocation clicks from three beaked whale species recorded in the northern Gulf of Mexico. The species included are Cuvier's and Gervais' beaked whales, as well as an unknown species denoted Beaked Whale Gulf. An optimal feature set for discriminating the three click types while also separating detected clicks from unidentified delphinids was determined using supervised step-wise discriminant analysis. Linear and quadratic discriminant analyses both achieved error rates below 1% with three features, determined by tenfold cross validation. The waveform fractal dimension was found to be a highly ranked feature among standard spectral and temporal parameters. The top-ranking features were Higuchi's fractal dimension, spectral centroid, Katz's fractal dimension, and -10 dB duration. Six clustering routines, including four popular network-based algorithms, were also evaluated as unsupervised classification methods using the selected feature set. False positive rates of 0.001 and 0.024 were achieved by Chinese Whispers and spectral clustering, respectively, across 200 randomized trials. However, Chinese Whispers clustering yielded larger false negative rates. Spectral clustering was further tested on clicks from encounters of beaked, sperm, and pilot whales in the Tongue of the Ocean, Bahamas.

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.

Automated classification of dolphin echolocation click types from the Gulf of Mexico

Delphinids produce large numbers of short duration, broadband echolocation clicks which may be useful for species classification in passive acoustic monitoring efforts. A challenge in echolocation click classification is to overcome the many sources of variability to recognize underlying patterns across many detections. An automated unsupervised network-based classification method was developed to simulate the approach a human analyst uses when categorizing click types: Clusters of similar clicks were identified by incorporating multiple click characteristics (spectral shape and inter-click interval distributions) to distinguish within-type from between-type variation, and identify distinct, persistent click types. Once click types were established, an algorithm for classifying novel detections using existing clusters was tested. The automated classification method was applied to a dataset of 52 million clicks detected across five monitoring sites over two years in the Gulf of Mexico (GOM). Seven distinct click types were identified, one of which is known to be associated with an acoustically identifiable delphinid (Risso’s dolphin) and six of which are not yet identified. All types occurred at multiple monitoring locations, but the relative occurrence of types varied, particularly between continental shelf and slope locations. Automatically-identified click types from autonomous seafloor recorders without verifiable species identification were compared with clicks detected on sea-surface towed hydrophone arrays in the presence of visually identified delphinid species. These comparisons suggest potential species identities for the animals producing some echolocation click types. The network-based classification method presented here is effective for rapid, unsupervised delphinid click classification across large datasets in which the click types may not be known a priori.

Health of marine mammal populations is often considered an indicator of overall marine ecosystem health and resilience, particularly in highly-impacted regions such as the Gulf of Mexico. Marine mammal populations are difficult to monitor given the many challenges of observing animals at sea (e.g. weather, limited daylight, ocean conditions, and expense). An increasingly common approach is the use of underwater acoustic sensors capable of recording marine mammal calls at remote locations for months at a time. Acoustic sensors generate large datasets in which dolphin echolocation clicks are commonly present. Dolphins are the most diverse family of marine mammals, and distinguishing click characteristics have only been described for a small subset of species. We developed a workflow to automatically identify distinct dolphin click types within large datasets without prior knowledge of their distinguishing features. Our algorithm then recognizes these click types in novel recording data across a range of monitoring locations. Known species-specific click types emerge from the data using this approach, as well as new click types potentially associated with additional species. This technique is a key step toward determining species identification for passive acoustic monitoring of offshore populations of dolphins and other toothed whales under a big data paradigm.

Categorizing click trains to increase taxonomic precision in echolocation click loggers

Passive acoustic monitoring is an efficient way to study acoustically active animals but species identification remains a major challenge. C-PODs are popular logging devices that automatically detect odontocete echolocation clicks. However, the accompanying analysis software does not distinguish between delphinid species. Click train features logged by C-PODs were compared to frequency spectra from adjacently deployed continuous recorders. A generalized additive model was then used to categorize C-POD click trains into three groups: broadband click trains, produced by bottlenose dolphin (Tursiops truncatus) or common dolphin (Delphinus delphis), frequency-banded click trains, produced by Risso's (Grampus griseus) or white beaked dolphins (Lagenorhynchus albirostris), and unknown click trains. Incorrect categorization rates for broadband and frequency banded clicks were 0.02 (SD 0.01), but only 30% of the click trains met the categorization threshold. To increase the proportion of categorized click trains, model predictions were pooled within acoustic encounters and a likelihood ratio threshold was used to categorize encounters. This increased the proportion of the click trains meeting either the broadband or frequency banded categorization threshold to 98%. Predicted species distribution at the 30 study sites matched well to visual sighting records from the region.

Using multipath reflections to obtain dive depths of beaked whales from a towed hydrophone array

Beaked whales are deep divers, emitting echolocation clicks while at depth. Little is known about the dive behavior of most species; however, passive acoustic data collected with towed hydrophone arrays can provide depth information using multipath reflections of clicks coupled with a two-dimensional localization of the individual. Data were collected during a shipboard survey in the western North Atlantic Ocean using a towed linear hydrophone array. Beaked whale tracks were classified as either Cuvier's (Ziphius cavirostris) or Gervais'/True's (Mesoplodon europaeus/Mesoplodon mirus). Weighted species average depths and weighted species standard deviations were 1158 m ± 287 m for Cuvier's (n = 24), and 870 m ± 151 m for Gervais'/True's (n = 15). Depth uncertainties ranged from 3% to 142% of the average depth. Slant ranges were corrected for depth to provide average horizontal perpendicular distance estimates. The average horizontal perpendicular distance distribution exhibited fewer detections in the first bin than the second. This is the first report of dive depths for Gervais'/True's beaked whales and use of this method to obtain depths for beaked whales using a towed linear array.

Geographic variation in Risso's dolphin echolocation click spectra

Discrimination of bioacoustic signals to the species or population level is critical for using passive acoustic monitoring to study cetacean ecology. Risso's dolphins off southern California have distinctive peaks and notches in their echolocation clicks, but it was unknown whether Risso's dolphins from other geographic areas have similarly distinctive click spectra and whether populations are acoustically distinct. This study investigates using clicks for species and population identification by characterizing the spectral structure of Risso's dolphin echolocation clicks recorded over wide-ranging geographic regions including the U.S. waters of the North Atlantic Ocean, Gulf of Mexico, and North Pacific Ocean; and international waters of the Eastern Tropical Pacific. All recordings with Risso's dolphin clicks exhibited the spectral peak and notch pattern described off southern California, indicating the presence of peak banding patterns is useful for species discrimination. Geographic regions were a significant explanatory factor for variability in the frequencies of click spectral peaks, with relatively higher frequency peaks and notches found off Hawaii compared to California waters and off the southeast U.S. compared to the Gulf of Mexico. In the North Atlantic Ocean, a latitudinal cline in frequencies was evident. Potential causes of acoustic variation within and among acoustic encounters are evaluated.

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.