Understanding vessel noise across a network of marine protected areas.

Protected areas are typically managed as a network of sites exposed to varying anthropogenic conditions. Managing these networks benefits from monitoring of conditions across sites to help prioritize coordinated efforts. Monitoring marine vessel activity and related underwater radiated noise impacts across a network of protected areas, like the U.S. National Marine Sanctuary system, helps managers ensure the quality of habitats used by a wide range of marine species. Here, we use underwater acoustic detections of vessels to quantify different characteristics of vessel noise at 25 locations within eight marine sanctuaries including the Hawaiian Archipelago and the U.S. east and west coasts. Vessel noise metrics, including temporal presence and sound levels, were paired with Automatic Identification System (AIS) vessel tracking data to derive a suite of robust vessel noise indicators for use across the network of marine protected areas. Network-wide comparisons revealed a spectrum of vessel noise conditions that closely matched AIS vessel traffic composition. Shifts in vessel noise were correlated with the decrease in vessel activity early in the COVID-19 pandemic, and vessel speed reduction management initiatives. Improving our understanding of vessel noise conditions in these protected areas can help direct opportunities for reducing vessel noise, such as establishing and maintaining noise-free periods, enhancing port efficiency, engaging with regional and international vessel quieting initiatives, and leveraging co-benefits of management actions for reducing ocean noise.

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.

SoundScape learning: An automatic method for separating fish chorus in marine soundscapes.

Marine soundscapes provide the opportunity to non-invasively learn about, monitor, and conserve ecosystems. Some fishes produce sound in chorus, often in association with mating, and there is much to learn about fish choruses and the species producing them. Manually analyzing years of acoustic data is increasingly unfeasible, and is especially challenging with fish chorus, as multiple fish choruses can co-occur in time and frequency and can overlap with vessel noise and other transient sounds. This study proposes an unsupervised automated method, called SoundScape Learning (SSL), to separate fish chorus from soundscape using an integrated technique that makes use of randomized robust principal component analysis (RRPCA), unsupervised clustering, and a neural network. SSL was applied to 14 recording locations off southern and central California and was able to detect a single fish chorus of interest in 5.3 yrs of acoustically diverse soundscapes. Through application of SSL, the chorus of interest was found to be nocturnal, increased in intensity at sunset and sunrise, and was seasonally present from late Spring to late Fall. Further application of SSL will improve understanding of fish behavior, essential habitat, species distribution, and potential human and climate change impacts, and thus allow for protection of vulnerable fish species.

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.

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.

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.

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.

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.

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.

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.

An empirical model for wind-generated ocean noise.

An empirical model for wind-generated underwater noise is presented that was developed using an extensive dataset of acoustic field recordings and a global wind model. These data encompass more than one hundred years of recording-time and capture high wind events, and were collected both on shallow continental shelves and in open ocean deep-water settings. The model aims to explicitly separate noise generated by wind-related sources from noise produced by anthropogenic sources. Two key wind-related sound-generating mechanisms considered are: surface wave and turbulence interactions, and bubble and bubble cloud oscillations. The model for wind-generated noise shows small frequency dependence (5 dB/decade) at low frequencies (10-100 Hz), and larger frequency dependence (∼15 dB/decade) at higher frequencies (400 Hz-20 kHz). The relationship between noise level and wind speed is linear for low wind speeds (<3.3 m/s) and increases to a higher power law (two or three) at higher wind speeds, suggesting a transition between surface wave/turbulence and bubble source mechanisms. At the highest wind speeds (>15 m/s), noise levels begin to decrease at high frequencies (>10 kHz), likely due to interaction between bubbles and screening of noise radiation in the presence of high-density bubble clouds.

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.

DetEdit: A graphical user interface for annotating and editing events detected in long-term acoustic monitoring data.

Passive acoustic monitoring has become an important data collection method, yielding massive datasets replete with biological, environmental and anthropogenic information. Automated signal detectors and classifiers are needed to identify events within these datasets, such as the presence of species-specific sounds or anthropogenic noise. These automated methods, however, are rarely a complete substitute for expert analyst review. The ability to visualize and annotate acoustic events efficiently can enhance scientific insights from large, previously intractable datasets. A MATLAB-based graphical user interface, called DetEdit, was developed to accelerate the editing and annotating of automated detections from extensive acoustic datasets. This tool is highly-configurable and multipurpose, with uses ranging from annotation and classification of individual signals or signal-clusters and evaluation of signal properties, to identification of false detections and false positive rate estimation. DetEdit allows users to step through acoustic events, displaying a range of signal features, including time series of received levels, long-term spectral averages, time intervals between detections, and scatter plots of peak frequency, RMS, and peak-to-peak received levels. Additionally, it displays either individual, or averaged sound pressure waveforms, and power spectra within each acoustic event. These views simultaneously provide analysts with signal-level detail and encounter-level context. DetEdit creates datasets of signal labels for further analyses, such as training classifiers and quantifying occurrence, abundances, or trends. Although designed for evaluating underwater-recorded odontocete echolocation click detections, DetEdit can be adapted to almost any stereotyped impulsive signal. Our software package complements available tools for the bioacoustic community and is provided open source at https://github.com/MarineBioAcousticsRC/DetEdit.

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.

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.

Limited trophic partitioning among sympatric delphinids off a tropical oceanic atoll.

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

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

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

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

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