@article {58467, title = {Temporal occurrence of three blue whale populations in New Zealand waters from passive acoustic monitoring}, journal = {Journal of Mammalogy}, year = {2022}, abstract = {

Describing spatial and temporal occurrence patterns of wild animal populations is important for understanding their evolutionary trajectories, population connectivity, and ecological niche specialization, with relevance for effective management. Throughout the world, blue whales produce stereotyped songs that enable identification of separate acoustic populations. We harnessed continuous acoustic recordings from five hydrophones deployed in the South Taranaki Bight (STB) region of Aotearoa New Zealand from January 2016 to February 2018. We examined hourly presence of songs from three different blue whale populations to investigate their contrasting ecological use of New Zealand waters. The New Zealand song was detected year-round with a seasonal cycle in intensity (peak February\–July), demonstrating the importance of the region to the New Zealand population as both a foraging ground and potential breeding area. The Antarctic song was present in two distinct peaks each year (June\–July; September\–October) and predominantly at the offshore recording locations, suggesting northbound and southbound migration between feeding and wintering grounds. The Australian song was only detected during a 10-day period in January 2017, implying a rare vagrant occurrence. We therefore infer that the STB region is the primary niche of the New Zealand population, a migratory corridor for the Antarctic population, and outside the typical range of the Australian population.

}, keywords = {bioacoustics, blue whale, distribution, ecology, marine mammals, New Zealand, passive acoustic monitoring, populations, vocalizations}, doi = {10.1093/jmammal/gyac106}, url = {https://doi.org/10.1093/jmammal/gyac106}, author = {Dawn R Barlow and Holger Klinck and Dimitri Ponirakis and Mattea Holt Colberg and Leigh G. Torres} } @article {53537, title = {Song variation of the South Eastern Indian Ocean pygmy blue whale population in the Perth Canyon, Western Australia}, journal = {PLOS ONE}, volume = {14}, year = {2019}, month = {Oct-01-2020}, pages = {e0208619}, abstract = {

Sea noise collected over 2003 to 2017 from the Perth Canyon, Western Australia was analysed for variation in the South Eastern Indian Ocean pygmy blue whale song structure. The primary song-types were: P3, a three unit phrase (I, II and III) repeated with an inter-song interval (ISI) of 170\–194 s; P2, a phrase consisting of only units II \& III repeated every 84\–96 s; and P1 with a phrase consisting of only unit II repeated every 45\–49 s. The different ISI values were approximate multiples of each other within a season. When comparing data from each season, across seasons, the ISI value for each song increased significantly through time (all fits had p \<\< 0.001), at 0.30 s/Year (95\%CI 0.217\–0.383), 0.8 s/Year (95\%CI 0.655\–1.025) and 1.73 s/Year (95\%CI 1.264\–2.196) for the P1, P2 and P3 songs respectively. The proportions of each song-type averaged at 21.5, 24.2 and 56\% for P1, P2 and P3 occurrence respectively and these ratios could vary by up to \± 8\% (95\% CI) amongst years. On some occasions animals changed the P3 ISI to be significantly shorter (120\–160 s) or longer (220\–280 s). Hybrid song patterns occurred where animals combined multiple phrase types into a repeated song. In recent years whales introduced further complexity by splitting song units. This variability of song-type and proportions implies abundance measure for this whale sub population based on song detection needs to factor in trends in song variability to make data comparable between seasons. Further, such variability in song production by a sub population of pygmy blue whales raises questions as to the stability of the song types that are used to delineate populations. The high level of song variability may be driven by an increasing number of background whale callers creating \‘noise\’ and so forcing animals to alter song in order to \‘stand out\’ amongst the crowd.

}, doi = {10.1371/journal.pone.0208619}, url = {http://dx.plos.org/10.1371/journal.pone.0208619}, author = {Jolliffe, Capri D. and McCauley, Robert D. and Gavrilov, Alexander N. and Jenner, K. Curt S. and Jenner, Micheline-Nicole M. and Duncan, Alec J.}, editor = {Matsumoto, Haru} } @article {53521, title = {Two unit analysis of Sri Lankan pygmy blue whale song over a decade}, journal = {The Journal of the Acoustical Society of America}, volume = {144}, year = {2018}, month = {Jan-12-2018}, pages = {3618 - 3626}, abstract = {

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.

}, issn = {0001-4966}, doi = {10.1121/1.5084269}, url = {http://asa.scitation.org/doi/10.1121/1.5084269}, author = {Jennifer L. Miksis-Olds and Nieukirk, Sharon L. and Danielle V. Harris} } @article {53357, title = {Long-Term and Seasonal Changes of Large Whale Call Frequency in the Southern Indian Ocean}, journal = {Journal of Geophysical Research: Oceans}, year = {2018}, month = {Mar-11-2020}, abstract = {

In the past decades, in the context of a changing ocean submitted to an increasing human activity, a progressive decrease in the frequencies (pitch) of blue whale vocalizations has been observed worldwide. Its causes, of natural or anthropogenic nature, are still unclear. Based on 7 years of continuous acoustic recordings at widespread sites in the southern Indian Ocean, we show that this observation stands for five populations of large whales. The frequency of selected units of vocalizations of fin, Antarctic, and pygmy blue whales has steadily decreased at a rate of a few tenths of hertz per year since 2002. In addition to this interannual frequency decrease, blue whale vocalizations display seasonal frequency shifts. We show that these intra-annual shifts correlate with seasonal changes in the ambient noise near their call frequency. This ambient noise level, in turn, shows a strong correlation with the seasonal presence of icebergs, which are one of the main sources of oceanic noise in the Southern Hemisphere. Although cause-and-effect relationships are difficult to ascertain, wide-ranging changes in the acoustic environment seem to have a strong impact on the vocal behavior of large baleen whales. Seasonal frequency shifts may be due to short-term changes in the ambient noise, and the interannual frequency decline to long-term changes in the acoustic properties of the ocean and/or in postwhaling changes in whale abundances.

}, doi = {10.1029/2018JC014352}, url = {http://doi.wiley.com/10.1029/2018JC014352}, author = {Leroy, Emmanuelle C. and Royer, Jean-Yves and Bonnel, Julien and Samaran, Flore} } @article {53329, title = {Environmental evidence for a pygmy blue whale aggregation area in the Subtropical Convergence Zone south of Australia}, journal = {Marine Mammal Science}, volume = {34}, year = {2018}, month = {Jan-10-2018}, pages = {901 - 923}, abstract = {

The importance of the Subtropical Convergence Zone south of Australia as a feeding area to the pygmy blue whale of the eastern Indian Ocean was investigated to better understand migration patterns and habitat use. A combination of satellite tagging studies during 2003\–2005 and acoustic and visual surveys during the austral summer of 2013 confirmed the presence of pygmy blue whales in the Subtropical Convergence Zone and provided evidence for feeding throughout the region. Of the 67 pygmy blue whales acoustically detected, many were localized in proximity to sea surface temperature fronts and high chlorophyll concentrations, which could be a behavioral strategy to attract conspecifics to good feeding sites. Aggregations of up to four pygmy blue whales, along with decreased call rates during the day, may suggest feeding despite no direct observations of pygmy blue whales consuming euphausiids. The oceanographic features present throughout the Subtropical Convergence Zone continue to create an environment productive enough to support the world\&$\#$39;s largest living mammals during their migratory foraging movements between the Southern Ocean and Indonesia.

}, doi = {10.1111/mms.v34.410.1111/mms.12494}, url = {http://doi.wiley.com/10.1111/mms.v34.4}, author = {Garcia-Rojas, Maria I. and Jenner, K. Curt S. and Gill, Peter C. and Jenner, Micheline-Nicole M. and Sutton, Alicia L. and McCauley, Robert D.} } @article {53297, title = {Detection and classification of whales calls using band-limited energy detection and transfer learning}, journal = {The Journal of the Acoustical Society of America}, volume = {144}, year = {2018}, month = {Jan-09-2018}, pages = {1769 - 1769}, abstract = {

The Monterey Bay Aquarium Research Institute has been recording since July 2015 almost continuously at the Monterey Accelerated Research System (MARS) cabled observatory in Monterey Bay, California, USA. This long-term recording contains thousands of whale calls to help further our understanding of interannual, seasonal, and diel patterns. Here we report on our highly accurate detection and classification method developed to classify blue whale A, B, and D calls and Fin whale 20 Hz pulses. The foundation of the method is a computationally efficient and tuned decimation filter to convert the broadband hydrophone 128 kHz signal to 2 kHz which preserves the low-frequency signal and avoids any high-frequency aliasing. Detection is done using a band-limited-energy-detection filter to find potential calls in the decimated data. Spectrograms are then generated for potential calls and enhanced with local image normalization followed by smoothing by convolving in either time or frequency. Classification is done using the Google Inception v3 model with a transfer learning method. Overall, false positive rates are very low despite variability in whale call shape and background noise.

}, issn = {0001-4966}, doi = {10.1121/1.5067825}, url = {http://asa.scitation.org/doi/10.1121/1.5067825}, author = {Cline, Danelle E. and Ryan, John P.} } @article {53103, title = {On the reliability of acoustic annotations and automatic detections of Antarctic blue whale calls under different acoustic conditions}, journal = {The Journal of the Acoustical Society of America}, volume = {144}, year = {2018}, month = {Jan-08-2018}, pages = {740 - 754}, abstract = {

Evaluation of the performance of computer-based algorithms to automatically detect mammalian vocalizations often relies on comparisons between detector outputs and a reference data set, generally obtained by manual annotation of acoustic recordings. To explore the reproducibility of these annotations, inter- and intra-analyst variability in manually annotated Antarctic blue whale (ABW) Z-calls are investigated by two analysts in acoustic data from two ocean basins representing different scenarios in terms of call abundance and background noise. Manual annotations exhibit strong inter- and intra-analyst variability, with less than 50\% agreement between analysts. This variability is mainly caused by the difficulty of reliably and reproducibly distinguishing single calls in an ABW chorus made of overlaying distant calls. Furthermore, the performance of two automated detectors, based on spectrogram correlation or subspace-detection strategy, is evaluated by comparing detector output to a \“conservative\” manually annotated reference data set, which comprises only analysts\&$\#$39; matching events. This study highlights the need for a standardized approach for human annotations and automatic detections, including a quantitative description of their performance, to improve the comparability of acoustic data, which is particularly relevant in the context of collaborative approaches in collecting and analyzing large passive acoustic data sets.

}, issn = {0001-4966}, doi = {10.1121/1.5049803}, url = {http://asa.scitation.org/doi/10.1121/1.5049803}, author = {Leroy, Emmanuelle C. and Thomisch, Karolin and Royer, Jean-Yves and Boebel, Olaf and Van Opzeeland, Ilse} } @article {53064, title = {Context-dependent variability in blue whale acoustic behaviour}, journal = {Royal Society Open Science}, volume = {5}, year = {2018}, abstract = {

Acoustic communication is an important aspect of reproductive, foraging and social behaviours for many marine species. Northeast Pacific blue whales (Balaenoptera musculus) produce three different call types\—A, B and D calls. All may be produced as singular calls, but A and B calls also occur in phrases to form songs. To evaluate the behavioural context of singular call and phrase production in blue whales, the acoustic and dive profile data from tags deployed on individuals off southern California were assessed using generalized estimating equations. Only 22\% of all deployments contained sounds attributed to the tagged animal. A larger proportion of tagged animals were female (47\%) than male (13\%), with 40\% of unknown sex. Fifty per cent of tags deployed on males contained sounds attributed to the tagged whale, while only a few (5\%) deployed on females did. Most calls were produced at shallow depths (less than 30\ m). Repetitive phrasing (singing) and production of singular calls were most common during shallow, non-lunging dives, with the latter also common during surface behaviour. Higher sound production rates occurred during autumn than summer and they varied with time-of-day: singular call rates were higher at dawn and dusk, while phrase production rates were highest at dusk and night.

}, keywords = {acoustic communication, Balaenoptera musculus, behavioural context, blue whale, song}, doi = {10.1098/rsos.180241}, url = {http://rsos.royalsocietypublishing.org/lookup/doi/10.1098/rsos.180241https://syndication.highwire.org/content/doi/10.1098/rsos.180241}, author = {Lewis, Leah A. and Calambokidis, John and Stimpert, Alison K. and Fahlbusch, James and Friedlaender, Ari S. and McKenna, Megan F. and Mesnick, Sarah L. and Southall, Brandon L. and Szesciorka, Angela R. and {\v S}irovi{\'c}, Ana} } @article {16153, title = {Seasonal acoustic behavior of blue whales ( Balaenoptera musculus ) in the Gulf of California, Mexico}, journal = {Marine Mammal Science}, volume = {33}, year = {2017}, month = {Jan-01-2017}, pages = {206 - 218}, doi = {10.1111/mms.2017.33.issue-110.1111/mms.12362}, url = {http://doi.wiley.com/10.1111/mms.2017.33.issue-1}, author = {Paniagua-Mendoza, Aurora and Gendron, Diane and Romero-Vivas, Eduardo} } @article {16152, title = {Using calls as an indicator for Antarctic blue whale occurrence and distribution across the southwest Pacific and southeast Indian Oceans}, journal = {Marine Mammal Science}, volume = {33}, year = {2017}, month = {Jan-01-2017}, pages = {172 - 186}, doi = {10.1111/mms.2017.33.issue-110.1111/mms.12373}, url = {http://doi.wiley.com/10.1111/mms.2017.33.issue-1}, author = {Balcazar, Naysa E. and Klinck, Holger and Nieukirk, Sharon L. and Mellinger, David K. and Klinck, Karolin and Dziak, Robert P. and Rogers, Tracey L.} }