Future Directions in Research on Bryde's Whales

One of the lesser known species of baleen whales, the Bryde's whale, also known as Eden's whale (Balaenoptera edeni edeni and B. edeni brydei), although hunted as part of a North Pacific Japanese research programme1, was not heavily exploited by commercial whaling and remains a data deficient species. Their taxonomic status is not fully resolved and they are often mistaken for other species leading to uncertainty about their true distribution, behavior and conservation status. Some populations are critically endangered, whilst others are small but have high genetic diversity suggesting wider connectivity. The species' unpredictable coastal and offshore global distribution throughout warm-temperate waters has led to populations with unknown genetic variation, and facing different threats. Few areas are well-studied, but each study reveals often contrasting movement patterns, foraging strategies, and vocal repertoires; there are considerable knowledge gaps for Bryde's whales. There are few Bryde's populations with abundance estimates but they typically number in the mid- to high-hundreds of individuals, with other populations small, <100 mature individuals, and exposed to high levels of anthropogenic impacts. Future research should focus on understanding the diversity within and between populations. Here, we suggest an integrative, comparative approach toward future work on Bryde's whales, including acoustic monitoring, trophic interactions, telemetry tools, understanding their novel behaviors, and resolving their species status. This will inform conservation management of this unusual species of whale vulnerable to anthropogenic impacts

Two unit analysis of Sri Lankan pygmy blue whale song over a decade

J.L.M.O. and S.L.N. were funded by the Office of Naval Research (Award No. N000141110619). D.V.H. was funded by the Office of Naval Research (Award No. N000141612364).Sri Lankan pygmy blue whale song consists of three repeated units: (1) low frequency pulsive unit, (2) frequency modulated (FM) upsweep, and (3) long tonal downsweep. The Unit 2 FM unit has up to three visible upsweeps with energy concentrated at approximately 40, 50, and 60 Hz, while the Unit 3 (∼100 Hz) tonal downsweep is the most distinct unit lasting 20–30 s. Spectral characteristics of the Units 2 and 3 song elements, along with ocean sound levels, were analyzed in the Indian Ocean from 2002 to 2013. The peak frequency of the tonal Unit 3 calls decreased from approximately 106.5 to 100.7 Hz over a decade corresponding to a 5.4% decrease. Over the same time period, the frequency content of the Unit 2 upsweeps did not change as dramatically with only a 3.1% change. Ambient sound levels in the vocalization bands did not exhibit equivalent patterns in amplitude trends. Analysis showed no increase in the ambient sound or compensated peak amplitude levels of the tonal downsweeps, eliminating the presence of a Lombard effect. Here it is proposed that each song unit may convey different information and thus may be responding to different selective pressures.PostprintPeer reviewe

Drone Up! Quantifying Whale Behavior From a New Perspective Improves Observational Capacity

During traditional boat-based surveys of marine megafauna, behavioral observations are typically limited to records of animal surfacings obtained from a horizontal perspective. Achieving an aerial perspective has been restricted to brief helicopter or airplane based observations that are costly, noisy, and risky. The emergence of commercial small unmanned aerial systems (UAS) has significantly reduced these constraints to provide a stable, relatively quiet, and inexpensive platform that enables replicate observations for prolonged periods with minimal disturbance. The potential of UAS for behavioral observation appears immense, yet quantitative proof of utility as an observational tool is required. We use UAS footage of gray whales foraging in the coastal waters of Oregon, United States to develop video behavior analysis methods, determine the change in observation time enabled by UAS, and describe unique behaviors observed via UAS. Boat-based behavioral observations from 53 gray whale sightings between May and October 2016 were compared to behavioral data extracted from video analysis of UAS flights during those sightings. We used a DJI Phantom 3 Pro or 4 Advanced, recorded video from an altitude ≥25 m, and detected no behavioral response by whales to the UAS. Two experienced whale ethologists conducted UAS video behavioral analysis, including tabulation of whale behavior states and events, and whale surface time and whale visible time (total time the whale was visible including underwater). UAS provided three times more observational capacity than boat-based observations alone (300 vs. 103 min). When observation time is accounted for, UAS data provided more and longer observations of all primary behavior states (travel, forage, social, and rest) relative to boat-based data, especially foraging. Furthermore, UAS enable documentation of multiple novel gray whale foraging tactics (e.g., headstands: n = 58; side-swimming: n = 17; jaw snapping and flexing: n = 10) and 33 social events (nursing and pair coordinated surfacings) not identified from boat-based observation. This study demonstrates the significant added value of UAS to marine megafauna behavior and ecological studies. With technological advances, robust study designs, and effective analytical tools, we foresee increased UAS applications to marine megafauna studies to elucidate foraging strategies, habitat associations, social patterns, and response to human disturbance

Drone Up! Quantifying Whale Behavior From a New Perspective Improves Observational Capacity

During traditional boat-based surveys of marine megafauna, behavioral observations are typically limited to records of animal surfacings obtained from a horizontal perspective. Achieving an aerial perspective has been restricted to brief helicopter or airplane based observations that are costly, noisy, and risky. The emergence of commercial small unmanned aerial systems (UAS) has significantly reduced these constraints to provide a stable, relatively quiet, and inexpensive platform that enables replicate observations for prolonged periods with minimal disturbance. The potential of UAS for behavioral observation appears immense, yet quantitative proof of utility as an observational tool is required. We use UAS footage of gray whales foraging in the coastal waters of Oregon, United States to develop video behavior analysis methods, determine the change in observation time enabled by UAS, and describe unique behaviors observed via UAS. Boat-based behavioral observations from 53 gray whale sightings between May and October 2016 were compared to behavioral data extracted from video analysis of UAS flights during those sightings. We used a DJI Phantom 3 Pro or 4 Advanced, recorded video from an altitude ≥25 m, and detected no behavioral response by whales to the UAS. Two experienced whale ethologists conducted UAS video behavioral analysis, including tabulation of whale behavior states and events, and whale surface time and whale visible time (total time the whale was visible including underwater). UAS provided three times more observational capacity than boat-based observations alone (300 vs. 103 min). When observation time is accounted for, UAS data provided more and longer observations of all primary behavior states (travel, forage, social, and rest) relative to boat-based data, especially foraging. Furthermore, UAS enable documentation of multiple novel gray whale foraging tactics (e.g., headstands: n = 58; side-swimming: n = 17; jaw snapping and flexing: n = 10) and 33 social events (nursing and pair coordinated surfacings) not identified from boat-based observation. This study demonstrates the significant added value of UAS to marine megafauna behavior and ecological studies. With technological advances, robust study designs, and effective analytical tools, we foresee increased UAS applications to marine megafauna studies to elucidate foraging strategies, habitat associations, social patterns, and response to human disturbance

Drone Up! Quantifying Whale Behavior From a New Perspective Improves Observational Capacity

During traditional boat-based surveys of marine megafauna, behavioral observations are typically limited to records of animal surfacings obtained from a horizontal perspective. Achieving an aerial perspective has been restricted to brief helicopter or airplane based observations that are costly, noisy, and risky. The emergence of commercial small unmanned aerial systems (UAS) has significantly reduced these constraints to provide a stable, relatively quiet, and inexpensive platform that enables replicate observations for prolonged periods with minimal disturbance. The potential of UAS for behavioral observation appears immense, yet quantitative proof of utility as an observational tool is required. We use UAS footage of gray whales foraging in the coastal waters of Oregon, United States to develop video behavior analysis methods, determine the change in observation time enabled by UAS, and describe unique behaviors observed via UAS. Boat-based behavioral observations from 53 gray whale sightings between May and October 2016 were compared to behavioral data extracted from video analysis of UAS flights during those sightings. We used a DJI Phantom 3 Pro or 4 Advanced, recorded video from an altitude >= 25 m, and detected no behavioral response by whales to the UAS. Two experienced whale ethologists conducted UAS video behavioral analysis, including tabulation of whale behavior states and events, and whale surface time and whale visible time (total time the whale was visible including underwater). UAS provided three times more observational capacity than boat-based observations alone (300 vs. 103 min). When observation time is accounted for, UAS data provided more and longer observations of all primary behavior states (travel, forage, social, and rest) relative to boat-based data, especially foraging. Furthermore, UAS enable documentation of multiple novel gray whale foraging tactics (e.g., headstands: n = 58; side-swimming: n = 17; jaw snapping and flexing: n = 10) and 33 social events (nursing and pair coordinated surfacings) not identified from boat-based observation. This study demonstrates the significant added value of UAS to marine megafauna behavior and ecological studies. With technological advances, robust study designs, and effective analytical tools, we foresee increased UAS applications to marine megafauna studies to elucidate foraging strategies, habitat associations, social patterns, and response to human disturbance

Confirmation of right whales near a historic whaling ground east of southern Greenland

North Atlantic right whales (Eubalaena glacialis) were found in an important nineteenth century whaling area east of southern Greenland, from which they were once thought to have been extirpated. In 2007–2008, a 1-year passive acoustic survey was conducted at five sites in and near the ‘Cape Farewell Ground’, the former whaling ground. Over 2000 right whale calls were recorded at these sites, primarily during July–November. Most calls were northwest of the historic ground, suggesting a broader range in this region than previously known. Geographical and temporal separation of calls confirms use of this area by multiple animals.This is the author's final peer-reviewed manuscript as accepted by the publisher, Royal Society. The publisher's pdf can be found at Biology Letters: http://rsbl.royalsocietypublishing.org

Sounds from airguns and fin whales recorded in the mid-Atlantic Ocean, 1999-2009

Between 1999 and 2009, autonomous hydrophones were deployed to monitor seismic activity from 16° N to 50° N along the Mid-Atlantic Ridge. These data were examined for airgun sounds produced during offshore surveys for oil and gas deposits, as well as the 20 Hz pulse sounds from fin whales, which may be masked by airgun noise. An automatic detection algorithm was used to identify airgun sound patterns, and fin whale calling levels were summarized via long-term spectral analysis. Both airgun and fin whale sounds were recorded at all sites. Fin whale calling rates were higher at sites north of 32° N, increased during the late summer and fall months at all sites, and peaked during the winter months, a time when airgun noise was often prevalent. Seismic survey vessels were acoustically located off the coasts of three major areas: Newfoundland, northeast Brazil, and Senegal and Mauritania in West Africa. In some cases, airgun sounds were recorded almost 4000 km from the survey vessel in areas that are likely occupied by fin whales, and at some locations airgun sounds were recorded more than 80% days/month for more than 12 consecutive months

An open access dataset for developing automated detectors of Antarctic baleen whale sounds and performance evaluation of two commonly used detectors

Since 2001, hundreds of thousands of hours of underwater acoustic recordings have been made throughout the Southern Ocean south of 60° S. Detailed analysis of the occurrence of marine mammal sounds in these circumpolar recordings could provide novel insights into their ecology, but manual inspection of the entirety of all recordings would be prohibitively time consuming and expensive. Automated signal processing methods have now developed to the point that they can be applied to these data in a cost-efective manner. However training and evaluating the efcacy of these automated signal processing methods still requires a representative annotated library of sounds to identify the true presence and absence of diferent sound types. This work presents such a library of annotated recordings for the purpose of training and evaluating automated detectors of Antarctic blue and fn whale calls. Creation of the library has focused on the annotation of a representative sample of recordings to ensure that automated algorithms can be developed and tested across a broad range of instruments, locations, environmental conditions, and years. To demonstrate the utility of the library, we characterise the performance of two automated detection algorithms that have been commonly used to detect stereotyped calls of blue and fn whales. The availability of this library will facilitate development of improved detectors for the acoustic presence of Southern Ocean blue and fn whales. It can also be expanded upon to facilitate standardization of subsequent analysis of spatiotemporal trends in call-density of these circumpolar species.http://www.nature.com/srep/index.htmlpm2022Mammal Research Institut

Temporal segregation of the Australian and Antarctic blue whale call types (Balaenoptera musculus spp.)

We examined recordings from a 15-month (May 2009–July 2010) continuous acoustic data set collected from a bottom-mounted passive acoustic recorder at a sample frequency of 6kHz off Portland, Victoria, Australia (38°33′01″S, 141°15′13″E) off southern Australia. Analysis revealed that calls from both subspecies were recorded at this site, and general additive modeling revealed that the number of calls varied significantly across seasons. Antarctic blue whales were detected more frequently from July to October 2009 and June to July 2010, corresponding to the suspected breeding season, while Australian blue whales were recorded more frequently from March to June 2010, coinciding with the feeding season. In both subspecies, the number of calls varied with time of day; Antarctic blue whale calls were more prevalent in the night to early morning, while Australian blue whale calls were detected more often from midday to early evening. Using passive acoustic monitoring, we show that each subspecies adopts different seasonal and daily call patterns which may be related to the ecological strategies of these subspecies. This study demonstrates the importance of passive acoustics in enabling us to understand and monitor subtle differences in the behavior and ecology of cryptic sympatric marine mammals.This is the publisher’s final pdf. The published article is copyrighted by the author(s) and published by Oxford University Press on behalf of American Society of Mammalogists. The published article can be found at: http://jmammal.oxfordjournals.org/content/96/3/603Keywords: cryptic sympatric marine mammals, seasonal, diel, Australia, calls, Balaenoptera musculus intermedia, Balaenoptera musculus brevicauda, ecology, vocalizationsKeywords: cryptic sympatric marine mammals, seasonal, diel, Australia, calls, Balaenoptera musculus intermedia, Balaenoptera musculus brevicauda, ecology, vocalization