Passive acoustic monitoring of marine mammals in South Africa, with special reference to Antarctic blue whales

Abstract

Marine mammals, and in particular Antarctic blue whales, represent an important predator component of marine ecosystems. These mammals are considered to be critically endangered due to unsustainable whaling practices in the previous century. Currently, it is also difficult to monitor the species’ population recovery through the use of sighting surveys. Passive acoustic monitoring (PAM) can be used to research Antarctic blue whales because they are quite vocal and can be detected over long distances through the use of this technology. PAM also has considerable application potential to other baleen species that reside in South African waters, including fin whales (Balaenoptera physalus). It is, however, still an emerging
methodology in South Africa and a number of challenges need to be addressed before it reaches the same level of maturity as visual surveys in South Africa and around the world.

Full text

2014
Published by: The Council for Scientific and Industrial Research
Pretoria, South Africa
www.csir.co.za
Funded by: The South African Maritime Safety Authority
The Department of Science and Technology
EDITORS: Nikki Funke • Marius Claassen • Richard Meissner • Karen Nortje
Reflections on the State of
Research and Technology
in South Africa’s
Marine and Maritime Sectors

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Reflections on the State of Research and Technology in South Africa’s Marine and Maritime Sectors
Chapter 8 Passive Acoustic Monitoring of Marine
Mammals in South Africa, with Special
Reference to Antarctic Blue Whales
Fannie W. Shabangu and Ken Findlay
1. Introduction
Marine mammals are an important predator component of marine ecosystems, both through
the transfer of nutrients in and between various elements of the ecosystem, and through the
ecosystem roles they play in the top-down forcing of the system structure (Huang et al., 2011;
Leaper and Miller, 2011). Antarctic blue whales (Balaenoptera musculus intermedia) are one
of the top predators that feed directly on the low-trophic-level prey in the krill-based trophic
ecosystem of the Southern Ocean (Nicol et al., 2008).
There are four supposed blue whale subspecies that occur in different oceans (Jefferson et al.,
1993; Bannister, 2002; Best, 2007). These are the northern hemisphere blue whale
(B. m. musculus) (Linnaeus, 1758), the Antarctic blue whale (B. m. intermedia) (Burmeister,
1871), the pygmy blue whale (B. m. brevicauda) (Ichihara, 1966) and the Indian Ocean
blue whale (B. m. indica) (Blyth, 1859). However, presently, only the first three subspecies are
recognised internationally (Reeves et al., 1998; Jefferson et al., 1993; Best, 2007), as there is
a broad uncertainty in morphologically distinguishing B. m. indica from other subspecies. It is
therefore considered an approximate synonym of B. m. brevicauda (Reeves et al., 1998; Rice,
1998). The Antarctic blue whale is the biggest of the blue whale subspecies, growing up to
30 metres and weighing up to 163 metric tons (Mackintosh and Wheeler, 1929; Best, 2007).
Blue whales have a cosmopolitan distribution, although they do not frequent coastal low-
latitude waters (Mackintosh and Wheeler, 1929; Best, 2007). Antarctic blue whales are widely
distributed in the southern hemisphere (Best, 2007; Širovic et al., 2009; Samaran et al., 2013).
Like other large Southern Ocean baleen whales, the majority of Antarctic blue whales migrate
seasonally between summer high-latitude feeding grounds and winter breeding grounds in
low-latitude waters, although the exact locations of such breeding grounds remain unknown
(Jefferson et al., 1993; Best, 2007; Double et al., 2014). It has been shown from passive
acoustic monitoring (PAM) studies that not all Antarctic blue whales migrate to the so-called
‘overwintering/breeding grounds’ in the mid and low latitudes (Stafford et al., 2004), since some
individuals remain in the feeding ground at the high latitudes all year round (Širovic et al., 2009;
Samaran et al., 2013). Then again, some individuals vocalise all year round on the breeding
grounds (Stafford et al., 2004; Širovic et al., 2009; Samaran et al., 2013).
Antarctic blue whales primarily filter feed on zooplankton prey, chiefly Antarctic krill (Euphausia
superba) (Best, 2007; Branch et al., 2007). Little or no feeding is thought to occur during winter
migrations and their distribution during the austral summer is particularly determined by prey
distribution (Best, 2007; Branch et al., 2007). Year-round passive acoustic recordings show that
Antarctic blue whales might be feeding on their breeding grounds and move in between regions
in a season, possibly to make use of available food resources in those regions (Samaran et al.,
2013).

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The International Union for the Conservation of Nature (IUCN) considers the Antarctic blue whale –
which was once considered to be one of the most abundant large whale species (Clapham
et al., 1999; Clapham and Baker, 2002) – to be Critically Endangered. This is due to their heavy
exploitation through whaling during the last century (Klinowska, 1991, Jefferson et al., 1993; Rice,
1998; Clapham et al., 1999). Based on catch statistics (Figure 1a), it is clear that Antarctic blue
whales were harvested at unsustainable rates that exceeded the maximum sustainable yield (MSY)
by great margins (Best and Ross, 1989). With some 360 000 blue whales caught in the southern
hemisphere during the last century (Clapham and Baker, 2002), Branch et al. (2004) estimated in
1996 that modern whaling had reduced the Southern Ocean blue whale population from a pristine
239 000 (95% interval 202 000 to 311 000) to a low of 360 (150 to 840) animals (Figure 1b) before
being protected by the International Whaling Commission (IWC) in 1964. Currently, it is estimated
that 1% to 3% of the pristine Antarctic blue whale population remains. The population is estimated
to increase at a rate of 7.3% (1.4% to 11.6%) per annum (Branch et al., 2004).
Figure 1: Multi-decadal patterns of catches (a) and abundance estimated by logistic models (b) of the Antarctic blue
whale in the southern hemisphere showing the discovery, exploitation and subsequent collapse of the species (adapted
from Branch et al., 2004).
It is currently difficult from sighting surveys to monitor the population recovery of the Antarctic
blue whale, which was so extensively decimated by commercial whaling (Branch et al., 2007).
The difficulty with sighting surveys is that trained observers can only see Antarctic blue whales
for a short period of time when these mammals surface to breathe, and those sighting surveys
can only be done in adequate daylight during good weather conditions (Mellinger and Barlow,
2003; Thomas and Marques, 2012). Such monitoring ideally requires an absolute abundance or
at least a relative abundance estimation over a sufficiently long period for a population trend
estimation to be apparent over the confidence limits of the abundance estimates (Buckland
and York, 2002; Branch et al., 2007).
Absolute abundance is the actual number of whales estimated in a spatial unit, while relative
abundance gives the relative indices of abundance, which may be used to estimate trends
when constant proportions of the population are estimated each year (Buckland and York,
2002). Abundance estimations of Antarctic blue whales have been and still are centred on
visual line-transect surveys or mark-recapture methodologies (Oleson et al., 2007; Kelly et al.,
2012), both of which may be subject to costly and logistically difficult research operations
(Buckland and York, 2002; Kelly et al., 2012; Thomas and Marques, 2012). Furthermore, factors
affecting the reliability of data (for example, limited population sizes, and the surfacing or
aggregation behaviour of the Antarctic blue whale) and factors affecting data collection (for
example, weather or sighting conditions) may increase the confidence limits of estimates
compromising the required data to estimate population trends in the Southern Ocean (Branch
et al., 2004; Branch et al., 2007; Kelly et al., 2012).

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PAM can be used to estimate the relative abundance of vocalising animals as Antarctic
blue whales are particularly vocal. It can also be used to provide information on behaviour
and distribution. The use of PAM to estimate Antarctic blue whale abundance is an emerging
methodology and a number of issues still need to be addressed before the method will be as
mature as visual surveys in South Africa and worldwide. The South African Blue Whale Project
(SABWP) is an initiative of the Mammal Research Institute’s Whale Unit based at the University
of Pretoria, which aims to investigate the distribution and relative abundance of the Antarctic
blue whale using both sighting survey and PAM methods. The SABWP conducts research over
a range of spatial and temporal scales, which contribute to the international management
and conservation of these marine mammals. However, relatively low levels of PAM research
have been done in South Africa. The work of the SABWP is pioneering many of the deep-water
PAM studies to follow. In this chapter, a remote and autonomous acoustic method is presented
that can provide indices of relative abundance and therefore population trends of marine
mammals, with particular reference to Antarctic blue whales as the most severely depleted
large whale species that occurs in South African waters. It should be noted that PAM has
considerable application to other baleen species that occur in South African waters, including
fin whales (B. physalus).
2. Sound in the sea
Acoustics research is the science that examines the physical properties of sound. The research
into sounds produced by living organisms is often referred to as bioacoustics (Au and Hastings,
2008). The ocean is by no means a quiet environment. Sounds are produced by a number of
sources, including the following:
x Natural events, such as rain, wind, seismic events or ice (Urick, 1983; Au and Hastings,
2008; Zimmer, 2011)
x Marine animals that are often very vocal and produce diverse loud and/or soft sounds
(Urick, 1983; Zimmer, 2011)
x Man-made noise sources, such as shipping or other anthropogenic activities (Urick, 1983;
Au and Hastings, 2008)
Urick (1983) states that, as early as 1490, Leonardo da Vinci discovered that “If you cause your
ship to stop, and place the head of a long tube in the water and place the outer extremity
to your ear, you will hear ships at a great distance from you.” It was therefore from this rather
simplistic observation that modern hydrophones and transducers were developed to study and
explore the marine world (Urick, 1983; Simmonds and MacLennan, 2005).
Sound comprises waves of energy moving through a medium as oscillations of particles in
that medium. Important characteristics of a sound include its frequency, or rate of oscillation,
which is measured in Hertz (Hz), period (the duration of an oscillation cycle in seconds (s))
and wavelength (the length of a single oscillation in metres). A decibel (dB) is the unit of
measurement of the acoustic intensity of a sound. Acoustic energy is the energy in a sound
wave. The power of a wave is the energy measured over a period of time. Acoustic intensity
is the acoustical power per unit area in the direction of propagation. The energy, power
and intensity of a sound wave are proportional to the mean square pressure. Acousticians
consequently refer to ratios of pressure or pressure squared, using a standard reference

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pressure against which sounds can be measured. A reference pressure of 1 μPa is used for
water, whereas 20 μPa is used for air.
When comparing the relative intensities of two sounds, the responses are logarithmic, which is
why sound intensities (I) are measured on a logarithmic scale (in decibels) as:
Intensity _ levels(dB)=10log I
I0 (1)
where I0 is the reference intensity.
As intensity is proportional to pressure squared, the sound pressure level (SPL) of sound
pressure (P) is defined as:
SPL(dB)=20log P
P0 (2)
where P0 is the reference pressure, e.g. 1 μPa for water.
The principles applied in acoustics are similar to those applied in light, since both physical
processes are subject to absorption, reflection and scattering. Both comprise energy waves that
travel through a medium and follow elementary laws of physics (Mobley, 1994; Simmonds and
MacLennan, 2005). However, the heterogeneous properties of water disrupt the basic linearity
principle of a perfect wave transmitting energy through a homogeneous ‘lossless’ medium
explained in most physics textbooks (Mobley, 1994; Simmonds and MacLennan, 2005). Thus,
electromagnetic, thermal, light, chemical and other forms of energy attenuate very quickly
in turbid waters due to scattering and absorption (Urick, 1983; Tyack and Miller, 2002; Au and
Hastings, 2008). Providentially, sound propagates faster and weakens less in water than in air
(Tyack and Miller, 2002).
3. Acoustic research of marine mammals
Sound is important to marine mammals as they use it for communication, searching for prey,
navigation, and to avoid unfavourable conditions or predators (Purves, 1967; Kenshalo, 1967;
Tyack, 1998; Tyack, 1999; Sears, 2002; Mellinger and Clark, 2003; Simmonds and MacLennan,
2005; Zimmer, 2011). Consequently, many marine mammals have evolved hearing and
mental capacity to detect and interpret acoustic signals with good sensitivity and accurate
localisation of the waterborne sound (Ketten, 1992; Ketten 1994; Au and Hastings, 2008) and
many have specialised sound-generating organs (Kenshalo, 1967; Frankel, 2002; Au and
Hastings, 2008). However, the hearing sensitivities of marine mammals are generally not well
studied, with best hearing sensitivities often assumed around the frequencies at which the
animal vocalises (Ketten, 1992; Ketten, 1994; Frankel, 2002).
Several balaenopteridae species of mysticete (or baleen) whales produce high-energy, low-
frequency (< 100 Hz) or infrasonic (< 20Hz) sounds (Ketten, 1992; Ketten, 1994; Sears, 2002;
Mellinger and Clark, 2003; Au and Hastings, 2008; Zimmer, 2011). Antarctic blue and other
baleen whales have larynxes like humans, but unlike humans, lack vocal cords to produce
sound, thus these mammals are presumed to recycle air in their bodies (presumably the lungs) to
vocalise (Frankel, 2002; McDonald et al., 2009). Antarctic blue whales and other baleen whales
use sound for “long range contacts, assembly calls, sexual advertisement, greeting, spacing,
threat and individual identification” (Dudzinski et al., 2002). Odontocetes (toothed whales and
dolphins) produce higher-frequency (ultrasonic) whistles and broadcast clicks using the upper
portion of the head, called the dorsal bursae, and the nasal passage, called the phonic lips,

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while directing the sound through the melon that combines vibrations produced by both the
dorsal bursae and phonic lips (Frankel, 2002). Whistles are used mainly for social interaction and
clicks for echolocation (Au and Hastings, 2008). Non-cetacean marine mammals like seals
are said to produce underwater sounds comparable to those of their terrestrial relatives via the
vibrations of their throats without emitting air through their mouths (Frankel, 2002).
3.1 Applications of passive acoustic monitoring
The use of passive acoustic techniques for estimating the abundance, behaviour and
distribution of marine mammals has many advantages over the conventional abundance
estimation methods (Urick, 1983; Simmonds and MacLennan, 2005; Au and Hastings, 2008;
Zimmer, 2011). Models of Peel et al. (2014) depicted the fact that real-time acoustic tracking
can result in increased encounters and subsequent photographic captures of Antarctic
blue whales by two to four extra times compared to conventional visual transect surveys.
Furthermore, based on the modelling of sighting rates, Kelly et al. (2012) argue that the
sole utilisation of the line-transect survey design is not the best method of estimating the
circumpolar abundance of Antarctic blue whales, but that mark-recapture using acoustics as a
supplementary tool would provide better results. For instance, some areas might be logistically
difficult for sighting surveys because they are remote, not accessible to direct observation, too
expensive or difficult to survey (Best, 1993).
PAM can be used as a cost-effective method to monitor and track both the population and
individuals in such areas (McDonald et al., 2006a; Mellinger et al., 2007; Van Parijs et al., 2009;
Marques et al., 2013). PAM can be carried out as real-time or archival, manual or autonomous
operations over a considerable duration (Van Parijs et al., 2009). Recording equipment can
be mounted on stationary platforms, such as oceanographic moorings, or on moving/drifting
platforms, such as research vessels or wave gliders (Bobbitt et al., 1997; Boisseau et al., 2008;
Baumgartner et al., 2013). Real-time PAM has been conducted as part of the Listening to the
Deep Ocean Environment (LIDO) project (André et al., 2011) and, more recently, from ocean
gliders (Baumgartner et al., 2013). Digital acoustic recording tags (DTAGs) are used to monitor
the behaviour of marine mammals and their response to sound stimuli, as archival sensors
onboard the suction cup tags measure the dive cycles, 3D orientation and movement of the
animals (Tyack, 2011). Instruments of this kind are unavailable in South Africa and the SABWP
aims to conduct such research in the near future.
Sonobuoys are sound-receiving buoys primarily used by the military to detect submarines,
and relay detected sounds to research platforms via ultra-high frequency (UHF) or very high
frequency (VHF) transmission (Zimmer, 2011). These have been utilised in PAM whale research
(McDonald, 2004; Rankin et al., 2005; Oleson et al., 2007; Miller et al., 2012; Miller et al., 2014a;
Miller et al., 2014b). Sonobuoys with differential frequency analysis and ranging (DIFAR) enable
estimations of the vocalising marine mammal’s bearing relative to the sonobuoy and the
surveying research vessel that can be used to track the animal in real time (McDonald, 2004;
Rankin et al., 2005; Oleson et al., 2007; Miller et al., 2012; Miller et al., 2014a). The advantage
of this type of sonobuoy is that acoustic research can be conducted simultaneously with visual
surveys, for example, to improve the probabilities of encountering vocalising and non-vocalising
animals for abundance estimation (Rankin et al., 2005; Oleson et al., 2007; Miller et al., 2012;
Peel et al., 2014).

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The abovementioned acoustic research techniques have particular advantages and
disadvantages. Their choice of use is often specific to sites or species. For example, acoustic
recorders towed behind research vessels may be limited to large baleen whales, as the
low-frequency calls of whales are masked by the underwater noise of the ship’s propellers
at the same frequency (5 Hz to 500 Hz) (Au and Hastings, 2008). However, these recorders
are particularly valuable for the monitoring of odontocete cetaceans that vocalise at a high
frequency, such as sperm whales (Physeter macrocephalus) (Thode, et al., 2002; Mellinger et
al., 2003).
3.2 Factors determining the detectability of marine mammal sounds
The speed of sound in seawater is approximately 1 500 m s-1. When assuming constant
temperature and increasing static pressure, this speed will increase by 1% for each 1 000 m of
depth, while a 1 °C increase in temperature will result in a 2% increase in sound speed (Rossing,
2007). Sound refraction and reflection occur at both the surface and the seafloor due to sound
speed changes, with these directional changes resulting in waveguides at different ocean
depths (Urick, 1983; Simmonds and MacLennan, 2005; Rossing, 2007). Sound transmitted in
both the upward and downward angles tends to propagate towards the minimum sound
velocity region from its source and refract towards the depth of its source (Urick, 1963; Rossing,
2007; Au and Hastings, 2008). During World War II (1939 to 1945), Ewing and Worzel (Urick, 1963)
discovered a deep sound channel in which sound waves could travel long distances. This
channel is known as the sound fixing and ranging (SOFAR) channel (Urick, 1963; Urick, 1983;
Medwin and Clay, 1998; Rossing, 2007). The SOFAR channel occurs at shallower depths in
high latitudes and at deep depths in low latitudes due to sound waves bending towards the
lower sound velocity region caused by the temperature or depth profile (Urick, 1983; Rossing,
2007; Au and Hastings, 2008). Antarctic blue whales and other baleen whales are known to
use the SOFAR channel for transmitting sounds over great distances, since the sound at this axis
encounters the least geometric spreading loss compared to surface or bottom reflection (Urick,
1983; Au and Hastings, 2008; Samaran et al., 2010b).
During World War II, military engineers developed the sound navigation and ranging (sonar)
equation (Equation 3), with the aim of determining the maximum range of sonar equipment
(Urick, 1983). The sonar equation models the functions of source level, transmission loss and
received levels over the sound travel path (under the source-path-receiver model introduced
earlier). Numerous parameters that affect the performance of the underwater sonar model
were therefore conveniently and logically merged into small units in the sonar equation. In
turn, the equation accommodates the effects of the propagation medium, target and the
equipment itself (Urick, 1983). In a biological context, the sonar equation therefore addresses
the acoustic energy reception in the animal’s in situ setting (Urick, 1983; Tyack, 1998; Au and
Hastings, 2008). Given that the aim of research relating to PAM is to listen to sounds produced
by animals, biologists are primarily concerned with the transmission loss from the animal of
interest (Tyack, 1998; Au and Hastings, 2008).
The simple passive acoustic sonar model of evaluating sound propagation in water is
measured in dB re 1 μPa as:
RL=SL–TL (3)
where RL is the received level, SL is the source level at 1 m from the source and TL is the
transmission loss.

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The intensity levels of acoustic signals weaken as sound propagates farther from the source
through a medium due to transmission loss caused by spreading, absorption, scattering,
reflection and rarefaction (Urick, 1983; Tyack, 1998; Swift, 2004). The majority of energy in any
given acoustic wave is concentrated at the centre of the sound source, hence, as the sound
propagates to a range (r), the acoustic energy will be spread in all directions over the sphere’s
area of 4ʌU2 (Tyack, 1998; Swift, 2004). Thus, the signal intensity is expected to decrease
exponentially with distance from the calling animal or sound source. This is called spherical or
geometrical spreading (Tyack, 1998; Lurton, 2002; Swift, 2004; Simmonds and MacLennan,
2005).
The transmission loss due to spherical spreading is calculated as follows:
TL= alogr =10log I
Iref
=10log ʌU2
ʌU2ref
= 20log r
rref
(4)
where a is the environment-dependent absorption coefficient, I is the intensity of the signal,
and Iref is the intensity at the reference source. For the Southern Ocean, a is estimated to be
17.8 dB/m under spherical spreading considerations (Širovic, et al., 2007). For South Africa,
a is undetermined, but it should be much less than 17.8 dB/m as the water is warmer around
the coast.
Spherical spreading assumes that sound propagates through a uniform or homogenous
environment (Swift, 2004) and occurs until the sound hits a boundary with a different acoustic
property, such as the sea surface, seafloor or waters of different densities, where the sound
waveform will refract in a plane according to Snell’s Law and cylindrical spreading results (Tyack,
1998; Swift, 2004). In such cylindrical spreading, the sound energy spreads in a cylindrical
fashion over the cylinder’s cross-sectional area of, 2ʌUwhere the sound energy will not be
restricted by planes. The cylindrical spreading is therefore calculated in the form of:
TL=10log I
Iref
=10log ʌU
ʌUref
= 10log r
rref
(5)
While the spreading of sound in the water column defined in Equation 4 and Equation 5
weakens the acoustic signal, the conversion of sound to heat results in further loss of sound.
This is known as absorption or attenuation (Tyack, 1998; Lurton, 2002, Shabangu et al., 2014).
However, Tyack (1998) agrees with Cummings and Thompson (1971) that, for species like
Antarctic blue whales, no significant absorption loss should be encountered as these animals
transmit acoustic signals at very low frequencies, for example, less than 1 dB per 100 m will be
lost to absorption for a 100 Hz frequency signal.
As established in Equation 3, the ability of a hydrophone to detect an animal’s call depends on
the received noise levels (NL) (Tyack, 1998; Au and Hastings, 2008). NL is expressed in
dB re 1 μPa2/Hz (Swift, 2004; Au and Hastings, 2008). Therefore, the modified passive acoustic
sonar equation will take the following form:
DT=SL–TL–(NL–DI) (6)
where DT is the detection threshold (dB) and will obviously vary for each animal species, and
DI is the directivity index of the receiving hydrophone (measured in degrees) relative to the
direction of the vocalising animal from the hydrophone.

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Au and Hastings (2008) propose that, provided marine mammals have a specific acoustic
detection system with a boundary specified by a direct filtering bandwidth, Equation 6 could
be revised to incorporate the filter effects in the sonar equation to fit the new measurement
system as follows:
DTA= 6/±7/±1/±',¨ƒ) (7)
where DTA is the new detection threshold of the system and ¨ƒ is the filter bandwidth of the
system.
This is calculated as follows:
¨ƒ= 2n–1
2n/2ƒc (8)
where n is 1/3, 1/2, or 1 for a 1/3-octave, 1/2-octave, or 1-octave band, respectively. Octave
bands are commonly utilised sets of frequency bands with ƒc (the centre frequency of
the band). A one-octave bandwidth has an upper band frequency twice the lower band
frequency, while a one-third octave band is a frequency band where the upper band-edge
frequency is the lower band-edge frequency multiplied by the cube root of two.
Au and Hastings (2008) further explain that if DTA equals zero, the mammal hearing system
would only detect the signal half the time due to equal intensities between the received signals
and received ambient or background noise. This defines the animal’s auditory system critical
ratio. However, a DTA of 3 dB would enable the animal to easily detect a signal because
the signal intensity will be twice as strong as the ambient noise intensity. This principle can also
be applied to acoustic systems to determine the transmission loss that can be tolerated by a
hydrophone without missing any signal detections (Tyack, 1998; Au and Hastings, 2008).
Marine mammals can tolerate transmission loss to a certain degree where they can hear a
signal. The transmission loss threshold is calculated as follows:
TL=SL–(NL–DI+10log¨ƒ) (9)
Following the computation of the amount of transmission loss an animal can tolerate in
Equation 9, the probability of a signal being detected can be mathematically computed as
the signal-to-noise ratio (SNR) expressed in a subtraction form:
SNR=RL–NL (10)
SNR is not only determined by RL, but also by external environmental noise and any internal
noise in the receiver (Tyack, 1998).
The source level, frequency and bandwidth of a call are the most crucial acoustic parameters.
However, their significance is determined by the transmission range and ambient noise (Tyack,
1998; Xiaohong et al., 2012). For a receiver (hydrophone or sonobuoy) to receive the most
prominent SNR, an animal must transmit sound at a carrier frequency and bandwidth of
the receivers’ detection capabilities (Xiaohong et al., 2012). The receiver can therefore be
designed to correspond with the frequency and time characteristics of the animal of interest,
and if the receiver bandwidth is tuned effectively to fit the signal bandwidth, the noise spectrum
level outside the frequency range of interest will be reduced (Tyack, 1998). Building on from the
octave bands in Equation 9, the frequency band (W) among the ambient noise spectrum
levels of the energy and at distinct frequencies can be calculated in the following form:

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Band_level = Spectrum_Level+10logW (11)
For the minimisation of the integration effects of signals throughout a given time period within a
given receiver, the integration time must be well matched to the duration of an animal signal
(Tyack, 1998). For example, a fin whale can produce an infrasonic pulse that lasts for 1 second
and contains 20 cycles (Tyack, 1998).
Therefore, if the receiver integration time (tint ) is longer than a given short pulse (tpulse), the
following equation will reduce the effective source level of the sound signal (SLeff ):
SLeff = SL +10log tpulse
tint
(12)
The SLeff is important to determine the detection range and the distance the sound will travel.
Another factor that determines the detection range or source level of the vocalisation is the size
of the animal. Bigger animals will generally produce higher-intensity sounds (Tyack, 1999).
3.3 Antarctic blue whale density estimation
Although challenging, once factors affecting the detectability of a signal are addressed and
considered, the estimation of Antarctic blue whale density based on PAM is possible if both
the cue rates per individual and group sizes are known (Marques et al., 2013). PAM density
estimation is an ongoing research area, with working algorithms required for each vocalising
species based on the species’ acoustic behaviour (Thomas and Marques, 2012). Density (D)
is generally defined as the number of animals in a given area, and calculated by the following
formula:
D= n
a (13)
where n is the whale number/count, and a is the survey area. Given that the area surveyed
by the recording instrument is known for the assumed source level, the abundance can be
estimated from density as n=D x a (Marques et al., 2009). Since n detected in the area a is
now known, the abundance ( ) can be estimated as:
= n
a (14)
where is the probability of a whale sound being detected by the PAM recorder, which is
dependent on source and noise levels as shown above in Section 3.2.
The estimated density of blue whales over time (t ) can be determined from PAM by
upgrading Equation 14 through the consideration of further parameters:
t = nc(1–ƙ
.ʌZ2T (15)
where nc is the number of calls, ƙ is the estimated amount of false positive detections, K is the
number of replicate recorders used, Z is the distance away from the recorder where vocalising
whales are assumed not to be detected, T is the time, and is the estimated call rate.
Thomas and Marques (2012), Marques et al. (2009) and Marques et al. (2013) provide methods
of estimating cetacean density from PAM data collected through arrays of hydrophones. Call

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rates, sound propagation and the frequency and source level of calls are important for the
determination of blue whale density. PAM data recorded through DIFAR sonobuoys during the
IWC’s International Decade of Cetacean Research (IDCR) and Southern Ocean Whale and
Ecosystem Research (SOWER) cruises have bearing on detected calling animals, but single
instruments were usually deployed at the time. Thus, the above density estimation mechanisms
are adequate for experiments with replicates extending to large spatial and temporal scales.
These are also applicable to a single recorder, while some additional errors are introduced
(Kusel et al., 2011, Thomas and Marques, 2012; Marques et al., 2013).
3.4 Antarctic blue whale calls
Blue whales are a good example of a sound producer with high source levels (around
188 dB re 1 μPa at 1 m) (Cummings and Thompson, 1971; Au and Hastings, 2008). Source levels
are determined using the above equations. Antarctic blue whales are the loudest blue whale
subspecies with a mean source level of 189±3 dB re 1 μPa at 1 m over the 25 Hz to 29 Hz range
(Širovic et al., 2007). However, there is a spread on the reliability of measurements of the source
levels for Antarctic blue whales. Samaran et al. (2010a) reported source levels of
179±5 dB re 1 μPa at 1 m over frequencies of 17 Hz to 30 Hz. The most recent preliminary source
level measurements by Miller et al. (2014a) are 182 to 185±2 dB re 1 μPa over 25 Hz to 29
Hz. Antarctic blue whales produce two types of calls that are both frequency- and amplitude-
modulated, namely ‘Z’ and ‘D’ calls (Figure 2 and Figure 3). The frequency of frequency-
modulated calls changes over time (Frankel, 2002). Individual units of stereotypical patterns
of frequency-modulated sounds are called ‘calls’ and the repetitive sequence of stereotyped
three-unit low-frequency calls are called ‘songs’ (Rankin et al., 2005; McDonald et al., 2006a). The
Z call is so named because the shape of the call resembles the English alphabetic letter ‘Z’ when
viewed on the spectrogram (Figure 2b). The Z call is only produced by Antarctic blue whales and
is presumably used by males to find mates.
McDonald et al. (2006a) found that these highly vocal cetaceans produce population-specific
sounds, and identified nine song types of blue whales from around the world. Subsequently,
other blue whale song types have been identified elsewhere in the world since this study (Miller
et al., 2014b). Antarctic blue whales’ Z calls are characterised by the distinct long-duration
(8 to 12 seconds), 28 Hz first tonal sounds (Figure 2b1), followed by a second relatively short-
duration (2 to 5 seconds) sound downsweeping from 28 Hz to 19 Hz (Figure 2b2). A third
component is an 8- to 12-second (Figure 2b3) slightly frequency-modulated tone between
20 Hz and 18 Hz (Ljungblad et al., 1998; Rankin et al., 2005). This call is also believed to be a
contact call usually produced intermittently by a single whale or a pod of travelling whales
(Edds-Walton, 1997; McDonald et al., 2006a). The average intercall interval (pause time
between calls) in a series of calls is estimated to be 48.5±2.8 seconds for Antarctic blue whales
(Stafford et al., 2004). A decline in the tonal frequencies of this Antarctic blue whale song has
been observed lately (McDonald et al., 2009).

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Figure 2: A typical Antarctic blue whale Z call illustrating the wave form amplitude modulation (a), with the corresponding
frequency modulation and duration of each unit of this three-unit call (b). The 28 Hz unit is the high-energy component of the
call as it has the highest amplitude compared to the other two components of the call as shown by the amplitude values. The
amplitude is presented here in a thousand unit, also known as a kilo unit (kU), of the dimensionless sample values. Data was
collected during the 2001/02 IWC SOWER cruise. [See colour figure on page 313.]
Sound produced at these low frequencies can travel hundreds to thousands of kilometres from
the source, but these low-frequency sounds are susceptible to noise due to less target definition
and separation (Urick, 1983; Rossing, 2007; Zimmer, 2011; Miller et al., 2012). The frequency
range of the signal transmits useful information from the transmitter to the recipient (Tyack and
Miller, 2002; Au and Hastings, 2008).
Only male Antarctic blue whales are thought to sing (Z calls) and little is known about female
blue whale vocalisation (Tyack, 1998; McDonald et al., 2001; McDonald et al., 2006a; Samaran
et al., 2013). However, Oleson et al. (2007) observed that both sexes of northern hemisphere
blue whales vocalise during feeding, producing a call more variable in duration and frequency,
called the D call. Antarctic blue whales’ D calls are shown in Figure 3. This higher-frequency call
is likely used for short-distance communication, and could be used to advertise the presence
of food to conspecific animals. D calls range in frequency from 22 Hz to 106 Hz (Thompson
et al., 1996; Rankin et al., 2005). The D call is a general, worldwide blue whale call that is
not population-specific and has been observed from different feeding areas like the gulfs of
California and Mexico (Thompson et al., 1996), as well as the Cortez and Tanner Banks and the
Southern California Bight (Oleson et al., 2007).
Figure 3: A spectrogram of the Antarctic blue whale’s high-frequency modulated D calls showing the waveform amplitude
modulations (a) and frequency modulations (b) over time during the 2001/02 IWC SOWER cruise. [See colour figure on page 313.]

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For Z calls, both the frequency sweeps within a call and the several replications of a call
(harmonics) improve long-distance communication by making the call stand out from the
ambient noise (Edds-Walton, 1997). McDonald et al. (2009) and Gavrilov et al. (2011) reported
a worldwide decrease in the frequency and source levels of blue whales. The reasons for this
are not well understood, but factors like depleted/recovering populations, mate selection,
animal size, cultural behaviour and ocean ambient noise have been associated with the
change. Comparisons of the regional call patterns of blue whales can provide biologists with
an understanding and knowledge of the population structure, seasonal relative abundance
patterns, migrations and distribution (McDonald et al., 2006a) of the species or populations.
Thus, the determination of species identification techniques is important for the effective
recognition of a sound producer at a particular location (Tyack, 1998).
3.5 Passive acoustic monitoring research on large baleen whales in South Africa –
the South African Blue Whale Project
South African cetacean scientists are actively involved in the Southern Ocean Research
Partnership (SORP), which is an IWC initiative to enhance cetacean conservation and deliver
methods of non-lethal whale research using techniques such as PAM in the Southern Ocean.
Prior to the initiation of the SORP, the IWC’s IDCR and SOWER cruises were conducted between
1979 and 2010. These cruises utilised PAM stations (1995 to 2009) that deployed sonobuoys. The
timing and distribution of the sounds recorded are shown in Figure 4 and Figure 5. However, the
main aim of the IWC’s IDCR and SOWER circumpolar surveys was to estimate the abundance
and distribution of whales using sighting surveys. The acoustic data collected during these
surveys is currently being analysed in South Africa to investigate the spatio-temporal distribution
patterns of vocalising Antarctic blue whales and to determine the call rates of the observed
whale pods. Demultiplexed bearings of vocalising Antarctic blue whales can be estimated from
directional DIFAR sonobuoy PAM data to differentiate between vocalising whale pods.
Figure 4: The IWC’s sonobuoy acoustic research effort over time in the Southern Ocean during the IDCR and SOWER
cruises, including the 1995 Australia, 1996 Madagascar and 1998 Chile cruises. A total of 633 sonobuoys were deployed
over 15 years, which recorded sounds for 1 505 hours. The database that is currently being analysed comprises 93% of
the IDCR and SOWER sonobuoy data.

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Reflections on the State of Research and Technology in South Africa’s Marine and Maritime Sectors
Figure 5: Detections of blue whales from sonobuoys deployed during the IWC’s SOWER voyages, 1999 to 2009. Sonobuoy
deployment sites are shown on the map as grey points, while black points show locations at which Antarctic blue whales
were heard by acoustic researchers. Each block is 5Ýof latitude and longitude. The data is courtesy of the IWC.
The SABWP started a long-term passive acoustic programme in 2014 to monitor Antarctic
blue whales in the Antarctic sector south of South Africa (000° to 020° E), one of the areas
with the highest abundance of the species in terms of calls recorded (Figure 5). An aural M2
autonomous acoustic recorder (AAR) deployed on the Maud Rise (65 00° S; 002 30° E) in water
depths of 1 200 m will monitor low-frequency whale calls until February 2015 when the mooring
(and the archived acoustic data) will be recovered and most probably redeployed for a further
year (Findlay et al., 2014). The recorded PAM data is archived on the recording instrument’s
hard drive for later analyses once the hydrophone is retrieved. The AAR is operated on batteries
for the duration of the deployment and the duty cycle is determined by both battery life and
hard drive space.
Such passive acoustic technology is being combined with the conventional sighting survey
and mark-recapture methods to study the distribution, abundance and migration of Antarctic
blue whales in the South-East Atlantic. The SABWP also deploys AAR moorings off the coast of
South Africa and Namibia to monitor and track the abundance, movement and distribution of
Antarctic blue whales during their migrations. The seasonal occurrence of other large baleen
whales, such as the humpback (Megaptera novaeangliae), fin and southern right whale
(Eubalaena australis) may also be monitored from this passive acoustic system, depending on
the target frequencies being recorded (which are obviously a trade-off on battery duration).
The research done by the SABWP contributes important knowledge towards estimating
the current population status of Antarctic blue whales, in conjunction with genetic and
photographic data collected to help understand the stock structure of the species. The SABWP
is also conducting investigations of predator-prey relationships by using active acoustic echo
sounders (discussed in Chapter 7) to determine the abundance and distribution of Antarctic krill
relative to whales.

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4. Challenges and the way forward
A number of challenges in PAM methodology need to be addressed in the future.
PAM only detects and records sounds from marine mammals that vocalise, so acoustic studies
need to be conducted at times when animals are known to vocalise or throughout the year to
determine the times when the animals are vocally active. Thus, sighting surveys combined with
PAM using DIFAR sonobuoys can assist in discriminating vocally active whales from non-vocal
ones. However, sonobuoys are not easily accessible in South Africa. The presence or absence
of a species in a particular area can be derived independently of the acoustic recording
instrument from visual sighting surveys and from historic whale catches, assuming those
mammals currently utilise the same areas as during whaling (although this can be biased by
catch selectivity). The acoustic research effort from the previous IWC programmes is low (Figure
4), varies over the years, and is non-randomly distributed as research was focused in areas with
high densities of whales (Figure 5). Consequently, a greater acoustic research effort is required
in all the other IWC management areas.
The determination of marine mammal call rates and their variation with age, sex and season are
still problematic. The detection range and source levels of many species are unknown and may
include considerable variability. Thus, density estimation is difficult to determine from source levels,
as they vary considerably between the three currently available Antarctic blue whale studies.
Research to determine the vocal behaviour of Antarctic blue whales will answer questions about
the diel, seasonal and annual variability of these marine mammals’ calls and songs.
Once call rates are determined, the relative amount of calling animals at a given time
and location can be determined, as calling animals will be identified to an individual level
through concurrent visual observations. The maximum ranges at which a marine mammal
call can be detected are estimated based on factors that affect sound propagation, i.e.
environmental factors (such as temperature and salinity) and bathymetric data. Therefore, the
lack of such data limits such estimations. Oceanographic mooring, as well as conductivity/
temperature/depth (CTD) instruments and model data, can be used effectively to provide such
environmental data around the South African coast for the duration of acoustic recordings.
Positional identification of individual marine mammals requires both source levels and
transmission loss to be known to accurately determine the relative density of animals in a given
area, as illustrated by the equations in Section 3.2.
The use of DIFAR hydrophones and arrays of hydrophones can enable the estimation of
detection range, bearing and source levels of the sounds of marine mammals, although
hydrophones must be calibrated regularly. The calibration of hydrophones used for collecting
acoustic data is challenging and complicated, as this process cannot be conducted at
sea easily, but needs laboratory conditions to produce reliable or robust outcomes. Miller
et al. (2014c) present a relatively smooth method of calibrating the magnetic compass of
the sonobuoy used for the real-time tracking of Antarctic blue whales in situ. The Institute for
Maritime Technology (IMT) in South Africa has laboratory facilities for ex situ calibrations, and
access to such facilities could facilitate an effective calibration process.
Acoustic instruments are expensive as these are usually manufactured overseas, and greater
capital investment is required in South Africa to purchase the equipment to conduct this
kind of research. Despite the expenses of deployment, the relative cost-effectiveness of
AAR systems’ long-term monitoring means that such acoustic monitoring is a highly cost-

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Reflections on the State of Research and Technology in South Africa’s Marine and Maritime Sectors
beneficial technique. The use of existing infrastructure may reduce the cost of deployment
(Van Opzeeland et al., 2014). For instance, hydrophones can be installed on existing South
African oceanographic moorings, and the embargoed acoustic data from the South African
Navy’s underwater acoustic surveillance hydrophone ‘waterbug’ can be used effectively for
PAM of marine mammals. The deployment of more hydrophones in arrays around the coast
of South Africa is recommended, and such deployments need to be aligned with the further
development of human capacity in acoustic research in the South African region.
The seas of the world are becoming increasingly noisy as anthropogenic noise at sea is
increasing dramatically. Seismic surveys and other anthropogenic activities can result in the
masking of sounds from marine mammals (Finneran et al., 2002). In turn, marine mammals
may change their behaviour in response to the prevailing noise levels (McDonald et al., 2006b).
Stricter marine laws are to be devised and implemented by the United Nations Convention on
the Law of the Sea (UNCLOS) to combat the increasing noise levels in the ocean (Reeve, 2012).
As AARs record ambient and anthropogenic noise across the frequencies of interest, monitoring
such noise levels can provide up-to-date knowledge about the status of background and
anthropogenic noise levels around the coast of South Africa.
Collaboration among researchers is fundamental and key to the future success in this field, as
exemplified by the SORP Antarctic blue and fin whale Acoustic Trends Working Group (ATW).
The ATW aims to establish simultaneous circum-Antarctic acoustic monitoring coverage through
a Southern Ocean Hydrophone Network (SOHN) in the next decade, thus effectively reducing
acoustic research costs to permit the density estimation of Antarctic blue and fin whales
(Van Opzeeland et al., 2014). The PAM component of the SABWP forms an integral regional
component of the SOHN.
Conclusion
The use of bioacoustics to study marine mammals is still in its infancy in South Africa, granting
South African researchers an ideal opportunity to develop and apply established methods
in South African coastal waters. This acoustic technique has great potential to study vocal
marine animals that are difficult to observe or survey visually. More acoustic research on marine
mammals is required in South Africa to fully understand the behaviour, distribution and migration
of the region’s marine mammals. There are opportunities to extend passive acoustic research
to other marine taxa to obtain useful data about these animals without disturbing the marine
environment and ecosystem.
Acknowledgements
We would like to thank the IWC for providing us with the IWC’s IDCR and SOWER cruise acoustic
data. We thank the South African National Research Foundation and the South African National
Antarctic Programme for funding the SABWP. Meredith Thornton and the 2013/14 Blue Whale
Team are thanked for their outstanding technical assistance with the deployment of the
Maud Rise AAR hydrophone. The authors thank Dr Ilse van Opzeeland, Karolin Thomisch and
anonymous reviewers for their invaluable comments and suggestions for improvements to this
chapter. Other members of the SORP ATW are thanked for their support and encouragement
towards the SABWP. Our sincere gratitude goes to Prof Peter Best for fruitful discussions and
valuable suggestions to the SABWP.

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Figure 10: Bathymetric map of the southern continental margin of South Africa and adjacent deep ocean area.
Bathymetric isobaths are spaced at 5-metre intervals for water depths ranging between 0 and -500 metres, at 10-metre
intervals for water depths ranging between -500 and -1 000 metres, and at 100-metre intervals for water depths greater
than -1 000 metres (Image taken from De Wet, 2012). [See page 139.]
Figure 2: A typical Antarctic blue whale Z call illustrating the wave form amplitude modulation (a), with the corresponding
frequency modulation and duration of each unit of this three-unit call (b). The 28 Hz unit is the high-energy component of the
call as it has the highest amplitude compared to the other two components of the call as shown by the amplitude values. The
amplitude is presented here in a thousand unit, also known as a kilo unit (kU), of the dimensionless sample values. Data was
collected during the 2001/02 IWC SOWER cruise. [See page 163.]
Figure 3: A spectrogram of the Antarctic blue whale’s high-frequency modulated D calls showing the waveform amplitude
modulations (a) and frequency modulations (b) over time during the 2001/02 IWC SOWER cruise. [See page 163.]