Singing to the sound of their own tune: Uncovering an increasingly complex vocal repertoire for the east Indian Ocean pygmy blue whale

Singing to the sound of their own tune: Uncovering an increasingly complex vocal repertoire for the east Indian Ocean pygmy blue whale | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Singing to the sound of their own tune: Uncovering an increasingly complex vocal repertoire for the east Indian Ocean pygmy blue whale Capri Jolliffe, Craig McPherson, Robert McCauley This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7938626/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract In an underwater world, acoustic signalling is an important aspect of the social communication of marine mammal species with the complexity of a species’ vocal repertoire often considered to reflect the social complexity of the population. The acoustic behaviour of blue whales is relatively well studied, though much of what is known is limited to the characteristically loud, low frequency songs that are believed to be produced as a reproductive display by male animals. Blue whales are known to produce song units outside of stereotypical song sequences, along with short duration down swept signals known as ‘D calls’ leading researchers to believe their acoustic communication, and by proxy their social cognition is relatively less complex when compared to other baleen whales such as humpback and bowhead whales. Drawing from a multidecadal data set of acoustic recorders deployed throughout the migratory range of blue whales, this paper characterises four previously undescribed signals for the East Indian Ocean pygmy blue whales and presents the first known evidence of a large baleen whale producing these social sounds in stereotyped patterned sequences that bear similarity to song. This indicate a higher level of complexity in the social communication of blue whales than previously understood and provides further support that blue whales have a higher level of social cognition than has been considered previously. Biological sciences/Zoology/Animal behaviour Physical sciences/Physics/Applied physics/Acoustics Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 1.0 INTRODUCTION Many cetaceans, including blue whales, have a large repertoire of sounds, many of which are region or population specific. The acoustic distinction of populations may be of critical importance for reproduction and migration, as well as allowing geographically distinct populations to communicate at the optimum frequency for their specific environment 1 . Blue whale ( Balaenoptera musculus spp ) calls are characteristically low frequency ( 175 dB re 1 µPa SPL source level; 2 ). These acoustic properties of blue whale calls mean that signals propagate over vast distances. Blue whales arrange some of these calls, which can be called units, into stereotypical sequences that are called phrases, and repeated in a consistent pattern that meets the definition of song (Jolliffe et al., 2019; McDonald et al., 2006). Blue whale song phrases are typically comprised of two to three song units 3 , with some level of variability in the production of these units and phrases between the songs of individual whales (Jolliffe et al., 2023, 2024; Jolliffe et al., 2019). While the individual units that comprise songs have been observed being produced by both male and female animals, only males have been observed to arrange their units into phrases and produce them in repetitive song sequences 4 . Songs are thus assumed to be a reproductive display, produced by males to attract females and mediate interactions with other males, consistent with the use of song in other baleen whales and singing animals 5 , 6 . Blue whale vocalisations are typically population specific with subpopulations defined by geographic range and song structure. Based on calling behaviour, blue whales found in the Southern Hemisphere have been separated into six acoustically distinct populations, one of Antarctic blue whales, and four vocally distinct pygmy blue whale populations separated by song types into Sri Lankan, Madagascan, “Australian” (referred to here as EIOPB), Chilean, New Zealand and most recently the Chagos population 7 – 10 . As such the correct classification of song types is important for successful acoustic monitoring of populations. To date, the body of research into blue whales has been dominated by passive acoustic based research programs and focused largely on using song to identify populations, and their spatial and temporal distributions (McDonald et al., 2006). While this approach has been incredibly valuable, studies focused solely on song may only be representative of a portion of the population, being sexually mature males. Non-song vocal behaviour in blue whales is less well understood, however both male and female blue whales are known to produce song units singularly outside of repetitive song structures, as well as a variety of frequency and amplitude modulated social sounds, including short low frequency downswept tones with harmonics 4 , 11 . Reports of social sounds in blue whales have typically been sparse and are mostly limited to observations of singular song units and downswept calls (‘D calls’) 12–15 . However, a review of the literature reveals inconsistent classification of social sounds (typically AM/FM with harmonics or overtones) and true ‘D calls’, which do not have harmonics or overtones (Schall et al., 2020). The song of the Eastern Indian Ocean Pygmy blue whale ( Balaenoptera musculus brevicauda ) is known to have several structural variants, though is comprised of between one and three stereotypical song units, termed type I, type II and type III units 1 repeated in either a consistent or alternating pattern 1 . These song units are all characteristically low frequency ( 18 sec) sounds with fundamental frequencies in the 20 to 28 Hz range and harmonics. The EIOPB whale is also known to produce a handful of social sounds that are distinct from song units and the downswept ‘D’ calls that are common to all populations of blue whales 11 . Social sounds for this population have previously been characterised from paired visual and acoustic studies in Geographe Bay, Western Australia. These sounds are typically short duration (< 10 s), frequency modulated, tonal sounds between 25 and 100 Hz. These previously identified social sounds are defined in Recalde-Salas et al. (2014) and have been named EIO1, EIO2, EIO3, EIO4 and EIO5 11 . Studying the interspecific communication of populations can provide valuable clues as to the evolution of vocal systems and mechanisms for vocal learning within a population 1 . While song in marine mammals is commonly accepted to be a reproductive display, the purpose and behavioural context of social sounds is less understood. The first step to understanding the vocal behaviour of blue whale populations is a more holistic understanding of their vocal repertoire. Focused studies on vocal behaviour outside of song displays also has the benefit of providing information on species presence and distribution that is not biased towards mature males. Investigating vocal repertoires may also provide further information on the social complexity of marine mammals’ lives as well as an indication of cognitive capacity. This study presents evidence that the vocal repertoire of the EIOPB whale population is more complex than previously thought and defines four new social sounds for the population that are similar in characteristics to previously documented social sounds for this population and song units for blue whales globally. This study also presents evidence of these signals occurring in ordered sequences akin to phrases and repeated, meeting the definition typically applied to whale song. Such an observation presents questions regarding the purpose of social signals and suggests a higher level of vocal and cognitive complexity in the EIOPB population than has been documented for any other rorqual whale population worldwide. 2.0 METHODS 2.1 Study Location Data were collected across four years from eight sample sites on the North West Shelf (NW Shelf) off Western Australia and the Perth Canyon, west of Rottnest Island, Western Australia (Fig. 1 , Table 1 ). The NW Shelf and Perth Canyon data collection sites fall within the migratory corridor for the EIOPB whale, with some NW Shelf sites and the Perth Canyon sites also sitting within defined foraging areas (Fig. 1 ). Recorders were deployed at depths of between 90 and 250 m, with deployment periods of between 77 and 310 days (Table 1 ). Table 1 Dataset locations and deployment dates Dataset ID Year Location Name Latitude (S) Longitude (E) Start Date End Date Recorder Type Data Source 1 2010–2012 Western Timor Sea 11° 36.026' 125° 9.266' 02 Dec 2010 9 Jun 2011 AURAL M2 (single channel) JASCO/PTTEP 2 09 Jun 2011 13 Dec 2012 3 2012–2014 Seringapatam Reef - West 13° 38.075' 121° 51.922' 9 Oct 2012 23 Feb 2014 AMAR G3 (single channel) JASCO/ConocoPhillips 4 2012–2014 Seringapatam Reef – East 13° 28.558' 122° 17.911' 9 Oct 2012 22 Feb 2014 JASCO/ConocoPhillips 5 2013–2014 IMOS Kimberley 15° 38.730' 121° 25.254' 01/10/2013 2 Jun 2014 CMST IMOS 6 2014–2015 IMOS Kimberley 19/08/2014 8 May 2015 IMOS 7 2012-13 IMOS Pilbara 19° 25.488' 115° 53.028' 20-Nov-12 16 Oct 2013 IMOS 8 2023–2025 Western Timor Sea 12° 57.981' 124° 4.430' 25 Sep 2023 15 Mar 2025 ALTO Mooring - AMAR UD (Directional) JASCO/Shell 9 2023–2025 Western Timor Sea 12° 58.057' 123° 42.304' 25 Sep 2023 15 Mar 2025 10 November 2024 Perth Canyon – Glider Area 31° 46.219' 114° 42.915' 1 Nov 2024 15 Nov 2024 OceanObserver™ (Directional) and AMAR (Directional) installed on Slocum glider JASCO 11 31° 46.219' 115° 18.836' 12 April-May 2025 32° 10.045' 115° 18.836' 26 April 2025 8 May 2025 13 32° 10.045' 114° 42.915' 2.2 Data Collection Methods CMST Deployments For the IMOS moorings, data were collected using Curtin University CMST-DSTO autonomous underwater sound recorders, described in McCauley et al. (2017). White noise of a known Power Spectral Density (PSD) level was used to calibrate the recording system response pre and post deployment with the hydrophone in sequence. Calibrated data was available from 1 Hz to the Nyquist frequency. Recorders sampled at a 6 kHz sample rate, with recordings of 5 to 7 minutes every 9 minute. A 2.8 kHz anti-liaising filter with a gentle high-pass filter and roll off below 8 Hz was used to flatten the low frequency noise curve. Autonomous Underwater Recorders for Acoustic Listening-Model 2 (AURAL-M2) AURAL-M2s (Multi-Electronique Ltd.) with a single omnidirectional hydrophone were employed for the PTTEP study in 2011. Data were recorded on dual 320GB hard drives at 16-bit resolution with 32 768 samples per second. The AURALs were fitted with HTI-96 hydrophones, which have a nominal sensitivity of 164 dBV re 1 µPa and gain set of 22 dB. The spectral density noise floor of the AURALs in this configuration is approximately 57 dB re 1 µPa, and the usable bandwidth is 10–16 000Hz. The AURALS were calibrated with a pistonphone type 42AC precision sound source (G.R.A.S. Sound & Vibration A/S) using a constant 250 Hz. The duty cycle for the first deployment was 49%, and for the second 46%, recording once every hour. Autonomous Multichannel Acoustic Recorders Generation 3 For the Seringapatam deployments in 2012–2014, AMAR G3 (JASCO) were used. Each recorder was fitted with an M8E calibrated omnidirectional hydrophone (GeoSpectrum Technologies Inc., − 165 ± 5 dB re 1 V/µPa nominal sensitivity) and set for a gain of 0 dB. Data were recorded on the 24-bit channel sampling at 64 kHz and stored onto 1.8 TB of internal solid-state memory. The recorders have an equivalent spectral noise floor of 23 dB re 1 µPa 2 /Hz at 64 kHz. The three deployments used different sampling configuration: for the first deployment the recorders sampled at a 50% duty cycle, 1800 s (30 min) per hour, then for the second the recorders sampled at a 33% duty cycle, 1190 s (19.83 min) per hour, and for the third the recorders sampled at a 75% duty cycle, 2700 s (45 min) per hour. Autonomous Long Term Observatory Deployments Underwater sound was recorded with AMAR Generation 4 (G4) Ultra Deep (JASCO) in glass sphere housings. Each AMAR was installed on an Autonomous Long-Term Observatory (ALTO, JASCO) lander. The ALTO is equipped with an orthogonal array of four M36 omnidirectional hydrophones (GeoSpectrum Technologies Inc., − 165 ± 3 dB re 1 V/µPa sensitivity) spaced between approximately 0.5 m and 2 m apart. By using beamforming analysis methods, the direction of arrival of sounds can be determined from the four hydrophones 16 . The hydrophones were protected by a hydrophone cage, which was covered with an open-cell foam shroud to minimise non-acoustic noise caused by water flowing over the hydrophone transducer (‘flow noise’). The AMARs recorded continuously with a duty cycle of 15 mins at a sampling rate of 32 kHz followed by 1 min at 256 kHz. The recording channel had 24‑bit resolution with a spectral noise floor of 20 dB re 1 µPa2/Hz and a nominal ceiling of 171 dB re 1 µPa. Acoustic data were stored on 7.68 TB of internal solid-state flash memory. OceanObserver™ and AMAR G4 For the Perth Canyon glider deployments in 2024 and 2025, Teledyne Slocum G3 gliders mounted OceanObserver™ and AMAR G4 systems were equipped with an array of four M36 omnidirectional hydrophones, with beamforming analysis methods as described above applied. The recorders operated continuously at a sampling rate of 8 kHz. The recording channel had 24‑bit resolution with a spectral noise floor of 20 dB re 1 µPa2/Hz and a nominal ceiling of 171 dB re 1 µPa. Acoustic data were stored on 7.68 TB of internal solid-state flash memory. 2.2 Data Analysis CMST Deployments Spectrograms of sea noise were viewed using Raven software ( 17 ). Spectrograms were produced with a 1024 point FFT and a Hanning window with no overlap. All spectrograms were analysed manually for occurrences of blue whale song, D calls and social sounds. For the purpose of this study, D calls were classified as downswept signals from between 75 and 20 Hz of between 2 and 4 seconds with no harmonics or tonal elements. Social sounds were classified as short duration (2 to 10 s), low frequency sounds (10 to 150 Hz) that could be down sweeping tones, amplitude modulated, or frequency modulated with harmonics or tonal overtones. Within each sample, where present, one example of song was selected and one D call, while all examples of social sounds were selected for further analysis. JASCO Deployments A combination of automated detector-classifiers (referred to as automated detectors) and manual review by experienced analysts was used to determine the presence of sounds produced by marine mammals in the acoustic data. First, a suite of automated detectors was applied to the full data set. The automated tonal signal detector identified continuous contours of elevated energy and classified them against a library of marine mammal signals. JASCO’s suite of tonal automated detectors includes species/signal-specific detectors and those that are more generic, capturing signals from potentially more than one species that overlap in spectral characteristics. JASCO’s suite of automated detectors are developed, trained, and tested to be as reliable and broadly applicable as possible. However, the performance of marine mammal automated detectors varies across acoustic environments 18 , 19 , e.g. 20,21 . Therefore, automated detector results must always be supplemented by some level of manual review to evaluate automated detector performance. Here, a subset of acoustic files was manually analysed for the presence/absence of marine mammal acoustic signals via spectrogram review in JASCO’s PAMlab software. A subset of acoustic data representing 1% to 5% of low frequency sound files (depending upon deployment), was selected based on automated detector results via JASCO’s Automatic Data Selection for Validation (ADSV) algorithm 22 . Throughout the manual review, signals that were suspected to be social sounds produced by blue whales were selected for further analysis. Additional files were also opportunistically reviewed based upon manual review findings. 2.3 Signal Feature Analysis Where social sounds and other sounds suspected to be produced by blue whales were detected and repeated in sequence, the entire sequence was selected for detailed analysis. Social sounds, and other blue whale-like sounds were assumed to be produced by blue whales if they fit the characteristic description of existing defined signals or were similar in frequency range and appearance to other known blue whale signals, and occurred in the same hour as other known blue whale songs when there were no other species of whale acoustically present. This approach was supported through the identification of song sequences in which singing blue whale(s) transitioned from known song sequences to structured groups of new signals (Fig. 2 ). The Discrete Fourier Transform (DFT) settings used for analysis are key to signal identification. The typical DFT for blue whale song (Setting 1, Table 2 ) enable a file to be opened quickly and work very well for song, and provide a suitable resolution for tonal social signals longer then 4–6 s. These settings do not however, provide good resolution for shorter social signals and downswept calls. For these calls, Setting 2 (Table 2 ) is recommended for making call identification. Setting 3 can be used to create very clean, high-fidelity spectrograms of calls such as EIO1, however results in blurred details for calls such as EIO6 and EIO9 and is computationally inefficient. These settings were tested on all datasets analysed and found to have similar performance trends. Examples of social signal sequences were difficult to find with a good signal to noise ratio and no propagation effects. However sufficient examples of all call types were found for inclusion in this analysis, with a greater number of the more common social signal types (EIO1 and EIO9) being able to be observed clearly. Typically, individual signals, and sequences of signals, were observed with a signal to noise ratio that did not support detailed analysis. The signals often appeared to have low structural spectral resolution despite optimising the DFT settings, making spectrograms appear ‘blurry’. This is potentially due to closely grouped tonal elements, including overtones and harmonics, and the amplitude and frequency-modulated nature of the calls, making them prone to transmission effects. The source levels of these signals are currently unknown but is a subject of ongoing analysis requiring paired acoustic and visual observations. While blue whale social sounds were often detected, identification of the discrete signals and categorisation for the less common signal types was often challenging. Consequently, a small subset of social signals was selected for signal feature analysis. Signal features, including maximum and minimum frequency and signal duration, were extracted from selected signals using PAMlab ( https://www.jasco.com/pamlab ). Table 2 Discrete Fourier Transforms Setting Name DFT Frequency Step (Hz) DFT Temporal Observation Window (s) DFT Time Advance (s) Window Setting 1 – Long Calls 0.4 2 0.5 Hann Setting 2 – Social and Song 1 0.8 0.125 Setting 3 – High fidelity downsweeps 1 0.2 0.002 2.4 Signal Classification Signals were classified by comparing the spectral appearance and waveform envelope of target signals with existing known blue whale song units, and existing defined social sounds for all populations known to occur within Australian waters including the Antarctic, EIOPB, Chagos and New Zealand pygmy blue whale. Downswept signals were classified based on the absence or presence of multiple overtones as being either D calls or the previously defined EIO1 signal, respectively. While D calls did not have consistent harmonic overtones, they did occasionally have a single higher frequency downswept component when observed in low SNR conditions. This was not consistently observed however, and D calls were by their nature ‘consistently inconsistent’ in that even signals that appeared to originate from the same animal were not consistent in their spectral characteristics. This led to what analysts called a ‘shooting star’ effect where D calls would often appear in the spectrogram as random vertical lines in a manner that resembled the tails of shooting stars. The EIO1 signal by comparison was relatively consistent and always appeared as a more teardrop shaped down sweep with at least two and often more overtones. For the purpose, of this study a harmonic was defined as a higher frequency component that was an exact integer of the fundamental frequency. Short duration frequency modulated sounds were compared with the existing social sounds defined in Recalde-Salas et al. (2014). Sounds that did not match any predefined social sounds but were confidently attributed to blue whales were grouped with similar signals using a decision tree. A sound considered to be confidently attributable to a blue whale if it was a low frequency (< 100 Hz) frequency/amplitude modulated sound with harmonic or tonal elements that did not extend above 200 Hz and was detected in the presence of known blue whale signals. Signals were confidently assigned to blue whales if no other acoustically identifiable species of baleen whale was present in the sample or samples preceding and following the target sample. The exception was with directional recordings where Omura’s whale vocalisations were present but originated from a different direction to the social signals. While Omura’s whales are suspected to produce downswept signals like all other baleen whales, they are not known to produce the ‘blue whale like’ tonal FM and AM signals observed here and classified as social signals. These signals were then grouped based on their spectral appearance and characterised as new social signals and named as follows – EIO6, EIO7, EIO8, EIO9. Where social signals appeared in sequences, the composition and temporal patterns of these sequences were characterised through manual viewing of spectrograms in PAMLAB and feature analysis. 2.4 Testing Signal Groupings To test the appropriateness of the signal classifications, an interobserver reliability test was undertaken. A group of 12 independent observers were provided with a subset of 12 social sounds and asked to classify the social sounds based on comparison of the spectrograms with a catalogue of the newly identified signals, EIO1 and D calls. The group of observers include five trained and experienced analysts, and seven naïve analysts who had never undertaken any form of acoustic analysis before. Observers ranged in age from six to forty years old. A Fleiss Kappa test was conducted in R Studio on the classifications to test how similarly observers classified the signals. The Kappa statistic provides a statistical measure of the level of agreement between a group of raters, in this context providing an indication of whether the definitions of the newly defined social signals, and distinction between EIO1 and D calls is logical and justified. The Kappa statistic ranges from less than 0 to 1, with 1 indicating perfect agreement among observers. A Kappa of greater than 0.8 indicates near perfect agreement, while a Kappa of greater than 0.6 indicates good agreement, 0.4 to 0.6 indicates moderate agreement, 0.2 to 0.4 indicates fair agreement, 0 to 0.2 indicates slight agreement, and less than 0 indicates no agreement. Separate Fleiss Kappa tests were also run to test agreement between experienced observers only, as well as the classification of only D calls and EIO1 calls by all observers. 3.0 RESULTS 3.1 Blue whale social sounds A total of 61,391.87 h of acoustic data was manually analysed for blue whale signals as part of this study. Four of the five known social sounds for the EIOPB whale were detected in the datasets, as well as D calls and EIOPB whale song. Similarly to Miller, et al. 14 , D calls were classified as a distinct signal type from other downswept sounds and were characterised by a down sweeping signal between approximately 90 and 25 Hz of approximately 2 to 4 seconds in length, that were highly variable in their appearance and did not appear in any kind of orderly sequence. D calls did not have what would typically be referred to as harmonics or overtones, but rather when recorded at a high signal to noise ratio (SNR), occasionally had a higher frequency tonal component. These signals were also highly variable even when produced by what appeared to be the same animal based on the direction of origin and received level of the signal. By comparison, social sounds were frequency and/or amplitude modulated signals with over tones that were relatively consistent in their spectral characteristics and were typically produced at consistent intervals or in sequence with other social signals. An additional four signals, that were similar in structure and acoustic characteristics to known EIOPB social sounds were also detected and are described in further detail below. Consistent with the existing nomenclature for EIOPB social sounds, the signals were named EIO6, EIO7, EIO8 and EIO9. Spectrograms, produced with a 1024-point FFT and a Hanning window with no overlap, when compared with known EIOPB social sounds show similarities in the acoustic characteristics of the signals (Fig. 4 ) These signals were produced in samples with known EIOPB social sounds and at times of year when EIOPB song events were also present. There were no other known whale vocalisations detected within the samples (aside from Omura’s in some samples), and the signals originated in the same direction as known blue whale signals detected at a similar time. Figure 7 shows an example of an EIOPB song sequence that shifts from song into sequences of social sounds. These were recorded on a directional AMAR and there is no change in bearing and a relatively consistent received level indicating these signals originated from the same animals. The signals are also similar in their spectral characteristics to known blue whale social and song signals 3 , 4 , 11 , consequently these signals can be confidently attributed to blue whales. (top: 1 Hz discrete Fourier Transform (DFT) frequency step, 1 s DFT temporal observation window (TOW), 0.125 s DFT time advance, and Hann window; bottom: 1 Hz DFT frequency step, 0.2 s DFT TOW, 0.02 s DFT time advance, and Hann window). The spectrograms are 360 s and 60 s long, respectively. The colour scheme represents the direction of arrival of sound, as per the wheel on the top right corner. A subset of the signals were analysed for time and frequency statistics. These were drawn from datasets 8,9,11 and 12. All social signals were short duration frequency modulated sounds of between 2 and 16 sec in length and 10 and 204 Hz in frequency (Table 3 ). Deterministic chaos, defined as broadband, non-random noise like segments 23 was present in the signals named EIO6 and EIO9. Table 3 Summary of call parameters Signal Number of samples Time statistics (s) Frequency statistics (Hz) Mean length (s) STD length (s) Mean Centroid (Hz) Mean Low (Hz) Mean High (Hz) EIO1 91 4.84 1.94 49.78 29.63 200 EIO6 12 11.84 2.01 54.32 26.93 102.13 EIO7 10 6.96 3.55 44.9 15.83 111.72 EIO8 26 7.18 2.36 52.15 21.48 115.75 EIO9 48 6.03 1.69 63.4 67.99 98.42 Based on our analysis, D calls were typically short duration signals ranging in duration from 2 to 4 seconds and downsweeping from a maximum of 50 to 100 Hz, down to a minimum of 20 to 40 Hz. They did not have typical harmonics though a higher frequency tonal element was at times visible in some spectrograms with very high signal to noise ratio. They were also found to be prone to interference and transmission effects that occasionally resulted in a ‘mirrored’ signal. The previously defined EIO1 signal was found to be a consistently short duration signal of 3 to 6 seconds that had a characteristic tear drop shape and was downswept in frequency from a maximum of 70 to 200 Hz, to a minimum of around 30 Hz. Harmonics were always present with this signal type and typically three harmonics were clearly visible in the spectrograms. Newly defined social signals were more difficult to separate into clear groupings and were all slightly longer than the downswept D and EIO1 signals. The EIO6, 7 and 8 signals were all amplitude and frequency modulated signals that bore some similarities to the unit III of the EIOPB song type. These signals were typically between 5 and 16 seconds in length with fundamental frequencies around 25, 15 and 20 H respectively (Fig. 4 , Table 3 ). The upper most visible harmonic for these signals was typically around 100 to 110 Hz (Fig. 4 , Table 3 ). Deterministic chaos was present at the start of the EIO6 signal. No deterministic chaos was present in EIO7 and EIO8 signals which were the most similar of the social signals described. EIO7 signals were consistently lower in frequency with the peak energy at 20 to 50 Hz and clearly defined harmonics (Fig. 4 , Table 3 ). EIO8 signals typically had ‘M’ or ‘N’ shaped harmonics and were consistently slightly higher frequency with peak energy was at 35 to 75 Hz (Table 3 ). The EIO9 signal was shorter than the other non-downswept signals at between 5 and 10 seconds long and resembled the first portion of the Unit 1 of the EIOPB song. This signal was characterised by the presence of deterministic chaos at the end of the signal and peak energy around 65 Hz (Fig. 4 , Table 3 ). All four newly identified social signals were recorded at both the northwest shelf sample sites across all sample years, and the Perth Canyon sample sites (Table 4 ). These signals are not known to have been recorded in Geographe Bay based on the results of Recalde Salas et al. (2014), however it cannot be excluded that they may be present in more recent years. The social sound EIO1 has been recorded at all sample sites in all sample years and is the most commonly observed social sound, even outnumbering true D calls. D calls were observed at all northwest shelf sample sites in all years and in the Perth Canyon (Table 4 ). The social sounds EIO2 and EIO4, previously identified from Geographe Bay, were observed in very low numbers at the northwest shelf sample sites in 2014 and 2015 (Table 4 ). 3.2 Phrase and song patterns Socials sounds appeared on numerous occasions to be organised into phrases and repeated in a manner consistent with song. The first phrase consisted of an EIO6, and two EIO8 signals. This was followed about 10 s later by a phrase consisting of an EIO8, EIO9 and EIO1 unit. The two phrases were repeated consistently in this manner. In total, there were over 300 observations of social sounds occurring in structured sequences across all the data sets. However, this is based on manual review of only 5 to 10% of most of the data sets, and complete manual analysis only of the three IMOS data sets. Despite this, structured sequences of social sounds comprised a relatively small proportion of the manually validated acoustic detections of blue whales. Blue whale song (specifically the Australian song of the EIO population) and the social signal EIO1 were considerably more abundant in the datasets. While the EIO1 signal often appeared alone without any other social signals, EIO6, 7, 8 and 9 typically occurred in what appeared to be bouts of social signalling. In these instances, even where a distinct phrase pattern was not discernible, there appeared to be some sequencing of signals with EIO1s following an EIO9s in 91.5% of observed occurrences (N = 281). Similarly, the EIO6 sample was followed by either an EIO7 or EIO8 in 92.6% (N = 122) of observed occurrences. The EIO7 and EIO8 signals did not appear to occur in any particular order but were also the most difficult to distinguish between owing to their similar properties. Sequences of social signals were observed in multiple data sets and first appeared in 2012 in the Western Timor Sea (Fig. 7 ). The structure and sequencing of the social signals appears to be relatively consistent between sample locations and over sample years (Fig. 9 ). The directrograms of these sequences shown in Fig. 9 provide further support that sequences are produced by an individual singing animal, with consistent bearings (denoted by colour) and received levels recorded throughout the sequence. 3.3 Interobserver Reliability Test The Fleiss Kappa test provided a measure of the level of agreement between all observers for the classification of the social sounds into the newly defined signals, EIO1 or D call groups. Classification by a group of 12 independent observers, including five trained and experienced observers and seven completely naïve observers yielded a kappa statistic of 0.73 (p-value = 0) indicating a good level of agreement between observers. When considering the classifications of only the five trained and experienced observers the test retuned a kappa statistic of 0.93 (p = 0) indicating near perfect agreement. A comparison of the reliability of the classification of D calls and EIO1 into distinct categories by all observers yielded a kappa statistic of 0.657 (p-value = 1.71e-09) indicating a good level of agreement. All kappa statistics were highly statistically significant. The results of the Fleiss Kappa analysis indicate that the newly defined social sounds represent logical and appropriate groupings and support the distinct classification of EIO1 signals from D calls. The signals with the highest level of disagreement in classification were EIO7 and EIO8. 4.0 DISCUSSION Population specific vocalisations are useful in the monitoring and management of cryptic species such as the EIOPB whale. Hunted to near extinction in the industrial whaling era and largely targeted by soviet whalers, the current status of the EIOPB stock remains largely unassessed. Passive acoustic monitoring (PAM) provides a cost-effective means for monitoring the species and the potential for long term abundance assessments. However, these methods require an adequate knowledge of the vocal repertoire of the species, particularly for PAM to be more effectively applied to census the whole population, as opposed to being biased towards singing males. Understanding the social sounds of the species presents the opportunity to more effectively quantify species presence using PAM without being subject to the inherent biases of sampling song, which are that songs are only produced by mature males, are mutually exclusive with some behaviours such as foraging and are seasonal with higher singing activity observed during the northbound migration to the calving grounds as opposed to the southbound migration. To date very few studies have focused on quantifying the social sounds of the blue whale. This may be because the identification and analysis of unknown acoustic signals is extremely time consuming, with most of the acoustic analysis reliant on the use of automated detection algorithms. These algorithms are trained based on existing knowledge of signals that can confidently be attributed to species and tend to focus on song elements as these are the most well-known, stereotyped and easily identifiable signals within acoustic data. In the context of the EIOPB whale, songs are comprised of long duration (> 18 s), high intensity, low frequency units that transmit over long distances and are typically easily distinguishable in acoustic data. Social signals by comparison are much shorter in duration (~ 2 to 10 s) and are presumed to have a lower source level as has been observed in other baleen whales 24 – 27 . These characteristics likely contribute to their poorer detectability in acoustic data with our observations indicating that with the exception of the downswept signals (D calls and EIO1), social sounds were difficult to identify and differentiate in acoustic data except in instances where there was a very good signal to noise ratio and low caller density. As discussed above, we also found that the FFT settings typically used for viewing spectrograms of blue whale song were not favourable for identifying social signals. 4.1 Definition of New Social Sounds Based on the data, four new social sounds can be defined for the EIOPB whale population. These social sounds are similar in acoustic characteristics to existing social sounds, with EIO7 and EIO8 also bearing a striking similarity to social sounds recorded by acoustic tags deployed on North Pacific blue whales 4 . Despite there not being paired visual observations, the sounds can confidently be attributed to blue whales due to their spectral characteristics including the frequency content of the signal (< 150 Hz), duration (2 to 5 s), the presence of tonal elements, and their frequency modulated structure. These social sounds were also all identified in the presence of other social sounds and song units known to be produced by the EIOPB whale. The social signals were recorded across multiple data sets from sample sites along the NW shelf, into the Kimberley region and in the Perth Canyon across sample years spanning from 2010 to 2025. This indicates that these social sounds are likely to have been present in many other acoustic data sets but just not identified or attributed to blue whales. The occurrence of the social sounds in these data sets and the relative consistency of these signals over time is consistent with what has been observed for other social sounds in this population. The newly defined social sounds are all frequency modulated tonal, low frequency sounds with energy focused between 20 and 75 Hz. The sounds are characteristically blue whale like in their appearance, and the similarity of the EIO1, EIO7 and EIO8 to social sounds produced by North Pacific blue whales, suggests that all blue whale populations may produce an array of social sounds and thus the vocal repertoire of blue whales globally may be considerably larger than previously thought. It is not clear why the EIOPB has a higher level of complexity in their vocal repertoire than any other mysticete species worldwide, however it is speculated this may be due to the overlap of several sub-populations of blue whales in the Indian Ocean leading to the evolution of a more complex vocal repertoire 6 . The relatively low number of observations of these signals in comparison to song is unsurprising noting that most acoustic detectors are trained to search data for song signals, and manual validation effort is generally directed at a small percentage of samples that correlate with song presence. As noted above, the characteristics of these social signals, including a presumed lower source level and shorter duration also make them more difficult to identify in course manual analysis of acoustic data sets. Fine scale manual analysis of data sets is time intensive and even so, when analysts come across signals that are not the target of their study or are unknown, they are often not annotated or noted in the data analysis. As a result, it is unsurprising that these signals have gone unnoticed for so long despite the EIOPB being one of the most studied sub populations of blue whales, and it is possible that detailed manual analysis of global data sets may identify similar signals for other blue whale populations worldwide. 4.2 Distinction of Downswept Signals The results of this study support the distinction between D calls and other downswept social sounds such as the EIO1 signal. Blue whales from all populations are known to produce low frequency downswept sounds that while somewhat variable in their acoustic characteristics, are consistently low frequency and short in duration (2 to 4 s) 3,28 . Historically, many studies have considered all downswept signals produced by blue whales to be D calls, though careful analysis of their spectral characteristics suggests that D calls should be separately classified to other downswept social signals with the primary determining feature for classification being the consistency of the signal characteristics and the presence of tonal units. The distinction of these two types of social signal is likely to be important when considering the behavioural context of signal production, particularly given that EIO1 signals have been recorded occurring in stereotypical, ordered sequences and appear to be relatively consistent in their spectral characteristics. Based on our fine scale analysis, and existing work, it is postulated that true D calls are highly variable, are not produced in rhythmic sequences, and lack any harmonics or additional tonals. Differentiating D calls from EIO1 signals is further complicated by propagation processes that may result in D calls appearing with ‘shadows’ that to the untrained eye may appear as a single harmonic. Similarly, long range propagation effects may result in EIO1 signals ‘losing’ their harmonics at longer ranges. Expert analysis is typically required to differentiate between these signal types. While calls resembling D calls are also produced by other mysticete whales including fin and sei whales, they can, in most cases, be confidently distinguished from blue whales with appropriate contextual consideration. For example, when detected in areas where blue whales have been sighted and blue whale songs are detected on the acoustic receiver but other mysticete species known to produce D calls have not historically been detected at that time. D calls produced by blue whales also tend to be lower in frequency, with the signal starting at between 60 and 100 Hz and sweeping down to around 20 to 40 Hz. 4.3 Behavioural Context of Social Sounds Given that the production of D calls appears to be rather distinct from that of other social sounds, with D calls being highly variable and not appearing in rhythmic ordered sequences, and other social sounds being relatively consistent and appearing in structured sequences, it is likely that the behavioural context of these two signal types is also distinct. The behavioural context of D calls has been studied for a number of populations of blue whales and appears to be consistent between populations. The signal is primarily detected on known foraging grounds where blue whales are aggregating to feed (Lewis et al. 2018). Acoustic tag data indicates that D calls are typically produced during shallow dives in breaks between foraging bouts. In general, D calls were recorded from whales that were loosely associated with other animals, though even those not obviously associated with another animal were within 1 km of other blue whales 4 . Based on the result of an acoustic tagging study, D calls were considered to have a clear behavioural context being produced by both male and female whales during breaks between foraging at depth 4 , 29 . Both Oleson et al. and Thode et al. found that blue whales produce multiple D calls per dive, typically at depths of between 15 and 35 m. It is hypothesised that at these depths, blue whales would be able to visually identify conspecifics and thus D calls likely have a social function as opposed to reproductive function. This is further supported by the fact D calls have been observed on foraging grounds as call-counter-call events within a group of two or more blue whales 3 , 29 . Geographically, recordings of D calls typically overlap known or likely foraging areas, for example the Perth Canyon in Western Australia 30 . Similarly, Barlow et al. 31,32 observed seasonal and daily trends in the production of D calls that aligned with seasonal and daily variability in blue whale foraging effort. Shabangu et al. 33 also found a correlation of D call presence and higher chlorophyll-a concentrations in the Benguelan current ecosystem, further supporting the association between foraging behaviours and D calls. D calls are also known to be produced during encounters of different group compositions, including mother-calf interactions (Lewis et al., 2018; Oleson et al., 2007). Social sounds appear to be produced by blue whales in a variety of contexts. Behaviours associated with singular song unit production were different to those associated with singing. Tagging studies have found that the production of singular calls was most common during shallow non lunging dives, and common during surface behaviour. Animals producing singular song units were always observed in close association with at least one other blue whale, and where tissue samples were available, were found to be produced by male and female pairs 4 . There has been one instance where an animal was recorded singing while travelling alone and was then observed to transition to producing singular song units once it had joined up with another blue whale. Another study observed downswept signals with harmonics, like the EIO1 signal identified in Recalde Salas et al. (2014), being produced during a heat run where two males were in pursuit of a female blue whale (Schall et al., 2020). These signals were associated with trios of animals in two populations of blue whales, as well as being recorded on foraging grounds (Schall et al., 2020). Schall et al. (2020) considered the context of D calls may be reproductive noting that D calls, along with EIO1 like signals and other unidentified grunts and blip sounds were produced during heart runs in two geographically distinct populations. While not likely to be a ‘reproductive’ display in the way that song is, these sounds could be used to mediate social interactions - including those of a reproductive nature. The occurrence of reproductive behaviours on foraging grounds is no surprise and has been speculated for blue whales given they are often solitary and are a low-density species. Feeding aggregations likely provide an opportunity for reproductive behaviours. Thus, the presence of D calls and social signals may be indicative not only of foraging but also of reproductive behaviours. Based on the results of acoustic tagging studies, social sounds are produced when blue whales are in close proximity with other conspecifics and do not appear to be produced at the same time as song. Consequently, it would be expected that social signals may be detected acoustically when blue whales are present but blue whale song may not be. This reflects the findings of Recalde Salas et al. (2014) who recorded many non-song social vocalisations but little to no song alongside visual observations of EIO pygmy blue whales on their southbound migration through Geographe Bay in Western Australia. 4.4 Complexity in Non-Song Communication Unlike D calls and EIO1 signals, the EIO6, EIO7, EIO8 and EIO9 social sounds were almost exclusively observed to occur in semi organised clusters with some level of rhythmicity. Some of the signals, such as EIO6 and EIO9 consistently occurred in sequence with other units, in particular EIO9 which occurred almost exclusively prior to an EIO1 signal, suggesting that social communication in blue whales may be governed by some form of simple syntax. The notion of syntax in marine mammal vocalisations is a topic of ongoing study, with research supporting the presence of syntactic rules in the vocal displays of vocal learning marine mammals 34 . Structural rules such as deterministic motifs, which drive stereotypy in sequences by limiting the sequence in which units appear, as well as a high level of unit redundancy and the disproportionately high usage of a few units, have been shown to influence the stability and stereotypy observed in animal song displays 34 , 35 . While the presence of syntactic features such as deterministic motifs and redundant unit usage have been confirmed in the songs of many songbirds, as well as both humpback and blue whale songs 34 – 42 , it is less clear whether these features apply in the non-song social communication of cetaceans. The observation of social signals arranged in what appeared to be two distinct phrase types that were repeated in a rhythmic fashion would meet the definition of song as it is typically applied for marine mammals. It is not clear whether this constitutes a new and alternative song for the EIOPB whale with the purpose of a reproductive display, or if the observed patterns are the result of complex non-song communication. Social signals form part of the signal repertoire for the species, and just as song units can be produced singularly and as part of song it is the organisation of units from a vocal repertoire into a structured sequence that defines song 43 . Consequently, the production of social sounds in structured sequences could suggest a novel use of pre-existing vocal units, which could indicate the cognitive capability of the individual and be a favourable display for sexual selection. However, if this were the case it would be expected that the song would be more prevalent in the datasets than it is. Noting that the social sounds have appeared in patterned sequences over many sample years with a high level of stability and low level of occurrence, it seems unlikely that they are part of a reproductive display and thus subject to sexual selection pressures. Rather, it seems much more likely that the observed rhythmicity and structure of these non-song vocalisation bouts is further evidence for syntax in the vocal behaviour of blue whales. 5.0 CONCLUSION This study presents evidence of four new non-song vocalisation types for the EIOPB whale, suggesting this population has a higher level of vocal complexity and possibly cognitive capacity than has been observed in other balaenopterid species. These signals are believed to be social sounds and have been recorded in across multiple sample years and sample locations indicating a high level of stability in the vocal repertoire of blue whales. This paper also presents the first evidence of blue whale social sounds being arranged in structured sequences and repeated in a rhythmic fashion, supporting the hypothesis that blue whale vocal communication is governed by a form of syntax, providing the first evidence of syntactic features in non-song vocalisations and contributing to our understanding of marine mammal vocal behaviour. Declarations The authors confirm they have no competing interests to declare. ACKNOWLEDGEMENTS Acoustic data used for analysis in this paper was sourced through a combination of JASCO acoustic monitoring programs and Integrated Marine Observing System (IMOS) moorings. Data for this work from JASCO monitoring programs was extracted from monitoring programs in the Perth Canyon (including with gliders in collaboration with Blue Ocean Marine Tech Services), and north-west Australia between 2011 and 2025. The monitoring programs in north-west Australia were conducted as part of baseline monitoring programs on behalf of PTTEP Australia, ConocoPhillips, Shell Australia Pty Ltd. Data from Integrated Marine Observing System (IMOS, 2008-2017). The IMOS observatory is supported by the Australian Government through the National Collaborative Research Infrastructure Strategy and is publicly available through the IMOS portal https://acoustic.aodn.org.au/acoustic/ or can be requested from https://portal.aodn.org.au/. Thank you to Scott French, Grace McPherson, Gabrielle Genty, James Tanner, Felix de Wattripont, Jess Cafagna, Dzenita Djamanovich and Callum Jolliffe who volunteered their time for the interobserver reliability test. Thank you to Julien Delarue for assistance in the review of the draft manuscript. A special acknowledgement to Ivy Beck, whose keen young eyes picked out some blue whale signals in a spectrogram that weren’t quite like the others while helping her mum work one Sunday morning. ETHICS The research presented and reported in this paper was conducted in compliance with the National Health and Medical Research Council Australian code for the care and use of animals for scientific purposes 8th edition (2013). The IMOS and CMST research study received animal ethics approval from the Curtin University Animal Ethics Committee, Approval Number # AEC_2013_28 - Passive acoustic recording of marine animal (mammal and fish) vocalisations. AUTHOR CONTRIBUTIONS C. Jolliffe: Conceptualisation, Data Collection, Figures, Manuscript Preparation, Data Analysis, Writing, Review. C. McPherson: Data Collection, Data Analysis, Figures, Manuscript Preparation, Writing, Review. R. 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J Ornithol 157:13–22. https://doi.org:10.1007/s10336-015-1238-x Jolliffe CD, McCauley RD, Gavrilov AN (2023) Variability in Temporal Characteristics of the South Eastern Indian Ocean Pygmy Blue Whale Song. Anim Cogn 10:211–231. https://doi.org:10.26451/abc.10.03.02.2023 Clarke E, Reichard UH, Zuberbühler K (2006) The Syntax and Meaning of Wild Gibbon Songs. PLoS ONE 1:e73. https://doi.org:10.1371/journal.pone.0000073 Garland EC, McGregor PK (2020) Cultural Transmission, Evolution, and Revolution in Vocal Displays: Insights From Bird and Whale Song. Front Psychol 11:2387. https://doi.org:10.3389/fpsyg.2020.544929 Additional Declarations There is NO Competing Interest. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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07:09:26","extension":"html","order_by":102,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":171591,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7938626/v1/38e5555fa431d53e705789f7.html"},{"id":94732573,"identity":"21cbae11-8c08-4bf3-b402-8b39a4d73e45","added_by":"auto","created_at":"2025-10-30 07:09:18","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":243507,"visible":true,"origin":"","legend":"\u003cp\u003eLocation of acoustic recording stations in relation to Western Australian coastline as well as designated biologically important areas (BIAs) for blue whales.\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-7938626/v1/1c0e66119d584d94bbc9be15.png"},{"id":94732534,"identity":"d187de2b-57ba-4cd3-aaa2-c0bde2fd0224","added_by":"auto","created_at":"2025-10-30 07:09:17","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1202475,"visible":true,"origin":"","legend":"\u003cp\u003eBlue whale song sequence that transitions into a sequence of social signals from what is presumed to be an individual animal based on the bearing to signal source (yellow signals). Omura whale signals are also present in the directrogam coming from a different direction (aqua blue signals), (0.4\u0026nbsp;Hz discrete Fourier Transform (DFT) frequency step, 2\u0026nbsp;s DFT temporal observation window (TOW), 0.5\u0026nbsp;s DFT time advance, and Hann window resulting in a 75 % overlap and DFT size (N\u003csub\u003eDFT\u003c/sub\u003e) of 131072).\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-7938626/v1/d47661a358f41fa6423c0f42.png"},{"id":94732701,"identity":"a505e0c3-0c28-4e5d-9a61-bafa55b9e392","added_by":"auto","created_at":"2025-10-30 07:09:23","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":54946,"visible":true,"origin":"","legend":"\u003cp\u003eDecision tree for the classification of new and commonly identified social signals for the EIOPB whale.\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-7938626/v1/8c50419a0bcd3ce7eb5deb5c.png"},{"id":94732619,"identity":"20c9e0b4-0a72-4676-917d-509ee3b7eaeb","added_by":"auto","created_at":"2025-10-30 07:09:20","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":950739,"visible":true,"origin":"","legend":"\u003cp\u003eSocial sounds of the Eastern Indian Ocean Pygmy Blue Whale (EIOPB) including previously defined EIO1 (top left) and D call (top right), and newly identified signals EIO6 (centre left), EIO7 (centre right), EIO8 (bottom left), EIO9 (bottom right).\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-7938626/v1/8f14da8cf6c24128b503fb35.png"},{"id":94732631,"identity":"66321e41-adf5-47a2-a5bd-26e5c3917168","added_by":"auto","created_at":"2025-10-30 07:09:21","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1367284,"visible":true,"origin":"","legend":"\u003cp\u003ePygmy blue whale non-song calls: (Top) waveform and spectrogram showing an EIO pygmy blue whale non-song vocal sequence with (bottom) a zoom in on four calls, from early November 2024\u003c/p\u003e\n\u003cp\u003e(top: 1 Hz discrete Fourier Transform (DFT) frequency step, 1 s DFT temporal observation window (TOW), 0.125 s DFT time advance, and Hann window; bottom: 1 Hz DFT frequency step, 0.2 s DFT TOW, 0.02 s DFT time advance, and Hann window). The spectrograms are 360 s and 60 s long, respectively. The colour scheme represents the direction of arrival of sound, as per the wheel on the top right corner.\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-7938626/v1/059fff47d4fb1469b5f438d3.png"},{"id":94732751,"identity":"e7379078-5482-4d95-87c9-01e7119106c4","added_by":"auto","created_at":"2025-10-30 07:09:24","extension":"jpeg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":659922,"visible":true,"origin":"","legend":"\u003cp\u003eSpectrograms of social sounds recorded from the NW Shelf \u0026nbsp;(0.4\u0026nbsp;Hz discrete Fourier Transform (DFT) frequency step, 2\u0026nbsp;s DFT temporal observation window (TOW), 0.5\u0026nbsp;s DFT time advance, and Hann window resulting in a 75 % overlap and DFT size (N\u003csub\u003eDFT\u003c/sub\u003e) of 131072)\u003c/p\u003e","description":"","filename":"image6.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7938626/v1/330a33ffe0071c4584c3dfe5.jpeg"},{"id":94732548,"identity":"45e1c490-e3d2-44fa-8cf3-a7a73f2fcf41","added_by":"auto","created_at":"2025-10-30 07:09:17","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":371145,"visible":true,"origin":"","legend":"\u003cp\u003eSpectrogram of the possible new EIOPB song variation showing with the blue box showing phrase 1, and the yellow box showing phrase 2. The purple box surrounds one entire song sequence comprised of phrase 1, and phrase 2 (0.4\u0026nbsp;Hz discrete Fourier Transform (DFT) frequency step, 2\u0026nbsp;s DFT temporal observation window (TOW), 0.5\u0026nbsp;s DFT time advance, and Hann window resulting in a 75 % overlap and DFT size (N\u003csub\u003eDFT\u003c/sub\u003e) of 131072).\u003c/p\u003e","description":"","filename":"image9.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7938626/v1/fba6e65bf38ae00660cdd623.jpg"},{"id":94732760,"identity":"f5aff47d-2afc-4972-8424-0856fdc58e53","added_by":"auto","created_at":"2025-10-30 07:09:25","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":293366,"visible":true,"origin":"","legend":"\u003cp\u003eExample of pygmy blue whale calls at Western Timor Sea site from 2012, NFFT 32768, 0.75s window, 0.1s advance, times in UTC.\u003c/p\u003e","description":"","filename":"image10.png","url":"https://assets-eu.researchsquare.com/files/rs-7938626/v1/cefcf7d3be8df3536c28fcbe.png"},{"id":94823736,"identity":"24e03e0f-bb32-45c3-b743-78ad20a6e8f2","added_by":"auto","created_at":"2025-10-31 06:47:55","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":637816,"visible":true,"origin":"","legend":"\u003cp\u003eExample of repeatability across years - directograms of call units at two locations over two years: Perth canyon April 2025 (top) and western Timor Sea May 2024 (bottom) (0.4\u0026nbsp;Hz discrete Fourier Transform (DFT) frequency step, 2\u0026nbsp;s DFT temporal observation window (TOW), 0.5\u0026nbsp;s DFT time advance, and Hann window resulting in a 75 % overlap and DFT size (N\u003csub\u003eDFT\u003c/sub\u003e) of 131072). The spectrogram is 120s long.\u003c/p\u003e","description":"","filename":"image11.png","url":"https://assets-eu.researchsquare.com/files/rs-7938626/v1/301f04ec8b720729cdc23532.png"},{"id":95797524,"identity":"ad579f29-685e-4cd0-99fd-1a1edf4f34be","added_by":"auto","created_at":"2025-11-13 08:06:14","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":6391421,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7938626/v1/8ae62952-a766-4fde-851b-228ec360bf60.pdf"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Singing to the sound of their own tune: Uncovering an increasingly complex vocal repertoire for the east Indian Ocean pygmy blue whale","fulltext":[{"header":"1.0 INTRODUCTION","content":"\u003cp\u003eMany cetaceans, including blue whales, have a large repertoire of sounds, many of which are region or population specific. The acoustic distinction of populations may be of critical importance for reproduction and migration, as well as allowing geographically distinct populations to communicate at the optimum frequency for their specific environment \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. Blue whale (\u003cem\u003eBalaenoptera musculus spp\u003c/em\u003e) calls are characteristically low frequency (\u0026lt;\u0026thinsp;100 Hz), long duration (tens of seconds) and intense sounds (\u0026gt;\u0026thinsp;175 dB re 1 \u0026micro;Pa SPL source level;\u003csup\u003e2\u003c/sup\u003e). These acoustic properties of blue whale calls mean that signals propagate over vast distances. Blue whales arrange some of these calls, which can be called units, into stereotypical sequences that are called phrases, and repeated in a consistent pattern that meets the definition of song (Jolliffe et al., 2019; McDonald et al., 2006). Blue whale song phrases are typically comprised of two to three song units \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e, with some level of variability in the production of these units and phrases between the songs of individual whales (Jolliffe et al., 2023, 2024; Jolliffe et al., 2019). While the individual units that comprise songs have been observed being produced by both male and female animals, only males have been observed to arrange their units into phrases and produce them in repetitive song sequences \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. Songs are thus assumed to be a reproductive display, produced by males to attract females and mediate interactions with other males, consistent with the use of song in other baleen whales and singing animals \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eBlue whale vocalisations are typically population specific with subpopulations defined by geographic range and song structure. Based on calling behaviour, blue whales found in the Southern Hemisphere have been separated into six acoustically distinct populations, one of Antarctic blue whales, and four vocally distinct pygmy blue whale populations separated by song types into Sri Lankan, Madagascan, \u0026ldquo;Australian\u0026rdquo; (referred to here as EIOPB), Chilean, New Zealand and most recently the Chagos population \u003csup\u003e\u003cspan additionalcitationids=\"CR8 CR9\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. As such the correct classification of song types is important for successful acoustic monitoring of populations. To date, the body of research into blue whales has been dominated by passive acoustic based research programs and focused largely on using song to identify populations, and their spatial and temporal distributions (McDonald et al., 2006). While this approach has been incredibly valuable, studies focused solely on song may only be representative of a portion of the population, being sexually mature males.\u003c/p\u003e\u003cp\u003eNon-song vocal behaviour in blue whales is less well understood, however both male and female blue whales are known to produce song units singularly outside of repetitive song structures, as well as a variety of frequency and amplitude modulated social sounds, including short low frequency downswept tones with harmonics \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Reports of social sounds in blue whales have typically been sparse and are mostly limited to observations of singular song units and downswept calls (\u0026lsquo;D calls\u0026rsquo;) \u003csup\u003e12\u0026ndash;15\u003c/sup\u003e. However, a review of the literature reveals inconsistent classification of social sounds (typically AM/FM with harmonics or overtones) and true \u0026lsquo;D calls\u0026rsquo;, which do not have harmonics or overtones (Schall et al., 2020).\u003c/p\u003e\u003cp\u003eThe song of the Eastern Indian Ocean Pygmy blue whale (\u003cem\u003eBalaenoptera musculus brevicauda\u003c/em\u003e) is known to have several structural variants, though is comprised of between one and three stereotypical song units, termed type I, type II and type III units \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e repeated in either a consistent or alternating pattern \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. These song units are all characteristically low frequency (\u0026lt;\u0026thinsp;100 Hz), long duration (\u0026gt;\u0026thinsp;18 sec) sounds with fundamental frequencies in the 20 to 28 Hz range and harmonics. The EIOPB whale is also known to produce a handful of social sounds that are distinct from song units and the downswept \u0026lsquo;D\u0026rsquo; calls that are common to all populations of blue whales \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Social sounds for this population have previously been characterised from paired visual and acoustic studies in Geographe Bay, Western Australia. These sounds are typically short duration (\u0026lt;\u0026thinsp;10 s), frequency modulated, tonal sounds between 25 and 100 Hz. These previously identified social sounds are defined in Recalde-Salas et al. (2014) and have been named EIO1, EIO2, EIO3, EIO4 and EIO5 \u003csup\u003e11\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eStudying the interspecific communication of populations can provide valuable clues as to the evolution of vocal systems and mechanisms for vocal learning within a population \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. While song in marine mammals is commonly accepted to be a reproductive display, the purpose and behavioural context of social sounds is less understood. The first step to understanding the vocal behaviour of blue whale populations is a more holistic understanding of their vocal repertoire. Focused studies on vocal behaviour outside of song displays also has the benefit of providing information on species presence and distribution that is not biased towards mature males. Investigating vocal repertoires may also provide further information on the social complexity of marine mammals\u0026rsquo; lives as well as an indication of cognitive capacity.\u003c/p\u003e\u003cp\u003eThis study presents evidence that the vocal repertoire of the EIOPB whale population is more complex than previously thought and defines four new social sounds for the population that are similar in characteristics to previously documented social sounds for this population and song units for blue whales globally. This study also presents evidence of these signals occurring in ordered sequences akin to phrases and repeated, meeting the definition typically applied to whale song. Such an observation presents questions regarding the purpose of social signals and suggests a higher level of vocal and cognitive complexity in the EIOPB population than has been documented for any other rorqual whale population worldwide.\u003c/p\u003e"},{"header":"2.0 METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Study Location\u003c/h2\u003e\u003cp\u003eData were collected across four years from eight sample sites on the North West Shelf (NW Shelf) off Western Australia and the Perth Canyon, west of Rottnest Island, Western Australia (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The NW Shelf and Perth Canyon data collection sites fall within the migratory corridor for the EIOPB whale, with some NW Shelf sites and the Perth Canyon sites also sitting within defined foraging areas (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Recorders were deployed at depths of between 90 and 250 m, with deployment periods of between 77 and 310 days (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDataset locations and deployment dates\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"10\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDataset ID\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYear\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eLocation Name\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eLatitude (S)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eLongitude (E)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eStart Date\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eEnd Date\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003eRecorder Type\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u003cp\u003eData Source\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e2010\u0026ndash;2012\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eWestern Timor Sea\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e11\u0026deg; 36.026'\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e125\u0026deg; 9.266'\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e02 Dec 2010\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e9 Jun 2011\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c9\" namest=\"c8\" rowspan=\"2\"\u003e\u003cp\u003eAURAL M2 (single channel)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eJASCO/PTTEP\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e09 Jun 2011\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e13 Dec 2012\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2012\u0026ndash;2014\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSeringapatam Reef - West\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e13\u0026deg; 38.075'\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e121\u0026deg; 51.922'\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e9 Oct 2012\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e23 Feb 2014\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c9\" namest=\"c8\" rowspan=\"2\"\u003e\u003cp\u003eAMAR G3 (single channel)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eJASCO/ConocoPhillips\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2012\u0026ndash;2014\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSeringapatam Reef \u0026ndash; East\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e13\u0026deg; 28.558'\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e122\u0026deg; 17.911'\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e9 Oct 2012\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e22 Feb 2014\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eJASCO/ConocoPhillips\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2013\u0026ndash;2014\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eIMOS Kimberley\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e15\u0026deg; 38.730'\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e121\u0026deg; 25.254'\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e01/10/2013\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2 Jun 2014\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" morerows=\"2\" nameend=\"c9\" namest=\"c8\" rowspan=\"3\"\u003e\u003cp\u003eCMST\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eIMOS\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2014\u0026ndash;2015\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eIMOS Kimberley\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e19/08/2014\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e8 May 2015\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eIMOS\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2012-13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eIMOS Pilbara\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e19\u0026deg; 25.488'\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e115\u0026deg; 53.028'\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e20-Nov-12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e16 Oct 2013\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eIMOS\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2023\u0026ndash;2025\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eWestern Timor Sea\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e12\u0026deg; 57.981'\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e124\u0026deg; 4.430'\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e25 Sep 2023\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e15 Mar 2025\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c9\" namest=\"c8\" rowspan=\"2\"\u003e\u003cp\u003eALTO Mooring - AMAR UD (Directional)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eJASCO/Shell\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2023\u0026ndash;2025\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eWestern Timor Sea\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e12\u0026deg; 58.057'\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e123\u0026deg; 42.304'\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e25 Sep 2023\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e15 Mar 2025\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eNovember 2024\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003ePerth Canyon \u0026ndash; Glider Area\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e31\u0026deg; 46.219'\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e114\u0026deg; 42.915'\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e1 Nov 2024\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c8\" namest=\"c7\" rowspan=\"2\"\u003e\u003cp\u003e15 Nov 2024\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eOceanObserver\u0026trade; (Directional) and AMAR (Directional) installed on Slocum glider\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eJASCO\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e31\u0026deg; 46.219'\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e115\u0026deg; 18.836'\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eApril-May 2025\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e32\u0026deg; 10.045'\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e115\u0026deg; 18.836'\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e26 April 2025\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c8\" namest=\"c7\" rowspan=\"2\"\u003e\u003cp\u003e8 May 2025\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e32\u0026deg; 10.045'\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e114\u0026deg; 42.915'\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Data Collection Methods\u003c/h2\u003e\u003cp\u003e\u003cem\u003eCMST Deployments\u003c/em\u003e\u003c/p\u003e\u003cp\u003eFor the IMOS moorings, data were collected using Curtin University CMST-DSTO autonomous underwater sound recorders, described in McCauley et al. (2017). White noise of a known Power Spectral Density (PSD) level was used to calibrate the recording system response pre and post deployment with the hydrophone in sequence. Calibrated data was available from 1 Hz to the Nyquist frequency. Recorders sampled at a 6 kHz sample rate, with recordings of 5 to 7 minutes every 9 minute. A 2.8 kHz anti-liaising filter with a gentle high-pass filter and roll off below 8 Hz was used to flatten the low frequency noise curve.\u003c/p\u003e\u003cp\u003e\u003cem\u003eAutonomous Underwater Recorders for Acoustic Listening-Model 2 (AURAL-M2)\u003c/em\u003e\u003c/p\u003e\u003cp\u003eAURAL-M2s (Multi-Electronique Ltd.) with a single omnidirectional hydrophone were employed for the PTTEP study in 2011. Data were recorded on dual 320GB hard drives at 16-bit resolution with 32 768 samples per second. The AURALs were fitted with HTI-96 hydrophones, which have a nominal sensitivity of 164 dBV re 1 \u0026micro;Pa and gain set of 22 dB. The spectral density noise floor of the AURALs in this configuration is approximately 57 dB re 1 \u0026micro;Pa, and the usable bandwidth is 10\u0026ndash;16 000Hz. The AURALS were calibrated with a pistonphone type 42AC precision sound source (G.R.A.S. Sound \u0026amp; Vibration A/S) using a constant 250 Hz. The duty cycle for the first deployment was 49%, and for the second 46%, recording once every hour.\u003c/p\u003e\u003cp\u003e\u003cem\u003eAutonomous Multichannel Acoustic Recorders Generation 3\u003c/em\u003e\u003c/p\u003e\u003cp\u003eFor the Seringapatam deployments in 2012\u0026ndash;2014, AMAR G3 (JASCO) were used. Each recorder was fitted with an M8E calibrated omnidirectional hydrophone (GeoSpectrum Technologies Inc., \u0026minus;\u0026thinsp;165\u0026thinsp;\u0026plusmn;\u0026thinsp;5 dB re 1 V/\u0026micro;Pa nominal sensitivity) and set for a gain of 0 dB. Data were recorded on the 24-bit channel sampling at 64 kHz and stored onto 1.8 TB of internal solid-state memory. The recorders have an equivalent spectral noise floor of 23 dB re 1 \u0026micro;Pa\u003csup\u003e2\u003c/sup\u003e/Hz at 64 kHz. The three deployments used different sampling configuration: for the first deployment the recorders sampled at a 50% duty cycle, 1800 s (30 min) per hour, then for the second the recorders sampled at a 33% duty cycle, 1190 s (19.83 min) per hour, and for the third the recorders sampled at a 75% duty cycle, 2700 s (45 min) per hour.\u003c/p\u003e\u003cp\u003e\u003cem\u003eAutonomous Long Term Observatory Deployments\u003c/em\u003e\u003c/p\u003e\u003cp\u003eUnderwater sound was recorded with AMAR Generation 4 (G4) Ultra Deep (JASCO) in glass sphere housings. Each AMAR was installed on an Autonomous Long-Term Observatory (ALTO, JASCO) lander. The ALTO is equipped with an orthogonal array of four M36 omnidirectional hydrophones (GeoSpectrum Technologies Inc., \u0026minus;\u0026thinsp;165\u0026thinsp;\u0026plusmn;\u0026thinsp;3 dB re 1 V/\u0026micro;Pa sensitivity) spaced between approximately 0.5 m and 2 m apart. By using beamforming analysis methods, the direction of arrival of sounds can be determined from the four hydrophones \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. The hydrophones were protected by a hydrophone cage, which was covered with an open-cell foam shroud to minimise non-acoustic noise caused by water flowing over the hydrophone transducer (\u0026lsquo;flow noise\u0026rsquo;). The AMARs recorded continuously with a duty cycle of 15 mins at a sampling rate of 32 kHz followed by 1 min at 256 kHz. The recording channel had 24‑bit resolution with a spectral noise floor of 20 dB re 1 \u0026micro;Pa2/Hz and a nominal ceiling of 171 dB re 1 \u0026micro;Pa. Acoustic data were stored on 7.68 TB of internal solid-state flash memory.\u003c/p\u003e\u003cp\u003e\u003cem\u003eOceanObserver\u0026trade; and AMAR G4\u003c/em\u003e\u003c/p\u003e\u003cp\u003eFor the Perth Canyon glider deployments in 2024 and 2025, Teledyne Slocum G3 gliders mounted OceanObserver\u0026trade; and AMAR G4 systems were equipped with an array of four M36 omnidirectional hydrophones, with beamforming analysis methods as described above applied. The recorders operated continuously at a sampling rate of 8 kHz. The recording channel had 24‑bit resolution with a spectral noise floor of 20 dB re 1 \u0026micro;Pa2/Hz and a nominal ceiling of 171 dB re 1 \u0026micro;Pa. Acoustic data were stored on 7.68 TB of internal solid-state flash memory.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Data Analysis\u003c/h2\u003e\u003cp\u003e\u003cem\u003eCMST Deployments\u003c/em\u003e\u003c/p\u003e\u003cp\u003eSpectrograms of sea noise were viewed using Raven software (\u003csup\u003e17\u003c/sup\u003e). Spectrograms were produced with a 1024 point FFT and a Hanning window with no overlap. All spectrograms were analysed manually for occurrences of blue whale song, D calls and social sounds. For the purpose of this study, D calls were classified as downswept signals from between 75 and 20 Hz of between 2 and 4 seconds with no harmonics or tonal elements. Social sounds were classified as short duration (2 to 10 s), low frequency sounds (10 to 150 Hz) that could be down sweeping tones, amplitude modulated, or frequency modulated with harmonics or tonal overtones. Within each sample, where present, one example of song was selected and one D call, while all examples of social sounds were selected for further analysis.\u003c/p\u003e\u003cp\u003e\u003cem\u003eJASCO Deployments\u003c/em\u003e\u003c/p\u003e\u003cp\u003eA combination of automated detector-classifiers (referred to as automated detectors) and manual review by experienced analysts was used to determine the presence of sounds produced by marine mammals in the acoustic data. First, a suite of automated detectors was applied to the full data set. The automated tonal signal detector identified continuous contours of elevated energy and classified them against a library of marine mammal signals. JASCO\u0026rsquo;s suite of tonal automated detectors includes species/signal-specific detectors and those that are more generic, capturing signals from potentially more than one species that overlap in spectral characteristics. JASCO\u0026rsquo;s suite of automated detectors are developed, trained, and tested to be as reliable and broadly applicable as possible. However, the performance of marine mammal automated detectors varies across acoustic environments \u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e,\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003c/sup\u003ee.g. \u003csup\u003e20,21\u003c/sup\u003e. Therefore, automated detector results must always be supplemented by some level of manual review to evaluate automated detector performance. Here, a subset of acoustic files was manually analysed for the presence/absence of marine mammal acoustic signals via spectrogram review in JASCO\u0026rsquo;s PAMlab software. A subset of acoustic data representing 1% to 5% of low frequency sound files (depending upon deployment), was selected based on automated detector results via JASCO\u0026rsquo;s Automatic Data Selection for Validation (ADSV) algorithm \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. Throughout the manual review, signals that were suspected to be social sounds produced by blue whales were selected for further analysis. Additional files were also opportunistically reviewed based upon manual review findings.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Signal Feature Analysis\u003c/h2\u003e\u003cp\u003eWhere social sounds and other sounds suspected to be produced by blue whales were detected and repeated in sequence, the entire sequence was selected for detailed analysis. Social sounds, and other blue whale-like sounds were assumed to be produced by blue whales if they fit the characteristic description of existing defined signals or were similar in frequency range and appearance to other known blue whale signals, and occurred in the same hour as other known blue whale songs when there were no other species of whale acoustically present. This approach was supported through the identification of song sequences in which singing blue whale(s) transitioned from known song sequences to structured groups of new signals (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe Discrete Fourier Transform (DFT) settings used for analysis are key to signal identification. The typical DFT for blue whale song (Setting 1, Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) enable a file to be opened quickly and work very well for song, and provide a suitable resolution for tonal social signals longer then 4\u0026ndash;6 s. These settings do not however, provide good resolution for shorter social signals and downswept calls. For these calls, Setting 2 (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) is recommended for making call identification. Setting 3 can be used to create very clean, high-fidelity spectrograms of calls such as EIO1, however results in blurred details for calls such as EIO6 and EIO9 and is computationally inefficient. These settings were tested on all datasets analysed and found to have similar performance trends.\u003c/p\u003e\u003cp\u003eExamples of social signal sequences were difficult to find with a good signal to noise ratio and no propagation effects. However sufficient examples of all call types were found for inclusion in this analysis, with a greater number of the more common social signal types (EIO1 and EIO9) being able to be observed clearly. Typically, individual signals, and sequences of signals, were observed with a signal to noise ratio that did not support detailed analysis. The signals often appeared to have low structural spectral resolution despite optimising the DFT settings, making spectrograms appear \u0026lsquo;blurry\u0026rsquo;. This is potentially due to closely grouped tonal elements, including overtones and harmonics, and the amplitude and frequency-modulated nature of the calls, making them prone to transmission effects. The source levels of these signals are currently unknown but is a subject of ongoing analysis requiring paired acoustic and visual observations. While blue whale social sounds were often detected, identification of the discrete signals and categorisation for the less common signal types was often challenging. Consequently, a small subset of social signals was selected for signal feature analysis. Signal features, including maximum and minimum frequency and signal duration, were extracted from selected signals using PAMlab (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.jasco.com/pamlab\u003c/span\u003e\u003cspan address=\"https://www.jasco.com/pamlab\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDiscrete Fourier Transforms\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSetting Name\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDFT Frequency Step (Hz)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDFT Temporal Observation Window (s)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eDFT Time Advance (s)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eWindow\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSetting 1 \u0026ndash; Long Calls\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eHann\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSetting 2 \u0026ndash; Social and Song\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.125\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSetting 3 \u0026ndash; High fidelity downsweeps\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.002\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.4 Signal Classification\u003c/h2\u003e\u003cp\u003eSignals were classified by comparing the spectral appearance and waveform envelope of target signals with existing known blue whale song units, and existing defined social sounds for all populations known to occur within Australian waters including the Antarctic, EIOPB, Chagos and New Zealand pygmy blue whale. Downswept signals were classified based on the absence or presence of multiple overtones as being either D calls or the previously defined EIO1 signal, respectively. While D calls did not have consistent harmonic overtones, they did occasionally have a single higher frequency downswept component when observed in low SNR conditions. This was not consistently observed however, and D calls were by their nature \u0026lsquo;consistently inconsistent\u0026rsquo; in that even signals that appeared to originate from the same animal were not consistent in their spectral characteristics. This led to what analysts called a \u0026lsquo;shooting star\u0026rsquo; effect where D calls would often appear in the spectrogram as random vertical lines in a manner that resembled the tails of shooting stars. The EIO1 signal by comparison was relatively consistent and always appeared as a more teardrop shaped down sweep with at least two and often more overtones. For the purpose, of this study a harmonic was defined as a higher frequency component that was an exact integer of the fundamental frequency.\u003c/p\u003e\u003cp\u003eShort duration frequency modulated sounds were compared with the existing social sounds defined in Recalde-Salas et al. (2014). Sounds that did not match any predefined social sounds but were confidently attributed to blue whales were grouped with similar signals using a decision tree. A sound considered to be confidently attributable to a blue whale if it was a low frequency (\u0026lt;\u0026thinsp;100 Hz) frequency/amplitude modulated sound with harmonic or tonal elements that did not extend above 200 Hz and was detected in the presence of known blue whale signals. Signals were confidently assigned to blue whales if no other acoustically identifiable species of baleen whale was present in the sample or samples preceding and following the target sample. The exception was with directional recordings where Omura\u0026rsquo;s whale vocalisations were present but originated from a different direction to the social signals. While Omura\u0026rsquo;s whales are suspected to produce downswept signals like all other baleen whales, they are not known to produce the \u0026lsquo;blue whale like\u0026rsquo; tonal FM and AM signals observed here and classified as social signals. These signals were then grouped based on their spectral appearance and characterised as new social signals and named as follows \u0026ndash; EIO6, EIO7, EIO8, EIO9.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eWhere social signals appeared in sequences, the composition and temporal patterns of these sequences were characterised through manual viewing of spectrograms in PAMLAB and feature analysis.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e2.4 Testing Signal Groupings\u003c/h2\u003e\u003cp\u003eTo test the appropriateness of the signal classifications, an interobserver reliability test was undertaken. A group of 12 independent observers were provided with a subset of 12 social sounds and asked to classify the social sounds based on comparison of the spectrograms with a catalogue of the newly identified signals, EIO1 and D calls. The group of observers include five trained and experienced analysts, and seven na\u0026iuml;ve analysts who had never undertaken any form of acoustic analysis before. Observers ranged in age from six to forty years old. A Fleiss Kappa test was conducted in R Studio on the classifications to test how similarly observers classified the signals. The Kappa statistic provides a statistical measure of the level of agreement between a group of raters, in this context providing an indication of whether the definitions of the newly defined social signals, and distinction between EIO1 and D calls is logical and justified. The Kappa statistic ranges from less than 0 to 1, with 1 indicating perfect agreement among observers. A Kappa of greater than 0.8 indicates near perfect agreement, while a Kappa of greater than 0.6 indicates good agreement, 0.4 to 0.6 indicates moderate agreement, 0.2 to 0.4 indicates fair agreement, 0 to 0.2 indicates slight agreement, and less than 0 indicates no agreement.\u003c/p\u003e\u003cp\u003eSeparate Fleiss Kappa tests were also run to test agreement between experienced observers only, as well as the classification of only D calls and EIO1 calls by all observers.\u003c/p\u003e\u003c/div\u003e"},{"header":"3.0 RESULTS","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Blue whale social sounds\u003c/h2\u003e\u003cp\u003eA total of 61,391.87 h of acoustic data was manually analysed for blue whale signals as part of this study. Four of the five known social sounds for the EIOPB whale were detected in the datasets, as well as D calls and EIOPB whale song. Similarly to Miller, et al. \u003csup\u003e14\u003c/sup\u003e, D calls were classified as a distinct signal type from other downswept sounds and were characterised by a down sweeping signal between approximately 90 and 25 Hz of approximately 2 to 4 seconds in length, that were highly variable in their appearance and did not appear in any kind of orderly sequence. D calls did not have what would typically be referred to as harmonics or overtones, but rather when recorded at a high signal to noise ratio (SNR), occasionally had a higher frequency tonal component. These signals were also highly variable even when produced by what appeared to be the same animal based on the direction of origin and received level of the signal. By comparison, social sounds were frequency and/or amplitude modulated signals with over tones that were relatively consistent in their spectral characteristics and were typically produced at consistent intervals or in sequence with other social signals.\u003c/p\u003e\u003cp\u003eAn additional four signals, that were similar in structure and acoustic characteristics to known EIOPB social sounds were also detected and are described in further detail below. Consistent with the existing nomenclature for EIOPB social sounds, the signals were named EIO6, EIO7, EIO8 and EIO9. Spectrograms, produced with a 1024-point FFT and a Hanning window with no overlap, when compared with known EIOPB social sounds show similarities in the acoustic characteristics of the signals (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e)\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThese signals were produced in samples with known EIOPB social sounds and at times of year when EIOPB song events were also present. There were no other known whale vocalisations detected within the samples (aside from Omura\u0026rsquo;s in some samples), and the signals originated in the same direction as known blue whale signals detected at a similar time. Figure\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e shows an example of an EIOPB song sequence that shifts from song into sequences of social sounds. These were recorded on a directional AMAR and there is no change in bearing and a relatively consistent received level indicating these signals originated from the same animals. The signals are also similar in their spectral characteristics to known blue whale social and song signals \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e, consequently these signals can be confidently attributed to blue whales.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003e(top: 1 Hz discrete Fourier Transform (DFT) frequency step, 1 s DFT temporal observation window (TOW), 0.125 s DFT time advance, and Hann window; bottom: 1 Hz DFT frequency step, 0.2 s DFT TOW, 0.02 s DFT time advance, and Hann window). The spectrograms are 360 s and 60 s long, respectively. The colour scheme represents the direction of arrival of sound, as per the wheel on the top right corner.\u003c/em\u003e\u003c/p\u003e\u003cp\u003eA subset of the signals were analysed for time and frequency statistics. These were drawn from datasets 8,9,11 and 12. All social signals were short duration frequency modulated sounds of between 2 and 16 sec in length and 10 and 204 Hz in frequency (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Deterministic chaos, defined as broadband, non-random noise like segments \u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e was present in the signals named EIO6 and EIO9.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSummary of call parameters\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eSignal\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eNumber of samples\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003eTime statistics (s)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e\u003cp\u003eFrequency statistics (Hz)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMean length (s)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSTD length (s)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eMean\u003c/p\u003e\u003cp\u003eCentroid (Hz)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eMean\u003c/p\u003e\u003cp\u003eLow (Hz)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eMean\u003c/p\u003e\u003cp\u003eHigh (Hz)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEIO1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e91\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.84\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e49.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e29.63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e200\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEIO6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11.84\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e54.32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e26.93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e102.13\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEIO7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e44.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e15.83\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e111.72\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEIO8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e52.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e21.48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e115.75\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEIO9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e63.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e67.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e98.42\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eBased on our analysis, D calls were typically short duration signals ranging in duration from 2 to 4 seconds and downsweeping from a maximum of 50 to 100 Hz, down to a minimum of 20 to 40 Hz. They did not have typical harmonics though a higher frequency tonal element was at times visible in some spectrograms with very high signal to noise ratio. They were also found to be prone to interference and transmission effects that occasionally resulted in a \u0026lsquo;mirrored\u0026rsquo; signal.\u003c/p\u003e\u003cp\u003eThe previously defined EIO1 signal was found to be a consistently short duration signal of 3 to 6 seconds that had a characteristic tear drop shape and was downswept in frequency from a maximum of 70 to 200 Hz, to a minimum of around 30 Hz. Harmonics were always present with this signal type and typically three harmonics were clearly visible in the spectrograms.\u003c/p\u003e\u003cp\u003eNewly defined social signals were more difficult to separate into clear groupings and were all slightly longer than the downswept D and EIO1 signals. The EIO6, 7 and 8 signals were all amplitude and frequency modulated signals that bore some similarities to the unit III of the EIOPB song type. These signals were typically between 5 and 16 seconds in length with fundamental frequencies around 25, 15 and 20 H respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The upper most visible harmonic for these signals was typically around 100 to 110 Hz (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Deterministic chaos was present at the start of the EIO6 signal. No deterministic chaos was present in EIO7 and EIO8 signals which were the most similar of the social signals described. EIO7 signals were consistently lower in frequency with the peak energy at 20 to 50 Hz and clearly defined harmonics (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). EIO8 signals typically had \u0026lsquo;M\u0026rsquo; or \u0026lsquo;N\u0026rsquo; shaped harmonics and were consistently slightly higher frequency with peak energy was at 35 to 75 Hz (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The EIO9 signal was shorter than the other non-downswept signals at between 5 and 10 seconds long and resembled the first portion of the Unit 1 of the EIOPB song. This signal was characterised by the presence of deterministic chaos at the end of the signal and peak energy around 65 Hz (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eAll four newly identified social signals were recorded at both the northwest shelf sample sites across all sample years, and the Perth Canyon sample sites (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). These signals are not known to have been recorded in Geographe Bay based on the results of Recalde Salas et al. (2014), however it cannot be excluded that they may be present in more recent years. The social sound EIO1 has been recorded at all sample sites in all sample years and is the most commonly observed social sound, even outnumbering true D calls. D calls were observed at all northwest shelf sample sites in all years and in the Perth Canyon (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The social sounds EIO2 and EIO4, previously identified from Geographe Bay, were observed in very low numbers at the northwest shelf sample sites in 2014 and 2015 (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cimg 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\" width=\"609\" height=\"320\"\u003e\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e3.2 Phrase and song patterns\u003c/h2\u003e\u003cp\u003eSocials sounds appeared on numerous occasions to be organised into phrases and repeated in a manner consistent with song. The first phrase consisted of an EIO6, and two EIO8 signals. This was followed about 10 s later by a phrase consisting of an EIO8, EIO9 and EIO1 unit. The two phrases were repeated consistently in this manner.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eIn total, there were over 300 observations of social sounds occurring in structured sequences across all the data sets. However, this is based on manual review of only 5 to 10% of most of the data sets, and complete manual analysis only of the three IMOS data sets. Despite this, structured sequences of social sounds comprised a relatively small proportion of the manually validated acoustic detections of blue whales. Blue whale song (specifically the Australian song of the EIO population) and the social signal EIO1 were considerably more abundant in the datasets.\u003c/p\u003e\u003cp\u003eWhile the EIO1 signal often appeared alone without any other social signals, EIO6, 7, 8 and 9 typically occurred in what appeared to be bouts of social signalling. In these instances, even where a distinct phrase pattern was not discernible, there appeared to be some sequencing of signals with EIO1s following an EIO9s in 91.5% of observed occurrences (N\u0026thinsp;=\u0026thinsp;281). Similarly, the EIO6 sample was followed by either an EIO7 or EIO8 in 92.6% (N\u0026thinsp;=\u0026thinsp;122) of observed occurrences. The EIO7 and EIO8 signals did not appear to occur in any particular order but were also the most difficult to distinguish between owing to their similar properties.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eSequences of social signals were observed in multiple data sets and first appeared in 2012 in the Western Timor Sea (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). The structure and sequencing of the social signals appears to be relatively consistent between sample locations and over sample years (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e). The directrograms of these sequences shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e provide further support that sequences are produced by an individual singing animal, with consistent bearings (denoted by colour) and received levels recorded throughout the sequence.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e3.3 Interobserver Reliability Test\u003c/h2\u003e\u003cp\u003eThe Fleiss Kappa test provided a measure of the level of agreement between all observers for the classification of the social sounds into the newly defined signals, EIO1 or D call groups. Classification by a group of 12 independent observers, including five trained and experienced observers and seven completely na\u0026iuml;ve observers yielded a kappa statistic of 0.73 (p-value\u0026thinsp;=\u0026thinsp;0) indicating a good level of agreement between observers. When considering the classifications of only the five trained and experienced observers the test retuned a kappa statistic of 0.93 (p\u0026thinsp;=\u0026thinsp;0) indicating near perfect agreement. A comparison of the reliability of the classification of D calls and EIO1 into distinct categories by all observers yielded a kappa statistic of 0.657 (p-value\u0026thinsp;=\u0026thinsp;1.71e-09) indicating a good level of agreement. All kappa statistics were highly statistically significant. The results of the Fleiss Kappa analysis indicate that the newly defined social sounds represent logical and appropriate groupings and support the distinct classification of EIO1 signals from D calls. The signals with the highest level of disagreement in classification were EIO7 and EIO8.\u003c/p\u003e\u003c/div\u003e"},{"header":"4.0 DISCUSSION","content":"\u003cp\u003ePopulation specific vocalisations are useful in the monitoring and management of cryptic species such as the EIOPB whale. Hunted to near extinction in the industrial whaling era and largely targeted by soviet whalers, the current status of the EIOPB stock remains largely unassessed. Passive acoustic monitoring (PAM) provides a cost-effective means for monitoring the species and the potential for long term abundance assessments. However, these methods require an adequate knowledge of the vocal repertoire of the species, particularly for PAM to be more effectively applied to census the whole population, as opposed to being biased towards singing males. Understanding the social sounds of the species presents the opportunity to more effectively quantify species presence using PAM without being subject to the inherent biases of sampling song, which are that songs are only produced by mature males, are mutually exclusive with some behaviours such as foraging and are seasonal with higher singing activity observed during the northbound migration to the calving grounds as opposed to the southbound migration. To date very few studies have focused on quantifying the social sounds of the blue whale. This may be because the identification and analysis of unknown acoustic signals is extremely time consuming, with most of the acoustic analysis reliant on the use of automated detection algorithms. These algorithms are trained based on existing knowledge of signals that can confidently be attributed to species and tend to focus on song elements as these are the most well-known, stereotyped and easily identifiable signals within acoustic data. In the context of the EIOPB whale, songs are comprised of long duration (\u0026gt;\u0026thinsp;18 s), high intensity, low frequency units that transmit over long distances and are typically easily distinguishable in acoustic data. Social signals by comparison are much shorter in duration (~\u0026thinsp;2 to 10 s) and are presumed to have a lower source level as has been observed in other baleen whales \u003csup\u003e\u003cspan additionalcitationids=\"CR25 CR26\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. These characteristics likely contribute to their poorer detectability in acoustic data with our observations indicating that with the exception of the downswept signals (D calls and EIO1), social sounds were difficult to identify and differentiate in acoustic data except in instances where there was a very good signal to noise ratio and low caller density. As discussed above, we also found that the FFT settings typically used for viewing spectrograms of blue whale song were not favourable for identifying social signals.\u003c/p\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003e4.1 Definition of New Social Sounds\u003c/h2\u003e\u003cp\u003eBased on the data, four new social sounds can be defined for the EIOPB whale population. These social sounds are similar in acoustic characteristics to existing social sounds, with EIO7 and EIO8 also bearing a striking similarity to social sounds recorded by acoustic tags deployed on North Pacific blue whales \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. Despite there not being paired visual observations, the sounds can confidently be attributed to blue whales due to their spectral characteristics including the frequency content of the signal (\u0026lt;\u0026thinsp;150 Hz), duration (2 to 5 s), the presence of tonal elements, and their frequency modulated structure. These social sounds were also all identified in the presence of other social sounds and song units known to be produced by the EIOPB whale. The social signals were recorded across multiple data sets from sample sites along the NW shelf, into the Kimberley region and in the Perth Canyon across sample years spanning from 2010 to 2025. This indicates that these social sounds are likely to have been present in many other acoustic data sets but just not identified or attributed to blue whales. The occurrence of the social sounds in these data sets and the relative consistency of these signals over time is consistent with what has been observed for other social sounds in this population. The newly defined social sounds are all frequency modulated tonal, low frequency sounds with energy focused between 20 and 75 Hz. The sounds are characteristically blue whale like in their appearance, and the similarity of the EIO1, EIO7 and EIO8 to social sounds produced by North Pacific blue whales, suggests that all blue whale populations may produce an array of social sounds and thus the vocal repertoire of blue whales globally may be considerably larger than previously thought. It is not clear why the EIOPB has a higher level of complexity in their vocal repertoire than any other mysticete species worldwide, however it is speculated this may be due to the overlap of several sub-populations of blue whales in the Indian Ocean leading to the evolution of a more complex vocal repertoire \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThe relatively low number of observations of these signals in comparison to song is unsurprising noting that most acoustic detectors are trained to search data for song signals, and manual validation effort is generally directed at a small percentage of samples that correlate with song presence. As noted above, the characteristics of these social signals, including a presumed lower source level and shorter duration also make them more difficult to identify in course manual analysis of acoustic data sets. Fine scale manual analysis of data sets is time intensive and even so, when analysts come across signals that are not the target of their study or are unknown, they are often not annotated or noted in the data analysis. As a result, it is unsurprising that these signals have gone unnoticed for so long despite the EIOPB being one of the most studied sub populations of blue whales, and it is possible that detailed manual analysis of global data sets may identify similar signals for other blue whale populations worldwide.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003e4.2 Distinction of Downswept Signals\u003c/h2\u003e\u003cp\u003eThe results of this study support the distinction between D calls and other downswept social sounds such as the EIO1 signal. Blue whales from all populations are known to produce low frequency downswept sounds that while somewhat variable in their acoustic characteristics, are consistently low frequency and short in duration (2 to 4 s)\u003csup\u003e3,28\u003c/sup\u003e. Historically, many studies have considered all downswept signals produced by blue whales to be D calls, though careful analysis of their spectral characteristics suggests that D calls should be separately classified to other downswept social signals with the primary determining feature for classification being the consistency of the signal characteristics and the presence of tonal units. The distinction of these two types of social signal is likely to be important when considering the behavioural context of signal production, particularly given that EIO1 signals have been recorded occurring in stereotypical, ordered sequences and appear to be relatively consistent in their spectral characteristics.\u003c/p\u003e\u003cp\u003eBased on our fine scale analysis, and existing work, it is postulated that true D calls are highly variable, are not produced in rhythmic sequences, and lack any harmonics or additional tonals. Differentiating D calls from EIO1 signals is further complicated by propagation processes that may result in D calls appearing with \u0026lsquo;shadows\u0026rsquo; that to the untrained eye may appear as a single harmonic. Similarly, long range propagation effects may result in EIO1 signals \u0026lsquo;losing\u0026rsquo; their harmonics at longer ranges. Expert analysis is typically required to differentiate between these signal types. While calls resembling D calls are also produced by other mysticete whales including fin and sei whales, they can, in most cases, be confidently distinguished from blue whales with appropriate contextual consideration. For example, when detected in areas where blue whales have been sighted and blue whale songs are detected on the acoustic receiver but other mysticete species known to produce D calls have not historically been detected at that time. D calls produced by blue whales also tend to be lower in frequency, with the signal starting at between 60 and 100 Hz and sweeping down to around 20 to 40 Hz.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003e4.3 Behavioural Context of Social Sounds\u003c/h2\u003e\u003cp\u003eGiven that the production of D calls appears to be rather distinct from that of other social sounds, with D calls being highly variable and not appearing in rhythmic ordered sequences, and other social sounds being relatively consistent and appearing in structured sequences, it is likely that the behavioural context of these two signal types is also distinct. The behavioural context of D calls has been studied for a number of populations of blue whales and appears to be consistent between populations. The signal is primarily detected on known foraging grounds where blue whales are aggregating to feed (Lewis et al. 2018). Acoustic tag data indicates that D calls are typically produced during shallow dives in breaks between foraging bouts. In general, D calls were recorded from whales that were loosely associated with other animals, though even those not obviously associated with another animal were within 1 km of other blue whales \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. Based on the result of an acoustic tagging study, D calls were considered to have a clear behavioural context being produced by both male and female whales during breaks between foraging at depth \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. Both Oleson et al. and Thode et al. found that blue whales produce multiple D calls per dive, typically at depths of between 15 and 35 m. It is hypothesised that at these depths, blue whales would be able to visually identify conspecifics and thus D calls likely have a social function as opposed to reproductive function. This is further supported by the fact D calls have been observed on foraging grounds as call-counter-call events within a group of two or more blue whales \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. Geographically, recordings of D calls typically overlap known or likely foraging areas, for example the Perth Canyon in Western Australia \u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. Similarly, Barlow et al. \u003csup\u003e31,32\u003c/sup\u003e observed seasonal and daily trends in the production of D calls that aligned with seasonal and daily variability in blue whale foraging effort. Shabangu et al. \u003csup\u003e33\u003c/sup\u003e also found a correlation of D call presence and higher chlorophyll-a concentrations in the Benguelan current ecosystem, further supporting the association between foraging behaviours and D calls. D calls are also known to be produced during encounters of different group compositions, including mother-calf interactions (Lewis et al., 2018; Oleson et al., 2007).\u003c/p\u003e\u003cp\u003eSocial sounds appear to be produced by blue whales in a variety of contexts. Behaviours associated with singular song unit production were different to those associated with singing. Tagging studies have found that the production of singular calls was most common during shallow non lunging dives, and common during surface behaviour. Animals producing singular song units were always observed in close association with at least one other blue whale, and where tissue samples were available, were found to be produced by male and female pairs \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. There has been one instance where an animal was recorded singing while travelling alone and was then observed to transition to producing singular song units once it had joined up with another blue whale. Another study observed downswept signals with harmonics, like the EIO1 signal identified in Recalde Salas et al. (2014), being produced during a heat run where two males were in pursuit of a female blue whale (Schall et al., 2020). These signals were associated with trios of animals in two populations of blue whales, as well as being recorded on foraging grounds (Schall et al., 2020). Schall et al. (2020) considered the context of D calls may be reproductive noting that D calls, along with EIO1 like signals and other unidentified grunts and blip sounds were produced during heart runs in two geographically distinct populations. While not likely to be a \u0026lsquo;reproductive\u0026rsquo; display in the way that song is, these sounds could be used to mediate social interactions - including those of a reproductive nature. The occurrence of reproductive behaviours on foraging grounds is no surprise and has been speculated for blue whales given they are often solitary and are a low-density species. Feeding aggregations likely provide an opportunity for reproductive behaviours. Thus, the presence of D calls and social signals may be indicative not only of foraging but also of reproductive behaviours. Based on the results of acoustic tagging studies, social sounds are produced when blue whales are in close proximity with other conspecifics and do not appear to be produced at the same time as song. Consequently, it would be expected that social signals may be detected acoustically when blue whales are present but blue whale song may not be. This reflects the findings of Recalde Salas et al. (2014) who recorded many non-song social vocalisations but little to no song alongside visual observations of EIO pygmy blue whales on their southbound migration through Geographe Bay in Western Australia.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003e4.4 Complexity in Non-Song Communication\u003c/h2\u003e\u003cp\u003eUnlike D calls and EIO1 signals, the EIO6, EIO7, EIO8 and EIO9 social sounds were almost exclusively observed to occur in semi organised clusters with some level of rhythmicity. Some of the signals, such as EIO6 and EIO9 consistently occurred in sequence with other units, in particular EIO9 which occurred almost exclusively prior to an EIO1 signal, suggesting that social communication in blue whales may be governed by some form of simple syntax. The notion of syntax in marine mammal vocalisations is a topic of ongoing study, with research supporting the presence of syntactic rules in the vocal displays of vocal learning marine mammals \u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. Structural rules such as deterministic motifs, which drive stereotypy in sequences by limiting the sequence in which units appear, as well as a high level of unit redundancy and the disproportionately high usage of a few units, have been shown to influence the stability and stereotypy observed in animal song displays \u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e,\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. While the presence of syntactic features such as deterministic motifs and redundant unit usage have been confirmed in the songs of many songbirds, as well as both humpback and blue whale songs \u003csup\u003e\u003cspan additionalcitationids=\"CR35 CR36 CR37 CR38 CR39 CR40 CR41\" citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e, it is less clear whether these features apply in the non-song social communication of cetaceans.\u003c/p\u003e\u003cp\u003eThe observation of social signals arranged in what appeared to be two distinct phrase types that were repeated in a rhythmic fashion would meet the definition of song as it is typically applied for marine mammals. It is not clear whether this constitutes a new and alternative song for the EIOPB whale with the purpose of a reproductive display, or if the observed patterns are the result of complex non-song communication. Social signals form part of the signal repertoire for the species, and just as song units can be produced singularly and as part of song it is the organisation of units from a vocal repertoire into a structured sequence that defines song \u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e. Consequently, the production of social sounds in structured sequences could suggest a novel use of pre-existing vocal units, which could indicate the cognitive capability of the individual and be a favourable display for sexual selection. However, if this were the case it would be expected that the song would be more prevalent in the datasets than it is. Noting that the social sounds have appeared in patterned sequences over many sample years with a high level of stability and low level of occurrence, it seems unlikely that they are part of a reproductive display and thus subject to sexual selection pressures. Rather, it seems much more likely that the observed rhythmicity and structure of these non-song vocalisation bouts is further evidence for syntax in the vocal behaviour of blue whales.\u003c/p\u003e\u003c/div\u003e"},{"header":"5.0 CONCLUSION","content":"\u003cp\u003eThis study presents evidence of four new non-song vocalisation types for the EIOPB whale, suggesting this population has a higher level of vocal complexity and possibly cognitive capacity than has been observed in other balaenopterid species. These signals are believed to be social sounds and have been recorded in across multiple sample years and sample locations indicating a high level of stability in the vocal repertoire of blue whales. This paper also presents the first evidence of blue whale social sounds being arranged in structured sequences and repeated in a rhythmic fashion, supporting the hypothesis that blue whale vocal communication is governed by a form of syntax, providing the first evidence of syntactic features in non-song vocalisations and contributing to our understanding of marine mammal vocal behaviour.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eThe authors confirm they have no competing interests to declare.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eACKNOWLEDGEMENTS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAcoustic data used for analysis in this paper was sourced through a combination of JASCO acoustic monitoring programs and Integrated Marine Observing System (IMOS) moorings.\u003c/p\u003e\n\u003cp\u003eData for this work from JASCO monitoring programs was extracted from monitoring programs in the Perth Canyon (including with gliders in collaboration with Blue Ocean Marine Tech Services), and north-west Australia between 2011 and 2025. The monitoring programs in north-west Australia were conducted as part of baseline monitoring programs on behalf of PTTEP Australia, ConocoPhillips, Shell Australia Pty Ltd.\u003c/p\u003e\n\u003cp\u003eData from Integrated Marine Observing System (IMOS, 2008-2017). The IMOS observatory is supported by the Australian Government through the National Collaborative Research Infrastructure Strategy and is publicly available through the IMOS portal https://acoustic.aodn.org.au/acoustic/ or can be requested from https://portal.aodn.org.au/.\u003c/p\u003e\n\u003cp\u003eThank you to Scott French, Grace McPherson, Gabrielle Genty, James Tanner, Felix de Wattripont, Jess Cafagna, Dzenita Djamanovich and Callum Jolliffe who volunteered their time for the interobserver reliability test. Thank you to Julien Delarue for assistance in the review of the draft manuscript. A special acknowledgement to Ivy Beck, whose keen young eyes picked out some blue whale signals in a spectrogram that weren\u0026rsquo;t quite like the others while helping her mum work one Sunday morning.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eETHICS \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe research presented and reported in this paper was conducted in compliance with the National Health and Medical Research Council Australian code for the care and use of animals for scientific purposes 8th edition (2013). The IMOS and CMST research study received animal ethics approval from the Curtin University Animal Ethics Committee, Approval Number # AEC_2013_28 - Passive acoustic recording of marine animal (mammal and fish) vocalisations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAUTHOR CONTRIBUTIONS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eC. Jolliffe: Conceptualisation, Data Collection, Figures, Manuscript Preparation, Data Analysis, Writing, Review.\u003c/p\u003e\n\u003cp\u003eC. McPherson: Data Collection, Data Analysis, Figures, Manuscript Preparation, Writing, Review.\u003c/p\u003e\n\u003cp\u003eR. McCauley: Data Collection, Data Analysis, Review.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eJolliffe CD et al (2019) Song variation of the Eastern Indian Ocean pygmy blue whale population. PLoS ONE. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.1371/journal.pone.0208619\u003c/span\u003e\u003cspan address=\"https://doi.org:10.1371/journal.pone.0208619\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSamaran F, Olivier A, Guinet C (2010) Discovery of a mid-latitude sympatric area for two Southern Hemisphere blue whale species. 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Front Psychol 11:2387. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.3389/fpsyg.2020.544929\u003c/span\u003e\u003cspan address=\"https://doi.org:10.3389/fpsyg.2020.544929\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-7938626/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7938626/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIn an underwater world, acoustic signalling is an important aspect of the social communication of marine mammal species with the complexity of a species\u0026rsquo; vocal repertoire often considered to reflect the social complexity of the population. The acoustic behaviour of blue whales is relatively well studied, though much of what is known is limited to the characteristically loud, low frequency songs that are believed to be produced as a reproductive display by male animals. Blue whales are known to produce song units outside of stereotypical song sequences, along with short duration down swept signals known as \u0026lsquo;D calls\u0026rsquo; leading researchers to believe their acoustic communication, and by proxy their social cognition is relatively less complex when compared to other baleen whales such as humpback and bowhead whales. Drawing from a multidecadal data set of acoustic recorders deployed throughout the migratory range of blue whales, this paper characterises four previously undescribed signals for the East Indian Ocean pygmy blue whales and presents the first known evidence of a large baleen whale producing these social sounds in stereotyped patterned sequences that bear similarity to song. This indicate a higher level of complexity in the social communication of blue whales than previously understood and provides further support that blue whales have a higher level of social cognition than has been considered previously.\u003c/p\u003e","manuscriptTitle":"Singing to the sound of their own tune: Uncovering an increasingly complex vocal repertoire for the east Indian Ocean pygmy blue whale","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-30 07:06:22","doi":"10.21203/rs.3.rs-7938626/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d22aa27a-34fb-4364-891a-35d82a70a820","owner":[],"postedDate":"October 30th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":56888560,"name":"Biological sciences/Zoology/Animal behaviour"},{"id":56888561,"name":"Physical sciences/Physics/Applied physics/Acoustics"}],"tags":[],"updatedAt":"2025-11-10T17:36:15+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-30 07:06:22","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7938626","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7938626","identity":"rs-7938626","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}