First published online October 7, 2004
Journal of Experimental Biology 207, 3969-3976 (2004)
Published by The Company of Biologists 2004
doi: 10.1242/jeb.01234
The energy cost of loaded flight is substantially lower than expected due to alterations in flight kinematics
C. Hambly1,*,
E. J. Harper2 and
J. R. Speakman1,3
1 Aberdeen Centre for Energy Regulation and Obesity, School of Biological
Sciences, University of Aberdeen, Aberdeen AB24 2TZ, Scotland, UK
2 The Waltham Centre for Pet Nutrition, Waltham-on-the-Wolds,
Leicestershire, LE14 4RT, England, UK
3 Aberdeen Centre for Energy Regulation and Obesity, Division of Energy
Balance and Obesity, Rowett Research Institute, Bucksburn, Aberdeen AB21 9BS,
Scotland, UK
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Fig. 1. The time after injection that the peak or plateau of isotope enrichment
(delta) occurs varies with different individuals. The longer the isotope was
within the body before the peak was reached, the lower the isotope enrichment
value. This relationship was significant (regression;
y=4746.3–188.36x, r2=0.4,
F1,95=65.10, P<0.001).
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Fig. 2. The calibration if the 13C-labelled bicarbonate technique in
cockatiels 20–30 min after injection. (A) There was no significant
relationship if isotope elimination rate (kc) alone is
used for the comparison with the metabolism
( O2) measured
simultaneously by indirect calorimetry (regression;
y=10.6x+3.8, r2=0.11,
F1,20=2.35, P=0.14) with a low
r2 of 10.99%. (B) The relationship of oxygen consumption
to the product of elimination rate and bicarbonate pool size was significant
(regression; y=5.12x+0.3, r2=0.72,
F1,20=49.54, P<0.001) with a high
r2 of 72.3%.
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Fig. 3. Relationship between the equilibrium of 13C-labelled bicarbonate
with varying amounts of CO2. The enrichment values have been
log-converted and plotted against the log-converted volume of CO2
added in moles. The relationship was linear and significant
(Regression; y=0.72–1.25x,
F1,31=7367.5, P<0.001). The equation for the
relationship was used to calculate the size of the body bicarbonate pool
(Nc) in moles and subsequently ml of CO2 given
a known isotope enrichment for each bird. See text for details.
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Fig. 4. Raw isotope enrichment data from one individual, which was used to
calculate its flight cost. Before flight (diamonds) the isotope enrichment
data conforms to a linear regression, while after flight (squares) a
polynomial regression provided the best fit. The regression equations were
extrapolated to the time when flight began and ended and the gradient between
these two values is the isotope elimination rate during the flight period. In
this example kc was 0.73 min–1.
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Fig. 5. Mean flight cost increases linearly with increased wing loading (diamonds);
however, there were large variations in flight cost between flights in the
same and different individuals and therefore the increase was not significant
(GLM; F4,65=0.11, P=0.98). The relationship for
the mean flight cost was described by y=0.43x+16.63,
r2=0.93. Adding a 10% body mass ventrally (square) had a
lower flight cost than adding the same mass dorsally, but this was not
significant (paired t-test; T=0.4, P=0.7).
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Fig. 6. Changes in (A) flight speed and (B) wing beat frequency
(Fb) with increasing body mass due to the artificially
added mass. *Significant difference from the same parameter in the
pre-manipulated birds (Pre). Values are means ± S.E.M.
(N=70 flights across 5 individuals).
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Fig. 7. Mean up- (A) and downstroke (B) duration in relation to added payload mass.
Upstroke duration was always significantly higher than downstroke duration
(asterisks; P<0.05). When masses were added, both wing upstroke
and wing downstroke significantly decreased as wing loading increased (one-way
ANOVA; upstroke F5,85=7.22, P<0.001;
downstroke F5,85=6.56, P<0.001). Values are
means ± S.E.M. (N=70 flights across 5 individuals).
Control, pre-manipulation.
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Fig. 8. Mean wing amplitude in relation to payload mass added. There were no
significant differences with increasing weight added, compared to the controls
(pre-manipulation). Values are means ± S.E.M. (N=70
flights across 5 individuals).
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Fig. 9. Neither the Pennycuick (one-way ANOVA; F4,24=2.58,
P=0.07) nor Rayner (one-way ANOVA; F4,24=1.60,
P=0.21) aerodynamic models predicted a significant increase in flight
cost with increasing extent of wing loading when calculated using all the
measured parameters for these birds. Values are means ±
S.E.M. Control, pre-manipulation.
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© The Company of Biologists Ltd 2004
