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First published online October 5, 2006
Journal of Experimental Biology 209, 4091-4101 (2006)
Published by The Company of Biologists 2006
doi: 10.1242/jeb.02478
Foraging energetics of a nectar-feeding ant: metabolic expenditure as a function of food-source profitability
Theodor-Boveri-Institut der Universität Würzburg, Lehrstuhl für Zoologie II, Biozentrum, Am Hubland, D-97074 Würzburg, Germany
* Author for correspondence at present address: University of California at San Diego, Division of Biological Sciences, Mail code 0116, 9500 Gilman Drive, La Jolla, CA 92093-0116, USA (e-mail: pschilman{at}yahoo.com)
Accepted 8 August 2006
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Key words: Camponotus rufipes, central-place foragers, metabolic rate, nectar feeding
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). A possible explanation is their social organization, which
allows them to collectively exploit food sources, and to build complex nests
that create a controlled environment for the inhabitants. The maintenance of a
large colony is often associated with an efficient foraging strategy. The
fitness of the colony is therefore directly related to its foraging success,
i.e. the net energy obtained by the workers over their life span. Foraging
performance can be constrained by many different factors including competition
(Milinski, 1982), predation
risk (Milinski and Heller,
1978; Nonacs and Dill,
1990), desiccation risk
(Nonacs and Dill, 1990),
forager's size (Medan and Josens,
2005), and food-source characteristics
(Possingham, 1989;
Schilman and Roces, 2003), and
can be improved by other factors such as learning
(Ganishaiah and Veena, 1988;
Johnson, 1991;
Veena and Ganeshaiah,
1991).
Ant workers are central-place foragers, i.e. they deliver collected food to
a central location, the nest. The most common currencies used in economic
analysis of foraging behavior are the rate of energy gain (net energy gain per
unit time) and energetic efficiency (net energy gain per unit energy
expenditure) (Krebs, 1981).
Costs are measured as time and energy spent foraging. Most studies have
evaluated time costs, which are easy to record, but only few investigations
provide direct measurements of foraging costs. Depending on the food type
being collected, gain–cost ratios in foraging ants range from 4 to 1000
for nectar-feeding and harvester ants, respectively
(Fewell, 1988;
Fewell et al., 1996).
Nectar-feeding ants repeatedly visit renewable resources such as
extrafloral nectaries or aphid aggregations. Such renewable resources usually
offer nectar at flow rates much lower than the maximal intake rate of
individual ants. Therefore ants have to wait for the nectar to be produced.
Rates of extrafloral nectar secretion are influenced by biotic and abiotic
factors (Heil et al., 2000);
however, these rates could be considered roughly constant for short periods of
time. For instance, maximal rates of 0.12 µl min–1 per
plant have been measured in species regularly visited by ants
(Dreisig, 2000). When the
maximal crop capacity of an ant worker is considered, averaging 6–7
µl for workers of the ant, Camponotus rufipes
(Schilman and Roces, 2003), it
becomes clear that in order to fill its crop, workers of this species should
spend about 60 min feeding.
Ants often leave a nectar source with only partially filled crops even
under ad libitum conditions
(Josens and Roces, 2000;
Mailleux et al., 2000). The
extent to which foragers fill their crop is a function of nectar concentration
(Josens et al., 1998). In
addition, we found that ants trained to collect sugar solution provided at
various flow rates spent different times feeding, and returned to the nest
with partial crop loads, depending on the nectar flow rate experienced at the
source (Schilman and Roces,
2003). Under such conditions, it may be relevant for ants to
adjust their foraging efforts at a patch in response to its quality, since
both time and energy costs may depend on food-source profitability.
It is an open question whether the observed partial loading in Camponotus, with a concomitant reduction in feeding times, and therefore the early departure to the nest, results from a trade-off between maximizing loading and minimizing feeding and transport costs. Quantitative studies that manipulate nectar production rate in the natural range of nectar flows and calculate energetic gains and measure time and energy costs, are lacking.
Nectar-feeding ants catabolize carbohydrates to cover their energy demands. Thus, the analysis of their foraging performance is straightforward because gain and costs can be measured in the same units (amount of carbohydrates ingested or consumed per unit time). In the present study, we measured the metabolic rates of trained ants during undisturbed feeding, and investigated time and energy allocation during foraging as a function of the profitability of the visited food source, with profitability expressed either as the sugar concentration of the provided solution or its flow rate.
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Materials and methods |
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All measurements were performed while the colony had free access to ad
libitum cockroaches and water but was deprived of sugar solution for
3–7 days. In this period, starvation does not significantly modify
foraging behavior in this species (P.E.S. and F.R., unpublished data). For a
detailed explanation of rearing conditions and standardization of the colony,
see elsewhere (Schilman and Roces,
2005).
Food sources
Sucrose solutions of different concentrations were provided at various flow
rates. All concentrations of fed solutions are reported as percentage sucrose
equivalents (g solute per 100 g solution) (Sigma-Aldrich; Deisenhofen,
Germany). A continuous and controlled flow rate of either 0.236, 1.18 or 2.36
µl min–1 sucrose solution, with concentrations of 1, 5,
10, 30 and 50%, were used. The flow rates assayed were provided by a nectar
pump, and these rates span the natural range of extrafloral nectar secretion
for plants regularly visited by ants. For instance, values ranging from 0.075
to 0.21 µl min–1 per plant were found for different plant
species (Dreisig, 1988), and an
average of 18.1% sugar (range: 6 to 34%) was reported for the natural nectar
loads collected by the ant Paraponera clavata
(Breed et al., 1987).
Respirometry measurements
The high-resolution respirometry system employed (Sable system TR-2, Sable
System International, Las Vegas, NE, USA; resolution 0.01 p.p.m.
CO2) has been described elsewhere
(Lighton, 1990). Briefly,
CO2- and H2O-free air was drawn through an acrylic
respirometric chamber (2.8 cmx2.8 cmx5.2 cm; volume=40.8
cm3) at a flow rate of 300 ml min–1 STP controlled
by a mass-flow controller. The CO2 produced by the ant was measured
by an IR-CO2 analyzer (Li-Cor, Inc., Lincoln, NE, USA), and the
data were stored in a computer. Each recording consisted of a variable number
of data points taken at 1.5-s intervals. To determined CO2 emission
rates, the data acquisition and analysis system DATACAN V software was used
(Sable System International, Las Vegas, NE, USA).
In all cases before and after each metabolic rate recording, the system baseline with the empty chamber was recorded. During analysis, the initial and final baselines were subtracted assuming a linear drift. All measurements were performed in a room with a controlled temperature of 25±0.5°C.
Experimental procedure
Each assay began by connecting the laboratory nest to a food patch by means
of a 50 cm-long wooden bridge. Only a single worker was allowed onto the
bridge and reach the respirometric chamber where the patch was placed
(Fig. 1). Once inside the
chamber, the CO2 released by the ant was measured during 4 min
prior to feeding, then during the actual feeding activity, and 4 min after
feeding before the ant was allowed to leave the chamber. To do this, the ant
was first allowed to enter into the chamber by itself, the chamber was then
closed and the CO2-release measured over 4 min prior feeding. After
that time, the nectar pump, which provided nectar at a given flow rate, was
switched on and the measurement continued during feeding. The feeding time of
the individuals varied according to the concentrations and flow rates of the
solutions offered, as previously reported
(Schilman and Roces, 2003).
When the ant voluntarily finished feeding and decided to return to the nest,
the pump was switched off and the CO2-release was measured for
another 4 min post-feeding. Afterward, the chamber door was opened and the
wooden bridge connected again in order to allow the ant to return to its nest.
Workers immediately returned to the nest without trying to return to the
respirometric chamber in order to collect more nectar. This was a clear
indication that they voluntarily decided to stop feeding and return to the
nest even with partial loads, as previously described
(Schilman and Roces, 2003).
For future identification, the worker was gently marked with colored powder
when running back over the bridge. Upon arrival at the nest, the marked worker
was allowed to enter and to unload the collected fluid via
trophallaxis with nestmates. After unloading, the marked worker returned to
the patch. Each marked ant performed 4 consecutive visits to the artificial
food source inside the chamber, collecting nectar during all of them. The
ant's metabolic rate was measured in the first and fourth visit. In the second
and third feeding visits, the marked ant was allowed to enter an identical
chamber that was not connected to the respirometric device. This allowed us to
measure the baselines of the empty respirometric chamber used, while the ant
was foraging in the alternative chamber, and so to control for any kind of
electronic drift of the device. When the marked ant attempted the fifth visit,
it was caged before entering the chamber so as to measure its unloaded body
mass to the nearest 0.01 mg (analytical balance Ohaus Model AS60, Karlsruhe,
Germany). The experimental procedure for measuring a single ant was time
consuming, but ensured a record of non-disturbed feeding and metabolic
expenditure of foraging ants.
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A potential methodological artefact that might compromise our measurements
could be the release of CO2 dissolved in the nectar delivered by
the pump. In order to control for that possibility, measurements with an empty
chamber were performed in the same way as described above, but with no ant
present in the chamber. Briefly, CO2 was measured for 4 min with
the nectar pump turned off, then for 30.52±0.24 min (for the flow rate
0.236 µl min–1; mean ± s.e.m.), 10.50±0.13
min (for 1.18 µl min–1) and for 5.41±0.07 min (for
2.36 µl min–1) with the pump turned on, and finally for
another 4 min with the pump off. The measuring interval with the nectar pump
on, represents the highest experimental feeding times measured, which depend
on both the solution flow rate and sucrose concentration. As a consequence,
exactly the same experimental procedure was employed in these control
measurements, but without the ant. These controls were performed with all
experimental flow rates assayed, using a sucrose concentration of 30%. For
each measurement, the difference between the average CO2 production
over the 4 min before and during nectar delivery was calculated. Differences
between the averages were expressed as absolute values (in µl
h–1) and as percentages of the experimental groups, as
follows:
 | (1) |
Measurements and calculations of `instantaneous' metabolic rate
During feeding, workers' body mass increases because of the collected load,
and it is an open question whether the extent of loading may cause changes in
the average metabolic expenditure during a visit. In order to separate the
effect of the carried load from the effect of the food source profitability on
the metabolic rate, we calculated `instantaneous' metabolic rates. We defined
`instantaneous' metabolic rate as the average metabolic rate over a very short
time interval, within which the worker reached a defined crop load during its
actual feeding event. Using these previously defined crop loads as independent
variables, it was possible to compare the `instantaneous' metabolic rates of
workers having the same crop loads, but collecting at different flow rates or
sucrose concentrations. Each ant's CO2 production rate was
calculated at the time when the crop load of the individuals reached either 1,
3, 5 or 7 mg of load during their feeding activity. These measurements were
converted to energy units of µW. We calculated, for each ant and load, the
`instantaneous' metabolic rate as the averaged measurement within either 30,
45, 60, 90 or 120 s. Taking into account the 1.5-s interval sampling of the
recordings, these intervals were the average of 20, 30, 40, 60 and 80
measuring points, respectively. To obtain reliable `instantaneous'
measurements, it is important to note that the shorter the time interval
chosen, the more realistic the instantaneous measure should be because of a
lower variation on loads associated with different flow rates and sugar
concentration. On the other hand, the shorter the interval chosen, the higher
the probability of errors produced by spontaneous fluctuations in
CO2 emission due to the cycled pattern of gas exchange. Thus, to
choose the most appropriate time interval, we calculated the coefficient of
variation (V) for each group, load and span time, as follows:
Coefficient of variation or coefficient of variability:
 | (2) |
). We found statistically significant differences of the V values using a one-way ANOVA (F4,147=2.450, P=0.049). A posteriori Tukey analysis did not show significant differences. However, a less conservative a posteriori analysis (LSD) showed that the 30-s interval was significantly higher than the others (LSD, P<0.05), but no other significant differences were found among the others. The fact that we did not detect differences between 45, 60, 90 and 120 s with a test like LSD, which has a higher possibility of finding false differences than more conservative tests, suggests that there are no differences among those intervals. Thus, we finally chose the 45-s average because it was the shortest interval with the low V value without significant differences compared to the longer intervals, i.e. 60, 90 and 120 s.
Data analyses and statistics
Out of a total of 285 metabolic recordings, only those in which the ant
completed the four visits to the feeder, i.e. 250 recordings made by 125 ants
(first and fourth visits), were considered for further analysis.
CO2 emission rate was converted to energy units of µW, assuming
(as is reasonable for carbohydrate-feeding ants) the dissipative catabolism of
glucose. Data were analyzed by one- and two-way analysis of variance (ANOVA)
as well as with linear regressions after logarithmic transformation when
appropriate (Zar, 1984).
Although the metabolism of two foraging visits was measured for each
individual, the average of these two visits was used for statistical analysis
in order to avoid pseudoreplication
(Hurlbert, 1984), except for
the regression between metabolic rate and final crop load where the two visits
were analyzed separately. In all cases, values are given as mean ±
s.e.m. A probability of error P<0.05 was considered statistically
significant.
Although C. rufipes can be considered as a polymorphic species
(Hölldobler and Wilson,
1990), we measured, to facilitate comparison of data, workers of
similar medium size in all experiments.
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An example of a respirometric record from a foraging ant collecting 30% sugar solution at a flow rate of 1.18 µl min–1 is presented in Fig. 2. Three different parts can be recognized on the plot, i.e. before, during and after feeding. Before and after feeding, a clear discontinuous pattern of CO2 production is evident, corresponding to the activity of the ant inside the chamber. The CO2 emission turned out to be more regular during feeding. We compared CO2 emission rates during actual feeding (Fig. 2, between arrows) among treatments.
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To investigate the effect of sucrose concentration on metabolic expenditure
while feeding, we presented individual ants in independent assays with 5
different concentrations of sugar solutions (1, 5, 10, 30 and 50%) at a
constant flow rate of 1.18 µl min–1. Feeding times
increased with increasing sucrose concentration
(Fig. 3A, one-way ANOVA,
F4,69=6.348, P<0.001). Since the sucrose
solution was provided at the same flow rate, the longer feeding times resulted
in larger crop loads with increasing sucrose concentration
(Fig. 3B, one-way ANOVA,
F4,69=11.673, P<0.001). However, the variation
of crop loads and feeding times with sucrose concentration are not exactly the
same because loads were expressed in mass units (mg), and the density of a
sucrose solution depends on its concentration
(Wolf et al., 1984). Metabolic
rate during feeding showed a tendency to increase with increasing sucrose
concentration, although the differences were not significant
(Fig. 3C, one-way ANOVA,
F4,69=0.346, NS).
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;
Paul and Roces, 2003).
Comparing 5 and 30% sucrose solution, feeding times significantly depended on
flow rate (F2,71=54.495, P<0.001), but not on
sucrose concentration (F1,71=0.816, NS). There was no
interaction of both factors, i.e. flow rate and concentration
(F2,71=1.553, NS). In a second two-way ANOVA, we examined
the differences among the three sucrose concentrations at 0.236 and 1.18 µl
min–1. We did not take into account the 2.36 µl
min–1 groups for the reason mentioned above. Feeding time
depended on flow rate (F1,63=54.225, P<0.001)
and concentration (F2,63=11.678, P<0.001), and
the interaction between flow rate and concentration was also significant
(F2,71=6.307, P<0.005).
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Fig. 4B shows an increase of the crop load with increasing flow rates and sucrose concentrations. Comparing 5% and 30% for the three flow rates assayed, we found significant differences of crop load as a function of the nectar flow rate (F2,71=56.985, P<0.001) but not with the nectar concentrations (F1,71=3.164, NS); the interaction between flow rate and concentration was not significant (F2,71=1.682, NS). In a second two-way ANOVA analysis of differences among all concentrations at 0.236 and 1.18 µl min–1 (we again did not take into account the 2.36 µl min–1 groups), we found highly significant differences of crop load as a function of the nectar flow rate (F1,63=27.936, P<0.001) and concentration (F2,63=12.047, P<0.001). The interaction between flow rate and concentration was not significant (F2,71=1.605, NS).
Metabolic rate (µW) varied with increasing flow rate and sucrose concentration (Fig. 4C). Comparing 5 and 30% for the three flow rates assayed, we found no significant differences of metabolic rates as a function of the nectar flow rate (F2,71=2.707, NS) or as a function of sucrose concentration (F1,71=0.571, NS); there was no significant interaction (F2,71=0.107, NS). In a second two-way ANOVA analysis of all concentrations at 0.236 and 1.18 µl min–1, we detected significant differences of metabolic rate with the nectar flow rate (F1,63=9.505, P<0.005), but not with concentration (F2,63=1.067, NS); the interaction term was not significant (F2,71=0.539, NS).
Control measurements for 30% sugar solution gave the following variation in CO2 between the first 4 min (prior to switch on the pump) and the nectar delivery time (during pump on): for 0.236 µl min–1: –0.123±0.236 µl h–1 of CO2 (mean ± s.e.m., N=7), which represents –0.86±1.65% of change with respect to the ant's measurements, for 1.18 µl min–1: 0.321±0.092 µl h–1 of CO2 (mean ± s.e.m., N=9) or 1.89±0.54%, and for 2.36 µl min–1: 0.004±0.192 µl h–1 of CO2 (mean ± s.e.m., N=9) or 0.03±1.12% of CO2 emitted by an ant.
Metabolic rate as a function of increasing crop load during feeding
As mentioned above (Fig. 4),
both crop loading and metabolic rate increased with increasing nectar flow
rate. To determine whether the increase in metabolic rate is a direct
consequence of the load carried, or whether the perceived nectar flow
influences the ant's activity and thus its metabolic expenditure while
feeding, irrespective of the crop load, we compared `instantaneous' metabolic
rates of animals at those times at which they reached similar crop loads.
Both Fig. 5 and Table 1 show the separate effects of the actual crop load and the nectar flow on the `instantaneous' metabolic rates. Nectar flow had a large effect on metabolic rate when controlled for load (for instance, compare the values at rates of 0.236 and 2.36 µl min–1 for a load of 3 mg, Fig. 5). Another way to determine the relationship between metabolic rate and loading is through a linear regression of metabolic rate as a function of the final crop load at the end of the visit for each different experimental group and visit (i.e. first and fourth visits). If the magnitude of loading affects metabolic expenditure, a positive relationship between final crop load and metabolic rate should be expected. Table 2 shows the values of the regression for three different flow rates (0.236, 1.18 and 2.36 µl min–1), five different concentrations (1, 5, 10, 30 and 50%) and two different visits (first and fourth). From the 20 different regressions performed only one was slightly significant (group 2.36 ml min–1, 5%, fourth visit, P=0.039) with load explaining less than 35% of the metabolic rate (Table 2).
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Gain, costs and foraging energetics
Fig. 6 shows the
relationship between the energy spent, directly measured via
respirometry, and the energy gain, which was contained in the nectar collected
by the individual ant, for the different flow rates and sucrose concentrations
assayed. Energy gain was always higher than the energy spent by the ant, even
for the poorest profitability offered, i.e. 0.236 µl min–1
and 1%. Even for the poorest food source, the forager gained ca. ten times of
what it spent. A forager's energy gain–cost ratio significantly
increased to a maximum value of ca. 220 times for the highest profitability
assayed (F1,123=9.630, P<0.005). The positive
correlation clearly shows an increase of the individual metabolic rate with
the profitability of the exploited nectar source.
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Based on the data of costs and gains, it is possible to estimate the
maximum distance traveled by a C. rufipes forager in a foraging trip
with the energy gained during the collection of a nectar load, by using the
following simplified model: Assuming no energy (E) loss, then:
 | (3) |
 | (4) |
Thus,
 | (5) |
). The energy spent for a round foraging trip (the ant
goes unladen and come back to nest loaded) is a function of the mass load and
ant mass. M is mass and GCOTu is the gross cost of
transport of an unladen worker, which has a value of 264 J
kg–1 m–1 for C. rufipes and a cost
of load carriage is 61% that of somatic load carriage
(Schilman and Roces,
2005).
With Eqn 5, the predicted values of maximum distances traveled are between
0.5 to 9 km, assuming no energy losses, for nectar loads ranging between 1 and
6 mg and nectar concentrations between 20 and 60%, which are values observed
in nature (Dreisig, 2000;
O'Dowd, 1979)
(Fig. 7).
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). Therefore
the 50% sugar solution is 7.6 times more viscous than the 10% one. The
similarity of these metabolic rates from different solution viscosities is not
surprising since the delivered flow rate was much lower than the insect's
maximal ingestion rate, which is about 4 µl min–1
(Schilman and Roces, 2003).
However, we did observe a significant increase in metabolic rate as a function
of the sugar solution flow rate (Fig.
4C). Assuming that an ant experiencing a richer food source will
increase its activity and metabolism more than an ant experiencing a poorer
food source, the results showed in Fig.
3C and Fig. 4C
suggest that flow rate is more important than sucrose concentration for the
assessment of resource profitability. This conclusion appears unexpected,
since the range of food source richness used (measured as energy content) was
larger for the sucrose concentrations than for the flow rates. However, it is
suggested that in nature, the amount of nectar found at a source may be a more
reliable measure of its richness, as it depends on both the delivered nectar
flow and the time elapsed since the last visit.
The increases in metabolic rates with increasing flow rates of sugar
solution are unlikely to be a result of an increased activity of the
pharyngeal muscles directly involved in fluid feeding, because they are
relatively small (Paul et al.,
2002), and because there was no increase in metabolic rate between
the nectar flows of 1.18 and 2.36 µl min–1
(Fig. 4C), for which the
ingestion rate has to be varied by a factor of 2. Differences in metabolic
rates with nectar flow could not be explained by intrinsic differences among
ants in different groups, because no significant differences were detected
among experimental groups for the first 4 min of the first visit of the
forager (F8,117=1.269, NS, one-way ANOVA).
In addition, differences could not be the result of CO2
dissolved in the nectar and released in the chamber, because control
measurements without ants did not show an increase in the CO2 with
nectar delivery. Such a potential experimental artifact should be particularly
pronounced in the control groups for two reasons. First, because the nectar
accumulated over time, while in the experimental groups the ant immediately
collected it. Second, because the measuring times during nectar delivery on
control groups were the maximum times measured on the experimental groups,
with most of the ants assayed showing shorter feeding times. However, we found
no evidence of CO2 released from the nectar, with the highest
average variation of CO2 over time being less than 2% of the
CO2 emitted by an ant. The increase of metabolic rates with nectar
flow could be the result of an increased activity of the ants. While feeding,
ants were observed to perform spontaneous interruptions, as previously
described (Schilman and Roces,
2003), briefly running around the source before continuing
feeding. However, since these activity bursts were not quantified, the
question of how a higher nectar flow increased the ant's metabolic rate
remains open. Although a tempting causal explanation for this observed
increase could be the load itself, we have to rule out this possibility
because our results showed no dependence of metabolic rate on crop load
(Fig. 5 and
Table 2). In other words, ants
collecting nectar at a higher flow rate have a higher metabolic rate compared
to ants collecting at lower flows, even when they attain the same crop
load.
We cannot exclude the possibility of an increased metabolic rate resulting
from an increase in the ant's activity as a result of an enhanced feeding
motivation, which is expected to be higher for higher food-source
profitabilities. In a previous study, C. rufipes workers that
previously experienced high nectar flow rates showed a higher activity, in
particular a higher rate of drinking attempts at an experimentally depleted
patch, than workers that experienced a low flow rate
(Schilman and Roces, 2003). In
leaf-cutting ants, Acromyrmex lundi, foragers were observed to
increase their running speed when recruited to a high-quality food source,
independent of the load carried (Roces and
Núñez, 1993). The same was observed in unloaded
leaf-cutting ant workers on their first way to a newly discovered source: they
ran at a faster pace, the higher the quality of the food found by the scout
ants. The information about food quality that caused this increase in speed
was transmitted through recruitment signals
(Roces, 1993). Previous
studies in honeybees also demonstrated an increased of metabolic rate with
increasing sucrose flow rate in free-flying foraging bees, when controlling
for load mass (Balderrama et al.,
1992; Moffatt,
2000), and also in non-flying foraging bees
(Moffatt and Núñez,
1997). Here it is important to note that although honeybees are
also nectar-collecting social insects, they have the ability to increase their
metabolic rates via the activation of the flight muscles and the
associated heat production that increases their thoracic temperature.
It is important to mention that the richness of the food source not only influences the metabolic rate of Camponotus rufipes foragers but also changes their individual trail-laying behavior, leading to an increase in trail-laying responses with increasing sucrose concentration (P.E.S. and F.R., unpublished data), which may cause increased foraging rates at the colony level.
Activity and catabolic flux rates
As might be expected for an unrestrained ant worker in a novel environment,
workers were active throughout the recordings, except for moments while
feeding. Thus each ant group collecting the different flow rates and sucrose
solutions showed a catabolic flux rate higher than that predicted on the basis
of body mass for inactive insects (Lighton
et al., 2001). For example, Lighton et al.'s equation
[(Lighton et al., 2001):
SMR=973M0.856, where the standard metabolic rate, SMR, is
in µW and the body mass M in g] predicts an SMR of 26.72 µW at
25°C for an ant of 15 mg live body mass. In our study, the mean metabolic
rate measured in 6 individual ant workers (mean body mass=14.97 mg) that
collected at a flow rate of 0.236 µl min–1 and 1% sugar
solution concentration at 25°C was 0.793 µl
CO2h–1 mg–1 of live body mass,
which is equivalent to 48.54 µW. Our measurement of metabolic rate was
almost twofold higher than previous measurements for caged ants of the same
species, i.e. 0.43 µl O2h–1
mg–1
(Takahashi-Del-Bianco et al.,
1998), and also than predicted values from the allometric equation
(Lighton et al., 2001).
However, allometric equations of SMR were usually based on measurements on
decapitated insects. In an unidentified Camponotus ant species (mass
about 12 mg), a 1.7-fold increase of metabolic power was found when comparing
measurements between intact and decapitated ants
(Lipp et al., 2005). Thus,
this could be an additional explanation for the difference between the
measured and the calculated values of SMR, besides the potential effects of
locomotion.
Foraging energetics in ants
Energetic measurements of locomotion and load carriage in a wide variety of
ant species showed similar low costs, suggesting that natural selection has
favored efficient load carriage in ants. These low costs favor a positive
gain–cost ratio or energy efficiency in all cases analyzed (e.g.
Baroni-Urbani and Nielsen,
1990; Fewell, 1988;
Fewell et al., 1996;
Weier and Feener, Jr, 1995).
Because of such low energy expenditure in foraging ants, the energetic content
of the food plays a main role in the outcome of any analysis of energetic
efficiency. Consequently, gain–cost ratios varied from 4 for
nectar-collectors (Fewell et al.,
1996) to 1000 for harvester ants
(Fewell, 1988). Comparisons of
foraging energetics in Pogonomyrmex maricopa, which forages
individually, and P. rugosus, which employs a trunk-trail foraging
system, showed an average energy gain–cost ratio of more than 100 for
both species (Weier and Feener, Jr,
1995). This study also showed that for Pogonomyrmex
maricopa and P. rugosus, the estimated energy intake on
successful foraging trips was always greater than energy expenditure in the
field (Weier and Feener, Jr,
1995). Similarly, our results indicate positive gain-cost ratios,
even with the poorest food source assayed
(Fig. 6).
On the one hand, measuring energetic costs of foraging in the laboratory
with a well controlled environment makes it possible to detect subtle
differences, such as the modulation of the metabolic rate by the sucrose flow
rate (Fig. 4C). On the other
hand, laboratory experiments have the disadvantage of giving rise to possible
artifacts in the results. However, a recent field-data validation of
laboratory measurements on ant locomotion
(Lighton and Duncan, 2002)
allows for the extrapolation of our energetic measurements in controlled
laboratory conditions to a model of ant's energetic foraging in the field.
The results presented in this study, together with a recent publication on
locomotion energetics in the same Camponotus species
(Schilman and Roces, 2005),
allowed us to develop a simple model of foraging energetics for the
nectar-feeding ant, C. rufipes. This model shows that single foraging
workers of C. rufipes have an autonomy of about 10 km of maximum
distance traveled with the energy collected in a foraging trip from a
high-quality food source (Fig.
7). A similar distance was calculated for the harvesting ant,
Messor capitatus, from the energetic content of wheat seeds
(Baroni-Urbani and Nielsen,
1990). However, we have to be cautious in taking this
oversimplified model as an indirect measure of colony fitness, because only a
proportion of the workers in the colony are foragers and the energy gathered
by foragers should maintain all colony members, even those workers performing
inside-nest tasks. [Also see discussion elsewhere
(Lighton and Duncan, 2002).]
Future research under field conditions will help make this model more
accurate.
Partial crop loads: time vs energy saving
In foraging honeybees, it was hypothesized that a forager returns to its
hive with partial crop loads in order to maximize its efficiency (ratio of
gain to cost) (Kacelnik et al.,
1986; Schmid-Hempel et al.,
1985). This `energetic' hypothesis found support in some studies
(e.g. Wolf et al., 1989), but
not in others (Balderrama et al.,
1992; Moffatt,
2000), and also Feuerbacher et al.
(Feuerbacher et al., 2003) to
some extent. An alternative explanation is that returning earlier with partial
crop loads increases the probability of information exchange at the colony,
and thus favors colony efficiency, as first suggested by Núñez
(Núñez, 1979;
Núñez, 1982).
This `informational' hypothesis was also investigated in other social insects,
i.e. leaf-cutting ants (Roces,
2002; Roces and
Hölldobler, 1994; Roces
and Núñez, 1993), and the nectar-feeding ant used in
this study (Schilman and Roces,
2003). The results on load-size selection for the three different
systems (i.e. honeybee, leaf-cutting and nectar-feeding ants) support the
informational hypothesis, even though the species considered largely differ in
terms of their energetic expenditures for locomotion and food gathering. For
example, nectar intake by honeybees is a low-cost activity, while flying to
and from the hive and from one flower patch to another is a high-cost activity
(Nachtigall et al., 1989). For
leaf-cutting ants, cutting a leaf fragment is highly expensive
(Roces and Lighton, 1995),
while carrying it back to the nest is much less costly
(Lighton et al., 1987).
Finally, for C. rufipes, both collection and carrying are low cost
activities (the present study) (Schilman
and Roces, 2005). The `informational' hypothesis seems robust
because it helps to explain the results found in three diverse systems, i.e.
three social insect species with different energetic investments during
foraging. In addition, while the `energetic' hypothesis clearly focuses on the
individual level because foraging rules are considered to increase the
efficiency of the individual forager, the `informational' hypothesis
emphasizes the colony level, i.e. strategies that increase the benefit to the
colony as a whole, even at expenses of reduced performance at the individual
(forager) level.
Finally, the calculations of losses and gains during nectar collection,
together with the fact that the cost of load carrying is about 40% cheaper
than carrying its body mass (Schilman and
Roces, 2005), support the hypothesis that saving time (with the
potential increase in colony-wide energy intake via social
recruitment) is more important than saving energy (or increasing individual
forager efficiency) when workers of the nectar-feeding ant C. rufipes
decide to stop drinking and come back to the nest with partially filled
crops.
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Acknowledgments |
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References |
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TOPSummaryIntroductionMaterials and methodsResultsDiscussionReferences |
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