Walking on inclines: energetics of locomotion in the ant Camponotus
Department of Neurobiology, University of Ulm, 89069 Ulm, Germany
* Author for correspondence (e-mail: fritz.lehmann{at}biologie.uni-ulm.de)
Accepted 6 December 2004
![]() |
Summary |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
Key words: insect, ant, Camponotus sp., metabolic rate, locomotion, slope walking, respirometry
![]() |
Introduction |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
Kleiber's classic equation on the relationship between metabolic rate and
body mass states that in mammals, resting metabolism scales in proportion to
the size of the animal to the power of three-quarters. It has been shown that
this allometric exponent applies to most organisms even including plants, and
indicates that resting metabolic rate becomes relatively smaller in larger
organisms (Schmidt-Nielsen,
1984; West et al.,
1997
). Recent studies on scaling laws suggest that the fractal
structure of transportation networks supplying the body tissue with nutrients
and oxygen is the ultimate reason for this inverse relationship
(Banavar et al., 1999
;
Darveau et al., 2002
). During
running, the body mass-specific rate of energy consumption increases linearly
with increasing speed in most animals, whereby the amount of energy used to
run a certain distance is nearly constant, regardless of the animal's actual
running speed. This independence between transport cost and speed was found
generally among running animals (for a review, see
Full, 1997
). Smaller animals
have shorter legs and thus need more steps to cover a certain distance. As a
consequence, the number of contraction-relaxation cycles of the leg
musculature and the associated energy loss, as well as frictional work emitted
into the environment, increases with decreasing body size, forcing the cost of
transport (COT) to increase likewise
(Heglund and Taylor, 1988
;
Taylor and Heglund, 1982
).
Most impressively, this relationship between COT and body size spans
approximately eight orders of magnitude in body mass and approximately 150
different species, including mammals and insects
(Full, 1997
). Kram and Taylor
(1990
) hypothesized that the
rate of energy per unit body mass consumed by the leg muscles is inversely
proportional to the time for which the foot applies force to the ground during
each stride. Since this force-reaction-time depends on step length, which in
turn increases with increasing body mass (larger animals typically have longer
legs), total energy expenditure may remain nearly constant independently of
running speed and body size.
In contrast to SMR and the cost during horizontal locomotion, the relative
work required to move a unit of body mass vertically against the force of
gravity is the same for large and small animals. For this reason, the absolute
cost of vertical locomotion decreases considerably with decreasing body size,
resulting in a tedious task for large mammals to scale steep slopes. The scope
for energy conservation during downhill walking follows corresponding
relationships because in some mammals, such as mice and chimpanzees, part of
the potential energy stored during uphill running can be released during
downhill running if the incline angle is sufficiently small (15°;
Taylor et al., 1972). It has
been suggested that gravity may efficiently accelerate swinging limbs and thus
lower the work done by the leg muscles during downhill running. Steep declines
may be more expensive to negotiate than level terrain or small downhill
inclines. This is due to the effort needed for braking in order to avoid
excessive acceleration (Taylor et al.,
1972
).
The above findings are well-documented for mammals and other vertebrates
(Schmidt-Nielsen, 1984), but
very few studies exist on terrestrial locomotion in small invertebrates such
as insects. Energetic costs of level walking have been examined in cockroaches
(Full, 1997
;
Full et al., 1990
;
Herreid et al., 1981
), flies
(Berrigan and Lighton, 1994
),
crickets (Full et al., 1990
),
beetles (Bartholomew et al.,
1985
; Full et al.,
1990
; Lighton,
1985
; Rogowitz and Chappell,
2000
) and ants (Fewell et al.,
1996
; Jensen and Holm-Jensen,
1980
; Lighton et al.,
1993
; Lighton and Feener,
1989
). The metabolic costs of negotiating ascending or descending
slopes has been addressed only in cockroaches
(Full and Tullis, 1990
;
Herreid et al., 1981
).
Cockroaches are among the largest insect species, yielding body masses of
between 1.0 and 6.5 g and thus overlapping with the lower range of vertebrate
species (Full and Tu, 1990
).
However, the results on cockroaches moving on inclines are not consistent,
either because the energetic costs of locomotion were unexpectedly large and
could not be attributed to the vertical component of transport costs
(Full and Tullis, 1990
), or
because the slope angles investigated were rather small (±5° to
±25°; Herreid et al.,
1981
), yielding ambiguous results.
Here, we investigate the energetic costs of locomotion in the small ant
Camponotus on level substrate and on ascending and descending slopes.
Ants are abundant and one of the ecologically most relevant groups of insects
(Hölldobler and Wilson,
1995). The nest in which a large colony lives and raises its brood
is energetically demanding. Thus, the overall fitness of a colony is directly
related to the success in locating and transporting food to the nest (foraging
efficiency). Foraging efficiency depends on several parameters such as the
nutritional content of the food returned to the nest, foraging distance, load
carrying costs and the gross cost of locomotion. Since this study aims at an
estimation of the relative energy required for vertical transport, the results
of the experiments might provide useful information for determining ecological
significance when comparing the cost of feeding in different ant species.
Examples are ants dwelling in level habitats such as desert ants
(Wehner, 1998
) and species
foraging mainly on vertical structures such as leafcutter ants
(Hölldobler and Wilson,
1995
). The present study further allows for the extension of the
allometric relationships outlined for large mammals regarding metabolic rates
and costs of horizontal transport towards the body mass of small insects.
Previous research on the subject of metabolic rate during running in ants
was pioneered by studies of Jensen and Holm-Jensen
(1980) and continued by
several others (Fewell, 1988
;
Fewell et al., 1996
; Lighton et
al., 1987
,
1993
; Nielsen and
Baroni-Urbani, 1990). The first experiments on the net cost of transport using
unloaded leaf cutter ants Atta colombica were performed by Lighton et
al. (1987
) who estimated the
relationship between metabolic cost and running speed to yield minimum cost of
transport (MCOT) on a treadmill. A major problem in these treadmill
experiments, however, was the fact that the animals were forced to run at
pre-defined speeds. Although later experiments confirmed the measurements of
MCOT made on the treadmill, the treadmill data showed a significant increase
in the y-intercept of MCOT above SMR. Lighton and Feener
(1989
) thus proposed a running
tube respirometer that allowed metabolic costs to be determined during
voluntary locomotion in ants. The data in the present study were obtained
using a running tube respirometer that could be tilted by ±60° with
respect to the horizontal, allowing us to determine the energetic cost of
locomotion in the ant Camponotus at five different inclines. In
conjunction with a new analytical method to correct for Doppler shift that
results from the relative motion of the ant with respect to the air flow
inside the `flow-through' running tube, we determined how metabolic cost
changed when the animals varied their running speed with various inclines.
![]() |
Materials and methods |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
Experimental setup
To select active foragers that were prepared to walk in the respirometric
chamber, we erected a scaffold of wooden sticks in the plastic container.
Individual ants that actively explored the scaffold were then placed in the
respirometric running chamber (adapted from
Lighton and Feener, 1989). For
our initial experiments (N=10 minor workers), the chamber
was a brass rail (493 mm length, 8 mm width, 9 mm height) covered with a
Perspex plate. To increase the visual contrast between ant and rail for video
analysis, we later exchanged this chamber for a Perspex running chamber
(N=36 minor workers; 500 mm length, 10 mm width, 7 mm
height) with a white painted floor. We combined data derived from both
chambers, because both experimental procedures yielded consistent results. A
small steel ball (diameter 2 mm) in the chamber could be swayed by a
hand-operated magnet to coax the animal into running
(Jensen and Holm-Jensen,
1980
). Resting metabolic rates of decapitated workers were
determined in a small conventional respirometric chamber
(Lighton, 1991
). After each
test we determined wet body mass of the ants and fixed the animals in ethanol
(90%) for further analysis of head size (see paragraph on the estimation of
resting metabolic rate).
Video monitoring
We monitored the ant's movement inside the respirometric chamber using a
commercial digital video camera (DCR-TRV120E, Sony, Cologne, Germany) mounted
approximately 50 cm above the chamber. The entire experimental arrangement
could be tilted to adjust the incline angle of the chamber between 60° and
-60° with respect to the horizontal. To synchronize respirometric
measurements and the position sampling of the ant inside the chamber, we
arranged a light-emitting diode next to the chamber. We connected the diode
signal to the external input of the CO2 analyser and flashed the
diode at the beginning and the end of each walking sequence in order to these
mark these particular points in time. To analyse the costs of incline
locomotion we tested 41 ants while they were walking on five different
inclines, 0°, ±30° and ±60°. Five ants were tested
while running on only one incline (0°, N=3; -60°,
N=1) or two inclines (0°, -30°, N=1). Depending on
the activity of the individual ant, we recorded on average 1-3 running
sequences per incline.
Flow-through respirometry
We recorded CO2 release of the animals using a computerized
flow-through respirometry system. Room air was cleaned, removing water vapour
and CO2 with a Drierite/ascarite column, and pulled through the
respirometric chamber and the attached CO2 analyser (LI-7000,
Li-cor, Lincoln, NE, USA) at a flow rate of 1000 ml min-1. Data
were recorded at 5 Hz sampling frequency and subsequently converted into body
mass-specific CO2 emissions (ml g-1 h-1) for
further analysis. We used a respiratory quotient of 0.71 (28.0 J
ml-1 CO2; fat metabolism) to calculate body
mass-specific metabolic power (Lighton and
Wehner, 1993). Baseline corrections were performed before and
after each experimental session by recording the gas concentration of the
empty chamber for 3 min.
Estimation of resting metabolic rate
To estimate the contribution of SMR to total running metabolic rate, we
found it crucial to determine SMR under two established experimental
conditions: in intact but motionless ants, and in decapitated ants.
Decapitated ants are typically used to address breathing patterns such as the
discontinuous gas exchange cycle. Both approaches are associated with
potential errors, making a reliable estimate of SMR in ants difficult. Resting
metabolic rates in intact animals might be higher than expected due to
energetic costs associated with small changes in leg or body position. In
contrast, decapitated ants, although typically motionless, might produce an
SMR that is too low, because the metabolism of the head (19.6% of the body
mass in Camponotus) is not considered.
To determine metabolic rate in inactive but intact minors, we measured CO2 emissions after the animal had stopped running and settled into a characteristic resting posture at 0° incline (N=15 ants). To avoid an overestimation of resting CO2 emission due to processes of paying off any anaerobic debts, or to a delayed release of CO2 through the tracheal system, we excluded at least the first 5 s from the analysis after the animal had settled down. We determined resting condition as described below, and throughout the experiment, the ants were monitored continuously using conventional video recording. After each experiment, we analysed the video sequences using a motion-tracking program (MaxTRAQ, Innovision, Columbiaville, MI, USA) and subsequently constructed an ethogram of the ants' locomotor behaviour. The computer software allowed us to quantify the movement of antennae, legs and the body of the animal on a frame-by-frame basis. We defined resting condition as the time in which no body, leg or antennal movements were measurable in consecutive video frames. To avoid any confounding effects of costs associated with movement in this analysis, we disregarded time sequences showing even the smallest changes in the orientation of the animal's antennae.
Although all minor workers stemmed from the same colony and were selected according to their locomotor activity, we observed two different types of gas exchange in the resting animals: discontinuous and continuous breathing behaviour. A discontinuous gas exchange cycle (DGC) was observed in 11 out of 15 tested decapitated minor workers and in 3 out of 15 intact animals. Fig. 1A-D illustrates this mode of respiration, showing sample recordings from decapitated minor workers. Small amounts of CO2 were released during the flutter phase (F-phase) indicated by the small spikes with gradually increasing amplitude, followed by the open phase (O-phase, large spikes), where most of the gas exchange took place, and a brief period where the tracheal spiracles were completely closed (C-phase, baseline without spikes). Mean DGC frequency in decapitated ants was 0.8±0.3 mHz (N=11, n=86 DGCs) and mean rate of CO2 release was 0.19±0.05 ml g-1 body mass h-1 (N=15, DGC and continuous breathing), yielding mass-specific metabolic power of 1.48±0.43 mW g-1 body mass. In contrast to decapitated animals, intact ants showed an unusual high DGC frequency that was approximately 15-fold higher and amounted to 12.2±3.6 mHz (N=3; n=52 breathing cycles, Fig. 1E). Intact ants released an average of 0.32±0.10 ml CO2 g-1 body mass h-1 (N=15, DGC and continuous breathing), which corresponds to mean metabolic power of 2.51±0.78 mW g-1 body mass. Despite the large difference in DGC frequency between both experimental groups, CO2 release and metabolic power were only 1.7-fold higher in intact ants compared to decapitated workers (ANOVA, P<0.001). SMR during continuous breathing tended to be slightly higher than SMR during DGC in both the decapitated ants (0.24 ±0.04 ml g-1 h-1 vs 0.20±0.05 ml g-1 h-1) and the intact animals (0.37±0.12 ml g-1 h-1 vs 0.29±0.05 ml g-1 h-1). However, we did not find a significant difference in either case (ANOVA, P>0.05). In sum, the data mentioned above suggest that SMR in Camponotus is independent of the breathing pattern but varies slightly between intact and decapitated animals. Since SMR only accounts for approximately 12% (decapitated) and 20% (intact) of total metabolic rate during horizontal running, we did not consider this difference in SMR further.
|
Data evaluation and statistics
The dark ants were clearly visible against the white background in the
video recordings, facilitating semi-automatic tracking of ant position in the
respirometry chamber (MaxTRAQ). To match video recording to the CO2
sampling rate, we reduced the video frame rate from 50 Hz half-frame mode to 5
Hz. Running speed was calculated from the ant's positions in adjacent video
frames. To analyse the relationship between CO2 release and running
speed, we averaged the CO2 data of each ant in separate speed bins.
Bin width was set to 10 mm s-1. A value of the 20 mm s-1
bin, for example, thus represents the mean of all measured CO2
values while the ant was running at speeds between 15 and 25 mm
s-1. Data were analysed using custom-made programming routines
developed in LabTalk (Origin 5.0, Microcal, Northampton, MA, USA). Unless
stated otherwise, all data are given as means ±
S.D. Differences between mean values were assessed by
employing the two-sided statistical
test. Linear regression, polynomial fit lines and Gaussian curves for normal
distributions were calculated using a commercial statistics program (Origin
5.0).
Doppler shift and wash-out time correction
Depending on the relative speeds between the walking ant and the air
current through the respirometric chamber, Doppler effects may occur
(Berrigan and Lighton, 1994).
To correct for possible Doppler shifts, we converted the delay associated with
the ant's position in the chamber (transport time for air parcel from and to
analyser) into a corresponding time shift of the CO2 sample point
(red curve in Fig. 2A). This
shift dated the measured CO2 back to the time of release by the
animal. To stay within the synchronized video frame and gas sample rates of 5
Hz, time-shifted CO2 values were distributed on two adjacent data
points where necessary. For example, when the time shift i was 3.4
data points, we distributed 60% of the CO2 value on data point
i-3 and 40% on data point i-4. All data traces were
subsequently filtered with a running average of 1.4 s. The time delay for
CO2 released by the animal was 1.03 and 1.62 s from the inlet to
the outlet of the chamber using the brass rail and Perspex chamber,
respectively.
|
|
|
![]() |
Results |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
The statistical analysis suggests that the increase in metabolic rate is
linearly correlated with speed for the two downhill inclines -60° and
-30°, and level walking (-test,
P<0.05, linear fit, -60°:
y=1.69-7.9x10-3x, r2=0.85;
-30°: y=1.73-10.2x10-3x,
r2=0.96; horizontal:
y=1.57-9.2x10-3x, r2=0.92, 13
speed bins; Fig. 4;
Sachs, 1992
). In contrast, the
cost of running on uphill slopes (30° and 60° inclines) appears not to
be linearly correlated with running speed
(
-test, P>0.05). However,
because only a small number of animals achieved running speeds above 90 mm
s-1 (mean N=25 ants for speeds below 100 mm s-1
vs mean N=12 ants for speeds above 90 mm s-1), in
conjunction with the short running time at higher speeds (see Discussion), we
tested the data on linearity using the 10 lower speed bins only. In this case,
metabolic data appear to be linearly correlated on all tested inclines
(
-test, P<0.05) and all
slopes were statistically identical
(
-test on slope, P>0.05).
Mean slope for the lower speed range, averaged over the five inclines, was
approximately 0.010 (y=1.59+0.010x, r2=0.93,
P<0.0001, N=10, red dots,
Fig. 4C). Statistical analysis
of possible differences in metabolic rate between the individual speed bins of
each respective incline demonstrated that in none of the speed ranges was
there a significant difference between the population means (ANOVA, d.f.=4;
P>0.05 for all 13 speed bins) and the population variances (ANOVA,
Levene's test, d.f.=4; P>0.05).
Metabolic rate and direction of air flow
To avoid extensive Doppler shifts of the CO2 signal in
flow-through respirometry measurements, we favoured high air flow speeds of
approximately 232 mm s-1 (brass rail) and 238 mm s-1
(Perspex rail). These values are approximately twice the maximum running speed
we measured in single walking ants (approximately 170 mm s-1,
Fig. 2B). As a consequence, an
animal always faced head wind when it ran against the direction of air flow
and always tail wind when running with the direction of air flow. The relative
flow speeds of head and tail wind with regard to the animal body, in turn,
depended on the ant's own running speed. An increase in running speed resulted
in an increased head-wind speed when the animal moved against the direction of
flow, and in a decreased tail-wind speed when the animal moved with the
direction of air flow. Since the running speed was always smaller than the air
speed inside the tube, this relationship was maintained throughout the entire
range of running speeds.
In Fig. 4 we sorted both
walking conditions (head and tail wind, respectively) into the same bins,
ignoring the energetic costs that might be associated with the difference
between walking with strong head and tail winds. To evaluate the relationship
between relative air speed and energetic costs in the running ant, we
estimated the difference in metabolic rate (a-b) for time periods when the ant
walked against (a) and with (b) the direction of air flow, and subsequently
pooled these data over all five inclines of the chamber. The relative
difference between head and tail wind speed (relative running speed) is thus
twice the running speed of the animal over ground
(Fig. 5A). For example, a
relative running speed of 80 mm s-1 indicates that the
animal faced an increase of 40 mm s-1 in head wind while walking
against the air flow, and a 40 mm s-1 decrease in tail wind while
walking with the direction of the air flow. The data suggest that the relative
difference in costs associated with different strength of head and tail wind
increased with increasing running speed and followed quite accurately a
`speed-squared' relationship (polynomial fit,
y=0.016+2.3x10-5x2,
r2=0.98, 2/d.f.=9.5x10-4;
Fig. 5A). Similar coefficients
were found for a polynomial fit to data determined during horizontal walking
only (y=-0.03+2.0x10-5x2,
r2=0.97,
2/d.f.=2.3x10-3).
|
Walking on inclines
The main objective of the present study was to examine the energy
consumption during walking on declining and ascending slopes in small ants.
Thus, in contrast to Fig. 5A,
where data from all inclines were pooled to examine the relationship between
metabolic rate and relative running speed, we pooled metabolic rates at all
walking speeds in order to study the effect of slope on energy consumption in
the small insect (Fig. 5B). As
suggested previously by the statistics given above, in most cases we did not
find significant differences between the energy requirements for walking on
different slope angles (ANOVA, P>0.05), except for the difference
between the 30° decline slope and level walking (0° inclination,
ANOVA, P<0.05, Fig.
5B). Pooling data across all speeds, however, might have obscured
small but significant effects of slope on the speed-dependency of locomotion,
even though the general relationship appears similar for all slope angles
(Fig. 4). Thus, to evaluate the
differences in energy consumption between level and slope walking for every
single speed bin, we calculated the differences by subtracting mean metabolic
rates at horizontal walking from the metabolic rate during slope walking and
plotted the differences for each speed bin ranging from 0 to 120 mm
s-1 (Fig. 6).
|
Superficially there was little difference in energy consumption when comparing incline running with horizontal running. Up to running speeds of 90 mm s-1, the differences were small, reaching a maximum value of ±0.4 ml g-1 h-1, which is a value close to SMR in these ants. A consistent feature of the data sets obtained from the four inclines is their negative gradient up to running speeds of 90 mm s-1 (linear regression between 0 and 90 mm s-1 speed: -60°: y=0.19-0.003x, r2=0.62, P=0.007; -30°: y=0.26-0.002x, r2=0.59, P=0.009; 30°: y=0.05-0.001x, r2=0.42, P=0.04; 60°: y=-0.004-0.002x, r2=0.16, P=0.25; Fig. 6). None of the regressions slopes were different when tested against each other (7 combinations, ANOVA, P>0.05), except for the comparison between -60° and 30° inclines (ANOVA, P<0.05). Thus, with increasing walking speed the difference in energy consumption between moving on level and inclined surfaces decreased and even resulted in negative differences in some cases. Although most of the linear regression lines suggest a significant decrease in the relative change of metabolic rate with increasing running speed, the changes are small and do not yield more than 0.28 ml g-1 h-1 (18% of the 1.5 ml g-1 h-1 mean metabolic rate at 0° slope) difference in metabolic rate below 100 mm s-1 walking speed.
Above 90 mm s-1 running speed the differences between level and slope walking became more pronounced. Uphill walking (positive incline angles) with maximum speed (120 mm s-1) appeared to be approximately 35% (60°) and 44% (30°) less expensive than level walking (Fig. 6C,D). In contrast, downhill walking (negative incline angles) with maximum speed was more costly by 17% (-60°) and 32% (-30°) than walking on a horizontal surface (Fig. 6A,B).However, none of these values were statistically different from each other (6 combinations, ANOVA, P>0.05). In sum, it is surprising that at high running speeds, uphill running tended to be energetically more favourable than level running, while downhill running caused an increase in metabolic rate compared to running in the horizontal.
![]() |
Discussion |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
Respiratory pattern during running
The spiracles of the tracheal system in many insects function as barriers
that control gas exchange between the tracheae and tracheoles, and the outer
environment. It has been shown previously that in the ant Camponotus,
water leaves the tracheal system when the spiracles open for gas exchange
(Lighton, 1992;
Lighton and Garrigan, 1995
).
Recordings of breathing behaviour in various insects support this observation,
which has led to the assumption that DGC evolved as a mechanism for reducing
rates of respiratory water loss (Snyder et
al., 1995
; see reviews by
Miller, 1981
;
Kestler, 1985
;
Slama, 1994
). During
locomotion in Camponotus, DGC completely ceased, and all animals
breathed continuously during walking (Fig.
2). This finding is consistent with previous studies on breathing
behaviour in insects during locomotion (for reviews, see Lighton,
1994
,
1996
) and probably reflects
the increased oxygen requirements during locomotion. However, in the desert
ant Pogonomyrmex rugosus, Lighton and Feener
(1989
) reported a
discontinuous breathing pattern while the animal was walking with constant
speed within a respirometric chamber. This behaviour was interpreted as an
example where the environment has constrained breathing behaviour to avoid
high water loss under xeric conditions
(Lighton, 1996
). An
alternative explanation of this finding is that the respiratory spikes were
artifacts produced by Doppler shifts due to flow-through respirometry. As
outlined in the Materials and methods section, an ant walking exactly with the
speed of air flow in the respirometric chamber would exchange O2
and CO2 only with the air parcel it is travelling in. It appears
evident that under such conditions the ant produces `pseudo' spikes of
CO2 release once it stops or reverses running direction at the end
of the chamber. At this moment the accumulated CO2 is shed toward
the gas analyser, which results in large CO2 peaks similar to those
produced by blowflies Protophormia terraenovae walking in a similar
respirometric chamber (Berrigan and
Lighton, 1994
). Under these experimental conditions, Doppler
correction of the CO2 samples appears to be necessary. This can
only be achieved if the speed of air flow inside the respirometric chamber
exceeds forward speed of the walking animal. The disadvantage associated with
high air speeds inside the chamber, however, is a reduction in signal-to-noise
ratio of gas samples, potentially limiting the size of the animal that can be
tested using flow-through respirometry. For example, in the present study
maximum CO2 concentrations in the sampled gas amounted to just
about 1.0 p.p.m. air, with a flow speed of 235 mm s-1 inside the
running tube (1000 ml min-1 flow rate). In the case of the walking
desert ant Pogonomyrmex, the flow speed inside the chamber was 21 mm
s-1, and the authors supposedly did not correct for Doppler
effects. A simple analytical model shows that, at an average walking speed of
42 mm s-1 and a chamber length of 1 m, the ants would have had to
run back and forth approximately 6 times within the 5 min measurement period
to produce Doppler artefacts corresponding to the measured data. Surprisingly,
this number of runs is similar to the 6 CO2 spikes per 5 min
observed by Lighton and Feener
(1989
), suggesting that
Doppler effects might have shaped the recorded signal.
Metabolic cost of locomotion
The cost for locomotion on inclines may be split into at least four
components: (i) resting metabolism of the animal, (ii) the energetic cost for
locomotion in the horizontal plane, (iii) metabolic cost to transport body
mass vertically, and (iv) (potentially) energy needed to overcome viscous air
friction. The examination of the costs of vertical transport was the initial
and main objective of the present study.
Horizontal walking
Fig. 4C shows that metabolic
rate in ants walking in the horizontal is at least approximately fourfold
higher than resting metabolism. This finding is consistent with previous
studies on the costs of walking that have demonstrated a twofold increase
during intermittent activity of an ant
(Lighton and Wehner, 1993) and
a 6- to 11-fold increase during level locomotion in cockroaches
(Herreid et al., 1981
;
Herreid and Full, 1984
;
Full and Tullis, 1990
).
Limiting our analysis to walking speeds below 100 mm s-1, we found
a linear relationship between energy consumption and speed at all inclines. A
linear relationship between metabolic rate and walking speed has also been
demonstrated consistently in mammals
(Taylor et al., 1982
; reviewed
in Heglund and Taylor, 1988
)
and insects (Full, 1997
). As a
consequence of a linear relationship, the cost of horizontal transport (COT)
is constant and independent of walking speed. In our 12 mg
Camponotus, transport costs were about 130 J g-1
km-1. The COT for Camponotus is similar to that reported
for other insects with similar body mass, varying approximately between
150-200 J g-1 km-1
(Berrigan and Lighton, 1994
;
Lighton and Feener, 1989
;
Lighton et al., 1993
).
In the few experimental studies where energy consumption saturated towards
higher locomotor speeds, similar to the present data set, researchers
attributed their findings to gait switching between lower and higher walking
speeds (Bartholomew et al.,
1985; Hoyt and Taylor,
1981
). In the present study we did not observe indications for use
of different gaits in Camponotus, such as different preferred speeds
or even discontinuous speed distributions
(Fig. 7A). Instead, the data
were scattered around small walking speeds and a simple Gaussian fit seems to
describe the speed histograms sufficiently. However, it has been shown
previously that the desert ant Cataglyphis bombycina changes gait,
from the tripod gait commonly employed at lower speeds to the tetrapod gait at
higher speeds (Zollikofer,
1994
). A possible explanation for this difference in the use of
gaits between the two ant species might be that Cataglyphis reaches
much higher running speeds of up to 1 m s-1 compared to
Camponotus, which reaches a maximum speed in the running tube of
approximately 0.17 m s-1. The much higher running speed of
Cataglyphis even holds when considering running speed in terms of
body lengths per unit time, since both species are approximately the same size
(Lighton and Wehner,
1993
).
|
However, a change in gait might not be the only reason for energy
consumption levelling off towards higher walking speeds in
Camponotus. An alternative explanation is that brief running
sequences at high walking speeds may favour misassignment of CO2
release. With brief and rapid walking bouts, the probability is high that
significant CO2 release occurs after the ant has already
decelerated to lower speeds. Likewise, the ants may have employed anaerobic
metabolic pathways during locomotion that could have influenced the
respirometric recordings (Hoback and
Stanley, 2001). It has been shown, for example, that during
jumping in locusts and grasshoppers phosphate stores are depleted up to 70% in
conjunction with accelerated glycolysis (30%). This was measured by an
increase in L-lactate
(Hitzemann, 1979
). In the
desert harvester ant Pogonomyrmex rugosus, Lighton and Bartholomew
(1988
) measured a mean
respiratory quotient (RQ) of 0.796 that changed with ambient temperature
(10-45°C). Although this change was small and not significantly
temperature dependent, it might indicate that ants could potentially employ
anaerobic metabolism during locomotor behaviour. To achieve the best
correlation between locomotor activity and CO2 release in our
experiments, we corrected our CO2 traces with the mean delay of 2.4
s, as derived from cross correlation analysis (see Materials and methods).
Nevertheless, longer delays may exist between walking activity and
CO2 release, which would be especially critical for the evaluation
of short time intervals. This assumption is supported by the data presented in
Fig. 7 illustrating the general
preference of the animals for short walking distances
(Fig. 7B), in conjunction with
low walking speeds (Fig. 7A).
In summary, the effects mentioned above might lead to an underestimation of
CO2 release at high running speeds and, less pronounced, an
overestimation of metabolic rate at lower walking speeds. The observation that
the increase in metabolic rate with increasing locomotor speed apparently
levels off beyond approximately 70 mm s-1 may thus partly be
attributed to the much rarer occurrence of higher walking speeds. As a
consequence, we disregarded walking speeds above 90 mm s-1 in the
evaluation and further discussion of our data (open bars in
Fig. 4 representing less than 3
s total recording time).
Walking on inclines
The finding that the metabolic rate of walking ants is rather independent
from the slope of the substrate appears surprising when considering the vastly
different energy requirements for level walking, ascent and descent in large
vertebrates (Taylor et al.,
1972; reviewed in
Schmidt-Nielsen, 1984
). Even
considering the sparse existing data on insects, we expected some change in
the locomotor costs of small Camponotus walking on ascending or
descending slopes (see Full and Tullis,
1990
; Herreid et al.,
1981
). A probable explanation for our result is that the relative
cost of vertical locomotion, caused by the gain in potential energy, becomes
progressively smaller in smaller animals, reflecting the relatively larger
cost of basic metabolism (Banavar et al.,
1999
). For example, a Camponotus minor worker with an
average body mass of 12 mg requires 5.89 µW or 0.49 mW g-1 body
mass of mechanical power for the vertical transport component when scaling a
60° ascent at a speed of 100 mm s-1
(Fig. 4). Assuming that the
muscular system of the ant converts metabolic energy into mechanical power
with an efficiency of 20%, that is about the upper limit to be expected for
extra loads (Taylor et al.,
1980
), this value results in metabolic power requirements for
vertical transport of approximately 30 µW or 2.5 mW g-1 body
mass. In comparison, energy consumption measured during horizontal walking at
similar speed amounts to 20 mW g-1 and is approximately eightfold
higher. In this perspective, and considering the variation inherent in
CO2 measurements during walking, it is not surprising that walking
on different inclines did not produce noticeable changes in energy consumption
(Fig. 5B).
Eventually, this result might stimulate an ongoing discussion regarding the
capability of ants to gauge the incline of foraging paths in uneven terrain
(Wohlgemuth et al., 2001).
Ants do not use optical flow for distance measurements
(Ronacher et al., 2000
), and
the results of this study appear to refute an energy-based mechanism for slope
angle measurements in small ants such as Camponotus.
Metabolic rate and flow speed
One of the most puzzling results in this study is the dependency of
metabolic rate on the head wind that the animal experiences during walking
(Fig. 5A). The data demonstrate
that there is little difference in energetic cost associated with head or tail
wind at low running speeds. In other words, when the animals experienced
almost equal strengths of head or tail wind while walking back and forth
inside the respirometric chamber at low speeds, we only measured an
insignificant difference in metabolic rate. With increasing running speed, the
difference between head and tail wind speeds changed and resulted in a
`speed-squared' increase in metabolic rate with increasing speed. At a running
speed of 100 mm s-1 (=335 mm s-1 head wind vs
135 mm s-1 tail wind) the ants released up to 0.93 ml
g-1 h-1 more CO2 while running against a head
wind than while running with a tail wind. This value compares to a mean value
of total metabolic activity of approximately 2.5 ml CO2
g-1 h-1 (Fig.
4C). Under our limited experimental conditions, it thus seems that
at a walking speed of 100 mm s-1, wind direction and strength may
account for up to 36% difference in metabolic rate. It is difficult to assess
the ecological significance of that finding but we believe that our results
might have some importance for animals foraging in windy environments.
We considered body friction as the most likely explanation for the observed
increase in energetic cost with increasing head wind, assuming that
Camponotus move in a domain of low Reynolds numbers. We estimated
Reynolds number, Re, for motion of the ant's body using the following
equation:
![]() | (1) |
where u is walking speed, c is the characteristic length
of the animal (body length), is air density, and
is kinematic
viscosity of air. For Camponotus minors with a body length of
approximately 10 mm, Re ranges from approximately 7 at a walking
speed of 10 mm s-1, to approximately 110 at the maximum running
speed measured in a single animal of 170 mm s-1. The low
Re suggest that viscous drag increases, as does energy expenditure,
when running speed increases. We derived a rough estimate of viscous drag,
D, according to Stoke's Law for laminar flow around a sphere with
radius r moving at low Re:
![]() | (2) |
where µ is dynamic viscosity of air. For animals that face a head wind of 335 mm s-1 at a walking speed of 100 mm s-1, for example, the cost to overcome viscous drag amounts to approximately 0.19 µW (0.016 W kg-1 body mass) of metabolic power. This surprising result is obtained when assuming 20% muscle efficiency and a radius of 1 mm for the ant's head. In comparison, the measured metabolic power for running is 86 µW, as noted above, and a value of 0.19 µW alone accounts for approximately 3% of the vertical transport cost during 60° uphill walking in Camponotus. In sum, the prediction derived from the simple analytical model is far too low and cannot explain the increase in metabolic rate associated with an increase in head-wind speed. An alternative explanation, though vague and able to account for only a fraction of the high power requirements, might be viscous drag on the legs, which is potentially able to outscore drag on head, thorax and gaster. Since energetic cost due to air friction (Stoke's friction) depends on the running speed squared, even small variations in leg movements might affect the power requirements for walking. In conclusion, we cannot offer a reasonable explanation for the finding presented in Fig. 5A, because the quantitative reasons for the observed relationship between metabolic rate and increasing running speed remain unclear.
Conclusions
The results of this study demonstrate that the energetic costs associated
with vertical transport in the comparatively small insect Camponotus
are small and do not significantly change the cost of transport within a range
of slope angles varying between ±60° (-30° appears to be an
exception). However, since the contribution of vertical transport cost to the
total cost of locomotion scales with the body mass of an animal, body mass
should constrain walking behaviour in larger insect species or when the ant is
heavily loaded with food or prey. Our results show that the metabolic
requirements for walking in unloaded Camponotus are within the range
expected from data obtained with other insects and small poikilotherms, and
these data are consistent with allometric scaling laws.
Nevertheless, the ability of an animal to walk on inclines might not depend
exclusively on the maximum mechanical power produced by the leg muscles but
also on other factors, such as the general biomechanics of the locomotor
system and the animal's ability to stay attached to the ground during slope
walking. The walking chamber in this study had a smooth surface and may thus
have allowed the ants to employ `wet adhesion' due to a liquid film secreted
by the pads of the ants' tarsi (Federle et
al., 2004). Desert ants such as Cataglyphis, in contrast,
move in rough terrain and loose sand
(Wehner, 1998
), and walking is
assumed to be more challenging. As a consequence, future research on the
evaluation of the significance of substrate structure to the costs of both
horizontal and vertical locomotion should allow us to draw a more
comprehensive picture of the overall energy budget during walking of small and
medium sized insects such as ants.
![]() |
Acknowledgments |
---|
![]() |
References |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
Alexander, R. M. (1991). Energy-saving mechanisms in walking and running. J. Exp. Biol. 160, 55-69.[Abstract]
Banavar, J. R., Maritan, A. and Rinaldo, A. (1999). Size and form in efficient transportation networks. Nature 399,130 -132.[CrossRef][Medline]
Bartholomew, G. A., Lighton, J. R. B. and Louw, G. N. (1985). Energetics of locomotion and patterns of respiration in tenebrionid beetles from the Namib Desert. J. Comp. Physiol. B 155,155 -162.
Berrigan, D. and Lighton, J. R. B. (1994). Energetics of pedestrian locomotion in adult male blowflies, Protophormia terraenovae (Diptera: Calliphoridae). Physiol. Zool. 67,1140 -1153.
Darveau, C. A., Suarez, P. K., Andrews, R. D. and Hochachka, P. W. (2002). Allometric cascades as a unifying principle of body mass effects on metabolism. Nature 417,166 -170.[CrossRef][Medline]
Federle, W., Baumgartner, W. and Hölldobler, B.
(2004). Biomechanics of ant adhesive pads: frictional forces are
rate- and temperature dependent. J. Exp. Biol.
207, 67-74.
Fewell, J. H. (1988). Energetic and time costs of foraging in harvester ants, Pogonomyrmex occidentalis. Behav. Ecol. Sociobiol. 22,401 -408.[CrossRef]
Fewell, J. H., Lighton, J. R. B. and Harrison, J. F. (1996). Energetics of foraging in the giant tropical ant Paraponera clavata. Oecologia 105,419 -427.[CrossRef]
Fish, F. E., Frappell, P. B., Baudinette, R. V. and Macfarlane,
P. M. (2001). Energetics of terrestrial locomotion of the
platypus Ornithorhynchus anatinus. J. Exp.
Biol. 204,797
-803.
Full, R. J. (1997). Invertebrate systems from a comparative viewpoint: locomotor systems. In Handbook of Comparative Physiology (ed. W. Dantzler), pp.853 -930. New York: Oxford University Press.
Full, R. J. and Tu, M. E. (1990). Mechanics of six-legged runners. J. Exp. Biol. 148,129 -146.[Abstract]
Full, R. J. and Tullis, A. (1990). Energetics of ascent: insects on inclines. J. Exp. Biol. 149,307 -317.[Abstract]
Full, R. J., Zuccarello, D. A. and Tullis, A. (1990). Effect of variation in form on the cost of terrestrial locomotion. J. Exp. Biol. 150,233 -246.[Abstract]
Heglund, N. C. and Taylor, C. R. (1988). Speed, stride frequency and energy cost per stride: how do they change with body size and gait? J. Exp. Biol. 138,301 -318.[Abstract]
Herr, H. M., Huang, G. T. and McMahon, T. A.
(2002). A model of scale effects in mammalian quadrupedal
running. J. Exp. Biol.
205,959
-967.
Herreid, C. F. and Full, R. J. (1984). Cockroaches on a treadmill: aerobic running. J. Insect Physiol. 30,395 -403.[CrossRef]
Herreid, C. F., Full, R. J. and Prawel, D. A. (1981). Energetics of cockroach locomotion. J. Exp. Biol. 94,189 -202.
Hitzemann, K. (1979). Untersuchungen über den Energie-Stoffwechsel in der Sprungmuskulatur von Locusta migratoria (L.). Thesis, University of Münster, Germany.
Hoback, W. W. and Stanley, D. W. (2001). Insects in hypoxia. J. Insect Physiol. 47,533 -542.[CrossRef][Medline]
Hölldobler, B. and Wilson, E. O. (1995). The Ants. Berlin: Springer-Verlag.
Hoyt, D. F. and Taylor, C. R. (1981). Gait and the energetics of locomotion in horses. Nature 292,239 -240.
Jensen, T. F. and Holm-Jensen, I. (1980). Energetic cost of running in workers of three ant species, Formica fusca L., Formica rufa L., and Camponotus herculeanus L. (Hymenoptera, Formicidae). J. Comp. Physiol. 137,151 -156.
Kestler, P. (1985). Respiration and respiratory water loss. In Environmental Physiology and Biochemistry of Insects (ed. K. H. Hoffmann), pp.137 -186. Berlin: Springer-Verlag.
Kram, R. and Taylor, C. R. (1990). Energetics of running: a new perspective. Nature 346,265 -267.[CrossRef][Medline]
Lighton, J. R. B. (1985). Minimum cost of transport and ventilatory patterns in three African beetles. Physiol. Zool. 58,390 -399.
Lighton, J. R. B. (1991). Measurements on insects. In Concise Encyclopedia of Biological and Biomedical Measurement Systems (ed. P. A. Payne), pp.201 -208. Oxford: Pergamon.
Lighton J. R. B. (1992). Direct measurement of
mass loss during discontinuous ventilation in two species of ants.
J. Exp. Biol. 173,289
-293.
Lighton, J. R. B. (1994). Discontinuous ventilation in terrestrial insects. Physio1. Zool. 67, 42-162.
Lighton, J. R. B. (1996). Discontinuous gas exchange in insects. Annu. Rev. Entomol. 41,309 -324.[CrossRef][Medline]
Lighton, J. R. B. and Bartholomew, G. A. (1988). Standard energy metabolism of a desert harvester ant, Pogonomyrmex rugosus: effects of humidity, temperature, body mass and group size. Proc. Natl. Acad. Sci. USA 85,4765 -4769.[Abstract]
Lighton, J. R. B. and Feener, D. H., Jr (1989). A comparison of energetics and ventilation of desert ants during voluntary and forced locomotion. Nature 342,174 -175.[CrossRef]
Lighton, J. R. B. and Garrigan, D. (1995). Ant breathing: Testing regulation and mechanism hypotheses with hypoxia. J. Exp. Biol. 198,1613 -1620.[Medline]
Lighton, J. R. B. and Wehner, R. (1993). Ventilation and respiratory metabolism in the thermophilic ant, Cataglyphis bicolor (Hymenoptera, Formicidae). J. Comp. Physiol. B 163,11 -17.
Lighton, J. R. B., Bartholomew, G. A. and Feener, D. H. (1987). Energetics of locomotion and load carriage and a model of energy cost of foraging in the leaf-cutting ant Atta colombica. Physiol. Zool. 60,524 -537.
Lighton, J. R. B., Weiler, J. A. and Feener, D. H.
(1993). The energetics of locomotion and load carriage in the
desert harvester ant Pogonomyrmex rugosus. J. Exp.
Biol. 181,49
-61.
Miller, P. L. (1981). Ventilation in active an in inactive insects. In Locomotion and Energetics in Arthropods (ed. C. F. Herreid, II), pp.367 -390. New York: Plenum-Press.
Nielson, M. G. and Baroni-Urbani, C. (1990). Energetics and foraging behavior of the European seed harvesting ant Messor capitatus. I. Respiratory metabolism and energy consumption of unloaded and loaded workers during locomotion. Physiol. Entomol. 15,441 -448.
Raab, J. L., Eng, P. and Waschler, R. A.
(1976). Metabolic cost of grade running in dogs. J.
Appl. Physiol. 41,532
-535.
Rogowitz, G. L. and Chappell, M. A. (2000).
Energy metabolism of eucalyptus-boring beetles at rest and during locomotion:
gender makes a difference. J. Exp. Biol.
203,1131
-1139.
Ronacher, B., Gallizi, K., Wohlgemuth, S. and Wehner, R.
(2000). Lateral optic flow does not influence distance estimation
in the desert ant Cataglyphis fortis. J. Exp.
Biol. 203,1113
-1121.
Sachs, L. (1992). Angewandte Statistik, pp. 553-556. Berlin: Springer-Verlag.
Schmidt-Nielsen, K. (1984). Scaling: Why is Animal Size so Important? Cambridge: Cambridge University Press.
Slama, K. (1994). Regulation of respiratory acidemia by the autonomic nervous system (coelopulse) in insects and ticks. Physiol. Zool. 67,163 -174.
Snyder, G. K., Sheafor, B., Scholnick, D. and Farrelly, C. (1995). Gas exchange in the insect tracheal system. J. Theor. Biol. 172,199 -207.[CrossRef][Medline]
Taylor, R. C. (1985). Force development during sustained locomotion: a determinant of gait, speed and metabolic power. J. Exp. Biol. 115,253 -262.[Abstract]
Taylor, C. R. and Heglund, N. C. (1982). Energetics and mechanics of terrestrial locomotion. Annu. Rev. Physiol. 44,97 -107.[CrossRef][Medline]
Taylor, C. R., Schmidt-Nielsen, K. and Raab, J. L.
(1970). Scaling of energetic cost of running to body size in
mammals. Am. J. Physiol.
219,1104
-1107.
Taylor, C. R., Caldwell, S. L. and Rowntree, V. J. (1972). Running up and down hills: some consequences of size. Science 178,1096 -1097.[Medline]
Taylor, C. R., Heglund, N. C., McMahon, T. A. and Looney, T. R. (1980). Energetic cost of generating muscular force during running. A small comparison of large and small animals. J. Exp. Biol. 86,9 -18.
Taylor, C. R., Heglund N. C. and Maloiy, G. M. O. (1982). Energetics and mechanics of terrestrial locomotion I. Metabolic energy consumption as a function of speed and body size in birds and mammals J. Exp. Biol. 97, 1-21.[Abstract]
Walton, B. M., Peterson, C. C. and Bennett, A. F.
(1994). Is walking costly for anurans? The energetic cost of
walking in the Northern toad Bufo boreas halophilus. J.
Exp. Biol. 197,165
-178.
Warncke, G., Bandholtz, J. and Schultze-Motel, P. (1988). Metabolic cost and body temperatures during grade running in quail (Coturnix coturnix). Comp. Biochem. Physiol. 89A,93 -96.
Wehner, R. (1998). Navigation in context: grand theories and basic mechanisms. J. Avian Biol. 29,370 -386.
West, G. B., Brown, J. H. and Enquist, B. J.
(1997). A general model for the origin of allometric scaling laws
in biology. Science 276,122
-126.
Wickler, S. J., Hoyt, D. F., Cogger, E. A. and Hirschbein, M.
H. (2000). Preferred speed and cost of transport: the effect
of incline. J. Exp. Biol.
203,2195
-2200.
Wickler, S. J., Hoyt, D. F., Cogger, E. A. and Myers, G.
(2003). The energetics of the trot-gallop transition.
J. Exp. Biol. 206,1557
-1564.
Wohlgemuth, S., Ronacher, B. and Wehner, R. (2001). Ant odometry in the third dimension. Nature 411,795 -798.[CrossRef][Medline]
Wunder, B. A. and Morrison, P. R. (1974). Red squirrel metabolism during incline running. Comp. Biochem. Physiol. 48A,153 -161.
Zollikofer, C. P. E. (1994). Stepping patterns
in ants. II. Influence of body morphology. J. Exp.
Biol. 192,107
-118.