Seasonal Trends and Diel Patterns of Downsweep and SEP Calls in Chilean Blue Whales

Abstract

To learn more about the occurrence and behaviour of a recently discovered population of blue whales, passive acoustic data were collected between January 2012 and April 2013 in the Chiloense ecoregion of southern Chile. Automatic detectors and manual auditing were used to detect blue whale songs (SEP calls) and D calls, which were then analysed to gain insights into temporal calling patterns. We found that D call rates were extremely low during winter (June–August) but gradually increased in spring and summer, decreasing again later during fall. SEP calls were absent for most winter and spring months (July–November) but increased in summer and fall, peaking between March and April. Thus, our results support previous studies documenting the austral summer residency of blue whales in this region, while suggesting that some individuals stay longer, highlighting the importance of this area as a blue whale habitat. We also investigated the daily occurrence of each call type and found that D calls occurred more frequently during dusk and night hours compared to dawn and day periods, whereas SEP calls did not show any significant diel patterns. Overall, these findings help to understand the occurrence and behaviour of endangered Chilean blue whales, enhancing our ability to develop conservation strategies in this important Southern Hemisphere habitat.

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Citation: Redaelli, L.; Mangia Woods,
S.; Landea, R.; Sayigh, L. Seasonal
Trends and Diel Patterns of
Downsweep and SEP Calls in Chilean
Blue Whales. J. Mar. Sci. Eng. 2022,
10, 316. https://doi.org/10.3390/
jmse10030316
Academic Editor: Roberto Carlucci
Received: 15 January 2022
Accepted: 21 February 2022
Published: 23 February 2022
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Journal of
Marine Science
and Engineering
Article
Seasonal Trends and Diel Patterns of Downsweep and SEP
Calls in Chilean Blue Whales
Laura Redaelli 1, * , Sari Mangia Woods 1, Rafaela Landea 2and Laela Sayigh 3,4
1Groningen Institute for Evolutionary Life Sciences, University of Groningen, P.O. Box 11103,
9700 CC Groningen, The Netherlands; sari.mangia@gmail.com
2Centinela Patagonia, Castro 5700289, Chiloe, Chile; rafaela.landea@gmail.com
3Biology Department, Woods Hole Oceanographic Institution, Woods Hole, MA 02543, USA;
lsayigh@whoi.edu
4School of Cognitive Science, Hampshire College, Amherst, MA 01002, USA
*Correspondence: laura.redaelli.95@gmail.com
Abstract:
To learn more about the occurrence and behaviour of a recently discovered population
of blue whales, passive acoustic data were collected between January 2012 and April 2013 in the
Chiloense ecoregion of southern Chile. Automatic detectors and manual auditing were used to detect
blue whale songs (SEP calls) and D calls, which were then analysed to gain insights into temporal
calling patterns. We found that D call rates were extremely low during winter (June–August) but
gradually increased in spring and summer, decreasing again later during fall. SEP calls were absent
for most winter and spring months (July–November) but increased in summer and fall, peaking
between March and April. Thus, our results support previous studies documenting the austral
summer residency of blue whales in this region, while suggesting that some individuals stay longer,
highlighting the importance of this area as a blue whale habitat. We also investigated the daily
occurrence of each call type and found that D calls occurred more frequently during dusk and night
hours compared to dawn and day periods, whereas SEP calls did not show any significant diel
patterns. Overall, these findings help to understand the occurrence and behaviour of endangered
Chilean blue whales, enhancing our ability to develop conservation strategies in this important
Southern Hemisphere habitat.
Keywords:
Chilean blue whales; marine bioacoustics; Balaenoptera musculus chilensis; Chile; D calls;
SEP calls; diel patterns; seasonal trends; marine conservation
1. Introduction
Cetaceans rely heavily on acoustic communication, which allows researchers to study
their occurrence and behaviour from a distance. Passive acoustic monitoring (PAM) can be
a powerful tool to study cetacean populations over various spatial and temporal scales [
1
,
2
].
Furthermore, PAM allows us to study animals without interfering with their behaviour [
3
].
Diel and seasonal variation in call production occur in a wide variety of marine
animals and may be correlated with different behaviours [
4
,
5
]. Diel patterning may be
caused by sleep or resting, tidal or lunar influences, or prey migrations [
6
]. A range of
diel patterns can be seen among cetacean species. Some odontocetes, such as common
dolphins (Delphinus delphis) and harbour porpoises (Phocoena phocoena), are more vocal at
night while feeding at depth [
5
,
7
], while baleen whales are known to call more during the
day (sei whales, Balaenoptera borealis) [
8
], or twilight hours (Chilean/Peruvian right whales,
Eubalaena australis) [
9
], and Californian blue whales, Balaenoptera musculus) [
10
], when likely
not foraging. Seasonal patterns can provide information on the general presence in an
area and migratory movements. Oestreich et al. [
11
] used song production rate to link the
individual and population-level behaviour of blue whales in California. Combining passive
acoustic and tag data, the authors identified a temporal acoustic signature of a behavioural
J. Mar. Sci. Eng. 2022,10, 316. https://doi.org/10.3390/jmse10030316 https://www.mdpi.com/journal/jmse

J. Mar. Sci. Eng. 2022,10, 316 2 of 18
transition from foraging to migrating. These findings highlight the effectiveness of acoustic
studies to understand the behaviour and movements of an endangered species, and to thus
identify when and where conservation efforts would be the most effective.
Extensive exploitation during industrial whaling days reduced the populations of
blue whales in the Southern Hemisphere to less than 3% of original numbers [
12
]. Since
legal protection from whaling, some blue whale stocks have shown signs of recovery
while others still lack data to determine their status. North Pacific stocks are labelled
as ‘Low risk: conservation dependent’, North Atlantic stocks as ‘Vulnerable’, Antarctic
stocks as ‘Critically Endangered’, and pygmy blue whales are ‘Data Deficient’ [
13
]. Cur-
rently, one of the main concerns for coastal marine mammals is loss of critical habitats,
such as feeding, breeding, and nursing grounds, due to human activities and climate
change [
14
].
Hucke-Gaete et al. [15]
discovered an important coastal blue whale feeding
and nursing ground in the Chiloe-Corcovado region in Chilean Patagonia; a subsequent
photo-identification study documented between 570 and 762 individuals during one aus-
tral summer [
16
]. Although blue whales in Chilean waters were previously classified as
either pygmy (B. m. brevicauda) or Antarctic blue whales (B. m. intermedia) [
17
,
18
], a recent
study [
19
] comparing anatomical, genetic, and morphometric evidence [
20
–
22
] proposed
that they represent a different subspecies, B. m. chilensis, and are thus referred to as ‘Chilean
blue whales’. Our study examines passive acoustic data in an effort to learn more about
Chilean blue whales and to inform the conservation efforts.
Blue whales produce sounds with frequencies among the lowest (16–100 Hz) and
loudest (176.8–188.5 dB re 1uPa) in the ocean, capable of propagating over extremely
long distances [
23
,
24
]. Blue whales in different geographic areas produce different song
patterns, consisting of repeated sequences of ‘phrases’ made up of recurring pulsed sounds
or ‘units’ [
25
], which are thought to function as a reproductive display [
25
–
27
]. Blue
whale songs have usually been attributed to males [
25
,
28
,
29
] and have been reported
to occur along entire migratory routes, from summer feeding areas to winter breeding
grounds [30–32]
. Different song types are typically characterized by differences in unit
characteristics (frequency, duration, modulation, inter-unit time intervals), ordering of
song units within each phrase (song phrasing), and song phrase duration [
25
,
27
,
33
,
34
].
Chilean blue whales produce SEP (Southeast Pacific) song types [
27
]. In the Chiloense
Ecoregion the SEP1 song type, which consists of three units, was first recorded in 1971
(A-B-C phrasing, total duration = 36.5 s) [
35
]. More recently, a four-unit song type with
a longer duration, called SEP2, has been found to occur more often than SEP1 (A-B-
C-D phrasing, total duration = 60 s; Figure 1B) [
27
]. Similar to changes seen in other
blue whale populations [
31
,
36
–
41
], both SEP call types showed a declining trend in peak
frequency and pulse rate over the span of decades, likely due to sexual selection and
cultural conformity [
42
]. Moreover, recent evidence [
11
] suggests that song production
might have a role in collective migration to mating grounds, helping dispersed populations
to appropriately sense and respond to environmental information.
All blue whale populations also produce so-called D calls, downsweeping sounds
that are produced by both sexes and that occur in irregular patterns [
28
] (see examples
in Figure 1A). D calls have been suggested to be contact calls, akin to up-calls of right
whales and downsweep calls of fin whales, which may be used to locate conspecifics
and maintain group cohesion on feeding grounds [
26
]. However, a recent study [
43
]
reported extensive use of D calls during competitive male-male behaviour in a reproductive
context. D calls have been proposed to occur as counter-calls among multiple whales, as
they sometimes occur in overlapping pairs, each produced by a different animal [
26
,
43
].
Oleson et al. [26]
proposed that D calls are unlikely to facilitate prey capture as they are not
used to cooperatively herd prey or coordinate underwater activity during feeding, such as
the feeding cries of humpback whales do. In fact, Oleson et al. [
26
,
28
] found that D calls
were inversely associated with foraging behaviour, although, Stafford et al. [
44
] suggested
a direct relationship of D calls with feeding behaviour. Overall, it appears likely that D
calls may have a common function (contact) in a variety of behavioural contexts.

J. Mar. Sci. Eng. 2022,10, 316 3 of 18
1
Figure 1.
Spectrogram of a series of high-quality D calls (
A
) and a SEP2 call (
B
) from this study. SEP
call units are marked by A, B, C, D. The red box indicates the portion of the call with higher SNR
used to detect fainter calls (see Section 2.1 in the Materials and Methods). Spectrogram parameters:
200 Hz frequency axis, DFT = 2048 samples, FFT = 750, 10% overlap and Hann window function.
Spectrograms produced with Raven Pro 1.6.
Given the proposed different functions of SEP and D calls, we were interested to learn
whether they show similar or different seasonal and geographic patterns of occurrence.
Buchan et al. [
30
,
45
] analysed seasonal variability in SEP call occurrence in the Chiloense
Ecoregion and found higher calling rates during summer and fall months (January–May).
Thus, one goal of our study was to examine the seasonal patterns of D calls in this area,
and relate them to those of SEP calls. We hypothesized that D call rates would be higher
during summer months, when food availability is high and more whales are attracted to
the area, while SEP call rates would increase later, as suggested by previous studies [
30
,
45
].
A second goal was to examine diel patterns of both call types, which is particularly relevant
for D calls as it could provide insights into their function and behavioural context. For
example, if D call production is related to prey availability, higher calling rates would be
found during periods of intense feeding, such as during the night when prey patches are
closer to the surface [
44
]. In contrast, if D calls are not related to feeding, higher calling rates
would be found when prey patches are more diffuse and foraging efforts less efficient, such
as during twilight hours [
9
,
10
,
46
]. The recent evidence of D call occurrence in a mating
context [
43
] suggests that the second scenario is more likely. Since SEP calls are considered
breeding calls and are thus not related to feeding and prey movements, we predicted that
they would not have a clear diel pattern.
2. Materials and Methods
Acoustic data from the Chiloense Ecoregion in the south of Chile (~43
◦
S–44
◦
S,
71◦W–73◦W
) were collected continuously during three five-month deployment periods,
from the end of January 2012 to the end of April 2013, using six Marine Autonomous
Recording Units (MARUs; Cornell University Laboratory of Ornithology’s K. Lisa Yang

J. Mar. Sci. Eng. 2022,10, 316 4 of 18
Center for Conservation Bioacoustics, Ithaca, NY, USA) deployed at four different loca-
tions: (1) Northwest Chiloe, (2) Guafo North, (3) Tic Toc Bay, and (4) Melimoyu (Figure 2).
Deployment details are listed in Table 1and periods of continuous recordings are visu-
ally displayed in Figure 3. MARUs were leased from Cornell University Laboratory of
Ornithology’s K. Lisa Yang Center for Conservation Bioacoustics (formerly the Bioacoustics
Research Program) and were programmed to record at a sampling rate of 2 kHz. Acoustic
data were recorded to an internal hard drive and were accessible upon instrument recovery;
recovered data were then extracted onto an external hard drive. Deployment sites were
chosen to provide wide geographic coverage of the Chiloense ecoregion, from offshore ar-
eas such as Northwest Chiloe and Guafo North to areas closer to the Chilean continent such
as Tic Toc and Melimoyu (Figure 2). Three MARU recovery attempts were unsuccessful;
therefore, certain sites lack some temporal coverage [30].
J. Mar. Sci. Eng. 2022, 10, x FOR PEER REVIEW 4 of 20
Units (MARUs; Cornell University Laboratory of Ornithology’s K. Lisa Yang Center for
Conservation Bioacoustics, Ithaca, NY, USA) deployed at four different locations: (1)
Northwest Chiloe, (2) Guafo North, (3) Tic Toc Bay, and (4) Melimoyu (Figure 2).
Deployment details are listed in Table 1 and periods of continuous recordings are visually
displayed in Figure 3. MARUs were leased from Cornell University Laboratory of Orni-
thology’s K. Lisa Yang Center for Conservation Bioacoustics (formerly the Bioacoustics
Research Program) and were programmed to record at a sampling rate of 2 kHz. Acoustic
data were recorded to an internal hard drive and were accessible upon instrument recov-
ery; recovered data were then extracted onto an external hard drive. Deployment sites
were chosen to provide wide geographic coverage of the Chiloense ecoregion, from off-
shore areas such as Northwest Chiloe and Guafo North to areas closer to the Chilean con-
tinent such as Tic Toc and Melimoyu (Figure 2). Three MARU recovery attempts were
unsuccessful; therefore, certain sites lack some temporal coverage [30].
Figure 2. Map of the study area showing the four MARU deployment locations: 1. Northwest
Chiloe, 2. Guafo North, 3. Tic Toc Bay, 4. Melimoyu.
Table 1. MARU deployment details: location, start and end date and total hours of recordings.
Unit Location Start Date End Date Total Hours
MARU 1 Guafo North 31 January 2012 17 June 2012 3370
MARU 2 Guafo North 4 December 2012 28 April 2013 3497
MARU 3 Melimoyu 19 June 2012 6 December 2012 4077
MARU 4 Melimoyu 6 December 2012 29 April 2013 3492
MARU 5 Northwest
Chiloe 23 January 2012 25 June 2012 3688
Figure 2.
Map of the study area showing the four MARU deployment locations: 1. Northwest Chiloe,
2. Guafo North, 3. Tic Toc Bay, 4. Melimoyu.
Table 1. MARU deployment details: location, start and end date and total hours of recordings.
Unit Location Start Date End Date Total Hours
MARU 1 Guafo North 31 January 2012 17 June 2012 3370
MARU 2 Guafo North
4 December 2012
28 April 2013 3497
MARU 3 Melimoyu 19 June 2012
6 December 2012
4077
MARU 4 Melimoyu
6 December 2012
29 April 2013 3492
MARU 5 Northwest Chiloe 23 January 2012 25 June 2012 3688
MARU 6 Tic Toc Bay
6 December 2012
29 April 2013 3495

J. Mar. Sci. Eng. 2022,10, 316 5 of 18
J. Mar. Sci. Eng. 2022, 10, x FOR PEER REVIEW 5 of 20
MARU 6 Tic Toc Bay 6 December 2012 29 April 2013 3495
Figure 3. Periods of continuous recordings between January 2012 and April 2013 analysed for each
deployment.
2.1. Blue Whale Sound Detection
Acoustic data were analysed as spectrograms using Raven Pro 1.6 (The Cornell Lab
of Ornithology, Ithaca, NY, USA) [47]. Spectrograms were made using the following dis-
play settings: 3 min time axis, 200 Hz frequency axis, DFT = 2048 samples, FFT = 750, 10%
overlap, and Hann window function. Data were then scanned for the presence of blue
whale D and SEP calls using the Raven Pro built-in Band Limited Energy Detector (BLED).
The BLED is a window-box detector that has a set of parameters that describe the targeted
signal. Detector parameters were developed independently for the two types of calls, due
to their different acoustic characteristics, and were tested on a small portion of the data,
tuning each parameter until the performance was considered acceptable. All parameters
set and tuned are reported in Table 2 and descripted in Raven’s user manual [48]. The D
call detector was trained on the full duration and frequency spectrum of the target calls,
and these parameters were relatively variable across D call exemplars. The SEP call detec-
tor targeted both complete calls (Figure 1B, units A, B, C, D) and the end portion of the
call (Figure 1B, red box), which typically had a higher signal to noise ratio (SNR), thus
enabling the detection of fainter calls. Indeed, since many calls had low SNR, the vast
majority of calls were detected through their end portion. During the subsequent visual
auditing (see Section 2.2), all detections that picked up only the end portion with higher
SNR were manually extended to encompass the whole SEP call.
Table 2. Settings of the BLED detector (see Raven’s user manual [48] for descriptions of the param-
eters).
Settings
Parameters D Calls SEP Calls
Min. frequency (Hz) 20 15
Max. frequency (Hz) 110 60
Min. duration (s) 0.4 5.1
Max. duration (s) 3.9 75
Min. separation (s) 0.6 10.1
Min. occupancy (%) 50 62.5
SNR threshold Above 6.0 Above 11.0
Block size (s) 4.5 200.1
Hop size (s) 3.9 24.9
Figure 3.
Periods of continuous recordings between January 2012 and April 2013 analysed for
each deployment.
2.1. Blue Whale Sound Detection
Acoustic data were analysed as spectrograms using Raven Pro 1.6 (The Cornell Lab
of Ornithology, Ithaca, NY, USA) [
47
]. Spectrograms were made using the following
display settings: 3 min time axis, 200 Hz frequency axis, DFT = 2048 samples, FFT = 750,
10% overlap, and Hann window function. Data were then scanned for the presence of blue
whale D and SEP calls using the Raven Pro built-in Band Limited Energy Detector (BLED).
The BLED is a window-box detector that has a set of parameters that describe the targeted
signal. Detector parameters were developed independently for the two types of calls, due
to their different acoustic characteristics, and were tested on a small portion of the data,
tuning each parameter until the performance was considered acceptable. All parameters set
and tuned are reported in Table 2and descripted in Raven’s user manual [
48
]. The D call
detector was trained on the full duration and frequency spectrum of the target calls, and
these parameters were relatively variable across D call exemplars. The SEP call detector
targeted both complete calls (Figure 1B, units A, B, C, D) and the end portion of the call
(Figure 1B, red box), which typically had a higher signal to noise ratio (SNR), thus enabling
the detection of fainter calls. Indeed, since many calls had low SNR, the vast majority
of calls were detected through their end portion. During the subsequent visual auditing
(see Section 2.2), all detections that picked up only the end portion with higher SNR were
manually extended to encompass the whole SEP call.
Table 2.
Settings of the BLED detector (see Raven’s user manual [48] for descriptions of the parameters).
Settings
Parameters D Calls SEP Calls
Min. frequency (Hz) 20 15
Max. frequency (Hz) 110 60
Min. duration (s) 0.4 5.1
Max. duration (s) 3.9 75
Min. separation (s) 0.6 10.1
Min. occupancy (%) 50 62.5
SNR threshold Above 6.0 Above 11.0
Block size (s) 4.5 200.1
Hop size (s) 3.9 24.9
Percentile 20.0 20.0

J. Mar. Sci. Eng. 2022,10, 316 6 of 18
Detector performance was not consistent over different months and deployments
due to background noise, which often partially or entirely masked blue whale calls, in
particular, the shorter and less structured D calls. As it was crucial for the aim of this study
to detect as many calls as possible, we assessed detector performance (see the following
Section 2.2) via manual audits. D call detections were then visually scanned and assigned
to a class of sound quality, using the criteria of Berchok et al. [
49
]: whether the quality of
the signal was sufficient to identify it as a legitimate call, and whether the quality of the
signal was sufficient to provide an accurate estimate of its parameters. High and Medium
quality calls met both criteria but varied in the amount of noise present, with high-quality
calls having the least amount of noise. Low quality calls have low signal-to-noise ratios and
were sometimes recognized only through the presence of other calls nearby; therefore, these
low-quality calls were not used during analysis of acoustic parameters but were included
in diel, seasonal, and geographic pattern analyses. The subset of high-quality detections
was used to define acoustic characteristics of blue whale D calls. We focused on minimum,
maximum, peak and centre frequency, bandwidth (Hz), and duration (s). For SEP calls,
analysis of acoustic characteristics was not performed, as they were already described for
this region by Buchan et al. [27] and Saddler et al. [50].
For each of the six deployments, we audited every other day’s worth of data, for a total
of 447 days (10,728 h, or 15 months) of recordings. We chose this approach as a time saving
measure, rather than analysing the entire data set, and we believe that this sub-sampling
method captured any temporal or geographic patterns in the data. For each deployment,
the first day of the analyses corresponded to the first full day recorded (from 0 a.m. to
24 p.m.) and ended with the last full day recorded.
2.2. Detector Performance
In order to assess detector performance, we first picked three days from each deploy-
ment, one at the beginning, one in the middle, and one towards the end. To determine the
number of false positives, we visually scanned all of the detector’s selections for both D and
SEP calls, and we scanned the entire audio recordings of those days to determine the num-
ber of missed detections. D calls are highly variable in frequency range, making it difficult
for the energy band detector to be consistent among different recordings. In addition, their
short duration make D calls easily masked by other sounds. Conversely, SEP calls have a
more stereotyped acoustic structure and longer duration, enabling the detector to perform
more consistently. Missed D call rate (number of missed detections/total number of de-
tections) for the chosen detector threshold varied from 10 to 27% in different recordings.
False detections of D calls were also highly variable among deployments, and were mainly
caused by anthropogenic and biological noise events (i.e., boat noise and fish sounds) as
well as undefined sounds. False detection rate (number of false detections/total number
of detections) for D calls ranged from 40 up to 97% in the noisiest days and deployments
over the recording period. On the other hand, the missed SEP call rate was consistent at
around 16% in all recordings, while false detections were around 26% of total detections,
although highly variable due to background noise. Due to this extremely high variability in
detector performance, we visually audited the automatic detections for both type of calls,
manually removing false detections and adding missed ones, for all 10,728 h of recordings.
Therefore, while we had to manually check all of the audio files, the employment of the
automatic detector helped to speed up the annotation process as a significant number of
true detections were already selected and we only needed to validate them.
2.3. Analysis of Acoustic Parameters
While SEP calls have a clearly distinctive acoustic structure [
27
,
35
], downsweep calls
can be more difficult to identify with certainty, especially in the presence of vocalizations
from other whale species. Several mysticete species can produce calls similar to blue
whale D calls in terms of frequency range and down-sweeping pattern, including fin
whales (Balaenoptera physalus; 30–100 Hz) [
51
], sei whales (Balaenoptera borealis; 35–100 Hz,

J. Mar. Sci. Eng. 2022,10, 316 7 of 18
occurring in singles, doublets, or triplets) [
52
], and minke whales (Balaenoptera acutorostrata;
50–130 Hz) [
53
]. In an effort to include in our analyses only downsweep (D) calls from blue
whales, we performed a preliminary analysis of acoustic parameters of all detected calls
(low, medium, and high-quality) and excluded detections that had a minimum frequency
lower than 30 Hz, maximum frequency higher than 121 Hz, and a duration shorter than
0.90 s or longer than 3.71 s. These cut-offs were chosen to exclude detections that exceeded
the values for 75% of the calls. While exclusion of these detections may have eliminated
some blue whale D calls with more extreme acoustic characteristics, it likely also reduced
the number of calls from other baleen whale species in our analysis.
2.4. Diel, Seasonal and Geographic Patterns
Day of the year and location of each detection were used to estimate seasonal and
geographic variability of blue whale D and SEP call rates. We report the average number
of each type of call from all MARUs, normalized by the number of MARUs that were
recording each day [
54
]. To explore seasonality, we show the average number of D and
SEP call detections for each deployment site over the whole recording period (January
2012–April 2013). In addition, we calculated the ratio of each type of call for each location
to see whether a certain type of call is more likely to occur in offshore rather than inshore
sites or vice versa.
To study diel calling patterns of Chilean blue whales, call detections were sorted into
four light regimes based on the altitude of the sun: dawn, light, dusk, and night. Dawn
and dusk hours were defined as when the sun was between 12
◦
to 0
◦
below the horizon
(respectively morning nautical twilight to sunrise and sunset to evening nautical twilight);
day hours are between sunrise and sunset, when the sun is more than 0
◦
over the horizon,
and night hours are between morning and evening nautical twilight, when the altitude of
the sun is less than
−
12
◦
. As data were recorded using GMT time zone, detection times
were adjusted for Chilean time (GMT-3/-4) before temporal patterns were analysed.
Daily hours of sunset, sunrise and nautical twilight were obtained using the ‘suncalc’
package [
55
] in R software version 3.6.0 (R Foundation for Statistical Computing, Vienna,
Austria) [
56
] for the coordinates of the study location, corrected to local time. Only days
with at least one detection were used for diel pattern analysis. Daily number of detections
in each light regime was calculated, and divided by the duration of the corresponding
light period for a given day, to account for differences in duration between the four light
regimes. The resulting normalized detection rates (in detections/h) for each light regime
and each day were then adjusted by subtracting the mean number of detections per
hour of the corresponding day (Mean adjusted no. of detections/h) [
10
]. Distributions
of call types in different sites, months, or light regimes were not normally distributed,
so we looked for differences using Kruskal-Wallis tests [
57
]. In cases where there were
significant differences between distributions, post-hoc Wilcoxon pairwise comparison tests
with Bonferroni corrections were used. Statistical analyses were performed using R.
3. Results
In total, 37,141 D and 63,255 SEP calls were automatically detected and manually
verified (see Materials and Methods). We detected 596 high quality, 13,499 medium quality,
and 23,046 low quality D calls.
3.1. D Call Acoustic Characteristics
The acoustic parameters of a subset of 596 high quality D calls are reported in Table 3.

J. Mar. Sci. Eng. 2022,10, 316 8 of 18
Table 3.
Mean, standard deviation (SD), minimum, maximum, and median values for various
frequency parameters (in Hz) and duration (in seconds) of high-quality D calls (n= 596). * Value set a
priori, in order to avoid inclusion of other species’ calls (see Section 2.3 in the Materials and Methods).
Frequency (Hz)
Minimum Maximum Peak Centre Duration (s) Bandwidth (Hz)
Mean 34.9 102.0 58.3 59.2 1.69 37.7
SD 5.94 10.8 13.4 10.1 0.69 10.4
Min 30.0 * 72.3 31.2 35.2 0.90 * 15.6
Max 61.1 121.0 * 113.0 97.7 3.71 * 74.2
Median 32.9 110.0 54.7 58.6 1.54 35.2
3.2. Seasonal Patterns
Due to the lack of consecutive temporal coverage in the recordings, it was not possible
to assess seasonal occurrence of Chilean blue whale calls for all sites. We had recordings
from 10 consecutive months (19 June 2012–28 April 2013) for just one site, Melimoyu.
For this site, we observed a very low number of both call types during winter months
(June–August) and a gradual increase in warmer months, with a delayed peak of SEP calls
over D calls (Figure 4). D calls (Figure 4A) showed a somewhat gradual increase during
spring (September–November) and summer months (December–February), peaking in
January, and decreasing towards fall months (March and April). Other than a peak in June,
which likely carried out from the previous spring, SEP calls (Figure 4B) instead were absent
for most winter and spring months (July–November) and started to gradually increase in
summer and fall months, peaking between March and April.
J. Mar. Sci. Eng. 2022, 10, x FOR PEER REVIEW 8 of 20
The acoustic parameters of a subset of 596 high quality D calls are reported in Table
3.
Table 3. Mean, standard deviation (SD), minimum, maximum, and median values for various fre-
quency parameters (in Hz) and duration (in seconds) of high-quality D calls (n = 596). * Value set a
priori, in order to avoid inclusion of other species’ calls (see Section 2.3 in the Materials and Meth-
ods).
Frequency (Hz)
Minimum Maximum Peak Centre Duration (s) Bandwidth (Hz)
Mean 34.9 102.0 58.3 59.2 1.69 37.7
SD 5.94 10.8 13.4 10.1 0.69 10.4
Min 30.0 * 72.3 31.2 35.2 0.90 * 15.6
Max 61.1 121.0 * 113.0 97.7 3.71 * 74.2
Median 32.9 110.0 54.7 58.6 1.54 35.2
3.2. Seasonal Patterns
Due to the lack of consecutive temporal coverage in the recordings, it was not possi-
ble to assess seasonal occurrence of Chilean blue whale calls for all sites. We had record-
ings from 10 consecutive months (19 June 2012–28 April 2013) for just one site, Melimoyu.
For this site, we observed a very low number of both call types during winter months
(June–August) and a gradual increase in warmer months, with a delayed peak of SEP calls
over D calls (Figure 4). D calls (Figure 4A) showed a somewhat gradual increase during
spring (September–November) and summer months (December–February), peaking in
January, and decreasing towards fall months (March and April). Other than a peak in
June, which likely carried out from the previous spring, SEP calls (Figure 4B) instead were
absent for most winter and spring months (July–November) and started to gradually in-
crease in summer and fall months, peaking between March and April.
Figure 4.
Total number of D (
A
) and SEP (
B
) call detections for 10 consecutive months of recording in
Melimoyu: 19 June 2012–28 April 2013. Color bar represents seasons (blue: winter; green: spring;
orange: summer; yellow: fall).

J. Mar. Sci. Eng. 2022,10, 316 9 of 18
3.3. Geographic Variation
The four deployment sites were spread over a relatively wide area and thus covered
both offshore and inshore locations (Figure 5). In particular, we considered Guafo North
and Northwest Chiloe as offshore sites and Melimoyu and Tic Toc Bay as inshore sites.
There was significant variability in the call production rates among the four sites (Figure 5),
but offshore sites had consistently higher call rates than inshore sites. For D calls, the
normalized number of detections (total number of detections/months recorded) were:
2233 in Guafo North, 3721 in Northwest Chiloe, 380 in Melimoyu, and 276 in Tic Toc Bay.
For SEP calls, the normalized number of detections were: 3626 in Guafo North, 2648 in
Northwest Chiloe, 688 in Melimoyu, and 751 in Tic Toc Bay.
J. Mar. Sci. Eng. 2022, 10, x FOR PEER REVIEW 9 of 20
Figure 4. Total number of D (A) and SEP (B) call detections for 10 consecutive months of recording
in Melimoyu: 19 June 2012–28 April 2013. Color bar represents seasons (blue: winter; green: spring;
orange: summer; yellow: fall).
3.3. Geographic Variation
The four deployment sites were spread over a relatively wide area and thus covered
both offshore and inshore locations (Figure 5). In particular, we considered Guafo North
and Northwest Chiloe as offshore sites and Melimoyu and Tic Toc Bay as inshore sites.
There was significant variability in the call production rates among the four sites (Figure
5), but offshore sites had consistently higher call rates than inshore sites. For D calls, the
normalized number of detections (total number of detections/months recorded) were:
2233 in Guafo North, 3721 in Northwest Chiloe, 380 in Melimoyu, and 276 in Tic Toc Bay.
For SEP calls, the normalized number of detections were: 3626 in Guafo North, 2648 in
Northwest Chiloe, 688 in Melimoyu, and 751 in Tic Toc Bay.
Figure 5. Normalized number of monthly D (red) and SEP (blue) call detections for each site: Guafo
North (A), Melimoyu (B), Northwest Chiloe (C) and Tic Toc Bay (D). Periods shaded in grey indicate
times when no data were collected. Colour bars represent seasons (orange: summer; yellow: fall;
blue: winter; green: spring).
SEP calls were always the prevalent type of call, representing between 61.9–73.1% of
total calls at each site. D calls ranged between 26.9 and 38.1% of total calls at each site
(Table 4).
Table 4. Percentages of call types at each recording site.
Site D Calls SEP Calls
Guafo North 38.1 61.9
Northwest Chiloe 35.4 64.6
Figure 5.
Normalized number of monthly D (red) and SEP (blue) call detections for each site: Guafo
North (
A
), Melimoyu (
B
), Northwest Chiloe (
C
) and Tic Toc Bay (
D
). Periods shaded in grey indicate
times when no data were collected. Colour bars represent seasons (orange: summer; yellow: fall;
blue: winter; green: spring).
SEP calls were always the prevalent type of call, representing between 61.9–73.1% of
total calls at each site. D calls ranged between 26.9 and 38.1% of total calls at each site
(Table 4).
Table 4. Percentages of call types at each recording site.
Site D Calls SEP Calls
Guafo North 38.1 61.9
Northwest Chiloe 35.4 64.6
Melimoyu 35.6 64.4
Tic Toc Bay 26.9 73.1

J. Mar. Sci. Eng. 2022,10, 316 10 of 18
3.4. Diel Patterns
Hourly differences were observed in blue whale D call rates but not SEP call rates for
all recording sites (Figure 6). We observed more D calls during late afternoon, evening,
and night than during early morning and day hours (Figure 6), and these differences were
statistically significant (Figure 7; Kruskal-Wallis,
χ2
= 46.51, df = 3, p-value < 0.001). Dawn
and dusk, dawn and night, day and dusk, and day and night periods were all significantly
different from one another (p< 0.05), while comparisons between dawn and day and
between dusk and night were non-significant (p= 1; = 0.1763—Figure 7A). In contrast,
there were no significant differences in SEP calling rate during different light periods
(Kruskal-Wallis χ2= 3.3264, df = 3, p-value = 0.344—Figure 7B).
J. Mar. Sci. Eng. 2022, 10, x FOR PEER REVIEW 11 of 20
Figure 6. Cont.

J. Mar. Sci. Eng. 2022,10, 316 11 of 18
J. Mar. Sci. Eng. 2022, 10, x FOR PEER REVIEW 12 of 20
Figure 6. Diel distribution of blue whale D (red) and SEP (blue) call detections for each recording
site: Guafo North (A), Melimoyu (B), Northwest Chiloe (C) and Tic Toc Bay (D). Left x-axis shows
hour in Chilean Standard Time (CST); the right x-axis shows the daily total number of calls; y-axis
shows the dates. Circles indicate the numbers of calls per hour, and the circle size is explained in
the legend below the figure. Dark blue shading shows night periods, light blue shading shows twi-
light periods. Grey shading indicates periods of no recordings.
Figure 6.
Diel distribution of blue whale D (red) and SEP (blue) call detections for each recording
site: Guafo North (
A
), Melimoyu (
B
), Northwest Chiloe (
C
) and Tic Toc Bay (
D
). Left x-axis shows
hour in Chilean Standard Time (CST); the right x-axis shows the daily total number of calls; y-axis
shows the dates. Circles indicate the numbers of calls per hour, and the circle size is explained in the
legend below the figure. Dark blue shading shows night periods, light blue shading shows twilight
periods. Grey shading indicates periods of no recordings.

J. Mar. Sci. Eng. 2022,10, 316 12 of 18
J. Mar. Sci. Eng. 2022, 10, x FOR PEER REVIEW 13 of 20
Figure 7. Boxplot of mean-adjusted number of D (A) and SEP (B) call detections per hour during
four light regimes. Lower and upper bounds of whiskers represent lower and upper quartiles re-
spectively. Red lines are median values, blue dots are mean values, and grey dots represent outliers.
Asterisks denote statistically significant differences: * = p < 0.05; ** = p < 0.01; *** = p < 0.001. Note that
means can differ from medians due to outliers.
4. Discussion
Passive acoustic monitoring is one of the most effective and non-invasive tools to
collect data about cetacean occurrence, but data are often not accompanied by visual ob-
servations. Thus, it is impossible to know if more calls are the result of individuals calling
more or a greater number of individuals, and likewise if the absence of calls is due to the
absence of whales or vocal behaviour [58]. Following previous PAM studies [54,59–62],
we assumed that more calls indicate more whales. In addition, we assumed that diel var-
iations in calling rates represent more vocal behaviour from individual whales [63], rather
than movement in and out of these areas. These assumptions must be viewed with caution
until more tag or observational data are collected for this population.
4.1. D Call Acoustic Characteristics
Our measurements of D call acoustic parameters were in close agreement to those
reported by Saddler et al. [50] for a small sample of D calls from tagged whales in the
Chiloense ecoregion. We can thus say that Chilean blue whale D calls typically range from
35 to 102 Hz, and last approximately 1.6 s. Our results also suggest that Chilean blue whale
D calls have a slightly shorter duration than those of other populations: durations have
been reported at 1.8 s for the North Pacific [28], 2 s for the North Atlantic [49], 2.1–2.5 s for
the Southern Ocean [64,65], and 2–4 s for pygmy blue whales of the Indian Ocean [37].
Moreover, Chilean D calls show a wider frequency range compared to most other popu-
lations (North Pacific 39.3–75.7 Hz; North Atlantic: 37.8–88.3 Hz; Southern Ocean: 38–80
Hz) [28,49,64,65], except for Indian Ocean pygmy blue whales (20–100 Hz) [37].
4.2. Seasonal Occurrence of Chilean Blue Whales in the Chiloense Ecoregion
Our data set included only one site (Melimoyu) with consecutive temporal coverage
across four seasons. At this site, very few calls occurred in winter, while call rates gradu-
ally increased toward the summer months. The D call rate started to increase in spring
and peaked in January, during summer, while SEP calls appeared towards the end of
Figure 7.
Boxplot of mean-adjusted number of D (
A
) and SEP (
B
) call detections per hour during four
light regimes. Lower and upper bounds of whiskers represent lower and upper quartiles respectively.
Red lines are median values, blue dots are mean values, and grey dots represent outliers. Asterisks
denote statistically significant differences: * = p< 0.05; ** = p< 0.01; *** = p< 0.001. Note that means
can differ from medians due to outliers.
4. Discussion
Passive acoustic monitoring is one of the most effective and non-invasive tools to
collect data about cetacean occurrence, but data are often not accompanied by visual
observations. Thus, it is impossible to know if more calls are the result of individuals
calling more or a greater number of individuals, and likewise if the absence of calls is due to
the absence of whales or vocal behaviour [
58
]. Following previous PAM studies [
54
,
59
–
62
],
we assumed that more calls indicate more whales. In addition, we assumed that diel
variations in calling rates represent more vocal behaviour from individual whales [
63
],
rather than movement in and out of these areas. These assumptions must be viewed with
caution until more tag or observational data are collected for this population.
4.1. D Call Acoustic Characteristics
Our measurements of D call acoustic parameters were in close agreement to those
reported by Saddler et al. [
50
] for a small sample of D calls from tagged whales in the
Chiloense ecoregion. We can thus say that Chilean blue whale D calls typically range
from 35 to 102 Hz, and last approximately 1.6 s. Our results also suggest that Chilean
blue whale D calls have a slightly shorter duration than those of other populations: dura-
tions have been reported at 1.8 s for the North Pacific [
28
], 2 s for the North Atlantic [
49
],
2.1–2.5 s for the Southern Ocean [
64
,
65
], and 2–4 s for pygmy blue whales of the In-
dian Ocean [
37
]. Moreover, Chilean D calls show a wider frequency range compared
to most other populations (North Pacific 39.3–75.7 Hz; North Atlantic: 37.8–88.3 Hz;
Southern Ocean:
38–80 Hz
) [
28
,
49
,
64
,
65
], except for Indian Ocean pygmy blue whales
(20–100 Hz) [37].
4.2. Seasonal Occurrence of Chilean Blue Whales in the Chiloense Ecoregion
Our data set included only one site (Melimoyu) with consecutive temporal coverage
across four seasons. At this site, very few calls occurred in winter, while call rates gradually
increased toward the summer months. The D call rate started to increase in spring and

J. Mar. Sci. Eng. 2022,10, 316 13 of 18
peaked in January, during summer, while SEP calls appeared towards the end of December
and peaked between March and April, during fall. Thus, the increase and peak of SEP
calls is delayed by about two months with respect to the trend for D calls. Although we
cannot draw conclusions on the seasonality of blue whale presence in the area (due to lack
of consecutive temporal coverage for all sites, as mentioned above) our findings are in
agreement with those of a recent study by Buchan et al. [
45
] (and of Buchan et al. [
30
] on
SEP calls only). Buchan et al. [
45
] described seasonal and geographic variation in D and
SEP calls in relation to zooplankton backscatter and oceanographic variables. As previously
reported, they found that SEP calls were mostly present during the austral summer and fall
months (January–May), peaking in April, while D calls were present between December
and May. The authors found that D calls did not show a clear seasonal pattern, but peaked
twice during this six-month period, and were highly correlated to sub monthly zooplankton
aggregations [45].
Blue whales congregate in mid/high-latitude feeding grounds where high seasonal
density of prey, such as euphausiids, are predictable as result of high primary produc-
tivity [
66
]. The Chiloense ecoregion has proven to be an area with high and strongly
seasonal primary productivity, with a peak in summer [
67
]. The main mesozooplanktonic
species in the area is the euphausiid Euphausia vallentini [
68
], which significantly increases
in abundance between spring and summer (October–December) and reaches a peak in late
summer [
45
,
69
,
70
]. Thus, our observed increase in D call detections during austral summer
follows the pattern of euphausiid abundance, which likely reflects a greater number of
whales in the area when there is more prey. Moderate sub monthly variations in D call
rates (i.e., during fall months; Figure 4A) might be related to short term variations in prey
abundance and patchiness [45,71] or to mating aggregations [43].
The SEP call rate increased later than D calls (January–April; this study, Buchan et al.) [30,45]
.
Due to their patterned sequence, SEP calls are considered a distinct song type from the
southeast Pacific blue whale population [
27
]. While breeding is thought to occur primarily
in winter and spring, occurrence of song in the summer and fall on feeding grounds might
serve to promote pair bonding for the upcoming breeding season or to advertise to oestrous
females, as was proposed for humpback whale (Megaptera novaeangliae) singing behaviour
on feeding grounds [
58
,
72
]. Moreover, the delayed peak of SEP calls over D calls might
suggest that some males have consumed enough prey to enable them to spend more time
singing. In addition, recent evidence of the use of D calls in a reproductive context [
43
]
supports the idea that blue whales do not exclusively forage on feeding grounds, but also
perform a wide variety of social behaviours.
D calls were detected during winter and spring months (June–November) while SEP
calls were absent from the end of June until December. Therefore, it appears that some
individuals, possibly immature females and juveniles, remain in the habitat longer, similarly
to what has been reported for humpback whales [
73
] and Antarctic blue whales [
74
].
Findings from visual, genetic [
75
,
76
], and acoustic studies [
27
] suggest that these whales
migrate thousands of kilometres to reach the winter breeding ground in the Eastern Tropical
Pacific (Costa Rica Dome, Galapagos waters). Undoubtedly, this migration can be extremely
demanding; thus, some animals might skip the migration to diminish energy expenditure
and extend exploitation of food sources on feeding grounds [
73
]. This is especially likely for
juveniles that have not yet reached sexual maturity, and are thus not ready to breed on the
breeding grounds. Indeed, recent studies on mesozooplankton abundance show that the
main euphausiid species in the Corcovado gulf, E. vallentini, is present year-round [
45
,
70
].
The fact that from June to November calls produced only by reproductive males (SEP
calls) were absent, while calls produced by both sexes (D calls) were present, although
very few, supports the idea that some animals may stay in the area to feed. However, we
analysed seasonality at only one site, and there are likely other factors influencing call
production beyond season. As Buchan et al. [
30
] suggested, long-term oceanographic and
passive acoustic datasets are necessary to gain a more comprehensive understanding of

J. Mar. Sci. Eng. 2022,10, 316 14 of 18
how the seasonal presence of blue whales may be linked to oceanographic processes in the
Chiloense ecoregion feeding ground.
4.3. Geographic Variation
Higher detection rates of both call types occurred at offshore (Guafo North and
Northwest Chiloe) vs. inshore (Melimoyu and Tic Toc Bay) sites. One factor that might
affect this difference is that offshore sites might receive signals from a greater area than
inshore sites, and thus may record more distant whales. Alternatively, higher call rates
might reflect that there are more whales foraging offshore [
26
]: food rich areas allow
animals to feed more efficiently and thus spend more time producing calls. Baleen whales
tend to be more abundant where prey availability is greater; offshore sites may have
higher zooplankton biomass because of oceanographic features that cause zooplankton to
aggregate further from the coast [
69
]. However, as our study area was relatively limited in
spatial scale, it is more likely that variability between sites is due to finer-scale patchiness in
euphausiid densities during our study period. Indeed, the preferred blue whale prey in the
area, E. vallentini, is characterized by patchy distributions [
33
,
67
,
69
,
77
]. However, future
studies that combine blue whale acoustic behaviour with concurrent prey measurements
are necessary to assess this hypothesis.
At all sites, SEP calls were more abundant than D calls, accounting for 61–73% of all
detected calls. This might be due to D calls being related to certain contexts, whereas SEP
calls may be produced by whales regardless of activity. This idea is also supported by
the fact that D calls show diel patterns, whereas SEP calls do not (see Section 4.4 below). Our
findings are in agreement with previous studies of other blue whale populations [26,28,37,58]
that found rates of these two call types to be significantly different and song to be the
prevalent call type. Indeed, while songs are produced in series, and a single male can sing
for several hours consecutively [
29
], D calls usually occur with irregular patterns of shorter
duration. However, another likely contributing factor is simply that SEP calls are louder,
and thus travel greater distances than D calls, as reported in previous studies [
45
,
49
]. This
would make sense based on their function as a reproductive advertisement display [
78
].
Thus, SEP call counts may represent whales from a wider range than D call counts do.
Further research is clearly needed to determine the contexts of both call types in different
geographic areas.
4.4. Diel Patterns
For all sites, there was no diel pattern in SEP calls, indicating that males produce these
calls regardless of the time of the day. In particular, we found SEP diel distribution to be
homogenous between seasons, thus not showing any acoustic signature of behavioural
transition as found by Oestreich et al. [11].
In contrast, D call detections were more numerous during dark hours than during
dawn and daytime hours. This may suggest that D calls are associated with zooplanktonic
vertical migration. Most euphausiid species, including Chilean blue whales’ main prey,
E. vallentinii, descend to deeper waters during the day and rise toward the surface at
night [
79
–
81
]. Chilean blue whales may forage more during the day when preys are
aggregated at depth, and feed less during dusk and night hours when prey patches are more
diffuse at the surface. This idea is supported by a recent study by Lewis and Širovi´c [
58
],
in which the use of animal borne tags showed that D calls were mostly produced when
animals were near the surface and rapidly decreased when they were more than 20 m
deep. Thus, as outlined earlier, it appears unlikely that D calls are directly related to
feeding. Payne and Webb [
82
] hypothesized that baleen whale social structure might
consist of a so-called ‘range herd’ in which individuals maintain acoustic contact over
large areas. This ability would free them from the constraint of having to be in a certain
place at a certain time, and individuals could migrate to different areas, for example to
take advantage of different feeding opportunities. The authors also proposed that well-
fed whales vocalize and that hungry whales head towards the greatest source of sounds.

J. Mar. Sci. Eng. 2022,10, 316 15 of 18
Individuals might thus be able to optimize the search for both food and conspecifics in
a patchy environment that may vary seasonally and inter-annually. Therefore, while D
calls function(s) remain unknown, it appears likely that they broadly serve in maintaining
contact with other individuals [
23
,
26
,
43
]. The tonal, downswept nature of D calls may
provide cues for binaural localization, and might be more detectable above background
noise than broadband calls such as SEP calls [
83
]. Use of tonal up-swept or down-swept
calls for locating conspecifics has been shown for right and fin whales [
84
,
85
]; production
of D calls among groups of widely separated blue whales might suggest a similar role [
26
].
However, more acoustic data coupled with visual observations are necessary to confirm
our hypothesis and to understand all the possible behavioural contexts in which these calls
may be used.
5. Conclusions
Knowledge of behavioural contexts of call production, as well as geographic and
temporal variation, are necessary to understand how acoustic communication functions
for a given species. Although other types of data, such as photo-identification, biopsies, or
tagging, would be necessary to gain a more fine-scale understanding of communication,
passive acoustic data can play an important role in the conservation of endangered species.
PAM can provide information about geographic and seasonal distributions in regions
that are difficult to monitor visually. Our results provide insights into the behaviour and
ecology of Chilean blue whales at different temporal scales, which could inform future
passive acoustic monitoring efforts by suggesting when they would be most effective. In
addition, these results provide a better understanding of when, where, and possibly how
these different call types are used by Chilean blue whales.
Author Contributions:
L.R. and L.S. conceived the study and wrote the paper; L.R. performed
the formal analysis and developed the methodology and visualization; L.R. and S.M.W. tuned the
parameters of the automatic detector and carried out the investigation on the original recordings; R.L.
provided the resources and funding for the field work expeditions; L.S. supervised and administrated
the project and cured the data. All authors have read and agreed to the published version of
the manuscript.
Funding:
Financial support for expeditions, deployments, and retrievals of MARUs, and for some
of the data analysis, was provided by Fundacion MERI, Av. Pdte. Kennedy 5682, Vitacure, Región
Metropolitana, Chile. The data analysis for this study was carried out without external funding.
Institutional Review Board Statement: Not applicable.
Informed Consent Statement: Not applicable.
Data Availability Statement:
The data presented in this study are openly available in WHOAS repos-
itory [https://hdl.handle.net/1912/27919] (accessed on 13 January 2022), doi:10.26025/1912/27919.
Acknowledgments:
Thanks to Rodrigo Hucke-Gaete, Susannah Buchan, and the Centro Ballena Azul
for their participation in the expeditions to deploy MARUs, and to Fundacion MERI for providing
financial support for the deployments, as well as for some data analysis. We also thank Thomas Montt,
Sociedad Pesquera y de Turismo Marítimo Los Elefantes Ltd.a., Pedro Montt 215, Dalcahue—Chiloe,
Chile, for his support (and that of his crew) in cruise logistics, and for deploying and retrieving
instruments. Finally, thanks to Alessandro Bocconcelli for support in project logistics, to Songhai Li
for his support in the publication of this paper, and to Thomas Uboldi for his continuous support to
our research.
Conflicts of Interest: The authors declare no conflict of interest.
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