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Mapping cetacean sounds using a passive acoustic
monitoring system towed by a Wave Glider on the
Southwestern Atlantic Ocean
Lis Bittencourta, William Soares-Filhob, Isabela Maria Seabra de Limaa,Sudhir Paic, Jose Lailson-Brito Jr.a, Leonardo Martins Barreirab, Alexandre
Freitas Azevedoa, Luiz Alexandre A. Guerrad
aLaboratorio de Mamıferos Aquaticos e Bioindicadores (MAQUA), Universidade doEstado do Rio de Janeiro (UERJ), Rio de Janeiro, RJ, Brazil
bInstituto de Pesquisas da Marinha (IPqM), Rio de Janeiro, RJ, BrazilcSchlumberger Robotics Services, Houston, TX, USA
dPETROBRAS/CENPES, Av. Horacio Macedo, 950 - Cidade Universitaria, Rio deJaneiro, RJ, 21941-915, Brazil
Abstract
Passive acoustic monitoring techniques have been shown to be useful to mon-
itor marine fauna efficiently since they do not depend on good visibility
and weather conditions. An unmanned surface vehicle, type Wave Glider,
equipped with an autonomous recording system collected acoustic data on the
Brazilian offshore waters of the Southwestern Atlantic Ocean between 6–25
February 2016. Nearly continuous data was provided during this period (light
and dark hours) for the 377 km traveled. There were 165184 high-frequency
detections in 31 events, being 1839 whistles, 389 burst-pulse sounds and
162956 echolocation clicks. Low-frequency detections summed up to 705, all
tonal signals, in 5 events. Although high-frequency detections occurred at all
hours of the day, the majority was at dark hours. Low-frequency detections
Email address: laguerra@petrobras.com.br (Luiz Alexandre A. Guerra)
Preprint submitted to Deep-Sea Research Part I May 12, 2018
did not occur at all hours of the day, but the majority also occurred during
dark hours. High-frequency and low-frequency detections represented 26%
and 3% of the recording hours, respectively. Duration, the number of emis-
sions, and ocean depth varied among acoustic events. Events composed by
high-frequency sounds were separated into seven different groups, probably
different species. One of the events presented whistles that were previously
recorded in the Rio de Janeiro Coast for Steno bredanensis (Rough-toothed
dolphins). All of the low-frequency events were composed of a type of Bal-
aenoptera brydei (Bryde’s whales) call. This type of data collection is un-
precedented for the Southwestern Atlantic Ocean and highlighted the use of
the sampled area by delphinids on different days and different times of the
day, including the dark hours.
Keywords: Passive Acoustic Monitoring, Cetaceans, Unmanned Surface
Vehicle, Wave Glider, South Atlantic Ocean, Brazil, Upwelling
1. Introduction1
The continental shelf edge is a productive ocean environment, and the oc-2
currence of large marine vertebrates is often associated with oceanographic3
features (Baumann-Pickering et al., 2016). Most studies focused on assessing4
diversity are performed with ship surveys, relying mostly on visual observa-5
tion data and thus restricted to animals that can be seen from the sur-6
face. Passive acoustic monitoring (PAM) can bring reliable information on7
marine vertebrates movements because many aquatic animals have species-8
specific sound emissions and can be acoustically identified (Klinck et al.,9
2012; Luczkovich et al., 2008; Oswald et al., 2007). Therefore, PAM tech-10
2
niques have been shown efficient to find and monitor marine fauna, allowing11
scientists to identify patterns of seasonal variation and habitat use in distinct12
environments (Baumgartner and Fratantoni, 2008; Bittencourt et al., 2016;13
Lammers et al., 2008; Locascio, 2010; Luczkovich et al., 2008; Moore et al.,14
2006; Wall et al., 2013; Wiggins et al., 2013; Wilson et al., 2013).15
Autonomous data samplers are capable of performing monitorings for16
long periods at a low cost and are non-invasive to the environment, allow-17
ing data collection even during rough weather conditions at remote locations18
worldwide. These recorders can either be fixed, moored to the marine floor19
or ocean buoys (Sousa-Lima et al., 2013; Van Parijs et al., 2009), or mo-20
bile, coupled to autonomous vehicles, like ocean gliders (Baumgartner and21
Fratantoni, 2008; Wall et al., 2012). While submarine buoyancy-driven glid-22
ers can trace vertical and horizontal paths on the water column collecting23
data, Wave Gliders harness energy from waves to endure long cruises trans-24
porting sensors close to the surface (Rudnick et al., 2004; Hine et al., 2009).25
Traditionally, gliders have been deployed to collect a variety of chemical, bi-26
ological and physical oceanographic variables (Villareal and Wilson, 2014;27
Martin et al., 2009). More recently, studies with gliders started collecting28
acoustical data (Baumgartner and Fratantoni, 2008; Wall et al., 2017, 2013;29
Bingham et al., 2012), opening a window to the soundscape of vast oceanic30
areas.31
Data regarding marine vertebrates’ occurrence in the South Atlantic Ocean32
is still scarce. Previous studies have identified several species of whales and33
dolphins in the waters covering the continental shelf and the continental slope34
of South America (Di Tullio et al., 2016a; Zerbini, 2004), but efforts are con-35
3
centrated on visual surveys or stranding data. In the present study, we used36
an unmanned surface vehicle coupled to a passive acoustic monitoring system37
to sample offshore waters in a region of the Brazilian coast well known for38
upwelling occurrence, searching for possible patterns of acoustical presence39
of cetaceans.40
2. Materials and Methods41
Acoustic data collection occurred through the deployment of an unmanned42
surface vehicle type Wave Glider model SV2 on the Brazilian offshore wa-43
ters of the southwestern Atlantic during the austral summer of 2016. The44
Wave Glider used for this study consists of a submerged glider with wings45
connected by a 7-m umbilical to a float element that remains at the surface.46
The Wave Glider converts wave motion into forwarding thrust, while solar47
panels charge onboard batteries that power the vehicle’s command and con-48
trol system, communications and sensors (Hine et al., 2009; Carragher et al.,49
2013).50
The recording system was composed of a Reson/Teledyne TC4014-5 hy-51
drophone (-180 dB re 1V/µPa, 15 Hz–480 kHz) and a SAIL Decimus R©digital52
acquisition and processing system (sampling rate of 50 kHz in 16 bits, with53
26 dB gain) housed in a tow-fish attached to the glider by a 15-m cable54
assembly with floats and weights fitted to its length (Figure 1).55
The Wave Glider traveled a distance of 377 km between 6–25 February,56
performing constant and uninterrupted recordings, generating 24 one-hour57
files per day. The only two occasions in which a whole 24-hour period was58
not sampled were on 6 February, on which nine hours were sampled because59
4
the equipment deployment occurred in the middle of the day; and on 1260
February, on which there was an equipment failure, and recordings were61
restricted to nine non-consecutive hours.62
The local depths were obtained from GEBCO-2014 Grid, available at63
http://www.gebco.net (Weatherall et al., 2015).64
Sound analyses were performed in Raven 1.5 (Program, 2011). Five de-65
tectors were employed to look for signals of biological origin in two differ-66
ent frequency scales (Table 1). Frequency and duration parameters used67
in each detector configuration were chosen based on literature available on68
marine fauna sound signals. Detectors with spectrograms of 512-point Han-69
ning windows and 50% overlap were used to find tonal and pulsed sounds70
above 2 kHz, which presented characteristic frequencies and durations of sig-71
nals produced by delphinids. Recordings were decimated from 50 kHz to72
6 kHz sampling rate with tuneR package (Krey et al., 2011) from R soft-73
ware so that low frequency sounds produced by whales and fishes could be74
found. For these sounds, we used detectors in Raven 1.5 with spectrograms75
of 512-point Hanning window and 75% overlap. Although each detector had76
different frequency and duration parameters, signal-to-noise ratio above 5 dB77
was maintained for all five detectors.78
All the detections were inspected by two experienced observers (LB and79
IMSL) and classified as positive or negative. Detection was considered neg-80
ative when it was identified as being a signal of non-biological origin (e.g.,81
glider generated noise, shipping generated noise) and positive when it could82
be identified as a signal of biological origin. The positive detections were then83
classified according to the signals characteristics: tonal signals, burst-pulsed84
5
sounds, echolocation click as shown in Figure 2. High-frequency tonal signals85
were referred to as whistles. A single detection event may sometimes include86
more than one type of sound, and in these cases, all sounds were counted.87
Consecutive detections with a time interval shorter than one hour were con-88
sidered as belonging to the same detection event, meaning an encounter with89
a group of animals or an encounter with single vocalizing animals. In case90
only one vocalization was detected and separated by more than one hour91
from others, this detection was accounted for in the number of total detec-92
tions but not considered as an individual detection event. It is unlikely that a93
group of delphinids would produce only a single sound emission of any kind,94
indicating that it belonged to another event in which the group of delphinid95
was too far from the glider.96
Detection events were quantified and mapped to obtain the spatial dis-97
tribution of encounters with animals in the sampling area. Temporal distri-98
bution of detection events was also observed by quantifying the number of99
detections per hour and per day. To investigate if the number of detections100
differed through different hours of the day, a Mann-Whitney U Test was used101
to compare the number of whistles, burst-pulses and echolocation clicks be-102
tween light hours and dark hours, after verifying data distribution was not103
normal.104
Of the detected signals, we analyzed the whistles with clear and strong105
contours (Oswald et al., 2004) that did not surpass the superior frequency106
limit of the recording system and that did not overlap with other signals.107
Seven acoustic parameters were extracted from tonal signals, as follow: initial108
frequency (IF), ending frequency (EF), minimum frequency (MinF), maxi-109
6
mum frequency (MaxF), delta frequency (DF), duration (DUR), number of110
inflection points (INF).111
We used the principal component analysis (PCA) to estimate the possible112
number of species recorded in the area. This analysis finds the combination113
of acoustic variables that is responsible for as much variation as possible114
(Quinn and Keough, 2002). The factors with the highest eigenvalues were115
considered to be the ones responsible for most of the variations. The corre-116
lations between each variable and the main factors of the PCA were used to117
define which of these variables were the most important. The main compo-118
nents were then used in place of the original acoustic variables in a posterior119
discriminant function analysis (DFA) so that the assumption of homoscedas-120
ticity of the DFA could be met (Quinn and Keough, 2002). The means of121
the canonical variables of the centroids of each event in relation to the two122
main roots of the DFA was plotted. The position of each centroid relative to123
each other and the roots were used to define the estimated number of species124
recorded.125
Also, an effort to identify the species, or at least the taxa, through visual126
inspection of detected signals was performed. Good quality signals were127
selected and had their contour visually compared to the bibliography and to128
the available delphinid signals in the MAQUA sound database.129
3. Results130
3.1. Temporal Distribution and Mapping131
In total, there were 165184 high-frequency detections, of which 165164132
were in detection events, and 20 were in isolated occurrences. Echolocation133
7
clicks were the most common high-frequency sound, with 162956 detections,134
followed by 1839 whistles and 389 burst-pulsed sounds. Low-frequency detec-135
tions summed up to 705, being all tonal signals. High-frequency detections136
occurred on all days of the sampling period, representing 26% of all record-137
ing hours (Fig. 3). In contrast, low-frequency detections occurred on five138
days of the sampling period, representing 3% of all recording hours (Fig. 3).139
High-frequency detections occurred in all hours of the day at least once, but140
the majority of detections occurred during dark hours with peak detection141
time being 04:00 am (Fig. 4). Low-frequency detections did not occur in all142
hours of the day, but the majority of detections also occurred during dark143
hours, possibly biased by a large detection peak at 02:00 am (Fig. 4).144
There were 31 high-frequency detection events (HF1 to HF31), which145
lasted from one up to eleven hours (Table 2). The composition of sound146
types varied among detection events. There were events composed solely of147
echolocation clicks and events composed solely of whistles, but both were of148
rare occurrence. Events composed of multiple sound types were the most149
common. The number of echolocation clicks did not differ between light150
hours and dark hours events (Mann-Whitney U, p > 0.05), but there was a151
difference for whistles (Mann-Whitney U, z = −2.09, p = 0.03) and burst-152
pulses (Mann-Whitney U, z = −2.49, p = 0.01), which were more numerous153
during dark hours.154
Mapping of detection events showed that delphinid encounters occurred155
across the entire sampling area (Fig. 5). Because the Wave Glider moved156
constantly, longer encounters covered larger distances.157
There were 5 low-frequency detection events (LF1 to LF5), which lasted158
8
from one up to three hours (Table 3), with only tonal signals of the same type159
occurring. Less frequent than high-frequency events, low-frequency events160
covered smaller areas as shown on the map in Figure 6.161
3.2. Species Identification162
The first three components of the PCA presented the highest eigenvalues163
and were responsible for 80.4% of the variation found in the data. The164
first component presented 41.7% of the total variance and the second, 19.9%165
of the variance. The frequency variables, especially maximum frequency,166
ending frequency and minimum frequency presented high correlations (> 0.7)167
with the first component. The number of inflection points presented high168
correlation, while delta frequency, minimum frequency, and duration had a169
moderate correlation (between 0.4 and 0.6) with the second component.170
The PCA plot of the events shows that there is overlap among several171
events while some do not mix. That is the case of HF5 and HF11 that are172
apart between themselves and from most of the other events (Figure 7). The173
plot of DFA centroids shows that events were separated into seven different174
groups, probably seven different species (Figure 8). Although the centroids175
of HF5, HF11 and HF12 were separated by both roots, the remaining events176
were grouped, which means that they share similar whistle characteristics177
and could be recordings from the same delphinid species. Examples of this178
are the group formed by HF7 and HF26, and the one formed by HF31, HF4,179
HF1, and HF21.180
The whistles from one of the detection events could be identified as part181
of the acoustic repertoire from rough-toothed dolphins, Steno bredanensis182
(Fig. 9). The whistle contour types registered in this study had positive183
9
matches with whistles found both in the literature and in the MAQUA sound184
database.185
All low-frequency sounds were identified as being a type of Brydes whale186
(Balaenoptera brydei) call (Fig. 10). The calls were all descendent in fre-187
quency, with: mean minimum frequency of 71.2 ± 8.7 Hz; mean maximum188
frequency of 182.0 ± 11.8 Hz; mean delta frequency of 110.8 ± 14.2 Hz; and189
mean duration of 442.8 ± 115.5 ms. The calls occurred in bouts of two or190
three, with bouts usually separated by two seconds on average, repeated191
during approximately one hour.192
4. Discussion193
Our results demonstrated that delphinid species used the studied area194
daily during the sampling period. Since recordings were continuous, except195
for two system failure occasions, the observed temporal distribution is free of196
recording cycle effect (Riera et al., 2013). Despite the fact that previous stud-197
ies had already identified the presence of delphinid species in the study area198
using visual observer methods (Di Tullio et al., 2016a), the higher number of199
delphinid acoustic detections during dark hours in this study highlights the200
importance of using PAM to assess cetacean occurrence. This methodology201
can be used independent of good light and weather conditions, which are202
necessary for visual surveys.203
The number of hours and sound emissions found in each detection event204
varied and this could be either due to delphinid group size, to the distance205
in which the animals were to the Wave Glider, or even to different acoustic206
behavior from different species. Events that lasted longer and presented a207
10
higher number of sound emissions could be composed by larger groups of208
delphinids and could also be involved in higher activity rates (dos Santos209
et al., 2005). Some of the detection events grouped together in statistical210
analysis not only have similar whistle characteristics but also occurred during211
similar times of the day, such as events HF8 and HF19. Temporal patterns212
of vocalization behavior can differ among odontocetes, with certain species213
producing more sound emissions during the night while others produce more214
during the day (Baumann-Pickering et al., 2016). Although the number215
of detected echolocation clicks did not differ between light and dark hour216
events, the number of detected whistles and burst-pulses did, corroborating217
that events from different hours of the day could be of different species.218
Habitat partitioning among different species is known to occur in these219
waters (Di Tullio et al., 2016b; Moreno et al., 2005), and now nocturnal data220
of cetacean presence can be added to this knowledge. It is noteworthy that221
the Wave Glider covered a broad range of depths while navigating through222
areas possibly occupied by distinct species which can show a preference for223
different depths and slope variations (Ballance et al., 2006; Dalla Rosa et al.,224
2012; De Stephanis et al., 2008). The delphinid encounters occurred across225
all depths, but no detection event covered an area in which local depth varied226
more than 400 m, suggesting that each registered group could have preferred227
depth association.228
Previous studies have shown that oceanographic features can influence229
the cetacean distribution (Ballance et al., 2006; Tynan et al., 2005), and230
that feeding habits and prey distribution are major components of habitat231
partitioning (Canadas et al., 2002; Friedlaender et al., 2006; Hastie et al.,232
11
2004).233
It is known that oceanographic features can influence cetacean distri-234
bution (Ballance et al., 2006; Tynan et al., 2005). Feeding habits and prey235
distribution are major components of habitat partitioning of cetacean species236
in a given area (Canadas et al., 2002; Friedlaender et al., 2006; Hastie et al.,237
2004). The occurrence of upwelling characterizes the region in the vicinities238
of the Cape Frio (23◦S, 42◦W) where relatively cold waters, rich in nutrients,239
surface creating a high biological productivity region (Valentin, 1984; Costa240
and Fernandes, 1993; Matsuura, 1996). The change of coastline orientation241
from north-south to east-west and the proximity of the 100-m isobath are242
favorable topographic conditions for the coastal upwelling next to the Cape243
Frio (Rodrigues and Lorenzzetti, 2001), but the primary process is the wind-244
driven Ekman transport due to persistent E-NE winds that prevail in spring245
and summer in the region (Emılsson, 1961; Ikeda et al., 1974; Castro and Mi-246
randa, 1998). Other mechanisms work to rise cold waters offshore the Cape247
Frio, like the passage of cyclonic eddies and meanders of the Brazil Current248
(Campos et al., 2000; Castelao et al., 2004) and vertical transport driven by249
the wind stress curl (Castelao and Barth, 2006).250
Upwelling regions are highly productive and aggregate diverse marine251
fauna, attracting top marine predators (Croll et al., 2005; Tynan et al., 2005).252
Since the Wave Glider passed through an area closely related to an upwelling253
system in the Southwestern Atlantic Ocean, it is possible that the great254
abundance of delphinid detections is due to prey concentration associated255
with nutrient-rich waters.256
Confirmation of species identification through whistles contour was pos-257
12
sible only for one event. Few studies characterized whistles of the species258
found in the Southwestern Atlantic Ocean and most of these used record-259
ings from coastal areas (de Andrade et al., 2015; Azevedo et al., 2010, 2007;260
Lima et al., 2012). Another difficulty is the possibility that more than one261
species has been recorded in the same detection event. Thus the presence of262
many whistle types with varying characteristics made the exclusion of some263
species of varied whistle repertoire impossible. Mixed-species associations264
among delphinids are common in several areas and present a challenge to265
species classification and identification through acoustic methods (Oswald266
et al., 2003). More bioacoustics studies focusing on acoustic repertoire char-267
acterization are necessary to fill the data gap on oceanic waters from the268
South Atlantic.269
The HF5 was the only event in which species identification was possible.270
The whistles from Rough-toothed dolphins, Steno bredanensis, were com-271
pared to a previous characterization of the species’ whistle repertoire in the272
coastal region of the Rio de Janeiro State Coast, adjacent to the Guanabara273
Bay (Lima et al., 2012). We found contour similarities between whistles274
from the database and the present study. The whistles were in most part275
differentiated from other delphinid species both in frequency and duration276
(Lima et al., 2016). Furthermore, in the Southwestern Atlantic Ocean rough-277
toothed dolphins are known to occur both in coastal waters (Lima et al., 2016,278
2012) and offshore waters (Wedekin et al., 2014), and the record from the279
present study adds information about the area of occurrence of this species.280
Despite species identification having been restricted, the acoustic param-281
eters extracted from whistles presented significant variations and no over-282
13
lapping among some events, which means that the sampled area was used283
by at least seven delphinid species. Previous studies have shown that whis-284
tle repertoires have species-specific characteristics that result in interspecific285
differences (Lima et al., 2016; Oswald et al., 2007; Steiner, 1981). Therefore,286
highest differences among whistle variables of different events in the present287
study may be related to the recordings of different species. The lowest dif-288
ferences registered among whistles of some events may reflect intraspecific289
variation, which can be influenced by the social context and environmental290
factors at the time in which each group was recorded (Azevedo et al., 2010;291
Bonato et al., 2015; Lopez, 2011; May-Collado, 2013). However, it is likely292
that one species has been recorded on more than one event, so this could293
account for some of the overlap observed among events. Also, some degree294
of overlap among whistles of different species is to be expected, as shown in295
previous studies of interspecific comparisons (Oswald et al., 2007, 2003).296
Considering that the PAM system was towed close to the surface, it is pos-297
sible that this has restricted the system’s capacity of registering deep-diving298
animals such as beaked whales and sperm whales (Physeter microcephalus).299
Although the sample rate employed in this study is not adequate to record300
beaked whale signals since their fundamental frequency is usually higher than301
100 kHz (Baumann-Pickering et al., 2014; Zimmer et al., 2008), sperm whale302
clicks, otherwise, fall within the recording system frequency range (Antunes303
et al., 2011; Rendell and Whitehead, 2005), and the species has been sighted304
in the area in previous studies (Di Tullio et al., 2016a; Zerbini, 2004). It305
is possible that either the sound detectors were not adequate to find sperm306
whale clicks, or that ecological factors influenced their absence.307
14
All calls produced by Brydes whales in the present study were of the same308
type and identified as a call first described in the eastern tropical Pacific ocean309
(Oleson et al., 2003), also registered in the Gulf of Mexico (Sirovic et al.,310
2014), indicating that this call type might be shared across different Brydes311
whale populations. During the austral summer, Brydes whales occur close312
to the southeastern coast of Brazil (Zerbini et al., 1997), thus, considering313
the sampling season, no baleen whale except for Brydes whale was expected314
to be recorded. Although it is possible that some unidentified signals were315
produced by minke whales, known for their mechanic sounding vocalizations316
(Gedamke et al., 2001; Rankin and Barlow, 2005), it is also possible that317
these signals are undescribed vocalizations produced by Brydes whales.318
Furthermore, data from PAM coupled with unmanned vehicle technology319
is unprecedented for the Southwestern Atlantic Ocean. This study was con-320
ducted through 20 days, and it produced large volumes of data, generating321
evidence that several species of delphinids use the area. The high number of322
detected sound emissions on some events also hints at the presence of large323
groups of delphinids engaging on high activity rates, indicating an abundant324
and diverse community of dolphins on the outer continental shelf and slope325
of the Southwestern Atlantic Ocean during the summer. Further research326
covering acoustic characterization and behavior of cetacean species, season-327
ality of habitat use and relationship with oceanographic features should be328
conducted to increase knowledge regarding this habitat.329
15
5. Acknowledgements330
This work was supported by PETROBRAS and the Brazilian Oil Reg-331
ulatory Agency (ANP), within the project PT-128.01.12041 - “New Tech-332
nologies and Innovations in Sensors and Metocean Sampling”. The acous-333
tic survey was executed in a partnership of PETROBRAS/CENPES, West-334
ernGeco/LROG, and Brazilian Navy/IPqM. Liquid Robotics Oil and Gas335
(LROG), previously a joint venture between Liquid Robotics and Schlum-336
berger, became wholly owned by Schlumberger on August 29, 2016, and has337
been renamed Schlumberger Robotics Services. We would like to acknowl-338
edge Fabian Van Der Werth and Levent Alkan, former employees of LROG,339
for the system setup and field operations. The authors would like to thank340
IPqM and Faculdade de Oceanografia (UERJ) for data analysis support.341
LB received a scholarship from CAPES. IMSL received a scholarship from342
FAPERJ. AFA and JL-B have research grant from CNPq (PQ-1D), FAPERJ343
(JCNE) and UERJ (Prociencia).344
6. References345
Ricardo Antunes, Tyler Schulz, Shane Gero, Hal Whitehead, Jonathan Gor-346
don, and Luke Rendell. Individually distinctive acoustic features in sperm347
whale codas. Animal Behaviour, 81(4):723–730, 2011.348
Alexandre F Azevedo, Alvaro M Oliveira, L Dalla Rosa, and J Lailson-Brito.349
Characteristics of whistles from resident bottlenose dolphins (Tursiops350
truncatus) in southern Brazil. The Journal of the Acoustical Society of351
America, 121(5):2978–2983, 2007.352
16
Alexandre F Azevedo, L Flach, Tatiana L Bisi, Luciana G Andrade, Paulo R353
Dorneles, and J Lailson-Brito. Whistles emitted by Atlantic spotted dol-354
phins (Stenella frontalis) in southeastern Brazil. The Journal of the Acous-355
tical Society of America, 127(4):2646–2651, 2010.356
Lisa T Ballance, Robert L Pitman, and Paul C Fiedler. Oceanographic in-357
fluences on seabirds and cetaceans of the eastern tropical pacific: a review.358
Progress in Oceanography, 69(2-4):360–390, 2006.359
Simone Baumann-Pickering, Marie A Roch, Robert L Brownell Jr, Anne E360
Simonis, Mark A McDonald, Alba Solsona-Berga, Erin M Oleson, Sean M361
Wiggins, and John A Hildebrand. Spatio-temporal patterns of beaked362
whale echolocation signals in the North Pacific. PLoS One, 9(1):e86072,363
2014.364
Simone Baumann-Pickering, Jennifer S Trickey, Sean M Wiggins, and Erin M365
Oleson. Odontocete occurrence in relation to changes in oceanography at366
a remote equatorial Pacific seamount. Marine Mammal Science, 32(3):367
805–825, 2016.368
Mark F Baumgartner and David M Fratantoni. Diel periodicity in both sei369
whale vocalization rates and the vertical migration of their copepod prey370
observed from ocean gliders. Limnology and Oceanography, 53(5part2):371
2197–2209, 2008.372
Brian Bingham, Nicholas Kraus, Bruce Howe, Lee Freitag, Keenan Ball,373
Peter Koski, and Eric Gallimore. Passive and active acoustics using an374
autonomous wave glider. Journal of field robotics, 29(6):911–923, 2012.375
17
Lis Bittencourt, Mariana Barbosa, Eduardo Secchi, Jose Lailson-Brito, and376
Alexandre Azevedo. Acoustic habitat of an oceanic archipelago in the377
Southwestern Atlantic. Deep Sea Research Part I: Oceanographic Research378
Papers, 115:103–111, 2016.379
M Bonato, E Papale, G Pingitore, S Ricca, A Attoumane, A Ouledi, and380
C Giacoma. Whistle characteristics of the spinner dolphin population381
in the Comoros Archipelago. The Journal of the Acoustical Society of382
America, 138(5):3262–3271, 2015.383
Edmo JD Campos, Denise Velhote, and Ilson CA da Silveira. Shelf break384
upwelling driven by brazil current cyclonic meanders. Geophysical Research385
Letters, 27(6):751–754, 2000.386
A Canadas, R Sagarminaga, and S Garcıa-Tiscar. Cetacean distribution387
related with depth and slope in the mediterranean waters off southern388
spain. Deep Sea Research Part I: Oceanographic Research Papers, 49(11):389
2053–2073, 2002.390
Peter Carragher, Graham Hine, Patrick Legh-Smith, Jeffrey Mayville, Rod391
Nelson, Sudhir Pai, Iain Parnum, Paul Shone, Jonathan Smith, and Chris-392
tian Tichatschke. A new platform for offshore exploration and production.393
Oilfield Review, 2014(25):4, 2013.394
Renato M Castelao and John A Barth. Upwelling around cabo frio, brazil:395
The importance of wind stress curl. Geophysical Research Letters, 33(3),396
2006.397
18
Renato M Castelao, Edmo JD Campos, and Jerry L Miller. A modelling398
study of coastal upwelling driven by wind and meanders of the brazil cur-399
rent. Journal of Coastal Research, pages 662–671, 2004.400
BM de Castro and LB de Miranda. Physical oceanography of the western401
atlantic continental shelf located between 4n and 34s. In A. R. Robinson402
and K. H. Brink, editors, The sea, chapter 8, pages 209–251. Wiley New403
York, Hoboken, N. J., 1998.404
Paulo Alberto S Costa and Flavio da Costa Fernandes. Seasonal and spatial405
changes of cephalopods caught in the cabo frio (brazil) upwelling ecosys-406
tem. Bulletin of Marine Science, 52(2):751–759, 1993.407
Donald A Croll, Baldo Marinovic, Scott Benson, Francisco P Chavez, Nancy408
Black, Richard Ternullo, and Bernie R Tershy. From wind to whales:409
trophic links in a coastal upwelling system. Marine Ecology Progress Series,410
289:117–130, 2005.411
Luciano Dalla Rosa, John KB Ford, and Andrew W Trites. Distribution412
and relative abundance of humpback whales in relation to environmental413
variables in coastal british columbia and adjacent waters. Continental Shelf414
Research, 36:89–104, 2012.415
Luciana Guimaraes de Andrade, Isabela Maria Seabra Lima, Halerson416
da Silva Macedo, Rafael Ramos de Carvalho, Jose Lailson-Brito, Leonardo417
Flach, and Alexandre de Freitas Azevedo. Variation in Guiana dolphin (So-418
talia guianensis) whistles: using a broadband recording system to analyze419
19
acoustic parameters in three areas of southeastern Brazil. acta ethologica,420
18(1):47–57, 2015.421
Renaud De Stephanis, Thomas Cornulier, Philippe Verborgh,422
Juanma Salazar Sierra, Neus Perez Gimeno, and Christophe Guinet.423
Summer spatial distribution of cetaceans in the strait of gibraltar in424
relation to the oceanographic context. Marine Ecology Progress Series,425
353:275–288, 2008.426
Juliana Couto Di Tullio, Tiago BR Gandra, Alexandre N Zerbini, and Ed-427
uardo R Secchi. Diversity and distribution patterns of cetaceans in the428
subtropical Southwestern Atlantic outer continental shelf and slope. PloS429
one, 11(5):e0155841, 2016a.430
Juliana Couto Di Tullio, Tiago BR Gandra, Alexandre N Zerbini, and Ed-431
uardo R Secchi. Diversity and distribution patterns of cetaceans in the432
subtropical southwestern atlantic outer continental shelf and slope. PloS433
one, 11(5):e0155841, 2016b.434
Manuel E dos Santos, Sonia Louro, Miguel Couchinho, and Cristina Brito.435
Whistles of bottlenose dolphins (Tursiops truncatus) in the Sado Estuary,436
Portugal: characteristics, production rates, and long-term contour stabil-437
ity. Aquatic Mammals, 31(4):453, 2005.438
Ingvar Emılsson. The shelf and coastal waters off southern brazil. Boletim439
do Instituto Oceanografico, 11(2):101–112, 1961.440
Ari S Friedlaender, Pat N Halpin, Song S Qian, Gareth L Lawson, Peter H441
Wiebe, Deb Thiele, and Andrew J Read. Whale distribution in relation to442
20
prey abundance and oceanographic processes in shelf waters of the western443
antarctic peninsula. Marine Ecology Progress Series, 317:297–310, 2006.444
Jason Gedamke, Daniel P Costa, and Andy Dunstan. Localization and visual445
verification of a complex minke whale vocalization. The Journal of the446
Acoustical Society of America, 109(6):3038–3047, 2001.447
Gordon D Hastie, BEN Wilson, LJ Wilson, KM Parsons, and Paul Michael448
Thompson. Functional mechanisms underlying cetacean distribution pat-449
terns: hotspots for bottlenose dolphins are linked to foraging. Marine450
Biology, 144(2):397–403, 2004.451
Roger Hine, Scott Willcox, Graham Hine, and Tim Richardson. The Wave452
Glider: A wave-powered autonomous marine vehicle. In OCEANS 2009,453
MTS/IEEE Biloxi-Marine Technology for Our Future: Global and Local454
Challenges, pages 1–6. IEEE, 2009.455
Y Ikeda, LB De Miranda, and NJ Rock. Observations on stages of upwelling456
in the region of cabo frio (brazil) as conducted by continuous surface tem-457
perature and salinity measurements. Boletim do Instituto Oceanografico,458
23:33–46, 1974.459
Holger Klinck, Sharon L Nieukirk, David K Mellinger, Karolin Klinck,460
Haruyoshi Matsumoto, and Robert P Dziak. Seasonal presence of cetaceans461
and ambient noise levels in polar waters of the North Atlantic. The Journal462
of the Acoustical Society of America, 132(3):EL176–EL181, 2012.463
S. Krey, O. Mersmann, S. Schnackenberg, G. Guenard, A. Preusser,464
A. Thieler, J. Mielke, and C. Weihs. Package “tuner”, 2011.465
21
Marc O Lammers, Russell E Brainard, Whitlow WL Au, T Aran Mooney,466
and Kevin B Wong. An ecological acoustic recorder (ear) for long-term467
monitoring of biological and anthropogenic sounds on coral reefs and other468
marine habitats. The Journal of the Acoustical Society of America, 123469
(3):1720–1728, 2008.470
Isabela Maria Seabra Lima, Luciana Guimaraes de Andrade, Rafael471
Ramos de Carvalho, Jose Lailson-Brito, and Alexandre de Freitas Azevedo.472
Characteristics of whistles from rough-toothed dolphins (Steno bredanen-473
sis) in Rio de Janeiro coast, southeastern Brazil. The Journal of the Acous-474
tical Society of America, 131(5):4173–4181, 2012.475
Isabela MS Lima, Luciana G Andrade, Lis Bittencourt, Tatiana L Bisi,476
Leonardo Flach, Jose Lailson-Brito Jr, and Alexandre F Azevedo. Whistle477
comparison of four delphinid species in Southeastern Brazil. The Journal478
of the Acoustical Society of America, 139(5):EL124–EL127, 2016.479
James Vincent Locascio. Passive acoustic studies of estuarine fish populations480
of southwest Florida. University of South Florida, 2010.481
Bruno Dıaz Lopez. Whistle characteristics in free-ranging bottlenose dolphins482
(Tursiops truncatus) in the Mediterranean Sea: influence of behaviour.483
Mammalian Biology-Zeitschrift fur Saugetierkunde, 76(2):180–189, 2011.484
Joseph J Luczkovich, David A Mann, and Rodney A Rountree. Passive acous-485
tics as a tool in fisheries science. Transactions of the American Fisheries486
Society, 137(2):533–541, 2008.487
22
JP Martin, CM Lee, CC Eriksen, C Ladd, and NB Kachel. Glider obser-488
vations of kinematics in a gulf of alaska eddy. Journal of Geophysical489
Research: Oceans, 114(C12), 2009.490
Y Matsuura. A probable cause of recruitment failure of the brazilian sardine491
sardinella aurita population during the 1974/75 spawning season. South492
African Journal of Marine Science, 17(1):29–35, 1996.493
Laura J May-Collado. Guyana dolphins (Sotalia guianensis) from Costa494
Rica emit whistles that vary with surface behaviors. The Journal of the495
Acoustical Society of America, 134(4):EL359–EL365, 2013.496
Sue E Moore, Kathleen M Stafford, David K Mellinger, and John A Hilde-497
brand. Listening for large whales in the offshore waters of Alaska. AIBS498
Bulletin, 56(1):49–55, 2006.499
Ignacio B Moreno, Alexandre N Zerbini, Daniel Danilewicz, Marcos C500
de Oliveira Santos, Paulo C Simoes-Lopes, Jose Lailson-Brito Jr, and501
Alexandre F Azevedo. Distribution and habitat characteristics of dolphins502
of the genus Stenella (Cetacea: Delphinidae) in the southwest Atlantic503
Ocean. Marine Ecology Progress Series, 300:229–240, 2005.504
Erin M Oleson, Jay Barlow, Jonathan Gordon, Shannon Rankin, and John A505
Hildebrand. Low frequency calls of bryde’s whales. 2003.506
Julie N Oswald, Jay Barlow, and Thomas F Norris. Acoustic identification507
of nine delphinid species in the eastern tropical Pacific Ocean. Marine508
mammal science, 19(1):20–037, 2003.509
23
Julie N Oswald, Shannon Rankin, and Jay Barlow. The effect of recording510
and analysis bandwidth on acoustic identification of delphinid species. The511
Journal of the Acoustical Society of America, 116(5):3178–3185, 2004.512
Julie N Oswald, Shannon Rankin, Jay Barlow, and Marc O Lammers. A513
tool for real-time acoustic species identification of delphinid whistles. The514
Journal of the Acoustical Society of America, 122(1):587–595, 2007.515
Bioacoustics Research Program. Raven pro: interactive sound analysis soft-516
ware. version 1.4, 2011.517
Gerry P Quinn and Michael J Keough. Experimental design and data analysis518
for biologists. Cambridge University Press, 2002.519
Shannon Rankin and Jay Barlow. Source of the North Pacific “boing” sound520
attributed to minke whales. The Journal of the Acoustical Society of Amer-521
ica, 118(5):3346–3351, 2005.522
Luke Rendell and Hal Whitehead. Spatial and temporal variation in sperm523
whale coda vocalizations: stable usage and local dialects. Animal Be-524
haviour, 70(1):191–198, 2005.525
Amalis Riera, John K Ford, and N Ross Chapman. Effects of different anal-526
ysis techniques and recording duty cycles on passive acoustic monitoring527
of killer whales. The Journal of the Acoustical Society of America, 134(3):528
2393–2404, 2013.529
Regina R Rodrigues and Joao A Lorenzzetti. A numerical study of the effects530
of bottom topography and coastline geometry on the southeast brazilian531
coastal upwelling. Continental Shelf Research, 21(4):371–394, 2001.532
24
Daniel L Rudnick, Russ E Davis, Charles C Eriksen, David M Fratantoni,533
and Mary Jane Perry. Underwater gliders for ocean research. Marine534
Technology Society Journal, 38(2):73–84, 2004.535
Ana Sirovic, Hannah R Bassett, Sarah C Johnson, Sean M Wiggins, and536
John A Hildebrand. Bryde’s whale calls recorded in the Gulf of Mexico.537
Marine Mammal Science, 30(1):399–409, 2014.538
Renata S Sousa-Lima, Thomas F Norris, Julie N Oswald, and Deborah P539
Fernandes. A review and inventory of fixed autonomous recorders for540
passive acoustic monitoring of marine mammals. Aquatic Mammals, 39541
(1):23, 2013.542
William W Steiner. Species-specific differences in pure tonal whistle vocal-543
izations of five western North Atlantic dolphin species. Behavioral Ecology544
and Sociobiology, 9(4):241–246, 1981.545
Cynthia T Tynan, David G Ainley, John A Barth, Timothy J Cowles,546
Stephen D Pierce, and Larry B Spear. Cetacean distributions relative547
to ocean processes in the northern california current system. Deep Sea548
Research Part Ii: Topical studies in Oceanography, 52(1-2):145–167, 2005.549
Jean L Valentin. Spatial structure of the zooplankton community in the cabo550
frio region (brazil) influenced by coastal upwelling. In Tropical Zooplank-551
ton, pages 183–199. Springer, 1984.552
Sofie M Van Parijs, Chris W Clark, Renata S Sousa-Lima, Susan E Parks,553
Shannon Rankin, Denise Risch, and Ilse C Van Opzeeland. Management554
and research applications of real-time and archival passive acoustic sensors555
25
over varying temporal and spatial scales. Marine Ecology Progress Series,556
395:21–36, 2009.557
Tracy A Villareal and Cara Wilson. A comparison of the pac-x trans-pacific558
wave glider data and satellite data (modis, aquarius, trmm and viirs). PloS559
one, 9(3):e92280, 2014.560
Carrie C Wall, Chad Lembke, and David A Mann. Shelf-scale mapping561
of sound production by fishes in the eastern Gulf of Mexico, using au-562
tonomous glider technology. Marine Ecology Progress Series, 449:55–64,563
2012.564
Carrie C Wall, Peter Simard, Chad Lembke, and David A Mann. Large-scale565
passive acoustic monitoring of fish sound production on the West Florida566
shelf. Marine Ecology Progress Series, 484:173–188, 2013.567
Carrie C Wall, David A Mann, Chad Lembke, Chris Taylor, Ruoying He,568
and Todd Kellison. Mapping the soundscape off the Southeastern USA by569
using passive acoustic glider technology. Marine and Coastal Fisheries, 9570
(1):23–37, 2017.571
Pauline Weatherall, KM Marks, Martin Jakobsson, Thierry Schmitt, Shin572
Tani, Jan Erik Arndt, Marzia Rovere, Dale Chayes, Vicki Ferrini, and573
Rochelle Wigley. A new digital bathymetric model of the world’s oceans.574
Earth and Space Science, 2(8):331–345, 2015.575
LL Wedekin, MR Rossi-Santos, C Baracho, AL Cypriano-Souza, and576
PC Simoes-Lopes. Cetacean records along a coastal-offshore gradient in the577
26
Vitoria-Trindade Chain, western South Atlantic Ocean. Brazilian Journal578
of Biology, 74(1):137–144, 2014.579
Sean M Wiggins, Kaitlin E Frasier, E Elizabeth Henderson, and John A580
Hildebrand. Tracking dolphin whistles using an autonomous acoustic581
recorder array. The Journal of the Acoustical Society of America, 133582
(6):3813–3818, 2013.583
Ben Wilson, Steven Benjamins, and Jim Elliott. Using drifting passive584
echolocation loggers to study harbour porpoises in tidal-stream habitats.585
Endangered Species Research, 22(2):125–143, 2013.586
Alexandre N Zerbini. Distribuicao e abundancia relativa de cetaceos na Zona587
Economica Exclusiva da regiao Sudeste-Sul do Brasil. Number 599.5 (81)588
DIS. 2004.589
Alexandre N Zerbini, Eduardo R Secchi, Salvatore Siciliano, and Paulo Cesar590
Simoes-Lopes. A review of the occurrence and distribution of whales of the591
genus Balaenoptera along the Brazilian coast. Report of the International592
Whaling Commission, 47:407–417, 1997.593
Walter MX Zimmer, John Harwood, Peter L Tyack, Mark P Johnson, and594
Peter T Madsen. Passive acoustic detection of deep-diving beaked whales.595
The Journal of the Acoustical Society of America, 124(5):2823–2832, 2008.596
27
Figure 1: The Wave Glider model SV2 connected to the PAM system through a 15-m tow
cable on deck after recovery.
28
Table 1: Detectors parameters used in Raven 1.5 to look for biological signals from the
offshore waters of the Southwestern Atlantic Ocean.
Detector Parameters Spectogram Frequency Limit Focal Sound Types
Det1 Minimum frequency: 8 kHz 25 kHz Whistles and burst-pulsed sounds
Maximum frequency: 22 kHz
Minimum duration: 60 ms
Maximum duration: 900 ms
Minimum separation: 50 ms
Det2 Minimum frequency: 2 kHz 25 kHz Whistles and burst-pulsed sounds
Maximum frequency: 7 kHz
Minimum duration: 60 ms
Maximum duration: 900 ms
Minimum separation: 50 ms
Det3 Minimum frequency: 15 kHz 25 kHz Echolocation clicks
Maximum frequency: 24 kHz
Minimum duration: 5 ms
Maximum duration: 10 ms
Minimum separation: 10 ms
Det4 Minimum frequency: 50 Hz 3 kHz Tonal and burst-pulsed sounds
Maximum frequency: 300 Hz
Minimum duration: 200 ms
Maximum duration: 600 ms
Minimum separation: 300 ms
Det5 Minimum frequency: 300 Hz 3 kHz Tonal and burst-pulsed sounds
Maximum frequency: 800 Hz
Minimum duration: 100 ms
Maximum duration: 600 ms
Minimum separation: 100 ms
29
Table 2: High-frequency acoustic detection events obtained through passive acoustic mon-
itoring in Brazilian offshore waters in the Southwestern Atlantic Ocean during the austral
summer.
Detection event Duration (h) Time of day interval Detection composition Local depth (m)
HF1 8 15 pm to 23 pm 8815 EC, 62 W, 32 BP 339 ± 78 (243–427)
HF2 7 00 am to 07 pm 37452 EC, 30 W, 54 BP 711 ± 74 (626–841)
HF3 1 14 pm to 15 pm 55 EC 1612
HF4 1 10 am to 11 am 16 EC, 8 W 1643
HF5 2 06 am to 08 am 9349 EC, 18 W, 12 BP 1629 ± 1 (1628–1629)
HF6 1 09 am to 10 am 31 clicks EC 1627
HF7 5 20 pm to 01 am of the following day 4564 EC, 159 W, 23 BP 1629 ± 5 (1621–1633)
HF8 3 04 am to 07 am 2722 EC, 18 W, 6 BP 1504 ± 6 (1497–1508)
HF9 4 21 pm to 01 am of the following day 18714 EC, 448 W, 47 BP 1569 ± 11 (1555–1579)
HF10 2 02 am to 04 am 10651 EC, 20 W, 11 BP 1218 ± 11 (1213–1255)
HF11 6 21 pm to 03 am of the following day 1757 EC, 122 W, 6 BP 697 ± 35 (667–756)
HF12 5 11 am to 15 pm 2995 EC, 59 W, 3 BP (352–468)
HF13 2 03 am to 05 am 1594 EC, 3 W, 2 BP 144 ± 1 (144–145)
HF14 2 19 pm to 21 pm 3 EC, 39 W, 6 BP 174 ± 5 (170–177)
HF15 3 04 am to 07 am 7 W, 4 BP 417 ± 91 (334–515)
HF16 1 10 am 28 EC 805
HF17 2 03 am to 05 am 763 EC 1364 ± 33 (1341–1387)
HF18 2 18 pm to 20 pm 4180 EC, 4 W, 48 BP 1566 ± 6 (1562–1570)
HF19 2 04 am to 06 am 11118 EC, 91 W, 53 BP 1791 ± 21 (1776–1806)
HF20 1 11 am 389 EC 1966
HF21 7 23 pm to 06 am 2575 EC, 26 W, 9 BP 2058 ± 23 (2031–2084)
HF22 2 03 am to 05 am 3 BP 1638 ± 19 (1624–1651)
HF23 2 03 am to 05 am 1188 EC, 2 BP 1177 ± 21 (1162–1191)
HF24 1 06 am 9017 EC, 9 W, 4 BP 1120
HF25 1 09 am 18 W 1026
HF26 11 22 pm to 09 am 18682 EC, 249 W, 52 BP 378 ± 160 (177–573)
HF27 1 11 am 36 EC 145
HF28 3 13 pm to 16 pm 85 EC 131 ± 1 (130–132)
HF29 5 19 pm to 00 am 654 EC, 74 W 379 ± 1 (224–513)
HF30 8 00 am to 08 am 15519 EC, 177 W, 12 BP 515 ± 27 (488–555)
HF31 2 09 am to 11 am 148 W 470
Sum 111 - 162952 EC, 1823 W, 389 BP 935 ± 619 (130–2084)
30
Table 3: Low-frequency acoustic detection events obtained through passive acoustic mon-
itoring in Brazilian offshore waters in the Southwestern Atlantic Ocean during the austral
summer.
Detection event Duration (h) Time of the day interval Detection composition Local depth (m)
LF1 2 08 am to 10 am 139 tonal signals 1041 ± 59 (999–1083)
LF2 2 20 pm to 22 pm 48 tonal signals 1576 ± 2 (1576–1579)
LF3 3 19 pm to 22 pm 122 tonal signals 841 ± 82 (756–920)
LF4 3 00 am to 03 am 393 tonal signals 677 ± 13 (667–692)
LF5 1 14 pm 3 tonal signals 392
Sum 11 - 705 tonal signals 926 ± 372 (392–1579)
Figure 2: Examples of biological signals categories as classified by two observers during
detection validation. (A) echolocations clicks (overlapped with a whistle), (B) burst-pulsed
sound, and (C) tonal signal, referred to as whistles in the case of delphinid.
31
Figure 3: Number of hours with high-frequency and low-frequency detections in all days
of the sampling period.
32
Figure 4: Sum of high-frequency (A) and low-frequency (B) detections per hour of the day
of the total sampling period.
33
Figure 5: Mapping of high-frequency detection events through unmanned vehicle pas-
sive acoustic monitoring on Brazilian offshore waters in the Southwestern Atlantic Ocean
between 6-25 February 2016.
34
Figure 6: Mapping of low-frequency detection events through unmanned vehicle passive
acoustic monitoring on Brazilian offshore waters in the Southwestern Atlantic Ocean be-
tween 6-25 February 2016.
35
Figure 7: Principal components analysis of 13 high-frequency events of delphinid detec-
tions registered during passive acoustic monitoring in Brazilian offshore waters in the
Southwestern Atlantic Ocean.
36
Figure 8: DFA centroids separating high-frequency events into seven groups, indicating
probable seven delphinid species registered during passive acoustic monitoring in Brazilian
offshore waters in the Southwestern Atlantic Ocean.
37
Figure 9: Examples of whistles of the same contour type in two situations: (A) whistle
recorded in the present study; and (B) whistle recorded during visual surveys of rough-
toothed dolphins and found in the MAQUA sound database.
38
Figure 10: Brydes whale calls recorded through unmanned vehicle passive acoustic moni-
toring on Brazilian offshore waters in the Southwestern Atlantic Ocean.
39
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