Two physiological parameters that have received a great deal of
attention from ecologists and physiologists alike are standard
metabolic rate (SMR) and active metabolic rate (AMR), usually
estimated from measurements of oxygen consumption rate (MO2).
Because SMR is defined as the minimal maintenance metabolic rate
of a post-absorptive resting ectotherm, below which physiological
function is impaired (Brett and Groves, 1979; Priede, 1985), it is
in fact the basic cost of living at a certain temperature and therefore
of major functional importance. In the other end of the metabolic
scale, AMR, the maximal aerobic metabolic rate at a given
temperature, provides the upper boundary for aerobic energy
metabolism. Subtracting the minimal from the maximal metabolic
rate provides a measure of the total amount of aerobic energy
available to the animal, the absolute aerobic scope (AAS). In
salmonid fish, a high SMR has been interpreted as an advantage,
despite the increased cost of living, because of its positive correlation
with dominance, aggression and growth rate (Metcalfe et al., 1995;
Cutts et al., 1998).
In order to ascribe certain properties to an individual animal on
the basis of a single physiological measurement, an in-depth
understanding of the temporal consistency (repeatability) of the trait
under investigation is essential. If a trait is not repeatable over time,
a single measure or estimate of the trait may not be representative
of future physiological performance. Repeatability studies differ
greatly in the time frame over which consistency has been evaluated.
Commonly, repeatability is high when evaluated over relatively short
periods of time but tends to decrease with increasing time between
measurements (van Berkum et al., 1989; Chappell et al., 1996;
Rønning et al., 2005). Because repeatability estimates provide a
measure of the consistency of individual differences within a
population (Dohm, 2002), and potentially an estimate (upper limit)
of heritability (e.g. Sadowska et al., 2005), a balance exists between
the period of time over which the trait is repeatable and the life
span (or a certain part of ontogeny) of the animal under investigation.
In other words, repeatability must persist across a significant part
of an animal’s life, or across some part of ontogeny, in order for
selection to affect the trait, provided that the trait is heritable.
Nespolo and Franco reviewed literature studies on the
repeatability of metabolic rates and concluded that, in biological
terms, metabolic rate could be considered a repeatable trait and that
no additional studies on repeatability were needed (Nespolo and
Franco, 2007). These authors assessed repeatability from whole-
animal metabolic rates but, as emphasized by Konarzewski et al.
(Konarzewski et al., 2005), whole-animal metabolic rate is intimately
associated with body mass, artificially producing high and consistent
repeatability of metabolism because of a reflection of body mass
repeatability. The conclusion drawn by Nespolo and Franco
(Nespolo and Franco, 2007) is based on 44 studies, of which only
two are on fish. A few additional studies on fish exist, but in these
the repeatability of metabolic rate has been estimated mainly as
consistency of SMR (McCarthy, 2000; O’Connor et al., 2000; Cutts
et al., 2001; Seppänen et al., 2010; Maciak and Konarzewski, 2010)
whereas AMR has received little attention (Reidy et al., 2000).
Although Seppänen et al. (Seppänen et al., 2010) were only partially
able to show consistency in SMR, the other studies found
repeatability of SMR (and AMR) to be quite high over periods of
time up to 5months.
The Journal of Experimental Biology 214, 1668-1675
© 2011. Published by The Company of Biologists Ltd
Repeatability of standard metabolic rate, active metabolic rate and aerobic scope in
young brown trout during a period of moderate food availability
Tommy Norin* and Hans Malte
Zoophysiology, Department of Biological Sciences, Aarhus University, DK-8000 Aarhus C, Denmark
*Author for correspondence (firstname.lastname@example.org)
Accepted 26 January 2011
Standard metabolic rate (SMR) and active metabolic rate (AMR) are two fundamental physiological parameters providing the floor
and ceiling in aerobic energy metabolism. The total amount of energy available within these two parameters confines constitutes
the absolute aerobic scope (AAS). Previous studies on fish have found SMR to closely correlate with dominance and position in
the social hierarchy, and to be highly repeatable over time when fish were provided an ad libitum diet. In this study we tested the
temporal repeatability of individual SMR, AMR and AAS, as well as repeatability of body mass, in young brown trout (Salmo trutta
L.) fed a moderately restricted diet (0.5–0.7% fish mass day–1). Metabolism was estimated from measurements of oxygen
consumption rate (M MO2) and repeatability was evaluated four times across a 15-week period. Individual body mass was highly
repeatable across the entire 15 week experimental period whereas residual body-mass-corrected SMR, AMR and AAS showed a
gradual loss of repeatability over time. Individual residual SMR, AMR and AAS were significantly repeatable in the short term
(5 weeks), gradually declined across the medium term (10 weeks) and completely disappeared in the long term (15 weeks). We
suggest that this gradual decline in repeatability was due to the slightly restricted feeding regime. This is discussed in the context
of phenotypic plasticity, natural selection and ecology.
Key words: repeatability, standard metabolic rate, active metabolic rate, absolute aerobic scope, body mass, brown trout, Salmo trutta, diet.
THE JOURNAL OF EXPERIMENTAL BIOLOGY
1669Repeatability of metabolic rate in trout
In the present study, we provide estimates of repeatability of
SMR, AMR and AAS, as well as body mass, in a salmonid fish,
the brown trout (Salmo trutta Linnaeus 1758). In contrast to other
repeatability studies on fish that have provided food ad libitum [or,
as in the study by O’Connor et al. (O’Connor et al., 2000), totally
deprived the fish of food] we assessed repeatability during a period
of moderate food availability, a situation that most resembles food
availability in the wild.
MATERIALS AND METHODS
All brown trout used in this experiment were offspring of wild trout
caught by electrofishing in the River Skjern, Denmark. Fertilised
eggs from parent fish were kept in freshwater trays and hatched in
March 2009 at The Danish Centre for Wild Salmon (Skjern,
Denmark). Immediately after hatching, fish were held in hatchery
troughs. Exogenous feeding commenced in late April/early May,
after which the fish were transferred to circular flow-through tanks,
kept at ambient temperature and photoperiod, and fed commercial
trout pellets. In October 2009, at a size of 95–110mm, 260 brown
trout were relocated to holding facilities at Aarhus University,
Denmark, where they were held in a 720l freshwater aquarium at
15±0.5°C and 9h:15h light:dark photoperiod. Water was continually
recirculated through a filter and exchanged at a rate of 700lweek–1.
Fish were fed daily with BioMar (Brande, Denmark) INICIO Plus
trout pellets from an automatic feeder, mounted above the aquarium,
at an amount corresponding to 0.5–0.7% fish mass per day. On 4
November 2009, 50 fish were randomly chosen from the population
and individually marked using small implantable FDX-B passive
integrated transponder (PIT) tags encapsulated in a bio-compatible
glass tube (LoligoSystems, Tjele, Denmark). The tags weighed 0.1g
with dimensions of 13.5?2.1mm and provided each fish with a
unique 15-digit code. PIT tags were surgically implanted into the
abdominal cavity of anaesthetised fish (0.1gl–1benzocain) through
a small incision on the ventrolateral side just posterior to the pectoral
fin. After marking, the aquarium was divided with a rigid plastic
net (mesh size 5?5mm) providing full separation of marked and
unmarked fish while allowing for complete mixing of water
throughout the aquarium. Only the marked fish were used in this
experiment. Effects of PIT-tag marking on growth and survival of
brown trout have been found to be negligible on fish larger than
55–57mm (Ombredane et al., 1998; Acolas et al., 2007). In the
present study, no fish died or exhibited reduced growth as a
consequence of the tagging procedure. Tag retention was 100%. Of
the 50 marked fish, 36 were randomly chosen for respirometric
As this study focused on the repeatability of aerobic energy
metabolism in fish fed a moderately restricted diet, appropriate ration
sizes, eliciting growth of brown trout in between maintenance and
ad libitum feeding rates, were predicted prior to the experiment
according to Elliott (Elliott, 1975a; Elliott, 1975b). At the time of
trial 1 (see Experimental protocol), fish in the present study were
fed average rations corresponding to 34.2% of ad libitum satiation
rations provided to brown trout of similar size by Elliott (Elliott,
1975a). At the time of trials 2, 3 and 4, average diets constituted
36.1, 38.2 and 38.6% of satiation rations, respectively. These rations
corresponded to 0.5–0.7% trout mass day–1in the present
experiment. In the studies by Elliott (Elliott, 1975a; Elliot, 1975b),
fish were fed the crustacean Gammarus pulex whereas fish in the
present study were fed the energetically more nutritious trout pellets.
Respirometry was performed using automated intermittent closed
respirometry. The experimental setup comprised six acrylic
respirometer chambers submerged in an ambient tank containing
115l fully aerated tap water at 15±0.2°C. This setup allowed for
simultaneous oxygen consumption measurements of six fish.
Water in the tank was recirculated through a UV steriliser to
minimise bacterial respiration. Each respirometer chamber was
equipped with two sets of gas-proof tubing. One set recirculated
water through the chamber past a galvanic oxygen electrode by
means of a pump, while the other set flushed the chamber at a
rate of 750mlmin–1by sucking in water from the ambient tank
and returning it through a tube elevated above the water surface.
Prior to the experiment, O2electrodes were calibrated against an
anoxic solution of sodium sulphite in 0.01moll–1sodium
tetraborate and fully aerated water from the ambient tank. Oxygen
saturation was assured by vigorous bubbling with atmospheric
air, and water oxygen tension (PwO2) was calculated as
PwO2FO2(PBAR–PH2O), where FO2is the fraction of oxygen in
the atmosphere (0.2095), PBARis the barometric pressure and PH2O
is the water vapour pressure at given temperature and salinity. The
flushing period replenished the respirometer chamber with fully
aerated water while at the same time removing metabolites. Total
volume of one respirometer chamber was 540ml. The recirculation
system was activated at all times whereas the flush system was
controlled by the computer and alternately turned on and off (i.e.
producing an open and closed phase, respectively). Changes in
PwO2due to fish respiration were continuously monitored at 1Hz
by AutoRespTMsoftware (LoligoSystems, Tjele, Denmark), but
only data for the closed phase of the cycle (referred to as the
measurement period) were used for later analysis.
To evaluate the repeatability of AMR, SMR and AAS, the MO2of
all fish was measured in four trials (mid December 2009, late January
2010, early March 2010 and early April 2010) over a period of
15weeks, incremented at 5week intervals. On each day of the
experiment, six fish were randomly caught by hand netting, lifted
out of the holding aquarium and individually placed in an oval 90l
tub containing 30l of fully aerated tap water at 15±0.8°C. Prior to
this, fish had not been fed for 23h. To measure AMR, fish in the
tub were chased by hand until signs of total exhaustion were evident
(i.e. the fish became unresponsive). This occurred within 2min of
chasing. The chasing protocol consistently produced short bursts of
very high activity and was believed to induce maximal oxygen
consumption rate as described by Cutts et al. (Cutts et al., 2002).
Following the 2min chase, fish were lifted out of the tub into the
air and immediately placed in the respirometer chambers where the
measurement period commenced after a maximum of 10s from
cessation of chasing. MO2was evaluated for 60s, after which the
chamber was flushed for 210s, allowing enough time to exchange
>99% of the water inside (Steffensen, 1989). This first measurement
of MO2(that was always higher than subsequent measurements) was
used as an estimate of AMR. Following measurements of AMR,
the software was reprogrammed and measurement periods were
increased to 105–120s depending on fish size. Periods of flush
remained the same. Half of the tank was covered with black plastic
sheeting to minimise disturbance and the system was left unattended
for the next 20h (until 08:00h the following morning). With a full
cycle of flush and measurement of 330s (maximum), this produced
over 218 measurements of MO2per fish. Through pilot experiments,
respiration from bacteria was found to be negligible over the short
THE JOURNAL OF EXPERIMENTAL BIOLOGY
periods of measurement and was disregarded in further analysis.
When experiments were terminated in the morning, fish were mildly
anaesthetised in benzocain and weighed to the nearest 0.1g before
being returned to the holding aquarium (which had been divided
with an additional mesh screen to avoid mixing of fish that had
already been, or were about to be, screened for MO2). After each
day, all experimental equipment was disassembled, disinfected and
thoroughly cleaned before new fish were introduced.
Two fish died during January measurements because of computer
failure, and one fish had to be excluded from analysis during March
measurements as a consequence of a faulty O2 electrode. This
reduced the sample size to 33 fish.
Data were analysed using Mathematica 5.2 (Wolfram Research, Inc.,
Champaign, IL, USA). Linear regressions between PwO2and time
were made for each period of measurement and slopes (k) derived
from these regressions were used to calculate oxygen consumption
by the fish according to the equation:
MO2 kVrespwO2, (1)
where MO2is the oxygen consumption rate (molmin–1), k is the
change in PwO2over time (kPamin–1), Vrespis the volume of the
respirometer minus the volume of fish (l) and wO2is the solubility
coefficient of oxygen in water at given temperature and salinity
(moll–1kPa–1) (Dejours, 1981). SMR was determined as the mean
of the 10 lowest MO2measurements, excluding outliers, over the
20h experimental period. To normalise data, all values of MO2and
body mass were log10-transformed prior to analysis. Mass-
independent data of MO2are expressed as residual metabolic rates
(rSMR, rAMR and rAAS) calculated from least-squares linear
regression of oxygen consumption rate on body mass. Residuals for
AAS were calculated from the relationship between MO2expressed
as AMR–SMR and body mass. Thus, fish with higher than expected
MO2have positive residuals and fish with lower than expected MO2
have negative residuals.
Growth rates were calculated as specific growth rate (SGR,
%day–1) according to the equation:
SGR [(lnMf– lnMi)t–1] ? 100, (2)
where Miand Mfare body mass (g) of fish at the start and end of
the experiment, respectively, and t is the time (days) it took the fish
to grow from Mito Mf.
Statistical analyses were performed in SigmaPlot®11 (Systat
Software Inc., San Jose, CA, USA). Repeatability of body mass and
T. Norin and H. Malte
residual metabolic rates was assessed from Kendall’s coefficient of
concordance (W) calculated according to Zar (Zar, 1996). Where
overall concordance proved significant (i.e. the null hypothesis of
independence were rejected), pairwise Spearman rank-order
correlations (rS) among variables were computed as suggested by
Legendre (Legendre, 2005) to assess the congruence of individual
trials. The level of significance was set to P<0.05. If not stated
otherwise, values presented are means ± s.e.m.
Metabolic rates, estimated from measurements of MO2as described
above, were divided into two groups: active and standard metabolic
rates (Fig.1). Minimum, maximum and mean MO2values from the
four trials are listed in Table1. Body mass of fish ranged from 20.7
to 45.7g (mean32.3±0.96g), 27.4 to 55.1g (mean40.9±1.13g),
37.7 to 64.9g (mean51.6±1.28g) and 38.4 to 68.2g (mean
54.0±1.39g) in trials 1, 2, 3 and 4, respectively.
Within trials, the two lines from regression equations describing
the relationship between SMR and AMR and body mass (Table2)
Body mass (g)
MO2 (µmol min–1)
Fig.1. Relationship between active and standard rate of oxygen
consumption (MO2,mol min–1) at 15°C and body mass (g) of brown trout
from the four trials. Red triangles, trial 1; blue circles, trial 2; green squares,
trial 3; pink diamonds, trial 4. Data are presented on double logarithmic
axes with fitted lines representing the power function MO2aMb, where a
and b are constants and M is body mass. For log10-transformed regression
equations, see Table 2. AMR, active metabolic rate; SMR, standard
Table1. Minimum, maximum and mean oxygen consumption rates (MO2, molmin–1) measured at 15°C in each of the four trials
Metabolic rateTrialN MinimumMaximumMean CV
AAS, absolute aerobic scope; AMR, active metabolic rate; CV, coefficient of variation (%); N, number of fish in each trial; SMR, standard metabolic rate.
Means are presented ±s.e.m.
THE JOURNAL OF EXPERIMENTAL BIOLOGY
1671Repeatability of metabolic rate in trout
significantly differed in slopes in trial 1 (ANCOVA, F1,6211.51,
P0.001) but not in trial 2 (ANCOVA, F1,623.82, P0.055), trial
3 (ANCOVA, F1,623.35, P0.072) or trial 4 (ANCOVA, F1,621.02,
P0.316). Elevation differed in all trials (ANCOVA, trial 2,
F1,635174.03, P<0.0001; trial 3, F1,633054.06, P<0.0001; trial 4,
F1,634089.61, P<0.0001), and AMR was always significantly
higher than SMR. Because slopes differed in trial 1, differences in
the elevation of data points between AMR and SMR were tested
by comparison of means from mass-standardised MO2values
[standardized to the mean body mass of fish in trial 1 according to
MO2(32.3g)MO2observed(M/32.3g)(1–b), where b is the slope for the
respective regression equation (AMR or SMR) listed in Table2].
This showed that AMR was significantly higher than SMR (t-test,
t6457.25, P<0.0001), as was expected.
Residual (body-mass-corrected) metabolic rates for the 33
surviving fish from trials 1, 2, 3 and 4, respectively, were calculated
from regression equations in Table2, and distributed as 20–/13+,
20–/13+, 19–/14+ and 18–/15+ for SMR; 18–/15+, 15–/18+,
17–/16+ and 18–/15+ for AMR; and 18–/15+, 17–/16+, 17–/16+
and 17–/16+ for AAS, with minus signs denoting the number of
fish with lower than expected metabolic rates and plus signs
denoting the number of fish with higher than expected metabolic
Because metabolism was estimated four times over 15weeks, six
combinations of either body mass or residual metabolic rates are
possible, presenting repeatability over three 5-week periods, two
10-week periods and one 15-week period. Individual body mass
was strongly correlated between all trials (Fig.2) and repeatability
was very high (overall W0.912, P<0.0001), with Spearman
correlation coefficients ranging from 0.786 to 0.973 for pairwise
combinations of trials (Table3).
Overall concordance coefficients for rSMR (W0.542, P<0.0001),
rAMR (W0.485, P0.0011) and rAAS (W0.517, P0.0004)
indicated significant associations amongst trials for all three
energetic parameters. To determine the influence of each of the trials
on the overall significance, pairwise Spearman rank-order
comparisons were performed. For rSMR (Fig.3), correlations
indicated significant repeatability in all trials 5weeks apart (Table3).
This significant relationship also persisted over the 10-week period
from trial 2 to trial 4 but not from trial 1 to trial 3. Over 15weeks,
no correlation existed between rSMR. The same pattern was
observed for rAMR (Fig.4), although repeatability at the significance
level of P<0.05 was absent in the first of the three 5-week periods
(Table3). rAAS was significantly repeatable across both 5 and
10weeks, although correlations were weaker for the 10-week
periods (Table3). As for rSMR and rAMR, no significant
repeatability of rAAS was found across 15 weeks. In other words,
repeatability of rSMR, rAMR and rAAS tended to gradually decline
across the entire experimental period (Fig.5).
Mean SGRs for trout across the various trial periods ranged from
0.13±0.01 to 0.62±0.02%day–1(Table4). For the full combination
of trials, we observed either a significant negative correlation
between individual SGR and rSMR at the start of the growing period
or no correlation at all (Table4), implying that fish with higher than
expected SMRs either grew less than or the same as conspecifics
with lower than expected SMRs.
In this study, the repeatability of body-mass-corrected SMR, AMR
and AAS gradually decreased over time, being highest over periods
of 5weeks (SMR, rS0.52–0.58; AMR, rS0.32–0.38; AAS,
rS0.39–0.43), decreasing over 10weeks (SMR, rS0.16–0.42;
AMR, rS0.25–0.35; AAS, rS0.35–0.36) and disappearing
altogether over 15weeks (SMR, rS0.09; AMR, rS0.23; AAS,
rS0.21). Gradual decline in repeatability of MO2is commonly found
in studies on birds, mammals and lizards (De Vera and Hayes, 1995;
Chappell et al., 1995; Chappell et al., 1996; Broggi et al., 2009),
although the magnitude of the decrease often is slight and the trait
Table2. Parameters from least-squares linear regression of log10-transformed oxygen consumption rates (MO2, molmin–1) versus
log10-transformed body mass (M, g), logMO2loga+blogM, for the four trials
Constants loga and b are presented ±s.e.m.
log Initial body mass (g)
184.108.40.206 220.127.116.11 1.8 1.9
log Final body mass (g)
Fig.2. Repeatability of body mass of brown trout for all combinations of
trials. Red circles, trial 1 vs 2; blue diamonds, 2 vs 3; black triangles, 3 vs
4; pink squares, 1 vs 3; green crosses, 2 vs 4; turquoise triangles, 1 vs 4.
See Table 3 for statistics.
THE JOURNAL OF EXPERIMENTAL BIOLOGY
under investigation still significantly repeatable. For fish, estimates
of repeatability often have been based on only two time points across
the experimental period (McCarthy, 2000; Reidy et al., 2000; Virani
and Rees, 2000; Maciak and Konarzewski, 2010) or, in those studies
including three or four time points, repeatability has been evaluated
as one overall measure (O’Connor et al., 2000; Cutts et al., 2001),
making an assessment of any gradual decline difficult. McCarthy
found repeatability of rSMR in Atlantic salmon (Salmo salar) to be
0.68 over a 16week period (McCarthy, 2000). For the spined loach
(Cobitis taenia), Maciak and Konarzewskifound repeatabilities of
rSMR of 0.68 and 0.73 in normoxia and hypoxia, respectively, over
a 5month period (Maciak and Konarzewski, 2010). These values
are at best comparable to repeatabilities found across the 5week
intervals in the present study, but not over longer time periods where
repeatability disappeared altogether. In a study by O’Connor et al.
(O’Connor et al., 2000), rSMR of Atlantic salmon was found to be
repeatable over a period of 8weeks (r0.40), even though the fish
had been starved in the middle of the period. This repeatability of
T. Norin and H. Malte
0.40 is similar to values from the present study across the same
Reidy et al. (Reidy et al., 2000) provide estimates of repeatability
of MO2in swimming Atlantic cod (Gadus morhua), but only include
values at swimming speeds below critical swimming speed (Ucrit),
which otherwise could have been analogous to AMR in the present
study. Nevertheless, these authors present a repeatability of MO2of
0.83 over 3months at a swimming speed of 50cms–1, the speed
closest to the mean Ucritof 58.4cms–1found in their study. This
value of repeatability seems quite high compared with repeatabilities
of AMR from our study, which at best reached 0.38 over a 5week
period. The high repeatability reported for the cod could be due to
the different, less conservative, mass-independent standardisation
procedure used, where MO2values for fish weighing between 0.67
and 2.66kg were adjusted to a standard mass of 1kg using a mass
exponent of 0.8.
A somewhat peculiar finding in the present study is the unusually
high exponents for scaling of SMR with body mass. Since the study
–0.20 –0.100 0.100.20
–0.20–0.1000.100.20 –0.20–0.1000.10 0.20
Final log rSMR
Initial log rSMR
Table3. Repeatability of body mass, residual standard and active metabolic rate, and residual absolute aerobic scope for pairwise
combinations of all trials
1 vs 2
2 vs 3
3 vs 4
1 vs 3
2 vs 4
1 vs 4
M, body mass; rAAS, residual absolute aerobic scope; rAMR, residual active metabolic rate; rSMR, residual standard metabolic rate.
NS, not significant.
Fig.3. Repeatability of residual (body-mass-corrected) standard metabolic rate (rSMR,molO2min–1) in brown trout for the three 5-week periods (A, trial 1
vs 2; B, 2 vs 3; C, 3 vs 4), two 10-week periods (D, 1 vs 3; E, 2 vs 4) and one 15-week period (F, 1 vs 4). See Table 3 for statistics.
THE JOURNAL OF EXPERIMENTAL BIOLOGY
1673 Repeatability of metabolic rate in trout
by Brett (Brett, 1965) on oxygen consumption of swimming sockeye
salmon (Oncorhynchus nerka), exponents for SMR have usually
been found to be lower than exponents for scaling of AMR.
However, high degrees of variation in scaling exponents for fish
have been acknowledged in several reviews. Clarke and Johnston
(Clarke and Johnston, 1999) report intraspecific exponents in the
range 0.40 to 1.29, both well below and above the general
interspecific exponent of 0.80 in their review. For larval fish
undertaking rapid growth, Giguère et al. (Giguère et al., 1988) report
exponents in the range of 0.65 to 1.69, whereas Post and Lee report
slopes in the range of 0.55 to 1.14 for larval and juvenile fish with
a more than tenfold difference in body mass (Post and Lee, 1996).
This often-observed high variation in exponents has recently led
several authors to suggest that no support for a universal exponent,
nor a universal model for its prediction, exists (Bokma, 2004;
Glazier, 2005; White et al., 2006; White et al., 2007). In relation to
the present study, we do not have a clear answer to why the scaling
exponents for SMR are so high, but it is possible that the elevation
is due to a combination of age (i.e. the fish still being in a stage of
ontogeny where growth is prevailing, despite the present feeding
regime) and reduced food availability, in conjunction with a small
difference between body masses within trials. This last factor has
been shown by Bokma (Bokma, 2004) to cause large variations in
exponents within species. In our study, mean body mass difference
within trials (difference between largest and smallest fish) was
27.4g. For such a mass difference, Bokma show exponents that vary
up to values of 1.5 (Bokma, 2004), as high as exponents found in
the present study. Reduced food availability as a cause of high
exponents is supported by the metabolic-level boundaries hypothesis,
which predicts that decreases in metabolic rates caused by low
energy availability should be accompanied by increases in scaling
exponents (Glazier, 2005). Finally, scaling exponents >1 for SMR
in salmonids, at similar temperatures and body masses as the present
study, have been reported for both brook trout (Salvelinus fontinalis)
(Beamish, 1964) and Atlantic salmon (Seppänen et al., 2010) and,
where MO2has been measured several times in the same individuals,
exponents commonly vary between trials (e.g. Cutts et al., 2001;
Seppänen et al., 2010). With the exception of the somewhat low
value of the scaling exponent for AMR in trial 3, these exponents
Initial log rAMR
Final log rAMR
Fig.4. Repeatability of residual (body-mass-corrected) active metabolic rate (rAMR,molO2min–1) in brown trout for the three 5-week periods (A, trial 1 vs 2;
B, 2 vs 3; C, 3 vs 4), two 10-week periods (D, 1 vs 3; E, 2 vs 4) and one 15-week period (F, 1 vs 4). See Table 3 for statistics.
Fig.5. Gradual decline in repeatability over time for rSMR (filled triangles,
—), rAMR (open circles, –··–) and rAAS (filled squares, – – ) in brown trout.
Asterisks denote lack of significance (cf. Table 3).
THE JOURNAL OF EXPERIMENTAL BIOLOGY
seem representative of the generally observed values for AMR [see
Glazier (Glazier, 2005) for a comprehensive review].
Even though repeatability of AMR in the present study showed
the same trend as SMR, declining over time, estimates of
repeatability of AMR were generally less consistent. As pointed out
by Chappell et al. (Chappell et al., 1995) inconsistency in (maximal)
performance may be the result of three factors, namely: (1)
equipment limitations, (2) failure to elicit maximal performance of
the experimental animal and (3) true physiological changes between
measurements. It is possible that individual fish responded
differently to the chasing protocol used to elicit maximal
performance in this study, introducing inconsistency into the
repeatability estimates of AMR (and thereby also AAS). This
potential pitfall was also emphasised by Reidy et al. (Reidy et al.,
1995), who compared different methods for eliciting exhaustion in
Atlantic cod. For measurements of SMR however, inconsistency
are most likely not introduced by either factor 1 or 2 and the decline
in repeatability in the long term (15weeks) should be interpreted
as a true physiological change.
The high repeatability of body mass found in this study
(rS0.79–0.97) is in agreement with the study by Maciak and
Konarzewski (Maciak and Konarzewski, 2010), who observed very
similar values of 0.98 and 0.99 over a 1month interval in spined
loach exposed to normoxia and hypoxia, respectively, as well as
long-term repeatability of 0.86 over an interval of 5months for a
combination of normoxic and hypoxic treatments. High repeatability
of body mass over long time periods has also been found for adult
birds (Broggi et al., 2009) (r0.74–0.81) and mammals (Szafranska
et al., 2007) (r0.93–0.95). In a study on lizards (van Berkum et
al., 1989), repeatability of body mass was found to be absent across
early ontogeny (age 2weeks to 13months), but present during later
life stages (age 2–13months). These findings could indicate that
repeatability of body mass does not so much depend on the time
frame over which it is estimated, but rather what part of an animals’
ontogeny is assessed; once you have grown big, you tend to remain
so, and vice versa. This of course calls for an answer to what the
ultimate factors may be that allow individuals within a species to
In Atlantic salmon, a link between SMR and dominance and
aggression has been demonstrated (Metcalfe et al., 1995; Cutts et
al., 1998; Metcalfe, 1998). Fish that have what seems to be an
energetic disadvantage, namely a high SMR and hence high cost
of living, can outcompete individuals of their own species, thereby
gaining preferential access to food through their high status in the
social hierarchy. A noteworthy finding in the present study is that
fish with high rSMRs grew less (or the same) than conspecifics
with lower rSMRs. In other words, no apparent advantage existed
in having relatively high SMRs. This somewhat contradicts the
findings in Atlantic salmon where the high relative SMR, found to
T. Norin and H. Malte
correlate with dominance (Metcalfe et al., 1995), also correlated
with growth rate (Metcalfe et al., 1992). However, as also pointed
out by Metcalfe et al. (Metcalfe et al., 1995), inflexibility in an
individuals’ SMR would be a disadvantage whenever food is not
so abundant as to offset the extra cost of maintaining a high relative
SMR. Because trout in the present study were fed a moderately
restricted diet throughout the experiment (compared with the normal
ad libitum diet in other repeatability studies), it is possible that the
benefits associated with high rSMRs disappeared, causing the social
hierarchy to break down and the repeatability to gradually diminish.
Such loss of repeatability in MO2is supported by the study of
O’Connor et al. (O’Connor et al., 2000), where a period of total
food deprivation caused the rank order of SMR in Atlantic salmon
to become inconsistent.
In the context of selection, temporal repeatability of a trait is often
used as an estimate of heritability [see Dohm (Dohm, 2002) for
discussion], i.e. the trait needs to be consistent long enough for
selection to have time to work on it. In relation to the present study,
this would infer that selection would not work on SMR, AMR or
AAS. It has often been discussed whether repeatabilities found in
laboratory settings can be transferred to animals in the wild (Rønning
et al., 2005; Labocha et al., 2004; Nespolo and Franco, 2007). If loss
of repeatability of rSMR (or aerobic metabolism in general) in the
present study is truly a consequence of the moderately restricted diet
as discussed before, this phenomenon of disintegration of
physiological performance would likely have a somewhat higher
resemblance to natural populations (compared with where an ad
libitum diet has been provided) because food in the wild will most
often be heterogeneously distributed, both temporally and spatially.
With this in mind, it would seem odd if selection did not influence
a physiological parameter as important as SMR, AMR or AAS, despite
its temporal instability. An alternative possibility, as also mentioned
by Rønning et al. (Rønning et al., 2005), is that selection instead would
work on the flexibility of a trait, giving animals with a relatively high
degree of phenotypic plasticity a selective advantage over conspecifics
with more restricted metabolic capacities whenever ecological
variability prevails. This was also recognised by Dohm, who stated
that repeatability estimates might be problematic in terms of providing
bounds for heritability when the trait under investigation is highly
plastic or context dependent (Dohm, 2002).
Ecologically, it is therefore likely that our study on repeatability
of aerobic performance, despite being a laboratory study, more
closely mimics natural conditions than studies where fish have had
unlimited access to food. Studies on correlations between metabolic
rate and growth in brown trout (Álvarez and Nicieza, 2005) and
between dominance and growth in Atlantic salmon (Harwood et al.,
2003) in the wild also suggest that shortage of food tends to dissolve
any relationships between traits, inferring no apparent advantage to
high SMR or dominance.
Table4. Mean specific growth rate (SGR, % day–1) across trials for the 33 fish and Pearson product-moment correlation coefficients (r) for
correlations of individual SGR and rSMR at the start of the growing period
1 to 2
2 to 3
3 to 4
1 to 3
2 to 4
1 to 4
SGRs are presented as means ± s.e.m. Negative r-values indicate a negative correlation between variables.
NS, not significant.
THE JOURNAL OF EXPERIMENTAL BIOLOGY
1675Repeatability of metabolic rate in trout Download full-text
In conclusion, we found that total body mass was highly stable
over a period of 15weeks, whereas rSMR, rAMR and rAAS did
not retain repeatability. In fact, we observed a gradual disappearance
of repeatability of both SMR and AMR, as well as AAS, across the
entire 15-week experimental period. SGR was either uncorrelated
or negatively correlated with rSMR, indicating that fish with high
rSMRs were at a disadvantage, at least under the present (slightly
restricted) feeding regime. We propose that the gradual
disappearance of repeatability of rSMR (and possibly overall
aerobic performance) is due to this feeding regime, and that such
a scenario, compared with an ad libitum feeding regime, more
closely resembles situations encountered by fish in the wild.
LIST OF SYMBOLS AND ABBREVIATIONS
absolute aerobic scope
active metabolic rate
fraction of oxygen in atmosphere
oxygen consumption rate
water vapour pressure
passive integrated transponder
partial pressure of oxygen in water
residual absolute aerobic scope
residual active metabolic rate
residual standard metabolic rate
specific growth rate
standard metabolic rate
critical swimming speed
volume of respirometer (minus volume of fish)
solubility coefficient of oxygen in water
This work was financed by the Danish Council for Independent Research, Natural
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