Cost-benefit analysis of mollusc-eating in a shorebird II. Optimizing gizzard size in the face of seasonal demands
1 Department of Marine Ecology and Evolution, Royal Netherlands Institute
for Sea Research (NIOZ), PO Box 59, 1790 AB Den Burg, Texel, The
Netherlands
2 Animal Ecology Group, Centre for Ecological and Evolutionary Studies
(CEES), University of Groningen, PO Box 14, 9750 AA Haren, The
Netherlands
* Author for correspondence (e-mail: janvg{at}nioz.nl)
Accepted 18 June 2003
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Summary |
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Key words: gizzard, digestive constraint, intake rate, red knot, Calidris canutus, ultrasonography, optimization, phenotypic flexibility
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Introduction |
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For two reasons we chose the red knot Calidris canutus as our
model species. First, its nutritional organs and especially the gizzard are
tremendously variable in size (Fig.
1; and see Piersma et al.,
1999a,b
).
Second, the muscular gizzard plays a pivotal role in the bird's feeding
ecology, crushing the mollusc prey that are ingested whole
(Piersma et al., 1993b
).
Changes in this organ's size are likely to result in changes in shell-crushing
and processing performance, thus changing energy intake rates. Given that
mollusc prey contain little flesh relative to the amount of shell (5-20%),
energy intake might readily be constrained by the rate at which shell material
is processed by the gizzard, particularly when (1) gizzard size is small,
and/or (2) the flesh-to-shell ratio (hereafter termed prey quality) is
low.
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Phenotypic flexibility offers great experimental opportunities. As organ
sizes vary within individuals, effects of such variability on performance can
be studied within individuals (Piersma and
Drent, 2003). If changes in organ size can be induced, one can
test for effects by manipulating the size. Using ultrasonography, which is a
non-invasive technique, Dekinga et al.
(2001
) showed that changes in
gizzard size of red knots can be induced by the hardness of the food. Gizzards
hypertrophied when knots were fed a hard-shelled diet (bivalves), and
atrophied when on a soft diet (pellets). These changes were reversible and
rapid; they occurred over a time scale of only 6-8 days.
Gizzard size was manipulated and confirmed by ultrasonography in individual
red knots by changing the diet on offer. We then tested in three separate
experiments the hypothesis that gizzard size constrains energy intake rate
via the rate of shell crushing and processing. [Note that intake rate
in this paper means intake over total time, which includes non-foraging
activities such as digestive breaks. When feeding rates are high, red knots
take short digestive breaks (20-300 s) at regular times (after 3-9 prey
ingestions, depending on prey size). In the terminology of foraging theory,
such intake rate over total time is called long-term intake rate, as
opposed to short-term intake rate, which considers intake over
foraging time only (see Fortin et al.,
2002).] This `shell-crushing hypothesis' predicts that (1) intake
rates (prey s-1) decline with the amount of shell mass per prey,
(2) intake rates on with-shell prey types increase with gizzard size, (3)
intake rates on intact prey (with shell) items are below those on
shell-removed prey items, (4) intake rates on shell-removed items do not vary
with gizzard size, and (5) intake rates on poor quality prey are insufficient
to balance the energy budget within short daily available foraging times.
These predictions were tested against those of an alternative hypothesis
inspired by foraging theory (Stephens and
Krebs, 1986), the `handling time hypothesis', which states that
intake rates are constrained by the rate at which prey can (externally) be
handled (i.e. the foraging activity between prey encounter and prey
ingestion). It predicts that (1) intake rates (prey s-1) are not
different from the rate at which prey can be externally handled before being
swallowed [note that handling rate (prey s-1) is the inverse of
handling time (s prey-1)], and (2) intake rates on with-shell prey
do not vary with gizzard size.
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Materials and methods |
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Gizzard size manipulations in each of the three experiments were successful. Birds had larger gizzards when fed hard-shelled prey than when fed soft food (Fig. 2 and Table 1;P<0.01; see below for the time scale over which these changes took place). Corrected for the effect of diet hardness, gizzard mass differed among experiments (P<0.05), but not among individual birds (P>0.15).
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Experiment 1
Using different prey species with different shell masses, we tested two
predictions that follow from the `shell-crushing hypothesis': (1) intake rates
(prey s-1) decline with a prey type's shell mass, and (2) intake
rates on with-shell prey types increase with gizzard size.
We created two groups, each of three birds Calidris canutus L., to which we randomly assigned individuals (because of logistic problems in collecting enough prey types for each bird we kept the total number of experimental birds at `only' six). Before the start of the experiment, these groups were similar with respect to gizzard mass (P>0.3) and structural body size (principal component 1, PC1, from principal component analysis that included lengths of tarsus, toe, head and bill, P>0.25). All six birds were adult, captured with mist-nets in the Dutch Wadden Sea in 1994, 1995 and 1999. Ever since their capture, these birds had been housed in large in- and outdoor aviaries at the Royal Netherlands Institute for Sea Research (NIOZ, Texel, The Netherlands).
In order to manipulate gizzard size, one group was offered soft food (trout
pellets; Trouvit, Produits Trouw, Vervins, France), the other group
hard-shelled food (cockles Cerastoderma edule). This feeding regime
was started 3 weeks before the experiment. Starting on 21 August 2000, we ran
36 trials with individual birds over 5 weeks (6 birds x 6 prey types).
Gizzard mass was confirmed by ultrasonographic measurements at the beginning
and at the end of the experiment, and remained at the particular level (small
or large; P=0.55), despite the fact that, during the short-lasting
trials, the birds encountered prey that should have made them adjust their
gizzard size (according to Dekinga et al.,
2001).
The experiment took place on the isle of Griend in the western Dutch Wadden Sea (53°15'N, 5°15'E). The close proximity to mudflats with a diverse array of prey species on offer facilitated the daily collection of prey items. Each group lived in a holding pen (2.5 mx1 mx0.5 m), which was placed under cover. Freshwater for drinking was always available.
Two bivalve prey species, which are commonly fed upon by red knots in the
wild (Piersma et al., 1993a),
were used in the experiment: the Baltic tellin Macoma balthica and
the cockle. To incorporate size-related variation in shell mass, we offered
different size classes of each prey species. The size criteria (all in mm)
were: 5-7 (small), 9-11 (medium) and 13-15 (large), providing six different
species-size categories or prey types. Prey length was measured to the nearest
mm.
Prey items of only one type were offered in a single tray (0.2 mx0.15 m). Trials lasted 40 min, which yielded on average about 40 prey ingestions per trial. This number of ingestions should have been sufficient for intake rates to be constrained by rates of shell crushing, which commences after the gizzard is filled up, usually after 3-9 ingested prey (J. A. van Gils, unpublished data).
Shell mass (DMshell) was measured by removing the soft, fleshy parts from a sub-sample of bivalves of each prey type class. Shells were put in crucibles and dried to constant mass for 3 days in a ventilated oven at 55-60°C, then weighed to the nearest 0.1 mg.
Intake rates were measured from video-recordings of the trials. The full
length of each trial was recorded using a Hi-8 video camera (SONY Nederland
B.V., Badhoevedorp, The Netherlands) on a tripod, 1-2 m from the foraging
bird. After each trial, the Hi-8 tape was copied to a VHS tape, to which a
time-code was added. This enabled us to analyse the foraging behaviour from
the VHS tapes by using `The Observer' package
(Noldus Information Technology,
1997). Tapes were analysed in slow motion (1/5 of recording speed)
and behaviour was scored with an accuracy of 0.04 s and directly coded into
digital files. We scored cumulative intake, handling times and non-foraging
time (comprising standing still, preening and walking around).
Handling times were recorded to test the two predictions of the alternative `handling time hypothesis' that intake rates were not governed by the rate of shell crushing but by the rate at which prey can externally be handled.
Experiment 2
Unlike experiment 1, where we offered different prey species and different
sizes, we now offered only one bivalve prey species of just one size class.
This was to eliminate variation in intake rate that was not due to variation
in shell mass. We offered this one prey type either intact (as a hard-shelled
prey) or with its shell removed (as a soft-bodied prey) in order to test three
predictions that follow from the `shell-crushing hypothesis': (1) intake rates
on intact prey items are below those on shell-removed prey items; (2) intake
rates on intact prey items increase with gizzard size; (3) intake rates on
shell-removed items do not vary with gizzard size.
We used the same birds in the same groups as in experiment 1, except that one bird from the small-gizzard group of experiment 1 had to be replaced with one caught in the Dutch Wadden Sea in 1998. This did not change the pre-experimental similarity between groups in gizzard mass (P>0.9) and structural body size (P>0.75).
Gizzard size was manipulated by offering soft food (trout pellets) to one
group, and hard-shelled food (blue mussels Mytilus edulis) the other
group. This feeding regime was initiated 4 weeks before the start of the
experiment. Unlike in experiment 1, we now varied gizzard size within
individuals by switching the diet between the two groups. This switch occurred
in the middle of the experimental period, after which we waited for 6 days to
allow the gizzards to hypertrophy/atrophy to the new size
(Dekinga et al., 2001). To
check if gizzards had changed in size, every third day each individual's
gizzard mass was estimated ultrasonographically. Starting on 3 May 2000, we
ran 24 trials with individual birds in a period of 3 weeks (6 birds x 2
treatments x 2 gizzard sizes per bird).
The birds were housed in a climatized sea-container (5 mx2 mx3
m) at NIOZ. To ensure that the birds maximised their intake rates, we
subjected them to cold-stress for the duration of the experiment at ambient
temperatures of 3-4°C (cf. Klaassen et
al., 1997), which should have increased their maintenance
metabolism by at least 50% (Wiersma and
Piersma, 1994
) and thus their willingness to feed at maximum
intake rates. The light-dark regime was kept constant (L:D=15 h:9 h). Each
group of birds lived in a holding pen (2.5 mx1 mx0.5 m), which was
kept clean continuously by seawater running over the floor. Freshwater for
drinking was always available.
The prey type offered during the trials was the blue mussel (length=11.0±0.1 mm, mean ±S.E.M., N=149). Mussels were collected by scraping them from basalt piers in the North Sea at Texel. After washing off most of the attached organic material, we sorted the mussels into different size classes by sieving through different mesh sizes. We kept the most abundant, medium-size class apart for the trials; the other size classes were offered as staple food. The mussels were stored in basins containing seawater of 5-12°C. We unshelled these prey by holding closed mussels in boiling water for 5-10 s, after which their valves opened, enabling us to remove the flesh with a pair of tweezers. Prey were offered in a single tray (0.6 mx0.4 m), that had running seawater through it to keep the mussels clean. To maintain methodological consistency with experiment 1, trials lasted 20 min each to guarantee about 40 prey ingestions per trial (note that these prey were generally eaten faster than the prey in experiment 1).
We used video-analysis as described for experiment 1 to measure intake rates and handling times. The latter measurement allowed us to test the two predictions of the alternative `handling time hypothesis'.
Experiment 3
By offering a prey type with a very low flesh-to-shell ratio (0.09,
equivalent to a metabolizable value of 1.44 kJ g-1
DMshell), we tested one of the predictions that follow
from the `shell-crushing hypothesis': knots feeding on poor quality prey
experience difficulty in maintaining balanced energy budgets within the
normally available foraging time (12 h per day in their intertidal habitat).
We did not manipulate gizzard size in this experiment; instead we worked only
with knots that had large gizzards. These were adult birds, caught in the
Dutch Wadden Sea in 1997. They were given cockles as their permanent staple
food 3 months before the experiment started. This ensured large gizzards in
these birds, which was confirmed by ultrasonography 2 weeks before the
experiment. Starting on 14 March 1998, we ran 28 trials with individual birds
over 6 weeks (5 birds x 3 treatments, with each combination in
duplo except for 2 trials). Prey quality at this time of year is poor
(Zwarts, 1991).
The birds were housed in an indoor aviary (4.7 mx1.1 mx2.5 m) at NIOZ, in a constant environment with respect to light (15 h:9 h, L:D) and air temperature (16-20°C). Prey were divided equally across four trays (each 0.6 mx0.4 m) that had seawater running through them to keep the prey fresh and alive. Freshwater for drinking was always available.
In the experiment we used cockles, as they are the Wadden Sea's poorest
quality prey (Zwarts, 1991) of
size 11.4±0.1 mm (mean ± S.E.M., N=208).
These bivalves were collected on intertidal mudflats adjacent to the island of
Texel. In the laboratory, the right size class (8-15 mm) was sorted out by
sieving through different mesh sizes, followed by storage in basins containing
seawater at 5-12°C.
The experimental treatment was the daily available time for foraging: either 2, or 6 or 16 h. We selected these times as they covered the extreme ranges of available daily foraging time in the tidally dictated circumstances in the wild. For all treatments, we always removed the food at the same time of day (20.00 h); thus we varied the length of the available foraging time by starting a feeding trial at different times of day (04.00 h, 14.00 h, 18.00 h). This enabled the birds to anticipate the time the food was on offer. In any other feeding schedule (random times or fixed starting times) the available daily foraging time could not have been anticipated by the birds.
Intake rate was measured as the total consumption during an entire trial divided by the length of a trial. As trials were long-lasting (2-16 h), we did not measure total consumption from video-analysis but from estimates of the initial number of prey offered minus the final number of prey remaining at the end of a trial. As we worked with many prey items per trial (up to 6000), initial and final prey numbers were estimated by weighing the fresh mass of a sub-sample of 100 cockles at the start and the end of each trial, respectively. These calibrations were then used to translate total fresh mass offered and remaining into total numbers. We used video-analysis only to measure handling times, by sampling random intervals of approximately 5 min h-1, yielding about 10 prey ingestions per interval. This enabled us to test one prediction of the `handling time hypothesis': intake rates (prey s-1) are not different from handling rates (prey s-1).
Shell mass was measured as in experiment 1. In addition, we measured
ash-free dry mass of the prey's flesh (MAFDflesh) by
weighing dried flesh mass to the nearest 0.1 mg before and after incineration
for 2 h at 550°C. This measurement was taken to calculate the intake rate
required to cover the daily energy expenses for each treatment
(IRrequired in prey s-1). For a given treatment
of n available foraging hours, IRrequired was
calculated as:
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Note that we did not take the costs of foraging into account (0.602 W;
Piersma et al., 2003) since
the prey were offered ad libitum in trays such that the birds did not
have search for them. As a check upon this estimate for energy expenditure, we
tested per treatment whether the birds lost weight on a daily basis.
General methodology in all three experiments
In each experiment we aimed to measure maximum intake rate (for a
given gizzard size) in captive red knots in three ways. Firstly, we kept the
birds at relatively low body mass (100-120 g) and starved them for at least 6
h before each trial to get them motivated and eager to eat. To keep the birds
at constant low body mass we weighed them daily and adjusted the amount of
food that they received accordingly. Secondly, we eliminated search time from
the foraging process by offering unburied prey in dense, excess quantities.
This ensures that intake rate will be constrained by either external handling
times or by internal digestive processes (such as shell crushing in the
gizzard). Thirdly, during each trial the test birds were feeding singly, so
that intake rate would not be subject to interference competition. The birds
not involved in a trial were kept in a separate cage for as long as a trial
lasted.
Statistical analyses
In each experiment, a trial was used as the experimental unit, meaning that
each trial yielded one data point on intake rate that was used for statistical
analyses. Intake rates were log-transformed to make them normally distributed.
As some trials in experiment 1 yielded an intake rate of 0, we added 0.001 to
all intake rates (prey s-1) in this experiment to enable
log-transforming 0 values (following Berry,
1987). Handling times were also log-transformed in order to
normalise their distribution. All tests were performed using the General
Linear Modelling procedure (GLM) in SYSTAT 10 (SPSS Inc., Chicago, IL, USA).
The order in which trials were performed was randomised with respect to bird
and treatment. Significance was accepted at P<0.05.
Experiment 1
The following analysis-of-variance (ANOVA) model on intake rates
IR on with-shell prey (model 1 in
Table 2) tested two predictions
of the `shell-crushing hypothesis', that intake rate (prey s-1)
declines with a prey type's shell mass (DMshell), and that
intake rate on with-shell prey types increases with gizzard size
Gj (j=small, large).
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![]() | (4) |
![]() | (5) |
![]() | (6) |
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The first prediction of the `handling time hypothesis', that intake rate (prey s-1) for with-shell prey is not different from handling rate, can formally be written as IR=1/H, where H is handling time. When log-transformed, log(IR)=-log(H), or log(IR)+log(H)=0. Thus, only for the trials on with-shell prey, we added log(H) to log(IR) for each trial, and tested the hypothesis that b0=0 (where H is the least-square mean handling time for a given prey type). The second prediction of the `handling time hypothesis', that intake rate for with-shell prey does not vary with gizzard size, is the opposite of the second prediction of the `shell-crushing hypothesis' and was therefore tested by Equations 3-6.
Experiment 2
This ANOVA model tested three predictions of the `shell-crushing
hypothesis': (1) intake rate of intact prey items is below that of
shell-removed prey items, (2) intake rate of intact prey items increases with
gizzard size, and (3) intake rate of shell-removed items does not vary with
gizzard size.
![]() | (7) |
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Experiment 3
The one prediction of the `shell-crushing hypothesis' that we tested here,
that knots feeding on poor quality prey can only marginally balance their
daily energy budget within the normally available foraging time (12 h), was
tested by the following ANOVA model (with and without interaction term):
![]() | (9) |
The one prediction of the `handling time hypothesis' that we could test, that intake rates are not different from handling rates, was tested as described for experiment 1.
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Results |
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To test whether intake rates were constrained by handling time, we used the observed relationships between handling time H (s) and shell length L (mm) for Macoma [log10(H)=-2.672+2.990log10(L), N=15, r2=0.932, P<0.001] and Cerastoderma [log10(H)=-0.978+1.604log10(L), N=12, r2=0.445, P<0.05]. Handling rates (1/H) did not vary with gizzard size class and were significantly higher than intake rates (P<0.001 for both prey species; Fig. 3).
Experiment 2
The results of the previous experiment on multiple prey types implied that
shell mass delimits intake rate. This interpretation is consistent with the
results in the present experiment for a single prey type
(Fig. 4;
Table 3). (1) Intake rates on
with-shell prey were higher for birds with large gizzards
(P<0.001) and (2) rates were correctly predicted by the regression
model from experiment 1 (P>0.45; Equation 8, using a
DMshell of 71.08±3.84 mg, mean ±
S.E.M., N=61). (3) Intake rates on unshelled prey did not
vary with gizzard size (P>0.45) and (4) for both gizzard size
classes, intake rates on unshelled prey are higher than intake rates on
with-shell prey (P<0.001), and (5) did not differ from the
postulated maximum metabolizable energy intake rate (P>0.05;
Kirkwood, 1983;
Kvist and Lindström, in
press
). Finally, (6) intake rates were not as high as handling
rates [P<0.001; handling times lasted 1.55 s on average, and were
unaffected by bird (nested within flock, P>0.9), flock
(P>0.3) and gizzard size (P>0.2)].
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Experiment 3
The observed intake rates on the poor prey type
(Fig. 5) were not sufficient to
cover the daily energy expenses when feeding for 2 h (P<0.001) or
6 h per day (P<0.002), but were sufficient when feeding for 16 h
(P>0.25; Fig. 5).
For these calculations (Equation 1) we used the mean
MAFDflesh (8.79±0.32 mg, mean ±
S.E.M., N=208). This is consistent with the finding that
the birds lost weight in the 2 h (P<0.005) and 6 h
(P<0.03) treatment, but not when fed for 16 h (P>0.1).
Intake rates did not vary with bird (P>0.7) and available foraging
time (P>0.95; Table
4).
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The two parameters from experiment 1 (b0=-4.293 and b3=2.000 in Equation 6) correctly predicted intake rate (prey s-1) from gizzard mass and shell mass (P>0.85; broken line in Fig. 5). For this calculation (Equation 8) we used the mean DMshell (97.54±4.67 mg, N=103).
Intake rates (prey s-1) were again much below handling rates (P<0.001; Fig. 5). Handling times lasted 2.93 s on average, and were unaffected by bird (P>0.35) and daily available foraging time (P>0.3).
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Discussion |
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The fact that the gizzard can only process a fixed amount of shell mass per
time unit suggests an underlying mechanism. From the breaking forces for
various molluscs measured by Piersma et al.
(1993b), it can be calculated
that these forces scale linearly with shell mass (J. A. van Gils, unpublished
data). It seems that a given gizzard size can only exert a given amount of
work per unit time, i.e. the maximum power that a gizzard is able to generate
seems to be responsible for the constraint on shell crushing rate.
Alternatively, as the volumetric density of shell material is likely to be
fairly constant across different prey types, the fixed amount of shell mass
that can be processed per unit time could reflect the total volume of shell
material that a full gizzard can contain. However, since the increase in
gizzard mass is most likely to be due to increased muscle mass around the
gizzard cavity, gizzard volume probably does not increase with gizzard mass
(A. Purgue, personal communication; T. Piersma, personal observation), which
makes the former `force-idea' more likely.
Using these gizzard-size-specific rates of processing shell material (model
4 in Table 2), we can predict
the ceiling on a knot's intake rate once we know its gizzard mass and the
shell mass per prey (as done for experiments 2 and 3; broken lines in Figs
4 and
5, respectively). Furthermore,
given the daily available feeding time (always ca. 12 h in the intertidal
non-breeding habitat) and the energy content per prey, we can then predict
whether a bird will be able to meet its daily energy requirements (experiment
3; Fig. 5). It is promising
that two field estimates of intake rate (over total time: squares in
Fig. 3;
Zwarts and Blomert, 1992;
González et al., 1996
)
are correctly predicted from the mean shell mass per prey in the diet and the
gizzard mass estimated from relevant carcass analysis (T. Piersma, personal
observation). This close match between field intake rates and model
predictions shows the necessity of taking digestive constraints into account
when using functional response models to predict long-term field intake rates.
Functional responses based on encounter rates and handling times might
correctly predict short-term intake rate (i.e. while foraging) from prey
densities (Piersma et al.,
1995
), but longterm intake rate (i.e. over total time) is likely
to be governed by digestive capacity (van
Gils et al., 2003
).
Having established that gizzard size and prey quality determine energy
intake rates, we can now apply a reverse optimization routine to predict, for
given environmental conditions, the gizzard size that is needed to fulfil the
daily energy requirement. This prediction needs as input parameters (1) prey
quality, (2) daily energy requirement and (3) daily available foraging time.
The first parameter peaks at the start of the reproductive season of the prey
(late spring in the Wadden Sea; Zwarts,
1991); the second parameter varies mainly with ambient temperature
and wind speed (Wiersma and Piersma,
1994
); and the third parameter is constant at 12 h
day-1 (Piersma et al.,
1994
). Since we know the monthly expectations in prey quality
[Fig. 6A; based on Zwarts
(1991
) while taking into
account diet composition; expressed as metabolizable kJ g-1
DMshell] and energy expenditure
(Fig. 6B, calculated in
Appendix), we can predict month-specific gizzard mass for red knots in living
in the Wadden Sea (Fig. 6B,C).
Depending on the criteria, the month-specific daily energy requirement can
take two values. (1) If knots aim to balance their energy budget,
daily energy requirement equals daily energy expenditure (i.e. satisficing;
Nonacs and Dill, 1993
). (2) If
knots aim to maximise their daily net energy intake (i.e. net
rate-maximization; Stephens and Krebs,
1986
), their daily energy `requirement' equals the physiologically
maximum daily gross energy intake, e.g. as derived by Kirkwood
(1983
) and Kvist and
Lindström (in press
).
When not constrained by gizzard size, this maximum is presumably set by the
size of other nutritional organs, such as the liver or the intestine
(McWhorter and Martínez del Rio,
2000
); we found that intestine lengths in knots are constant
throughout the year (T. Piersma, unpublished data). These two foraging
currencies lead to two unique predictions on optimal gizzard size for each
month (Fig. 6B,C).
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Data on gizzard mass of free-roaming red knots sampled in the Wadden Sea
(N=920) fit a combination of these predictions remarkably well
(Fig. 6C). Net rate-maximizing
gizzards are found for red knots in spring, while satisficing gizzards are
found throughout the remainder of the year (the best fit is found when
modelling rate-maximization in February-May and satisficing in July-January;
r2=0.23, P<0.001). This shift in `foraging
currency' is consistent with seasonal changes in body mass and energy stores.
Red knots accumulate large amount of energy stores in spring when preparing
for their long-distance migrations, while in NW Europe their body mass remains
quite stable during the rest of the year
(Piersma, 1994). It is also
consistent with an experimental study showing that red knots in spring
maximised their net intake rate while exploiting food patches
(van Gils et al., 2003
).
Furthermore, body mass increases a little in late autumn (October-December;
Piersma, 1994
), which is line
with the gizzards being in between the satisficing and net-rate maximizing
size at that time of year (Fig.
6C).
The fact that knots that are not building body mass appear to obey a
satisficing strategy (but feed during the entire low tide period) fits the
growing number of studies that show, in contrast to the original assumptions
of optimal foraging theoreticians
(Stephens and Krebs, 1986),
that animals do not always forage at maximal intensities
(Swennen et al., 1989
;
Norris and Johnstone, 1998
;
Iason et al., 1999
). Note,
however, that such satisficing behaviour should still be considered as part of
an optimization process (see discussions in
Stephens and Krebs, 1986
;
Nonacs and Dill, 1993
), in
which energy gain is traded against cost factors associated with foraging,
such as the risk of parasite infestation or predation
(Iason et al., 1999
) or, in
the case of probing waders, the risk of bill damage
(Swennen et al., 1989
;
Norris and Johnstone, 1998
).
The way in which red knots balance their energy budgets adds another element
to this discussion. Daily energy budgets could be balanced in periods shorter
than 12 h per day if knots grew larger gizzards. For example, if knots in
January had gizzards of about 14 g instead of the observed 9 g, their daily
energy budget would be balanced when feeding for only 6 h per day. However,
this would increase their average daily metabolic rate by 17% (due to higher
maintenance and transport costs and reduced amounts of heat substitution). The
fact that knots prefer to feed with smaller gizzards for the full extent of
the low-tide period (12 h per day; Piersma
et al., 1994
), suggests that satisficing knots aim to minimise
their overall rate of energy expenditure, perhaps in order to maximise
lifespan by minimizing the level of free radicals
(Daan et al., 1996
;
Deerenberg et al., 1997
;
Tolkamp et al., 2002
).
To conclude, gizzard size sets the maximum processing rate of shell material, and the constraint on a knot's daily energy intake is therefore a function of (1) the amount of flesh per g shell material (i.e. prey quality), (2) gizzard size and (3) the daily time available for foraging. Seasonal variation in prey quality and required energy consumption (being a function of ambient temperature and migratory phase) together explain the seasonal variation in gizzard mass of red knots living in the Wadden Sea.
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Appendix |
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Income
From the results of experiment 1 (model 4,
Table 2) we know that energy
intake rate IR (W) depends on prey quality Q (J
metabolizable energy per g shell mass) and gizzard mass G (g) in the
following form:
![]() | (A1) |
Expenditure
From Piersma et al. (1996)
we know that basal metabolic rate (BMR, in W) scales linearly to lean mass
(L) in the following form:
![]() | (A2) |
![]() | (A3) |
From Kvist et al. (2001),
we know that the metabolic rate while flying Rfly (W)
scales to total body mass B (g) in the following way (assuming that
the birds in that study had BMR values of 0.95 W):
![]() | (A4) |
From the accompanying paper (Piersma et
al., 2003) we know that metabolic costs of foraging amount to
0.602 W. If we assume that these costs are the sum of the cost of probing
(Rprobe) and the cost of walking
(Rwalk), we can predict how foraging costs will vary with
gizzard mass. Bruinzeel et al.
(1999
) show that the
Rwalk (W) equals:
![]() | (A5) |
Piersma et al. (2003) show
that the metabolic costs of digesting (i.e. the heat increment of feeding,
HIF) amount to 1.082 W. Assuming that HIF increases linearly with the amount
of flesh that is digested, and given the observed flesh intake rate of 0.208
mg s-1 (fig. 1B in
Piersma et al., 2003
), the HIF
cost of digesting 1 g of MAFDflesh equals 5195 J. Since we
know how intake rate (prey s-1) scales with gizzard mass (Equation
A1), HIF (W) depends on gizzard mass G (g) in the following form:
![]() | (A6) |
The month-specific thermostatic costs in the Wadden Sea range from 1.64 W
in August to 2.93 W in January (Wiersma
and Piersma, 1994). Some of the heat generated in other
cost-components can substitute for this thermoregulatory heat, which makes
life considerably cheaper. All of the heat generated by BMR
(Scholander et al., 1950
;
Wiersma and Piersma, 1994
) and
presumably also all of the HIF heat can be used for thermoregulatory purposes
(like BMR, HIF is after all generated in the core of the body). From Bruinzeel
and Piersma (1998
) we
calculated that about 30% of the heat generated due to walking substitutes for
thermostatic heat.
Daily energy income and expenditure depends on the time devoted to all of
the above-mentioned activities. Of course, BMR and thermoregulatory costs are
expended for 24 h per day. Red knots in the Wadden Sea devote about 1 h per
day to flight (between roosts and feeding sites) and about 12 h per day to
foraging (i.e. walking, probing, and HIF;
Piersma et al., 1993a). Taking
these time budgets into account while equating income with expenditure solves
for optimal gizzard mass in satisficing knots.
Optimal gizzard size for net rate-maximizing red knots
Net-rate-maximizing knots should aim for gizzard sizes that process food at
the physiologically maximum rate (see fig.
4 in Piersma et al.,
2003). According to Kirkwood
(1983
) and Kvist and
Lindström (in press
),
this should yield red knots a gross income of 544 kJ on a daily basis. Using
the gizzard-size-dependent function for intake rate (Equation A1), and again
assuming that knots feed for 12 h per day on prey of quality Q (J
g-1 DMshell), the optimal gizzard mass for
net-rate-maximizing knots Gnet-rate (g) therefore equals:
![]() | (A7) |
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Acknowledgments |
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References |
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