Sperm whale demographics in the Gulf of Alaska and Bering Sea/Aleutian Islands: An overlooked female habitat.

Sperm whales exhibit sexual dimorphism and sex-specific latitudinal segregation. Females and their young form social groups and are usually found in temperate and tropical latitudes, while males forage at higher latitudes. Historical whaling data and rare sightings of social groups in high latitude regions of the North Pacific, such as the Gulf of Alaska (GOA) and Bering Sea/Aleutian Islands (BSAI), suggest a more complex distribution than previously understood. Sperm whales are the most sighted and recorded cetacean in marine mammal surveys in these regions but capturing their demographic composition and habitat use has proven challenging. This study detects sperm whale presence using passive acoustic data from seven sites in the GOA and BSAI from 2010 to 2019. Differences in click characteristics between males and females (i.e., inter-click and inter-pulse interval) was used as a proxy for animal size/sex to derive time series of animal detections. Generalized additive models with generalized estimation equations demonstrate how spatiotemporal patterns differ between the sexes. Social groups were present at all recording sites with the largest relative proportion at two seamount sites in the GOA and an island site in the BSAI. We found that the seasonal patterns of presence varied for the sexes and between the sites. Male presence was highest in the summer and lowest in the winter, conversely, social group peak presence was in the winter for the BSAI and in the spring for the GOA region, with the lowest presence in the summer months. This study demonstrates that social groups are not restricted to lower latitudes and capture their present-day habitat use in the North Pacific. It highlights that sperm whale distribution is more complex than accounted for in management protocol and underscores the need for improved understanding of sperm whale demographic composition to better understand the impacts of increasing anthropogenic threats, particularly climate change.

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.

Comparing pre-industrial and modern ocean noise levels in the Santa Barbara Channel.

To understand the extent of anthropogenic noise in the ocean, it is essential to compare the differences between modern noise environments and their pre-industrial equivalents. The Santa Barbara Channel, off the coast of Southern California, is a corridor for the transportation of goods to and from the busiest shipping ports in the Western hemisphere. Commercial ships introduce high levels of underwater noise into the marine environment. To quantify the extent of noise in the region, we modeled pre-industrial ocean noise levels, driven by wind, and modern ocean noise levels, resulting from the presence of both ships and wind. By comparing pre-industrial and modern underwater noise levels, the low-frequency (50 Hz) acoustic environment was found to be degraded by more than 15 dB. These results can be used to identify regions for noise reduction efforts, as well as to model scenarios to identify those with the greatest potential to support marine conservation efforts.

Resonance of the tympanoperiotic complex of fin whales with implications for their low frequency hearing.

The tympanoperiotic complex (TPC) bones of the fin whale skull were studied using experimental measurements and simulation modeling to provide insight into the low frequency hearing of these animals. The study focused on measuring the sounds emitted by the left and right TPC bones when the bones were tapped at designated locations. Radiated sound was recorded by eight microphones arranged around the tympanic bulla. A finite element model was also created to simulate the natural mode vibrations of the TPC and ossicular chain, using a 3D mesh generated from a CT scan. The simulations produced mode shapes and frequencies for various Young's modulus and density values. The recorded sound amplitudes were compared with the normal component of the simulated displacement and it was found that the modes identified in the experiment most closely resembled those found with Young's modulus for stiff and flexible bone set to 25 and 5 GPa, respectively. The first twelve modes of vibration of the TPC had resonance frequencies between 100Hz and 6kHz. Many vibrational modes focused energy at the sigmoidal process, and therefore the ossicular chain. The resonance frequencies of the left and right TPC were offset, suggesting a mechanism for the animals to have improved hearing at a range of frequencies as well as a mechanism for directionality in their perception of sounds.

Impact of ship noise on the underwater soundscape of Eclipse Sound in the northeastern Canadian Arctic.

Eclipse Sound, in the northeastern Canadian Arctic, has experienced a substantial increase in ship traffic due to growing tourism and industrial development in the region. This study aims to describe the natural soundscape as well as to assess the noise levels associated with shipping. Underwater sound recordings were collected at two locations: Eastern Eclipse Sound (72° 43.730 N, 76° 13.519 W, 670 m) leading to Baffin Bay, and Milne Inlet (72° 15.260 N, 80° 34.205 W, 313 m) situated near the southwest end of Eclipse Sound. To capture the dynamic nature of the soundscape, the data from these two locations were divided into three seasons: late spring, summer, and early fall. These periods were selected to account for the changing contribution of sea ice to the soundscape during the sea ice break-up, two months of open water, and the sea ice freeze-up. By analyzing ship tracks and underwater acoustic recordings, we identified patterns of ship traffic and estimated underwater noise levels due to ships. Noise emitted by ships is quantified by vessel type, including three cargo ship types, passenger ships, pleasure craft, and icebreakers. Individual ship transits through the region introduce transient noise at frequencies from <20 Hz to >20 kHz, with durations lasting from a few minutes to >6 h. The impact of ship noise on the soundscape is significant, resulting in increases in sound levels by 15 to >30 dB when ships are within 10 km and measurable ship noise below 200 Hz at distances of >50 km.

Kinematics and energetics of foraging behavior in Rice's whales of the Gulf of Mexico.

Rorqual foraging behavior varies with species, prey type and foraging conditions, and can be a determining factor for their fitness. Little is known about the foraging ecology of Rice's whales (Balaenoptera ricei), an endangered species with a population of fewer than 100 individuals. Suction cup tags were attached to two Rice's whales to collect information on their diving kinematics and foraging behavior. The tagged whales primarily exhibited lunge-feeding near the sea bottom and to a lesser extent in the water-column and at the sea surface. During 6-10 min foraging dives, the whales typically circled their prey before executing one or two feeding lunges. Longer duration dives and dives with more feeding-lunges were followed by an increase in their breathing rate. The median lunge rate of one lunge per dive of both animals was much lower than expected based on comparative research on other lunge-feeding baleen whales, and may be associated with foraging on fish instead of krill or may be an indication of different foraging conditions. Both animals spent extended periods of the night near the sea surface, increasing the risk for ship strike. Furthermore, their circling before lunging may increase the risk for entanglement in bottom-longline fishing gear. Overall, these data show that Rice's whale foraging behavior differs from other lunge feeding rorqual species and may be a significant factor in shaping our understanding of their foraging ecology. Efforts to mitigate threats to Rice's whales will benefit from improved understanding of patterns in their habitat use and fine-scale ecology.

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.

Retrofit-induced changes in the radiated noise and monopole source levels of container ships.

The container shipping line Maersk undertook a Radical Retrofit to improve the energy efficiency of twelve sister container ships. Noise reduction, identified as a potential added benefit of the retrofitting effort, was investigated in this study. A passive acoustic recording dataset from the Santa Barbara Channel off Southern California was used to compile over 100 opportunistic vessel transits of the twelve G-Class container ships, pre- and post-retrofit. Post-retrofit, the G-Class vessels' capacity was increased from ~9,000 twenty-foot equivalent units (TEUs) to ~11,000 TEUs, which required a draft increase of the vessel by 1.5 m on average. The increased vessel draft resulted in higher radiated noise levels (<2 dB) in the mid- and high-frequency bands. Accounting for the Lloyd's mirror (dipole source) effect, the monopole source levels of the post-retrofit ships were found to be significantly lower (>5 dB) than the pre-retrofit ships in the low-frequency band and the reduction was greatest at low speed. Although multiple design changes occurred during retrofitting, the reduction in the low-frequency band most likely results from a reduction in cavitation due to changes in propeller and bow design.

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.

Acoustic localization, validation, and characterization of Rice's whale calls.

The recently named Rice's whale in the Gulf of Mexico is one of the most endangered whales in the world, and improved knowledge of spatiotemporal occurrence patterns is needed to support their recovery and conservation. Passive acoustic monitoring methods for determining spatiotemporal occurrence patterns require identifying the species' call repertoire. Rice's whale call repertoire remains unvalidated though several potential call types have been identified. This study uses sonobuoys and passive acoustic tagging to validate the source of potential call types and to characterize Rice's whale calls. During concurrent visual and acoustic surveys, acoustic-directed approaches were conducted to obtain visual verifications of sources of localized sounds. Of 28 acoustic-directed approaches, 79% led to sightings of balaenopterid whales, of which 10 could be positively identified to species as Rice's whales. Long-moan calls, downsweep sequences, and tonal-sequences are attributed to Rice's whales based on these matches, while anthropogenic sources are ruled out. A potential new call type, the low-frequency downsweep sequence, is characterized from tagged Rice's whale recordings. The validation and characterization of the Rice's whale call repertoire provides foundational information needed to use passive acoustic monitoring for better understanding and conservation of these critically endangered whales.

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.

The influence of sea ice on the detection of bowhead whale calls.

Bowhead whales (Balaena mysticetus) face threats from diminishing sea ice and increasing anthropogenic activities in the Arctic. Passive acoustic monitoring is the most effective means for monitoring their distribution and population trends, based on the detection of their calls. Passive acoustic monitoring, however, is influenced by the sound propagation environment and ambient noise levels, which impact call detection probability. Modeling and simulations were used to estimate detection probability for bowhead whale frequency-modulated calls in the 80-180 Hz frequency band with and without sea ice cover and under various noise conditions. Sound transmission loss for bowhead calls is substantially greater during ice-covered conditions than during open-water conditions, making call detection ~ 3 times more likely in open-water. Estimates of daily acoustic detection probability were used to compensate acoustic detections for sound propagation and noise effects in two recording datasets in the northeast Chukchi Sea, on the outer shelf and continental slope, collected between 2012 and 2013. The compensated acoustic density suggests a decrease in whale presence with the retreat of sea ice at these recording sites. These results highlight the importance of accounting for effects of the environment on ambient noise and acoustic propagation when interpreting results of passive acoustic monitoring.

Update on frequency decline of Northeast Pacific blue whale (Balaenoptera musculus) calls.

Worldwide, the frequency (pitch) of blue whale (Balaenoptera musculus) calls has been decreasing since first recorded in the 1960s. This frequency decline occurs over annual and inter-annual timescales and has recently been documented in other baleen whale species, yet it remains unexplained. In the Northeast Pacific, blue whales produce two calls, or units, that, when regularly repeated, are referred to as song: A and B calls. In this population, frequency decline has thus far only been examined in B calls. In this work, passive acoustic data collected in the Southern California Bight from 2006 to 2019 were examined to determine if A calls are also declining in frequency and whether the call pulse rate was similarly impacted. Additionally, frequency measurements were made for B calls to determine whether the rate of frequency decline is the same as was calculated when this phenomenon was first reported in 2009. We found that A calls decreased at a rate of 0.32 Hz yr-1 during this period and that B calls were still decreasing, albeit at a slower rate (0.27 Hz yr-1) than reported previously. The A call pulse rate also declined over the course of the study, at a rate of 0.006 pulses/s yr-1. With this updated information, we consider the various theories that have been proposed to explain frequency decline in blue whales. We conclude that no current theory adequately accounts for all aspects of this phenomenon and consider the role that individual perception of song frequency may play. To understand the cause behind call frequency decline, future studies might want to explore the function of these songs and the mechanism for their synchronization. The ubiquitous nature of the frequency shift phenomenon may indicate a consistent level of vocal plasticity and fine auditory processing abilities across baleen whale species.

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.

Scientists in the line of fire.

The devastation and despair gripping Ukraine following the unprovoked invasion by neighboring Russia is heartbreaking and unthinkable. Such a loss of life and homeland has stirred wide concern around the world. This war sets back progress to establish a peaceful and sustainable world and to address important problems faced by all humanity, including climate change, environmental degradation, public health, and inequality. The international community of scientists cooperates extensively to address the challenges of our time, and a war that is destroying a stable and healthy nation and provoking a refugee crisis is no exception. What can the scientific community do most immediately to provide support and aid to its Ukrainian colleagues in their time of need? The community should focus on strengthening regional partnerships in Eastern Europe, networking to find refugees safe havens, speaking out forcefully against this invasion, and preparing to help rebuild Ukrainian science when the time is right.

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 sea ice and range expansion of sperm whales in the eclipse sound region of Baffin Bay, Canada.

Sperm whales (Physeter macrocephalus) are a cosmopolitan species but are only found in ice-free regions of the ocean. It is unknown how their distribution might change in regions undergoing rapid loss of sea ice and ocean warming like Baffin Bay in the eastern Canadian Arctic. In 2014 and 2018, sperm whales were sighted near Eclipse Sound, Baffin Bay: the first recorded uses of this region by sperm whales. In this study, we investigate the spatiotemporal distribution of sperm whales near Eclipse Sound using visual and acoustic data. We combine several published open-source, data sets to create a map of historical sperm whale presence in the region. We use passive acoustic data from two recording sites between 2015 and 2019 to investigate more recent presence in the region. We also analyze regional trends in sea ice concentration (SIC) dating back to 1901 and relate acoustic presence of sperm whales to the mean SIC near the recording sites. We found no records of sperm whale sightings near Eclipse Sound outside of the 2014/2018 observations. Our acoustic data told a different story, with sperm whales recorded yearly from 2015 to 2019 with presence in the late summer and fall months. Sperm whale acoustic presence increased over the 5-year study duration and was closely related to the minimum SIC each year. Sperm whales, like other cetaceans, are ecosystem sentinels, or indicators of ecosystem change. Increasing number of days with sperm whale presence in the Eclipse Sound region could indicate range expansion of sperm whales as a result of changes in sea ice. Monitoring climate change-induced range expansion in this region is important to understand how increasing presence of a top-predator might impact the Arctic food web.

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.

Seal bomb explosion sound source characterization.

Small explosive charges, called seal bombs, used by commercial fisheries to deter marine mammals from depredation and accidental bycatch during fishing operations, produce high level sounds that may negatively impact nearby animals. Seal bombs were exploded underwater and recorded at various ranges with a calibrated hydrophone to characterize the pulse waveforms and to provide appropriate propagation loss models for source level (SL) estimates. Waveform refraction became important at about 1500 m slant range with approximately spherical spreading losses observed at shorter ranges. The SL for seal bombs was estimated to be 233 dB re 1 µPa m; however, for impulses such as explosions, better metrics integrate over the pulse duration, accounting for the total energy in the pulse, including source pressure impulse, estimated as 193 Pa m s, and sound exposure source level, estimated as 197 dB re 1 µPa2 m2 s over a 2 ms window. Accounting for the whole 100 ms waveform, including the bubble pulses and sea surface reflections, sound exposure source level was 203 dB re 1 µPa2 m2 s. Furthermore, integrating the energy over an entire event period of multiple explosions (i.e., cumulative sound exposure level) should be considered when evaluating impact.