Effects of physiological state, mass change and diet on plasma metabolite profiles in the western sandpiper Calidris mauri
1 Department of Biological Sciences, Simon Fraser University, 8888
University Drive, Burnaby, V5A 1S6, Canada
2 Division of Biological Sciences, University of Montana, Missoula MT 59812,
USA
Author for correspondence (e-mail:
tdwillia{at}sfu.ca)
Accepted 14 December 2004
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Summary |
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Key words: metabolites, mass change, migration physiology, fattening, captive shorebirds
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Introduction |
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Several recent studies have suggested that measurement of plasma metabolite
concentrations might provide useful information on rates of mass change or
physiological state (e.g. feeding vs fasting;
Jenni-Eiermann and Jenni,
1994; Williams et al.,
1999
; Jenni and Schwilch,
2001
), patterns of fuel utilization
(Gannes, 2001
;
Jenni-Eiermann et al., 2002a
)
and inter-population or inter-site variation in fattening rates
(Schaub and Jenni, 2001
;
Guglielmo et al., 2002
).
Direct validation of the use of plasma metabolite profiles to predict mass
change in free-living birds will require independent assessment of fattening
rates, which is difficult because of the problems associated with multiple
recaptures of individuals, as outlined above (but see
Guglielmo et al., 2005
). Thus,
the biological interpretation of changes in plasma metabolite concentrations
in free-living individuals is currently based on relationships between
metabolite concentrations and rate of mass change established in captive
individuals (e.g. Jenni-Eiermann and
Jenni, 1994
; Williams et al.,
1999
). However, there have been relatively few thorough
validations of this technique, and it is unclear how the relationship between
metabolites and mass change is affected by captivity itself (see
Lambrechts et al., 1999
), or
factors such as variation in diet quality, or the rate of mass change itself.
For example, DeGraw et al.
(1979
) found that metabolite
concentrations in captive white-crowned sparrows (Zonotrichia
leucophrys) differed from those in free-living individuals. Diet quality
has been shown to influence fuel utilization and fattening rates in some
passerines (e.g. Bairlein,
1998
; Gannes,
2001
), but, to our knowledge, the effect of diet composition on
plasma metabolite concentrations has not yet been tested. This information is
important since it can indicate how robust mass-change-dependent variation in
metabolite levels will be in the context of even greater ecological
variability experienced by free-living birds.
In this paper, we examine the effects of rate and trajectory of mass change
and diet quality on plasma metabolite levels (triglyceride, glycerol, uric
acid and ß-OH-butyrate) in western sandpipers (Calidris mauri,
Cabanis), a long-distance migrating, Arctic-nesting shorebird. The specific
objectives of the study were (a) to experimentally manipulate rates of mass
change and mass trajectory, using high- and low-fat diets, to investigate
effects of diet quality on metabolite levels during different mass cycle
phases or physiological states (i.e. mass loss, mass gain, and stable mass),
and (b) to determine the effect of diet quality on the relationship between
plasma metabolite levels and rate of mass change. Finally, since there is
often marked individual variability in plasma metabolite levels, even for a
given mass or physiological state (e.g.
Guglielmo et al., 2002;
Ydenberg et al., 2002
) we also
investigated whether measures of body condition or plasma metabolite levels at
time of capture (i.e. in free-living individuals) predicted variation in these
parameters in the same birds in captivity.
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Materials and methods |
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Two different diets were used in this experiment. Our standard diet was 1.5
mm (width) pelleted Clark's Fry trout chow (Moore-Clark, Vancouver, Canada);
the same diet was used in our previous studies
(Williams et al., 1999;
Egeler et al., 2003
) and is
similar to that used in other studies
(Jenni-Eiermann et al.,
2002b
). This high-fat, high-protein diet, referred to hereafter as
the high-fat diet, is primarily fish meal-based and consists of 47% protein,
18% fat, 2% fiber, 9% ash and 16.5% nitrogen-free extract (NFE), with a total
energy content of 18.2 kJ g-1. The second diet used was Hikari
Cichlid Baby 2.0 mm (diameter) pellet (Hikari USA, Hayward, California, USA),
a low-fat, high-protein diet, referred to hereafter as the low-fat diet. This
is primarily fish meal-based and consists of 35% protein, 4% fat, 5% fiber, 9%
ash and 37% NFE, with a total energy content of 16.2 kJ g-1 (this
second, low-fat diet more closely approximates to the fat content of natural
prey items; see Egeler and Williams,
2000
).
General experimental protocol
Daily food consumption (g bird-1 day-1) was measured
as the combined amount for all birds in each experimental group throughout the
experiment (see below for final sample sizes). All birds were weighed weekly
(±0.1 g), and birds were weighed every other day during periods of mass
loss and gain, to closely monitor mass change. Any individuals with body mass
<22 g (lean mass in this species;
Guglielmo and Williams, 2003)
were separated out and excluded from the experiment. These individuals were
held in a separate pen on the high-fat diet and if they recuperated to a mass
>22 g they were used in subsequent experiments. Birds were caught a few at
a time (4-5 birds per experimental group) and blood sampled indoors to allow
the remaining individuals to return to normal foraging activity between
disturbances; birds returned to foraging within 1 min of the researcher
vacating the aviary. Total disturbance time, the number of minutes between the
first disturbance of birds in a cage and the final bird being caught and
sampled in that cage, averaged 23.7±14.9 min. Bleed time, between
capture and blood sampling of each individual, averaged 7.6±3.7 min,
and 90% of the bleed times were less than 12 min. All birds were blood sampled
and mass recorded between 10.00 h and 12.00 h PST (Pacific standard time; so
time of day, or time since last meal was not a confounding factor in our
study, see Discussion). Birds were blood sampled via brachial
venipuncture with a 26.5 gauge needle and blood (up to 300 µl) was
collected with heparinized capillary tubes and centrifuged at 1800
g for 10 min. Plasma was drawn off using heparanized capillary
tubes and was stored at -20°C until assayed.
Diet experiments
Experimental work was conducted over several months beginning in October
2002. Ad libitum food was defined as 12.5 g bird-1
day-1, based on preliminary experiments where average food
consumption was 6.6±1.7 g bird-1 day-1. Birds
were divided into two experimental groups (low-fat and high-fat diets),
equally divided in terms of age (juveniles, N=36, caught in August
2002, and yearlings, N=4, caught in 2001) and capture site (Boundary
Bay and Robert's Bank). Birds were transitioned from the high- to low-fat diet
over a 2 week period. In Trial 1, both the high-fat and low-fat groups were
cycled through mass loss (food restriction) and mass gain (refeeding). Blood
samples were taken in the middle of the `Loss' phase (day -7 relative to the
end of the experiment, see Fig.
1) and 2 days after refeeding during the `Gain' phase (day -2,
Fig. 1). Mass loss was achieved
by food restriction, during which time birds received 85% of the average food
consumption (g bird-1 day-1) for that group. To ensure
continued mass loss, food was further restricted to 80% of average consumption
during the final 2 days of the Loss phase. At the end of the mass Gain phase,
once body mass stabilized, birds were blood sampled again during ad
libitum food consumption (`Adlib' phase), and the birds were left on that
diet for at least 2 weeks after the last blood sampling before being switched
to the alternate diet and used in Trial 2. The same cycle of mass loss/gain
was then repeated on the alternate diet (Trial 2) so that each individual
served as its own control. This random order design accounts for possible time
of year effects, given that a minimum of 1 month separated the two cycles
because of recovery and transition periods. This experimental design also
controls for possible effects of experience (i.e. birds having previously been
through a loss-gain cycle), because half of the birds experienced diet
manipulation for the first time on the high-fat diet and the other half
experienced the manipulation for the first time on the low-fat diet. Some
birds (N=7) in the first group transitioned to the low-fat diet were
unable to stabilize body mass on that diet and were isolated from the rest of
the birds. As soon as their body mass did stabilize they were run through the
mass cycle on the low-fat diet as a separate group. There was no significant
difference between these two groups of birds in the rate of mass change during
either the Adlib or Loss phases (P>0.7, both phases). The lighter
birds that were separated achieved a marginally lower rate of mass gain than
the original group (F1,13=5.04, P=0.045);
however, there was no significant difference in the percentage of mass gain or
loss achieved between these two groups (P>0.1, both parameters).
Therefore, the results of these two groups were pooled together and analyzed
as a single set of birds on the low-fat diet in Trial 1. Data were pooled
between trials and analyzed for each diet treatment (low- or high-fat). Final
sample sizes were N=19 for birds cycled through a loss-gain cycle on
the low-fat diet, N=28 for on the high-fat diet and N=15 for
the mass cycle on both diets.
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Plasma metabolite assays
Free plasma glycerol and triglyceride were assayed using a sequential color
endpoint assay (Trinder reagent A and B, respectively, Sigma-Aldrich Canada,
Oakville, Ontario, Canada), using 5 µl of sample with 240 µl and 60
µl of reagents A and B respectively, with a reading taken at 540 nm after
10 min of incubation at 37°C after the addition of each reagent.
Triglyceride concentration (mmol l-1) was calculated by subtracting
free glycerol from total glycerol. Uric acid was assayed via color endpoint
assay (WAKO USA, Richmond, Virginia, USA), using 5 µl of sample with 300
µl of reagent, with a reading taken at 550 nm after 10 min of incubation at
37°C. Assays were run in 400 µl flat-bottom 96-well microplates (NUNC,
Denmark) and read with a microplate spectrophotometer (Biotek 340EL). Each
plate was run with a standard curve based on a serial dilution of 2.54 mmol
glycerol (Sigma-Aldrich Canada, Oakville, Ontario, Canada) for the
triglyceride-glycerol assay and 2.97 mmol uric acid (prepared in our
laboratory) for the uric acid assays. Each plate also included a 19-day-old
hen plasma pool used to calculate inter-assay coefficient of variation.
Inter-assay coefficients of variation were 3.1% (N=11), 7.0%
(N=11), 6.1% (N=4) and 9.4% (N=5), and intra-assay
coefficients of variation were 3.2% (N=6), 3.9% (N=6) and
3.1% (N=17) for glycerol, triglyceride and uric acid respectively.
ß-OH-butyrate was analyzed by one of us (C.G.G.) via kinetic
endpoint assay (Guglielmo et al.,
2005).
Statistical analysis
All four metabolite levels were non-normally distributed, so we transformed
the data using ln(metabolite) to approximate normality and transformed data
were used in all analyses. Owing to the very short period of mass gain, we
calculated Mass over the first two days of mass gain (between day -4
and -2). However, the period of mass loss was more prolonged. We therefore
calculated
Mass over the 3-day period prior to the Loss blood sample
(i.e. between day -10 and day -7, Fig.
1). We considered the shorter intervals of mass gain and loss (2-3
days) as more biologically relevant since they approximate average flight and
stop-over times for migrating western sandpipers
(Warnock and Bishop,
1998
).
The relationship between the rate of mass change (Mass; g
day-1) and residual metabolite values (controlling for covariates
as necessary, see below) was tested for each metabolite independently on a
pooled data set including individuals and in all three mass cycle phases,
using a linear mixed model with repeated measures to account for repetition of
individuals with diet as a main effect. Testing the mass change-metabolite
relationship for all phases of the loss-gain cycle with a single model allowed
for maximization of range of mass change. In each case if the
Mass*diet interaction term was significant the relationship
between
Mass and metabolite concentration was tested separately by
diet; otherwise the interaction term was dropped from the model. All
statistical analyses were carried out using SAS
(SAS Institute, 1990
).
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Results |
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For the pooled data, the lowest mass reached during Loss and the final mass reached during Gain were both lower for birds on the low-fat diet than for birds on the high-fat diet (lowest mass, day -4, t43=-3.40, P<0.01; final mass, day 0, t41=-2.26, P<0.05; Fig. 1); however, initial mass was independent of diet (t42=-1.11, P>0.2; Fig. 1B). As we had anticipated, mass cycle phase (gain, loss, ad lib) had a highly significant effect on rate and trajectory of mass change (low-fat diet, F2,16=75.2, P<0.0001; high-fat diet, F2,21=32.3, P<0.0001; Table 2). For both diets, all pair-wise contrasts of mass change between mass cycle phases were highly significant (P<0.01 in all cases). However, there was no effect of diet on rate of mass change for either the Loss, Gain or Adlib phases of mass change (P>0.60 in all cases; Table 2). Mean mass change was significantly different from zero for the Loss and Gain phases, but not when birds were on Adlib food (Table 2).
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For each diet, size-corrected body mass (controlling for tarsus length) was positively correlated between all three mass cycle phases (low-fat: r>0.5, P<0.02; high-fat: r>0.4, P<0.04 all cases), i.e. the heaviest individual during Loss would also be the heaviest individual during Gain. In contrast, none of the four metabolite values were correlated within individuals between different phases of mass change on either diet (P>0.07, all cases).
Effects of bleed time, handling time and body mass on metabolite levels
Plasma glycerol levels were independent of plasma levels of the other three
measured metabolites (P>0.1 for each comparison with the three
other metabolites), so this metabolite was analyzed separately. There was a
positive correlation between triglyceride and uric acid levels
(r=0.47, P<0.0001), and both triglyceride and uric acid
were negatively correlated with ß-OH-butyrate (triglyceride,
r=-0.47, P<0.0001; uric acid, r=-0.56,
P<0.0001). Plasma triglyceride levels were positively related to
bleed time (triglyceride: F1,205=6.64, P<0.02,
b=0.016), whereas glycerol, uric acid, and ß-OH-butyrate levels
were independent of bleed time (P>0.1, in all cases). In addition,
plasma triglyceride and uric acid were negatively related to total disturbance
time (triglyceride, F1,172=5.70, P<0.02,
b=-0.007; uric acid: F1,171=16.90,
P<0.0001, b=-0.011), while ß-OH-butyrate levels were
positively related to total disturbance time (F1,158=7.75,
P<0.01, b=0.009). Plasma triglyceride and uric acid were
positively related to body mass (triglyceride,
F1,205=56.68, P<0.0001, b=0.069; uric
acid, F1,203=3.26, P=0.07, m=0.018)
whereas ß-OH-butyrate was negatively related to body mass
(F1,178=12.97, P<0.001, b=-0.041).
For subsequent analyses, of triglyceride, uric acid and ß-OH-butyrate
residual metabolite values were calculated from a regression analysis
including mass, disturbance time or bleed time as factors where appropriate.
Glycerol was independent of all three factors (body mass, bleed time, and
total disturbance time, P>0.3, in all cases) and log transformed
plasma glycerol concentrations will be referred to as glycerol levels
hereafter.
Effect of mass cycle phase and diet on plasma metabolite levels
On the low-fat diet, there was an overall phase effect for all four
metabolite values, i.e. metabolite levels varied significantly in relation to
phase of mass change (repeated measures ANOVA, P<0.001 in all
cases; Fig. 2). In contrast, on
the high-fat diet, there was a significant overall phase effect for glycerol
and uric acid (P<0.002 in both cases), but triglyceride and
ß-OH-butyrate levels were independent of phase of mass change
(P>0.1; Fig. 2). Birds losing mass had higher glycerol levels than birds in both Gain and Ad
Lib phases of mass change, on both diets (P<0.05), with no
difference in glycerol levels between Gain and Adlib phases
(Fig. 2B). Similarly, on the
low fat diet, birds losing mass had lower levels of uric acid and higher
levels of ß-OH-butyrate than birds in both Gain and Adlib phases
(P<0.005; Fig.
2C,D). On the high fat diet, birds losing mass also had lower uric
acid levels than in the Adlib phase (P<0.001), but uric acid
levels were only marginally different between Loss and Gain phases
(P=0.08; Fig. 2C).
There were few significant differences in metabolite levels between Gain and
Adlib phases of mass change, except that triglyceride levels were higher
during the Adlib phase on the high-fat diet (P<0.05;
Fig. 2A).
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Comparing metabolite levels between diets, within each phase of mass change there were no significant differences in metabolite levels between the low- and high-fat diets for the Loss phase (P>0.1; all four metabolites). For both the Gain and Adlib phases of mass change, birds on the low-fat diet had higher triglyceride and uric acid levels and lower ß-OH-butyrate levels than those on the high-fat diet (P<0.001 in all cases), but glycerol levels were independent of diet (P>0.4 in both cases; Fig. 2).
Relationship between metabolites and rate of mass change
For triglyceride and glycerol levels, the Mass*diet
interaction was not significant (P>0.09), so it was dropped from
the model. Triglyceride levels were independent of the rate of mass change
(F1,41=2.02, P>0.1;
Fig. 3A). However, there was a
significant effect of diet for this relationship with birds on the low-fat
diet having higher triglyceride levels than birds on the high-fat diet
(F1,27=83.63, P<0.001), consistent with the
analysis of mean metabolite levels for each phase. Glycerol levels were
negatively related to the rate of mass change
(F1,40=14.59, P<0.005, b=-0.10) and
this relationship was independent of diet (F1,24=0.19,
P>0.6; Fig. 3B).
For uric acid and ß-OH-butyrate, there was a significant
Mass*diet interaction term (uric acid:
F1,32=6.02, P<0.02; ß-OH-butyrate:
F1,28=25.64, P<0.001); therefore we analyzed
each diet separately for these metabolites. Uric acid was positively related
to the rate of mass change for birds on the low-fat diet
(F1,23=10.02, P<0.005, b=0.12);
however, uric acid levels were independent of the rate of mass change on the
high-fat diet (F1,32=0.83, P>0.4;
Fig. 3C). ß-OH-butyrate
was negatively related to the rate of mass change on both diets (low-fat:
F1,15=73.81, P<0.001, b=-0.30; high-fat:
F1,27=5.13, P=0.03, b=-0.06;
Fig. 3D).
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Comparison of mass and metabolite levels in free-living and captive birds
There was no correlation between size-corrected body mass and any
metabolite values between birds at the time of original capture and the
Pre-treatment phase (P>0.2, all parameters). Similarly, there was
no correlation for these parameters between time of capture and birds in the
Wild and Gain phases on either diet (P>0.1, all cases). Birds
after transition into captivity, given an ad libitum high-fat diet,
prior to diet manipulation (Pre-treatment) had lower uric acid levels and
higher glycerol and ß-OH-butyrate levels than they did at the time of
original capture (glycerol: t35=2.54, P<0.02;
uric acid: t31=-4.04, P<0.0005;
ß-OH-butyrate: t17=4.48, P<0.0005).
However, triglyceride levels did not differ between pre-treatment and time of
capture (t33=-1.17, P>0.2). Birds actively
gaining mass (Gain) on the same high-fat diet had higher values of
ß-OH-butyrate and lower values of the other three metabolites than at the
time of capture (triglyceride: t25=-5.83,
P<0.0001; glycerol: t26=-2.82,
P<0.01; uric acid: t23=-5.11,
P<0.0001; ß-OH-butyrate: t15=5.19,
P<0.0001). In contrast, birds during the Gain phase on the low-fat
diet did not differ from the original time of capture in any of the metabolite
levels (glycerol: P>0.05; all others: P>0.4), i.e. the
plasma metabolite profiles on the low-fat diet were more similar to those of
free-living, migratory birds.
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Discussion |
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There are several factors that could have complicated our experimental
design, e.g. time of year and the effects of molt. Jenni-Eiermann et al.
(2002b) showed that in a
congeneric shorebird, the red knot, there is a naturally occurring cycle in
fattening captivity, which is reflected in changes in plasma metabolite
concentrations. However, in our experiment birds went through the mass change
cycle on the two different diets in random order. In addition, our entire
experiment took place between October and January, which falls within a stable
mass phase in the natural cycle reported in the study of Jenni-Eiermann et al.
(2002b
). We are, therefore,
confident that time of year effects do not confound our results. Plasma
triglyceride levels have been shown to vary with timing of molt
(Jenni-Eiermann and Jenni,
1996
; Totzke and Bairlein,
1998
; Jenni-Eiermann et al.,
2002b
). However, our study (October to January) occurred almost
exclusively outside of the periods of body molt for the western sandpiper. No
individuals in our study experienced wing molt. Body molt was observed in a
few of the individuals, however, only toward the end of the second trial
(January), so we are confident that molt does not confound our results.
Plasma metabolite concentrations and physiological state
Numerous studies in captive passerines have shown that plasma metabolite
concentrations reflect the physiological state of a bird in relation to
fattening or fasting (DeGraw et al.,
1979; Jenni-Eiermann and
Jenni, 1994
; Totzke and
Bairlein, 1998
). Jenni-Eiermann et al.
(2002b
) showed that certain
plasma metabolites (triglyceride and ß-OH-butyrate) reflect seasonally
changing metabolic processes among different life cycle stages (molt,
migration, oversumering) in captive red knot (with birds on a similar diet to
our high-fat diet). Our study confirms some of the results of Jenni-Eiermann
et al. (2002b
;
ß-OH-butyrate), and extends their results for other metabolites
(glycerol), but there are also differences between their study and ours for
uric acid and triglyceride. In both the red knot and the western sandpiper
periods of mass gain are characterized by low ß-OH-butyrate levels,
relative to phases of mass loss. However, this relationship between mass gain
and ß-OH-butyrate was only evident on the low-fat diet in our study: on
the high-fat diet ß-OH-butyrate did not differ for birds losing or
gaining mass, even though absolute rate of mass gain was the same as for the
low-fat diet. In western sandpipers we found higher uric acid levels
associated with mass gain, but again this was only significant on the low fat
diet. Jenni-Eiermann et al.
(2002b
) found no significant
change in uric acid levels across different life stages, despite birds showing
clear periods of body mass increase.
In their red knot study, Jenni-Eiermann et al.
(2002b) reported triglyceride
including free glycerol (rather than reporting free glycerol separately; see
Williams et al., 1999
) so
their triglyceride results are not directly comparable to our study. However,
Jenni-Eiermann et al. (2002b
)
concluded that life-stages with body mass gain were also associated with
increased plasma triglyceride levels, reflecting increased turnover of lipids.
In contrast, correcting for free glycerol, we found no difference in plasma
triglyceride levels between phases of mass gain and loss on the low-fat diets,
and again on the high-fat diet triglyceride levels did not vary with any phase
of mass change. Free glycerol was higher during mass loss than during mass
gain, consistent with results from some passerine studies
(Jenni-Eiermann and Jenni,
1994
) and this was the only metabolite in our study for which this
relationship was independent of diet. Glycerol has traditionally been assumed
to increase during mass loss (i.e. when birds are in negative energy balance)
because it is released into the plasma during lipolysis of triglycerides in
adipose tissue (Ramenofsky,
1990
). Recently Guglielmo et al.
(2005
) suggested that glycerol
might demonstrate a U-shaped relationship with body mass, such that it was
also high in birds with very high rates of mass gain, but we found no evidence
to support this in our study.
The effect of diet composition on plasma metabolite concentrations of avian
migrants has not, to our knowledge, been tested before, although Bairlein
(1998) tested for effects of
diet lipid and protein content on rates of migratory fattening in the
passerine garden warbler Sylvia borin. Bairlein
(1998
) measured fattening on a
more exhaustive suite of 13 different diets and the results offer insight into
our study. In our study, the diets varied dramatically in lipid content (18%
vs 4%) but protein content was only slightly higher for the high-fat
diet (47% vs 35%). Bairlein
(1998
) demonstrated that the
fattening rate achieved by the warblers depended on the percentage protein and
the relative proportion of protein to fat, as well as the percentage lipid in
the diet. The warblers achieved the highest rate of fattening on a diet
consisting of 5% protein and 10% fat (5:10), which is lower in protein but
similar in fat to their natural diet (15:10). Furthermore, the warblers
achieved a higher rate of fattening on the 5:10 diet than on a diet of
identical protein content but higher fat content (5:20). Similarly, in our
study, the birds on the diet lower in both fat and protein (
4:35
vs
18:47) had plasma metabolite concentrations indicative of
higher fattening (although we cannot rule out an effect of the different NFE
content of our two diets).
Relationship between metabolite levels and rate of mass change
The relationship between the rate of mass change and plasma
concentrations of three of the four metabolites tested (triglyceride,
ß-OH-butyrate and uric acid) was also dependent on diet composition in
our study. For ß-OH-butyrate we found a negative relationship between
metabolite level and rate of mass change on both diets, even though the slope
of this relationship differed among diets. The same relationship has been
reported previously for several passerines
(Jenni-Eiermann and Jenni,
1994; Jenni and Schwilch,
2001
) and the red knot
(Jenni-Eiermann et al.,
2002b
). Fewer studies have reported on the relationship between
mass change and uric acid, but Jenni-Eiermann and Jenni
(1994
) also found a positive
relationship, as we found on our low-fat diet. However, this result contrasts
with that of Jenni-Eiermann et al.
(2002b
) in which the uric acid
levels of red knots were negatively related to the rate of mass change over a
period of 5-7 days. The reasons for this difference are not clear; although in
our study and that of Jenni-Eiermann et al.
(2002b
) birds were fed trout
chow, it is possible these differed in protein content, which is known to
affect uric acid levels (Jenni and
Jenni-Eiermann, 1998
). Furthermore, elevated uric acid levels can
be associated with both protein catabolism and high protein turnover during
hyperphagia and fattening (Jenni-Eiermann
and Jenni, 1994
; Jenni-Eiermann and Jenni, 1998). Therefore,
differential representation of range of mass change (i.e. loss or gain) in the
two studies is a possible explanation for the positive versus negative
relationship between uric acid and rate of mass change detected by our study
and that of Jenni-Eiermann et al.
(2002b
).
We also detected a significant negative relationship between the rate of
mass change and plasma glycerol in captive western sandpipers, which is
consistent with the relationship previously demonstrated in this species by
Williams et al. (1999). As
with data on phases of mass change, this relationship was independent of diet.
We did not detect any relationship between plasma triglyceride levels and mass
change in the present study, which contrasts with the similar study of the
same species by Williams et al.
(1999
). Nevertheless, Williams
et al. (1999
) failed to detect
a relationship between triglyceride and mass change over 7 days in western
sandpipers, whereas a significant positive relationship between plasma
metabolite concentrations and the rate of mass change was detected over 1-2
days, i.e. the relationship between mass change and triglyceride was less
robust than that for glycerol and mass change. Williams et al.
(1999
) also generated mass
loss over 1-2 days via food removal, not food restriction, so
metabolic responses might have reflected short-term starvation, with much
higher rates of mass loss than in the present study. Conversely, the sampling
periods of 7 days that were tested by Williams et al.
(1999
) were under natural mass
change conditions and reflected less extreme mean rates of mass change
(± S.E.M.; gain, 0.13±0.08 g
day-1; loss, -0.36±0.08 g day-1, cf. rates in
Table 2) than those experienced
by the birds on the experimentally induced mass cycle in the present study
(see Table 1). Nevertheless,
Jenni-Eiermann et al. (2002b
)
also found no relationship between triglycerides and body mass change in their
study of captive red knot. These inconsistent results for triglyceride in
captive sandpipers contrast with generally consistent positive relationships
between triglycerides and mass change in passerines (e.g.
Jenni-Eiermann and Jenni,
1994
; Jenni and Schwilch,
2001
). This difference might be due, in part, to the fact that
some studies report total triglyceride including free glycerol whereas others
calculate triglyceride as total glycerol - free glycerol; free glycerol can
represent a substantial, and highly variable, proportion of total glycerol. It
is interesting that the relationship between plasma triglyceride and mass
change is the most inconsistent of all the metabolites in experimental studies
of captive birds, whereas plasma triglyceride appears to be the most robust
indicator of mass change in studies of free-living birds (e.g.
Schaub and Jenni, 2001
;
Guglielmo et al., 2002
,
2005
; D. S., unpublished
data). Our study suggests that one reason for these inconsistencies might be
effects of different quality diets used in experimental studies: high-fat,
trout chow diets typically used in shorebird studies generally appear to
result in very different plasma metabolite profiles, and different
relationships between metabolites and physiological state or mass change, than
do low-fat diets (which more closely approximate natural shorebird diets).
Plasma metabolite profiles of western sandpipers gaining mass on the low-fat
diet were more consistent with data from field studies and, in our study, were
more similar to those of free-living birds at the time of capture.
In conclusion, at least on the low-fat diet (4%), which more closely
represents the average lipid content of marine invertebrate prey targeted by
western sandpipers, our study confirms that measurement of plasma metabolites
can provide robust information on physiological state (gain, loss) and the
rate of mass change in free-living shorebirds caught only once, as has been
demonstrated for passerines (e.g. Jenni
and Schwilch, 2001; although we should stress that these results
are only valid for birds that have been feeding for several hours prior to
sampling). Nevertheless, in migratory species where the lipid composition of
the natural diet can be high, or highly variable (e.g. passerines feeding on
fruit, or sandpipers feeding on crab or fish spawn), researchers should be
cogniscent of effects of diet composition for certain metabolites. Future
studies should consider possible confounding effects of experimental diets in
validating, or comparing, plasma metabolite profiles in relation to mass
change for free-living versus captive birds, particularly for
non-passerines.
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Acknowledgments |
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Footnotes |
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References |
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Alerstam, T. and Lindstrom, A. (1990). Optimal bird migration: the relative importance of time, energy, and safety. In Bird Migration: Physiology and Ecophysiology (ed. E. Gwinner), pp. 331-351. Berlin: Springer-Verlag.
Baker, A. J., Gonzalez, P. M., Piersma, T., Niles, L. J., de Lima Serrano do Nascimento, I., Atkinson, P. W., Clark, N. A., Minton, C. D. T., Peck, M. K. and Aarts, G. (2003). Rapid population decline in red knots: fitness consequences of decreased refuelling rates and late arrival in Delaware Bay. Proc. R. Soc. Lond. B 271,875 -882.
Bairlein, F. (1998). The effect of diet composition on migratory fuelling in Garden Warblers Sylvia borin. J. Avian Biol. 29,546 -551.
Brown, S., Hickey, C., Harrington, B. and Gill, R. (2001). The United States Shorebird Conservation Plan, 2nd edn. Manomet: Manomet Center for Conservation Sciences.
DeGraw, W. A., Kern, M. D. and King, J. R. (1979). Seasonal changes in the blood composition of captive and free-living white-crowned sparrows. J. Comp. Physiol. 129,151 -162.
Dunn, E. H. (2000). Temporal and spatial patterns in daily mass gain of Magnolia Warblers during migratory stopover. Auk 117,12 -21.
Egeler, O. and Williams, T. D. (2000). Seasonal, age, and sex-related variation in fatty-acid composition of depot fat in relation to migration in Western Sandpipers. Auk 117,110 -119.
Egeler, O., Seaman, D. and Williams, T. D. (2003). The influence of diet on fatty acid composition of depot fat in Western Sandpipers. Auk 120,337 -345.
Gannes, L. Z. (2001). Comparative fuel use of migrating passerines: effects of fat stores, migration distance and diet. Auk 118,665 -677.
Guglielmo, C. G. and Williams, T. D. (2003). Phenotypic flexibility of body composition in relation to migratory state, age and sex in the Western Sandpiper (Calidris mauri). Physiol. Biochem. Zool. 76, 84-98.[CrossRef][Medline]
Guglielmo, C. G., O'Hara, P. D. and Williams, T. D. (2002). Extrinsic and intrinsic sources of variation in plasma lipid metabolites of free-living western sandpipers (Calidris mauri). Auk 119,437 -445.
Guglielmo, C. G., Cerasale, D. J. and Eldermire, C. (2005). A field validation of plasma metabolite profiling to assess refueling performance of migratory birds. Physiol. Biochem. Zool. In press
Jenni, L. and Jenni-Eiermann, S. (1998). Fuel supply and metabolic constraints in migrating birds. J. Avian. Biol. 29,521 -528.
Jenni, L. and Schwilch, R. (2001). Plasma metabolite levels indicate change in body mass in reed warblers Acrocephalus scirpaceus. Avian Sci. 1, 55-65.
Jenni-Eiermann, S. and Jenni, L. (1994). Plasma metabolite levels predict individual body-mass changes in a small long-distance migrant, the garden warbler. Auk 112,888 -899.
Jenni-Eiermann, S. and Jenni, L. (1996). Metabolic differences between the postbreeding, moulting and migratory periods in feeding and fasting passerine birds. Funct. Ecol. 1, 62-72.
Jenni-Eiermann S., Jenni L., Kvist A., Lindstrom A., Piersma T. and Visser, G. H. (2002a). Fuel use and metabolic response to endurance exercise: a wind tunnel study of a long-distance migrant shorebird. J. Exp. Biol. 205,2453 -2460.[Medline]
Jenni-Eiermann, S., Jenni, L. and Piersma, T. (2002b). Plasma metabolites reflect seasonally changing metabolic processes in a long-distance migrant shorebird (Calidris canutus). Zoology 105,239 -246.
Lambrechts, M. M., Perret, P., Maistre, M. and Blondel, J. (1999). Do experiments with captive non-domesticated animals make sense without population field studies? A case study with blue tits' breeding time. Proc. R. Soc. Lond. B 266, 1311.[CrossRef]
Ramenofsky, M. (1990). Fat storage and fat metabolism in relation to migration. In Bird Migration: Physiology and Ecophysiology (ed. E. Gwinner), pp.214 -231. Berlin: Springer-Verlag.
SAS Institute (1990). SAS/STAT User's Guide, Release 6.03 Edition. Cary, NC, SAS Institute.
Schaub, M., and Jenni, L. (2001). Variation in fuelling rates among sites, days and individuals in migrating passerine birds. Funct. Ecol. 15,584 -594.[CrossRef]
Totzke, U. and Bairlein, F. (1998). The body mass cycle of the migratory garden warbler (Sylvia borin) is associated with changes in basal plasma metabolite levels. Comp. Biochem. Physiol. 121A,127 -133.
Warnock, N. and Bishop, M. A. (1998). Spring stopover ecology of migrant Western Sandpipers. Condor 100,456 -467.
Williams, T. D., Guglielmo, C. G., Egeler, O. and Martyniuk, C. J. (1999). Plasma lipid metabolites provide information on mass change over several days in captive Western Sandpipers. Auk 116,994 -1000.
Ydenberg, R. C., Butler, R. W., Lank, D. B., Guglielmo, C. G., Lemon, M. and Wolf, N. (2002). Trade-offs, condition dependence, and stopover site selection by migrating sandpipers. J. Avian Biol. 33,47 -55.[CrossRef]