Acoustic behavior of melon-headed whales varies on a diel cycle
- 1.3k Downloads
Many terrestrial and marine species have a diel activity pattern, and their acoustic signaling follows their current behavioral state. Whistles and echolocation clicks on long-term recordings produced by melon-headed whales (Peponocephala electra) at Palmyra Atoll indicated that these signals were used selectively during different phases of the day, strengthening the idea of nighttime foraging and daytime resting with afternoon socializing for this species. Spectral features of their echolocation clicks changed from day to night, shifting the median center frequency up. Additionally, click received levels increased with increasing ambient noise during both day and night. Ambient noise over a wide frequency band was on average higher at night. The diel adjustment of click features might be a reaction to acoustic masking caused by these nighttime sounds. Similar adaptations have been documented for numerous taxa in response to noise. Or it could be, unrelated, an increase in biosonar source levels and with it a shift in center frequency to enhance detection distances during foraging at night. Call modifications in intensity, directionality, frequency, and duration according to echolocation task are well established for bats. This finding indicates that melon-headed whales have flexibility in their acoustic behavior, and they collectively and repeatedly adapt their signals from day- to nighttime circumstances.
KeywordsAdaptive acoustic behavior Echolocation Ambient noise Melon-headed whale Diel pattern
Many organisms, from invertebrates to vertebrates, both in marine and terrestrial environments, have diel behavioral activity patterns, often observed with corresponding changes in the acoustic behavior. This has been documented, to name a few, for the dawn chorus of birds, nighttime echolocation of bats, nighttime calls of moths, crepuscular chorus of fish, and dusk calling of frogs (Griffin 1958; Kamimura and Tatsuki 1993; Staicer et al. 1996; Bridges and Dorcas 2000; Širović et al. 2009). A number of cetacean species show diel behavior that may be regulated by an internal circadian clock or may be linked to daily cycles in prey behavior (Klinowska 1986). Diel acoustic behavior has been shown in some baleen whale species using autonomous acoustic monitoring techniques (Au et al. 2000; Wiggins et al. 2005; Oleson et al. 2007; Munger et al. 2008; Matthews et al. 2014). Traditionally, descriptions of diel behavior of many dolphin species were based on daylight visual observations, and nighttime foraging was inferred from evening foraging activity or stomach content analysis (Würsig and Würsig 1979; Norris and Dohl 1980; Amano et al. 1998). Toothed whale echolocation clicks, which generally are used to detect, characterize, and localize a target for spatial orientation or feeding (Au 1993), have been shown to increase in number and repetition rates at night for harbor porpoise (Phocoena phocoena), spinner dolphins (Stenella longirostris), and Risso’s dolphins (Grampus griseus) (Norris et al. 1994; Carlström 2005; Todd et al. 2009; Soldevilla et al. 2010a). Also, spinner dolphin acoustic activity typically is low in the morning hours during resting and increased whistling occurs during socializing in the afternoon (Norris et al. 1994). Two different Pacific white-sided dolphin (Lagenorhynchus obliquidens) click types, possibly from two distinct populations with different foraging strategies, exhibit diel patterns with one type being dominant during daytime hours and the other at night (Soldevilla et al. 2010b).
Most acoustically active species are capable of collectively adapting their signals to optimize communication dependent on their behavior and environment (Bradbury and Vehrencamp 1998). For example, bird populations have been found to adapt song modulation rates in forest versus open-country environments to overcome propagation challenges (Krebs and Davies 1993). Adaptations in the acoustic behavior are often associated with changes in the environment; for example, many echolocating bats shorten their signal duration and increase their bandwidth as they navigate closer to vegetation (e.g., Schaub and Schnitzler 2007). Adaptive acoustic behavior to changes in the soundscape has been a more recent focus, particularly in the context of anthropogenic noise and its impact (e.g., Brumm 2013). Soundscapes are shaped by geophonies (e.g., wind, waves, volcanic eruptions, earthquakes), biophonies (e.g., chorus of birds, stridulation of insects, spawning chorus of fish), and anthropophonies (e.g., vehicle motor noise, seismic surveys, explosions) (Farina 2014). With increased sounds, an acoustic signal may be masked, evoking compensating modifications in the acoustic properties of signals. Most commonly, animals increase their signal amplitude to improve the signal-to-noise ratio and therefore detectability. Initially observed and described for humans as the Lombard response (Lombard 1911), it has since been found in many terrestrial species (e.g., frogs, primates, bats, and songbirds; Sinnott et al. 1975; Schmidt and Joermann 1986; Cynx et al. 1998; Brumm and Todt 2002; Pytte et al. 2003; Brumm 2004; Penna et al. 2005; Tressler and Smotherman 2009). Beyond an increase in amplitude, other signal changes include extending duration (e.g., Penna et al. 2005; Bermudez-Cuamatzin et al. 2011), increasing repetition rate (e.g., Potvin et al. 2011), shifting the dominant frequency to a band unaffected by the noise (e.g., Lopez et al. 1988; Feng et al. 2006; Bermudez-Cuamatzin et al. 2011; Potvin et al. 2011), or a combination of these (e.g., Lopez et al. 1988; Tressler and Smotherman 2009).
Changes in the acoustic behavior in response to noise have also been shown for cetacean species. North Atlantic right whales (Eubalaena glacialis), killer whales (Orcinus orca), and beluga whales (Delphinapterus leucas) adjust the call structure of their tonal signals and pulsed-tone calls in response to natural or anthropogenic noise. Right whales increase their calling amplitude with increasing ambient noise (Parks et al. 2011). In the presence of anthropogenic noise, beluga whales may reduce their calling rate, change the occurrence of specific calls, increase their dominant call frequency (Lesage et al. 1999), and increase the signal amplitude (Scheifele et al. 2005). Killer whales have been shown to respond to vessel noise with an increase in call amplitude (Holt et al. 2009, 2011) and an increase in call duration (Wieland et al. 2010). Low frequency wind noise resulted in an upward shift in call frequency of offshore killer whales (Foote and Nystuen 2008).
Few studies of captive animals have shown adaptations of echolocation clicks in response to noise. A captive beluga whale increased the source level and peak frequency of its echolocation clicks when moved from the quieter San Diego Bay to the noisier Kaneohe Bay, Hawaii (Au et al. 1985). Au (1993) concluded from findings in two studies (Thomas et al. 1988; Thomas and Turl 1990) that false killer whales (Pseudorca crassidens) also shift their frequencies and increase their call amplitudes when confronted with a noisy environment. However, findings in studies with captive animals may not be reflective of what can be expected in field studies when animals may be operating at the limits of their sound production system. In contrast, Cuvier’s beaked whales reduce their overall echolocation click rates in the presence of ship noise (Aguilar Soto et al. 2006).
Melon-headed whales (Peponocephala electra) are regularly observed around Palmyra Atoll. They are pelagic dolphins that occur worldwide in tropical and subtropical oceanic waters (40° N–35° S) (Jefferson et al. 2008; Perryman 2009). They are mostly observed offshore in deep water and are a highly social species with 100–500 animals (up to 2000) per group (Jefferson et al. 2008). Melon-headed whales use daytime hours for resting and socializing, and feed during the night on mesopelagic prey (Brownell Jr. et al. 2009). Whistles of melon-headed whales are described as relatively simple up and down sweeps, as well as sinusoidal signals (Watkins et al. 1997; Frankel and Yin 2010). Echolocation clicks of melon-headed whales recorded during daytime hours have been shown to have species-specific properties allowing them to be classified (Baumann-Pickering et al. 2010).
In this study, we investigated the diel acoustic activity pattern of melon-headed whales from a year-long survey and the animals’ acoustic adaptations in correlation with changes in ambient sound. We tested the hypothesis that melon-headed whale acoustic activity changed with their diel behavioral pattern, comparable to that of spinner dolphins given their shared preferred prey and similar behavioral diel pattern.
Materials and methods
Echolocation clicks were automatically detected within the HARP long-term data using a two-step approach as described in Soldevilla et al. (2008). During the first step, clicks were detected using a frequency energy detector. Spectral frames (1024 FFT, 50 % overlap, Hann window) were assumed to contain echolocation clicks when 12.5 % of the frequency bins between 15 and 85 kHz exceeded a threshold of 10 dB. Individual echolocation clicks were identified within these regions using a Teager energy operator (Kaiser 1990; Kandia and Stylianou 2006) applied to the time-series waveform as described in Roch et al. (2011). The recording sequences with detected clicks were digitally filtered with a 10-pole Butterworth band-pass filter. The low frequency cutoff was set to 5 kHz to minimize the influence of low frequency noise from boats and weather. The high-frequency cutoff was set to 95 kHz. Filtering was done on 800 samples. Spectra of each detected signal were calculated using 2.56 ms of data and a 512-point Hann window centered on the click. A calibrated transfer function was applied to account for the frequency dependent instrument response. Peak frequency was extracted as the frequency with the highest level within each click spectrum. Click received levels were computed from waveform peak-to-peak signal amplitudes and adjusted for the system response at center frequency of each click. The HARP raw data format used 75-s segments, making this a convenient analysis length. To ensure statistical independence of data points, only the first 75-s segment per 20 min was used in further analysis. All clicks within each segment with peak-to-peak received levels less than 130 dB re 1 μPa were discarded to allow only strong clicks well above the noise level in both nighttime as well as daytime situations. Segments with less than 20 clicks detected within a 75-s interval were not included into the analysis. To reduce variability in click data and to find species-specific features, medians over all click features of each 75-s segment were computed. To produce a dataset comparable to the published daytime data (Baumann-Pickering et al. 2010), a second set of medians per segment was calculated omitting clicks with peak frequency less than 20 kHz.
Sunrise and sunset data for Palmyra Atoll were acquired from the U.S. Naval Observatory website (http://aa.usno.navy.mil/data/docs/RS_OneYear.php). Sunrise occurred between 06:33 and 07:06, sunset between 18:29 and 19:01. These differences in sunrise and sunset were not considered substantial, so full hours of the day were pooled in the diel analysis. Hours between 07:00 and 19:00 were defined as daytime. Presence and absence data were calculated for 75-s HARP recording segments to count segments with whistles in each hour of the day using all manually identified acoustic encounters, presented as a histogram. Numbers of clicks per 75-s segment in each hour of the day were extracted from the reduced number of independent segments and presented as boxplot distributions. Two sample t tests with unequal variance were used to evaluate whether or not differences in measurements of click characteristics varied between day and night time echolocation click medians. The validity of the equal variance condition was evaluated through their F-ratios.
For the calculation of ambient noise levels, each 75-s segment within the first 30 min of each hour was, like the click data, filtered between 5 and 95 kHz with a 10-pole Butterworth band-pass filter. Root mean square (RMS) levels were calculated for the quietest segment of each hour when melon-headed whale whistles were present. Median RMS levels were calculated to compare daytime versus nighttime noise levels. The relationship of click peak-to-peak received levels and ambient noise RMS received levels was tested with a linear regression for day- and nighttime segments separately. Noise spectra were computed over the quietest segment using a 2048-point DFT and the Welch algorithm (Welch 1967) with no overlap over one exemplary week. Spectral levels were extracted for each hour at 5, 10, 30, and 50 kHz. Spectral levels of each of these frequencies were normalized to the lowest value within each frequency.
Spectral and temporal characterization of echolocation clicks partitioned by day and night. In each case, characteristics are given for all echolocation clicks, and only those that have peak frequencies (pf) above 20 kHz
Day all clicks n = 390
Night all clicks n-237
Day pf >20 kHz n = 390
Night pf >20 kHz n = 237
Two sample t-test with unequal variance (tested on all clicks)
22.7 (18.3, 29.5)
32.0 (28.5, 39.8)
28.1 (23.4, 39.4)
33.6 (29.7, 40.6)
21.7 (18.0, 25.9)
28.2 (21.5, 33.5)
24.7 (20.7, 28.9)
28.8 (24.0, 33.6)
−3 dB bandwidth
2.7 (2.3, 5.0)
3.5 (2.6, 5.1)
3.9 (2.7, 6.6)
3.9 (3.1, 5.4)
−10 dB bandwidth
16.0 (5.8, 26.1)
19.8 (11.3, 28.0)
22.4 (11.5, 31.2)
22.2 (14.8, 29.2)
240 (19, 330)
270 (211, 370)
256 (205, 370)
279 (220, 377)
Received level (peak-to-peak)
dB re 1 μPa
133 (132, 136)
136 (133, 140)
133 (130, 136)
136 (133, 140)
Click counts per segment
189 (44, 931)
735 (84, 2151)
116 (22, 556)
578 (73, 2028)
Long-term passive acoustic monitoring at Palmyra Atoll revealed diel acoustic behavior of melon-headed whales. Click rates increased in the late afternoon and continued to be high during the night, decreased towards sunrise, and had their lowest values late in the morning and around noon. Echolocation clicks are used by the animals to detect, characterize, and localize a target for spatial orientation or feeding (Au 1993). There is evidence for particularly high rates of echolocation during periods of foraging (e.g., Van Parijs and Corkeron 2001; Nowacek 2005). Detections of segments with melon-headed whale whistles had a strong peak in the afternoon until shortly before sunset, a steep drop-off at the beginning of the night and the lowest detections before sunrise. Whistles have been shown to be important for socializing (Herman and Tavolga 1980; Norris et al. 1994; Janik and Slater 1998; Janik 2000; Lammers et al. 2006). This comparison indicated that whistles and clicks were used selectively during different phases of the day. Variability in hourly detection rates of both whistles and clicks were likely a result of changing animal densities within the detection range of the recorder as well as variability in their behavior.
Melon-headed whales have a diel migratory and behavioral pattern at Palmyra Atoll (Brownell et al. 2009). They rest and socialize along the reef edge near the atoll over shallower water (70 m minimum sighted depth, Fig. 1b) in the morning and early afternoon, with active whistling and low click rates. In the early evening, they move towards deep water to feed on mesopelagic prey (Brownell et al. 2009) and the vocalization pattern reverses with high click rates and less whistling. This is consistent with behavior exhibited by other delphinid species that prey on vertical migrators from the mesopelagic boundary layer during the night (Weilgart and Whitehead 1990; Norris et al. 1994; Nowacek 2005; Benoit-Bird and Au 2009). High rates of nighttime echolocation for melon-headed whales are likely related to diel patterns in prey migration similar to the echolocation behavior of spinner dolphins (Benoit-Bird and Au 2003; Benoit-Bird et al. 2004). Mesopelagic biomass communities undergo a vertical and horizontal migration from deep waters during the day to surface waters at night, with a peak density near the surface around midnight (Enright and Hamner 1967). The diel whistle and click rate pattern of melon-headed whales at Palmyra Atoll supports the hypothesis of nighttime foraging and daytime resting and socializing for this species. Echolocating bats show the most closely related acoustic behavior in the terrestrial environment. They use echolocation at night to forage (Griffin 1958) but also produce social calls under certain circumstances, some of which are related to a diel or seasonal pattern. These social calls are known to occur during mating, to communicate with animals in the roost, to recruit conspecifics, or to defend foraging patches (Bradbury 1977; Rydell 1986; Wilkinson and Wenrick Boughman 1998; Davidson and Wilkinson 2004; Chaverri et al. 2010; Arnold and Wilkinson 2011).
Median values of echolocation click parameters reported here for melon-headed whales are not directly comparable to values derived exclusively from assumed on-axis click measurements. All values were calculated over on- as well as off-axis clicks within a 75-s time segment, and likely, only a small minority of these clicks was on-axis. While on-axis clicks have energy beyond the 100-kHz bandwidth of the HARP, towed array recordings in close vicinity to melon-headed whales with sampling frequency up to 480 kHz show only a 3-kHz increase in median center frequency when grouping more than 50 random on- or off-axis clicks (Baumann-Pickering et al. 2010). This is likely an effect of a dominance of off-axis click in the average spectra and demonstrates its stability across sampling schemes.
Spectral features of melon-headed whale clicks received at the HARP were different from day to night with the entire broadband energy shifted to higher frequency and stronger amplitude at night. The energy started at about 15 kHz during the day and at about 20 kHz during the night. Median center frequency was at 22 kHz during the day at 28 kHz during the night. The higher frequency and stronger amplitude of the recorded clicks could be a result of (1) animals being closer to the HARP and pointing their echolocation beam towards the recorder during nighttime periods of foraging or (2) effort to improve target detectability through an increase of biosonar source level and changes in other click characteristics, such as frequency, are a by-product.
With melon-headed whales moving offshore and to greater depth at night to prey on the mesopelagic boundary layer, one might assume the animals to be closer to the HARP location and more likely to point their echolocation beam downwards towards the hydrophone when possibly diving deeper than during the day. A movement towards the HARP would increase the received level and center frequency due to reduced absorption and geometric spreading loss. Furthermore, directing the echolocation beam downwards during foraging would result in more on-axis clicks, which tend to have a higher received level and higher center frequency.
A number of factors weaken this most parsimonious explanation. Daytime sightings of melon-headed whales were in water depths that would place the animals typically within 300–500 m of the HARPs bathymetry line. Morning sightings were in depths ranging from 70 to 300 m, afternoon sightings in 300–400 m, and one evening sighting in 1300 m. While no night time observations were possible, the tendency towards deeper water as the day moved on coupled with a diet of mesopelagic prey would suggest that the animals were likely offshore of the HARPs’ bathymetry line during the night. The southern reef edge extends over many nautical miles. There is no indication for the probability of echolocating melon-headed whales to be closer to the HARP during the night than during the day.
Furthermore, daytime array recordings (Baumann-Pickering et al. 2010) from groups of up to 1000 animals were made at distances varying from adjacent to the hydrophone to ~2000 m away. The interest of melon-headed whales in these boat and towed array surveys resulted in many strong click trains that were oriented towards the array hydrophone. The median center frequency of these encounters was 31 kHz. The closest the animals were observed to the HARP during a daytime visual encounter was a perpendicular surface distance of about 500 m with a resulting diagonal distance to depth of 800 m. Center frequencies recorded on the HARP during that visual encounter were reported as 30 kHz. Daytime HARP-recorded values presented in this article using the method in Baumann-Pickering et al. (2010), excluding clicks with peak frequencies below 20 kHz, were a median of 29 kHz. This indicates that the change to higher amplitude and higher frequency at night are unlikely a result of the animals being closer to the HARP or pointing their echolocation beam more towards it.
During foraging at night, an echolocation signal with a higher source level should increase prey detection by either increasing the detection range for prey or overcoming, in this particular situation, the increased ambient noise at Palmyra Atoll, or possibly a combination of both. An increased biosonar source level would improve signal detectability based on a higher signal-to-noise ratio. Strong upward frequency shifts together with higher level echolocation clicks were reported for captive beluga and false killer whales in response to noise (Au et al. 1985; Thomas et al. 1988; Thomas and Turl 1990; Turl et al. 1991). Captive bottlenose dolphins are capable of adjusting their echolocation click amplitude yet have more difficulties in precise modification of the frequency structure of their clicks (Moore and Pawloski 1990). The positive relationship of click received levels and ambient noise levels suggests that at least some of the observed amplitude adjustment at night might be a Lombard response (Lombard 1911), and the alteration of other click features, such as higher center frequency, may be a result of the production of higher amplitude clicks.
Bats have been shown to use their echolocation signals in a highly adaptive way depending on the current task and in reaction to changes in the environment. Signal parameters, such as frequency, duration, intensity, and beamwidth, are being adjusted to shape a signal appropriate for the situation (Jakobsen et al. 2013). It is well established that bats adapt the time-frequency structure of their echolocation pulses to the acoustic limits of their habitat and foraging circumstances, which results in the concept of bat guilds (e.g., Neuweiler 1989; Schnitzler et al. 2003; Denzinger and Schnitzler 2013). More recently, levels of intensity and changes in beam width have been investigated. Bats are capable of adjusting their echolocation pulse intensity to overcome frequency dependent attenuation resulting in similar detection ranges for prey across species (Surlykke and Kalko 2008). Additionally, bats are not only adapting the time-frequency components of their signals as they search and approach prey (e.g., Melcón et al. 2007), but they also adjust their signal strength and beamwidth to suit the task (e.g., Koblitz et al. 2011).
A long-term, collective diel adaptation in free-ranging odontocetes’ biosonar source levels and spectral content either as an adjustment for larger detection distances of prey or to overcome diel changes in ambient sound was discussed. The results show that in the field, just as in captivity, the structure of echolocation clicks is not a rigid entity but changes in response to environmental or situational stimuli.
Future research should test further in the field, how echolocation click structures are modified as a result of increased detection range, as animals change their focal behavior from navigation to foraging, and in the presence of natural or anthropogenic noise. In relation to adjustments due to noise, it seems relevant at what point masking is becoming a disadvantage for equal foraging success and what effect additional energy expenditure due to prolonged foraging has on the ecology of echolocating species.
The authors would like to thank two anonymous reviewers and the associate editor, Vincent M. Janik, for their insightful comments and discussion. The authors also thank Chief of Naval Operations N45, Frank Stone and Ernie Young, and Naval Postgraduate School, Curt Collins and John Joseph for support. We thank M. A. McDonald for his helpful critique on versions of this manuscript. We thank X. Alvarez Mico, Y. Barkley, G. S. Campbell, M. Chitre, C. Garsha, E. Roth, N. Rubio, P. J. Seekings, M. Soldevilla, C. Speed, E. Taylor, and K. P. Yeo, for fieldwork, gear, and analysis assistance. Successful fieldwork was possible with the cooperative work of staff of The Nature Conservancy, the Palmyra Atoll Research Consortium, and U. S. Fish and Wildlife Service.
This study was carried out in compliance with local regulations. Fieldwork was conducted under the United States Fish and Wildlife Service Special Use Permit No. 12533 and National Marine Fisheries Service Permit 727-1915.
Conflict of interest
The authors declare that they have no competing interests.
- Baumann-Pickering S, Wiggins SM, Hildebrand JA, Roch MA, Schnitzler H-U (2010) Discriminating features of echolocation clicks of melon-headed whales (Peponocephala electra), bottlenose dolphins (Tursiops truncatus), and Gray’s spinner dolphins (Stenella longirostris longirostris). J Acoust Soc Am 128:2212–2224CrossRefPubMedGoogle Scholar
- Benoit-Bird KJ, Au WWL (2003) Prey dynamics affect foraging by a pelagic predator (Stenella longirostris) over a range of spatial and temporal scales. Behav Ecol Sociobiol 53:364–373Google Scholar
- Bradbury JW, Vehrencamp SL (1998) Principles of animal communication. Sinauer Associates, Inc., SunderlandGoogle Scholar
- Griffin DR (1958) Listening in the dark: the acoustic orientation of bats and men. Yale University Press, New HavenGoogle Scholar
- Herman LM, Tavolga W (1980) The communications systems of cetaceans. In: Herman LM (ed) Cetacean behavior: mechanisms and function. Wiley-Interscience, New York, pp 149–209Google Scholar
- Jefferson TA, Webber MA, Pitman RL (2008) Marine mammals of the world—a comprehensive guide to their identification. Elsevier, LondonGoogle Scholar
- Kaiser JF (1990) On a simple algorithm to calculate the “energy” of a signal. In: IEEE ICASSP, Albuquerque, NM., pp 381–384Google Scholar
- Klinowska M (1986) Diurnal rhythms in cetacea: a review. Rep Int Whal Comm (Spec Issue) 8:75–88Google Scholar
- Krebs JR, Davies NB (1993) An introduction to behavioral ecology, 3rd edn. Blackwell Publishing, OxfordGoogle Scholar
- Lombard E (1911) Le signe de l’élévation de la voix. Ann Mal Oreille Larynx 37:101–119Google Scholar
- Munger LM, Wiggins SM, Moore SE, Hildebrand JA (2008) North Pacific right whale (Eubalaena japonica) seasonal and diel calling patterns from long-term acoustic recordings in the southeastern Bering Sea, 2000–2006. Mar Mammal Sci 24:795–814Google Scholar
- Norris KS, Dohl TP (1980) Behavior of the Hawaiian USA spinner dolphin Stenella longirostris. Fish Bull 77:821–850Google Scholar
- Norris KS, Wursig B, Wells RS, Wursig M (1994) The Hawaiian spinner dolphin. University of California Press, BerkeleyGoogle Scholar
- Staicer C, Spector D, Horn A (1996) The dawn chorus and other diel patterns in acoustic signaling. In: Kroodsma D, Miller E (eds) Ecology and evolution of acoustic communication in birds. Cornell University Press, IthacaGoogle Scholar
- Watkins WA, Daher MA, Samuels A, Gannon DP (1997) Observations of Peponocephala electra, the melon-headed whale, in the southeastern Caribbean. Caribb J Sci 33:34–40Google Scholar
- Welch PD (1967) The use of fast Fourier transform for the estimation of power spectra: a method based on a time averaging over short, modified periodograms. IEEE T Acoust Speech 15:70–73Google Scholar
- Wiggins SM, Hildebrand JA (2007) High-frequency acoustic recording package (HARP) for broad-band, long-term marine mammal monitoring. International Symposium on Underwater Technology 2007 and International Workshop on Scientific Use of Submarine Cables & Related Technologies, IEEE., pp 551–557Google Scholar
- Würsig B, Würsig M (1979) Behavior and ecology of the dusky dolphin, Lagenorhynchus obscurus, in the south Atlantic. Fish B-Noaa 77:871–890Google Scholar
Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.