Risso’s dolphins (Grampus griseus) produce broadband echolocation clicks that vary across regions, offering insight into population structure and habitat use. Two stocks are recognized in U.S. Pacific waters: the California–Oregon–Washington stock and the Hawaiian stock, but these designations may overlook finer-scale structure within the California Current Ecosystem (CCE). Building on evidence of geographic variation in Risso’s dolphin echolocation click types across the U.S. East Coast, Gulf of Mexico, Southern California Bight, and Hawaiian Islands, spectral peak and notch frequencies were measured from Risso’s dolphin echolocation clicks during three NOAA surveys between 2016 and 2023. Acoustic recordings were collected with drifting buoys, allowing broad coverage of the entire CCE region along the U.S. West Coast. Clustering of spectral features highlighted several different click types. We compared spatio-temporal variation in Risso’s click types across Oregon, Northern California, and Central California, including seasonal and diel variation. These results provide the first comprehensive assessment of Risso’s dolphin click characteristics across the CCE and enable comparison with other U.S. regions where click-type divergence has been observed. Fine-scale spatial, seasonal, and diel acoustic patterns can inform population assessment, ecological understanding, and ecosystem-based management.

Recent research suggests that toothed whales possess anatomical specializations enabling lateralized register vibrations, contribute to a rich and complex vocal repertoire. Along with vocal learning abilities, this indicates that their communication systems may be among the most complex in the animal kingdom. However, the evolutionary processes shaping vocal repertoire complexity remain unclear due to the lack of standardized, quantitative analyses of their vocal signals. This study addresses that gap by examining the tonal sound repertoires of 15 toothed whale species representing major evolutionary lineages. Using acoustic data from the Watkins database and from the authors, 500 tonal contours were randomly selected per species. These were analyzed to generate measures of vocal diversity (Hill numbers), composition (contour types), complexity (modulation patterns), and acoustic structure (frequency and duration). Trait reconstructions using Maximum Likelihood methods were used to identify patterns of convergence and divergence across species. Preliminary results show that high-frequency, diverse, and complex repertoires are most common among Delphinidae species, especially those living in fission–fusion societies where vocal communication supports social cohesion. The study also accounts for sampling bias and missing data. These preliminary findings represent a first step toward reconstructing the macroevolutionary history of vocal repertoire traits in toothed whales.

The International Whaling Commission (IWC) carried out blue whale research within its annual Southern Ocean Whale and Ecosystem Research (SOWER) cruises between 1996 and 2010. Over 700 sonobuoys were deployed to record blue whale vocalisations during 11 Antarctic and three low‐latitude blue whale cruises off Australia, Madagascar and Chile. The recorded acoustic files from Antarctic deployments were collated and reviewed to develop a database of digital acoustic files and the associated deployment station metadata of 7,486 acoustic files from 484 stations. Acoustic files were analysed using the automated detection template and visual verification method. We found a significant difference between the total number of acoustic recording hours (2,481) reported in the associated cruise reports and the currently available number of acoustic recording hours (1,541). Antarctic blue whale vocalisations (9,315 D‐calls and 24,902 Z‐calls) were detected on 4,183 out of the total 7,486 acoustic files. December had the lowest call rates; January and February yielded high call rates. While most sonobuoys (63%) were deployed between 1800hrs and 0600hrs, the majority of calls (62%) were detected during observation periods between 0600hrs and 1800hrs. The difference between the available and reported data is a significant concern. Reconciliation of these and any future IWC acoustic data is strongly recommended.

Passive acoustic monitoring is increasingly used for assessing populations of marine mammals; however, analysis of large datasets is limited by our ability to easily classify sounds detected. Classification of beaked whale acoustic events, in particular, requires evaluation of multiple lines of evidence by expert analysts. Here we present a highly automated approach to acoustic detection and classification using supervised machine learning and open source software methods. Data from four large scale surveys of beaked whales (northwestern North Atlantic, southwestern North Atlantic, Hawaii, and eastern North Pacific) were analyzed using PAMGuard (acoustic detection), PAMpal (acoustic analysis) and BANTER (hierarchical random forest classifier). Overall classification accuracy ranged from 88% for the southwestern North Atlantic data to 97% for the northwestern North Atlantic. Results for many species could likely be improved with increased sample sizes, consideration of alternative automated detectors, and addition of relevant environmental features. These methods provide a highly automated approach to acoustic detection and classification using open source methods that can be readily adopted for other species and geographic regions.

Blue whale vocalisations recorded during the 2001/2002 and 2002/2003 International Whaling Commission-Southern Ocean Whale and Ecosystem Research (IWC/SOWER) cruises were analysed to determine the feasibility of using acoustic recordings for sub-species identification of the Antarctic blue whale (Balaenoptera musculus intermedia) and the pygmy blue whale (B.m. brevicauda). The research was conducted in IWC Area V, from latitude 60°S to the ice edge and between longitudes 130°E and 150°E on the Shonan Maru (2001/2002), and between 150°E and 170°W on the Shonan Maru No.2 (2002/2003). Data including 15 groups consisting of 42 animals, as well as opportunistic recordings of an unknown number of animals during evening sonobuoy stations were examined for this study. Vocalisations included long-duration 28Hz tonal sounds and relatively short-duration frequency-modulated sounds. The short-duration calls were similar to vocalisations recorded in the presence of blue whales in other locations worldwide. Not all recordings contained the longduration 28Hz call, considered to be a species-specific vocalisation of Antarctic blue whales. None of the sounds that have previously been attributed to pygmy blue whales were detected. The long-duration 28Hz tonal vocalisations included 3-unit calls, considered to be song phrases, as well as simple 28Hz sounds and 28Hz sounds followed by a downsweep. The centre and peak frequencies of the 28Hz tone for these three sound types were stable regardless of signal strength; however, for the 3-unit vocalisation, the presence and characteristics of their 2nd and 3rd units were variable. Examination of two distinct groups of simultaneously vocalising blue whales showed no evidence of temporally repeated patterns of vocalisations (song phrases). The results of this study suggest that the peak frequency of the 28Hz vocalisations may be used as a diagnostic feature to aid in discriminating between Antarctic blue whales and pygmy blue whales in the field; however, examination of vocalisations in relation to group size and behaviour are necessary to understand the circumstances in which the 28Hz vocalisations are produced.

While most animal behavior researchers have mastered the process of knowledge creation, generating knowledge that can readily be applied requires a different set of skills. The process and timeframe of fundamental scientific knowledge production is often not relevant to those who might apply it, such as conservation or wildlife managers. Additionally, the complex challenges that policy makers, managers and practitioners face are often not adequately communicated to and among scientists. This mutual disconnect in discourse, relationships, common terms, and practices is especially apparent when animal behavior researchers seek to have applied impact. We argue that bridging the complex implementation gap in animal behavior requires a formalized vision for change. We turn to change model theory, a tool commonly used in other fields for identifying the links between actions and outcomes necessary for enacting large-scale change. We focus on the subfield of conservation behavior with a change model that outlines specific ways to improve collaboration and coordination between animal behavior science and conservation practice. We present this targeted change model, review each strategy the model outlines, and highlight pressing actions that people from various career stages and backgrounds can take. We encourage researchers to further the alignment of science with management needs by developing the proper communication mechanisms for improved cultural exchange and plan future change model efforts directly targeting managers. Beyond the conservation behavior change model we present, we also discuss the broad applicability of change models to enhance the application of academic research to other fields. Fundamental science researchers are increasingly required to show impact of their work on society; the change model process we describe here can enable further impact.

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.

Belugas ( Delphinapterus leucas ) and narwhals ( Monodon monoceros ) are highly social Arctic toothed whales with large vocal repertoires and similar acoustic profiles. Passive Acoustic Monitoring (PAM) that uses multiple hydrophones over large spatiotemporal scales has been a primary method to study their populations, particularly in response to rapid climate change and increasing underwater noise. This study marks the first acoustic comparison between wild belugas and narwhals from the same location and reveals that they can be acoustically differentiated and classified solely by echolocation clicks. Acoustic recordings were made in the pack ice of Baffin Bay, West Greenland, during 2013. Multivariate analyses and Random Forests classification models were applied to eighty-one single-species acoustic events comprised of numerous echolocation clicks. Results demonstrate a significant difference between species’ acoustic parameters where beluga echolocation was distinguished by higher frequency content, evidenced by higher peak frequencies, center frequencies, and frequency minimums and maximums. Spectral peaks, troughs, and center frequencies for beluga clicks were generally > 60 kHz and narwhal clicks < 60 kHz with overlap between 40–60 kHz. Classification model predictive performance was strong with an overall correct classification rate of 97.5% for the best model. The most important predictors for species assignment were defined by peaks and notches in frequency spectra. Our results provide strong support for the use of echolocation in PAM efforts to differentiate belugas and narwhals acoustically.

In order to help develop hypotheses of connectivity among North Pacific fin whales, we examine recordings from 10 regions collected in the spring and fall. We develop a Random Forest model to classify fin whale note types that avoids manual note classification errors. We also present a method that objectively quantifies the note and pattern composition of recordings. We find that fin whale recordings near Hawaii have distinctive patterns, similar to those found in other regions in the central North Pacific, suggesting potential migration pathways. Our results are consistent with previous studies that suggest there may be two different populations utilizing the Chukchi Sea and central Aleutians in the fall and mix to some degree in the southern Bering Sea. Conversely, we found little difference between spring and fall recordings in the eastern Gulf of Alaska, suggesting some residency of whales in this region. This is likely due to fine scale similarities of calls among the inshore regions of British Columbia, while offshore areas are being utilized by whales traveling from various distant areas. This study shows how our novel approach to characterize recordings is an objective and informative way to standardize spatial and temporal comparisons of fin whale recordings.

In the California Current off the United States West Coast, there are three offshore cetacean species that produce narrow-band high frequency (NBHF) echolocation pulses: Dall's porpoise (Phocoenoides dalli) and two species of Kogia. NBHF pulses exist in a highly specialized acoustic niche thought to be outside the hearing range of killer whales and other potential mammal-eating odontocetes. Very little is known about the dwarf and pygmy sperm whales (K. sima and K. breviceps), including their NBHF pulse characteristics. This paper presents a multivariate clustering method using data from unmanned drifting acoustic recorders and visually verified porpoise recordings to discriminate between probable porpoise and Kogia clicks. Using density clustering, this study finds three distinct clusters whose geographic distributions are consistent with the known habitat range for Kogia and Dall's porpoise. A Random Forest classification model correctly assigned 97% of the clicks to their cluster. Visually verified Dall's porpoise clicks from towed hydrophones were strongly associated with one of the clusters, while a second cluster tended to be outside the geographic range of Dall's porpoise and unlike the Dall's porpoise cluster. These clicks, presumed to be made by Kogia, exhibited greater spectral variance than previous Kogia echolocation studies. It is possible that the structure of Kogia NBHF pulses may not be as stereotypical as previously described.

Anthropogenic noise is a known threat to marine mammals. Decades of research have shown that harbor porpoises are particularly sensitive to anthropogenic noise, and geographic displacement is a common impact from noise exposure. Small, localized populations may be particularly vulnerable to impacts associated with displacement, as animals that are excluded from their primary habitat may have reduced foraging success and survival, or be exposed to increased threats of predation or bycatch. Seal bombs are underwater explosives used in purse seine fisheries to deter marine mammals during fishery operations. Pinnipeds are believed to be the primary target for seal bomb use, however there may be indirect impacts on harbor porpoises. Active purse seine fishing using seal bombs in the greater Monterey Bay area may, at times, span the entire range of the Monterey Bay harbor porpoise stock, which may lead to negative impacts for this population. In this contribution, we review anthropogenic noise as a threat to harbor porpoises, with a focus on the potential for impacts from seal bomb noise exposure in the Monterey Bay region.

Cetacean abundance estimation often relies on distance sampling methods using shipboard visual line-transect surveys, which assumes that all animals on the trackline are detected and that the detection of animals decreases with increasing distance from the trackline. Mark–Recapture Distance Sampling (MRDS) typically employs a secondary visual observation team and may be used to identify the fraction of animals detected on the trackline when it is suspected that animals may have been missed. For species that are difficult to detect using visual observation methods, such as deep-diving species or those with cryptic surfacing behavior, this secondary team may be prone to the same limitations in detection as the primary observation team and alternative modes of detection may improve estimates. Here we examine the potential use of passive acoustic detection as a secondary platform for MRDS of rough-toothed dolphins (Steno bredanensis) during a combined visual and acoustic shipboard line-transect survey. The average trackline detection probability for rough-toothed dolphins was less than one for both the trial configuration (average $$ p\left( 0 \right) = 0.45 $$ for the visual team) and independent observer configuration (average $$ p\left( 0 \right) = 0.37 $$ for the visual, $$ p\left( 0 \right) = 0.77 $$ for the acoustic and $$ p\left( 0 \right) = 0.84 $$ for both teams combined). This study, while limited in scope, strongly suggests that passive acoustic methods may be an effective alternative for estimating $$ p\left( 0 \right) $$ for some cetaceans species.

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

A maximum likelihood method is presented for estimating drift direction and speed of a directional sonobuoy given the deployment location and a time series of acoustic bearings to a sound source at known position. The viability of this method is demonstrated by applying it to two real-world scenarios: (1) during a calibration trial where buoys were independently tracked via satellite, and (2) by applying the technique to sonobuoy recordings of a vocalising Antarctic blue whale that was simultaneously tracked by photogrammetric methods. In both test cases, correcting for sonobuoy drift substantially increased the accuracy of acoustic locations.

Passive acoustic monitoring of dolphins is limited by our ability to classify calls to species. Significant overlap in call characteristics among many species, combined with a wide range of call types and acoustic behavior, makes classification of calls to species challenging. Here, we introduce BANTER, a compound acoustic classification method for dolphins that utilizes information from all call types produced by dolphins rather than a single call type, as has been typical for acoustic classifiers. Output from the passive acoustic monitoring software, PAMGuard, was used to create independent classifiers for whistles, echolocation clicks, and burst pulses, which were then merged into a final, compound classifier for each species. Classifiers for five species found in the California Current ecosystem were trained and tested using 153 single-species acoustic events recorded during a 4.5 mo combined visual and acoustic shipboard cetacean survey off the west coast of the United States. Correct classification scores for individual species ranged from 71% to 92%, with an overall correct classification score of 84% for all five species. The conceptual framework of this approach easily lends itself to other species and study areas as well as to noncetacean taxa.

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.

The following document presents the result of a project aimed at improving the hydrodynamics of the volumetric array design for towing at faster speeds of 10 knots from large research vessels. The document explains the theory behind the design considerations for each prototype presented, sea trial results and subsequent modifications, and discuss improvements for future designs.

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.