Stroke frequencies of emperor penguins diving under sea ice
1 Center for Marine Biotechnology and Biomedicine, Scripps Institution of
Oceanography, University of California San Diego, La Jolla, CA
92093-0204, USA
2 Natural History Unit, National Geographic Television, 1145 17th Street NW,
Washington, DC 20036, USA
* Author for correspondence (e-mail: pponganis{at}ucsd.edu)
Accepted 16 September 2002
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Summary |
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Key words: accelerometer, aerobic dive limit, Aptenodytes forsteri, Crittercam, dive, emperor penguin, stroke frequency
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Introduction |
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The measured ADL (ADLM), or diving lactate threshold (DLT) as
determined by blood lactate measurements
(Butler and Jones, 1997) of
emperor penguins Aptenodytes forsteri is 5.6 min
(Ponganis et al., 1997
). That
ADL study involved relatively shallow dives (<50 m) of emperors foraging
from an isolated dive hole. Depth profiles of these dives typically include
descent to depth, travel at depth, hunting ascents to the undersurface of the
ice to catch fish, and then return to depth for travel and eventual exit at
the dive hole (Ponganis et al.,
2000
) Although shallow dives (<60 m) comprise about 60% of all
dives during foraging trips to sea, emperors also routinely dive to 500 m
depth, and frequently have diving durations greater than the ADLM
(Kooyman and Kooyman, 1995
;
Kirkwood and Robertson, 1997
).
Given the large diving air volume of penguins
(Kooyman et al., 1973
;
Ponganis et al., 1999
;
Sato et al., 2002
) and the
potential role of buoyancy changes and intermittent locomotion patterns in
affecting the magnitude of the ADL, it is unknown if swim behaviors during
deep and shallow dives differ, and if the aerobic dive limit of deep-diving
emperors is the same as that of the shallow-diving birds at the experimental
dive hole. In order to begin to assess these possibilities, we sought to
measure stroke frequency and determine the locomotory pattern during the
shallow dives of emperor penguins foraging from an isolated dive hole.
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Materials and methods |
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Forward acceleration was measured in seven birds with an accelerometer datalogger unit attached to the back. The accelerometer was oriented to measure acceleration in the direction of the penguin's spine. The datalogger consisted of a microprocessor (5F, Onset Computer, Pocasset, MA, USA) measuring the low-pass output (<10 Hz) of a single-axis acceleration sensor (ADXL105, Analog Devices, Norwood, MA, USA) at a rate of 20 Hz. The sensor was calibrated statically against the earth's gravitational acceleration at five inclinations.
The acceleration datalogger was attached to the penguins for 1 h periods in
two configurations: (1) inside a streamlined aluminum housing (275 g, 14 cm
x 6 cm x 3 cm) secured with cable ties to a previously glued
Velcro strip on the central back of the birds; or (2) incorporated into a
National Geographic Crittercam underwater video camera worn by harness
(approximately 1 kg, neutral buoyancy, 9 cm diameter, 25 cm length, 63
cm2 frontal area, 3.6 s depth sampling rate; see
Ponganis et al., 2000). In
configuration (1), a time depth recorder (TDR, Mk7, Wildlife Computers,
Redmond, WA, USA; 41 g, 9.3 cm x 2.4 cm x 1.3 cm, 0.5 m
resolution, 1 s sampling rate) was simultaneously deployed on the bird's back
behind the accelerometer datalogger. Underwater observations of departures and
returns to the dive hole were made from a sub-ice observation chamber
(Ponganis et al., 2000
).
Penguin swim strokes observable in the Crittercam video footage were correlated with the acceleration record to guide the design of an automated stroke detection algorithm from the accelerometer measurements. Stroke frequency was determined in a subset of Crittercam footage with customized software, which detected, in each video frame (29.97 frames s-1), the vertical location of the horizontal scan line with the highest luminance. Assignment of a single location value to each video frame yielded a frame-accurate, time series that tracked the vertical movement associated with swim strokes as visible in the video sequence (see Fig. 1).
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In order to detect wing strokes from the accelerometer data, a customized peak detection software program was applied to the data after first processing it with a five-sample moving average. Analysis of three randomly selected dives of birds equipped with both the Crittercam and accelerometer revealed that 68 and 97% of wing strokes detected by algorithm from the accelerometer data coincided, within 100 and 200 ms, respectively, with strokes detected by the video frame analysis. Stroke rates above 2 beats s-1 were considered to be artifacts; they constituted less than 1% of detected wing beats, and were excluded from the data analysis.
For comparison of stroke frequencies during different dive phases in birds with the accelerometer/TDR, stroke frequency data were separated into six dive segment categories: initial descent (0-12 m depth), travel (>12 m depth), foraging ascent (12-2 m depth), foraging descent (2-12 m depth), final ascent (12-0m depth), and other (shallow ascents and descents near the ice holes). The 12 m criterion corresponds to the maximum depth of the shallowest dive examined; the underside of the sea ice was at 2 m depth.
Values are expressed as means ± S.D. unless otherwise indicated. Statistics were considered significant at P<0.05.
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Results |
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Swim stroke frequencies in birds equipped with the accelerometer/TDR varied by dive segment (Fig. 2). Mean stroke rates were highest (0.92 Hz) during the initial descent from the dive hole, and lowest (0.61 Hz) during the travel segments of dives (Table 2). Travel segments constituted on average 66.4% of the birds' dive time (Table 2). For dives of greater duration than the ADLM, mean travel segment stroke frequencies were significantly lower than those during the travel segments of shorter dives (t-test on 1/f transformed data, 0.56±0.07 versus 0.69±0.11 Hz). Histogram analysis (Fig. 3) revealed that >50% of wing beats were associated with a stroke interval >1.6 s.
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Mean stroke frequencies while foraging were similar for both ascent and descent segments above 12 m depth. Analysis of the stroke frequency during the entire foraging ascent (from depth to under the ice) resulted in a mean value of 0.54±0.23 Hz (N=88 ascents). Feeding excursions to the underside of the sea ice also yielded the longest measured wing beat interval of 8.6 s. However, no significant periods (>10 s) of wing inactivity interpretable as prolonged gliding behavior were observed in any of the dives.
Mean dive stroke frequencies (i.e. of the entire dive) of birds equipped with an accelerometer/TDR were not significantly different from those of birds carrying the Crittercam (t-test on 1/f transformed data, 0.68±0.12 versus 0.74±0.12 Hz, respectively), although the stroke frequency distributions were slightly different (Fig. 3). In both circumstances, mean dive stroke frequencies correlated significantly with dive duration (r=-0.57 and -0.58, respectively, Fig. 4) and with mean dive depth (r=-0.50 and -0.40, respectively).
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Discussion |
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Earlier observations of emperor penguins in the near-surface zone made from
a submerged observation chamber, yielded wing-beat frequencies of around 0.75
Hz (Kooyman and Ponganis,
1994). These observations correspond to those parts of dives
classified in our study as initial descent and final ascent segments, and the
reported value falls within the range of stroke frequencies we measured for
these segments. Although drag secondary to the recorders may have contributed
to slight differences between the chamber observations of birds without
recorders and the measurements in this study, the accelerometer/TDR unit
weighed less than 1.5% of the body mass of these birds and constituted less
than 3% of the frontal cross-sectional area, i.e. less than the criteria cited
as significant by most investigators
(Wilson et al., 1986
).
We attribute the high stroke frequencies we measured for penguins during
their initial descent phase of dives to the need to overcome substantial
initial buoyancy. The buoyancy of a typical 23 kg emperor penguin with a 69 ml
kg-1 diving air volume
(Ponganis et al., 1999)
calculated with the equation of Sato et al.
(2002
) is 17.5 N. By 10m
depth, this initial buoyancy would be reduced by 46%. A reduction in buoyancy
is consistent with the high stroke frequencies during initial descents, and
with the lower stroke frequencies during travel segments. Low stroke
frequencies during the entire foraging ascent (from depth to the sub-ice
surface) are also consistent with an increase in buoyancy during ascent. The
role of buoyancy in energetic costs of diving penguins has also been
emphasized by Sato et al.
(2002
). Those investigators
documented prolonged gliding behavior during ascents from depth in both Adelie
Pygoscelis adeliae and king penguins Aptenodytes
patagonicus, and reported that calculated diving air volume increased
with maximum dive depth, suggesting that a smaller diving air volume during
shallow dives of penguins reduced the cost of overcoming buoyancy during
shallow dives. The findings in the present study and that of Sato et al.
(2002
) are therefore
consistent with a significant role for diving air volume and buoyancy in the
diving energetics of penguins. The actual diving air volume of emperor
penguins is unknown; the above calculation utilized a value measured during
simulated dives of king penguins, a value which is also in the range of values
estimated by Sato et al.
(2002
) for shallow dives of
free-diving king penguins. The role of buoyancy may be even more important in
birds than in marine mammals since diving air volume is 3-7 times greater in
birds (Butler and Jones, 1997
).
In the lesser scaup Aythya affinis, for example, buoyancy contributes
to about 75% of the mechanical cost of underwater locomotion
(Stephenson, 1994
).
In contrast to the findings of Sato et al.
(2002), in which gliding was
also observed during ascents from shallow depths, prolonged gliding was never
observed in emperor penguins foraging under sea ice. This may be partially
accounted for by the nature of such dives at the isolated dive hole, and the
necessity of horizontal travel beneath fast ice. The majority of distance
traveled was horizontal for the emperors, and they returned to a small dive
hole, not an open surface. However, a stroke/glide swim pattern, similar to
that reported for horizontal swimming in marine mammals
(Williams, 2001
), was evident
in the stroke frequency distribution of these birds. More than 50% of strokes
were associated with a glide period (stroke interval) greater than 1.6 s;
almost 20% of strokes had intervals greater than 2.5 s.
Stroke frequencies of entire dives correlated inversely, although weakly,
with both dive duration and mean dive depth. In addition, stroke frequencies
during travel segments of dives >ADLM, were significantly less
than those of dives <ADLM. In addition to longer glide periods
during such dives, this implies that the distance traveled per stroke was
greater in longer/deeper dives, or that swim velocity was lower. If one
assumes similar swim speeds near 3 ms-1
(Kooyman et al., 1992) during
the travel segments of all dives, then the average distance traveled per
stroke ranges from approximately 3 to 5 m. Swim speeds, however, were not
measured. Regardless of this, lower stroke frequencies in longer dives could
decrease locomotory work, due to both a decreased work rate and decreased drag
secondary to the reduction in limb movement
(Williams, 2001
).
The increased workload imposed on the penguins equipped with the larger Crittercam system had a significant negative effect on dive duration, but not on mean stroke frequencies. This suggests that the Crittercam birds compensated for the increased drag either through reduced swim speed, or by augmenting propulsion power through means other than wing-beat frequency. Neither swim speed nor wing-beat parameters such as stroke amplitude and angle of attack were measurable with our instruments. The observation that the Crittercam-equipped penguin, when sighted swimming with a group of birds, would typically return last suggests that swim speed was reduced. The correlation of lowered stroke frequencies with increasing dive duration implies that the birds most likely followed a strategy of reduced swim effort, resulting in lower velocities and decreased induced drag.
A stroke/glide swim pattern, consistent with energy efficiency in diving,
has now been demonstrated in emperor penguins. Stroke frequencies in these
free-diving penguins were less than the 1-1.2 Hz stroke frequencies observed
in emperor penguins swimming in a flume at a metabolic rate of 20 ml
O2 kg-1 min-1
(Kooyman and Ponganis, 1994).
Since heart rates were also lower in free-diving penguins
(Kooyman et al., 1992
) than in
birds swimming at 20 ml O2 kg-1 min-1
(Kooyman and Ponganis, 1994
),
all the evidence suggests that the O2 consumption rate during the
submerged period of the dive is lower than that swim flume metabolic rate.
However, other factors also affecting energy output, such as stroke amplitude
and thrust, were not measured in either the flume study or this study.
The lack of prolonged gliding during shallow foraging dives both
<ADLM and >ADLM has several implications. First,
prolonged gliding may not be a significant mechanism of energy conservation in
60% of dives at sea and in the longest duration dives recorded in emperor
penguins, since these dives are predominantly shallow (<60 m). The lack of
gliding may be secondary to buoyancy effects as well as the necessity of
horizontal travel during such dives. Second, since recent data from king
penguins indicates that gliding during ascent may begin as deep as 125 m
(Sato et al., 2002), prolonged
gliding in deep dives may represent a potential mechanism to decrease
locomotory effort and increase the ADL of deep dives of emperor penguins.
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Acknowledgments |
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