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Effects of Whale-Watching Vessels on Adult Male Sperm Whales Off Andenes, Norway

  • Whalesafari AS / Aarhus University

Abstract and Figures

This study investigated the effects of whale-watching vessels (WWV) on solitary sperm whales off Andenes in northern Norway. The presence of WWV did not have a significant effect on the duration of the surface and foraging dive periods or on the respiration pattern and dynamics. However, the presence of WWV made sperm whales almost seven times more likely to perform a near-surface event (NSE). NSEs are submersions without fluking for short periods of time that take place during the surface phase. The occurrence of NSEs led to a significant increase of 75% in surface time, which is 6 min more at the surface that were not compensated with longer foraging dives. Additionally, the occurrence of NSEs was associated with changes in the animals' respiration pattern and dynamics. Data collection concerning NSEs and respiration dynamics (both parameters assessed here for the first time) is strongly recommended in future impact studies on this species. NSEs may be indicators of disturbance and are reasonably easy to identify, and thus identifying and better understanding the causes of this behavior have management implications.
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Tourism in Marine Environments, Vol. 11, No. 4, pp. 215–227 1544-273X/16 $60.00 + .00
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1Current affiliation: Wild Earth Foundation, Av de las Ballenas 9500, Puerto Pirámides, Peninsula Valdes, Chubut, Argentina.
Address correspondence to A. Mel Cosentino, 1 Roslin Terrace, Aberdeen, AB24 5LJ, UK. Tel: +44-7806648692;
cetaceans and whale-watching vessels has raised
concerns over the potential impact of the activity.
Short-term effects have been reported worldwide
for many cetacean species. The presence of whale-
watching vessels has been associated with changes
in surface behavior and changes in activity and
energy budgets, including reduction of resting and
foraging bouts (Constantine, Brunton, & Dennis,
2004; Lusseau, 2003b; Lusseau, 2004; Lusseau,
Whale watching is a growing form of wildlife
tourism. Over 13 million people go whale and
dolphin watching in 119 countries every year
(O’Connor, Campbell, Cortez, & Knowles, 2009),
generating over US$2.1 billion in revenues, directly
and indirectly (e.g., travel expenses and accommo-
dation). However, the increased interaction between
*School of Biological Sciences, University of Aberdeen, Aberdeen, UK
†Marine Research and Education Fund of Andenes, Andenes, Norway
This study investigated the effects of whale-watching vessels (WWV) on solitary sperm whales off
Andenes in northern Norway. The presence of WWV did not have a significant effect on the dura-
tion of the surface and foraging dive periods or on the respiration pattern and dynamics. However,
the presence of WWV made sperm whales almost seven times more likely to perform a near-surface
event (NSE). NSEs are submersions without fluking for short periods of time that take place during
the surface phase. The occurrence of NSEs led to a significant increase of 75% in surface time, which
is 6 min more at the surface that were not compensated with longer foraging dives. Additionally, the
occurrence of NSEs was associated with changes in the animals’ respiration pattern and dynamics.
Data collection concerning NSEs and respiration dynamics (both parameters assessed here for the
first time) is strongly recommended in future impact studies on this species. NSEs may be indicators
of disturbance and are reasonably easy to identify, and thus identifying and better understanding the
causes of this behavior have management implications.
Key words: Sperm whale; Tourism impact; Behavior; Respiration
in the world where whale watching is focused on
adult male sperm whales, together with Japan and
New Zealand (Hoyt, 2001; O’Connor et al., 2009).
Only solitary adult male sperm whales inhabit
high latitudes, as it is the case off Andenes, in
Northern Norway (e.g., Letteval et al., 2002). These
males migrate back to breeding areas in warmer
waters, although the frequency and routes of those
migrations remain unknown. Roving males and
sexual dimorphism indicates size-dependent male
competition (Whitehead, 1994); thus, high ener-
getic returns are needed in order to reach and main-
tain a greater size. This could explain why males
migrate to distant feeding grounds in high produc-
tivity areas, such as the deep waters of the Bleik
Canyon in Northern Norway (Sundby, 1984).
Studies on the impact of whale-watching vessels
on the behavior of solitary adult male sperm whales
Bain, Williams, & Smith, 2009; Stamation, Croft,
Shaughnessy, Waples, & Briggs, 2009; Stockin,
Lusseau, Binedell, Wiseman, & Orams, 2008;
Visser et al., 2011; Whaley, Wright, Bonnelly de
Calventi, & Parsons, 2007; Williams, Trites, &
Bain, 2006).
In Norway, the whale-watching industry has
been growing at an annual rate of about 5% (Dutton,
2011; International Whaling Commission [IWC],
2011; O’Connor et al., 2009), with over 35,000
visitors in 2008 (O’Connor et al., 2009). The two
largest companies are based in Andenes and Stø,
in the Vesterålen archipelago in Northern Norway
(Fig. 1), and, together with a third operator (also
based in Andenes), conduct daily trips in the same
waters during the summer months. The main tar-
geted species is the sperm whale (Physeter mac-
rocephalus). This is one of the only three locations
Figure 1. Location and detailed map of the study area in Northern Norway. Whale-watching trips depart from
Andenes and Stø. Contour interval is 250 m; thicker lines show 1000 m and 2000 m, respectively.
the management of the activity, both in the study
area and beyond.
Study Area
This study was conducted in waters off Andenes,
in Northern Norway. On the northwest side of
Andøy Island there is a deep submarine canyon
known as Bleik Canyon that reaches depths of near
2,000 m towards the end of the continental shelf,
and where sperm whales have been found histori-
cally (Ciano & Huele, 2001; unpublished data from
Hvalsafari). On the east side of the island there is a
350–500-m-deep fjord, known as Andfjord, where
whales have also been encountered in recent years
(unpublished data from Hvalsafari) (Fig. 1).
Data Collection
Data were collected during the summer months
of 2012 onboard a 28.46-m whale-watching ves-
sel that was used as an opportunistic research ves-
sel (hereafter “research vessel”). The research vessel
typically conducted two trips per day. Depending
on weather conditions, before the first trip of the
day (and when required), a land-based observer
scanned the study area using Bigeyes® binoculars
(25×, 80 mm). Land-based observers were trained
by an experienced observer (i.e., the author). Loca-
tion of animals at sea was approximated through the
use of an internal reticule system (i.e., distance) and
a graduated wheel (i.e., bearing), and the approxi-
mate distance and direction to the animals were
then provided to the team on the vessel.
Onboard the research vessel, whales were tracked
acoustically using two mounted directional hydro-
phones. The incoming signals were monitored by an
operator equipped with a pair of headphones. Due to
stereo effect, the operator would determine whether a
given signal was on the port side or the starboard side.
The vessel would turn slowly to the side where the
signal is stronger. The procedure would be repeated
until the signal on both hydrophones is equally strong,
when the bearing to the whale would simply be the
heading of the vessel. The stronger the signal, the
closer the whale (Nielsen & hl, 2006). As sperm
whales in the study area typically cease clicking a few
in feeding grounds have been carried out off the
coasts of Kaikoura, in New Zealand. The presence
of whale-watching vessels has been associated with
more erratic breathing, changes in the interbreath
interval, and reduced surface time (Gordon, Leaper,
Hartley, & Chappell, 1992; Markowitz, Richter, &
Gordon, 2011; Richter, Dawson, & Slooten, 2003,
2006). These authors also mentioned that whales
would occasionally “shallow dive” when disturbed
(e.g., during close vessel approaches). The term
“shallow dive” was coined by Gordon et al. (1992),
who described it simply as “diving without fluk-
ing.” Given the potential for confusing this term
with dives in shallow waters, this behavior (studied
here for the first time in an impact study) has been
renamed as “near surface event” (NSE).
In previous studies, encounters where sperm whales
performed a NSE were terminated (i.e., not further
monitored) and data were excluded from further
analysis (Gordon et al., 1992; Markowitz et al., 2011;
Richter et al., 2003, 2006). These NSEs are short
underwater periods that do not involve foraging (i.e.,
the whales are not clicking) and appear to interrupt
resting and normal oxygen intake. They also appear
to entail an unnecessary increase in energy expendi-
ture, especially when accompanied by an avoidance
behavior. Alterations in the behavioral budget result-
ing in reduced energy intake or increased energy
expenditure affect the overall energetic budget, and
thus potentially the fitness of the individual or popula-
tion (e.g., Lusseau, 2004; Lusseau & Bejder, 2007).
This study investigates the effects of whale-
watching vessels on the behavior of solitary adult
male sperm whales off Andenes. To that end, and to
allow for comparison with previous studies on adult
male sperm whales off Kaikoura (Gordon et al.,
1992; Markowitz et al., 2011; Richter et al., 2003,
2006), data were collected on the respiration pat-
tern and dynamics as well as on the duration of sur-
facings and foraging dives. Additionally, data were
collected on the occurrence and duration of NSEs.
Both NSEs and the respiration dynamics were
assessed here for the first time in an impact study
for sperm whales. Lastly, consideration is given to
whether the observed short-term effects could have
long-term consequences for the individuals.
The results of this study are important to
the understanding of sperm whales’ behavioral
response to disturbance and have implications for
occurrence of NSEs. NSEs are considered a compo-
nent of the surface phase of the sperm whale forag-
ing bouts and were used as a covariate. Additionally,
coordinates were recorded using a portable Garmin
eTrex GPS. These coordinates were used both to map
the sightings (Fig. 2) as well as to obtain water depth
as described below.
Lastly, when the whale fluked, pictures of the
dorsal and ventral side of the fluke were taken for
photo identification purposes using a Canon 1000D
SLR camera fitted with a 70-3000mm Canon lens or
a Canon EOS 40D fitted with a 28-135-mm Canon
lens. Fluke images from each trip were organized
and edited using Adobe Photoshop CS5. When an
individual was first observed in the season, it was
given a consecutive identification number (ID), 1
being the first whale identified in the season.
A sighting was considered to be “in the presence
of a whale-watching vessel” (WWV) when a WWV
minutes before surfacing, it was possible to anticipate
when the whale that was being monitored was about
to surface. Given that there were at least two observ-
ers onboard the research vessel, it is fair to assume
that the whale was spotted as soon as, or right after, it
appeared on the surface. When whales were spotted,
small movements were made to reposition the vessel
parallel to the whale and (not directly) behind it, to
allow for a proper photo ID of the individual.
During every whale encounter and using an Olym-
pus Recorder WS-750M, the following data were
collected: weather conditions (sea state, wind speed,
and direction); time of surfacing and time of dive (i.e.,
fluking) to calculate the duration of surfacing; dura-
tion of foraging dives (i.e., time between fluking and
resurfacing) to the nearest minute, when two consecu-
tive sightings of the same whale occurred; interbreath
intervals (to the nearest second) to study the respira-
tion pattern and dynamics (described below); and the
Figure 2. Sightings of sperm whales (Physeter macrocephalus) in the study area (n = 247). Contour interval is
250 m; thicker lines show 1000 m and 2000 m, respectively.
period, linear mixed models were used with the fol-
lowing predictor variables (i.e., fixed effects): sea
state (i.e., environmental conditions), water depth
(i.e., ecological factor), and presence and number
of WWV (i.e., potential stressors). Additionally,
and in order to investigate any associated behav-
ioral response, the occurrence of NSEs was used as
a covariate. The individual ID was used as a ran-
dom factor. The same models with follow number
within ID as a random factor were used to account
for temporal correlation.
Respiration Pattern and Dynamics. The respira-
tion pattern is described by the number of blows
per follow, the interbreath intervals (IBI), and its
standard deviation. Two linear mixed-effect mod-
els with WWV presence and occurrence of NSEs
as fixed effects, and ID as the random factor were
used to investigate if the predictor variables had an
effect on the number of blows per follow.
The IBI is the time elapsed between two con-
secutive blows during the surface phase. A subset
was created removing blow intervals correspond-
ing to shallow dives (30 out of 6193), under the
assumption that the inclusion of those intervals
would affect the interpretation of results regarding
mean IBI and its standard deviation. Subsequently,
four linear mixed-effect models with WWV pres-
ence and occurrence of NSEs as fixed effects and
ID as the random factor were used to investigate if
the predictor variables had an effect on IBI and its
standard deviation per follow.
The respiration dynamics is the variation of
the IBI throughout the surface period, and it is
described by “blow number” in the x-axis and the
standardized IBI (i.e., IBI/mean interval for that fol-
low) in the y-axis. Therefore, each blow was given
a consecutive blow number, 1 being the first blow
immediately before diving, and the standardized
IBI for each blow number per follow was estimated
(Gordon et al., 1992).
It was not possible to model the respiration
dynamics due to its complexity; thus, a nonpara-
metric test (Kolmogorov–Smirnov 2 sample) was
performed. The predictor variables considered
were the presence of WWV and the occurrence of
NSEs. To that end, the joint respiration dynamics of
all observations made in the presence of WWV was
approached and remained within the impact zone,
defined as 300 m around the focal whale (the distance
was estimated by eye by the captain of the vessel, who
has over 25 years of whale-watching experience). The
impact zone was determined arbitrarily, given that
there are no whale-watching regulations in the area.
In all cases solitary individuals were followed.
On one occasion two whales were within the impact
zone at about 100 m from each other. No interaction
between them was observed; hence, these sightings
were analyzed independently from each other.
Each follow was given a consecutive follow
number, 1 being the first follow of the season. Using
latitude and longitude at dive, water depth (in m)
was extracted from a shape file [downloaded from
GEBCO (] using R (version
3.0.1; R Development Core Team, 2013). Pack-
ages used were adehabitat (Calenge, 2006) and
SDMTools (VanDerWal, Falconi, Januchowski,
Shoo, & Storlie, 2008).
Pictures were matched against the catalog of
individuals previously identified in the season.
All statistical analyses were made using R [Pack-
ages nlme (Pinheiro, Bates, DebRoy, Sarkar, & R
Development Core Team, 2013) and lme4 (Bates,
Maechler, & Bolker, 2011)]. Graphical exploration
indicated that no data transformation was required
(i.e., the assumptions of homocedasticity and nor-
mality of residuals were met).
Surface Behavior
Occurrence of Near Surface Events (NSEs). The
occurrence of NSEs during a given encounter fol-
lows a binomial distribution (i.e., presence/absence).
In order to investigate if the presence of WWV had
an influence in the probability of a whale performing
a NSE, a mixed-effect logistic regression model was
used, with WWV presence as the predictor variable
and ID as the random factor to account for individual
variability (i.e., heterogeneity of variance) and pseu-
doreplication (Hurlbert, 1984).
Duration of the Surface Period. When studying
the factors influencing the duration of the surface
Data were collected over 78 days, from the June
1 until September 14, 2012. In total 247 individ-
ual follows were selected, 95 of which were in the
Bleik Canyon (Fig. 2). In 39.3% (n = 97) of follows,
sightings were in the presence of at least one WWV.
Whales in this study were individually monitored
from 1 to 39 occasions (mean = 5.75, median = 3),
on 1 (n = 13) to 17 different days.
All 247 follows were used to study the respi-
ration pattern and dynamics, while only follows
where whales were identified, representing 40 indi-
viduals, were used in surface models (n = 230). In
89 encounters the whale was monitored for a full
dive cycle (i.e., surfacing and the following forag-
ing dive) representing 26 different whales; thus,
these data were used in foraging dive models.
A total of 64 whales were individually identified
in this study and this number was used to estimate
individual whale exposure to whale watching in the
season (see “Level of Exposure”).
Surface Behavior
Occurrence of NSEs. In 11.7% (n = 29) of fol-
lows the whale performed at least one NSE. The
overall probability of a whale performing a NSE
during a given observation was 0.065 (95%
CI = 0.031 to 0.129). The mean duration of NSEs
was 3.11 ± 3.2 min (SD), ranging from 24 to 921 s.
Whales that performed a NSE were seen once or
more during the season and were similarly distrib-
uted over the study area. The presence of WWV
had a significant effect in the probability of a whale
performing a NSE (χ2 = 10.78, p = 0.001), increas-
ing the probability from 0.026 (95% CI = 0.008 to
0.096) to 0.171 (95% CI = 0.078 to 0.284).
Model validation suggested that some factors not
accounted for in this study were also influencing
the occurrence of NSEs (see discussion).
Duration of the Surface Period. Although the
duration of the surface period increased by a few
seconds in the presence of WWV, the effect was
not significant [F(1.189) = 0.432, p = 0.511). The
model that best fitted the data includes exclusively
the occurrence of NSEs (Table 1), which had a
significant effect [F(1.189) = 82.03, p < 0.001],
compared to those in the absence of WWV (i.e.,
only the research vessel present); similarly, the res-
piration dynamics of all observations where whales
performed a NSE was compared to those where the
whale did not perform a NSE.
Foraging Dives
To study the factors affecting the duration of
foraging dives, linear mixed models were used
with the following predictor variables (i.e., fixed
effects): sea state (i.e., environmental conditions),
water depth (i.e., ecological factor), and WWV pres-
ence and number of WWV (i.e., potential stressors).
Additionally, and in order to investigate any associ-
ated behavioral response, the occurrence of NSEs
was used as a covariate. The same models with
follow number within ID as a random factor were
used to account for temporal correlation. Lastly,
the number of blows (as a proxy for oxygen intake)
and duration of the surface period (i.e., recovering/
preparation period) were used as covariates.
The individual ID was used as a random factor.
The same models with follow number within ID as
a random factor were used to account for temporal
Model Selection
Model selection was based on the Akaike Infor-
mation Criterion (AIC), retaining those models
with the smallest AIC numbers. Akaike weight of
ith model i, how likely it is that the ith model is
the best model given the data) was used to retain
or discard models with higher AIC numbers. Dur-
ing the model selection process, model validation
tests were run to identify potential violations of the
underlying assumptions of the models.
Level of Exposure
Based on data from this study and personal com-
munication with other companies in the area, an
approximate level of exposure for each whale per
season was estimated. To that end, the total number
of individually identified whales during the season
(n = 64) and the whale-watching days per season,
as well as the number of daily trips per vessel and
whale encounters per trip were used.
that the long dive was not a response to compensate
for the NSE when at the surface, this data point was
removed from further analyses in order to avoid
misinterpretation of results.
The model that provided more information about
the duration of the foraging dive given the data
(i.e., lowest AIC) was the null model (i.e., with no
independent variables). The other models had less
support (Table 3). The estimated dive duration was
29.11 ± 0.88 min (SE). The second best model was
the one with water depth as the only predictor vari-
able, although it did not have a significant effect on
the duration of the dive [F(1,61) = 1.35, p = 0.2488].
The mean water depth where the whales started
their foraging dives was 418.54 ± 252.96 m. Water
depth ranged from 97 to 1,965 m, and it was greater
than 1,000 m only in 11 occasions.
Level of Exposure
During the summer season all tour vessels taken
together approximate 1,860 sightings. Given that
approximately 30% of encounters will include at
least two vessels, only 1,302 encounters represent
one individual whale and at least one vessel (i.e.,
the research vessel or a whale-watching vessel).
increasing the expected surface time (8.01 min,
SE = 0.28) by 6.05 min (SE = 0.66).
Respiration Pattern and Dynamics. The number
of blows per follow was not affected by WWV pres-
ence [F(1,189) = 1.09, p = 0.297] or the occurrence
of NSEs [F(1,189) = 0.91, p = 0.34]. The presence
of WWV did not have a significant effect on the
IBI or its standard deviation either. However, the
IBI and its standard deviation were significantly
affected in those follows where the whale per-
formed a NSE (Table 2).
The IBI varied throughout the surface period as
expected (Gordon et al., 1992), becoming longer as
time progresses but shortening immediately before
fluking (Fig. 3). The result of the nonparametric
Kolmogorov–Smirnov (2-sample) test showed that
the presence of WWV did not have a significant
effect (p = 0.08) on the respiration dynamics while
the occurrence of NSEs did (p < 0.0001) (Fig. 4).
Foraging Dives
One whale that spent a total of 13.7 min at the sur-
face (including a NSE of almost 2 min) performed
a 55-min foraging dive. Based on the assumption
Table 1
Physeter microcephalus: Selection of Models Explaining the Duration of the Surface Period (n = 247)
Type Fixed Effects
Effects df AIC ΔAIC ωi
1 LME Depth + Sea state + NSE ID 6 1162.023 5.515 0.039
2 LME Sea state + NSE ID 8 1163.031 3.524 0.108
3 LME Depth + NSE ID 5 1161.506 1.999 0.229
4 LME NSE ID 4 1159.507 0 0.624
LME, linear mixed-effect model; AIC, Akaike’s information criterion; ωi, weight of evidence for each
model; NSE, occurrence of near surface events; ID, individual identification number.
Table 2
Physeter microcephalus: Respiration Pattern
# Response Variable Fixed Effects AIC Estimate Slope F(df )p
1 Interval (sec) WWV presence 37641.27 17.85 ± 0.45 −0.28 ± 0.15 F(6122) = 3.63 0.056
2 Interval (sec) NSE 37445.6 17.12 ± 0.48 3.92 ± 0.27 F(6122) = 208.54 <0.001
4 Standard deviation WWV presence 967.18 4.20 ± 0.24 0.16 ± 0.26 F(189) = 0.374 0.541
5 Standard deviation NSE 950.7 4.06 ± 0.21 1.77 ± 0.42 F(189) = 17.34 <0.001
Linear mixed-effect models with ID as a random effect. NSE, occurrence of near surface events; ID, individual identification
number. Blow intervals representing NSE were excluded.
Figure 3. Physeter macrocephalus. Respiration dynamics. Blow number against mean values of standardized interbreath
intervals (IBI). Standardized intervals are IBI divided by the mean IBI for that individual follow. Time runs backwards (i.e.,
the whale dives at blow number 0) and each point represents the mean of all the standardized intervals for that given blow
number. Peaks represent long shallow dives (n = 247).
Figure 4. Physeter macrocephalus. Respiration dynamics. Graphical comparison of the respiration dynamics between
encounters with and without the occurrence of shallow (intervals corresponding to shallow dives were removed). Blow
number against mean values of standardized interbreath intervals (IBI). Standardized intervals are IBI divided by the mean
IBI for that individual follow. Time runs backwards (i.e., the whale dives at blow number 0) and each point represents the
mean of all the standardized intervals for that given blow number. Peaks represent long shallow dives (n = 247).
behavioral reactions (and sometimes no reaction at
all) to natural (Wright, 2003) and anthropogenic
underwater sounds (e.g., Madsen & Møhl, 2000;
Madsen, Møhl, Nielsen, & Wahlberg, 2002), to
the presence of whale-watching platforms (e.g.,
Magalhães et al., 2002; Richter et al., 2003) and
to killer whale presence/sounds (i.e., predators) and
attacks (e.g., Curé et al., 2013; Pitman, Ballance,
Mesnick, & Chivers, 2001; unpublished data from
Hvalsafari). It appears that sperm whales may react
less to the presence of tour vessels than other ceta-
cean species, with recent studies only reporting
changes in the interbreath intervals (e.g., Markowitz
et al., 2011; Richter et al., 2006). On the other hand,
impact studies conducted on the species so far have
not accounted for NSEs or variations in the respira-
tion dynamics.
The variations of the IBI per follow, and its stan-
dard deviation, do not adequately describe the res-
piration dynamics in sperm whales given that the
IBI naturally varies throughout the surface period
(Gordon & Steiner, 1992; Gordon et al., 1992; this
study) (Fig. 3). This variation was first described
in undisturbed whales off the Azores (Portugal)
by Gordon and Steiner (1992), who proposed that
blow intervals becoming longer may reflect carbon
dioxide being removed from the body and oxygen
reserves replenishing achieving maximal oxygen
levels, while the increased respiration rate just
before fluking could be a hyperventilation to reduce
carbon dioxide levels (cited in Gordon et al., 1992).
In this study, neither the described dynamics, nor
the mean IBI, its standard deviation, or the number
of blows per follow were found to be significantly
affected by the presence of WWV.
Thus, each whale will be in the presence of at least
one vessel an average of 20.34 times during a given
summer season and it would perform a NSE less
than twice (1.38 times).
The average number of times a given whale is
encountered per season presented here might be
overestimated given that it is likely that there are
more whales in the study area than those encoun-
tered (n = 64) by the vessel used as a research plat-
form during this study. On the other hand, some
whales may be encountered more often, as dis-
cussed below.
Behavioral changes due to human disturbance
has been reported for several cetacean species, such
as bottlenose (e.g., Constantine et al., 2004; Lusseau,
2003a, 2003b, 2004), common (e.g., Stockin et al.,
2008) and Risso’s dolphins (Visser et al., 2011), killer
(e.g., Lusseau et al., 2009; Williams et al., 2006),
humpback (e.g., Stamation et al., 2009; Whaley
et al., 2007), and sperm whales (e.g., Gordon et
al., 1992; Magalhães et al., 2002; Markowitz et
al., 2011; Richter et al., 2003). The risk-disturbance
hypothesis argues that animals perceive human
disturbance in a similar manner to nonlethal pre-
dation risk, and thus an animal’s response should
follow the same economic principles as if encoun-
tering a predator (Frid & Dill, 2002), as observed,
for example, in elk (Becker, Moi, Maguire,
Atkinson, & Gates, 2012) and birds (Blumstein,
Fernández-Juricic, Zollner, & Garity, 2005; Peters
& Otis, 2005). Sperm whales do not seem to fol-
low this principle, exhibiting various acoustic and
Table 3
Physeter microcephalus: Selection of Models Explaining the Duration of the Foraging
Dive (n = 88)
Type Fixed Effects
Effects df AIC ΔAIC ωi
1 LME Surface time ID 4 558.140 3.523 0.086
2 LME WWV presence ID 4 558.122 3.505 0.086
3 LME NSE ID 4 558.121 3.504 0.086
4 LME # of blows ID 4 558.032 3.415 0.09
5 LME Depth ID 4 556.974 2.357 0.153
6 LME ~1 ID 3 554.616 0 0.498
LME, Linear mixed effect model; AIC, Akaike’s information criterion; ωi, weight of evidence
for each model; NSE, occurrence of near surface events; ID, individual identification number.
of NSEs did not lead to longer dives; hence, the
additional time spent at the surface due to NSEs
represents time that will no longer be available for
other activities, such as foraging and resting. It is
possible, however, that whales performed dives
only a few seconds longer each time (i.e., compen-
sating throughout the day or season), or that signifi-
cantly longer dives were performed randomly (i.e.,
not detected with the factors used in our models),
or that significantly longer dives occurred during
times when animals were not followed. Neverthe-
less, this time loss, under the current level of expo-
sure, represents only about 12 min loss in an entire
season. It is thus unlikely to be biologically signifi-
cant, as discussed below.
Sperm whales have a low cost of living, low diet
quality (Spitz et al., 2012), and one of the highest
diving efficiencies reported for a diving animal
(Watwood, Miller, Johnson, Madsen, & Tyack,
2006). Their foraging strategies are related to their
specific energetic requirements (Spitz et al., 2012)
and the behavior of their prey (e.g., Davis et al.,
2007; Fais et al., 2015); therefore, performing lon-
ger dives might not be worth the effort. Changes
in behavior leading to reduced energy intake or
increased energy use can negatively affect the
energy budget of the individuals (Lusseau, 2003b),
which in turn can affect the reproductive success
of individuals (Steven, Pickering, & Castley, 2011),
and, potentially, the survival of the population.
It is noteworthy that when whales performed
NSEs in this study they also showed more erratic
breathing and changes in the respiration dynam-
ics (Fig. 4). It is unknown whether these observed
associated behavioral responses are due to NSEs, or
that NSEs are a consequence of disturbing a whale
that is already distressed. At least some bird species
change their response to human disturbance accord-
ing to their individual state and the state of the envi-
ronment (Beale & Monaghan, 2004), and cetaceans
have also been observed to change their behavior
depending on which behavior they are engaged in
(e.g., Lundquist, Gemmell, & Würsig, 2012; Lusseau,
2003a). However, it was not the purpose of this study
to make analyses that were redundant for whales
that already showed signs of disturbance, but to
present a more holistic approach.
The results of this study also suggest that some
factors not accounted for may also influence the
A more evident behavioral response are NSEs
(e.g., Gordon et al., 1992; Richter et al., 2006) and
this is the first time, to our knowledge, that this
parameter is included in an impact study. Whales
were almost seven times more likely to perform a
NSE in the presence of WWV, leading to a signifi-
cant increase of 6 min (75%) in surface time. The
difference between the mean duration of a NSE
(~ 3 min) and the additional time spent at the surface
has two possible explanations: 1) some individuals
performed more than one NSE per surfacing affect-
ing the mean increase in surface time, and 2) sperm
whales may need time to recover from the NSE
before engaging in a foraging dive.
In previous studies, when sperm whales per-
formed a NSE, the observation was terminated
and not included in further analyses; however, the
resurfacing was analyzed as a complete surface
period, possibly affecting the results and its inter-
pretation. This seems to be the case in Richter et al.
(2003), who found a minimum surface time of 6 s
for an adult male sperm whale off Kaikoura. Also,
Gordon et al. (1992) reported 10% of encounters
ending with a NSE and found a 17% reduction of
the surface time in the presence of WWV, together
with a positive correlation between surface and
dive durations, suggesting that longer dives require
longer times at the surface. If, as in Richter et al.
(2003), resurfacings were treated as full surface
phases, the reduction in surface time found by Gordon
et al. (1992) may be the result of discarding data
regarding NSEs.
A previous study on sperm whales off Andenes
(Teloni, Johnson, Miller, & Madsen, 2008) found
that the mean duration of foraging dives in indi-
viduals not exposed to whale watching was similar
(~32 min) to that found in this study. The authors
also found that 72% of these foraging dives were in
depths less than 400 m. Based on the buzz produc-
tion they proposed that during those dives whales
target epipelagic prey, feeding on more sparsely
distributed prey items (i.e., most likely fish instead
of cephalopods) than during deeper and longer
dives (Teloni et al., 2008).
The results of the present study suggest that the
duration of the foraging dives is independent of all
the studied predictor variables, including the pres-
ence of WWV, water depth, and duration of the pre-
vious surface period. Additionally, the occurrence
Sperm whales may be present in waters off
Andenes year round (unpublished data from Hval-
safari). And although the residency patterns of indi-
vidual whales are unknown, some males have been
repeatedly encountered within and between years.
Consequently, some sperm whales could be repeat-
edly targeted over the course of a season, perform-
ing NSEs more often than expected and suffering
reduced energy intake. Under the current level of
exposure, however, it is unlikely that such a reduc-
tion would have detrimental consequences for the
energetic budget of individuals.
When this study was conducted, the whale-watch-
ing season was carried out only during the summer
months. However, since 2011 whale watching has
also been carried out during the winter months.
Although mainly targeting killer, humpback, and
fin whales, it also targets sperm whales when the
other species are not readily accessible.
Conclusions and Recommendations
The presence of whale-watching vessels had a
statistically significant effect on sperm whales’
behavior while at the surface, making them more
likely to perform near surface events. These NSEs
led to an increase in surface time that was not fol-
lowed by longer foraging dives, and were associ-
ated with changes in the pattern and dynamics of
respiration. Such short-term effects likely do not
have biological consequences for the individ uals
under the current level of exposure. However, a
larger number of whale-watching vessels in the
area and the development of the winter season
could increase the occurrence of the observed
short-term effects and potentially lead to long-term
consequences. The use of hydrophones as well as
increased collaboration between companies, espe-
cially with the use of the land-based station, can
help avoid targeting the same individual. Sperm
whales that show signs of disturbance (e.g., NSEs)
should be avoided, minimizing or preventing the
adverse consequences of cumulative effects.
Near surface events are an easy to identify indi-
cator of likely disturbance, and thus they could be
included in regulations or protocols of whale watch-
ing targeting sperm whales. Hence, the collection
of further data concerning NSEs and respiration
dynamics is strongly recommended in future impact
occurrence of NSEs. For instance, Gordon et al.
(1992) and Richter et al. (2003) reported that tran-
sient sperm whales off Kaikoura showed a stron-
ger reaction to the presence of WWV than resident
individuals. The low level of resightings found in
this study could indicate that also this area is vis-
ited by both resident and transient individuals.
Future research should aim at understanding the
circumstances under which whales are more likely
to perform NSEs, and the relationship with other
anthropogenic factors (e.g., vessel handling, speed
of approach), internal factors specific to that whale
(e.g., duration of the previous dive, resident/transient
individual), or a combination of both. In the interim,
and given that NSEs are easy to identify (i.e., the
whales simply “disappear” underwater), whales that
engage in NSEs should be abandoned by whale-
watching vessels to reduce disturbance levels.
Land-based follows were not attempted because
of the local rapid changing weather conditions and
an inability to determine if two consecutive surfac-
ings corresponded to the same whale. Thus, it is
possible that the whale-watching vessel that used
as an opportunistic research platform may have had
an effect on the animals. On the other hand, mean
surface and foraging dive durations found in this
study are consistent with the findings of Teloni et al.
(2008), who tagged four whales in the Bleik Can-
yon that were not exposed to tourist (or any other)
vessels. Additionally, the results do show significant
changes in the presence of other WWVs, suggesting
that the research vessel was a suitable observation
platform to contrast behavioral changes.
Long Term Consequences
During the summer season, whale-watching trips
are conducted on a daily basis (weather allowing)
from 9 am to around 9 pm. The results of this study
suggest that a whale would be encountered about
20 times during a given summer season and, thus,
it would perform NSEs less than twice per season.
Nonetheless, currently only two out of six vessels
use hydrophones to locate whales, thus it is nor-
mal practice to remain in the area where the first
animal was seen, as well as to return on the fol-
lowing trip. As a result, the same individual may
be targeted several times a day by more than one
whale-watching vessel.
Davis, R., Jaquet, N., Gendron, D., Markaida, U., Bazzino,
G., & Gilly, W. (2007). Diving behavior of sperm whales
in relation to behavior of a major prey species, the jumbo
squid, in the Gulf of California, Mexico. Marine Ecology
Progress Series, 333, 291–302.
Dutton, A. (2011). Norwegian use of whales: Past, pres-
ent and future trends. Retrieved from http://www.
Fais, A., Aguilar Soto, N., Johnson, M., Pérez-González, C.,
Miller, P. J. O., & Madsen, P. T. (2015). Sperm whale
echolocation behaviour reveals a directed, prior-based
search strategy informed by prey distribution. Behav-
ioral Ecology and Sociobiology, 69(4), 663–674.
Frid, A., & Dill, L. (2002). Human-caused disturbance stim-
uli as a form of predation risk. Conservation Ecology,
6(1), 11. Retrieved from
Gordon, J., Leaper, R., Hartley, F. G., & Chappell, O. (1992).
Effects of whale watching vessels on the surface and
underwater acoustic behavior of sperm whales off Kaik-
oura, New Zealand. Science and Research Series No. 52,
Department of Conservation, Wellington, New Zealand.
Gordon, J., & Steiner, L. (1992). Ventilation and dive pat-
terns in sperm whales, Physeter macrocephalus, in the
Azores. Report of the International Whaling Commis-
sion, 42, 561–565.
Hoyt, E. (2001). Whale watching 2001: Worldwide tourism
numbers, expenditures and expanding socioeconomic
benefits. Yarmouth Port, UK: International Fund for Ani-
mal Welfare.
Hurlbert, S. H. (1984). Pseudoreplication and the design of
ecological field experiments. Ecological Monographs,
International Whaling Commission. (2011). Annual report
of the scientific committee of the international whaling
commission. 63rd Meeting held in Tromsø, Norway, in
May 2011.
Lettevall, E., Richter, C., Jaquet, N., Slooten, E., Dawson,
S., Whitehead, H., Christal, J., & McCall Howard, P.
(2002). Social structure and residency in aggregations
of male sperm whales. Canadian Journal of Zoology,
80(7), 1189–1196.
Lundquist, D., Gemmell, N. J., & Würsig, B. (2012). Behav-
ioural responses of dusky dolphin groups (Lageno-
rhynchus obscurus) to tour vessels off Kaikoura, New
Zealand. PLoS One, 7(7), e41969.
Lusseau, D. (2003a). Male and female bottlenose dolphins
Tursiops spp. have different strategies to avoid interac-
tions with tour boats in Doubtful Sound, New Zealand.
Marine Ecology Progress Series, 257, 267–274.
Lusseau, D. (2003b). Effects of tour boats on the behavior of
bottlenose dolphins: Using Markov chains to model anthro-
pogenic impacts. Conservation Biology, 17(6), 1785–1793.
Lusseau, D. (2004). The hidden cost of tourism: Detecting
long-term effects of tourism using behavioral informa-
tion. Ecology and Society, 9(1), 2–16.
studies on sperm whales, as these data may well help
explain the circumstances under which obvious and
subtle responses occur in the presence of whale-
watching vessels or other potential stressors
I would like to thank Dr. Lusseau for his help
during this project and the reviewers for their input
on early versions of this manuscript. I would also
like to thank MAREFA for their support, Hvalsafari
AS for allowing the use of its platforms, and all the
volunteers that helped with data collection.
Biographical Note
Mel Cosentino is a biologist interested in the impact of
anthropogenic activities on cetaceans. Born in Argentina,
she earned her B.Sc. in Biology in Spain and her M.Res.
in Applied Marine and Fisheries Ecology in the UK. Her
research to date has focused on cetaceans, using opportunistic
data from whale-watching platforms and dedicated research
surveys with teams in Spain, Portugal, and Norway.
Bates, D., Maechler, M., & Bolker, B. (2011). lme4: Linear
mixed-effects models using S4 classes. R package ver-
sion 0.999375-39.
Beale, C. M., & Monaghan, P. (2004). Behavioural responses
to human disturbance: A matter of choice? Animal Behav-
iour, 68(5), 1065–1069.
Becker, B. H., Moi, C. M., Maguire, T. J., Atkinson, R., &
Gates, N. B. (2012). Effects of hikers and boats on Tule
elk behavior in a national park wilderness area. Human–
Wildlife Interactions, 6(1), 147–154.
Blumstein, D. T., Fernández-Juricic, E., Zollner, P. A., &
Garity, S. C. (2005). Inter-specific variation in avian
responses to human disturbance. Journal of Applied
Ecology, 42, 943–953.
Calenge, C. (2006). The package adehabitat for the R soft-
ware: A tool for the analysis of space and habitat use by
animals. Ecological Modelling, 197, 516–519.
Ciano, J. N., & Huele, R. (2001). Photo-identification of
sperm whales at Bleik Canyon, Norway. Marine Mam-
mal Science, 17(1), 175–180.
Constantine, R., Brunton, D. H., & Dennis, T. E. (2004).
Dolphin-watching tour boats change bottlenose dolphin
(Tursiops truncatus) behaviour. Biological Conserva-
tion, 117 , 299–307.
Curé, C., Antunes, R., Alves, A. C., Visser, F., Kvadsheim,
P. H., & Miller, P. J. O. (2013). Responses of male sperm
whales (Physeter macrocephalus) to killer whale sounds:
Implications for anti-predator strategies. Scientific
Reports, 3, 1579–1585.
Spitz, J., Trites, A. W., Becquet, V., Brind’Amour, A.,
Cherel, Y., Galois, R., & Ridoux, V. (2012). Cost of liv-
ing dictates what whales, dolphins and porpoises eat:
The importance of prey quality on predator foraging
strategies. PLoS One, 7(11), e50096.
Stamation, K. A., Croft, D. B., Shaughnessy, P. D., Waples,
K. A., & Briggs, S. V. (2009). Behavioral responses of
humpback whales (Megaptera novaeangliae) to whale-
watching vessels on the southeastern coast of Australia.
Marine Mammal Science, 26(1), 98–122.
Steven, R., Pickering, C., & Castley, G. J. (2011). A review
of the impacts of nature based recreation on birds. Jour-
nal of Environmental Management, 92(10), 2287–2294.
Stockin, K., Lusseau, D., Binedell, V., Wiseman, N., &
Orams, M. (2008). Tourism affects the behavioural bud-
get of the common dolphin Delphinus sp. in the Hauraki
Gulf, New Zealand. Marine Ecology Progress Series,
355, 287–295.
Sundby, S. (1984). Influence of bottom topography on the
circulation at the continental shelf off Northern Norway.
Fiskeridirektoratets Skrifter. Serie Havundersøkelser,
17, 501–519.
Teloni, V., Johnson, P. M., Miller, J. O. P., & Madsen, T. P.
(2008). Shallow food for deep divers: Dynamic foraging
behavior of male sperm whales in a high latitude habitat.
Journal of Experimental Marine Biology and Ecology,
354(1), 119–131.
Van Der Wal, J., Falconi, L., Januchowski, S., Shoo, L., &
Storlie, C. (2008). Species distribution modelling tools:
Tools for processing data associated with species distri-
bution modelling exercises. R package, Version 1.1-13.
Visser, F., Hartman, K. L., Rood, E. J. J., Hendriks, A. J.
E., Zult, D. B., Wolff, W. J., Huisman, J., & Pierce, G.
J. (2011). Risso’s dolphins alter daily resting pattern in
response to whale watching at the Azores. Marine Mam-
mal Science, 27(2), 366–381.
Watwood, S. L., Miller, P. J. O., Johnson, M., Madsen, P. T.,
& Tyack, P. L. (2006). Deep-diving foraging behaviour
of sperm whales (Physeter macrocephalus). The Journal
of Animal Ecology, 75(3), 814–825.
Whaley, A. R., Wright, A. J., Bonnelly de Calventi, I., &
Parsons, E. C. M. (2007). Humpback whale sightings
in southern waters of the Dominican Republic lead to
proactive conservation measures. Marine Biodiversity
Records, 1, e70, 1–3.
Whitehead, H. (1994). Delayed competitive breeding in rov-
ing males. Journal of Theoretical Biology, 166, 127–133.
Williams, R., Trites, A. W., & Bain, D. E. (2006). Behavioural
responses of killer whales (Orcinus orca) to whale-
watching boats: Opportunistic observations and experi-
mental approaches. Journal of Zoology, 256(2), 255–270.
Wright, A. J. (2003). The effects of a tropical storm on the
use of clicks by sperm whales in the northern Gulf of
Mexico. Master’s Thesis, University of Wales, Bangor,
Lusseau, D., Bain, D., Williams, R., & Smith, J. (2009).
Vessel traffic disrupts the foraging behavior of southern
resident killer whales Orcinus orca. Endangered Species
Research, 6(3), 211–221.
Lusseau, D., & Bejder, L. (2007). The long-term consequences
of short-term responses to disturbance experiences from
whale watching impact assessment. International Journal
of Comparative Psychology, 20(2–3), 228–236.
Madsen, P. T., & Møhl, B. (2000). Sperm whales (Physeter
catodon L. 1758) do not react to sounds. The Journal of
the Acoustical Society of America, 107(1), 668–671.
Madsen, P. T., Møhl, B., Nielsen, B. K., & Wahlberg, M. (2002).
Male sperm whale behaviour during exposures to distant
seismic survey pulses. Aquatic Mammals, 28(3), 231–240.
Magalhães, S., Prieto, R., Silva, M. A., Gonçalves, J.,
Afonso-Dias, M., & Santos, R. S. (2002). Short-term
reactions of sperm whales (Physeter macrocephalus)
to whale-watching vessels in the Azores. Aquatic Mam-
mals, 28(3), 267–274.
Markowitz, T., Richter, C., & Gordon, J. (Eds). (2011).
Effects of tourism on the behavior of sperm whales inhab-
iting the Kaikoura Canyon. Report submitted to the New
Zealand Department of Conservation by PACE-NZRP,
Kaikoura Sperm Whale and Tourism Research Project.
Nielsen, B. K., & Møhl, B. (2006). Hull-mounted hydro-
phones for passive acoustic detection and tracking of
sperm whales (Physeter macrocephalus). Applied Acous-
tics, 67, 1175–1186.
O’Connor, S., Campbell, R., Cortez, H., & Knowles, T.
(2009). Whale watching worldwide: Tourism numbers,
expenditures and expanding economic benefits. Yar-
mouth, MA: International Fund for Animal Welfare.
Peters, K. A., & Otis, D. L. (2005). Using the risk-distur-
bance hypothesis to assess the relative effects of human
disturbance and predation risk on foraging American
oystercatchers. The Condor, 107, 716–725.
Pinheiro, J., Bates, D., DebRoy, S., Sarkar, D., & R Devel-
opment Core Team. (2013). nlme: Linear and nonlinear
mixed effects models. R package version 3.1- 109.
Pitman, R. L., Ballance, L. T., Mesnick, S. I., & Chivers,
S. J. (2001). Killer whale predation on sperm whales:
Observations and implications. Marine Mammal Sci-
ence, 17(3), 494–507.
R Development Core Team. (2013). The R project for statis-
tical computing. R Foundation for Statistical Computing,
Vienna, Austria. Retrieved from http://www.R-project.
Richter, C. F., Dawson, S. M., & Slooten, E. (2003). Sperm
whale watching off Kaikoura, New Zealand: Effects of
current activities on surfacing and vocalisation patterns.
Science for Conservation, 219, 5–78.
Richter, C. F., Dawson, S. M., & Slooten, E. (2006). Impacts
of commercial whale watching on male sperm whales
at Kaikoura, New Zealand. Marine Mammal Science,
22(1), 46–63.
... So far, past research only focused on changes in interbreathing intervals to characterize short-term effects of ww activities in sperm whales in the area (Magalhães et al., 2002). Meanwhile, more recent studies off Norway, found that sperm whales significantly increase their surface time (75%), as they were almost seven times more likely to perform near-surface-events (NSEs) in the presence of ww boats (Cosentino, 2016). ...
... Therefore, it is important to account for NSEs and respiration dynamics in such impact studies, as they are suitable indicators of human disturbance. Aiming to reduce exposure and to avoid negative consequences of cumulative impacts, ww boats should avoid targeting the same individual and animals indicating signs of disturbance, such as NSEs (Cosentino, 2016). ...
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... the whole Vesterålen region, yet fishing remains the main economic pillar (Cosentino 2016, Bertella 2017). There are plans to initiate a project known as The Whale in Andenes, which is designed to be a major whale-themed museum, science, and culture hub ( ...
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The social-ecological change in the Arctic is accelerated by the multifaceted effects of climate change and globalization. Among other things, this means changing human-ecosystem dynamics through altered availability, co-production, and governance of ecosystem services (ES). A group of species illustrative of this change are whales, migratory species that have played an important part in the culture and subsistence of Arctic communities for millennia. This study explores the changing human-nature interactions and whale ES governance by combining ES and interactive governance theories. A multi-method approach is applied to assess qualitatively the qualitative governability of whale ES in three Arctic coastal locations: Húsavík in Iceland, Andenes in Norway, and Disko Bay in Greenland. Based on a literature review, stakeholder mapping, observations, and analysis of 54 semi-structured stakeholder interviews, the study finds that whale ES governance involves multiple actors with differing preferences and values and that much of it happens outside of formal institutions, necessitating inclusive approaches to improve it. The study reveals some whale ES governance deficiencies and potentials, such as a mismatch between governance scales and a need for more formal governance practices based on scientific research and stakeholder inputs. Governance frameworks were present for provisioning whale ES related to whaling, but they were lacking for non-consumptive whale ES, such as whale watching. Addressing these issues can help to direct marine resource management toward sustainability by making it more inclusive, adaptive, and reflective of stakeholder needs and values. This goal could be advanced by applying the governance principles that view humans as an integral part of social-ecological systems, e.g., ecosystem stewardship and ecosystem-based management.
... Andenes is a small town in the northern region of Vesterålen in Arctic Norway, populated by 2,561 inhabitants (Statistics Norway, 2021). The most common species of whales observed in the waters within close vicinity of Andenes are sperm, minke, and long-finned pilot whales, with orcas, humpback and fin whales being more common in the winter (Cosentino, 2016;Sea Safari, 2021). Whale watching was initiated in the late 1980 s and has since become the main pillar of the region's tourism industry, not least because of the year-round presence of sperm whales in the area due to the nutrient-rich Bleik canyon, located around 15 km offshore of Andenes (Malinauskaite, 2021). ...
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A booming whale-watching industry in Juneau, Alaska, is raising concerns over potential impacts to humpback whales (Megaptera novaeangliae) and the sustainability of this growing industry. In this study, we investigated the physiological response of these whales to chronic vessel disturbance by measuring hormone concentrations (cortisol, progesterone, testosterone, and estradiol) that have been sequestered in blubber throughout the whale-watching season. We focused our analysis on cortisol, a steroid hormone associated with stress response, and hypothesized that cortisol in biopsy samples would be positively correlated with the amount of vessel traffic in the 3 to 4 months prior to sampling. Humpback whales in the Juneau area were compared with whales from control areas with far less vessel traffic in both Southeast Alaska and the western Gulf of Alaska using biopsies collected late in the tour season. We did not find elevated cortisol in whales sampled in the Juneau area relative to the Southeast Alaska control area (p= 0.14) or sites in the western Gulf of Alaska, which had higher cortisol levels (p < 0.001). The cause of the regional cortisol differences is not known but could be representative of regional differences in baseline hormone concentrations or be linked to predator or nutritional stressors. The lack of elevated cortisol in Juneau-area whales suggests high vessel traffic is not resulting in chronic cortisol sequestration in whales and may be indicative of whales near Juneau being habituated to vessel traffic.
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As part of the Littoral Acoustic Demonstration Center’s Phase I study into the ambient noise baseline at the shelf edge of the north Gulf of Mexico, three bottom-moored EARS buoys were deployed around 28o15’N 88o50’W for about 36 days in the summer of 2001. The EARS buoys, situated at depths of 600 m, 800 m and 950 m, incorporated hydrophones suspended 50 m off the seabed. In early August, tropical storm Barry passed within 200 km of the EARS buoys, providing an unexpected opportunity to assess the impact of the storm conditions on sperm whales. 19 days of clicks, including from the storm period, were analysed using automatically detection software. Despite daily dissimilarity, click rates in 1,000 m water were generally found to be higher over night than during the day while rates at the shallower buoys tended to increase throughout the day, before declining over night to reach a minimum around dawn. The high levels of variation seen within and between the EARS buoys may explain the range of results found throughout the literature. Detected click rates and daily patterns also suggested that more whales may have moved into the region in response to the tropical storm Barry, especially around the shallower buoys. It is also possible that at least some of the whales at the 1,000 m buoy may have left that area during the storm. Residual effects from Barry are seen after the storm had dissipated, especially at the deepest buoy. Although it is not known if these responses were caused by the increases in ambient noise or sea state, it is suggested that sperm whales may be producing clicks of greater amplitude in response to the ambient noise levels; a result which may have implications in areas of high boating activity. Experimental limitations are acknowledged and appropriate future research is suggested.
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The risk-disturbance hypothesis asserts that animals perceive human disturbance similar to nonlethal predation stimuli, and exhibit comparable responses in the form of optimization tradeoffs. However, few studies have examined how natural predation risk factors interact with human-disturbance stimuli to elicit such responses. We observed American Oystercatcher (Haematopus palliatus) vigilance behavior from September–December 2002 on the Cape Romain National Wildlife Refuge, South Carolina. A set of models was constructed based on 340 focal-animal samples and models revealed relationships between vigilance behavior, predator density, and boat activity. Oystercatchers increased vigilance in response to aerial predators, particularly late in the season when predator species composition was dominated by Northern Harriers (Circus cyaneus). At a broader temporal scale, oystercatchers exhibited the highest vigilance rates during simultaneous peaks in boating disturbance and Osprey (Pandion haliaetus) activity. Due to this temporal overlap of stimuli, it is difficult to interpret what may have been driving the observed increased in vigilance. Foraging rates appeared to be primarily driven by habitat and tidal stage indicating that time lost to vigilance did not effectively reduce intake. Taken together, these findings provide some support for the risk-disturbance hypothesis, underscore the sensitivity of disturbance studies to temporal scale, and draw attention to the potential confounding effects of natural predation risk. Uso de la Hipótesis de Riesgo-Disturbio para Evaluar los Efectos Relativos de los Disturbios Humanos y del Riesgo de Depredación en Haematopus palliatus Resumen. La hipótesis de riesgo-disturbio propone que los animales perciben los disturbios causados por los humanos de un modo similar a como perciben estímulos de depredación no letales, y que exhiben respuestas comparables en términos de compromisos de optimización. Sin embargo, pocos estudios han examinado cómo interactúa el riesgo natural de depredación con los estímulos causados por disturbios humanos para causar dichas respuestas. Observamos el comportamiento de vigilancia del ostrero Haematopus palliatus entre septiembre y diciembre de 2002 en el Refugio Nacional de Vida Silverstre Cape Romain, South Carolina. Con base en 340 muestras de animales focales se construyeron una serie de modelos, los cuales mostraron relaciones entre el comportamiento de vigilancia, la densidad de depredadores y la actividad de botes. Los ostreros incrementaron la vigilancia como respuesta a los depredadores aéreos particularmente hacia el final de la temporada, cuando la composición de especies de depredadores estaba dominada por Circus cyaneus. A una escala temporal más amplia, los ostreros presentaron las tasas de vigilancia más altas durante picos simultáneos en los disturbios causados por botes y en la actividad de Pandion haliaetus. Debido a esta superposición de los estímulos es difícil interpretar cuál de ellos habría estado determinando el incremento en vigilancia observado. Las tasas de forrajeo parecieron estar dadas principalmente por el hábitat y la posición de la marea, lo que indica que el tiempo perdido en vigilancia no redujo la ingestión de alimento efectivamente. En conjunto, estos hallazgos proveen algo de evidencia que apoya la hipótesis de riesgo-disturbio, resaltan la sensibilidad a la escala temporal de los estudios sobre disturbios y enfatizan la necesidad de prestar atención a la posibilidad de que existan efectos enmascarados del riesgo de depredación natural.
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Predators make foraging decisions based upon sensory information about resource availability, but little is known about how large, air-breathing predators collect and use such information to maximize energy returns when foraging in the deep sea. Here, we used archival tags to study how echolocating sperm whales (Physeter macrocephalus) use their long-range sensory capabilities to guide foraging in a deep-water habitat consisting of multiple, depth-segregated prey layers. Sperm whales employ a directed search behaviour by modulating their overall sonar sampling with the intention to exploit a particular prey layer. They forage opportunistically during some descents while actively adjusting their acoustic gaze to sequentially track different prey layers. While foraging within patches, sperm whales adjust their clicking rate both to search new water volumes as they turn and to match the prey distribution. This strategy increases information flow and suggests that sperm whales can perform auditory stream segregation of multiple targets when echolocating. Such flexibility in sampling tactics in concert with long-range sensing capabilities apparently allow sperm whales to efficiently locate and access prey resources in vast, heterogeneous, deep water habitats.
Mean observed inter-blow intervals were 12.7s for small whales (females and immature males) and 19.3s for large males. Blows later in a surfacing, which had longer intervals, were more likely to be scored. Blow intervals increased through a surfacing but decreased markedly for the last three blows before fluke-up. The modal duration of a complete dive cycle was 52.5 mins. Data suggest an overall mean blow interval for feeding sperm whales of 70.6s for small whales and 107.1s for large males. The relevance of these findings to sightings surveys is briefly discussed. -from Authors