The Lombard effect in singing humpback whales: Source levels increase as ambient ocean noise levels increase.

Many animals increase the intensity of their vocalizations in increased noise. This response is known as the Lombard effect. While some previous studies about cetaceans report a 1 dB increase in the source level (SL) for every dB increase in the background noise level (NL), more recent data have not supported this compensation ability. The purpose of this study was to calculate the SLs of humpback whale song units recorded off Hawaii and test for a relationship between these SLs and background NLs. Opportunistic recordings during 2012-2017 were used to detect and track 524 humpback whale encounters comprised of 83 974 units on the U.S. Navy's Pacific Missile Range Facility hydrophones. Received levels were added to their estimated transmission losses to calculate SLs. Humpback whale song units had a median SL of 173 dB re 1 µPa at 1 m, and SLs increased by 0.53 dB/1 dB increase in background NLs. These changes occurred in real time on hourly and daily time scales. Increases in ambient noise could reduce male humpback whale communication space in the important breeding area off Hawaii. Since these vocalization changes may be dependent on location or behavioral state, more work is needed at other locations and with other species.

Lombard effect: Minke whale boing call source levels vary with natural variations in ocean noise.

Minke whales were acoustically detected, localized, and tracked on the U.S. Navy's Pacific Missile Range Facility from 2012 to 2017. Animal source levels (SLs) were estimated by adding transmission loss estimates to measured received levels of 42 159 individual minke whale boings. Minke whales off Hawaii exhibited the Lombard effect in that they increased their boing call intensity in increased background noise. Minke whales also decreased the variance of the boing call SL in higher background noise levels. Although the whales partially compensated for increasing background noise, they were unable or unwilling to increase their SLs by the same amount as the background noise. As oceans become louder, this reduction in communication space could negatively impact the health of minke whale populations. The findings in this study also have important implications for acoustic animal density studies, which may use SL to estimate probability of detection.

Swim track kinematics and calling behavior attributed to Bryde's whales on the Navy's Pacific Missile Range Facility.

Time difference of arrival methods for acoustically localizing multiple marine mammals have been applied to recorded data from the Navy's Pacific Missile Range Facility in order to localize and track calls attributed to Bryde's whales. Data were recorded during the months of August-October 2014, and 17 individual tracks were identified. Call characteristics were compared to other Bryde's whale vocalizations from the Pacific Ocean, and locations of the recorded signals were compared to published visual sightings of Bryde's whales in the Hawaiian archipelago. Track kinematic information, such as swim speeds, bearing information, track duration, and directivity, was recorded for the species. The intercall interval was also established for most of the tracks, providing cue rate information for this species that may be useful for future acoustic density estimate calculations.

Minke whales (Balaenoptera acutorostrata) respond to navy training.

Minke whales (Balaenoptera acutorostrata) were acoustically detected and localized via their boing calls using 766 h of recorded data from 24 hydrophones at the U.S. Navy's Pacific Missile Range Facility located off Kauai, Hawaii. Data were collected before, during, and after naval undersea warfare training events, which occurred in February over three consecutive years (2011-2013). Data collection in the during periods were further categorized as phase A and phase B with the latter being the only period with naval surface ship activities (e.g., frigate and destroyer maneuvers including the use of mid-frequency active sonar). Minimum minke whale densities were estimated for all data periods based upon the numbers of whales acoustically localized within the 3780 km(2) study area. The 2011 minimum densities in the study area were: 3.64 whales [confidence interval (CI) 3.31-4.01] before the training activity, 2.81 whales (CI 2.31-3.42) for phase A, 0.69 whales (CI 0.27-1.8) for phase B and 4.44 whales (CI 4.04-4.88) after. The minimum densities for the phase B periods were highly statistically significantly lower (p < 0.001) from all other periods within each year, suggesting a clear response to the phase B training. The phase A period results were mixed when compared to other non-training periods.

Delphinid behavioral responses to incidental mid-frequency active sonar.

Opportunistic observations of behavioral responses by delphinids to incidental mid-frequency active (MFA) sonar were recorded in the Southern California Bight from 2004 through 2008 using visual focal follows, static hydrophones, and autonomous recorders. Sound pressure levels were calculated between 2 and 8 kHz. Surface behavioral responses were observed in 26 groups from at least three species of 46 groups out of five species encountered during MFA sonar incidents. Responses included changes in behavioral state or direction of travel, changes in vocalization rates and call intensity, or a lack of vocalizations while MFA sonar occurred. However, 46% of focal groups not exposed to sonar also changed their behavior, and 43% of focal groups exposed to sonar did not change their behavior. Mean peak sound pressure levels when a behavioral response occurred were around 122 dB re: 1 µPa. Acoustic localizations of dolphin groups exhibiting a response gave insight into nighttime movement patterns and provided evidence that impacts of sonar may be mediated by behavioral state. The lack of response in some cases may indicate a tolerance of or habituation to MFA sonar by local populations; however, the responses that occur at lower received levels may point to some sensitization as well.

Offshore killer whale tracking using multiple hydrophone arrays.

To study delphinid near surface movements and behavior, two L-shaped hydrophone arrays and one vertical hydrophone line array were deployed at shallow depths (<125 m) from the floating instrument platform R/P FLIP, moored northwest of San Clemente Island in the Southern California Bight. A three-dimensional propagation-model based passive acoustic tracking method was developed and used to track a group of five offshore killer whales (Orcinus orca) using their emitted clicks. In addition, killer whale pulsed calls and high-frequency modulated (HFM) signals were localized using other standard techniques. Based on these tracks sound source levels for the killer whales were estimated. The peak to peak source levels for echolocation clicks vary between 170-205 dB re 1 µPa @ 1 m, for HFM calls between 185-193 dB re 1 µPa @ 1 m, and for pulsed calls between 146-158 dB re 1 µPa @ 1 m.

Tracking dolphin whistles using an autonomous acoustic recorder array.

Dolphins are known to produce nearly omnidirectional whistles that can propagate several kilometers, allowing these sounds to be localized and tracked using acoustic arrays. During the fall of 2007, a km-scale array of four autonomous acoustic recorders was deployed offshore of southern California in a known dolphin habitat at ~800 m depth. Concurrently with the one-month recording, a fixed-point marine mammal visual survey was conducted from a moored research platform in the center of the array, providing daytime species and behavior visual confirmation. The recordings showed three main types of dolphin acoustic activity during distinct times: primarily whistling during daytime, whistling and clicking during early night, and primarily clicking during late night. Tracks from periods of daytime whistling typically were tightly grouped and traveled at a moderate rate. In one example with visual observations, traveling common dolphins (Delphinus sp.) were tracked for about 10 km with an average speed of ~2.5 m s(-1) (9 km h(-1)). Early night recordings had whistle localizations with wider spatial distribution and slower travel speed than daytime recordings, presumably associated with foraging behavior. Localization and tracking of dolphins over long periods has the potential to provide insight into their ecology, behavior, and potential response to stimuli.

Classification of behavior using vocalizations of Pacific white-sided dolphins (Lagenorhynchus obliquidens).

Surface behavior and concurrent underwater vocalizations were recorded for Pacific white-sided dolphins in the Southern California Bight (SCB) over multiple field seasons spanning 3 years. Clicks, click trains, and pulsed calls were counted and classified based on acoustic measurements, leading to the identification of 19 key call features used for analysis. Kruskal-Wallis tests indicated that call features differ significantly across behavioral categories. Previous work had discovered two distinctive click Types (A and B), which may correspond to known subpopulations of Pacific white-side dolphins in the Southern California Bight; this study revealed that animals producing these different click types also differ in both their behavior and vocalization patterns. Click Type A groups were predominantly observed slow traveling and milling, with little daytime foraging, while click Type B groups were observed traveling and foraging. These behavioral differences may be characteristic of niche partitioning by overlapping populations; coupled with differences in vocalization patterns, they may signify that these subpopulations are cryptic species. Finally, random forest decision trees were used to classify behavior based on vocalization data, with rates of correct classification up to 86%, demonstrating the potential for the use of vocalization patterns to predict behavior.

Classification of Risso's and Pacific white-sided dolphins using spectral properties of echolocation clicks.

The spectral and temporal properties of echolocation clicks and the use of clicks for species classification are investigated for five species of free-ranging dolphins found offshore of southern California: short-beaked common (Delphinus delphis), long-beaked common (D. capensis), Risso's (Grampus griseus), Pacific white-sided (Lagenorhynchus obliquidens), and bottlenose (Tursiops truncatus) dolphins. Spectral properties are compared among the five species and unique spectral peak and notch patterns are described for two species. The spectral peak mean values from Pacific white-sided dolphin clicks are 22.2, 26.6, 33.7, and 37.3 kHz and from Risso's dolphins are 22.4, 25.5, 30.5, and 38.8 kHz. The spectral notch mean values from Pacific white-sided dolphin clicks are 19.0, 24.5, and 29.7 kHz and from Risso's dolphins are 19.6, 27.7, and 35.9 kHz. Analysis of variance analyses indicate that spectral peaks and notches within the frequency band 24-35 kHz are distinct between the two species and exhibit low variation within each species. Post hoc tests divide Pacific white-sided dolphin recordings into two distinct subsets containing different click types, which are hypothesized to represent the different populations that occur within the region. Bottlenose and common dolphin clicks do not show consistent patterns of spectral peaks or notches within the frequency band examined (1-100 kHz).

Gaussian mixture model classification of odontocetes in the Southern California Bight and the Gulf of California.

A method for the automatic classification of free-ranging delphinid vocalizations is presented. The vocalizations of short-beaked and long-beaked common (Delphinus delphis and Delphinus capensis), Pacific white-sided (Lagenorhynchus obliquidens), and bottlenose (Tursiops truncatus) dolphins were recorded in a pelagic environment of the Southern California Bight and the Gulf of California over a period of 4 years. Cepstral feature vectors are extracted from call data which contain simultaneous overlapping whistles, burst-pulses, and clicks from a single species. These features are grouped into multisecond segments. A portion of the data is used to train Gaussian mixture models of varying orders for each species. The remaining call data are used to test the performance of the models. Species are predicted based upon probabilistic measures of model similarity with test segment groups having durations between 1 and 25 s. For this data set, 256 mixture Gaussian mixture models and segments of at least 10 s of call data resulted in the best classification results. The classifier predicts the species of groups with 67%-75% accuracy depending upon the partitioning of the training and test data.