Behavioral Ecology Vol. 13 No. 6: 766-775
© 2002 International Society for Behavioral Ecology
Effects of feeding time constraints on body mass regulation and energy expenditure in wintering dunlin (Calidris alpina)
a Cypress Grove Research Center, Audubon Canyon Ranch, PO Box 808, Marshall, CA 94940, USA b Department of Animal Science, University of California, Davis, CA 95616, USA
Address correspondence to J.P. Kelly. E-mail: kellyjp{at}svn.net.
Received 4 July 2001; revised 5 February 2002; accepted 19 February 2002.
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMETHODSRESULTSDISCUSSIONREFERENCES |
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We examined the effects of time-restricted feeding on regulation of body mass and activity energy expenditure in captive wintering dunlin (Calidris alpina) held in outdoor aviaries at Tomales Bay, California. In the first of two experiments, we compared birds under 24 h : 24 h (fasting : ad libitum feeding) food restriction with controls under continuous ad libitum feeding. In the second experiment, we compared birds under 24 h : 6 h : 12 h : 6 h (fasting : ad libitum : fasting : ad libitum) food restriction with birds under 24 h : 24 h food restriction. We estimated total energy expended on activities from daily mass balance using an additive model based on measures of gross energy intake, thermoregulation, basal metabolism, and a sensitivity analysis of gross utilization efficiency and energy density of reserve body tissue. Dunlin under 24 h : 24 h food restriction overcompensated for body mass lost while fasting, increasing their body mass relative to controls fed ad libitum. Dunlin under 24 h : 6 h : 12 h : 6 h food restriction were unable to recover body mass lost during the first fasting day. When allowed to feed, food-restricted birds reduced the amount of energy spent on being active and increased food intake and energy storage relative to controls, but when forced to fast, they increased their activity energy expenditure. These patterns suggest winter body mass regulation consistent with the behaviors of free-living dunlin in winter.
Key words: body mass regulation, Calidris alpina, dunlins, energy balance, food availability, metabolism, shorebirds, winter storms.
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONREFERENCES |
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Animals that depend on daily foraging in habitats that become unsuitable during storms include ground-foraging animals in areas prone to sudden snowfall (Goodson et al., 1991
; Neuhaus et al.,
1999; Rogers and Smith,
1993); birds that prey on flying or active insects subject to
periods of inactivity during extreme weather
(Grubb, 1978;
Murphy, 1987); shorebirds
wintering in temperate estuaries where storms, rainfall, wind, high tides, and
freshwater runoff interact to influence thermal and foraging conditions
(Burger, 1984;
Evans, 1976;
Kelly, 2001); and other
animals that winter at high latitudes and experience sharp reductions in
foraging time and intake rate during periods of bad weather
(Cuthill and Houston, 1997).
In such environments, individuals can improve their chances of survival by
maintaining energy stores in the form of fat and protein that can be mobilized
to provide fasting endurance during periods of extreme cold or reduced food
availability (Davidson, 1981;
Evans and Smith, 1975;
Lindström et al., 2000).
However, a trade-off exists between the costs and benefits of fattening
(Lima, 1986;
McNamara and Houston, 1990;
Witter and Cuthill, 1993).
Deposition of fat reduces starvation risk by increasing fasting endurance, but
it increases the energetic costs of flight, requires additional foraging time
and associated exposure to predators, and reduces a bird's ability to evade
predator attacks (Witter and Cuthill,
1993; Witter et al.,
1994). Thus, unless food supply or digestion rate precludes
additional intake (Kersten and Visser,
1996; Wiener,
1992), birds should increase energy stores when food availability
declines or becomes less predictable and reduce energy stores as foraging
conditions improve (Lima,
1986). Empirical support for this prediction has been found in
greenfinches (Carduelis chloris;
Ekman and Hake, 1990), great
tits (Parus major, Bednekoff and
Krebs, 1995), European starling (Sturnus vulgaris;
Witter et al., 1995), and
other passerines (Rogers and Smith,
1993). In passerines, the extent of body mass gain associated with
reductions in feeding time or food availability also depends on nutritional
state (Ekman and Hake, 1990;
Lehikoinen, 1987;
Lilliendahl et al., 1996).
Published studies have not determined the extent to which nonpasserines
regulate energy stores under varying levels of feeding restriction or
uncertainty. As energy stores decline, additional feeding restriction presents
a greater threat, and starvation risk becomes more immediate. Therefore, the
extent of regulatory change in body mass should reflect an interaction between
the influences of external feeding conditions and individual state (internal
energy stores). Wintering shorebirds are particularly suitable for testing
these ideas because of their dynamic foraging environments
(Burger, 1984) and high
metabolic rates (Kersten and Piersma,
1987).
Kelly et al. (2002) found
evidence for regulation of body mass in dunlins (Calidris alpina)
based on proximal influences related to winter storms (e.g., rainfall, wind,
temperature), but did not address specifically the effects of feeding
restrictions imposed by winter weather. Dugan et al.
(1981) and Davidson
(1981) provided evidence
suggesting the recovery of winter body mass to previous levels after periods
of negative energy balance in gray plover (Pluvialis squatarola) and
redshank (Tringa totanus). Similarly, oystercatchers (Haematopus
ostralegus) forced to forage for shorter periods of time increased food
intake to a level that maintained the same mean consumption over a longer
period (Swennen et al., 1989).
However, adaptive change in regulated level of body mass in response to
changing feeding conditions has not been demonstrated in shorebirds.
Animals could regulate energy stores through a variety of behavioral and
physiological mechanisms (Bautista et al.,
1998) that involve increasing food intake (energy supply) or
decreasing metabolic rate (energy demand). For example, changing the extent of
energy expended on a particular activity or changing the choice of activity
among alternatives that differ in energetic cost could increase energy stores
by increasing the supply side or by decreasing the demand side of energy
balance. Some potential changes in behavior or physiology suggest costs
(energetic or nonenergetic) related to increased chance of starvation,
predation, reproductive failure, or other fitness risks that may outweigh
their use in regulating energy stores. In wintering shorebirds, reduction of
resting metabolism through temporary (e.g., nightly) hypothermia is unlikely
because it would interfere with active foraging and predator evasion that
occur both day and night (Dodd and
Colwell, 1996; Mouritsen,
1992,
1993;
Page and Whitacre, 1975).
Slight reductions in resting metabolism through reduction of lean mass might
be possible in shorebirds, but substantial energy savings would require
trade-offs related to loss of structural tissue needed for normal life
(Klaassen and Biebach, 1994;
Piersma and Lindström,
1997). For example, loss of muscle mass has been found to
correlate with a decline in flight performance and increased predation risk
(Veasey et al., 2000).
Conserving energy through behavioral thermoregulation is important in
shorebirds (Wiersma and Piersma,
1994), which generally encounter thermostatic costs of 50-60% or
more of daily expenditure (Kelly,
2000; Piersma and Morrison,
1994; Piersma et al.,
1991). However, shorebirds that use open mudflats are probably not
able to increase behavioral thermoregulation to achieve additional energy
savings (Kersten and Piersma,
1987). Therefore, the most likely mechanisms for regulating energy
stores in shorebirds should involve changes in the overall rate of energy
expended on activities and/or rate of energy intake, up to the limits on
intake rate set by digestion or food supply
(Kersten and Visser, 1996).
Changing either of these rates will alter the net rate of energy gain per unit
time (including feeding and nonfeeding time), which has been considered the
most effective currency in modeling foraging decisions made under time
constraints (early models used net rate while foraging;
Cuthill and Houston, 1997;
Schoener, 1971;
Ydenberg and Hurd, 1998).
In this study, we tested the prediction that shorebirds regulate body mass
by increasing energy stores when available feeding time is reduced and
decreasing energy stores when feeding time is extended. In addition, we tested
the prediction that the extent of regulatory change in body mass depends on
the individual's state of internal energy stores. Dunlins were suitable
subjects for this work because they exhibit non-migratory midwinter flights in
response to deteriorating feeding conditions
(Warnock et al., 1995),
suggesting that both activity expenditure and storage of reserve energy may be
important in avoiding winter starvation. In two experiments involving captive
dunlins, we manipulated available feeding time and assessed daily changes in
food intake and body mass. Finally, to examine mechanisms of energy balance
involved in body mass regulation, we measured thermoregulatory and resting
metabolic costs and, based on daily mass balance, estimated activity levels
associated with differences in feeding regime.
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METHODS |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONREFERENCES |
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Captive birds
Wintering dunlins were captured in mist nets in November and December of 1997 (n = 14) and 1998 (n = 17), on Tomales Bay, California, USA, and held in outdoor aviaries (5.5 m x 6 m x 2.5 m high) on the east shore of the bay. Conditions of captivity were approved by the University of California Protocol for Animal Use and Care (no. 7481) and are described in detail in Kelly (2000
). Food was provided ad
libitum (Aquamax Fry Starter 5D00, Purina Mills, Inc., St. Louis, MO, USA; 56%
protein, 18% fat, 9% carbohydrate; pellet diam < 1.5 mm), except during
periods of imposed fasting. We allowed dunlins to adjust to captivity for at
least 5 weeks before we began experimental work, and they maintained stable
body masses slightly above capture weights. We captured each bird daily,
approximately 1 h after dark, using a 0.8 m-diam, fine-mesh hoop net, and
measured body mass with a digital electronic balance calibrated to 0.01 g. We
conducted feeding-restriction experiments from 11 January to 13 March 1998,
and monitored daily change in body mass under ad libitum feeding and natural
weather conditions during both winters. We released all dunlins by mid-March
each year, before spring migration.
Experimental design
We examined the effects of feeding regime on body mass regulation by
measuring body mass change in food-restricted birds (n = 7) relative
to controls fed ad libitum (n = 7). Dunlins were assigned randomly to
treatment groups housed in separate aviaries, with the constraint that groups
were closely balanced by age and sex (individuals in groups A and B,
respectively: juvenile males = 3, 3; juvenile females = 3, 2; adult males = 1,
1; adult females = 0, 1). Daily proportional changes in body mass under ad
libitum feeding conditions did not differ over the course of the study between
juveniles and adults (F1,679 = 0.13, p > .71)
or by sex (F1,679 < 0.01, p > .97).
Davidson (1984) found that
fat mass and lean mass in wintering dunlins were metabolized at constant rates
for at least 24 h after capture, which was the maximum duration of fasting in
our study, and that fat levels were adequate to sustain substantially longer
fasts. This indicates that mass loss during a day of fasting reflects use of
available energy stores, rather than emergency use of energy in structural
tissues, because the early stages of starvation should be marked by a
breakpoint in rates of fat and lean mass loss
(van der Meer and Piersma,
1994). The following considerations further suggest that fasting
birds did not deplete their energy stores during our study: (1) Fat mass at
capture in wintering dunlin at Bodega Harbor, 12 km northwest of Tomales Bay
(4-6 g; Ruiz, 1987) was
comparable to levels measured at capture by Davidson (4.9-5.4 g); (2) dunlins
that had adjusted to captivity in our study maintained body mass slightly
above capture weights; (3) dunlins measured by Davidson lost less than half of
their fat mass over 24 h; (4) rate of body mass loss by fasting dunlin in our
study (0.23 g/h) was less than observed by Davidson (0.34-0.40 g/h after
initial period of water mass loss). Therefore, we used proportional change in
individual body mass as an index of changes in stored energy imposed by
temporary periods of fasting, assuming that fat and lean mass were metabolized
and deposited at constant rates.
Dramatic changes in winter weather, tides, and runoff can make shorebird
prey unavailable or foraging impossible for one or more tidal cycles
(Kelly, 2001;
Nordby and Zedler, 1991).
Under such conditions, the extent of time available for feeding within a day
may predict starvation risk more effectively than subtler changes in the mean
or variance of prey availability or the timing of feeding sessions. Therefore,
we used extent of feeding time under fixed schedules of fasting and ad libitum
feeding as a relevant measure of food restriction experienced by wintering
shorebirds in tidal habitats. When feeding time was restricted, feeding
opportunities were also less predictable because they could be anticipated
only after a period of adjustment.
In the first of two experiments to test for body mass regulation in birds exposed to changes in available feeding time, we conducted two 8-day comparisons of 24 h : 24 h (fasting: ad libitum)-restricted birds with ad libitum fed controls (Figure 1A). During 3 weeks of ad libitum feeding before the experiment, daily body mass change did not differ between groups (F1,291 = 0.014, p = .91), was highly correlated between groups (r = .88, n = 21, p < .001; Figure 1A), and in most cases (95%), was less than 0.017 x body mass. After each test period, birds were returned to ad libitum feeding conditions for at least 7 days. Before the second test period, body mass in food-restricted birds had recovered to pretest levels (F1,12 = 0.88, p > .36) and did not differ significantly from controls (F1,12 = 0.34, p > .56). To allow for self comparisons of individual body mass responses, we switched treatment and control groups in the second test.
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We standardized body mass changes among individuals by using proportional
change in individual mean pretest body mass as the dependent variable, based
on 7-day means before the first period of restricted feeding. Differences in
body mass between groups were evaluated during a 4-day response period
immediately after ad libitum feeding was restored. This allowed birds to
respond to manipulation without a limit on food intake, while minimizing the
possibility of birds perceiving a return to predictable daily feeding
(Ekman and Hake, 1990). We
also evaluated daily differences in body mass change between groups during
each test.
In the second experiment, we compared body mass changes under 24 h : 24 h food restriction with more severe 24 h : 6 h : 12 h : 6 h (fasting : ad libitum feeding : fasting : ad libitum feeding) food restriction (Figure 1B). During the week before the experiment, groups did not differ significantly in body mass (F1,12 = 0.07, p = .79) or daily change in body mass (F1,84 = 0.06, p = .79); daily changes were significantly correlated between groups (r = .89, n = 7, p < .01) and were usually (95%) less than 0.017 x body mass. After the 1-week pretest period, treatment and control groups were both placed under 24 h : 24 h food restriction for 6 days. The test group (group B) was then further restricted with a 24 h : 6 h : 12 h : 6 h feeding schedule for an additional 6 days, while controls remained under 24 h : 24 h food restriction. After the final 6-day test period, both groups were returned to ad libitum feeding.
State dependence
To examine the influence of body condition on body mass regulation, we
measured the effects of size of energy stores on daily change in body mass
within individuals, using repeated-measures regression. We estimated the size
of energy stores for each dunlin as the difference in individual body mass
(M) from the expected population mean body mass under ad libitum
feeding conditions, adjusted for the structural size of the individual. This
estimate is equivalent to the residual value for each individual from
repeated-measures regression of M (g) on length (mm) of exposed
culmen (B) and wing chord (W; F = 203.6, n
= 1,380 bird-days, p < .001; R2 = .85) and is
expressed in the following equation:
 | (1) |
Energetic costs of activity
To examine the influence of feeding regime on daily energetic costs of
being active, we estimated activity energy expenditure from the equation:
 | (2) |
). This model
assumes that the energetic costs of being active are additive with other
energy costs. If heat produced as a by-product of being active substitutes
partially for thermoregulatory costs
(Bruinzeel and Piersma, 1998;
Webster and Weathers, 1990),
estimated energetic costs of activity represent only the unsubstituted portion
of activity energy expenditure. The model also assumes that HI does not
substitute for TR. The extent to which substitution for thermoregulatory
requirements might occur in birds is not clear
(Dawson and O'Connor, 1996).
Therefore, we considered the possible effects of substitution in our
evaluation of the results.
Evidence suggests that change in body mass of wintering shorebirds reflects
a constant protein:fat ratio, up to a breakpoint in use of energy reserves
when fat stores approach depletion
(Lindström et al., 2000;
van der Meer and Piersma,
1994). Therefore, we assumed a constant RE on fasting and
refeeding days (but evaluated the results across a range of possible RE
values). On fasting days, HI drops out of the model (GEI = 0). If the heat
increment associated with the catabolism of stored tissue is not substituted
for TR, the model would overestimate the energetic costs of activity in
fasting birds by 5-10% of the decrease in energy stores
(Blaxter, 1989). Therefore, we
considered this difference in evaluating the results. We measured food intake
as the difference between dry mass equivalents of food supplied and dry mass
of food removed each day (using an Excalibur dehydrator at 50°C) and
calculated GEI by multiplying food intake by the energy density of the dry
food (23.95 kJ/g; Griffin M, Purina Mills, Inc., personal communication).
We used a Campbell Scientific 21X microdata logger to record ambient and
operative temperature and wind speed inside the aviary, based on sensor output
intervals of 60 s averaged every 0.5 h. Wind speed was measured with a
Thornthwaite model 901-LED sensitive cup anemometer at dunlin height. Ambient
air temperature was measured with a shaded copper-constantan thermocouple also
mounted near the ground. We used four unheated copper dunlin taxidermic mounts
(constructed by Georg Nehls), faced in different directions, to estimate
operative temperature (Bakken,
1976; Bakken and Gates,
1975) and calculated standard operative temperature by adjusting
for the effects of wind speed (Bakken,
1990). We determined TR and BMR using standard operative
temperatures measured in the aviaries and measurements of resting metabolic
rate for wintering dunlin on Tomales Bay (see below).
Metabolism measurements
We used an open-circuit respirometer to determine resting metabolic rates
of 17 wintering dunlins captured on Tomales Bay. Before measurements, birds
were held for at least 2 weeks in the outdoor aviary in conditions described
above. Birds were fasted for 4 h before measurement. From 21 November to 22
December 1998, we measured oxygen consumption (ml [g/h]) in postabsorptive
individuals at night (1900-0400 h). In addition, we conducted some daytime
measurements to investigate whether dunlins exhibit circadian differences in
resting metabolism. Dunlins were held individually in 4-l metabolic chambers,
in complete darkness and stable ambient temperature (Ta)
for 1-4 h before metabolic determinations were made. We calculated oxygen
consumption from the change in fractional O2 concentration of dry,
CO2-free air passed through the metabolic chambers, measured with
an Applied Electrochemistry model S-3A O2 analyzer. Details of the
respirometry system design and methods are presented in Weathers and Greene
(1998) and Kelly
(2000).
No more than two determinations of resting metabolic rate were made on each
individual on a given day. After measurements were made, birds were returned
to ad libitum food and water in the aviary for at least 24 h. Each individual
was used in two to seven metabolic determinations
(
i = 4.6; n =
78), conducted at ambient temperatures from 0.4° to 34.0°C. We
calculated rates of metabolic heat production using a conversion of 20.1 kJ/l
O2 consumed. We analyzed results using repeated-measures regression
to allow for random differences among individual dunlins. Oxygen consumption
(ml [g/h]) predicted by Ta did not differ significantly
between juveniles (n = 9) and adults (n = 8;
F1,75 = 0.02, p > .88) or between males
(n = 7) and females (n = 10; F1,75 =
2.74, p > .10). Therefore, dunlins of different age and sex were
pooled in the analysis.
Statistical analyses
We used analysis of variance and linear and quadratic regression to model
body mass change, energetic costs of being active, and metabolic rates, with
repeated measures to account for the random effects of individual dunlins
(SYSTAT 8.0, SPSS Inc.). Residuals did not differ significantly from normality
(p > .05), and variances were stable. Residuals of proportional
weight change were not significantly autocorrelated among days when feeding
was possible (|r| < 0.15, p > .05, power
> 0.90), so we considered sequential daily measurements to be independent.
We minimized the possibility of pseudoreplication by testing effects
simultaneously in adjacent aviaries of identical design and thermal
conditions, randomly assigning individuals to groups, switching control and
treatment groups between trials so that individual differences contributed
equally to each effect, and testing for nonsignificance of pretreatment
differences and temporal autocorrelation
(Hurlbert, 1984). In the
second experiment, only a single trial was conducted. Post-hoc pairwise
comparisons represent t tests and were considered significant if
Bonferroni adjustments indicated an experimentwise error rate of p
< .05. We also used t tests to examine differences between
regression slopes, with degrees of freedom (subscript) based on independent
estimates of body mass change in each group (individuals x days).
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RESULTS |
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24 h : 24 h food restriction
In the first experiment, dunlins responded to food restriction in four ways. First, birds lost body mass on fasting days relative to control birds (F1,24 = 115.2, p < .001) and relative to pretrial body mass (F1,38 = 23.1, p < .001; panels 1 and 2, Figure 1A). Second, on the ad libitum refeeding day after the first day of fasting in each trial, birds recouped those losses relative to controls (F1,23 = 0.29, p = .60), although they did not regain pretrial levels (F1,37 = 20.0, p < .001; test days 2 and 16, Figure 1A). Third, on the subsequent 3 refeeding days in each trial, birds overcompensated for losses incurred on alternate fasting days, increasing their peak (refeeding) body mass, on average, by a factor of 0.018/day (SE = 0.003) over all fasting and refeeding days relative to controls (t138 = 4.50, p < .001). These increases reflected "true fattening" indicated by a proportional increase in minimum (fasting) body mass (Lehikoinen, 1987
) of
0.019/day (SE = 0.003) over all fasting and refeeding days. Finally, during
the 4-day period after birds were returned to continuous ad libitum conditions
identical to those before restriction, they maintained significantly more mass
than controls (F1,24 = 82.1, p < .001) and
exceeded the body mass exhibited during pretrial conditions
(F1,24 = 83.2, p < .001). After 5 days of
restored ad libitum feeding, birds had reduced their body mass to pretest
levels (F1,24 = 1.24, p = .28) and did not differ
significantly from controls (F1,24 = 1.25, p =
.28).
24 h : 6 h : 12 h : 6 h food restriction
In the second experiment, the responses of birds to 24 h : 24 h food
restriction were similar to those observed in the first experiment (panel 3,
Figure 1B). Dunlins (in control
and treatment groups) lost body mass on alternate fasting days relative to
pretest mass (F1,26 = 1136, p < .001) and
overcompensated for those loses on intermittent 24 h : 24 h refeeding days,
increasing their peak (refeeding) body mass, on average, by a factor of
0.011/day (SE = 0.001) over all fasting and refeeding days. True fattening was
indicated by proportional increases in minimum (fasting) body mass of
0.004/day (SE = 0.001) over all fasting and refeeding days. On the last
refeeding day of pretreatment 24 h : 24 h restriction (test day 0,
Figure 1B), the cumulative
proportional increase in body mass was nearly identical between groups
(
= 0.051 for both groups, F
< 0.001, p > .99).
Dunlins responded differently under 24 h : 6 h : 12 h : 6 h restriction (panel 4, Figure 1B). Birds lost body mass on fasting days but undercompensated for those losses on intermittent 6 h : 12 h : 6 h refeeding days, reducing their mass at an average rate of 0.011 x body mass/day (SE = 0.001, F1,40 = 43.1, p < .001), or 0.016 x body mass/day relative to 24 h : 24 h-restricted controls (SE = 0.002; t12 = 2.37, p < .05). On the last refeeding day of the test period, body masses were significantly lower than controls (F1,12 = 14.8, p < .01; test day 6, Figure 1B). When returned to unrestricted ad libitum conditions, birds previously under 24 h : 6 h : 12 h : 6 h restriction increased their body mass for 3 days at a linear rate of 0.033 x body mass/day (F1,20 = 60.80, p < .001), exceeding levels in the control group, which declined by a factor of 0.006/day (F1,19 = 9.44, p < .01; test days 7-9, Figure 1B). Body mass then declined, converging toward controls. After 3 additional days, the two groups did not differ (F1,12 = 0.81, p = .39).
State dependence
The extent of daily body mass change depended significantly on individual
state of energy stores. On average, birds fed ad libitum exhibited daily
compensatory gains and losses of 0.20 g for each gram deviation from expected
body mass, revealed by repeated-measures regression of daily mass change on
individual energy stores (F1,1371 = 174.4, p <
.001; Figure 2A). This trend
accounted for 30% of daily body mass variation within individuals; nonlinear
(quadratic and power) functions did not improve the fit.
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On refeeding days during 24 h : 24 h food restriction (panels 1 and 2, Figure 1A), birds gained significantly more body mass (0.56 g gained per gram lost; F1,82 = 33.2, p < .001) than predicted by trends under continuous ad libitum conditions (separate variance t14 = 3.01, p < .01; Figure 2A). On these days, individuals gained more mass when their energy stores were smaller than when their stores were greater, and energy stores accounted for 84% of body mass change within individuals (Figure 2A). However, energy stores before and after 24 h : 24 h restriction were strongly correlated among individuals (r = .76, n = 14, p < 0.002), indicating that state-dependent responses did not eliminate differences among individual states (Figure 2B).
Differential responses of individuals were further revealed by increased variation in body mass change when feeding time constraints were applied. In the first experiment, variance among birds in both groups increased significantly under 24 h : 24 h restriction relative to previous ad libitum conditions, although only one group increased relative to controls (F tests, p < .05; Figure 1A). Neither group increased their variance when returned to ad libitum feeding (p > .05). In the second experiment, variation among individual responses increased significantly under 24 h : 24 h restriction (in both groups), and again under 24 h : 6 h : 12 h : 6 restriction (F tests, p < .05; Figure 1B). When birds were returned to ad libitum feeding, individual variation increased further among 24 h : 24 h controls (F test, p < .05), but not among 24 h : 6 h : 12 h : 6 h-restricted birds (p > .05).
Food consumption
Change in food consumption was an important mechanism contributing to daily
body mass regulation. Dunlins fed on a 24 h : 24 h schedule consumed more
energy on days when food was available than did birds fed ad libitum
(F1,14 = 23.6, p < .001). However, over all
fasting and refeeding days, birds on the 24 h : 24 h schedule consumed less
energy than birds fed ad libitum (F1,13 = 4.85, p
< .05). Therefore, differences in gross energy intake alone are
insufficient to explain the increases in body mass under restricted feeding.
The amount of energy consumed per hour of available feeding time by 24 h : 6 h
: 12 h : 6 h-restricted birds was not significantly different from the amount
consumed by 24 h : 24 h-restricted birds (F1,4 = 4.5,
p > .05), but the amount of energy consumed per day was
significantly less (F1,4 = 119.1, p < .001),
resulting in body mass declines associated with an apparent upper limit on
intake rate.
Energetic costs of activity
Food-restricted dunlins increased their body mass by reducing the energetic
costs of being active (Equation 2) while increasing food intake. Measurements
of resting metabolism (BMR and TR) used to estimate activity energy
expenditure indicated that the lower critical temperature of the thermal
neutral zone in wintering dunlins was 19.8°C
(Kelly, 2000). Mean BMR
calculated using each bird's mean metabolic rate within the thermal neutral
zone was 1.017 kJ (g/day) (SE = 0.024, n = 17). Below 19.8°C,
metabolism increased at a rate of 0.046 kJ (g/day) (r2 =
.93, F16,22 = 17.03, p < .001). Daytime
measurements did not differ from nighttime measurements, suggesting that
resting metabolic rates may not reflect active and passive phases in the
circadian cycle (Kelly,
2000).
On days when feeding was allowed, 24 h : 24 h-restricted birds not only
consumed significantly more energy but were also significantly less active
energetically than controls fed ad libitum. Consequently, net energy
efficiency (gain per unit expended) was higher on refeeding days, and net rate
of energy gain increased enough to overcompensate for energy costs incurred
over all fasting and refeeding days. The reduction in energetic costs of being
active was significant across all likely levels of gross utilization
efficiency and RE (Figure 3;
p < .05). Similarly, on refeeding days, 24 h : 6 h : 12 h : 6
h-restricted birds reduced the energetic costs of being active to levels
significantly below those of 24 h : 24 h-restricted birds (p <
.05). However, net efficiency on 6 h : 12 h : 6 h refeeding days did not
significantly improve (p = .24), and rate of energy intake
undercompensated for energy costs over all fasting and refeeding days. If HI
substitutes completely for TR, gross utilization efficiency would probably be
near 0.75 (Castro et al.,
1989), which would not affect the significance of the results
(Figure 3).
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On days when food was not available, ranks for the amount of energy
expended on being active were reversed among the different feeding regimes.
The 24 h : 24 h-restricted birds spent significantly more energy on being
active than birds forced to fast for a day after 3 or more weeks of continuous
ad libitum feeding (Figure 3;
p < .05). Also on fasting days, birds restricted to the more
severe 24 h : 6 h : 12 h : 6 h feeding schedule spent significantly more
energy being active than birds on a 24 h : 24 h feeding regime (p
< 0.05). If the heat increment associated with catabolism of stored tissue
does not substitute for TR, the difference in energetic costs of being active
on fasting days would be overestimated by 5-10%
(Blaxter, 1989; see Methods),
but this would not affect the significance of the results
(Figure 3).
Plots of the energetic costs of being active relative to GEI revealed differences in energy expenditure as a mechanism in the regulation of energy stores (Figure 4). In general, the amount of energy spent being active declined at lower rates of energy intake. When forced to fast for a day after 3 or more weeks of ad libitum feeding (GEI = 0), control birds further reduced the amount of energy spent on being active. Food-restricted birds also expended less energy being active when rate of energy intake was lower but increased their activity energy expenditure on alternating days when food was not available (Figure 4). Quadratic models, calculated over the range of gross utilization efficiencies and RE, provided a better fit to the data than linear models (F tests, p < .10). Random variation among individuals (tested with repeated measures) had virtually no influence on y-intercepts or on linear or quadratic components of the slopes, and accounting for this variation did not improve the fit over simpler models (F tests, p > .42).
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|
DISCUSSION |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONREFERENCES |
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Dunlins under feeding-time constraints exhibited changes in daily mass predicted by models of optimal body mass regulation (Lima, 1986
;
McNamara and Houston, 1990;
Witter and Cuthill, 1993) by
altering both food intake and energy expended on activities. Most previous
models have focused on net energy intake rate as the appropriate currency for
evaluating body mass change under time constraints and have attributed
increases in body mass to higher rates of food intake (e.g.,
Lehikoinen, 1987;
Lima, 1986;
McNamara et al., 1994;
Pravosudov and Lucas, 2001;
Schoener, 1971). However, some
authors have found, as we have, that reduced activity and metabolic
expenditure contribute substantially to daily gains in body mass
(Bednekoff and Krebs, 1995;
Cuthill et al., 2000).
Although dunlins under feeding restriction consumed less food energy than
controls, they managed to increase their body mass, indicating increases in
both net intake efficiency and net rate of gain (over all feeding and
nonfeeding periods). As animals increase their foraging rate, net efficiency
normally declines because the costs of searching for prey increase at a faster
rate than energy intake (Ydenberg and
Hurd, 1998). Therefore, free-living birds foraging under time
constraints may increase their net rate of gain but are unlikely to increase
net efficiency, unless they can overcome additional energetic costs of
foraging by reducing the energetic costs of other (nonforaging) activities or
adopt a different foraging method that improves both net efficiency and net
rate of return. In addition, increases in foraging rate or reductions of
energy expenditure must be weighed against opportunity costs associated with
activities such as social interactions, body maintenance, or predator
avoidance and nonenergetic costs such as increased exposure to predators while
foraging.
Although dunlins experienced increases in feeding unpredictability, the
effects of variance or unpredictability per se could not be distinguished from
differences in the extent of available feeding time. Therefore, the particular
role of unpredictability as a proximal influence on body mass regulation is
not clear and should be considered cautiously
(Cuthill and Houston, 1997;
Witter et al., 1995). However,
in small animals such as dunlins, which store only 1.5-4 days of reserve
energy (Castro et al., 1992;
Piersma et al., 1994) and
forage according to tidal routines, starvation risk imposed by episodic winter
storms might be more effectively predicted by the extent of feeding time
during the next low tide than by longer term assessments involving the
variance or predictability of feeding periods.
Dunlins compensated quickly for major losses in body mass. They also
anticipated future loss by increasing their mass above previous levels over
several fasting—refeeding cycles. When feeding was no longer restricted,
birds continued to anticipate future losses, increasing their body mass for a
few days, at which point they reduced their mass to pre-restriction levels.
The results are consistent with theoretical predictions that birds may
temporarily alter their body mass for 1-2 days in response to short-term
shifts in starvation (or predation) risk
(Lima, 1986). In dynamic
environments, loss of fitness associated with sudden unpredicted changes in
starvation risk should lead to selection that favors body mass regulation over
such short time scales, especially in animals with high metabolic rates
relative to available energy stores. Unfortunately, changes in body condition
at such short time scales can be difficult to detect in field studies,
especially for shorebirds. For example, the apparent recovery of body mass in
gray plover up to but not above previously regulated levels after a period of
wind-induced negative energy balance
(Dugan et al., 1981) was based
on banding weights of birds measured only once and may have failed to detect
short-term differences within individuals.
Dunlin body mass increased when continuous feeding was possible on
alternate days, but, under more severe (24 h : 6 h : 12 h : 6 h) restriction,
energy intake per hour remained the same and body mass declined, suggesting
that intake available for regulating body mass may have been limited by
digestive rate (Kersten and Visser,
1996; Wiener,
1992). Other explanations for intake limits, involving food
access, social dominance, acquisition rates, or handling time
(Goss-Custard, 1984), are
unlikely given feeding conditions in the aviaries. Alternatively, 24 h : 6 h :
12 h : 6 h-restricted birds might not have predicted a further increase in
starvation risk because of untested factors such as shorter mean duration of
fasting periods or more frequent shifts between feeding and nonfeeding periods
(from two to four per 2-day cycle). We know of no evidence that digestive
constraints occur in free-living dunlins. Further work is needed to elucidate
thresholds in the timing, frequency, and duration of feeding periods required
for the regulation of energy stores in wintering shorebirds.
State dependence
Individual dunlins exhibited stronger state dependence (greater mass gain
per gram lost) under restricted feeding than under ad libitum feeding. That
mass-dependent energy gains also depend, differentially, on feeding time
constraint was further indicated by increased variance in net gain when
feeding time was restricted. These results suggest an interaction between
internal and external sources of energy. However, we could not distinguish the
underlying functional form, relating net daily gain to state of energy stores,
from the confounding effects of alternate days of fasting. Therefore, we did
not further investigate the interaction, which could involve complex shifts in
the response function under different feeding regimes, reflecting differences
in physiological and behavioral thresholds (capacities and requirements for
energy acquisition, storage and use), values of current or future rewards, and
trade-offs between fitness risks such as starvation and predation
(Clark and Mangel, 2000;
Cuthill and Houston, 1997;
Mangel and Clark, 1986). In
addition, individuals differed in their regulated (mean) levels of energy
stores, suggesting differences in the perception of optimal body mass and the
effects of other, unknown, individual-state variables such as social dominance
(Gosler, 1996) or basal
metabolic requirements (Weber and Piersma,
1996).
Energetic costs of activity
Our results reflected the following pattern, suggesting mechanisms of
energy balance in birds faced with feeding time constraint but not limited by
digestive rate or overall food supply: increased energy intake, reduced energy
expended on being active, increased internal energy stores when food is
available, and increased energy expended on being active when normal feeding
is not possible. Increasing energetic expenditure on activities when food is
not available is consistent with the occurrence of regional mid-winter flights
to new wintering areas during periods of heavy rainfall
(Warnock et al., 1995), as
well as with broader use of alternative habitats locally when foraging
opportunities in preferred areas are restricted by winter storms
(Gerstenberg, 1979;
Kelly, 2001;
Page et al., 1979). The
reduction of activity energy expenditure by unrestricted dunlins confronted
with novel periods of fasting may reflect the energy-saving responses of birds
that seek refuge to ride out unpredictable events such as severe storms
(Wingfield and Ramenofsky,
1997). However, free-living shorebirds often feed during storms
and may be forced to increase the amount of energy spent on foraging to
overcome storm-related declines in food availability or feeding time. The
decision to increase or decrease activity energy expenditure during periods of
fasting may hinge on an individual's knowledge or assessment of current and
future feeding conditions; on the costs and benefits of activity options such
as enhanced local foraging or flying to a new area; or on the amount of
available energy stores (see below). Fasting birds should increase their
activity energy expenditure if they are more likely to minimize loss of energy
stores (increasing net rate of gain) by investing in such activities than by
conserving energy until feeding becomes possible. In captive dunlins,
differences in feeding regime were great enough to shift the preferred
choice.
Patterns of energy storage and use by dunlins demonstrate how an
understanding of physiological processes can contribute to evaluations of
adaptive function. Animals under risk of immediate starvation should discount
completely all options based on future rewards
(Kagel et al., 1986) or other
less critical risks, whereas decisions made before this point should involve
more complex assessments of competing alternatives (including nonenergetic
costs). The decision by fasting dunlins to become more energetically active
was made before they faced a physiological emergency (starvation). Several
authors have found that fasting birds exhibit a dramatic increase in locomotor
activity as fat supplies approach depletion, indicated by the transition from
phase II fasting, when most energy use is derived from lipid stores, to phase
III fasting, when birds exhibit a sharp increase in protein use and rate of
body mass loss (Boismenu et al.,
1992; Cherel et al.,
1988; Piersma and Poot,
1993; Robin et al.,
1998). Piersma and Poot
(1993) attributed
fasting-induced increases in locomotor activity in red knots (Calidris
canutus) to this transition from phase II to phase III fasting. Such
heightened activity might reflect potential net benefits of emergency
food-searching or movement to alternative feeding areas, in spite of increased
exposure to predation and reduced escape capacity
(Witter and Cuthill, 1993;
Witter et al., 1994), a flight
range shortened by low fuel, and other costs associated with metabolizing
structural tissues needed for normal body function. In rats, fasting-induced
increases in locomotor activity were immediately suppressed when feeding
opportunities were restored (Koubi et al.,
1991). Consistent with these patterns, food-restricted dunlins
increased the amount of energy spent on overall activity when fasting and
reduced activity energy expenditure when feeding, but apparently in the
absence of stravation (before phase III). Therefore, increased energy
expenditure in dunlin during periods that are unsuitable for feeding may not
be an emergency response to impending starvation (depletion of energy stores)
but rather a decision that also reduces other risks, such as further decline
in dispersal ability or flight capacity that could result from additional use
of energy stores while waiting for conditions to improve.
Birds are known to respond to a wide range of proximal environmental
stressors by increasing plasma levels of corticosterone, an adrenal
glucocorticoid hormone involved in short-term mobilization of energy stores as
well as winter fattening (Gray et al.,
1990; Harvey et al.,
1984). Exogenous stressors known to stimulate secretion of
corticosterone include inclement winter weather
(Rogers et al., 1993;
Schwabl et al., 1985) and
disruption of normal feeding patterns
(Astheimer et al., 1992;
Harvey et al., 1984). Pine
siskins (Carduelis pinus) with substantial fat loads exhibit dramatic
increases of corticosterone and locomotor activity when forced to fast,
indicating that food stress can lead to enhanced activity before phase III
(Astheimer et al., 1992). In
contrast, white-crowned sparrows with corticosterone implants fed ad libitum
reduce their locomotor activity relative to controls
(Astheimer et al., 1992). Our
results are consistent with these patterns: when forced to fast,
food-restricted dunlins became more active energetically, whereas birds fed ad
libitum became less active. Other recent research, on rodents, primates,
humans, and chickens, indicates that circulating concentrations of OB protein
(leptin) may provide signals, proportional to fat levels, that regulate food
intake and activity expenditure
(Campfield, 2000;
Campfield et al., 1996;
Denbow et al., 2000). Patterns
of energy use in dunlins and the possible role of endocrinemediated cues
reflecting the interplay of changing energy stores, thermal and foraging
conditions, predation pressure, and other proximal indicators of potential
fitness suggest functional processes for maintaining an energy safety margin
to minimize the risk of using structural body tissues as emergency energy
substrate.
Additional study is necessary to determine if the patterns presented here occur in free-living shorebirds. We emphasize the potential importance of available feeding time and regulation of energy stores in understanding facultative local movements or regional dispersal to alternative feeding areas. Elucidation of possible age, sex, and species differences in daily energy storage and use will require further refinement. Because fitness may correlate with nutritional state in winter, such studies may prove valuable in understanding the limits of winter site fidelity and survival in dynamic foraging environments.
|
ACKNOWLEDGEMENTS |
|---|
We thank Gay Bishop, Ken Burton, Lynn Campbell, Katie Etienne, Katie Fehring, Dan Froehlich, Ken Fox, Shane Kelly, Philippa Shepherd, and Chris Wood for assistance in capturing birds in the field. David Greene assisted in managing the aviaries. Doug Oman provided valuable statistical advice. William J. Hamilton III, Thomas R. Famula, David F. Westneat, and two anonymous reviewers provided valuable comments on the manuscript. This article is a publication of Audubon Canyon Ranch.
|
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