Functional Ecology 2008, 22, 245–254
doi: 10.1111/j.1365-2435.2007.01368.x
Estimating field metabolic rates of pinnipeds: doubly
labelled water gets the seal of approval
Blackwell Publishing Ltd
C. E. Sparling*,1, D. Thompson1, M. A. Fedak1, S. L. Gallon1 and J. R. Speakman2
1
Sea Mammal Research Unit, Gatty Marine Laboratory, University of St Andrews, St Andrews, Fife, KY16 8LB Scotland,
UK; and 2School of Biological Sciences, University of Aberdeen, Tillydrone Avenue, Aberdeen, AB24 2TZ Scotland, UK
Summary
1. Measures of the field metabolic rate of marine mammals are extremely difficult to make but they
are essential for assessing the impacts of marine mammals on prey populations, and for assessing
dive performance in relation to aerobic limits.
2. The doubly labelled water (DLW) method is an isotope-based technique for the estimation of the CO2
production, and hence energy expenditure, of free-living animals. Estimates of field metabolic rate
(FMR) from DLW in pinnipeds to date are extremely high and at the upper range for most mammals.
DLW has previously been validated in pinnipeds but logistical difficulties meant for these validations
were less than ideal, and it has been hypothesised that DLW may overestimate FMR in these animals.
3. To test this hypothesis, we used DLW and simultaneous open-flow respirometry to determine the
daily energy expenditures (DEE) of wild grey seals (Halichoerus grypus) held temporarily in a
captive facility, during 4–5 days of simulated foraging at sea. Comparing DEE from DLW and
respirometry, we found that DLW predicted DEE accurately (average difference between the two
estimates was 0·7% SD = 17% n = 31), but as with validations of other species there was a large
range of individual errors (from –39% to +44%).
4. The results dispel the doubts surrounding the use of DLW as a field method for estimating energy
expenditure in grey seals, and by implication other pinnipeds, and simultaneously open a series of
questions about their ability to maintain surprisingly high metabolic rates for protracted periods.
5. We make a number of recommendations for future studies of pinniped FMR using DLW. We
suggest use of the Speakman two-pool calculation will be most appropriate. Studies should aim for
enrichment levels as high as economically feasible but to at least 150 p.p.m. above background for
the O2 isotope. Measurement periods should be extended between one and two half-lives (5–10 days
for a typical foraging seal). We also encourage the calculation and presentation of estimates of
precision in estimates of FMR.
Key-words: grey seal, doubly labeled water, energetics, respirometry, isotopes
Functional Ecology (2007)
List of abbreviations
BMR: Basal metabolic rate
cADL: Calculated aerobic dive limit
DEE: Daily energy expenditure
DLW: Doubly labelled water
FMR: Field metabolic rate
RQ: Respiratory quotient (ratio of carbon dioxide produced to oxygen consumed).
rCO2: Rate of carbon dioxide production as calculated by DLW
TBE: Total body Energy
TBW: Total body water
TBF: Total body fat
TBP: Total body protein
VCO2: Rate of carbon dioxide production as calculated by open flow respirometry
VO2: Rate of oxygen consumption as calculated by open flow respirometry
*Correspondence author. E-mail: ces6@st-andrews.ac.uk
© 2007 The Authors. Journal compilation © 2007 British Ecological Society
246
C. E. Sparling et al.
Introduction
The marine ecosystem is increasingly perceived as being
under threat from over-exploitation by fisheries activity. The
top predators of the marine may be adversely affected by such
activity, and/or may exacerbate the effects of fishing on prey
species, and consequently come into direct competition with
fishing activity. Our understanding of these interactions
requires knowledge of the energy flux through marine mammal
populations, as this sets their food requirements, which in
turn determines their impact on fish stocks and potential
competition with fisheries. Knowledge about energy expenditure
of marine mammals while at sea is also important in the
context of diving physiology and life history. For example,
studies of the at-sea metabolic rates of some species of seals
and sea lions have shown that they are operating close to their
physiological limits (Costa & Gales 2003). Energetic or nutritional
stress has been implicated in several marine mammal population
declines; therefore, it is essential that reliable and accurate
field metabolic rate estimation techniques are available.
There are four main approaches to estimate energy flux
in free living animals: (i) a combination of quantification of
costs of various activities using indirect calorimetry, and time
and activity budget information from the field (e.g. Sparling
& Fedak 2004); (ii) correlative techniques that link physiological
measurements that can be telemetered from the wild, such as
heart rate (HR), to laboratory observations of energy flux
determined in the laboratory, typically also using indirect
calorimetry (e.g. Bevan, Speakman & Butler 1995; Butler
et al. 1992); (iii) measuring the changes in body mass and
composition over time to provide an estimate of energy output;
however, this is only possible when animals are fasting; and
(iv) an isotope washout technique, called the doubly labelled
water (DLW) method (Lifson & McClintock 1966; Nagy
1980, 1983; Speakman & Racey 1988; Speakman 1997, 1998),
that involves dosing animals with isotopes followed by
repeated captures to trace the isotope elimination, and
provides an overall measure of energy expenditure between
captures (Costa 1987; Reilly & Fedak 1991; Aquarone, Born
& Speakman 2006). The DLW technique allows the estimation
of CO2 production and hence energy expenditure from the
differential elimination of isotopes of hydrogen and oxygen
introduced into the body water. The O2 label is eliminated
from the body by continuous flux through the body of both
water and expired CO2, but the hydrogen label is only
eliminated by the water flux. The difference between the two
elimination rates is therefore correlated with CO2 production
(Lifson, Gordon & McClintock 1955). Multiplying the
difference in the gradients of the exponential declines in
isotope enrichments over time by the size of the body water
pool gives a quantitative estimate of CO2 production, but
there are many complexities involved in correcting for differential
distribution spaces of the labels and fractionation during
elimination (Speakman 1997) providing a number of alternative
calculation methods.
These different approaches have been used to estimate
metabolic rates and hence food intake in several pinniped species.
Unfortunately, the estimates provided by the different
methods differ greatly and are currently impossible to reconcile.
In particular, there are discrepancies between metabolic rate
measurements using the DLW technique and those obtained
from time and energy budgets based on respirometry in
captive conditions. At-sea field metabolic rates derived using
DLW in pinnipeds are generally high, for example, harbour
seals (Phoca vitulina) 6× basal metabolic rate (BMR) (Reilly
& Fedak 1991) and Antarctic fur seals (Arctocephalus gazella)
4·6–7·4 times BMR (Costa, Croxall & Duck 1989; Arnould,
Boyd & Speakman 1996a). These levels are exceptional
among mammals more generally where the average field
metabolic rate (FMR) is only 2 – 3× BMR (reviewed in Speakman
2000). In captive studies, such high rates have only been seen
where seals have been pushed to their maximal rates of energy
expenditure using swim flumes and additional drag from drag
cups or weights. Such rates appear to be sustainable aerobically for only very short periods (Davis, Williams & Kooyman
1985; Fedak 1986; Elsner 1987; Williams, Kooyman & Croll
1991; Butler et al. 1992). In contrast, laboratory-based
indirect calorimetry estimates of MR at realistic long-term
exercise levels, combined with time-energy budgets from wild
grey seals (Halichoerus grypus) generate estimates of at-sea
FMR between 1·5 and 3× BMR (Sparling 2003).
In other cases where FMR has been estimated from methods
other than DLW, for example, direct measurements of O2
consumption in freely diving Weddell seals (Leptonychotes
weddellii) under ice (Castellini, Kooyman & Ponganis 1992)
and using turnover of deuterium and changes in proximate
body composition in free living harbour seals (Bowen,
Oftedal & Boness 1992; Coltman et al. 1998), FMR estimates
were around 2–3× BMR, that is, consistent with the estimates
based on indirect calorimetry.
There are several possible explanations for this apparent
mismatch. FMR estimates from wild seals may have only
been taken from animals during periods of extremely high
metabolic activity. Alternatively it may be difficult to replicate
the conditions in the field to get correct estimates of energy
demands by respirometry to multiply by field time budgets.
Finally, there may be a discrepancy between the two main
techniques used to estimate FMR in seals, and previous
estimates of FMR for pinnipeds from DLW may have been
overestimated.
Speakman (1993) first suggested that DLW might overestimate FMR of seals on the basis that there may be an
unaccounted for additional flux of the O2 isotope in the
ornithine–arginine cycle that becomes quantitatively significant
in obligate carnivores. This view was reinforced after Boyd
et al. (1995) used DLW concurrently with respirometry to
measure the metabolism of California sea lions (Zalophus
californianus) swimming in a flume. Moreover, the only DLW
measurements available for large terrestrial carnivores (the
African wild dog, Lycaon pictus: Gorman et al. 1998) have
similar high levels of expenditure to the seals.
However, the overestimate by DLW compared to respirometry
in the Boyd et al. (1995) study is compromised by the short
duration of the measurement which meant the precision of
© 2007 The Authors. Journal compilation © 2007 British Ecological Society, Functional Ecology, 22, 245–254
Estimating FMR of seals 247
the DLW method was poor. Although Costa (1987) validated
the DLW method against food intake in a single nonswimming northern fur seal (Callorhinus ursinus) and found a
reasonable correspondence this situation involved activities
divorced from those representative of most FMR measurements on pinnipeds. In addition, validation of the method in
domestic dogs (Speakman et al. 2001) suggested no gross
overestimate by the DLW method relative to respirometry,
indicating the flux of O2 in the ornithine–arginine cycle was
not an issue.
This mismatch has direct management implications. What
estimate of energy flux and hence food consumption should
be used in fisheries and ecosystem models? As the DLW
estimates are consistently about twice those derived from the
alternative laboratory-based approach, it is clear that choice
of method could lead to a factor of two differences in predicted food consumption. At present we do not know if this
reflects real differences in metabolism between the laboratory
and field, or if it is the consequence of some problem with the
DLW method in its application to marine mammals.
Logistical problems involved have hitherto precluded a
simultaneous cross validation of methods for marine mammal
species in anything approaching realistic conditions. Here, for
the first time we present the results from a large-scale validation of the DLW method for use in pinnipeds over realistic
time-scales and foraging and diving schedules. In this study,
we tested the hypothesis that the DLW method overestimates
the metabolism of free-living seals.
Methods
We measured FMR of temporarily captive wild grey seals within a
purpose-built simulated foraging setup, which also functioned as a
respirometry chamber. All seals were caught in the wild, from local
haul-out sites and taken by boat to the captive facility of the Sea
Mammal Research Unit in St Andrews. Seals were released back
into the wild after a maximum period of 1 year. While at SMRU, the
animals were housed in outdoor seawater pools at ambient temperature and fed a diet of herring (Clupea harengus), mackerel (Scomber
scombus) and sprat (Sprattus sprattus) supplemented with vitamins
(Aquavits, International Zoo Vet Group, Keighley, UK).
We simulated 5-day long foraging trips, whereby the seal was ‘at
sea’ for 4–5 days, alternating periods of foraging (diving between
surface and underwater feeding device to feed) with periods of rest.
During this time seals were kept in a large pool (40 × 6 × 2·5 m) with
the surface covered by panels of aluminium mesh preventing the seal
from surfacing anywhere other than a clear acrylic breathing chamber
situated in one corner of the pool. This allowed for continual measurement of gas exchange. Each animal underwent three or four of these
simulated foraging trips, each measurement consisting of a range of
workloads and food intakes. Workload was manipulated by altering
the schedules of feeding dives during simulated foraging. Because of
the difficulty of serial capture and blood sampling (also likely to
be a constraint for studies on wild seals) we used the two-sample
approach where only a background, initial (equilibration) and final
isotope determination is made to track the turnover of both isotopes
over the experimental period.
At the beginning of each week a seal was taken into an enclosure
and weighed on a platform scale (Avery, ± 0·1 kg). It was then
sedated using an intravenous injection (dose of 0·005 mL kg–1) of
zoletil (Virbac, France). A blood sample (10 mL) was taken from
the extradural vein for determination of isotope background levels
(Speakman & Racey 1987: method D), before intravenous injection
of a weighted dose of isotopically labelled water containing 2H and
18
O. The syringe used to inject the DLW was weighed empty, and
then containing the DLW. On injection, the syringe was flushed
fully four times to ensure that all DLW had been injected into the
seal. The seal was then left in the enclosure with no access to food or
water for a 3-h equilibration period, after which a further 10-mL
blood sample was taken. Immediately after this second blood sample,
the seal went into the main pool and the aluminium mesh panels
were closed down. The panels remained closed until the end of the
trial, 4 – 5 days later. During this entire time the only place that the
seal could surface was the breathing box. At the end of the 5-day
period the seal was taken out of the main pool set up into an enclosure
where they were weighed and on a subset of individuals, a final isotope
dilution body composition was carried out. Blood tubes were
centrifuged immediately after collection at 1000 g for 15 min and
then plasma (50 μL) samples were drawn-off and the flame was
sealed into Vitrex precalibrated pipettes (Camlab, UK) for analysis.
SIMULATION OF FORAGING
The simulated foraging set up is described in detail in Sparling et al.
(2007). Briefly, seals were trained to swim from the breathing box
(the surface) to an automatic feeding device (prey patch), situated
80 m away from the breathing box. The feeder is an aluminium box that
houses a conveyor belt driven by an electric motor. The experimenter
placed fish into slots on the belt that were then presented to the seal at
an underwater window. A video camera was mounted above this underwater window recorded the seals’ presence at the feeder. Fish was presented on the feeder over a series of dives where prey encounter rate
(PER) remained constant within a given dive, but varied between dives.
RESPIROMETRY
O2 consumption and CO2 production during the entire 5-day trial
was measured using an open-flow respirometry system connected to
the breathing box. The breathing chamber had an inlet, which
opened to the outside, and an outlet, which was connected by 1·5–
in. diameter flexible hosing to a pump, situated inside the laboratory
(c. 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), sufficient to make the change in O2 concentration
during breathing around 1% and to prevent a build-up of CO2 levels.
Flow was maintained and monitored using Sable Systems Flow Kit
500H (Sable Systems International, Las Vegas, NV). A 500-mL min–1
subsample was pumped at positive pressure through a drying column,
and then to a CO2 analyser (Sable Systems CA10a, accuracy 1%,
resolution 0·001%, zero drift) and an O2 analyser (Sable Systems
FC-10a, accuracy 0·1%, resolution 0·0001%). Outputs of the gas
analysers (and the flow rates from the FlowKit) were connected to
the serial ports of a desktop PC. The PC stored fractional O2 and
CO2 concentration, pressure, temperature and flow rate with a time
stamp once per second. Analyser drift was minimal, but if it
occurred it was corrected for during data analysis. The system had
a lag of c. 30 – 40 s from when the seals began breathing (or bleeding
nitrogen gas into the chamber) until the first deflection on the O2
analyser, and a 95% response time of c. 1·5 min. CO2 analyser was
© 2007 The Authors. Journal compilation © 2007 British Ecological Society, Functional Ecology, 22, 245–254
248
C. E. Sparling et al.
calibrated daily using a 5% CO2 in nitrogen mix (BOC gases). O2
analyser was calibrated daily using ambient air and oxygen free
nitrogen gas (Fedak, Rome & Seeherman 1981). Rates of O2 consumption (V˙O2 ) and CO2 production (V˙CO2 ) were calculated using
the following equations:
V ( FIO2 − FEO2 ) + FIO2 ( FICO2 − FECO2 )
V˙O2 =
1 − FIO2
V ( FECO2 − FICO2 ) + FICO2 ( FIO2 − FECO2 )
V˙CO2 =
1 + FICO2
where V is the flow rate at STPD, FIO2 and FICO2 = O2 and CO2 fractions
of the air before it passed by the seal and FEO2 and FECO2 were the
fractions after it had passed the seal (Arch et al. 2006).
ISOTOPE SAMPLE ANALYSIS
Samples of plasma in capillaries were vacuum distilled into glass
Pasteur pipettes (Nagy 1983) and the water obtained used for isotoperatio mass spectrometric analysis of 2H and 18O. The 2H analysis was
performed on hydrogen gas, produced by on-line chromium reduction
of water (Morrison et al. 2001; Speakman & Krol 2005).
For analysis of 18O enrichment in blood samples, water distilled
from blood was equilibrated with CO2 gas using the small sample
equilibration technique (Speakman et al. 1990). For analysis of
18
O : 16O ratios, equilibrated water samples were admitted to an
ISOCHROM μ GAS system (Micromass, UK), which uses a gas
chromatograph column to separate nitrogen and CO2 in a stream of
helium gas before analysis by IRMS.
For estimation of the injectate enrichment, the original injectate
was diluted with tap water (five different solutions, ± 0·0001 g), in
proportions similar to those expected in the seals. Mass spectrometric analysis of 2H and 18O was performed on five subsamples of each
solution and five subsamples of tap water. The enrichment of the
injectate was calculated for the five different solutions (Prentice
1990; Speakman 1997), and then averaged. We used isotopically
characterized gases of H2 and CO2 (CP grade gases, BOC Ltd) in the
reference channels of the IRMSs. Reference gases were characterized
every 3 months relative to SMOW and SLAP (Craig 1961) supplied by
the IAEA. Each batch of samples was run adjacent to triplicates of
three laboratory standards to correct for day-to-day differences in mass
spectrometer performance and inlet cross-contamination (Meijer,
Neubert & Visser 2000). All isotope enrichments were measured in
δ per mille relative to the working standards and converted to
p.p.m., using the established ratios for these reference materials.
The measures of isotope enrichment in blood samples were based on
analysis of five subsamples (2H) or two subsamples (18O); all subsequent calculations were performed on the mean values.
CALCULATING ENERGY EXPENDITURE AND BODY
COMPOSITION WITH DLW
CO2 production was calculated for each trial using several different
published models each making different assumptions about
fractionation of isotopes, evaporative water loss and different combinations of body water pool estimates. Each model is described
briefly below but for a full discussion of the different calculations
and their assumptions see Speakman (1997). The Lifson & McClintock
(1966) model (eqn 7·3 in Speakman 1997) uses only the O2 dilution
space to estimate of the body water pool size. Fractionation factors
were derived at 25 °C and evaporation is assumed to be 50% of
water loss. Nagy (1980; eqn 17·13) is a simpler calculation ignoring
the fractionation corrections. Speakman (1997) derived a new
equation (eqn 7·17), which assumes only 25% of water loss is
fractionated and fractionation factors reflecting a mix of kinetic and
equilibrium processes at 37 °C.
These models are collectively called one-pool models and make
the assumption that the oxygen and hydrogen dilution spaces are
the same. However, hydrogen partakes in other exchange reactions
in the body and thus spreads to a slightly larger pool than oxygen
(Sheng & Huggins 1971; Culebras & Moore 1977). Coward, Prentice &
Murgatroyd (1985; eqn 7·34) suggested that the calculation should
involve the elimination rate ( k o and k d) and for each isotope
multiplied by their respective dilution spaces (No and Nd). Models
such as this, utilizing both dilution spaces are called two-pool
models. Schoeller et al. (1986) devised a two-pool model with revised
fractionated factors (eqn 7·40 in Speakman 1997). Speakman (1987,
1993) showed that in theory two-pool models will be more appropriate
in larger animals (above 10 kg). Speakman (1997; eqn 7·43) derived
a two-pool model equivalent in all other respects to the one-pool
model represented by eqn 7·17.
Initial isotope dilution spaces (mol) were calculated using the
plateau method (Halliday & Miller 1977) and were converted to
millilitres assuming a molecular weight of body water of 18·020.
This technique has been previously validated against chemical
analysis in seals (Arnould, Boyd & Speakman 1996b). Final dilution
spaces were measured in 16 of the 32 trials and were estimated for
the remaining 16, from final body mass, assuming the same percentage
of body mass as measured for the initial dilution spaces (average
difference between body water as percentage of body mass between
initial and final across the 16 trials where both were measured was
< 1%). CO2 production rates from both respirometry and DLW
were converted into energy expenditure using energy equivalents
calculated from the measured respiratory quotient (RQ) using the
Weir equation (1949).
CALCULATION OF UNCERTAINTY
We used a Monte Carlo simulation approach to incorporate uncertainty
in all input parameters to calculate confidence limits for our body
composition and daily energy expenditure (DEE) calculations (after
Speakman 1995).
DLW estimates
To compute one estimate of DEEdlw, we’d generally use the mean
isotope values from four replicate analyses. These replicate analyses
gave us an indication of the analytical variability. For each isotope
datum, four values were drawn at random from a distribution
described by the mean of the replicate analyses for that sample and
the standard deviation either (i) calculated as the average standard
deviation across isotope samples from all 3 years of the study or
(ii) the average standard deviation from the year the samples were
from (see Table 1). The mean of the four resulting values were then
used to calculate the rate of carbon dioxide production (rCO2).
Repeating this process 1000 times gives a distribution of DEE estimates
from which we can calculate confidence limits (Speakman 1995).
Respirometry estimates
We used the manufacturer’s accuracy levels to describe uncertainty
in each parameter in the equations for calculating the rate of O 2
© 2007 The Authors. Journal compilation © 2007 British Ecological Society, Functional Ecology, 22, 245–254
Estimating FMR of seals
Table 1. Variation in replicate hydrogen (H) and oxygen (O) isotope
analyses in the 3 years of the study
2004
2005
2006
All
Mean number
of replicate
analyses
Mean standard
deviation of
replicates
Mean
standard
error
H
O
H
O
H
O
5·8
4·3
3·4
4·4
4
4
4
4
0·40
0·42
0·54
0·45
0·97
1·32
3·30
1·93
0·19
0·23
0·33
0·25
0·56
0·77
1·91
1·12
consumption (VO2) and the rate of CO2 production (VCO2). For a
particular experiment, each iteration of the calculation drew each
parameter from a distribution described by the mean value of that
parameter from that experiment and a standard deviation which
was calculated using the manufactures quoted accuracy estimate as
a co-efficient of variation (these were 1% of full scale measurement
for measurement of FCO2 and flow rate, and 0·1% for measurement
of FO2).
For comparison, we also carried out empirical tests using gas
dilutions where we bled a mixture of 5% CO2 in nitrogen gas into the
breathing chamber at a measured rate. This gas affected the
downstream gas fractions in a similar manner to the respiratory gas
exchange of an animal – i.e. elevated CO2 fraction and depleted O2
fraction. Expected values of VO2 and VCO2 were compared to values
derived from the downstream respirometer flowmeter and gas
analysis after the calibration gas stream was diluted and mixed into
the respirometer airstream at the empty animal chamber.
Body composition changes
We used the same approach as for DLW to calculate error in dilution
spaces from variation in isotope analysis. From these we also
calculated error in our body composition measures. Because TBF
and TBP are estimated using TBW as a percentage of body mass, to
estimate error in fat and protein we had to incorporate a value for
uncertainty in our measurements of body mass. Uncertainty in body
mass is likely to be a result of differences in wetness of animal,
amount of food in digestive tract as well as variability in the scales.
We carried out repeat weighing of animals at different stages of fur
wetness and at different times of day and estimated a CV of 1·5%.
So for the Monte Carlo simulations, the standard deviation was set
at 1·5% of measured mass.
Results
We carried out 32 comparisons of DLW to respirometry over
3 years, using nine female grey seals (three adults and six
juveniles < 1 year). The measurement period ranged from
96·5 to 120 h. During the comparisons, seals swam 70 ± 1·8 km.
For full details of all trials see Supplementary Table S1.
ISOTOPE DILUTION
Dilution space ratios were between 0·975 and 1·078, with an
overall mean of 1·022 (see Supplementary Table S2). TBW of
the seals at the start of each measurement ranged from 46% to
249
Table 2. Estimates of precision in various stages of estimation of
body composition changes
Nd (mls)
TBW (mls)
TBW (% body mass)
TBF (kg)
TBF (% body mass)
ΔFat (kg)
Mean value
Mean CV%
32 104
30 982
53
16·6
27·4
1·45
0·27
0·27
1·63
6·7
5·2
268
Fig. 1. Correlation between DEE (daily energy expenditure in MJ d–1)
as measured by DLW (Speakman 1997 two-pool model) and by
respirometry. The dashed line is the line of unity.
65% of total body mass (mean 53% ± 4). We estimated precision of absolute TBW to be 0·3%. Expressed as a percentage
of total body mass, however, and therefore including variability
due to imprecision in our estimates of body mass, precision
increases to 1·63%. As fat and protein content are estimated
using TBW%, precision of these values were 5% – 7%. In
addition, because changes in body composition during each
experiment rely on two measurements of TBW% the error in
Δfat are very large (Table 2).
DAILY ENERGY EXPENDITURE
(DEE)
We recorded a range of DEEresp estimates ranging from
8·74 to 26·18 MJ day–1 (Fig. 1). These values, along with
corresponding DEEdlw estimates and the ratio between the
two estimates are detailed in Supplementary Table S3. Adult
values averaged 20·10 ± 4·2 MJ day–1 and juveniles averaged
at 11·23 ± 1·7 MJ day–1. These values correspond to 1·9 and
2·6 times predicted basal metabolic rates (Kleiber 1975), and
0·9 and 1·2 times predicted field metabolic rates for mammals
of a similar mass (Nagy 2005). DEEdlw estimates covered a
similar range from 7·29 to 27·89 MJ day–1.
The original method of calculation of rCO2 using DLW
advocated by Lifson & McClintock (1966) resulted in a mean
overestimate of 0·5% (SD = 17·4). Individual estimates using
this method varied from an underestimate of 38% in experiment G3 to an overestimate of 44% in experiment B2. When
© 2007 The Authors. Journal compilation © 2007 British Ecological Society, Functional Ecology, 22, 245–254
250
C. E. Sparling et al.
Fig. 2. Bland–Altman plot of differences between two methods.
using the two-pool model by Coward et al (1985; using
individual ratios for dilution space) DEE is underestimated
on average by 7% (SD = 17·8), individual errors ranged from
–42% to +30%. Schoeller et al. (1986; two-pool model using
fixed estimate of dilution space ratio of 1·03) generally underestimated DEE. Errors varied between –30% and +37%, with
a mean error of –5% (SD = 17·5). The alternative approach of
using the observed mean dilution space of 1·02 (Speakman
1997; two-pool model) produced errors of between –39% and
+44% with a mean error of 0·5% (SD = 17·5) (Fig. 1). See
Supplementary Table S3 for details of all individual model
calculations. No significant differences were found between
DEEdlw and DEEresp when using the Speakman (1997) two-pool
(paired sample t = 1·09, df = 31, P = 0·284), Lifson and
McLintock (t = 0·81, P = 0·424) or Speakman (1997)
one-pool models (t = –1·55, P = 0·131). However, significant
differences were indicated between DEEdlw and DEEresp when
using the Nagy (1980) (t = –2·50, P = 0·018) or Schoeller (1986)
equations (t = 2·19, P = 0·036). The random scatter of points
on a Bland–Altman plot (Fig. 2) demonstrates good agreement between the two methods (respirometry and DLW using
the Speakman 1997 two-pool model) (Bland & Altman 1987).
For all calculations of precision in DLW, we used the results
from the Speakman (1997) two-pool model. We calculated an
overall precision of our DLW estimates at 7%. Supplementary Table S4 shows the confidence intervals calculated for
both estimates of DEE. Confidence intervals overlapped in
75% of all trials. When the mean standard deviation across all
isotope analyses (across the three different years of analysis)
was used in the simulations, there was a negative relationship
between the CV of the DLW estimate and both the initial
enrichment above background and the difference between the
initial and final enrichments (Fig. 3).
Incorporating the manufacturers estimates of measurement
accuracy in respirometry calculations gave an overall CV of
2·5% for our estimates of DEEresp. This compared to a CV of
2·1% calculated by carrying out empirical tests comparing
expected and measured volumes of calibration gases flowed
through the system. In calculating confidence intervals
for our respirometry estimates of DEE, we used the wider
estimate of uncertainty.
Fig. 3. Variation in precision of calculated DEEdlw with variation in
(a) level of initial isotope enrichment in p.p.m. above background
levels and (b) the extent of depletion of the initial isotope dose (initial
minus final enrichment in p.p.m.). See text for description of precision
estimation.
Table 3. Mass and body composition changes over each 5-day trial
as predicted by isotope dilution
Trial
ΔMass
(kg)
ΔFat
(kg)
ΔWater
(kg)
ΔProtein
(kg)
ΔTBE
(MJ)
A1
A2
A4
B1
B2
D1
D2
D3
D4
E1
E2
E3
E4
G1
G2
G3
1·2
–3·0
–3·2
–0·2
1·6
1·0
–0·6
3·0
0·0
3·4
–0·4
3·8
–1·2
8·6
7·6
3·2
4·07
4·32
0·83
1·89
2·36
0·94
0·01
1·72
0·73
1·99
0·64
–2·13
0·43
–2·45
3·12
3·42
–1·98
–5·16
–2·92
–1·48
–0·52
0·05
–0·46
0·96
–0·52
1·06
–0·74
4·15
–1·17
7·82
3·31
–0·04
–0·89
–2·02
–1·07
–0·61
–0·29
–0·03
–0·16
0·26
–0·22
0·28
–0·29
1·56
–0·44
2·87
1·03
–0·17
1451·7
1345·9
134·2
636·3
882·9
367·2
–24·7
726·3
251·7
839·5
201·0
–563·5
92·6
–453·0
1421·4
1323·0
FOOD INTAKE AND MASS BALANCE
Mean body mass change over the period of the DLW measurements was +1·7 kg (Table 3), ranging from a decrease in
3·2 kg to an increase in 8·6 kg. Food intake varied greatly
between individual trials – between 4·3 and 32 kg during the
trials with an average of 13·5 kg. There was a significant
© 2007 The Authors. Journal compilation © 2007 British Ecological Society, Functional Ecology, 22, 245–254
Estimating FMR of seals
251
Fig. 4. Predictions of energy intake given different assumptions of the composition of mass change between the start and end of experiment.
The different assumptions were: (a) water; (b) lean tissue; (c) fat; (d) same composition as initial; and (e) as estimated by initial and final isotope
dilution. Energy Intake (MJ) = Energy Expended (MJ as estimated by DLW) + ΔBody Energy (MJ).
correlation between food intake and mass change (R2 = 39·2%,
P < 0·0001). We converted food intake into energy intake
using the established energy content of the diet depending on
fish species consumed (7·6 kJ/g for herring, 7·5 kJ/g for mackerel,
7·9 kJ/g for sprat). For those trials where we performed body
composition determinations at the start and end, we calculated the change in body fat and protein, and converted this
into changes in energy content (using the values of 39·6 kJ/g
for fat and 16·8 kJ/g for protein) and added this to the energy
expended to give an estimate of actual energy intake. For all
the trials, we also estimated energy intake using four different
assumptions about the composition (and thus energy content) of mass change: (i) changes in mass were due to
changes only in water content and the energy content of the
animal did not change; (ii) 100% of the mass change was fat;
(iii) 100% of the mass change was lean tissue; and (iv) the mass
lost or gained was identical in composition to the starting
body composition.
Assuming that the mass change consisted of lean mass or
water consistently underestimated food intake and assuming
fat overestimated suggesting that the body composition of the
mass change was a mixture. Assuming that the mass change
was of the same proportion as in starting body composition
gave the best predictions of energy intake (Fig. 4).
Discussion
The good correspondence between DEEdlw and DEEresp in
this study lends confidence to the utility of the DLW method
for estimating the FMR of seals. Most validation studies of
the DLW method report good agreement between the mean
values averaged over a group of individuals. Taking the 0·5%
mean difference over all individual validations, our results
are well within the range of previous validation studies in
terrestrial mammals, which have an average discrepancy of
2·23% (Speakman 1997).
© 2007 The Authors. Journal compilation © 2007 British Ecological Society, Functional Ecology, 22, 245–254
252
C. E. Sparling et al.
Precision increased with increasing initial isotope enrichment above background and also increased with an increase
in the difference between initial and final enrichments. The
latter effect depends on the relative contribution of water
turnover and metabolism to washout of the O2 isotope.
However, the initial enrichment is within the control of the
researcher. These data suggest that while injecting more
isotope is more expensive, the payback for this expense is an
estimate with greater precision. Figure 3 provides an empirical
picture of the likely nature of this trade-off in a free-living
seal, which may be useful in the design of future DLW studies
of pinnipeds to aid researchers in choosing the necessary
injection levels of isotopes to achieve given levels of precision.
In the only other validation of the DLW technique against
respirometry in marine mammals Boyd et al. (1995) reported
that DLW overestimated DEE of California sea lions (Z. californianus) on average by between 36% and 46% depending on the
calculation method employed. However, the duration of this
validation was not ideal, depletion of oxygen and hydrogen
isotopes was only 14% and 9%, respectively (compared to
46 ± 13% and 38 ± 12% in the present study), and precision in
the resulting estimate, therefore, was very low (overall CV of
35% compared to the 7% calculated in this study). This
comparison highlights the importance of carrying out DLW
trials over long enough periods. Nagy (1983) recommended at
least one and preferably two half-lives, and we concur with
this recommendation. In seals this would mean a period of
between about 5 and 10 days. Our data extend the only other
validation of the method over this duration in seals made by
Costa (1987) who compared the DLW method to material
balance in a single individual on land, and found reasonable
correspondence between the techniques. Although the cost of
O2 isotopes can limit the amount used for dosing animals,
particularly for such large animals as seals, our data support
the suggestion from Speakman (1997) that the lowest dose
used in large mammals should be at least 150 p.p.m. excess for
the O2 isotope. Although it may appear tempting to reduce
the isotope dose to enable more animals to be measured, the
resultant quality of the data makes this a false economy.
The difference in dilution spaces between the two isotopes,
with hydrogen space exceeding O2 space by an average of 2%,
is consistent with other studies of mammals (Speakman 1997)
and is slightly lower than that found in other studies of marine
mammals and humans (Speakman, Nair & Goran 1993).
Although some studies of DLW present estimates of
precision in individual metabolic rate determinations (e.g.
Corp, Gorman & Speakman 1999), the same cannot be said
for most published uses of isotope dilution estimation of body
composition. Our estimates of 1·6% and 5·2% CV in estimates
of TBW and TBF as percentage of body mass, respectively,
are larger than some of the reported changes over the trials
highlighting the fact that the precision of the method is not
sufficient to detect small changes over short time-scales.
Precision in estimates of changes in body composition could be
improved by decreasing error in body mass estimation. However,
we found that variation in the amount of food seals had in
their digestive system had a large effect on mass. Such factors
are likely to be difficult to control for in the field situation.
Most previous field applications of the DLW method to
pinnipeds have used the Nagy (1983) equation. This equation
is a one-pool model equation which makes no correction for
fractionation effects. In the current validation, this equation
resulted in an overestimate of the simultaneous respirometry
by about 13%. Using a two-pool approach, and taking into
account fractionation effects both lead to reductions in the
DLW estimate. The extent of the reduction compared with
the Nagy equation depends on the details of the assumptions
made about the relative pool sizes and, with respect to
fractionation, the proportion of water lost in fractionated
form and the detailed fractionation factors. The Lifson and
McClintock equation is also a one-pool equation like the
Nagy equation, but it attempts to correct for fractionation.
When Lifson and McClintock made their fractionation
correction they used the only available fractionation factors
at the time, which were for effects at 25 °C. They also assumed
that 50% of water loss is fractionated. In the current study
using this equation reduced the estimated DEE by DLW
by about 15% giving a very good match to the respirometry
data. However, one-pool models are probably inappropriate
for large animals like seals (Speakman 1987, 1993). The
Coward & Prentice (1985) equation combines the Lifson and
McClintock assumptions about fractionation with a two-pool
approach. This resulted in a decreased estimate of metabolism
by DLW of about 20% below that derived by the Nagy
equation and 7% lower than the simultaneous respirometry.
Schoeller et al. (1986) pointed out that the fractionation
assumptions made by Lifson & McClintock (1966) probably
result in an over-correction for fractionation effects. The
Schoeller et al. (1986) equation makes more realistic assumptions
for fractionation, but it combines these with a fixed assumption
for the pool size ratio (1·036), which for these seals is too large.
Consequently, because these effects cancel out, the Schoeller
equation also underestimated the DEE compared to simultaneous respirometry. The correct fractionation effects make
the estimate larger, but the excessive pool size ratio reduces
the estimate again. The result is an underestimate of the
respirometry again by 5%. The Speakman two-pool model
uses the observed pools size ratio and therefore overcomes the
problem of making a fixed assumption, as in the Schoeller
equation, and it also makes more realistic estimates of the
fractionation effects. This equation also gives an answer that
is almost identical to the simultaneous respirometry.
Although on the face of it there appears little to choose
between the Lifson and McClintock, and Speakman two-pool
equations, we would argue that the latter equation is a better
choice. This is because the Lifson and McClintock equation
reaches the correct answer only because its faults in this
situation cancel each other. That is, it ignores the two-pool
effect, but overestimates fractionation effects. This fortuitous
cancelling of errors may not occur in all circumstances.
Accordingly using the Speakman two-pool model will be
more robust to variations in the conditions under which
measurements are made. As expected the Speakman one-pool
model gives an estimate that is too high because it makes
© 2007 The Authors. Journal compilation © 2007 British Ecological Society, Functional Ecology, 22, 245–254
Estimating FMR of seals
realistic fractionation assumptions but does not account for
the two-pool effect.
Interestingly, the difference between the Nagy and Speakman
two-pool equations of 12% in this study is very close to the
difference of 14% found in studies of Australian sea lions
(Costa & Gales 2003) and New Zealand sea lions (Costa &
Gales 2000).
Our results do not support the hypothesis that DLW
significantly overestimates the metabolic rates of pinnipeds
(Speakman 1993; Boyd et al. 1995). This suggests that field
metabolic rates of pinnipeds have been measured during
periods of very high energy expenditure (e.g. Reilly & Fedak
1991; Costa & Gales 2000, 2003; Aquarone et al. 2006). These
high rates of energy expenditure have implications for the
impact of pinniped populations on their prey and open a
series of questions about their ability to maintain surprisingly
high metabolic rates for protracted periods.
In conclusion, our validation of the DLW method in seals
was carried out under conditions and over durations comparable to those encountered during field applications of the
method. The use of either the Speakman (1997) two-pool
model or the Lifson & McClintock (1966) one-pool model
yielded the best estimates of DEE. We suggest use of the
Speakman two-pool calculation will be most appropriate for
future studies. We recommend that future studies of large
mammal FMR using DLW aim for enrichment levels as high
as economically feasible but to at least 150 p.p.m. above
background for the O2 isotope (as suggested by Speakman
1997). Measurement periods should be extended to between
one and two half-lives as recommended by Nagy (1983) (5–10
days for a typical foraging seal). This has the added advantage
that animals are more likely to be in energy balance over the
measurement period if the measure is protracted (Speakman
et al. 1994). We encourage the calculation of precision
using the variability in input parameters and endorse the
recommendation of Speakman (1997) that raw data from
such studies should be presented (in appendices or electronic
supplements) to allow easy comparison with future studies.
We also conclude that, where the body composition changes
are likely to be small relative to the uncertainty in isotope
determination of TBW, TBF and TBP, there is nothing to
gain from performing isotope dilution both at the start and
the end of the DLW trial and equally satisfactory results can
be gained from assuming that the composition of any mass
change is the same as the starting body composition.
Acknowledgements
S. Moss provided invaluable assistance with animal handling; A. Zollinger and
S. Brando helped with simulated foraging trials; P. Thomson and P. Redman
carried out the isotope analysis. The Natural Environment Research Council
UK provided funding for this work (NER/D/S/2003/00650).
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Received 25 May 2007; accepted 06 November 2007
Handling Editor: Daniel Costa
Supplementary material
The following supplemental material is available for this article:
Table S1. Details of all DLW trials. DEE is Daily Energy
Expenditure as measured by respirometry. No TDR in the
column ‘Distance travelled’ indicates the experiments for
which there is no time depth recorder data. *Respiratory
Quotient: O2 consumption/CO2 production
Table S2. Isotope turnover rates (oxygen, ko and hydrogen
kd) and dilution spaces (No and Nd)
Table S3. Comparison of respirometry and DLW estimates
of Daily Energy Expenditure. See text for details of the
different calculation models
Table S4. Results of Monte Carlo simulations of calculations
of DEE derived from both respirometry and DLW using
variability in input parameters
Table S5. All replicate oxygen isotope analyses (18O p.p.m.)
Table S6. All replicate hydrogen isotope analyses (2H p.p.m.)
This material is available as part of the online article from:
http://www.blackwell-synergy.com/doi/full/10.1111/
j.1365-2745.2007.01368.x
(This link will take you to the article abstract).
Please note: Blackwell Publishing is not responsible for the
content or functionality of any supplementary materials supplied
by the authors. Any queries (other than missing material)
should be directed to the corresponding author for the article.
© 2007 The Authors. Journal compilation © 2007 British Ecological Society, Functional Ecology, 22, 245–254