Metabolic rates of captive grey seals during voluntary diving
Sea Mammal Research Unit, Gatty Marine Laboratory, University of St Andrews, St Andrews, Scotland, UK, KY16 8LB
* Author for correspondence (e-mail: ces6{at}st-and.ac.uk)
Accepted 17 February 2004
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Summary |
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Key words: grey seal, Halichoerus grypus, diving metabolic rate, aerobic dive limit, hypometabolism
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Introduction |
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The present study examines the relationships between diving behaviour and oxygen consumption in grey seals diving voluntarily in a quasi-natural setting.
A second reason for an interest in the metabolic rates of diving seals is
that the energetic costs of diving are incorporated, explicitly or implicitly,
in various models of seal prey consumption that are used to predict the
impacts of seal populations on prey species (e.g.
Øritsland and Markussen,
1990; Markussen and
Øritsland, 1991
;
Olesiuk, 1993
;
Mohn and Bowen, 1996
;
Stenson et al., 1997
;
Nilssen et al., 2000
;
Winship et al., 2002
).
Metabolism while at sea makes up a large component of a seal's annual energy
budget, yet it is this component we know least about. For example, in the
Steller sea lion (Eumetopias jubatus) bioenergetic model developed by
Winship et al. (2002
),
uncertainty in metabolism parameters, particularly activity cost parameters,
had the largest effect on the error in estimates of food consumption.
The doubly labelled water (DLW) technique has been used to measure at-sea
field metabolic rates (FMR) of many otariid species, e.g. New Zealand sea
lions (Phocartos hookeri; Costa
and Gales, 2000), northern fur seals (Callorhinus
ursinus; Costa and Gentry,
1986
), Australian sea lions (Neophoca cinerea;
Costa et al., 1989
;
Costa and Gales, 2003
) and
Antarctic fur seals (Arctocephalus gazella;
Costa et al., 1989
;
Arnould et al., 1996
). To date,
at-sea metabolic rate has only been measured using this method in two phocid
species, the harbour seal (Phoca vitulina;
Reilly and Fedak, 1991
) and
the northern elephant seal (Andrews,
1999
). The need for timely recapture and the cost involved in
dosing large animals with isotopes makes it difficult to apply this technique
to phocids such as the grey seal. Grey seals go out to sea on foraging trips
that can last several days and move between haul-out sites in an unpredictable
manner (McConnell et al.,
1999
). They can be captured at haul-outs but the chances of
recapturing the same animal are small. Furthermore, DLW can only give measures
of the average energy expenditure over a time period of several days, and
individual metabolic rates cannot be assigned to individual dive types. At-sea
FMR integrates the energy expended during all activities, including resting
periods, so FMR measured in this way has limited utility for examining the
relationships between energy expended and dive variables such as depth,
duration and swimming speed over periods shorter than an entire foraging
trip.
Other approaches to estimate at-sea energy requirements include predicting
basal metabolic rate (BMR) based on empirically derived equations relating
body mass to metabolic rate (Kleiber,
1975), then using a multiplier of BMR to account for activity at
sea. This multiplier is generally extrapolated from metabolic rate data from
animals swimming in flumes or in small tanks (e.g.
Davis et al., 1985
;
Fedak et al., 1988
;
Williams et al., 1991
);
however, these are not likely to provide realistic models of the varied
behaviour of free-ranging, unrestrained animals. Flume studies require seals
to swim continuously against a current, on or near the surface, something that
phocid seals do not do in the wild. Similarly, animals restricted to small
tanks cannot exhibit the same range of behaviour as their wild counterparts.
Free-ranging animals need to manage their O2 stores to maximise
foraging time and energy intake (Fedak and
Thompson, 1993
; Thompson et
al., 1993
). How an animal manages O2 use in a situation
of forced exercise or while diving in small tanks may be very different. A
complete understanding of the energetic requirements of the time spent at sea
by phocid seals will require an approach that combines laboratory-based
measurements with data on freely living animals.
This paper presents estimates of dive-by-dive metabolic rates in grey seals with simultaneous measurement of behaviour in an experimental set-up that mimics the natural dive behaviour of grey seals more closely than in any previous captive studies. Because of the difficulties in directly measuring DMR in wild seals, we present a general model that can be used to predict the energy expenditure of diving grey seals from behavioural parameters. It is proposed that this model be used in conjunction with telemetry-derived behavioural information from field-based studies to estimate the metabolic cost of foraging in free-living animals.
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Materials and methods |
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Measurement of oxygen consumption during diving
Oxygen consumption was measured during voluntary diving in a large pool
measuring 42 mx6 mx2.5 m. All seals used in this study were fasted
overnight before measurements were made. Oxygen consumption was measured by
open-flow respirometry. A schematic of the system used is shown in
Fig. 1. A Perspex breathing
chamber was set into a modified mesh panel at one corner of the pool; an
airtight seal was formed by submerging the edges of the box under 6 cm of
water. Aluminium mesh panels covered the entire pool, preventing the seals
from surfacing anywhere apart from the breathing chamber during experiments.
The pool was divided into four lanes to increase the distance that seals could
travel in any one dive (Fig.
2). For several weeks before the diving trials were carried out,
the seals were trained to dive away from the breathing box by receiving food
rewards at feeding holes. The breathing chamber had an inlet, which opened to
the outside, and an outlet, which was connected by 3.8 cm-diameter flexible
hosing to a pump situated inside the laboratory (6 m away). Another
section of this flexible hose, 1.5 m long, was attached to the inlet, acting
as `dead space', so that none of the seals' expirations were lost through the
inlet. Ambient air was drawn through the box at a rate depending on the
animals' requirements (200-400 l min-1), sufficient to make the
change in O2 concentration during breathing around 1%. Flow was
maintained and monitored using Sable Systems Flow Kit 500H (Sable Systems
International, Las Vegas, NV, USA). A 500 ml min-1 subsample was
pumped at positive pressure through a drying column, a CO2 absorber
and another drying column before entering a `Servomex' paramagnetic oxygen
analyser (model OA570; Sybron Taylor; Servomex, Crowborough, UK), which
measured the oxygen concentration in the sample gas. The oxygen analyser was
connected to a laptop computer using a PCMIA16-bit analogue-to-digital
converter (PC-CARD DAS16/16; Amplicon Liveline, Brighton, UK). The
O2 analyser output was sampled 10 times per second using a program
designed and written for this application in Hewlett Packard Virtual
Engineering Environment (HPVEE). The program calculated and stored a moving
average of the fractional O2 concentration every 10 s. The system
had a lag of approximately 110 s from when the seals began breathing until the
first deflection on the O2 analyser, and a 95% response time of
2.5-3 min.
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The respirometry system was calibrated at the beginning of every run using
the nitrogen dilution technique described by Fedak et al.
(1981). This calibration
technique has relatively small errors as long as the flow through the system
remains constant between measurement and calibration. Flow rates of nitrogen
were regulated to arbitrary values using a glass tube flow-meter (Brooks
Instruments, Emerson Process Management, Stockport, UK). This flow-meter was
calibrated weekly using a Brooks Vol-U-Meter gas calibrator. All volumes of
gas were converted to STPD. Calibration curves relating flow-meter reading to
measured flow in l s-1 were constructed and equations produced
using least-squares regression.
Oxygen consumption
(O2) of the seal
was calculated using the following equation from Fedak et al.
(1981
):
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Measurement of behaviour
The seals' behaviour was measured using a time depth recorder (Mk 8 TDR;
Wildlife Computers, Redmond, WA, USA) attached to the head of the animal. The
turbine housed in the tag rotated as the animal swam and the tag counted and
logged the number of revolutions of the paddle wheel per second (measured TDR
speed or MTS). MTS was converted to estimated true speed (ETS) using a
calibration, where actual speed measured by observers timing a seal swimming
over known distances was compared with the measured TDR speed
(Jones, 2001). The equation
relating measured speed to true speed using least-squares regression
(r2=0.96) was:
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A wet/dry sensor measured surface and dive durations. A digital watch was synchronised with the TDR clock, and the time the seal entered and left the water was noted for each individual trial. This enabled the experimental period to be isolated from the TDR record when it was downloaded. Data from the TDR were downloaded at the end of a set of measurement trials (typically 1 week), and the following parameters were calculated for each dive: dive duration, surface duration, total length of dive cycle, proportion of dive cycle spent submerged, overall mean speed during the dive (in m s-1; average of per second ETS), total distance travelled over dive (ETS in m s-1 x duration in s), percentage of dive spent swimming and the mean active swim speed (average of per second ETS readings where ETS >0.02).
So that we could compare the behaviour of the seals in captivity with the
dive behaviour of wild seals, information on the dive behaviour of free-living
grey seals was obtained using Argos satellite relay data loggers (SRDLs)
deployed on 108 grey seals at various locations around the UK between 1990 and
1999. The process by which dive data were collected and processed by the SDRLs
is detailed by Fedak et al.
(2002).
Model predicting DMR from behaviour
We constructed a generalised linear model that could be used to predict the
DMRs of free-ranging seals given the sorts of information about their diving
behaviour available from SRDL records from studies of wild grey seals.
Post-dive oxygen consumption (in litres) was the response variable whilst only
behavioural variables that were likely to be measured in telemetry studies of
the dive behaviour of wild seals were included as predictors. The generalised
linear model assumes that the response variable comes from a gamma
distribution, i.e. it is a continuous variable with non-normal errors; the
variance is proportional to the mean in this case
(Venables and Ripley, 1999).
The best model was chosen by minimising the Akaike Information Criterion or
AIC (Akaike, 1974
). The fit of
the model was also assessed by examining residual plots and plots of fitted
versus observed values.
The predictive power of the model was assessed by removing all dives from one individual from the full data set, then re-fitting the model using this reduced data set, and using the new model to calculate the predicted oxygen consumption of the excluded `novel' animal over all their dives. These could then be compared with the observed oxygen consumption. This was done with each animal in turn.
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Results |
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Diving metabolic rates
Mean rates of oxygen consumption during diving ranged from 0.25 l
min-1 in a juvenile under one year of age to 0.69 l
min-1 in the largest adult. Regressing the log10 of mean
DMR (l min-1) against the log10 mass (kg) of each animal
resulted in the following equations (Fig.
5):
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|
The slope of the relationship is not significantly different from Kleiber's
equation (Kleiber, 1975)
relating basal metabolism to body mass using Bailey's computation for the
comparison of two regression coefficients
(Bailey, 1959
). (Although the
number of animals is low and thus may give an unreliable measure of the
scaling exponent, within the animals studied here at least, which exhibited a
sixfold size range, DMR did seem to scale to mass0.76.) All
subsequent metabolism measurements, where data are combined from more than one
animal, are expressed as a multiple of Kleiber's prediction of BMR for a
similarly sized animal, hereafter symbolised by K. Expressing metabolism in
this way allows us to effectively control for the effect of mass when
investigating variation in metabolic rates related to variables other than
mass within this sample. When expressed this way, DMR in this study ranged
from 1.4(K) to 2.2(K). Rates of oxygen consumption for the seven seals for
which we managed to measure both states were lower during diving than when
they were resting at the surface (Fig.
6). Across individuals, there was a mean reduction in metabolic
rate of 10-33%. This difference was significant (paired t=3.86,
P=0.003).
|
DMR and dive behaviour
Fig. 7 shows a 3-D plot of
the relationship between swim speed, dive duration and DMR. From this we can
see that the longest dives are also those with the lowest mean swim speeds and
the lowest metabolic rates. Conversely, the shortest dives tend to have higher
mean speeds and higher metabolic rates.
Fig. 8 shows DMR in relation to
dive duration. It shows a cloud of points with a curvilinear upper edge. We
hypothesised that this edge was suggestive of a physiological limit imposed by
available O2 stores, which would operate as a constraint on
behaviour during the dive. We examined the hypothesis that this upper edge was
related to oxygen stores and the rate of their use by fitting a line through
the 95th percentile of DMR. A theoretical limit to aerobic metabolism was
modelled by calculating the mass-specific maximum rate of metabolism during a
dive of a given duration, given the total body oxygen stores available to the
animal. For example, the oxygen store available to a diving grey seal of 50 kg
can be estimated as 3 litres (60 ml O2 kg-1;
Kooyman, 1989). Therefore, for
a dive lasting 5 min, the maximum possible rate of oxygen utilisation during
that dive is 0.6 l min-1 or 12 ml min-1 kg-1.
Likewise, a seal of 100 kg has an estimated oxygen store of 6 litres,
corresponding to a maximum rate of 1.2 l min-1 or, similarly, 12 ml
min-1 kg-1 for a 5-min dive. The slopes of the two lines
could then be compared. Because of the curvilinear appearance of this edge,
and the curvilinear nature of the relationship between maximum possible
aerobic DMR and dive duration, the y-axis was log10
transformed.
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This regression yielded a significant negative relationship between maximum log10 DMR and dive duration for seven out of eight seals. When dives from all animals were pooled, this regression was significant (P<0.05). Dives from all animals were pooled, and the edge predicted by regression of the 95th percentile was compared to the maximum predicted aerobic DMR. The line depicting maximum theoretical metabolic rate lies within the confidence limits of the fitted 95th quantile regression line (Fig. 9).
|
Predictive model
The full model predicting post-dive oxygen consumption
(O2; litres)
from dive behaviour is as follows:
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Discussion |
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Relevance to free-living animals
The range of dive behaviour exhibited by the seals in this study, in terms
of dive durations, swimming speed and distance travelled, is similar to that
recorded in wild grey seals using satellite telemetry. Although there may be
differences in behavioural motivation for performing dives between the seals
in this study and freely diving seals in the wild, the physiological processes
and consequences are likely to be similar. However, there are some obvious
differences in diving behaviour between the animals in our study and
free-living seals. Depth was simulated in our experiments by the distance that
seals could swim away from the breathing box, i.e. depth was transformed from
a vertical to a horizontal distance. Thus, all portions of the dive were
0.5-2.5 m below the surface and there was no true ascent or descent phase.
There may be problems, therefore, in making direct extrapolations from the
seals in our study to seals diving in the wild. The energetic consequences of
the interactions between buoyancy, pressure, drag and swimming mode are not
clear. Phocid seals generally exhale before diving so the relative
contribution of lung compression to buoyancy changes is likely to be less than
in other marine mammal species. Although Williams et al.
(1999) did demonstrate that
Weddell seals consumed more oxygen during the post-dive surface recovery
period following gliding dives than stroking dives that covered the same
distance, the authors only present total oxygen consumed and do not control
for the length of the dive or for the length of the surface recovery period.
For a negatively buoyant animal during descent, the negatively buoyant force
will exceed the magnitude of drag, so the animal will be aided in descent by a
net downward force. During ascent, the animal has to overcome the effects of
negative buoyancy and drag and therefore it has to work harder
(Webb et al., 1998b
;
Beck et al., 2000
). Any
energetic savings made on descent will therefore presumably be balanced by
these additional costs during ascent. Conversely, a positively buoyant animal
may expend more energy descending but savings may be made on ascent. Although
the exact balance of costs during ascent and descent remains to be addressed,
there may be no net difference in terms of energetic cost between horizontal
dives and vertical dives. There are also other aspects of behaviour exhibited
by wild seals that were not represented in our diving trials, such as prey
pursuit and capture. However, grey seals may adopt a `sit and wait' tactic
during foraging rather than actively pursuing prey
(Thompson and Fedak, 1993
),
which may not add to the energetic cost of the dive. How different modes of
locomotion and different foraging strategies affect diving metabolism are
avenues of exploration that we are currently addressing with further
experimental work. Despite these limitations, we believe that our experimental
set-up approximates the behaviour of free-living animals more closely than any
previous work on the diving metabolism of captive phocids.
Diving metabolic rate - evidence of hypometabolism?
Mean DMR of all 770 dives in this study was 1.7±0.45(K). This is
comparable to 1.6(K) in free-living Weddell seals diving under ice
(Castellini et al., 1992).
Eighty percent of all DMRs, even when seals were active and swimming an
average of 100 m during dives, were lower than resting levels measured under
standard conditions in the same seals. Kooyman
(1989
) defined hypometabolism
as a rate of metabolism lower than the rate that occurs under the standard
conditions of resting in the post-absorptive and normally quiet period of the
24-h cycle. In the present study, DMRs were lower than those measured under
standard resting conditions by 10-30%, suggesting hypometabolism during diving
in grey seals. This is further reinforced if we consider that we have
potentially overestimated the rate of oxygen utilisation over the submerged
part of the dive cycle, since `excess' oxygen is consumed during the surface
period and is not utilised during the dive. The reduction between standard RMR
and submerged metabolic rate is lower than the 47-65% reduction reported by
Hurley and Costa (2001
) in
trained California sea lions and the 60-70% reduction of metabolic rate in
grey seals found by Scholander
(1940
) during forced dive
experiments with grey and hooded seals. This difference in the extent of the
hypometabolism demonstrated between these studies and ours is probably a
result of the higher levels of activity of the animals in our study and the
fact that our animals were diving voluntarily and were therefore not
exhibiting the extreme response typical of forced dives.
Our findings have implications for estimates of food consumption by seal
populations. Bioenergetic models of phocid seal populations generally use a
multiplier of 2-3 times the Kleiber predicted metabolic rate to estimate the
energy requirements associated with at-sea activity in free-living phocid
seals (Olesiuk, 1993;
Mohn and Bowen, 1996
;
Nilssen et al., 2000
). If
free-living seals spend a significant portion of their time at the lower rates
demonstrated in the present study, current estimates of energy requirements
might be higher than they are in reality. More information is therefore
required on the activity budgets and foraging energy requirements of wild
seals.
Mass and DMR
Mass had a large effect on absolute diving metabolic rate (l
min-1). This is not surprising since, on an individual level,
energy associated with maintaining body tissues probably represents the
biggest single portion of expenditure and this is obviously higher in absolute
terms for larger animals. On a per kg basis, pups had a higher DMR than adults
but, when DMR was expressed as a multiple of Kleiber, pups had identical rates
to adults, suggesting that DMR scales intra-specifically with
mass0.75. This result emphasises the premium of large size to
diving ability. Furthermore, bioenergetic models generally use a higher
multiplier of Kleiber's predicted metabolic rate for juveniles than the one
used for adults to predict average requirements. This may be a source of error
in such models, especially for populations that are skewed towards juvenile
age classes (e.g. Olesiuk,
1993).
Dive duration and swim speed
Both the duration and mean swim speed of a dive influenced DMR. Our results
indicate that DMR decreases with increasing dive duration. Several other
studies have reported a similar relationship between DMR and submersion
duration. Thorson (1993)
reported that elephant seals showed decreasing MR with increasing submersion
duration. Hurley and Costa
(2001
) reported a similar
finding for California sea lions. The plot of DMR as a function of dive
duration shows points scattered below a maximum boundary that decreases
curvilinearly with dive duration and above a minimum boundary that is largely
independent of dive duration. A similar pattern has also been demonstrated in
free-ranging Weddell seals (Castellini et
al., 1992
) and in previous laboratory studies of grey seals
(Reed et al., 1994
). The
points that form the upper boundary are likely to represent the maximum
possible aerobic metabolic rate, a value that is determined by a combination
of the dive duration and the size of the oxygen store available to the animal
during that dive. Our data suggest that there is close agreement between the
maximum DMRs exhibited by our seals and the limit imposed by body oxygen
stores. Only 2% of all dives measured exceeded the theoretical capacity of the
animal to provide all the energy for the dive aerobically. We could not
directly address the possible contribution of anaerobic metabolism to DMR in
this study, since we did not measure blood lactate levels. However, we
consistently observed a high proportion (80-90%) of time spent submerged
during diving periods, suggesting that animals were not using anaerobic
metabolism to extend dive duration.
When submerged, diving mammals must balance the energetic demands of
locomotion with the conservation of a limited oxygen store
(Castellini et al., 1992;
Skrovan et al., 1999
).
Swimming activity during a dive influences the rate of oxygen consumption of
the actively exercising muscles, which in turn affects the aerobic limit to
dive duration. Williams et al.
(1999
) found that Weddell seal
dives that consisted of prolonged gliding resulted in lower post-dive oxygen
consumption than dives that consisted of continuous swimming, although the
duration of the dives or surface periods was not reported so a direct
comparison in terms of metabolic rate is not possible. In the present study,
mean swim speed during the dive had a significant effect on the metabolic rate
of a dive, and the dives with the highest swim speeds also tended to be the
shortest. Hindell et al.
(2000
) examined the influence
of swimming speed on dive duration in free-living southern elephant seals
(Mirounga leonina). They showed that maximum dive duration is
dependent on swimming speed; consequently, a seal has a range of different
ADLs depending on its activity during the dive, as well as possibly the extent
of metabolic suppression. It is clear that exercise performed when submerged
requires energy for the working muscles, and this rate of energy usage has
implications for the amount of time a seal can remain submerged before having
to return to the surface to replenish oxygen stores. This idea is by no means
novel and has been discussed by many authors (e.g.
Kooyman, 1989
;
Fedak 1986
;
Thompson et al., 1993
;
Hindell et al., 2000
) but
there have been few empirical studies describing how whole-body metabolism
varies as a function of variation in pinniped diving activity of the type
performed routinely by free-living animals.
Metabolic rate of grey seals measured in a swim flume displayed a fivefold
range, with activity ranging from sleep to swimming at 1.6 m s-1
(Fedak et al., 1988).
Furthermore, the fraction of time spent submerged decreased as speed increased
(Fedak, 1986
). This pattern
was also seen in harbour seals swimming in a flume at speeds over 1.2 m
s-1 (Williams et al.,
1991
). Our seals had metabolic rates that ranged between 1 and 4
times predicted basal rates as speeds increased up to a maximum of 1.4 m
s-1. We did not observe a similar increase in the proportion of
time spent at the surface when seals were swimming at higher speeds during
dives. The present study differs from those involving seals swimming in flumes
in that any swimming activity is voluntary and occurs as part of a dive. The
mean swim speed of our seals rarely reached these higher speeds; although the
speed reported for each dive is the mean for the whole dive, some dives
consist of bursts of fast swimming at speeds over 2 m s-1.
Similarly, in nature, grey seals spend a significant fraction of their time
during dives motionless or swimming at low speeds
(Thompson and Fedak, 1993
).
Furthermore, seals in a flume are forced to swim just below the surface where
drag is much higher than a few metres below, a behaviour that phocid seals do
not display in the wild. This will add to the energetic costs for animals in
flumes, costs that are not likely to be an issue for free-living, foraging
grey seals.
The diving patterns exhibited by wild seals are likely to be a product of a complex interplay of many interrelated variables. On an individual dive level, the outcome will be particular to a set of circumstances such as prey type, distribution and size. Unravelling these relationships further will require approaches that combine laboratory studies of physiology and behaviour, such as this one, with field studies on diving behaviour and observations and further lab studies of a more manipulative nature testing behavioural and physiological responses to differences in prey type and distribution.
Predictive model
Across the range of mass in this study (from juvenile seals of 32 kg to
adults of 150 kg), the relationship between predicted and actual metabolic
rate had a slope close to 1. On average, over all dives tested, our model
overestimated actual metabolic rates by 4%. To put these errors into context,
predicting diving metabolic rates for the animals in this study by applying a
Kleiber multiplier of 2 resulted in overestimates of 14-18%. Our model
predicted the metabolic rate of seals in captivity, with relatively little
error, based on their behaviour as monitored by telemetry. Therefore, we can
conclude that applying the model to telemetry-derived behavioural data from
wild seals would allow us to predict the metabolic costs of dives of different
types exhibited in the wild with increased accuracy over the use of a simple
multiplier applied over all at-sea behaviour. We can then use these
predictions as an input into models that predict the energy requirements of
the population.
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Acknowledgments |
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