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Effect of Pile-Driving Playback Sound Level on Fish-Catching Efficiency in Harbor Porpoises (Phocoena phocoena)



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Aquatic Mammals 2019, 45(4), 398-410, DOI 10.1578/AM.45.4.2019.398
Effect of Pile-Driving Playback Sound Level on Fish-Catching
Efficiency in Harbor Porpoises (Phocoena phocoena)
Ronald A. Kastelein,1 Léonie A. E. Huijser,1 Suzanne Cornelisse,1
Lean Helder-Hoek,1 Nancy Jennings,2 and Christ A. F. de Jong3
1Sea Mammal Research Company (SEAMARCO), Julianalaan 46, 3843 CC Harderwijk, The Netherlands
2Dotmoth, 1 Mendip Villas, Crabtree Lane, Dundry, Bristol BS41 8LN, UK
3TNO Acoustics and Sonar, Oude Waalsdorperweg 63, 2597 AK, The Hague, The Netherlands
Abstract differences in responses to sound, termination
rates, and fish-catching success (even in ambi-
The foundations of offshore wind turbine parks ent conditions) may complicate the quantification
are often constructed by means of percussion pile of the impacts of pile driving sounds on harbor
driving. Broadband impulsive sounds generated porpoises.
by pile driving may disturb and distract marine
mammals such as harbor porpoises (Phocoena
Key Words: anthropogenic sound, distraction,
phocoena); their concentration may be reduced,
behavior, foraging, harbor porpoise, odontocete,
affecting the skills they need for foraging (e.g.,
marine mammal, individual variation, pile driving,
timing and precision) or reducing their ability to
wind park
catch prey and, thus, their foraging efficiency. The
resulting reduction in fitness may eventually lead Introduction
to population declines. Therefore, it is important
to understand the effects of these anthropogenic In the coming decades, many wind turbine parks
sounds on the ability of harbor porpoises to catch will be built in the North Sea and in nearby waters
fish. Two captive harbor porpoises (porpoise F05 (
and porpoise M06) performed a fish-catching task pdf/news-29718-scenario-2020-eolien-Europe-
(i.e., retrieving dead fish from a net feeding cage) WindEurope.pdf) within the geographic range of
while they were exposed to low ambient noise the harbor porpoise (Phocoena phocoena; Rice,
(quiet conditions) and impulsive pile-driving 1998). Impulsive sounds are produced during the
playback sounds at three (porpoise M06) or four construction of offshore wind turbines by means
(porpoise F05) mean received single-strike sound of percussion pile driving (so far, the most com-
exposure levels (SELss) between 125 and 143 dB monly used method). It may take several thousand
re 1 µPa2s. The two study animals differed in blows (depending on the pile diameter and length,
their fish-catching success rate at all noise levels, and the composition of the substrate) to drive one
including under quiet conditions: Porpoise F05 pile into the sea floor in a time period of 2 to 3 h.
was less likely to catch fish than porpoise M06. Typically, one pile is placed per day, and the con-
They also responded differently to increasing struction of an entire offshore wind park may take
SELss: Only porpoise F05 was significantly more months. The broadband high-amplitude sounds
likely to terminate trials and less likely to catch produced during offshore percussion pile driving
fish as SELss increased above 134 dB, but her have most of their energy below 1 kHz (Bailey
trial failure rate remained unaffected by increas-et al., 2010; Gabriel et al., 2011; Norro et al.,
ing SELss. The time taken to catch a fish did not 2013), so they are not expected to mask the high-
vary with SELss but was slightly longer for por-frequency echolocation signals used by harbor
poise F05 than for porpoise M06. Results suggest porpoises (around 125 kHz, narrow band; Møhl
that high-amplitude pile driving sounds are likely to
& Andersen, 1973). However, at certain received
negatively affect foraging in some harbor porpoises
levels, percussion pile driving does affect the
by decreasing their catch success rate and increasing
behavior of harbor porpoises (Carstensen et al.,
the termination rate of their fish-catching attempts;
2006; Tougaard et al., 2009; Bailey et al., 2010;
the severity of the effects is likely to increase with
Brandt et al., 2011; Dähne et al., 2013; Haelters
increasing pile driving SELss.
However, individual et al., 2014).
399Effect of Pile Driving Sound on Fish-Catching Efficiency of Porpoises
Apart from the most commonly used percus-the species’ biological traits. If exposure to sounds
sion pile driving method, vibratory pile driving is produced during wind park construction routinely
sometimes used, which also produces broadband affects harbor porpoise foraging and animals
high-amplitude sounds. The effect of vibratory cannot compensate, then in the long term, the pop-
pile driving sounds on echolocation vigilance has ulation dynamics of the species may be affected.
been investigated in another odontocete, the bot-Policymakers need to assess to what extent
tlenose dolphin (Tursiops truncatus; Branstetter acoustic disturbances are likely to affect the popu-
et al., 2018). The vibratory sounds have energy lation dynamics of marine mammals in order to
up to 80 kHz, so their spectra overlap with those make informed wildlife management decisions.
of the echolocation signals of bottlenose dolphins. Several theoretical models are being developed,
While the echolocation performance of two of the such as the Population Consequences of Acoustic
five dolphins used in the study was unaffected, the Disturbance model (PCAD; National Research
remaining three almost completely stopped echo-Council, 2005), and model principles have been
locating during their first exposure to the high-implemented in mathematical frameworks such
est sound level, suggesting that these dolphins as the Interim Population Consequences of
were distracted by the sounds (Branstetter et al., Disturbance model (iPCoD; King et al., 2015) and
2018). Wild bottlenose dolphins exposed to vibra-the Disturbance Effects of Noise on the Harbour
tory pile driving sounds (with energy in the 0 to Porpoise Population in the North Sea model
80 kHz range) may temporarily stop echolocating (DEPONS; Nabe-Nielsen et al., 2014, 2018).
and, thus, stop foraging (Branstetter et al., 2018). These models require input parameters such as
Pile driving sounds are unlikely to mask the the number of animals that will be significantly
echolocation signals of harbor porpoises, but affected by a noise disturbance, the energetic
they may distract foraging harbor porpoises since needs of a species (DEPONS), the relevant food
porpoises use echolocation to find, track, and availability (DEPONS), and other parameters
catch prey items (DeRuiter et al., 2009; Miller, affecting the vital rates (birth and death rates). So
2010; Wahlberg et al., 2015). When closing in far, most of the information that is needed is lack-
on their prey, usually small to medium-sized fish ing for most marine mammal species, though esti-
(Sveegaard et al., 2012; Wisniewska et al., 2016), mates for input parameters for the iPCoD model
harbor porpoises produce very rapid echoloca-have been made via an expert elicitation method
tion click sequences (DeRuiter et al., 2009). They (Donovan et al., 2016).
catch a fish by grabbing it with their teeth or by
The goal of this study was to contribute towards a
sucking it into their mouth cavity by withdraw-
more accurate assessment of an input parameter for
ing their tongue (Kastelein et al., 1997b). This
models of acoustic disturbances for the harbor por-
requires precision and good timing, skills that
poise. The effect of pile-driving playback sounds on
may be impaired if the porpoise is distracted by
the efficiency (success rate and speed) of attempts
underwater anthropogenic sounds. Such effects of
by harbor porpoises to catch fish in a controlled
sound have been observed in fish; they made more
environment is quantified.
prey-handling errors in the presence of intermit-
tent sound (Purser & Radford, 2011; Shafiei Sabet Methods
et al., 2015).
Harbor porpoises are relatively small and Study Animals
inhabit the cold temperate waters of the Northern The two harbor porpoises that participated in the
Hemisphere (Rice, 1998), so their thermoregu-study, an adult female and a subadult male, had
lation imposes energetic challenges (Lockyer, both been found stranded on the North Sea coast
2007). Because of their high relative heat loss and had been rehabilitated. The long duration of
and rapid life history, harbor porpoises have their rehabilitation deemed the porpoises unsuit-
been referred to as “aquatic shrews” (Kanwisher able for release, and they were therefore made
& Sundnes, 1965). To sustain their high meta-available for research. The female (identified as
bolic rates, harbor porpoises must spend a large porpoise F05) was ~11 mo old when she stranded;
portion of their time feeding (Wisniewska et al., the male (identified as porpoise M06) was ~7 mo
2016, 2018; Hoekendijk et al., 2017); and if their old. At the time of the study, both animals were
foraging is interrupted, they are susceptible to healthy and in good physical condition. Porpoise
starvation (MacLeod et al., 2007). Although the F05 had reached her maximum body length
resilience of harbor porpoises to anthropogenic (154 cm) and was 7 years old. Her weight varied
disturbances is debated (Wisniewska et al., 2016, between 43 and 46 kg during the study period.
2018; Hoekendijk et al., 2017), distraction of for-Porpoise M06 was 4 years old and still growing
aging harbor porpoises by pile driving sounds may (130 cm). His weight varied between 30 and 34 kg
have particularly detrimental impacts because of during the study period.
400 Kastelein et al.
Food Consumption with a 20-cm-thick layer of sloping sand on which
The harbor porpoises were normally fed four to aquatic vegetation grew and invertebrates lived.
five times a day on a diet of thawed sprat (Sprattus Skimmers kept the water level constant. Sea water
sprattus), herring (Clupea harengus), mackerel was pumped directly from the Eastern Scheldt, a
(Scomber scombrus), and squid (Loligo opales-lagoon of the North Sea, into the water circulation
cens). Vitamin supplements (Akwavit; Arie Blok system; partial recirculation through biological
Animal Nutrition, Woerden, The Netherlands) and sand filters ensured year-round water clarity
were added to the thawed fish. Fish were fed to and quality.
the porpoises at a temperature of ~4°C. The fish The pool water temperature was measured once
were weighed digitally (5 g accuracy), and the per day and varied between 2 and 15°C during
mass of each fish species eaten during each meal the study period. The minimum and maximum
was recorded. During experimental fish-catching air temperatures over each 24-h period were also
sessions, only thawed sprats were used (~15 cm recorded. The mean daily air temperature ranges
long). Before a session began, the sprats were (2.3 to 16.9°C in winter and 5.7 to 26.9°C in
dropped into a bucket of sea water, and only those summer) and salinity (~3.4%) experienced during
that sank were used (i.e., those which did not con-the study period by the captive study animals were
tain gas). similar to those experienced by wild conspecifics
in the North Sea (occurring ~200 m away on the
Study Area other side of the dyke in the Eastern Scheldt).
The study was conducted at the Sea Mammal
Research Company (SEAMARCO) Research Net Feeding Cage
Institute in the Netherlands. The animals were To quantify fish-catching efficiency, fish were
kept in a pool complex consisting of an outdoor offered to the harbor porpoises under water in
pool (12 × 8 m; 2 m deep; Figure 1) connected a custom-built net feeding cage (Figure 2). The
via a channel (4 × 3 m; 1.4 m deep) to an indoor cage was made of monofilament transparent twine
pool (8 × 7 m; 2 m deep). The bottom was covered net with a mesh size of 12 cm. The entire back of
Figure 1. The outdoor pool used for the study, showing the location of the test harbor porpoise (Phocoena phocoena) at the
start buoy, the net feeding cage, the underwater transducer, and the various aerial and underwater cameras. Also shown is
the research cabin which housed the sound-producing, sound-monitoring, and video-recording equipment and the operator.
During the sessions, the test porpoise remained to the left of the dashed central imaginary demarcation line. An air-bubble
screen reduced the high-frequency components of the impulsive broadband pile driving sound that could reach the indoor
pool where the non-test porpoise was housed while the test porpoise participated in the study.
401Effect of Pile Driving Sound on Fish-Catching Efficiency of Porpoises
Figure 2. The net feeding cage (104 cm wide, 188 cm high,
and 36 cm deep) which was placed in the water and attached
to the side of the pool by the suspension system (1) when in
use. The white markings (2) indicate the water level during
fish-catching trials. Top view camera mounting locations
are shown (3; aerial cameras #2 and 3; see Figure 1). The
back of the net feeding cage (4) was covered with white
pond liner so that fish remained in the cage. Fish that were
not caught by the harbor porpoise fell into the drop box (5)
made of black pond liner.
the cage was covered with white pond liner so that
the fish could not swirl through the meshes at the
back and get stuck between the cage and the side
of the pool. The lower sides and front of the net
cage were covered with black pond liner (36 cm
high) so that the porpoises could not access a fish
once it had reached the bottom of the net cage
within this so-called drop box.
Background Noise and Stimulus Measurements
Unless stated otherwise, acoustic terms and defini-
tions follow ISO 18405 Underwater Acoustics –
Terminology (ISO, 2017). The background noise and
pile driving sounds were measured via three hydro-
phones (Brüel & Kjaer [B&K] – 8106) with a mul-
tichannel high-frequency analyzer (B&K PULSE –
3560 D) and a laptop computer with B&K PULSE
software (Labshop, Version 12.1; sample frequency
used: 524,288 Hz). Before analysis, the recordings
were high-pass filtered (cut-off frequency 100 Hz;
3rd order Butterworth filter; 18 dB/octave) to remove
low-frequency sounds made by water surface move-
ments. The system was calibrated with a pistonphone
(B&K – 4223). The received sound pressure of the
impulsive pile driving sounds was analyzed in terms
of unweighted single-strike sound exposure level
(SELss) in dB re 1 µPa2s.
Fish-catching sessions were not performed
under unfavorable weather conditions such as
rain or hard wind (i.e., Beaufort wind force 6 or
more). Raindrops falling on the water surface may
distract the harbor porpoises or distort the images
made by the top view cameras. Strong wind may
move the water surface, thereby changing the
random swirling pattern of fish in the net feeding
cage. In addition, when the wind came from the
south, sessions were not performed if the Beaufort
wind force was 4 or more, as under these condi-
tions; the fish always moved towards the back of
the net cage where the porpoise could not reach
them. Only the people involved in the tests were
allowed within 15 m of the pool during sessions,
and they were required to stand still. During test
conditions without pile driving sounds, the back-
ground noise in the pool was below that typical of
sea state 0 (see Kastelein et al., 2012).
Pile-Driving Playback Sound
The sound intended to distract the harbor por-
poises consisted of playbacks of a series of off-
shore percussion (impulsive) pile driving sounds
recorded at 800 m from a 4.2-m diameter pile
being driven into the sea bed as the foundation for
a wind turbine for the Dutch offshore wind farm
“Egmond aan Zee” in the North Sea. No mitiga-
tion, such as bubble screens, was used. The strike
rate was 2,760/h. A WAV file was made of a series
of consecutive pile-driving strike sounds. The
original recordings were sampled at 65 kHz and
band-pass filtered between 50 Hz and 32.5 kHz.
For the generation of the WAV files used in the
study, signals were resampled to 88.2 kHz.
A random section of five strikes from the digi-
tized original recording of a series of pile driv-
ing sounds (WAV file) was played back repeat-
edly by a laptop computer (ASUS PC 1001 PXD)
with Adobe Audition, Version 3.0, to a digitally
controlled attenuator. The output went through a
custom-built variable passive low-pass filter (set
to 125 kHz), after which it went to a power ampli-
fier (East & West Inc. – LS5002), which drove
the transducer (Lubell – LL1424HP) through an
isolation transformer (Lubell – AC1424HP). The
transducer was placed at the southwestern end of
the pool at 2 m depth (~10 m away from the net
402 Kastelein et al.
feeding cage; Figure 1). The linearity of the trans-level in the pool, converted to SELss based on a
mitter system used for the pile-driving playback t pulse duration of 151 ms, was measured to be
sound deviated at most by 1 dB within a 42 dB in the range between
50 and 65 dB re 1 µPa2s in
range. the one-third octave bands between 100 Hz and
The sound distribution was measured both in 10 kHz. The spectrum and level of the playback
the general area where the harbor porpoises swam sound in the pool (Figure 3b) resembled the spec-
during the sessions (6 × 7 m, 1-m grid on the left tra of pile driving sounds recorded in shallow
side of the central dashed line in Figure 1; 42 loca-water at 7 km from a North Sea pile driving site
tions) and up to 1 m from the net feeding cage (Remmers & Bellmann, 2016). Below 600 Hz, the
(four locations). The SELss was measured at three energy at sea could not be replicated in the pool
depths per location (0.5, 1.0, and 1.5 m below the due to the characteristics of the transducer and the
surface). Three strikes were recorded per depth dimensions of the pool.
and location over a 10-s period. The analysis of a
single strike was done for a 500-ms time window. Experimental Procedure
The average received SELss (dB re 1 µPa2s) of the Before each session, the harbor porpoises were
played back impulsive sound, as experienced by not fed for approximately 2 h to ensure that their
the harbor porpoises when they were near the net motivation to feed was strong and consistent.
feeding cage, was calculated as the power average While they were in the indoor pool, the trans-
of all 12 individual measurement positions (four ducer and the net feeding cage were lowered into
locations, three depths at each). There were only the outdoor pool, and the video cameras were
small differences in SELss per position, showing activated (Figure 1). Then, the test porpoise for
that the sound field near the net feeding cage was that session was asked to swim into the outdoor
fairly homogeneous (Table 1). pool. The non-test porpoise was kept in the indoor
Both study animals were tested during expo-pool and was tested once the session with the first
sure to pile driving sounds at SELss = 125 dB, animal had been completed. The air-bubble screen
134 dB, and 143 dB re 1 µPa2s. Porpoise F05 (Figure 1) was lowered during each session; this
responded differently (she showed a profound reduced the high-frequency components of the
reaction by increasing swimming speed) to the pile driving sound in the indoor pool so that the
highest level than porpoise M06, so exposure to non-test animal was not disturbed by it.
SELss = 137 dB re 1 µPa2s was added to show a The fish-catching task required skill, con-
response gradient. Porpoise M06 was not exposed centration, and prior training (which had taken
to pile driving sound at SELss = 137 dB re 1 µPa2s 2 wks). Once the test porpoise had stationed at
because his pattern of behavior remained constant the start buoy near the trainer, 8 m from the net
at the highest and lower levels. Therefore, based feeding cage (Figure 1), the fish supplier held a
on the study animals’ behavior, the pile driving fish just under the water surface in the middle of
sounds were played back at three levels for por-the top of the net cage (always in the same posi-
poise M06 and at four levels for porpoise F05. tion; the fish was held horizontally, parallel to the
The highest amplitude was the maximum level pool wall, with its ventral side pointing down-
that could be produced by the sound emitting wards; Figure 4). The trainer counted out loud
system: a mean SELss of 143 dB re 1 µPa2s in from one to three, then gave a hand signal and the
the swimming area of the porpoise (the waveform vocal command “search” to send the porpoise to
is shown in Figure 3a). The background noise the net cage. The fish supplier released the fish
Table 1. The four mean (± standard deviation [SD]) exposure levels (expressed as SELss and peak level) and t90 of the pile-
driving playback sound in the area where the harbor porpoises (Phocoena phocoena) swam during the fish-catching sessions
(“Overall”; n = 126 locations) and in the 1 m area around the net feeding cage (“Cage”; n = 12 locations).
Mean SELss
(dB re 1µPa2s) ± SD
Mean t90
(ms) ± SD
Mean peak level
(dB re 1 µPa2) ± SD
Porpoise Overall Cage Overall Cage Overall Cage
F05 & M06 125 ± 2 123 ± 1 151 ± 11 158 ± 11 148 ± 2 146 ± 1
F05 & M06 134 ± 2 132 ± 1 151 ± 11 158 ± 11 157 ± 2 155 ± 1
F05 137 ± 2 135 ± 1 151 ± 11 158 ± 11 160 ± 2 158 ± 1
F05 & M06 143 ± 2 141 ± 1 151 ± 11 158 ± 11 166 ± 2 164 ± 1
403Effect of Pile Driving Sound on Fish-Catching Efficiency of Porpoises
when the trainer began counting with the word (Conrad), connected to a monitor (camera 3 in
“one.” After releasing the fish, the fish supplier Figure 1), allowed the fish supplier to see whether
sat down and was not visible to the porpoise. the fish was caught or not without distracting the
During each session, the porpoise and net feed- porpoise.
ing cage were filmed simultaneously by five cam-As the harbor porpoise swam towards the net
eras (Figure 1): one underwater camera on each feeding cage (usually taking ~3 s for the 8 m dis-
side of the net cage (Rollei Actioncam 300), one tance), the fish slowly swirled down through the
aerial top view camera (Rollei Actioncam 300) on water column (mean swirling time between sur-
a 1.5 m high pole, and one aerial camera on a 6-m- face and drop box, where the fish was no longer
high pole for a top view of the swimming tracks accessible to the porpoise: 30 s; SD: 6 s; range:
(GoPro Hero 3; Figure 1). Another aerial camera 14 to 40 s; n = 30). Once the porpoise reached
Figure 3. (a) The waveform of a pile-driving playback sound in the pool, measured at a distance of 2 m from the source and at
a depth of 1.5 m; and (b) the one-third octave (base-10) band spectra of a pile-driving playback sound in the pool measured at
the same location (at source levels corresponding to a mean SELss in the pool part used by the porpoises during the sessions
of 125, 134, and 143 dB re 1 µPa2s), and, for comparison, the one-third octave band spectrum of a pile driving sound recorded
at 7 km distance from a North Sea pile driving site (Remmers & Bellmann, 2016).
404 Kastelein et al.
the net cage, it (1) sucked or grabbed the fish
through the net and ingested it (“catch” or “suc-
cess”), (2) tried to catch the fish but was unable to
so the fish ended up in the drop box (“failure”), or
(3) abandoned any attempt to catch the fish before
the fish reached the drop box (“termination”; in
some cases, no attempt to capture the fish was
made, but the porpoise always swam towards the
net cage).
To catch a fish before it fell into the drop box,
the harbor porpoise had to be in the right place
(vertically and horizontally), and the fish had to
be near a hole in the net. The position of the fish
was partially determined by chance as it swirled
down through the water, but it could be manip-
ulated by currents created by the mouth of the
porpoise (suction) or by movement of its entire
body. After each trial, the porpoise returned to the
trainer at the start buoy and was then sent back to
the net feeding cage for the next trial.
Each session consisted of 20 trials per harbor
porpoise, and both porpoises were tested in
random order once a day, usually in the after-
noon. Sessions were conducted either in the low
background noise level of the pool or during play-
backs of the pile driving sound at three or four
(depending on the animal) source levels. Sessions
were conducted in random order; during sessions
with pile driving sound, the sound was played
back throughout the session (one strike every
1.2 s; 47 strikes/min). Data collection took place
between October 2017 and March 2018.
Data Collection and Analysis
The outcome of each trial (success, failure, or
termination) was recorded by the fish supplier at
the net feeding cage. A separate nominal logistic
regression (Hosmer & Lemeshow, 2000) was used
for each animal to assess the effects of the factor
SELss on the outcome of each trial, with success-
ful fish capture as the reference event and the
quiet condition as the reference level of SELss.
Video recordings of successful trials were ana-
lysed to quantify the catch time—the time between
the moment a fish was released (when the trainer
at the buoy said “one”) and when the fish was
caught. All catch times were quantified by the
same person, mostly using the video recordings
made by top view aerial camera #2 mounted on
the net cage (Figures 1 & 2). On the rare occa-
sions when a trial outcome was not clearly visible
on these video images, the video recordings from
underwater cameras #1 and 2, mounted on either
side of the net cage, were used. A general linear
model (Zar, 1999) was used to evaluate the effect
of the factors “porpoise” and “SELss” on the catch
time (which was log transformed to bring it close
to normal distribution). Assumptions of general
linear models were checked for and mostly met.
Some slight departures from homogeneity of
variances and normality occurred in the data, but
models are robust to such departures. All statisti-
cal analysis was conducted with Minitab 18; the
significance level was set at 5% (Zar, 1999).
In all, 1,640 trials were conducted in 57 sessions:
1,060 trials with porpoise F05 and 580 with por-
poise M06. The sample size for porpoise M06 was
lower than for porpoise F05, mainly because only
three SELss were tested. Overall, 991 trials resulted
in a successful fish catch, 373 trials resulted in fail-
ure, and 276 trials were terminated. Responses
differed greatly between the two study animals:
Compared to porpoise F05, porpoise M06 was
much more likely to capture fish successfully, less
likely to fail to catch a fish, and less likely to ter-
minate trials (Figure 5). The harbor porpoises also
used different fish-catching techniques. Porpoise
F05 approached the net feeding cage forcefully,
swimming fast, slowing down at the last moment,
and sometimes swimming on her back (i.e., with
her dorsal fin pointing down), thus causing water
displacement; she then used a biting technique to
grab the fish. Porpoise M06 used either this biting
and grabbing technique or the suction technique
(i.e., sucking the fish into his oral cavity by quickly
withdrawing his tongue; Kastelein et al., 1997b).
Porpoise F05 was observed to increase her swim-
ming speed at SELss above 134 dB dB re 1 µPa2s,
whereas porpoise M06 maintained a constant
swimming speed.
For porpoise F05, the nominal logistic regres-
sion model revealed a statistically significant
Figure 4. A schematic representation (lateral view) of the
experimental set-up used for the fish-catching task.
405Effect of Pile Driving Sound on Fish-Catching Efficiency of Porpoises
Figure 5. The outcomes of fish-catching trials, shown as percentages of the number of trials for each SELss (in total, there
were 1,060 trials with porpoise F05 and 580 with porpoise M06). Outcomes are shown as T = termination, F = failure,
and S = successful fish capture. Porpoise M06 had a higher overall success rate than porpoise F05. For porpoise F05 only,
success rate declined with increasing SELss (from 134 dB re 1 µPa2s), as failure rate remained approximately constant and
termination rate increased. Porpoise M06 was not tested during exposure to pile driving sound at 137 dB re 1 µPa2s because
his pattern of behavior remained constant even at the highest level (143 dB re 1 µPa2s). Porpoise F05 did behave differently
at the highest level, so the 137 dB re 1 µPa2s SELss was added to show a response gradient.
correlation between the outcome of the trials and affected by SELss but were affected by porpoise
the terms in the model (G = 96.88; p = 0.000). (Table 3); porpoise F05 had slightly longer catch
Trials were significantly more likely to be termi-times than porpoise M06 (untransformed and
nated when the SELss was 134 dB dB re 1 µPa2s uncorrected means ± SD: F05, 12.0 ± 4.2 s, n =
or above (Logit 1, comparing termination with 495; M06, 11.5 ± 4.1 s, n = 490).
success; Table 2); SELss had a significant effect
on trial outcome in Logit 1 (χ2 = 79.24; p = 0.000) Discussion and Conclusions
but not in Logit 2 (comparing failure with success,
χ2 = 1.98 ; p = 0.739). The odds of termination Substantial individual variation in the responses
were ~10 times
higher when SELss was 143 dB re of the two captive harbor porpoises to underwater
1 µPa2s than in quiet conditions (odds ratio = 9.79, sound was seen in the present study, which was
p = 0.000). Thus, as the SELss increased, there in line with results of research on bottlenose dol-
was an increasing likelihood of trial termination, phins (Branstetter et al., 2018). The fish-catching
but the trial failure rate was not affected by SELss ability of porpoise F05 was negatively influenced
(Logit 2; Table 2). by pile driving sounds, while porpoise M06’s per-
For porpoise M06, the nominal logistic regres-
formance remained constant in the presence of the
sion model revealed that there was no statistically
playback sound. Porpoise M06’s capture success
significant correlation between the outcome of the
rate was higher than porpoise F05’s in general and
trials and the terms in the model (G = 7.256; p =
was unaffected by the pile-driving sound play-
backs, even at the highest SELss. As the noise
The mean catch time in successful trials was level increased above SELss = 134 dB re 1 µPa2s,
11.7 ± 4.2 s (n = 985). Analysis of the log-trans-fish-catch success declined for porpoise F05, and
formed catch times showed that they were not she was more likely to terminate trials, especially
406 Kastelein et al.
Table 2. Results of the nominal logistic regression model to assess the effects of SELss on the outcome of each trial (success,
failure, or termination) for porpoise F05. The reference outcome is S (successful catch). Logit 1 relates S to T (termination)
and shows that trials were significantly more likely to be terminated when the SELss was 134 dB or above. The odds of
termination were ~10 times higher when SELss was 143 dB dB re 1 µPa2s than in quiet conditions (odds ratio = 9.79). Logit 2
relates S to F (failure) and shows that SELss had no significant effect on the trial failure rate.
Predictor Coefficient ± SE Z pOdds ratio
95% CI
Logit 1: (T/S)
Constant -1.4 ± 0.2 -7.49 0.000
SELss = 125 dB 0.2 ± 0.3 0.62 0.536 1.18 0.70-1.99
SELss = 134 dB 0.7 ± 0.2 2.99 0.003 2.11 1.29-3.43
SELss = 137 dB 1.2 ± 0.3 4.66 0.000 3.26 1.98-5.36
SELss = 143 dB 2.3 ± 0.3 7.80 0.000 9.79 5.52-17.38
Logit 2: (F/S)
Constant -0.5 ± 0.1 -3.81 0.000
SELss = 125 dB -0.1 ± 0.2 -0.37 0.715 0.92 0.63-1.38
SELss = 134 dB -0.1 ± 0.2 -0.38 0.706 0.92 0.62-1.39
SELss = 137 dB 0.1 ± 0.2 0.48 0.630 1.11 0.72-1.72
SELss = 143 dB 0.3 ± 0.3 0.94 0.346 1.34 0.73-2.47
Table 3. Results of the general linear model on the dependent variable “catch time” (log transformed) in successful trials only
to evaluate the effects of the factors “porpoise” and “SELss.” Source = source of variation, df = degrees of freedom, Adj SS
= adjusted sum of squares, and Adj MS = adjusted mean squares.
Source df Adj SS Adj MS F value p value
SELss 4 0.1664 0.04160 2.02 0.090
Porpoise 1 0.0915 0.09147 4.44 0.035
Error 979 20.1856 0.02062
Total 984 20.4332
at the highest SELss (Figure 5). This suggests that The decline in fish-catch success and the
her ability to catch fish was negatively affected increase in trial termination seen in porpoise F05
by the increasing sound levels, most of all by when unweighted broadband SELss increased
decreasing her motivation to complete a trial. In above 134 dB suggest that some harbor porpoises
addition, as porpoise F05 was observed to increase may experience a distraction threshold for percus-
her swimming speed at SELss above 134 dB, she sion pile driving sounds, approximately between
might have increased the task’s difficulty (and 125 and 134 dB re 1 µPa2s. Distraction is defined
thus decreased the chance of success) in some herein as the involuntary diversion of attention
trials herself by displacing more water than usual from one stimulus or set of stimuli to another. In
(see below) and pushing the fish temporarily out this case, the decrease in success rate for porpoise
of reach. During such trials, which only rarely F05 suggested that the (auditory) stimuli of play-
occurred, a decreased motivation might have led back pile driving sounds diverted her attention
porpoise F05 to decide not to wait for the fish to from the fish-catching task. Since actual echolo-
come within reach again before it reached the cation activity was not measured in this study, we
drop box. can only speculate that the decrease in fish-catch
407Effect of Pile Driving Sound on Fish-Catching Efficiency of Porpoises
success rate exhibited by porpoise F05 was caused Goldbogen et al., 2013) and for squid-hunting
by a decrease in vigilance behavior similar to that sperm whales (Physeter macrocephalus; Miller
in the bottlenose dolphins tested by Branstetter et al., 2004). Using electronic tags, Akamatsu
et al. (2018). Besides distraction, aversive stimuli, et al. (2010) observed rolling dives in finless por-
such as loud sounds, may influence motivation- poises (Neophocaena phocaenoides) in which the
related behaviors, as has been shown for grey porpoises often rotated their bodies more than 60°
seals (Halichoerus grypus; Götz & Janik, 2010). around the body axis in a dive bout. This behavior
For instance, avoidance behavior may be induced, occupied 31% of the dive duration, and the rolling
and foraging behavior may be suppressed. The dives were associated with extensive searching
latter seems to be the case for porpoise F05: at effort. The authors suggest that the finless por-
the highest SELss, she terminated over half of all poises searched extensively for targets and rolled
trials, even though hunger was the intrinsic moti-their bodies to enlarge the search area by changing
vation for both porpoises to perform the task. This the narrow beam axis of their biosonar. Though
decrease in motivation is also consistent with the echolocation was not recorded, occasional checks
findings by Branstetter et al. (2018). Finally, the with a hydrophone and a bat detector showed that
increase in swimming speed observed in porpoise the harbor porpoises in the present study did use
F05 for the highest SELss is consistent with the echolocation in addition to vision when approach-
behavioral response of captive harbor porpoises ing the net cage with the fish.
to pinger-like sounds observed by Teilmann et al.
The suction technique in harbor porpoises was
(2006). In their study, Teilmann et al. also mea-
described in detail by Kastelein et al. (1997b).
sured a concurrent increase in heart rate, indicat-
The biting and grabbing technique and the suction
ing stress. The concept of stress, however, is diffi-
technique have also been observed in harbor seals
cult to define, and more accurate measurements of
(Phoca vitulina; Marshall et al., 2014). In the set-
stress in relation to sound exposure would require
ting of the present study, porpoise F05 was a less
a physiological approach (e.g., Romano et al.,
effective forager than porpoise M06. Porpoise F05
2004). Regardless, stress could have been a factor
approached the net cage at higher speeds than por-
contributing to distraction from and/or a decrease
poise M06 and, because of her speed and because
in motivation to perform the fish-catching task.
she was bigger than porpoise M06, she displaced
Surprisingly, the catch times in successful trials
more water and produced more waves, which
remained stable for porpoise F05 with increasing
sometimes pushed the fish towards the back of the
SELss. When the same harbor porpoises involved
net cage, thus making it more difficult to retrieve
in the present study were asked to perform a fish-
the fish.
searching task while exposed to various intermit-Measurements in shallow parts of the North
tent and continuous sounds at two different levels Sea (34 m deep) show that the spectrum of the
in another behavioral response study, search times playback sound at a broadband SELss = 134 dB
were also found to be stable (Kok et al., 2018). re 1 µPa2s in the present study resembles the
Individual differences in the harbor porpoises’ spectrum of pile driving sounds recorded at 7 km
approach to the fish-catching task also became from a pile driving site at frequencies above about
apparent: porpoise F05 terminated trials more 500 Hz (Remmers & Bellmann, 2016). The cor-
readily than porpoise M06 (Figure 5), and she took responding unweighted broadband SELss mea-
slightly longer to catch fish in successful trials. In sured in the field was 163 dB re 1 µPa2s. However,
a study of prey-searching behavior by the same harbor porpoises can probably sense the distance
porpoises, Kok et al. (2018) found that porpoise to a sound source due to reverberations, which
M06 spent less time searching than porpoise F05. may affect their reaction to a sound apart from the
The two harbor porpoises certainly had dif-received SELss. Porpoises have a low hearing sen-
ferent fish-catching techniques. Porpoise M06 sitivity for low-frequency sounds, so pile driving
approached the net feeding cage relatively slowly sounds with a frequency content below 500 Hz,
and used either the biting and grabbing tech-which could not be reproduced in this playback
nique or the suction technique. He sometimes study, are unlikely to be relevant for their behav-
pushed himself as far as possible into the net to ioral response (Tougaard et al., 2015). However,
reach the fish. Porpoise F05 did not use the suc-individual differences in both fish-catching suc-
tion technique and did not push into the net cage. cess (even in ambient conditions) and termina-
She sometimes rotated horizontally and grabbed tion rates may complicate the quantification of
the fish through the net while swimming with her the impacts of percussion pile driving sounds
dorsal fin pointing down. It is not known whether on harbor porpoises. Individual differences in
this twisting maneuver is normal during prey responses to sound found in both bottlenose dol-
capture by harbor porpoises, as it is for lunge- phins (Branstetter et al., 2018) and in harbor por-
feeding blue whales (Balaenoptera musculus; poises (present study) could be due to differences
408 Kastelein et al.
in a wide range of factors that may, or may not, be porpoises: Acoustic monitoring of echolocation activ-
quantifiable, such as sex, motivation, age, history, ity using porpoise detectors (T-PODs). Marine Ecology
reproductive state, body condition, degree of need Progress Series, 321, 295-308.
for food, or character. meps321295
Dähne, M., Gilles, A., Lucke, K., Peschko, V., Adles, S.,
Acknowledgments Krügel, K., . . . Siebert, U. (2013). Effects of pile-driv-
ing on harbour porpoises (Phocoena phocoena) at the
We thank assistants Stacey van der Linden, Ruby
first offshore windfarm in Germany. Environmental
van Kester, Kimberly Biemond, and Naomi Claeys,
Research Letters, 8, 1-16.
and students, Britt Spinhoven, Jennifer Smit, Tessa
Kreeft, and Femke Bucx, for their help with the
DeRuiter, S. L., Bahr, A., Blanchet, M-A., Hansen, S. F.,
data collection. We thank Bert Meijering (Topsy
Kristensen, J. H., Madsen, P. T., . . . Wahlberg, M.
Baits) for providing space for the SEAMARCO
(2009). Acoustic behaviour of echolocating porpoises
Research Institute. We thank Arie Smink for the
during prey capture. Journal of Experimental Biology,
design, construction, and maintenance of the elec-
212, 3100-3107.
tronic equipment, and Rob Triesscheijn for creat-
Donovan, C., Harwood, J., King, S., Booth, C., Caneco,
ing Figures 1 and 4. We thank Erwin Jansen (TNO)
B., & Walker, C. (2016). Expert elicitation methods in
for the sound measurements. We also thank Floor
quantifying the consequences of acoustic disturbance
Heinis (HWE Consulting), Cormac Booth (SMRU
from offshore renewable energy developments. In A. N.
Consulting), Inger van den Bosch (Netherlands
Popper & A. Hawkins (Eds.), The effects of noise on
Ministry of Infrastructure and Water Management),
aquatic life: II. Advances in experimental medicine and
Suzanne Lubbe (Netherlands Ministry of Infra-
biology (pp. 29-31). New York: Springer.
structure and Water Management), and two anony-
Gabriel, J., Neumann, T., Grießmann, T., & Rustenmeier, J.
mous reviewers for valuable comments on the
(2011). Results of underwater sound research projects
manuscript. Funding for this project was obtained
focused on construction noise caused by offshore wind
from Gemini, Buitengaats C.V. (PO GEM-03-
farms. Wilhelmshaven, Germany: DEWI GmbH. 4 pp.
185; contact Luuk Folkerts). The harbor porpoises
Goldbogen, J. A., Calambokidis, J., Friedlaender, A. S.,
were tested under authorization of the Netherlands
Francis, J., DeRuiter, S. L., . . . Southall, B. L. (2013).
Ministry of Economic Affairs, Department of Nature
Underwater acrobatics by the world’s largest predator:
Management, with Endangered Species Permit
360° rolling manoeuvres by lunge-feeding blue whales.
FF/75A/2009/039. We thank the ASPRO group for
Biological Letters, 9, 20120986.
making the porpoises available for this study.
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... A limited number of studies have investigated the effects of sound exposure on the foraging behaviour (e.g. Aguilar Soto et al., 2006;Blair et al., 2016) and prey capture rates (Kastelein et al., 2019;Wisniewska et al., 2018) of marine mammals, and have inferred that these might have longer-term fitness consequences (e.g. Blair et al., 2016;Williams et al., 2006). ...
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Avoidance of anthropogenic sounds has been measured in many species. The results, which are typically based on observations in limited exposure contexts, are frequently used to inform policy and the regulation of industrial activities. However, the occurrence and magnitude of avoidance may be a consequence of complex risk‐balancing decisions made by animals. The importance of the factors in decision‐making, such as perceived risks associated with the sounds or prey quantity and quality during sound exposure, is unknown. Here we address this knowledge gap by measuring the relative influence of perceived risk of a sound (silence, pile driving, and a tidal turbine) and prey patch quality on decision making and foraging success in grey seals (Halichoerus grypus). Seals were given access to two underwater ‘prey patches’ in an experimental pool where fish were delivered at controlled rates to simulate a low density (LD) and a high density (HD) prey patch. Acoustic playbacks were made using an underwater speaker above one of the prey patches (randomised during the study), and three decision and foraging metrics (foraging duration, foraging effort allocation between the prey patches, and foraging success) were measured. Foraging success was highest during silent controls and was similar regardless of speaker location (LD/HD). Under the tidal turbine and pile driving treatments, foraging success was similar to the controls when the speaker was located at the HD prey patch but was significantly reduced (~16‐28% lower) when the speaker was located at the LD prey patch. Foraging decisions by the seals were consistent with a risk/profit balancing approach. Avoidance rates depend on the quality of the prey patch as well as the perceived risk. Policy implications: The results suggest that foraging context is important when interpreting avoidance behaviour and should be considered when predicting the effects of anthropogenic activities. For example, sound exposure in different prey patch qualities may result in markedly different avoidance behaviour, potentially leading to contrasting predictions of impact in Environmental Assessments. We recommend future studies explicitly consider foraging context, and other contextual factors such as behavioural state (e.g. foraging or travelling) and habitat quality.
... The actual impact of such offshore constructions on the marine environment, however, remains unclear in some aspects. Studies are available on the influence of noise emissions on mammals (Carstensen et al., 2006;Dolman and Jasny, 2015;Kastelein et al., 2019;Rose et al., 2019), on seabird habitat changes (Larsen and Guillemette, 2007;Busch et al., 2013;Best and Halpin, 2019;Goodale et al., 2019), on pelagic primary productivity (Slavik et al., 2018), on ocean turbulence (Carpenter et al., 2016;Grashorn and Stanev, 2016;Schultze et al., 2017;Callies et al., 2018) and even on concepts for multi-use of OWFs in terms of marine aquaculture systems (Buck et al., 2008(Buck et al., , 2017. A comprehensive report on a multi-disciplinary monitoring program was recently published by the Royal Belgian Institute of Natural Sciences studying most of the afore mentioned aspects for the Belgian part of the North Sea (Degraer et al., 2019). ...
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The impact of offshore constructions on the marine environment is unknown in many aspects. The application of Al- and Zn-based galvanic anodes as corrosion protection results in the continuous emission of inorganic matter (e.g. >80 kg Al-anode material per monopile foundation and year) into the marine environment. To identify tracers for emissions from offshore wind structures, anode materials (Al-based and Zn-based) were characterized for their elemental and isotopic composition. An acid digestion and analysis method for Al and Zn alloys was adapted and validated using the alloy CRMs ERM®-EB317 (AlZn6CuMgZr) and ERM®-EB602 (ZnAl4Cu1). Digests were measured for their elemental composition by ICP-MS/MS and for their Pb isotope ratios by MC ICP-MS. Ga and In were identified as potential tracers. Moreover, a combined tracer approach of the elements Al, Zn, Ga, Cd, In and Pb together with Pb isotope ratios is suggested for a reliable identification of offshore-wind-farm-induced emissions. In the Al anodes, the mass fractions were found to be >94.4% of Al, >2620 mg kg⁻¹ of Zn, >78.5 mg kg⁻¹ of Ga, >0.255 mg kg⁻¹ of Cd, >143 mg kg⁻¹ of In and >6.7 mg kg⁻¹ of Pb. The Zn anodes showed mass fractions of >2160 mg kg⁻¹ of Al, >94.5% of Zn, >1.31 mg kg⁻¹ of Ga, >254 mg kg⁻¹ of Cd, >0.019 mg kg⁻¹ of In and >14.1 mg kg⁻¹ of Pb. The n(²⁰⁸Pb)/n(²⁰⁶Pb) isotope ratios in Al anodes range from 2.0619 to 2.0723, whereas Zn anodes feature n(²⁰⁸Pb)/n(²⁰⁶Pb) isotope ratios ranging from 2.0927 to 2.1263.
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Offshore wind energy is a renewable source with strong prospects of development that may decisively contribute to guarantee energy independence for several world countries. Worldwide offshore wind capacity has increased significantly over the past decade with 22 GW installed by the end of 2018; this capacity presents itself as an effective tool for several countries to address their renewable production targets, as extensive areas of strong winds are available offshore. However, offshore wind is not yet cost competitive within the European electricity markets, and frequently requires support schemes to finance the extensive capital cost requirements. Therefore, cost reductions are critical to make offshore wind technologies competitive within the electricity markets. Structural Health Monitoring systems are currently used in the inspection of the structural integrity of mechanical structures, with the main goal of guaranteeing safe operation, thus minimizing failure occurrence – they can, then, contribute to cost reduction within offshore wind implementation. Until now, structural health monitoring systems have not been the focus of much research from the agencies and stakeholders regarding its implementation in the OSW field. Towers and foundations can indeed be considered to be very reliable structures. This does not mean, however, that these structures are flawless, which means monitoring systems may possess a relevant role on OSW operations in the future. The main objective of this work is to evaluate the viability of structural health monitoring systems on the support structures of offshore wind. This evaluation is sustained by a holistic framework which is divided in three different branches of research. Firstly, the evaluation of the socio-economic and environmental impacts of offshore wind implementation is done. It is fundamental to understand what are the policy frameworks that are necessary to promote the installation of technologies that are not yet iv commercially competitive, and how these frameworks are shaping themselves to help bring costs down. Then, the technical implementation of structural health monitoring systems on offshore wind supporting structures is investigated. A computationally aided engineering methodology is used to provide insights on the types of monitoring systems which are most relevant, and the cost of these systems is estimated at the end using data provided by sensor manufacturers and providers. Finally, the impact of structural health monitoring systems on the life-cycle costs of offshore wind is evaluated, using several economic models that estimate the capital expenditures of future farms, the impact of using structural monitoring systems on the revenues of the farm, and the overall non-discounted and discounted cash flows of a certain farm. A model that evaluates the optimum year for farm repowering, considering that turbines are getting more efficient, powerful and cheaper, is also presented. The general results obtained from the produced research seem to indicate that installing structural health monitoring systems on the support structures of offshore wind can provide economic benefits related with potential savings from insurance costs. Moreover, the use of these systems can shift the maintenance strategies from preventive to predictive-based, which allows the intervals between inspections to be increased without equipment loss. However, the greatest benefit seems to be related with the possibility of extending the operational life of a certain farm, as this may result in additional revenues of dozens or hundreds of millions of euros. Also, the research concluded that monitoring the support structures of a certain farm at a particular cadency (for example, one in each 10 foundations), as it is currently defined on the respective standards, does not seem to provide any of the benefits that these systems can bring at the operational and economic levels.
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The question of how individuals acquire and allocate resources to maximize fitness is central in evolutionary ecology. Basic information on prey selection, search effort, and capture rates are critical for understanding a predator's role in its ecosystem and for predicting its response to natural and anthropogenic disturbance. Yet, for most marine species, foraging interactions cannot be observed directly. The high costs of thermoregulation in water require that small marine mammals have elevated energy intakes compared to similar-sized terrestrial mammals [1]. The combination of high food requirements and their position at the apex of most marine food webs may make small marine mammals particularly vulnerable to changes within the ecosystem [2-4], but the lack of detailed information about their foraging behavior often precludes an informed conservation effort. Here, we use high-resolution movement and prey echo recording tags on five wild harbor porpoises to examine foraging interactions in one of the most metabolically challenged cetacean species. We report that porpoises forage nearly continuously day and night, attempting to capture up to 550 small (3-10 cm) fish prey per hour with a remarkable prey capture success rate of >90%. Porpoises therefore target fish that are smaller than those of commercial interest, but must forage almost continually to meet their metabolic demands with such small prey, leaving little margin for compensation. Thus, for these "aquatic shrews," even a moderate level of anthropogenic disturbance in the busy shallow waters they share with humans may have severe fitness consequences at individual and population levels.
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Wahlberg and his colleagues explore the concept of Umwelt, the comprehensive picture of the world an animal forms from all of its senses as it relates to the acoustic abilities of the harbor porpoise. This close connection has allowed them to tease out details of how the animals produce sounds, as well as how they hear and echolocate simultaneously. Adult harbor porpoise females weigh about 60 kilograms and are about 170 centimeters in length whereas adult males are about 45 kilograms and 150 centimeters long. When the clicks bounce off a fish or another item in the water, a faint echo returns. If the echo is audible to the porpoise, the delay time from the emitted click to the returning echo tells the porpoise the distance to the fish and, with its sensitive hearing, the porpoise can also determine the direction to the prey. Thus, the porpoise has a built-in echo sounder it can use for echolocating prey and for orientation. When swimming and searching for prey, harbor porpoises emit clicks about 20 times a second. When homing in on prey, the click rate increases and ends at several hundred clicks per second in what's called a terminal buzz when the prey is captured. Besides echolocation, porpoises also use their high-pitched clicks for communication. By varying the repetition rate of clicks, porpoises can express various types of signals, but the meaning of these click patterns is still largely unknown.
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Anthropogenic sound is a potential stressor for marine mammals that may affect health, as has been demonstrated in other mammals. Therefore, we have initiated investigations on the effects of intense underwater sounds on nervous system activation and immune function in marine mammals. Blood samples were obtained before and after sound exposures (single underwater impulsive sounds (up to 200 kPa) produced from a seismic water gun and (or) single pure tones (up to 201 dB re 1 µPa) resembling sonar "pings" from a white whale, Delphinapterus leucas, and a bottlenose dolphin, Tursiops truncatus, to measure neural-immune parameters. Norepinephrine, epinephrine, and dopamine levels increased with increasing sound levels and were significantly higher after high-level sound exposures (>100 kPa) compared with low-level sound exposures (100 kPa) qu'après une exposition à un son de basse intensité (
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This paper reviews some specific studies of cetacean life history energetics over the past 20–30 y that include one of the largest species, the baleen fin whale, Balaenoptera physalus, the medium-sized odontocete long-finned pilot whale, Globicephala melas, and one of the smallest marine odontocetes, the harbour porpoise, Phocoena phocoena. Attention is drawn to the decrease in longevity with size and the differences in biological parameters that reflect this and affect life history strategy and energy utilization. Data from the past whaling industry in Iceland for fin whales, the Faroese ‘grindedrap’ for pilot whales, and by-catches as well as some live captive studies for harbour porpoise have been used. The studies demonstrate how information can be gathered to compile energy budgets for individuals, relying on carcase measurement and analysis, dietary investigations, biochemical analyses of tissues, and general life history studies including reproduction; as well as from monitoring living animals. The individual examples presented show how food energy storage in the form of fat can be variously important in insulation in the smallest species to controlling reproductive efficiency in large migratory species. The paper concludes by noting that an understanding of energy use in the individual can be an important input in multi-species ecosystem modelling.
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Behavioral reactions of harbor porpoises (Phocoena phocoena) to underwater noise from pile driving were studied. Steel monopile foundations (4 m diameter) for offshore wind turbines were driven into hard sand in shallow water at Horns Reef, the North Sea. The impulsive sounds generated had high sound pressures [source level 235 dB re 1 microPa(pp) at 1 m, transmission loss 18 log(distance)] with a strong low frequency emphasis but with significant energy up to 100 kHz. Reactions of porpoises were studied by passive acoustic loggers (T-PODs). Intervals between echolocation events (encounters) were analyzed, and a significant increase was found from average 5.9 h between encounters in the construction period as a whole to on average 7.5 h between first and second encounters after pile driving. The size of the zone of responsiveness could not be inferred as no grading in response was observed with distance from the pile driving site but must have exceeded 21 km (distance to most distant T-POD station).
The effects of noise on Ministry of Infrastructure and Water Management), aquatic life: II. Advances in experimental medicine and Suzanne Lubbe (Netherlands Ministry of Infrabiology
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Heinis (HWE Consulting), Cormac Booth (SMRU from offshore renewable energy developments. In A. N. Consulting), Inger van den Bosch (Netherlands Popper & A. Hawkins (Eds.), The effects of noise on Ministry of Infrastructure and Water Management), aquatic life: II. Advances in experimental medicine and Suzanne Lubbe (Netherlands Ministry of Infrabiology (pp. 29-31). New York: Springer. structure and Water Management), and two anony-
Results of underwater sound research projects manuscript. Funding for this project was obtained focused on construction noise caused by offshore wind from Gemini
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Gabriel, J., Neumann, T., Grießmann, T., & Rustenmeier, J. mous reviewers for valuable comments on the (2011). Results of underwater sound research projects manuscript. Funding for this project was obtained focused on construction noise caused by offshore wind from Gemini, Buitengaats C.V. (PO GEM-03-farms. Wilhelmshaven, Germany: DEWI GmbH. 4 pp.
Applied logistic Sea
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the Horns Rev II offshore wind farm in the Danish North Hosmer, D. W., & Lemeshow, S. (2000). Applied logistic Sea. Marine Ecological Progress Series, 421, 205-216. regression. New York: Wiley.
consumption and body weight of harbour porpoises Impacts of offshore wind farm construction on harbour (Phocoena phocoena)
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Carstensen, J., Hendriksen, O. D., & Teilmann, J. (2006). consumption and body weight of harbour porpoises Impacts of offshore wind farm construction on harbour (Phocoena phocoena). In A. J. Read, P. R. Wiepkema, &