Vocal characteristics of pygmy blue whales and their change over time Alexander N. Gavrilov,a) Robert D. McCauley, and Chandra Salgado-Kent Centre for Marine Science and Technology, Curtin University of Technology, G.P.O. Box U1987, Perth, Western Australia 6845, Australia
Joy Tripovich School of Biological, Earth and Environmental Sciences, The University of New South Wales, Sydney, New South Wales 2052, Australia
Chris Burton Western Whale Research, P.O. Box 1076, Dunsborough, Western Australia 6281, Australia
(Received 1 June 2011; revised 7 September 2011; accepted 13 September 2011) Vocal characteristics of pygmy blue whales of the eastern Indian Ocean population were analyzed using data from a hydroacoustic station deployed off Cape Leeuwin in Western Australia as part of the Comprehensive Nuclear-Test-Ban Treaty monitoring network, from two acoustic observatories of the Australian Integrated Marine Observing System, and from individual sea noise loggers deployed in the Perth Canyon. These data have been collected from 2002 to 2010, inclusively. It is shown that the themes of pygmy blue whale songs consist of ether three or two repeating tonal sounds with harmonics. The most intense sound of the tonal theme was estimated to correspond to a source level of 179 6 2 dB re 1 lPa at 1 m measured for 120 calls from seven different animals. Short-duration calls of impulsive downswept sound from pygmy blue whales were weaker with the source level estimated to vary between 168 to 176 dB. A gradual decrease in the call frequency with a mean rate estimated to be 0.35 6 0.3 Hz/year was observed over nine years in the frequency of the third harmonic of tonal sound 2 in the whale song theme, which corresponds to a negative trend of C 2011 Acoustical Society of America. about 0.12 Hz/year in the call fundamental frequency. V [DOI: 10.1121/1.3651817] PACS number(s): 43.30.Sf, 43.80.Ka, 43.30.Nb [WWA]
I. INTRODUCTION
Pygmy blue whales are a subspecies of blue whales (Balaenoptera musculus) inhabiting the Indian Ocean and the South-west Pacific (Rice, 1998). The species found in the southwestern part of the Indian Ocean south off Madagascar and in the eastern Indian Ocean west off Australia and Indonesia is commonly referred to in the biological literature as Balaenoptera musculus brevicauda (Ichihara, 1966). Pygmy blue whales have also been observed in the Southern Ocean from the Great Australian Bight to Bass Strait (Gill et al., 2011). They are believed to belong most likely to the same population as pygmy blue whales in the eastern Indian Ocean (Branch et al., 2007). This is proven to a certain extent by the same song structure of whales observed in the Indian and Southern Oceans in this study. The whales from the southwestern Pacific population found mainly north off New Zealand and around the Southwest Pacific Islands differ from the pygmy blue whales of the eastern Indian Ocean population in their size and in the sounds they produce (McDonald, 2006). A separate population of pygmy blue whales was identified in the Northern Indian Ocean. The animals from this population appear to stay year-round within a limited area between Somalia and Sri Lanka and make calls a)
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Pages: 3651–3660
distinct from those of the other pygmy blue whales in the Indian Ocean (Alling et al., 1991). This population has been suggested to comprise of a separate subspecies referred to as Balaenoptera musculus indica. Characteristics of pygmy blue whale vocalization have been considered in several publications. McDonald et al. (2006) summarized data from passive underwater acoustic observations of whales distinguishing blue whale subspecies and populations by the spectrograms of their songs. Stafford et al. (2010) reported different call structures of pygmy blue whales from the Sri Lanka, Madagascar and Australian populations in the Indian Ocean. McCauley et al. (2001) analyzed the structure of pygmy blue whale songs of the eastern Indian Ocean population observed in Western Australia. Samaran et al. (2010) measured the source level of calls from pygmy blue whales of the Madagascar population, using acoustic data from the comprehensive nuclear-test-ban treaty (CTBT) hydroacoustic station off Crozet Island in the Southeast Indian Ocean. Assuming a simple spherical spreading model for the transmission loss and using hyperbolic location of whales from a triangular array of the hydroacoustic station, the source level of whale calls was estimated to be 174 6 1 dB re 1 lPa at 1 m, which is at least 10-dB lower than the estimates made for other blue whale subspecies (e.g., Thode et al., 2000, McDonald et al., 2001 and Sˇirovia´c et al., 2007). Recently, McDonald et al. (2009) made an interesting discovery revealing a gradual decrease of tonal frequencies
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in songs of different blue whale subspecies worldwide. This observation was unambiguous only for the northeastern Pacific population of blue whales, where the number of calls and animals sampled was large enough to estimate the mean call frequency and the duration of observations was long enough to reveal an interannual trend. However, for pygmy blue whales in the Indian Ocean, the number of animals and samples made in different years was too small to make a reliable conclusion regarding trends in the call frequency. Although the population of pygmy blue whales is believed to have been growing since the end of commercial whaling, little is published about the abundance and migration patterns of pygmy blue whales in the eastern Indian and Southern Oceans. McCauley and Jenner (2010) reported on the northward and southward migratory phases of pygmy blue whales travelling along the Western Australia coast. Based on passive acoustic detections, they estimated the number of whales, migrating southward past Exmouth in 2004, to be between seven and fifteen hundred. For monitoring the population and studying the migration of pygmy blue whales by means of passive acoustic observations in the ocean, the structure of whale songs and acoustic characteristics of individual calls need to be known. For example, knowing the song structure is crucial for determining the number of vocalizing whales within a certain time period. The acoustic source level of whale vocalization is required for estimating the detection range in the ocean from a passive acoustic station. The structure and frequency of whale calls and their changes over time need to be known to design an efficient acoustic detector of vocalizing whales. The aim of the study presented in this article was to analyze the structure and acoustic characteristics of vocalizations produced by pygmy blue whales of the eastern Indian Ocean population and to examine changes in these characteristics over time. This analysis was made using (1) acoustic data collected at the CTBT hydroacoustic station off Cape Leeuwin in Western Australia (referred to as HA01 in the CTBT nomenclature) in 2002 – 2007, (2) underwater acoustic recordings made by the passive acoustic observatories of the Integrated Marine Observing System (IMOS) deployed in the Perth Canyon in Western Australia and off Portland in Victoria in 2009 – 2010, and (3) sea noise data collected in the Perth Canyon before 2009 under support from Australian Defense. The passive acoustic observing systems and the data used for the analysis presented in this article are described in Sec. II. The structure of pygmy blue whale songs and their individual calls are discussed in Sec. III. The source level of whale vocalization is analyzed in Sec. IV using hyperbolic location of signals sources from a triangle array of the HA01 station and numerical modeling of acoustic propagation at the station. The location errors and ambiguity are also considered. Longterm changes in acoustic characteristics of whale calls observed from 2002 to 2010 are discussed in Sec. V. II. DATA COLLECTION
The locations of three passive acoustic stations used for detection of pygmy blue whales and recording their calls are 3652
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FIG. 1. Locations of the HA01 CTBT station (black triangle) and two IMOS acoustic observatories (black squares) used for studying vocalization characteristics of pygmy blue whales.
shown in Fig. 1. Three acoustic receivers of the HA01 station are moored at a depth of about 1100 m below the sea surface at approximately 2 km from each other to form a triangular array. The timing accuracy of signal sampling in all three receive channels is 1 ms, provided by synchronization to GPS clock. The hydrophones are calibrated to ensure the accuracy of acoustic pressure measurements of 61 dB within the frequency band of 10–100 Hz. The seafloor around the station is gently sloping with the sea depth of about 1600 m at the array center. The receiving system records sea noise continuously at a sampling frequency of 250 Hz and communicate acoustic data to the shore in real time via an underwater cable. The IMOS acoustic observatories consist of four autonomous sea noise loggers set on the seafloor as a triangular array of about 5-km sides with the fourth logger placed at the array center. Sea noise recordings are programmed to sample 500 s starting every 900 s. The sampling frequency is 6 kHz and the upper limit of the frequency band is 2.8 kHz at 3 dB. Sea noise is recorded almost year round with a short interruption for system redeployment with data retrieval every eight to twelve months. Recordings of sea noise and whale calls in the Perth Canyon in 2005 and 2008 were made on a single bottom-mounted sea noise logger. Continuous recordings of 200 s long were made at a sampling frequency of 6 kHz and repeated every 900 s over approximately six months in both seasons. III. WHALE SONG STUCTURE
Songs produced by pygmy blue whales of the eastern Indian Ocean population consist of a series of sounds, sometimes referred to as themes, repeated with more or less regular intervals over a long time from several tens of minutes to hours. The most common theme observed in Perth Canyon consists of three quasi-tonal multi-harmonic sounds made within approximately 120 s from the theme initiation to the end of the last sound (top panel in Fig. 2.). The introductory Gavrilov et al.: Pygmy blue whale vocalization
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FIG. 2. Spectrograms of pygmy blue whale songs consisting of repeating three-sound themes (top panel) and two-sound themes (bottom panel). Spectrogram parameters: 1024-point FFT, 1024-point Hanning window with 95% overlap.
sound (or sound 1 of the theme) is usually the weakest and longest one lasting up to 50 s. The principal frequency of this call is about 20 Hz. It often increases stepwise by about 1 Hz in the middle of calls. The power spectrum of this call spans frequencies typically to 70–80 Hz. This introductory sound is least stable compared to the other two sounds in terms of the amplitude, duration, frequency content and the consistency it appears in the song theme. The introductory sound, when it is present, is followed by the second sound (sound 2) after a pause of a few seconds. This sound is usually the most intense and invariable one. The fundamental frequency of this call always increases from 20–21 Hz to 23–24 Hz during the call duration of about 25 s, so do the multiple harmonics. The third harmonic is most prominent after the principal frequency in the signal spectrum. In a noisy ocean environment, when the noise level decreases noticeably with the frequency increase from 20 Hz to 70 Hz, the third harmonic of this call often has the maximum signal-to-noise ratio (SNR) and hence can be used as the main feature for call detection. The last sound of the theme usually starts about 20 s after the end of the previous sound and lasts for approximately 20 s. Its spectrum consists of many spectral lines that do not change frequency noticeably during the call. These spectral lines include the principle frequency of 19–20 Hz, its harmonics of high amplitude and a number of other frequencies J. Acoust. Soc. Am., Vol. 130, No. 6, December 2011
of lower spectral levels. A series of tones offset from the harmonics of the fundamental frequency can also be distinguished in this sound, when the signal-to-noise ratio is high, which may indicate that there is another source of sound in the whale vocal apparatus. The most typical repetition interval of the whale songs consisting of the three-sound theme is about 190 6 5 s. However, it can vary between different songs and animals from approximately 175 s to 220 s. There are probably other factors of environmental or behavioral origin that affect the theme repetition rate of individual animals. Whale songs consisting of the three-sound theme were also often recorded at the HA01 station off Cape Leeuwin and at other locations along the continental slope of Western Australia. However, more than half of the songs detected off Cape Leeuwin have the introductory sound omitted in the periodical themes, while the second and third sounds of the theme preserve similar frequency and time characteristics to those of the three-sound theme. Moreover, when the whale skips the introductory sound, the theme repetition interval reduces to approximately 80 s (bottom panel in Fig. 2). There is no obvious explanation why pygmy blue whales alter their song theme and the theme repetition interval. The difference in the whale behavior in different areas can be one of the likely reasons for such an alteration. It is believed that the area around Perth Canyon can be a feeding ground for pygmy blue whales (Rennie et al., 2009), so whales may stay there for many weeks, if the productivity is high within a season. In contrast to the Perth Canyon, the continental shelf and slope area southwest of Cape Leeuwin is thought to be a region the whales travel through during migration, so most of the whales recorded are believed to be moving in a certain direction. One of the authors of this article made simultaneous visual and acoustical observations of a pygmy blue whale in Geographe Bay in Western Australia and recorded calls from this animal that were totally different from the tonal sounds commonly produced by pygmy blue whales. These calls were impulsive signals of about 1 to 2 s long with the call frequency changing rapidly with time (top panel in Fig. 3). Similar calls were also found in the acoustic recordings made off Cape Leeuwin (bottom panel in Fig. 3) and in the Perth Canyon during the presence of pygmy blue whales in the listening areas. Based on these observations, this type of call was attributed to pygmy blue whales. The longest and most intense part of the call is a downsweep signal with the principal frequency decreasing rapidly from 70–100 Hz to 20–50 Hz within different frequency bounds in different calls. A similar type of blue whale call, sometimes referred to as a D-type call, is frequently observed in the Northern Pacific (Oleson et al., 2007) and in the Southern Ocean (Rankin et al., 2005). In Australia, this type of pygmy blue whale call is less common than the tonal sounds. In contrast to the song themes of tonal sounds, the D-type calls are not repeated with regular intervals. IV. SOURCE LEVEL OF PYGMY BLUE WHALE CALLS
To estimate the source level of whale calls, it is necessary to (1) detect calls from a vocalizing whale; (2) accurately measure the acoustic pressure of the received signal; (3) Gavrilov et al.: Pygmy blue whale vocalization
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FIG. 3. Spectrograms of downsweep signals of pygmy blue whales calls recorded in Geographe Bay (top panel) and off Cape Leeuwin (bottom panel) in Western Australia. Spectrogram parameters: 256-point FFT, 128point Hanning window with 95% overlap.
measure the distance to the calling whale; (4) have some knowledge of the most likely source depth; (5) estimate the transmission loss (TL) at the measured distance and expected source depth using either empirical or numerical acoustic propagation models; and (6) estimate the source level reduced to a reference distance, which is usually 1 m. Whale detection can be implemented either through visual inspection of sea noise spectrograms or via an automatic searching algorithm capable of recognizing calls by certain whale species in sea noise. Measuring the received level is straightforward if the acoustic receive system is accurately calibrated. The accuracy of the other three operations greatly depends on the measurement geometry and the knowledge of the environment. The triangular array of the HA01 station was used to locate vocalizing whales and estimate the source level of their calls. The array geometry is shown in Fig. 4. A. Whale detection and measurements of received signal level
A signal recognition algorithm for automatic detection of pygmy blue whale calls was designed and tested using the CTBT and IMOS passive acoustic data. The algorithm searches for transient signals in sea noise with time-frequency features similar to those of the first and third harmonics of theme sound 2, which is common for all whale songs. These features are the signal duration, the frequency band and the slope of frequency change with time. The algorithm demonstrated misdetection and false detection rates of less than 5%. Misdetected calls were either very weak or hidden in noise 3654
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FIG. 4. Located positions of two vocalizing whales (small dots) making regular tonal calls (top panel) and sporadic downsweep calls (bottom panel) recorded in 2002 and 2003 respectively; the relative location of the HA01 hydrophones (black circles); location ambiguity zones (shadowed areas in the top panel); and error ellipses of location at 95% confidence level (dashed ellipses). The arrow in the top panel shows the general travel direction of the singing whale with the mean speed hVi.
from other sources with similar spectral characteristics, e.g., shipping noise. Only the signals of a high SNR were chosen from several thousands of detected calls for locating whales. For each event of successful location of a vocalizing whale, the received signal level was measured for sound 2 of the song theme, as the most intense one, at all three hydrophones of the receive array. The level was estimated from the mean intensity of the signal band-pass filtered in 22–25 Hz and 66–75 Hz frequency bands, which spanned the principal frequency and its third harmonic containing more than 90% of the signal energy. The measured signal intensity was also corrected for the noise intensity, i.e., squared RMS amplitude, Gavrilov et al.: Pygmy blue whale vocalization
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estimated in the same frequency bands. Signals with the SNR of less than 6 dB were not considered in further analysis of the source level. The received level of downsweep signals from pygmy blue whales was estimated from the maximum RMS amplitude of acoustic pressure measured in a 0.5-s window in a broad frequency band of the signal spectrum. The measured signal levels were corrected for the mean noise level immediately before the signal detection. B. Location
Location of an underwater acoustic source using a triangular array, similar to that of the HA01 CTBT hydroacoustic station, is not a trivial problem. Firstly, at least five receivers are needed to unambiguously locate a point source in threedimensional space using a hyperbolic method (Spiesberger, 2001), if the time differences of signal arrivals (TDOA) are accurately measured and the sound speed is known. Secondly, the ocean acoustic environment is not free space. It is bounded by the sea surface and seafloor and commonly has depth dependent sound speed, which causes multipath propagation from an acoustic source to a receiver. Acoustic signals propagated along different paths interfere with each other, resulting in errors of the TDOA measurements for direct signal arrivals using cross-correlation of signals at different hydrophones. Finally, the acoustic environment in the observation area, including the sound speed profile, bathymetry and acoustic properties of the seafloor, is not absolutely known in practice. To overcome these problems, one can make the assumptions and implement the approaches as follow: (1) The receivers’ depth is usually known to certain accuracy (about 1100 m for the HA01 hydrophones). The depth of the source to be located (e.g., whale) is usually unknown. However, some assumptions with respect to the most likely source depth and its possible variations can be made based on available data. According to the measurement made by Oleson et al. (2007), blue whales of the northeast Pacific population make quasi-tonal calls, somewhat similar to those of Australian pygmy blue whales, at depths varying from 20 to 30 m, i.e., near the sea surface in a deep-water environment. If the sound production physiology is similar for blue whales regardless of their habitation area, then we can assume that pygmy blue whales make tonal calls within the same depth range. Once the receivers’ and source depths are determined, the 3D hyperbolic location problem reduces to a 2D scenario. However, a triangular array of three receivers has zones of ambiguous location (shadowed zones shown in the top panel of Fig. 4), where two solutions of the hyperbolic equation system exist for the same set of TDOA data. If the location solution falls into one of those zones, then such a location is either ignored in further analysis of the source level or compared to the other possible solution to select the most likely one based on other criteria, e.g., the locations of previous calls by a periodically vocalizing whale and the feasible speed of its motion. J. Acoust. Soc. Am., Vol. 130, No. 6, December 2011
(2) It is difficult to allow for the effect of multipath propagation in TDOA estimates by locating maxima of the signal cross-correlation. Cross-correlating signal spectrograms rather than waveforms reduces the multipath effect to a certain extent (Samaran et al., 2010), but at the cost of considerable degradation of the TDOA measurement accuracy. The problem can be partly conquered by ignoring events of inconsistent TDOA measurements when Dt12 6¼ Dt13 Dt23 ; Dtij is the TDOA measurement for receivers i and j. (3) Because the TDOA measurements contain errors due to limited SNR and multipath propagation effects and the actual positions (X, Y, Z) of the receivers and the source depth are known only to a certain accuracy, the location problem can be solved only in the least squares (LS) sense. The functional to be minimized is Wð X S ; Y S Þ ¼
X
2 Dtij Ri Rj =C ;
(1)
i;j6¼i
where Ri ¼ ½ðXS Xi Þ2 þðYS Yi Þ2 þðZS ZR Þ2 1=2 is the distance from the source to receiver i located at Xi, Yi and ZR, ZS is the source depth, XS and YS are horizontal coordinates of the source to be estimated, and C is the sound speed. Here we assume that the sound speed averaged along direct paths to all receivers is the same. We can also assume that errors in the distances Ri due to uncertainties in the receivers’ positions Xi, Yi and ZR and the source depth ZC can be allowed for in the errors of TDOA measurements. Moreover, in the LS approach to the hyperbolic location problem, the requirement for the TDOA measurements to be consistent for three pairs of receivers can be less strict: jDt12 Dt13 Dt23 j < dt; where dt is the criterion of the TDOA discrepancy chosen to omit measurements resulting in large location errors. A Levenberg-Marquardt method (Bjo¨rck, 1996) for solving non-linear LS problems was used in this study to locate pygmy blue whales from the triangular array of the HA01 station. Sound 2 of the song theme was chosen for TDOA measurements, as it was generally the most intense sound of pygmy blue whale songs. The TDOA maximum discrepancy dt was chosen to be 0.05 s, which is about one period of the principal frequency of this sound. The detected whales were located in two iterations. Firstly, possible locations of a vocalizing whale were searched for by using a set of initial guesses distributed on an equidistant grid spanning an area of 10 by 10 km wide around the receive array. The grid size was 0.5 km. The LS algorithm stopped searching the solution either after 1000 iterations or when two consecutive iterations did not change the criterion v2 ¼ W=r2t by more than 0.01, where r2t ¼ dt2 was the initial guess for the variance of the TDOA measurements common for all three pairs of receivers. The solution of smallest covariance (smallest error ellipse) was taken as a coarse location estimate. If two solutions with Gavrilov et al.: Pygmy blue whale vocalization
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significantly different locations and small covariance were found, then one of those was selected based on the previous locations of the vocalizing whale. The selected location was used as an initial guess for refining location and estimating location errors in the second iteration, where the variance r2t of TDOA measurements was updated separately for each pair of receivers, based on the coarse location estimate and the variance of the receivers’ horizontal positions and source depth. The standard deviation of the HA01 hydrophones from their relative horizontal position in the triangular array was estimated to be most likely less than 20 m (Li and Gavrilov, 2007). The source depth was assumed to be 25 6 5 m. Locations of a whale traveling through the HA01 array and making regular tonal calls are shown in the top panel in Fig. 4. The whale was moving generally in the northnorthwestern direction, although its track was not rectilinear. The average travel speed was 5 to 6 km/h. Most of the calls by this whale were located outside the ambiguity zones. The error ellipses of 95% confidence level shown in this figure decreased rapidly as the animal approached the array. Another six whales traveled close to the HA01 station in 2002 – 2006, such that their locations during vocalization could be determined more or less accurately. Some of these whales were also travelling in the north-northwestern direction. The distance from each located position of vocalizing whales to all three receivers of the HA01 station was used to estimate the source level of whale calls. A series of downsweep calls of type D from pygmy blue whales that were close and strong enough to be located from the HA01 station was recorded in early March 2003. These calls were definitely from a few different animals, although the actual number of vocalizing whales could not be identified. The whales did not cross over the receive array while vocalizing and stayed farther from the array than the whales located by their tonal sounds. The SNR of these calls was much lower than that of the tonal calls used for location. Nevertheless, the TDOA measurements were accurate enough to locate several calls, which was due to a much broader frequency band of the downsweep signals. The locations of the calling whales detected from the HA01 station is shown in the bottom panel of Fig. 4. The approximate detection time of whale vocalizations is also shown at each location. Based on the locations and times of four calls detected between 7:26 and 7:36, one can conclude that one animal was moving in the north-northeastern direction away from the acoustic array. The other six calls are difficult to interpret with respect to whale identification and motion. C. Source level of whale calls 1. Tonal calls
Transmission losses (TL) were estimated using both numerical modeling and a simple approximate equation. Because (1) the signal source was located at relatively short distances compared to the sea depth of about 1600 m and (2) the seafloor within the area of whale location was rather flat, the numerical prediction of TL was made using a wavenumber integration method (Jensen et al., 2000). This allowed us to take into account the signal energy reflected from the sea3656
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floor at steep angles. The sound field was modeled at frequencies from 20 Hz to 75 Hz with a 0.5-Hz increment for two sources depths of 20 m and 30 m. The sound speed profile was calculated from the World Ocean Atlas 2009 seasonal temperature and salinity data. Acoustic properties of the seafloor were modeled based on results of geoacoustic inversion for airgun signals recorded at the HA01 station at different distance from 20 km to 80 km from the signal source (Gavrilov et al., 2007). A simple fluid half-space model was assumed with the geoacoustics properties corresponding to medium to coarse sand: compressional wave velocity of 1800 m/s, density of 2100 kg/m, and sound attenuation of 0.15 dB/m kHz. The transmission losses averaged in the two frequency bands of signal filtering are shown in Fig. 7. The effect of source depth is noticeable at distances less than approximately 3 km. Beyond this transition range, the transmission losses tend to follow a cylindrical spreading law and their changes are not significant when the source depth varies from 20 m to 30 m. For lack of adequate environmental data, especially those related to the acoustic properties of the bottom, some authors (e.g., McDonald et al., 2001 and Samaran et al., 2010) used a simple spherical spreading model to predict the transmission losses. This could be a reasonable approximation at relatively short distance, if two factors were taken into account. Firstly, for a shallow source and deep receivers in deep water, the slant distance between the source and the receiver must be used rather than the horizontal range. Secondly, the signal from a shallow source reflected from the sea surface contributes to the received signal energy nearly as much as the direct signal. Consequently, the transmission losses are expected to be more accurately approximated with the following range dependence: h 1=2 i 3 dB; TL 20 lg R2 þ ZR2
(2)
where R is the horizontal distance to the source and ZR is the receiver depth. The source depth is neglected in Eq. (2), as small compared to ZR. The transmission loss calculated from Eq. (2) and shown in Fig. 5 by the dash-and-dot line approximates reasonably well the numerically predicted transmission losses up to the transient range of about 3 km, beyond which the numerically predicted and approximate TL curves gradually diverge tending to the spherical and cylindrical decay rates, respectively. The received levels of 120 signals from seven pygmy blue whales located close to the HA01 station in 2002–2006 are shown in Fig. 6. The measured signal level decreases almost consistently with range with relatively small dispersion. Moreover, there is no evident difference between the levels of signals received from different animals at the same ranges. The sound from the whale observed in 2006 was slightly more intense at shorter distances than that from the other whales, but only by 1–2 dB. Using the numerically modeled TL curves for estimating the source level was not straightforward, because the source depth, that greatly affects the signal level at short distances, was not precisely known. For this reason, we used the spherical spreading approximation given by Eq. (2) to estimate the source level. The best fit Gavrilov et al.: Pygmy blue whale vocalization
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FIG. 5. Acoustic transmission losses averaged in two frequency bands of 22–25 Hz and 66–75 Hz, modeled for the ocean acoustic environment at the HA01 station and two source depths of 20 m (dashed line) and 30 m (solid line). The dash-and-dot line shows the approximate TL curve based on spherical spreading of acoustic energy with slant range to the source near the sea surface and corrected for the contribution from the surface reflected signal.
of the experimental measurements by the approximate TL curve is shown in Fig. 6 by the dashed line. It corresponds to the source level of 179 dB with 2-dB standard deviation. 2. Downsweep calls
The signal levels of downsweep calls from pygmy blue whales measured at the HA01 hydrophones are shown in Fig. 7. The first observation from this plot is that the received signal level varied among different calls much more than with distance to the calling whale. At distances from 3 km to 5 km from the calling whales, the received signal levels varied from about 101 dB to 109 dB re 1 lPa. This means that the source level of different downsweep calls by pygmy blue whales varies considerably in contrast to the tonal calls. Based on the approximate TL curve given in Eq. (2) and the signal levels measured at 3–5 km, the source level of downsweep calls might vary from about 168 dB to nearly 176 dB re 1 lPa at 1 m.
FIG. 6. Received signal levels measured for seven whales located at different distances from the HA01 hydrophones. The dashed line shows the best fit of the measured level by the approximate TL curve given in Eq. (2). J. Acoust. Soc. Am., Vol. 130, No. 6, December 2011
FIG. 7. Received signal levels measured for ten downsweep signals from pygmy blue whales received at different distances from the HA01 hydrophones.
V. LONG-TERM CHANGES IN PYGMY BLUE WHALE SOUND
McDonald et al. (2009) found recently that the tonal frequencies of blue whale songs had been gradually decreasing in several parts of the world ocean since the earliest recordings in the mid 1960 s. This astonishing finding was primarily supported by a long series of observations made in the northeastern Pacific from 1963 to 2008. The number of different animals assessed with respect to their call frequency varied from one to ten in different years of the observation period. These authors also noticed that pygmy blue whales of the eastern Indian Ocean population had slightly higher call frequencies in 1993 than those recorded in 2000. The comparison was made for six calls of two different animals recorded in 1993 and about 200 calls from an unknown, but presumably small number of whales recorded in 2000. A similar observation was made in this study based on the acoustic recordings at the HA01 station. Figure 8 shows a superposition of two spectrograms of sounds 2 and 3 in pygmy blue whale calls recorded in March 2002 and 2007. The structure of the whale call recorded in 2007 was similar to that in
FIG. 8. Superposition of two spectrograms of theme sounds 2 and 3 recorded from different whales in 2002 and 2007. Gavrilov et al.: Pygmy blue whale vocalization
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2002, but the principal frequencies and their harmonics were slightly lower. The frequency of the third harmonic in sound 2 and the higher harmonics of sound 3 decreased by about 1.5 Hz. To obtain more accurate estimates of the frequency change, we measured the maximum frequency of the third harmonic in all calls recorded from these two different whales. This frequency was 72.9 6 0.2 Hz in 2002 and 71.2 6 0.2 Hz in 2007 measured from 25 calls of each animal. However, comparing calls from a small number of animals is not sufficient for making conclusions regarding general trends in vocalization characteristics of the entire whale population. The calls compared could be from whales of different age and size and, consequently, the frequency of their calls could be expected to differ to a certain extent. From several hundreds to thousands of pygmy blue whale calls were recorded every summer-autumn season at the HA01 hydroacoustic station and the Perth Canyon from 2002 to 2010. These data represent hundreds of whales migrating seasonally along the coastal shelf and continental slope off Australia’s South West and, therefore, can be used to assess long-term changes in the vocal characteristics of pygmy blue whales of the eastern Indian Ocean population. Sound 2 of the typical song theme was chosen to analyze the frequency change, as the most persistent and best-detected sound in pygmy blue whale songs. The frequency of the third harmonic was measured, as it was most indicative of absolute change in the call frequency. Because the frequency of this whale sound increases slightly with time during the call, it is necessary to choose a reference point in either the temporal or frequency domain for measuring frequency variations between different calls. We measured the maximum frequency of the third harmonic at the end of whale calls, which was determined from the power spectrum of this harmonic by a 3-dB decrease in the spectral level towards higher frequencies. To reduce the
effect of variations between different animals, the mean value of the maximum frequency was calculated for all calls recorded in each two-week period, if the number of calls was not less than ten. The standard deviation of frequency variations was also calculated. Because the CTBT acoustic data from the HA01 station were available only until the beginning of 2008, we extended the time series using acoustic recordings made at the IMOS acoustic observatory in the Perth Canyon in 2008 – 2010, where many thousands of calls were recorded every season. Moreover, to make sure that the region of whale observation did not significantly affect the call frequency, we also analyzed the whale calls recorded in Perth Canyon in 2005 and at the IMOS acoustic observatory off Portland in Victoria in 2009. The top panel in Fig. 9 shows the number of calls detected fortnightly at the three observational sites and used for measuring the call frequency. The number of calls recorded in the Perth Canyon is an order greater than that at the other two sites, likely because the Perth Canyon is a relatively small geographical area attracting many pygmy blue whales as a regular feeding ground. The bottom panel of Fig. 9 shows the mean value of the maximum frequency measured at the third harmonic of sound 2 in the whale song theme. The error bars in the legend indicate typical standard deviation of the frequency variations observed every two weeks. It is important to note that these variations could be due not only to the vocal variability among individual whales, but also to selective-frequency fading, which results from multipath acoustic propagation and affects the signal power spectrum including its maximum frequency, depending on range and depth of the signal source. A downward trend in the interannual changes of the call frequency is evident from this observation. The total decrease over these years was much larger than the variations during
FIG. 9. The number of whale calls detected fortnightly at the HA01 station of Cape Leeuwin, in Perth Canyon and off Portland that were used to measure the mean value and standard deviation of call frequency (top panel) and the mean value of the maximum frequency of the third harmonic in sound 2 of the whale song theme measured at these three sites in 2002–2010 (bottom panel). Asterisks represent data from the Cape Leeuwin station, circles, the Perth Canyon, and pluses, the Portland IMOS observatory.
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particular seasons. A regression analysis applied to the temporal variations of the fortnightly averaged call frequency showed a decrease rate of approximately 0.35 Hz/year with the standard error of about 0.01 Hz/year (R2 statistics value of approximately 0.95 and t-statistics p-value less than 0.001 at 101 degrees of freedom). A more conservative estimate of possible errors based on the maximum standard deviation of about 0.8 Hz for all fortnightly measurement sets resulted in a 95% confidence interval of approximately 0.35 6 0.06 Hz/ year for the decrease rate. Thus the trend estimation errors were considerably smaller than the measured interannual trend. The decrease rate of 0.35 Hz/year estimated for the third harmonic of sound 2 corresponds to an approximately 0.12 Hz/year decrease rate of the fundamental frequency and is close to a 0.4 Hz/year decrease rate estimated by McDonald et al. (2009) for the third harmonic (from about 65 Hz to 45 Hz) of the tonal sounds produced by blue whales of the northeastern Pacific population. A downward trend in the mean value of the call frequency can be seen even during one year of data collection in the Perth Canyon in 2010, although the observed change is noticeably smaller than the standard deviation of variations. VI. DISCUSSION
The structure and acoustic characteristics of songs and individual calls from pygmy blue whales of the eastern Indian Ocean population were considered in this paper. The longlasting songs are formed by repeating themes of either three or two different quasi-tonal sounds with harmonics spanning the frequency band from about 20 Hz to 100 Hz. The theme repetition period in a three-sound song varies from 180 s to 220 s. The first sound is skipped in a two-sound song, which has the theme repetition period of 90–100 s. These two songs structures and their individual sounds remained generally unchanged over eight years of passive acoustic observations off the western and southern cost of Australia. The second sound in the three-sound theme (first in the two-sound theme) is usually the most intense one. The source level of 179 6 2 dB estimated for this sound from 120 calls did not vary significantly between seven different whales recorded at the HA01 hydroacoustic station over 2002–2006. This estimate of the source level is noticeably higher than the estimate of 174 6 1 dB reported for pygmy blue whales of the southwestern Indian Ocean population observed in 2003–2004 (Samaran et al., 2010). It is not certain yet whether this difference in the source level is due to possible distinctions in average size or vocalization habit of these two populations or the estimate made in the western Indian Ocean was not representative or accurate enough. The source level estimate of 174 dB was obtained only for one animal, using a 2D model for hyperbolic location, which ignored the depth difference of the source and receivers, and assuming a simple spherical spreading model for the transmission loss. Like some other sub-species of blue whales, pygmy blue whales of the eastern Indian Ocean population produce impulsive downsweep sounds of 2–4 s long within the frequency range from about 20 Hz to more than 100 Hz. This type of calls is relatively infrequent and irregular in terms of J. Acoust. Soc. Am., Vol. 130, No. 6, December 2011
occurrence, duration and spectral characteristics. Varying from 168 dB to 176 dB re 1 lPa at 1 m, the source level of these calls is noticeably lower and much less stable than that of the tonal sounds of blue whale songs. The only significant change in the acoustic characteristics of vocalizing pygmy blue whales observed over eight years in Australia was a noticeable decrease of the tonal frequencies in whale songs. The third harmonic of sound 2 in the song theme has decreased by approximately 3 Hz over these years, which corresponds to a 1-Hz decrease of the principal frequency. Moreover, a comparison of individual calls recorded in different years showed that the frequencies of the third sound in the typical song theme have also likely decreased in a similar way. This observation strongly supports the conclusion made by McDonald et al. (2009) regarding a worldwide decline in tonal frequencies of blue whale songs. These authors also considered a number of possible reasons for such change, which included: sexual selection; an increase in body size due to, in particular, the population recovery from whaling; global climate change and ocean acidification resulting in sound speed change; biological interference with other marine mammals; and an impact of man-made noise. None of these reasons look plausible, except an increase in the relative population density and a consequent slight decrease of the call intensity suggested by the authors as the only possible but yet speculative explanation for the frequency decline of blue whale songs. The most significant change of blue whale source level from 188.4 dB in 1963 to 185.3 dB in 2008 was estimated for whales of the northeastern Pacific population. The study presented in this paper did not reveal any noticeable change in the source level of pygmy blue whale calls over eight years of data collection. This should be expected, because errors of source level measurements for whales are certainly larger than 6 1 dB, which includes errors of location and TL prediction. Moreover, the intensity of calls can vary among animals during one season, depending on their size, age and behavioral context. Therefore, to assess general trends in the intensity of blue whale calls, the source level of many animals should be accurately measured over a much longer time period. The probability of long-term trends can be determined only if short-term variations observed within different years are taken into account. There is another hypothesis regarding the decline in call frequency with time that was overlooked in McDonald at al. (2009). The resonance frequency of an air-filled elastic body, e.g., the respiratory system of whales, changes with depth in water. According to Jones et al. (2002), this change can be approximated as f1 =f2 ½ð1 þ d1 =10Þ=ð1 þ d1 =10Þ5=6 and f1 =f2 ½ð1 þ d1 =10Þ=ð1 þ d1 =10Þ for spherical and cylindrical bodies respectively, where f1 and f2 are resonance frequencies at depths d1 and d2 respectively. If the resonance frequency was 24 Hz at 25 m, then it is expected to drop to 23 Hz at 23.3–23.5 m, depending on body shape. This small change in the average depth of blue whale vocalization looks quite realistic in explaining the observed decline of call frequency; however, it is not possible at present to justify this hypothesis and provide a reasonable explanation as to why it may be occurring. Gavrilov et al.: Pygmy blue whale vocalization
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ACKNOWLEDGMENTS
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