Baleen whales (Mysticeti ) communicate using low-frequency acoustic signals. These long-wavelength sounds can be detected over hundreds of kilometres, potentially allowing contact over large distances. Low-frequency noise from large ships (20-200 Hz) overlaps acoustic signals used by baleen whales, and increased levels of underwater noise have been documented in areas with high shipping traffic. Reported responses of whales to increased noise include: habitat displacement, behavioural changes and alterations in the intensity, frequency and intervals of calls. However, it has been unclear whether exposure to noise results in physiological responses that may lead to significant consequences for individuals or populations. Here, we show that reduced ship traffic in the Bay of Fundy, Canada, following the events of 11 September 2001, resulted in a 6 dB decrease in underwater noise with a significant reduction below 150 Hz. This noise reduction was associated with decreased baseline levels of stress-related faecal hormone metabolites (glucocorticoids) in North Atlantic right whales (Eubalaena glacialis). This is the first evidence that exposure to low-frequency ship noise may be associated with chronic stress in whales, and has implications for all baleen whales in heavy ship traffic areas, and for recovery of this endangered right whale population.

Archival bottom‐mounted audio recorders were deployed in nine different areas of the western Mediterranean Sea, Strait of Gibraltar, and adjacent North Atlantic waters during 2006–2009 to study fin whale (Balaenoptera physalus) seasonal presence and population structure. Analysis of 29,822 recording hours revealed typical long, patterned sequences of 20 Hz notes (here called “song”), back‐beats, 135–140 Hz notes, and downsweeps. Acoustic parameters (internote interval, note duration, frequency range, center and peak frequencies) were statistically compared among songs and song notes recorded in all areas. Fin whale singers producing songs attributable to the northeastern North Atlantic subpopulation were detected crossing the Strait of Gibraltar and wintering in the southwestern Mediterranean Sea (Alboran basin), while songs attributed to the Mediterranean were detected in the northwest Mediterranean basin. These results suggest that the northeastern North Atlantic fin whale distribution extends into the southwest Mediterranean basin, and spatial and temporal overlap may exist between this subpopulation and the Mediterranean subpopulation. This new interpretation of the fin whale population structure in the western Mediterranean Sea has important ecological and conservation implications. The conventionally accepted distribution ranges of northeastern North Atlantic and Mediterranean fin whale subpopulations should be reconsidered in light of the results from this study.

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BackgroundLittle is known about migration patterns and seasonal distribution away from coastal summer feeding habitats of many pelagic baleen whales. Recently, large-scale passive acoustic monitoring networks have become available to explore migration patterns and identify critical habitats of these species. North Atlantic minke whales (Balaenoptera acutorostrata) perform seasonal migrations between high latitude summer feeding and low latitude winter breeding grounds. While the distribution and abundance of the species has been studied across their summer range, data on migration and winter habitat are virtually missing. Acoustic recordings, from 16 different sites from across the North Atlantic, were analyzed to examine the seasonal and geographic variation in minke whale pulse train occurrence, infer information about migration routes and timing, and to identify possible winter habitats.ResultsAcoustic detections show that minke whales leave their winter grounds south of 30° N from March through early April. On their southward migration in autumn, minke whales leave waters north of 40° N from mid-October through early November. In the western North Atlantic spring migrants appear to track the warmer waters of the Gulf Stream along the continental shelf, while whales travel farther offshore in autumn. Abundant detections were found off the southeastern US and the Caribbean during winter. Minke whale pulse trains showed evidence of geographic variation, with longer pulse trains recorded south of 40° N. Very few pulse trains were recorded during summer in any of the datasets.ConclusionThis study highlights the feasibility of using acoustic monitoring networks to explore migration patterns of pelagic marine mammals. Results confirm the presence of minke whales off the southeastern US and the Caribbean during winter months. The absence of pulse train detections during summer suggests either that minke whales switch their vocal behaviour at this time of year, are absent from available recording sites or that variation in signal structure influenced automated detection. Alternatively, if pulse trains are produced in a reproductive context by males, these data may indicate their absence from the selected recording sites. Evidence of geographic variation in pulse train duration suggests different behavioural functions or use of these calls at different latitudes.Electronic supplementary materialThe online version of this article (doi:10.1186/s40462-014-0024-3) contains supplementary material, which is available to authorized users.

Beluga whales, Delphinapterus leucas, have a graded call system; call types exist on a continuum making classification challenging. A description of vocalizations from the eastern Beaufort Sea beluga population during its spring migration are presented here, using both a non-parametric classification tree analysis (CART), and a Random Forest analysis. Twelve frequency and duration measurements were made on 1019 calls recorded over 14 days off Icy Cape, Alaska, resulting in 34 identifiable call types with 83% agreement in classification for both CART and Random Forest analyses. This high level of agreement in classification, with an initial subjective classification of calls into 36 categories, demonstrates that the methods applied here provide a quantitative analysis of a graded call dataset. Further, as calls cannot be attributed to individuals using single sensor passive acoustic monitoring efforts, these methods provide a comprehensive analysis of data where the influence of pseudo-replication of calls from individuals is unknown. This study is the first to describe the vocal repertoire of a beluga population using a robust and repeatable methodology. A baseline eastern Beaufort Sea beluga population repertoire is presented here, against which the call repertoire of other seasonally sympatric Alaskan beluga populations can be compared.

The endangered beluga whale (Delphinapterus leucas) population in Cook Inlet, AK faces threats from a variety of anthropogenic factors, including coastal development, oil and gas exploration, vessel traffic, and military activities. To address existing gaps in understanding about the occurrence of belugas in Cook Inlet, a project was developed to use passive acoustic monitoring to document the year-round distribution of belugas, as well as killer whales (Orcinus orca), which prey on belugas. Beginning in June 2009, ten moorings were deployed throughout the Inlet and refurbished every two to eight months. Despite challenging conditions consisting of strong tidal currents carrying debris and seasonal ice cover, 83% of mooring deployments were successfully recovered. Noise from water flow, vessel traffic, and/or industrial activities was present at several sites, potentially masking some signals. However, belugas were successfully detected at multiple locations. Detections were relatively common in the upper inlet and less common or absent at middle and lower inlet locations. Killer whale signals were also recorded. Some seasonal variability in the occurrence of both belugas and killer whales was evident.

While hearing is the primary sensory modality for odontocetes, there are few data addressing variation within a natural population. This work describes the hearing ranges (4-150 kHz) and sensitivities of seven apparently healthy, wild beluga whales (Delphinapterus leucas) during a population health assessment project that captured and released belugas in Bristol Bay, Alaska. The baseline hearing abilities and subsequent variations were addressed. Hearing was measured using auditory evoked potentials (AEPs). All audiograms showed a typical cetacean U-shape; substantial variation (>30 dB) was found between most and least sensitive thresholds. All animals heard well, up to at least 128 kHz. Two heard up to 150 kHz. Lowest auditory thresholds (35-45 dB) were identified in the range 45-80 kHz. Greatest differences in hearing abilities occurred at both the high end of the auditory range and at frequencies of maximum sensitivity. In general, wild beluga hearing was quite sensitive. Hearing abilities were similar to those of belugas measured in zoological settings, reinforcing the comparative importance of both settings. The relative degree of variability across the wild belugas suggests that audiograms from multiple individuals are needed to properly describe the maximum sensitivity and population variance for odontocetes. Hearing measures were easily incorporated into field-based settings. This detailed examination of hearing abilities in wild Bristol Bay belugas provides a basis for a better understanding of the potential impact of anthropogenic noise on a noise-sensitive species. Such information may help design noise-limiting mitigation measures that could be applied to areas heavily influenced and inhabited by endangered belugas.

Over a decade after the Cook Inlet beluga (Delphinapterus leucas) was listed as endangered in 2008, the population has shown no sign of recovery. Lack of ecological knowledge limits the understanding of, and ability to manage, potential threats impeding recovery of this declining population. National Oceanic and Atmospheric Administration Fisheries, in partnership with the Alaska Department of Fish and Game, initiated a passive acoustics monitoring program in 2017 to investigate beluga seasonal occurrence by deploying a series of passive acoustic moorings. Data have been processed with semi-automated tonal detectors followed by time intensive manual validation. To reduce this labor intensive and time-consuming process, in addition to increasing the accuracy of classification results, the authors constructed an ensembled deep learning convolutional neural network model to classify beluga detections as true or false. Using a 0.5 threshold, the final model achieves 96.57% precision and 92.26% recall on testing dataset. This methodology proves to be successful at classifying beluga signals, and the framework can be easily generalized to other acoustic classification problems.