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First published online December 14, 2006
Journal of Experimental Biology 210, 56-64 (2007)
Published by The Company of Biologists 2007
doi: 10.1242/jeb.02618
Echolocation signals of wild harbour porpoises, Phocoena phocoena
1 Department of Zoophysiology, Institute of Biological Sciences, University
of Aarhus, C. F. Møllers Alle, DK-8000 Aarhus C., Denmark
2 Fjord & Bælt, Margrethes Plads 4, DK-5300 Kerteminde,
Denmark
3 National Environmental Research Institute, Fredriksborgvej 399, DK-4000
Roskilde, Denmark
* Author for correspondence (e-mail: anne.villadsgaard{at}biology.au.dk)
Accepted 25 October 2006
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Summary |
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 TOP Summary IntroductionMaterials and methodsResultsDiscussionReferences |
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Key words: Odontoceti, Phocoena phocoena, biosonar, target detection, click, source level, inter-click interval, bycatch, acoustic monitoring
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Introduction |
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TOPSummaryIntroductionMaterials and methodsResultsDiscussionReferences |
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The performance of a biosonar system can be evaluated by means of the sonar
equation in its transient form (Au,
1993
). This equation relates the emitted sound energy flux density
to the energy flux density of the returning echo. The simplest form of the
sonar equation, in which noise is ignored, states that the energy flux density
of the returning echo is equal to the energy flux density of the outgoing
signal minus the propagation loss due to geometric spreading and sound
absorption, plus the reflective properties of the ensonified target:
 | (1) |
where EE is the returning echo energy flux density (in dB re 1
µPa2s), SE is the source energy flux density (the
acoustic energy flux density 1 m in front of the sound source measured on its
acoustic axis, in dB re 1 µPa2s), TL is the
transmission loss (the reduction in sound energy between a point 1 m from the
source and the target, in dB) and TSE is the target
strength (the ratio of the reflected energy flux density measured 1 m from the
target relative to the energy flux density impinging on the target, also in
dB). Instead of using the notation energy flux density, the acoustic output of
a sound source can be presented as the sound pressure level, which is the
intensity of the signal, or the sound energy per unit time. Most studies on
harbour porpoise biosonar report the sound pressure level rather than the
energy flux density, even though the latter is more relevant when discussing
biosonar performance (Au, 1993;
Kastelein et al., 1999). In
this paper, we favour the energy flux density notation, but for comparison
with earlier work we also report the sound pressure level 1 m in front of the
animal, also known as the source level.
Harbour porpoises produce high-frequency, narrowband signals. These
so-called clicks, measured from animals in captivity, have a duration of
100 µs, a peak frequency of 130 kHz, an inter-click interval of
60 ms and a maximum source level of 172 dB re 1 µPa pp @ 1 m
(Dubrovskij et al., 1971;
Møhl and Andersen,
1973; Akamatsu et al.,
1994; Teilmann et al.,
2002). This is more than 40 dB less intense than has been measured
from other toothed whales [e.g. bottlenose dolphin
(Au et al., 1974); sperm whale
(Møhl et al., 2003);
narwhal (Møhl et al.,
1990); white-beaked dolphin
(Rasmussen et al., 2002)].
Consequently, the biosonar of harbour porpoises is expected to have
considerably shorter detection ranges than that of larger odontocetes, such as
the bottlenose dolphin. This is consistent with target detection experiments
involving captive animals, where the detection ranges of similar sized steel
spheres were about five times shorter for porpoises than for bottlenose
dolphins (Kastelein et al.,
1999).
|
)
is known to us, but it contains no quantitative data. Observations of other
species of toothed whales have shown that animals echolocating in open water
produce signals that are orders of magnitude more intense than those from
animals recorded in tanks. This can have large implications on how we
interpret the animals' biosonar performance, not only during prey detection
and capture but also during interactions with fishing gear that may lead to
incidental entanglement (Perrin et al.,
1994; Cox et al.,
1998; Vinther,
1999). For designing sustainable methods that reduce bycatch and
also for passive acoustic monitoring of harbour porpoise distribution, it is
crucial to know the animals' biosonar performance, especially in terms of the
sound pressure levels being emitted by the animals in their natural
habitat. The aim of the present study was to provide information on the source properties and use of the echolocation clicks of wild harbour porpoises and compare the results with data obtained from captive specimens. The results show that the clicks can be considerably more intense in the field than has previously been reported from captivity. The implications of this are discussed in relation to biosonar performance, bycatch and passive acoustic monitoring.
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Materials and methods |
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TOPSummaryIntroductionMaterials and methodsResultsDiscussionReferences |
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Recordings were made with a linear, vertical array consisting of either three or four Reson TC 4034 hydrophones with a sensitivity of -220 dB re 1 V/1 µPa in the frequency range up to 250 kHz (Reson A/S, Slangerup, Denmark). The array configurations are depicted in Fig. 1. A relative calibration of the hydrophones was performed in an anechoic tank to make sure that the sensitivity of the hydrophones corresponded within 3 dB to that given by the manufacturer within the frequency range 120-150 kHz.
The hydrophones were mounted in holes made in a 5 cm-diameter and 6 m-long, rigid PVC pipe, aligned within a few mm on the vertical axis (Fig. 1).
Two different recording systems were used. The 3-hydrophone array was connected through a custom-built band pass and amplifier unit to a Wavebook 512 (IOtech, Cleveland, OH, USA) for digitisation. Sampling frequency for each of the three channels was 330 kHz, 12 bit resolution. The 4-hydrophone array was connected through a custom-built band pass and amplifier unit to a lunchbox computer containing a 4-channel sound card (AD-Link, NuDAQ 20 MHz 4-channels, 12 bit; Danbit, Copenhagen, Denmark). The sampling frequency for each of the four channels was 400 kHz. A first-order (-6 dB octave-1) high-pass filter at 10 Hz and a eighth-order (-48 dB octave-1) low-pass filter at 150 kHz were used for the Bay of Aarhus recordings, and a first-order (-6 dB octave-1) high-pass filter at 100 Hz and a second-order (-12 dB octave-1) low-pass filter at 200 kHz were used for the recordings made in Bogense and Little Belt. An overall gain of 60 dB was used at all three locations.
Source level measurements
The sound pressure level that we recorded on our systems is termed the
received level. From the received level, we wish to estimate the source level,
which is defined as the sound pressure level back-calculated to 1 m in front
of the harbour porpoise on its acoustic axis. To do this we need to know the
distance between the array and the porpoise in order to estimate the
transmission loss. The distance was back-calculated, using a custom-built
Matlab (Mathworks, Natick, MA, USA) routine, from the time-of-arrival
distances (TOADs) of the same signal between the different
hydrophones [similar to the equations given in Wahlberg et al.
(Wahlberg et al., 2001)]. The
speed of sound in water that we used was 1495 m s-1, as calculated
from the Medwin equation (Medwin,
1975) from salinity and temperature measurements made on location.
Assuming spherical spreading, the transmission loss is given by
TL=20log(R)+R
, where R is the
distance between the porpoise and the array and is the
frequency-dependent absorption at the centroid frequency of the received
signal [0.04 dB/m at 135 kHz (Fisher and
Simmons, 1977)].
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; Beedholm and Møhl,
2006). This does not apply to narrowband porpoise clicks
(Au et al., 1999). In this
paper we therefore refer to the measurements as `apparent source levels'
(ASL), which equals the backcalculated sound intensity at a distance of 1 m
from a directional source in an unknown direction (sensu
Møhl et al., 2000). At
worst, we underestimate the on-axis source levels, as the clicks may very well
have been recorded off the acoustic axis, and the apparent source level should
thus be regarded as conservative estimates of the true source level.
Harbour porpoises emit trains of clicks in a narrow, forward-oriented beam
(Au et al., 1999). When the
sound beam of an echolocating porpoise intersects a hydrophone, a series of
clicks are recorded, usually first increasing and then decreasing in
amplitude. We call such a click sequence a `scan' (sensu
Møhl et al., 2003).
The criteria for selecting clicks for source level measurements were: (1) the click was detectable on all channels, (2) the direct path of the click was stronger than any trailing surface or bottom reflections, (3) the click was of maximum amplitude in a scan and (4) the porpoise was localized within 75 m of the array.
Analysis
Analysis of data was performed with Adobe Audition 1.5 (Syntrillium, Adobe,
Mountain View, CA, USA) and custom written routines in Matlab 6.5.1
(Mathworks) to estimate click parameters.
A number of parameters were extracted or calculated from each click. These parameters were chosen to obtain data for accurate comparison with previous work on signals from harbour porpoises and other species.
The centroid frequency (fc) is the frequency dividing
the spectrum in equal halves of energy, and the peak frequency
(fp) is the highest frequency in the spectrum. The click
duration (
) was determined using two techniques: the -10 dB duration
(-10dB) and the 95% energy duration (E). The
-10dB is the click duration 10 dB below the peak of the click
envelope (Fig. 2A). To
calculate the E of the signal, a window is defined around the
signal, and the duration is determined as the interval containing 95% of the
energy within that window (Fig.
2B) (see also Madsen,
2005). The bandwidth (BW) was determined as the -3 dB BW (3 dB
below the spectral peak), the -10 dB BW (10 dB below the spectral peak) and
the RMS BW [the root-mean-square BW of the signal spectrum
(Madsen, 2005)]. The Q-value,
or quality factor (Au, 1993),
was calculated as the centroid frequency divided by the RMS BW. The
inter-click interval (ICI) was determined as the interval between successive
clicks in a click train, measured with a semi-automated routine (click
detector) written with Matlab. The click sequences were selected manually from
the data as being of a favourable signal-to-noise ratio. The click detector
detected all signals exceeding a certain peak threshold, set by the operator.
By running a few tests, it was shown that the click detector detected >99%
of the clicks in sequences of decent signal-to-noise ratio and produced very
few erroneous results.
Click intensity (ASLpp, ASL-10dB,
ASL95%E) and energy flux density
(E-10dB, E95) measurements were done
according to Madsen (Madsen,
2005).
Array calibration and measurement accuracy
In order to test if our chosen transmission loss model
[TL=20log(R)+R] was realistic, the array was
used in the field to localize an omni-directional sound source [Brüel
& Kjær 8105 (Nærum, Denmark) connected to an Agilent Waveform
Generator (Agilent Technologies Denmark A/S, Nærum, Denmark)] emitting
artificial porpoise clicks at different distances at a depth of 3 m. The depth
of the hydrophone array was 3 m (to the top hydrophone) and the water depth
was 12 m.
The transmission loss measurements are displayed in
Fig. 3A. The received level as
a function of the measured range (5, 10, 25 and 50 m) follows the theoretical
line for spherical spreading plus absorption. The variation in the received
level within each of the four ranges was 3-4 dB.
Fig. 3B displays the RMS error
for the acoustic range estimation for the 4-hydrophone array and the
3-hydrophone array, calculated as:
 | (2) |
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The maximum variation in ranging errors is expressed in decibels calculated from the corresponding transmission loss (Fig. 3C). Both the localization RMS error and the transmission loss error ('variation') increase with the increasing distance between the porpoise and the array (Fig. 3B,C). The measurements show that the chosen transmission loss model is acceptable within 4 dB at distances up to at least 50 m at this source and array depth (Fig. 3A).
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Results |
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Based on the criteria described above, 37 clicks from 33 different scans were selected as candidates for being recorded on or close to the acoustic axis and used in the analysis. Clicks within the same scan are from the same individual, whereas clicks from different scans are most likely from different animals. An example of a harbour porpoise click is shown in Fig. 2A. The accumulated energy content in the click over time is displayed in Fig. 2B.
All click parameters are summarized in
Table 1. Apparent source levels
from 178 to 205 dB re µPa pp @ 1 m were derived. When measured as the -10
dB energy flux density, the maximum ASL corresponds to 150 re 1
µPa2s @ 1 m and the minimum ASL corresponds to 123 dB re 1
µPa2s @ 1 m. The clicks were considerably weaker in Bogense and
Bay of Aarhus as compared with the clicks recorded in Little Belt
(Fig. 4). There is a clear
relationship between the porpoise-to-array range and the apparent source level
for the clicks recorded in Little Belt up to 30 m, but outside this range
the ASL seems to be independent of range
(Fig. 4). For the clicks
recorded in Bogense and the Bay of Aarhus, the ASL got more intense when
moving away from the array up to 75 m (Fig.
4).
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A power spectrum of a click is depicted in Fig. 5. The peak and centroid frequencies ranged from 129 kHz to 145 kHz (Table 1).
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Discussion |
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TOPSummaryIntroductionMaterials and methodsResultsDiscussionReferences |
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) were able to produce signals 40 dB more intense than
signals from animals in concrete tanks
(Evans, 1973). The reason for
this may be that the animal is reluctant to emit high-powered signals in
highly reverberant environments, such as concrete tanks, due to the possible
annoyance of being exposed to very high levels of returning echoes
(Au, 1993). Field recordings of
other species of dolphin have confirmed that this is not unique for the
bottlenose dolphin (Madsen et al.,
2004; Au and Benoit-Bird,
2003).
The biosonar performance of a toothed whale under low noise and
reverberation conditions is described by the transient form of the sonar
equation (Eqn 1). The returning echo energy flux density is a function of the
emitted source energy flux density and the target strength. As the target
strength is dependent on the frequency content of the impinging signal
(Urick, 1983), the energy flux
density of the returning echo will depend on both the frequency and energy
content of the emitted signal. Most toothed whales emit broadband clicks
during echolocation. In theory, these animals could regulate their biosonar
performance by changing both the frequency content and the intensity of the
click independently. In practice, however, these parameters are closely
interrelated so that high intensity clicks will also contain higher
frequencies (Au, 1993).
The harbour porpoise and the rest of the Phocoenidae family, plus dolphins
of the genus Cephalorhynchus and the pygmy sperm whale of the genus
Kogia, produce narrowband clicks of high frequency
(Dubrovskij et al., 1971;
Møhl and Andersen,
1973; Dawson and Thorpe,
1990; Au et al.,
1999; Marten,
2000). The variation in the frequency content of harbour porpoise
signals is small (Au et al.,
1999) compared with odontocetes using broadband signals.
Therefore, the only way in which the porpoise can affect the returning echo
energy flux density is to alter the emitted source energy flux density, as
seen by the sonar equation. An increased source energy flux density will lead
to a higher received echo energy flux density, everything else being equal,
and hence a better chance for the animal to detect and classify the target.
However, there may be good reasons for odontocetes not to use the highest
possible sound pressure levels. Some fish species are known to be able to
detect biosonar signals (Astrup and
Møhl, 1993; Mann et
al., 2001). There are also physical limitations to the intensity
of the signals an odontocete can produce, depending on the size of the animal
and the frequency of the signals used. In addition, in reverberant
environments containing extraneous echoes (clutter), the received clutter
level will depend on the emitted source energy flux density, so that the
animal may not necessarily improve its signal-to-clutter ratio by increasing
the energy flux density of its signals.
In Table 1, the apparent source level, click duration, peak frequency and ICI from field data are compared with existing data from animals in captivity. In spite of the considerably higher source levels in the field recordings, the other source parameters are very similar. This seems to indicate that harbour porpoises can maintain many signal features such as signal duration and frequency content over a large dynamic range of source levels.
The source levels recorded in one of the study areas, Little Belt, were
significantly higher than those recorded in the other two areas. We have no
clear explanation for this. It could be a result of the extensive boat traffic
in the Little Belt area, leading to increased background noise levels.
However, there is no reason to believe that the background noise will change
in the porpoises' frequency range (120-140 kHz) and hence influence the
porpoises' echo-to-noise ratio. Another reason could be that the clicks were,
by chance, recorded more off-axis in the other two areas. In general, the
porpoises seemed to be more vocal, less shy and easier to approach in the
Little Belt area, thereby improving the chance of getting on-axis recordings.
Finally, the animals in Little Belt were probably involved in more intense
foraging compared with the porpoises in the other areas, and this activity may
have triggered a much more intense biosonar activity.
In previous studies, where arrays have been used to record dolphin biosonar
signal, a positive relationship between the source level and the range between
the dolphin and the array has been reported (e.g.
Au and Benoit-Bird, 2003). Such
data have been interpreted as evidence for automatic gain control (AGC; a
mechanism that regulates the amplitude of the perceived echo level, either by
improving the hearing abilities or increasing the source level of the emitted
signals, for varying ranges to the target) in the sound production or hearing
system of odontocetes (Au and Benoit-Bird,
2003). Also, in our study, the highest apparent source levels are
found at the greatest ranges from the array
(Fig. 4). This could putatively
be used as evidence of AGC. However, for such a conclusion to be valid, we
must be certain that the porpoise is actually echolocating on the array and
not just making an accidental scan across it. Also, it is crucial that the
dynamic range of the recording system can handle both close and distant
on-axis clicks without clipping them. In addition, a bias in the localization
system towards longer distances may occur if the hydrophones were not
perfectly aligned. Thus, a valid explanation for the observed increased ASL
with range may be found without concluding that porpoises are using AGC. For
example, it turned out that the positive relationship between ASL and range in
Fig. 4 within 30 m from the
array in the Little Belt recordings was completely explained by clipping of
received levels above 172 dB re 1 µPa pp. More studies are needed on
the target detection abilities of harbour porpoises to resolve this issue. The
only study of this kind performed to date seems to indicate that there is no
AGC in this species (Beedholm et al.,
2006).
It is important to note that in previous field studies where AGC has been
inferred (see Au and Benoit-Bird,
2003), it was not possible to confirm that the animals were
echolocating towards the hydrophones, and therefore the variation in click
source levels could not be discerned from the effect of recording the clicks
at various degrees off the acoustic axis. In addition, it should be noted that
the study of Au and Benoit-Bird also has the potential bias of larger
localization errors at greater distances due to minor errors in the positions
of the hydrophones, especially when recording off the array symmetry axis. The
only study known to us where both the relative changes in output levels and
the returning echo levels could be simultaneously estimated on a free-ranging
odontocete (a ziphiid, Mesoplodon densirostris) did not show any
clear indication of AGC (Madsen et al.,
2005).
Improvement of net and fish detectability and passive acoustic monitoring due to an increased source level
The high source levels obtained in this study are important for
understanding the foraging behaviour of wild harbour porpoises in terms of at
which distance they may detect their prey. The results are also crucial for
understanding mechanisms underlying the bycatch problem in terms of at which
distances porpoises are able to detect gillnets. In addition, if wild harbour
porpoises use considerably higher source levels than has been previously
assumed, the distance at which acoustic data loggers can detect harbour
porpoises will be significantly increased, thereby affecting the
interpretation of data obtained from passive acoustic monitoring of this
species.
It should be noted that the following calculated detection distances for harbour porpoises are only theoretically derived and that other parameters besides the source level may influence the detection ability of the porpoise.
In the only existing target detection experiment made with harbour
porpoises, Kastelein et al. found that harbour porpoises could detect a 5.08
cm water-filled stainless-steel sphere at a maximum distance of 15.9 m
(Kastelein et al., 1999). The
harbour porpoise in these target detection trials was emitting clicks with
source levels of 165-170 dB re 1 µPa pp.
In order to calculate the distance at which a harbour porpoise can detect a
fish, we need to know the relationship between the echo energy received by the
porpoise and the distance to the target. For this, the following equation is
used (see Kastelein et al.,
1999):
 | (3) |
Here, we use the relationship between source energy (SE) and
peak-to-peak source level (SE=SLpp-56.7 dB) for
harbour porpoises (Kastelein et al.,
1999).
In the following, we assume that the ambient noise level is the same in our
field recordings as in the target detection trials conducted by Kastelein et
al. (Kastelein et al., 1999)
so that the detection threshold is identical. In the study by Kastelein et
al., the echo energy flux density at threshold was 27 dB re 1
µPa2s. We may use this information to estimate the distance at
which a porpoise can detect a fish. With a source level of 165 dB re 1 µPa
pp (Kastelein et al., 1999),
Eqn 3 gives a detection distance of 10 m for captive porpoises to detect a
fish of target strength -40 dB (similar to that of an adult herring). For a
wild porpoise producing signals of a mean source level of 191 dB re 1 µPa
pp, the detection distance increases to 40 m for detecting the fish, using Eqn
3. Thus, the distance over which a porpoise can detect a fish will increase by
up to four times when increasing the source level from 165 to 191 dB re 1
µPa pp.
One may use a similar argument to estimate how the new source level
estimates may change the detection distance to gillnets. Kastelein et al.
addressed the detection distance of porpoises to bottom-set gillnets
(Kastelein et al., 2000). They
calculated the maximum detection distance to be 3-6 m using source level data
from captive porpoises combined with the results of the above-mentioned
detection experiments (Kastelein et al.,
1999). The detection distance of wild porpoises can be calculated
as follows with the help of data from Kastelein et al.
(Kastelein et al., 2000) and
the data presented here. Eqn 3 is used twice, both for the data obtained in
captivity ('old') and the data obtained in the field ('new'). Assuming that
the echo level at threshold is the same in the field as in the study by
Kastelein et al. (Kastelein et al.,
1999), we can reduce the two equations to one, and the TS
can be eliminated. This gives the following equation:
 | (4) |
The new detection range can now be deduced from TLnew.
Using source levels of 165 dB re 1 µPa pp ('old') and 191 dB re 1 µPa pp
('new'), the detection distance will theoretically increase to 13-26 m, or at
least four times compared with the detection distances estimated by Kastelein
et al. (Kastelein et al.,
2000).
The results presented here on source levels of wild harbour porpoises also
affect the interpretation of data obtained with acoustic data loggers. The
distance (R) over which an acoustic data logger can detect a porpoise
will depend on the detection threshold (DT) of the detector and can
be estimated from the passive sonar equation:
 | (5) |
In the following calculations, we use data from an acoustic data logger
called a T-POD (Chelonia Ltd, Long Rock, Cornwall, UK). For this equipment, a
minimal detection threshold of 123 dB re 1 Pa pp and a maximal threshold of
132 dB re 1 Pa pp were measured by Kyhn
(Kyhn, 2006). Source levels of
165 dB re 1 µPa pp [captive source level measured by Kastelein et al.
(Kastelein et al., 1999)] and
191 dB re 1 µPa pp (mean source level from wild porpoises found in the
present study) were used. By inserting this data into Eqn 5 we can numerically
estimate the maximal distance (R) over which a T-POD can detect a
porpoise. For the minimum T-POD threshold, this gives an increased detection
distance from 85 to 400 m when increasing the source level from the captive to
the wild situation. For the maximal threshold, the corresponding increase in
detection distance is from 38 to 260 m.
Thus, overall the harbour porpoises should be able to detect or be detected over significantly larger distances than has been previously assumed (summarized in Table 2). It should be noted that there is likely to be a large dynamic range in the emitted source levels and thereby also in the ranges at which fish and nets can be detected by the porpoises and the ranges at which automatic detectors can detect the animals.
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Transmission loss of harbour porpoise signals and measurement accuracy
The transmission loss is a central factor when calculating the energy flux
density of a sound source. Several formulas are known for estimating the
transmission loss in different propagation conditions. Most often the
transmission loss model for spherical spreading and absorption
[TL=20log(R)+R] is used when calculating the
source level of echolocating odontocetes
(Au, 1993). This simple
propagation model states that the energy generated by the source is radiated,
as if it was distributed over the surface of a sphere surrounding the source
(Urick, 1983). It is usually
assumed that the spherical transmission loss model is accurate up to a
source-received distance of at least a few tens of metres when recording
biosonar signals in shallow waters. Beyond this the signal will start to
interact with the water surface or the bottom.
The accuracy in the source levels derived in this study depends on the ranging accuracy of the localization system and on the accuracy in the assumed transmission loss model (spherical spreading and absorption). We therefore tested if the spherical spreading and absorption model for transmission loss was applicable to our data.
The transmission loss measurements were within 4 dB of those predicted by
the spherical spreading and absorption [20log(R)+R]
model within a sound source-array distance of 50 m
(Fig. 3A). Even though the
transmission loss may vary significantly when the source or the hydrophones
are shallower or deeper than is assumed in
Fig. 3A, it seems safe to apply
the spherical spreading and absorption transmission loss model to all data
analysed in this study.
The transmission loss used in the calculation of the source level is
back-calculated from the estimated range between the porpoise and the array.
Thus the accuracy of the transmission loss depends on the accuracy of the
range estimate. The accuracy of the range estimation will diminish with
increasing distance between the porpoise and the array. The accuracy of the
localization of the porpoise and hence the range was evaluated by comparing
the RMS error between the measured range (determined with a rope) and the
acoustic range (estimated from the TOADs) during the transmission loss
experiment. The RMS error (RMS taken of the relative error) was very similar
for the 4-hydrophone array and the 3-hydrophone array within 25 m from the
array (Fig. 3B). Beyond this
range the extra hydrophone gave a more accurate estimation of range and
therefore a smaller error in the derived source levels than by using only
three hydrophones. At a 50 m range, there was an RMS error of 28% for the
4-hydrophone array and 52% for the 3-hydrophone array. The impact on the
transmission loss estimates due to the error in the measured ranges increases
with increasing distance between the porpoise and the array
(Fig. 3C). There is hardly any
variation in the transmission loss (
2 dB) at a distance up to 25 m. At a
distance of 50 m there is a variation of 5 dB for the 4-hydrophone array and a
variation of 8 dB for the 3-hydrophone array. These values are regarded as the
result of a worst-case scenario, as they are calculated from the maximum
measured ranging deviation between the acoustic range and the range measured
with a rope. In addition, an omnidirectional sound source was used for the
calibrations whereas harbour porpoise clicks are very directional. An
omnidirectional sound source will cause more interactions between sound paths
reflected at the surface and the bottom and the direct sound path. Therefore,
probably both the localization errors and the deviations from a spherical
spreading transmission loss given here are significantly exaggerated. Adding
the anomaly in transmission loss to the ranging error, this implies that all
apparent source levels reported here are measured with a total error of less
than 10 dB {calculated as [(TL error)2 + (ranging
error)2)]
} at a distance of 50 m and for shorter
distances this is considerably less.
Inter-click intervals
The preferred ICI by harbour porpoises in the presented recordings was
60 ms (Fig. 6), which is
similar to that found in experiments with captive animals. Teilmann et al.
found in a detection study that the porpoise preferred a mean ICI of 59 ms
(Teilmann et al., 2002).
Preference for a certain ICI is also found in other odontocete species, e.g.
Madsen and coworkers have shown that foraging beaked whales prefer a certain
ICI (400 ms) in their search and approach phase
(Madsen et al., 2005).
In a study conducted on actively swimming harbour porpoises, Verfuß
et al. measured ICIs between 10 and 120 ms from a swimming porpoise in a pool
(Verfuß et al., 2005).
They showed that there was a clear relationship between the assumed target
distance and the ICI. There is, however, a great variation in the ICIs both in
the presented field recordings and in the study by Verfuß et al. on
captive animals. Therefore more studies are needed to elucidate the
relationship between target distance and the ICI.
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Acknowledgments |
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References |
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TOPSummaryIntroductionMaterials and methodsResultsDiscussionReferences |
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