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  • 1
    Online Resource
    Online Resource
    Dive characteristics of Cross Seamount beaked whales from long‐term passive acoustic monitoring at the Pacific Missile Range Facility, Kauaʻi
    Wiley ; 2023
    In:  Marine Mammal Science Vol. 39, No. 1 ( 2023-01), p. 22-41
    Details
    In: Marine Mammal Science, Wiley, Vol. 39, No. 1 ( 2023-01), p. 22-41
    Abstract: Beaked whale foraging pulses were detected on the Pacific Missile Range Facility (PMRF) off Kauaʻi, Hawaiʻi, via long term passive acoustic monitoring. The unidentified pulses do not match foraging pulses of known species on the range but are similar to the unidentified beaked whale first detected at Cross Seamount, Hawaiʻi. Although there has not been a visual confirmation of the unidentified beaked whale species, analysis of data collected from 2007 to 2019 has identified beaked whale foraging dive characteristics from echolocation pulses. From the 13 years of data, the most distinct patterns were that all foraging dives occurred at night and the nighttime foraging dive rate was 0.11 group vocal periods (GVP) per hour, with most detections on shallow hydrophones (625–1,000 m deep) over steep bathymetric slopes. Data collected during U.S. Navy training events were used to compare dive behavior during mid‐frequency active sonar (MFAS) activity against baseline periods; it was determined that the whales reduced GVPs during sonar and these remained low for at least 3 days after the training events. These results are the first long‐term record of acoustic signals from the Cross Seamount beaked whale and provide important insights into their habitat use and occurrence patterns.
    Type of Medium: Online Resource
    ISSN: 0824-0469 , 1748-7692
    URL: Issue
    URL: Article
    DOI: 10.1111/mms.v39.1
    DOI: 10.1111/mms.12959
    Language: English
    Publisher: Wiley
    Publication Date: 2023
    detail.hit.zdb_id: 12787-5
    detail.hit.zdb_id: 2218018-7
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  • 2
    Online Resource
    Online Resource
    North Pacific minke whales call rapidly when calling conspecifics are nearby
    Frontiers Media SA ; 2022
    In:  Frontiers in Marine Science Vol. 9 ( 2022-8-22)
    Details
    In: Frontiers in Marine Science, Frontiers Media SA, Vol. 9 ( 2022-8-22)
    Abstract: North Pacific minke whale ( Balaenoptera acutorostrata ) boing calls are commonly detected in Hawaiian waters. When producing boing vocalizations, minke whales seem to be in one of two calling behavioral states. Most often minke whales produce boings with inter-call intervals of several minutes, but sometimes minke whales call rapidly with inter-call intervals of less than a minute. Since minke whales are difficult to detect visually, cue-rate-based density estimation using passive acoustic monitoring has been proposed. However, the variables that influence cue rate or calling rate are poorly understood in most whales, including minke whales. We collected passive acoustic recordings from 47 bottom-mounted hydrophones at the Pacific Missile Range Facility’s instrumented range off the coast of Kauaʻi, Hawaiʻi to test the hypothesis that minke whales call more rapidly when closer in proximity to other calling conspecifics. A total of 599 days of data were recorded between August 2012 and July 2017 and were automatically post-processed to detect, classify, and localize calls. Localized calls were grouped into tracks and manually validated, resulting in 509 individual tracks composed of 36,033 calls within a 16 x 39 km focal study area. Tracked minke whales exhibited a strong bimodal call rate with means of one call every 6.85 min ( σ = 2.54 min) and 0.63 min ( σ = 0.36 min). We ran hidden Markov models to quantify the relationship between call rate and the distance to the nearest calling conspecific. Overall, the probability of the higher call rate occurring increased as the distance to the nearest conspecific decreased, and the probability of the lower call rate occurring increased as the distance to the nearest conspecific increased. We also examined individual track data and found that minke whales may also exhibit other responses (i.e. increased speed, changes in heading, and cessation of calling) when calling conspecifics are nearby. These findings provide new information about minke whale calling behavior in what is likely a breeding area.
    Type of Medium: Online Resource
    ISSN: 2296-7745
    URL: Article
    DOI: 10.3389/fmars.2022.897298
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2022
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  • 3
    Online Resource
    Online Resource
    Table_1.XLSX
    Frontiers Media SA ; 2020
    In:  Frontiers in Marine Science Vol. 7 ( 2020-10-29)
    Details
    In: Frontiers in Marine Science, Frontiers Media SA, Vol. 7 ( 2020-10-29)
    Type of Medium: Online Resource
    ISSN: 2296-7745
    URL: Article
    URL: Article
    URL: Article
    DOI: 10.3389/fmars.2020.587110
    DOI: 10.3389/fmars.2020.587110.s001
    DOI: 10.3389/fmars.2020.587110.s002
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2020
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  • 4
    Online Resource
    Online Resource
    Minke whales change their swimming behavior with respect to their calling behavior, nearby conspecifics, and the environment in the central North Pacific
    Frontiers Media SA ; 2023
    In:  Frontiers in Marine Science Vol. 10 ( 2023-4-11)
    Details
    In: Frontiers in Marine Science, Frontiers Media SA, Vol. 10 ( 2023-4-11)
    Abstract: Behavioral responses to sonar have been observed in a number of baleen whales, including minke whales ( Balaenoptera acutorostrata ). Previous studies used acoustic minke whale boing detections to localize and track individual whales on the U.S. Pacific Missile Range Facility (PMRF) in Kaua ‘i, Hawai‘i before, during, and after Navy training activities. These analyses showed significant changes in central North Pacific minke whale distribution and swimming behavior during Navy sonar events. For the purposes of contextualizing changes in animal movement relative to Navy sonar, we expanded on this research to examine the natural variation in minke whale movement when Navy sonar was not present. This study included 2,245 acoustically derived minke whale tracks spanning the years 2012–2017 over all months that minke whales were detected (October–May). Minke whale movement was examined relative to calling season, day of the year, hour of day, wind speed, calling state (nominal or rapid), and distance to the nearest calling conspecific. Hidden Markov models were used to identify two kinematic states (slower, less directional movement and faster, more directional movement). The findings indicate that minke whales were more likely to travel in a faster and more directional state when they were calling rapidly, when other vocalizing minke whales were nearby, during certain times of the day and calling seasons, and in windier conditions, but these changes in movement were less intense than the changes observed during exposure to Navy sonar, when swim speeds were the fastest. These results start to put behavioral responses to Navy sonar into an environmental context to understand the severity of responses relative to natural changes in behavior.
    Type of Medium: Online Resource
    ISSN: 2296-7745
    URL: Article
    DOI: 10.3389/fmars.2023.1148987
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2023
    detail.hit.zdb_id: 2757748-X
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  • 5
    Online Resource
    Online Resource
    Improving marine mammal classification using context from multiple hydrophones
    Acoustical Society of America (ASA) ; 2017
    In:  The Journal of the Acoustical Society of America Vol. 142, No. 4_Supplement ( 2017-10-01), p. 2619-2620
    Details
    In: The Journal of the Acoustical Society of America, Acoustical Society of America (ASA), Vol. 142, No. 4_Supplement ( 2017-10-01), p. 2619-2620
    Abstract: Detection, classification, localization, and tracking (DCLT) of marine mammals is oftentimes performed in that order. However, in the sonar-signal processing communities and elsewhere, classification is usually the final step. Thus, more appropriately, the working order should be “DLTC.” If classification is performed as the final step, the results can be greatly improved by using the context of the calls. By grouping likely calls into tracks, a collective of calls can provide much more information for classification than single calls alone. Additionally, when multiple species are calling at the same time, the location of the calls can be used to distinguish confusing signals. The time-series and spectral information of a call can also be enhanced by localizing first, and choosing the nearest hydrophone to the calling animal for signal analysis. If localization is not possible, classification can still be improved if two or more hydrophones are available with overlapping coverage, by using cross-correlograms. Multiple sensors also provide the ability to reduce detections due to sensor self-noise, and noise from fish and snapping shrimp. Collectively, these techniques were applied to vocalizing baleen whales on the Navy’s Pacific Missile Range Facility, and proved to greatly enhance the ability to classify Bryde’s, humpback, fin, and minke whales.
    Type of Medium: Online Resource
    ISSN: 0001-4966 , 1520-8524
    URL: Article
    DOI: 10.1121/1.5014594
    RVK:
    EQ 1000
    Language: English
    Publisher: Acoustical Society of America (ASA)
    Publication Date: 2017
    detail.hit.zdb_id: 1461063-2
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  • 6
    Online Resource
    Online Resource
    Development of deep neural networks for marine mammal call detection using an open-source, user friendly tool
    Acoustical Society of America (ASA) ; 2022
    In:  The Journal of the Acoustical Society of America Vol. 151, No. 4_Supplement ( 2022-04-01), p. A28-A28
    Details
    In: The Journal of the Acoustical Society of America, Acoustical Society of America (ASA), Vol. 151, No. 4_Supplement ( 2022-04-01), p. A28-A28
    Abstract: As the collection of large acoustic datasets used to monitor marine mammals increases, so too does the need for expedited and reliable detection of accurately classified bioacoustic signals. Deep learning methods of detection and classification are increasingly proposed as a means of addressing this processing need. These image recognition and classification methods include the use of a neural networks that independently determine important features of bioacoustic signals from spectrograms. Recent marine mammal call detection studies report consistent performance even when used with datasets that were not included in the network training. We present here the use of DeepSqueak, a novel open-source tool originally developed to detect and classify ultrasonic vocalizations from rodents in a low-noise, laboratory setting. We have trained networks in DeepSqueak to detect marine mammal vocalizations in comparatively noisy, natural acoustic environments. DeepSqueak utilizes a regional convolutional neural network architecture within an intuitive graphical user interface that provides automated detection results independent of acoustician expertise. Using passive acoustic data from two hydrophones on the Ocean Observatories Initiative’s Coastal Endurance Array, we developed networks for humpback whales, delphinids, and fin whales. We report performance and limitations for use of this detection method for each species.
    Type of Medium: Online Resource
    ISSN: 0001-4966 , 1520-8524
    URL: Article
    DOI: 10.1121/10.0010547
    RVK:
    EQ 1000
    Language: English
    Publisher: Acoustical Society of America (ASA)
    Publication Date: 2022
    detail.hit.zdb_id: 1461063-2
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  • 7
    Online Resource
    Online Resource
    Automated passive acoustic detection, classification, localization, and tracking methods applied to recorded data from the Pacific Missile Range Facility, Kauai, Hawaii
    Acoustical Society of America (ASA) ; 2017
    In:  The Journal of the Acoustical Society of America Vol. 142, No. 4_Supplement ( 2017-10-01), p. 2588-2588
    Details
    In: The Journal of the Acoustical Society of America, Acoustical Society of America (ASA), Vol. 142, No. 4_Supplement ( 2017-10-01), p. 2588-2588
    Abstract: Automated methods will be reviewed for performing passive acoustic detection, classification, localization, and tracking of some marine mammal species and man-made sources. The methods have been applied to recorded hydrophone data from a large aperture seafloor array at the Pacific Missile Range Facility (PMRF) at Kauai, Hawaii, with some of the methods currently implemented in a real-time system at PMRF. The process consists of custom software both in C + + and Matlab in a 3 or 4-step process. Automated detections of various sounds in specific frequency bands are first performed. In some cases, a classification stage is also performed. The third stage involves model-based localization of the detections or classifications. The fourth stage converts the localizations into individual source tracks. Source tracks are currently generated for fin, sei, Bryde’s, humpback, and sperm whales and mid-frequency active sonar (MFAS) transmissions. Performing this process on marine mammals allows information regarding the movement patterns of the whales while calling, as well as information on the species’ calls (e.g., call rate, frequencies, durations, estimated source levels). By performing similar processes on man-made sources, it is possible to determine some marine mammal responses from proximity of Navy vessels and mid-frequency active sonar sources.
    Type of Medium: Online Resource
    ISSN: 0001-4966 , 1520-8524
    URL: Article
    DOI: 10.1121/1.5014478
    RVK:
    EQ 1000
    Language: English
    Publisher: Acoustical Society of America (ASA)
    Publication Date: 2017
    detail.hit.zdb_id: 1461063-2
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  • 8
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    Online Resource
    Lessons learned from acoustically tracking baleen whales on the Navy’s Pacific Missile Range Facility
    Acoustical Society of America (ASA) ; 2018
    In:  The Journal of the Acoustical Society of America Vol. 144, No. 3_Supplement ( 2018-09-01), p. 1816-1816
    Details
    In: The Journal of the Acoustical Society of America, Acoustical Society of America (ASA), Vol. 144, No. 3_Supplement ( 2018-09-01), p. 1816-1816
    Abstract: Detection, localization, classification, and tracking of marine mammals has been performed on the U.S. Navy’s Pacific Missile Range Facility (PMRF) for over a decade. The range hydrophones are time-synchronized, have excellent spatial coverage, and monitor an area of approximately 1200 km2. Even with these ideal assets, there are hidden challenges when attempting acoustic density estimates of baleen whales on the range. This talk will cover lessons learned from tracking several species of baleen whales on the range over the last decade.
    Type of Medium: Online Resource
    ISSN: 0001-4966 , 1520-8524
    URL: Article
    DOI: 10.1121/1.5068010
    RVK:
    EQ 1000
    Language: English
    Publisher: Acoustical Society of America (ASA)
    Publication Date: 2018
    detail.hit.zdb_id: 1461063-2
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  • 9
    Online Resource
    Online Resource
    Swimming and acoustic calling behavior attributed to Bryde’s whales in the central North Pacific
    Frontiers Media SA ; 2024
    In:  Frontiers in Marine Science Vol. 11 ( 2024-4-3)
    Details
    In: Frontiers in Marine Science, Frontiers Media SA, Vol. 11 ( 2024-4-3)
    Abstract: A unique acoustic call type was identified and attributed to Bryde’s whales in the central North Pacific in 2015, but little is known about the distribution, calling behavior, or swimming behavior of Bryde’s whales in the region. Acoustic detections attributed to Bryde’s whales were used to localize and track individual whales on the U.S. Pacific Missile Range Facility (PMRF) in Kaua‘i, Hawai‘i. This study included 150 acoustically derived tracks from recordings spanning the years 2011–2022 with recording effort in nearly every month. Bryde’s whale movement was examined relative to calendar year, day of year, hour of day, wind speed, and acoustic calling rate. Hidden Markov models were used to identify two kinematic states (slower, less directional movement and faster, more directional movement). The findings indicate that Bryde’s whales were more likely to travel in a faster and more directional state during the daytime than at night and between May and August when compared to other times of year. The along-track acoustic cue rate was examined for 118 tracks, and the findings indicate a possible lengthening of the median inter-call interval over the duration of the study period. These results are an important first step in understanding more about behavior in Bryde’s whales, a relatively under-studied species.
    Type of Medium: Online Resource
    ISSN: 2296-7745
    URL: Article
    DOI: 10.3389/fmars.2024.1305505
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2024
    detail.hit.zdb_id: 2757748-X
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  • 10
    Online Resource
    Online Resource
    Image_8.EPS
    Frontiers Media SA ; 2021
    In:  Frontiers in Marine Science Vol. 8 ( 2021-9-3)
    Details
    In: Frontiers in Marine Science, Frontiers Media SA, Vol. 8 ( 2021-9-3)
    Abstract: Male fin whales sing using 20 Hz pulses produced in regular patterns of inter-note intervals, but little is known about fin whale swimming behavior while they are singing. Even less is known about fin whales in Hawaiian waters because they have rarely been sighted during surveys and passive acoustic monitoring has been limited to sparse hydrophone systems that do not have localization capabilities. We hypothesized that fin whale kinematics may be related to their singing behavior, or external variables such as time and sea state. To investigate this hypothesis, we analyzed 115 tracks containing 50,034 unique notes generated from passive acoustic recordings on an array of 14 hydrophones from 2011 to 2017 at the U.S. Navy Pacific Missile Range Facility off Kauai, Hawaii. Fin whales swam at an average speed of 1.1 m/s over relatively direct paths. We incorporated the whales' speed and turning angle into hidden Markov models to identify different behavioral states based on the whales' movements. We found that fin whale kinematic behavioral state was related to the vocalization rate (also known as cue rate) and time of day. When cue rate was higher, fin whales were more likely to swim slower and turn more than when cue rate was lower. During the night, fin whales were also more likely to swim slower and turn more than during the day. In addition, we examined whether the presence of singing fin whales was related to time and sea state using generalized additive models. Fin whale track presence was affected by day of the year and song season, and possibly also wind speed and wave height. Although the track kinematics from the fin whale tracks presented here are limited to a subset of whales that are acoustically active, they provide some of the only detailed movements of fin whales in the region and can be compared against fin whale swim speeds in other regions. Understanding how fin whale swimming behavior varies based on their vocalization patterns, time, and environmental factors will help us to contextualize potential changes in whale behavior during Navy training and testing on the range.
    Type of Medium: Online Resource
    ISSN: 2296-7745
    URL: Article
    URL: Article
    URL: Article
    URL: Article
    URL: Article
    URL: Article
    URL: Article
    URL: Article
    URL: Article
    URL: Article
    URL: Article
    DOI: 10.3389/fmars.2021.696002
    DOI: 10.3389/fmars.2021.696002.s001
    DOI: 10.3389/fmars.2021.696002.s002
    DOI: 10.3389/fmars.2021.696002.s003
    DOI: 10.3389/fmars.2021.696002.s004
    DOI: 10.3389/fmars.2021.696002.s005
    DOI: 10.3389/fmars.2021.696002.s006
    DOI: 10.3389/fmars.2021.696002.s007
    DOI: 10.3389/fmars.2021.696002.s008
    DOI: 10.3389/fmars.2021.696002.s009
    DOI: 10.3389/fmars.2021.696002.s010
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2021
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