First published online March 17, 2006
Journal of Experimental Biology 209, 1231-1244 (2006)
Published by The Company of Biologists 2006
doi: 10.1242/jeb.02135
Kinematics of foraging dives and lunge-feeding in fin whales
Jeremy A. Goldbogen1,2,*,
John Calambokidis3,
Robert E. Shadwick1,
Erin M. Oleson2,
Mark A. McDonald4 and
John A. Hildebrand2
1 Department of Zoology, University of British Columbia, 6270 University
Boulevard, Vancouver, British Columbia, V6T 1Z4, Canada
2 Scripps Institution of Oceanography, University of California, San Diego,
La Jolla, CA 92093-0205, USA
3 Cascadia Research Collective, Olympia, WA 98501, USA
4 Whale Acoustics, Bellvue, CO 80512, USA
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Fig. 1. Bioacoustic probe. The high-resolution digital tag contains a depth gauge,
a two-axis accelerometer and a hydrophone (Bioacoustic Probe;
Burgess et al., 1998 ). The tag
was harnessed with silicon suction cups for attachment and a flotation device
for retrieval. Scale bar, 20 cm.
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Fig. 3. Flow noise increases with flow speed. The tag was attached to a wing and
towed at different speeds in order to establish a relationship between flow
noise magnitude and flow velocity. Flow noise was determined by calculating
the root-mean-square sound pressure at the 50-Hz 1/3 octave bands. The 50-Hz
1/3 octave band was chosen because it exhibited both a high flow noise level
and a distinct partitioning of flow noise magnitude for each flow velocity.
The least-squares regression through the data is described by the equation
y=0.0015x2–0.3327x+18.748;
r2=0.99. This equation was used to estimate the
instantaneous speed of the whale throughout the dive cycle for a given level
of flow noise recorded by the tag.
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Fig. 4. Dual-axis accelerometer response as a function of pitch angle. The tag was
held statically at different pitch angles and rolled at 5° intervals. Data
points represent mean static acceleration measured by the y-axis
(Ay) of the accelerometer from three different tags.
Varying pitch angles are characterized by different colors as defined in the
legend. At high pitch angles, the magnitude of the accelerometer response
decreases along the y-axis.
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Fig. 5. Roll predicted by theory (see Eqn 3) accurately predicts roll measured
experimentally by static calibration. The solid line represents the
least-squares linear regression through the data
(r2=0.99). The broken lines mark 95% prediction
intervals.
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Fig. 6. A representative foraging dive, including five lunges at depth. Black dots
correspond to depth over the course of the dive cycle. Fluking patterns are
depicted by the orange line. Red and blue lines show changes of body pitch and
roll, respectively. Instantaneous speed of the body estimated by flow noise
(purple line) and from the kinematics of the body (yellow dots). Note that
roll was not estimated during ascent and descent whereas instantaneous speed
from the kinematics of the body was only calculated during these particular
phases of the dive. Also note that there may be a lunge that occurs at the end
of the initial descent.
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Fig. 7. Comparison of the two methods, VS (flow noise) and
VK (kinematics), used to estimate speed of the body during
descent and ascent (dark grey dots). The slope of the least-squares linear
regression (blue line; N=4062, r2=0.91,
P<0.001) through all data points is not significantly different
from unity (red line). Note that VS tends to underestimate
VK at speeds greater than 5 m s–1, the
highest speed for which flow noise was recorded by the towed wing
(Fig. 3).
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Fig. 8. Body acceleration (grey dots) and pitch (red dots) as a function of depth.
Values are shown in the first 200 m of the water column and thus only show
data for descent (A) and ascent (B). Positive acceleration is always in the
direction of forward motion of the body. Thick lines represent the mean of
each respective parameter at a particular depth. The orange vertical line
denotes the mean depth where gait transition from fluking to gliding occurs
during descent (21±7 m, N=28) and during ascent (30±5
m, N=28).
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Fig. 9. Detailed kinematics of the body and fluke during four consecutive lateral
lunges at depth. The kinematic parameters presented over time include fluking
dynamics (orange), acceleration (green) and speed (purple) of the body, and
body pitch (red) and roll (blue). Fluking is derived from the small-scale,
dynamic oscillations in the accelerometer signals. Dynamic acceleration values
are presented with negative peaks pointing up and positive peaks pointing down
to intuitively show upstrokes and downstrokes of the fluke, respectively (see
Materials and methods for explanation). Instantaneous speed of the body is
estimated from the magnitude of flow noise measured by the hydrophone. Body
orientation is resolved in two dimensions from the changes in static
acceleration along two orthogonal axes. Associated maxima (filled circles),
minima (open circles) and zero values (crosses) of each kinematic parameter
are superimposed onto the dive profile in the upper panel to illustrate the
temporal coordination of rotational torques with translational accelerations.
The onset of body acceleration and rotation are coincident with each fluking
bout. The body becomes level prior to each lunge. Jaw opening is assumed to
take place at maximum speed (3.0±0.5 m s–1;
N=62; purple circles). Fluking continues after maximum velocity
occurs. Maximum body deceleration and roll maxima (87±18°;
N=62) occur concomitantly (open green circle and filled blue circle).
The kinematic sequence is completed as the body reaches its minimum speed and
comes to a maximum pitch angle.
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Fig. 10. Body and fluke mechanics during one lateral lunge. Kinematic parameters
follow the definitions from Fig.
9. Note the temporal coordination between body roll and body
deceleration.
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Fig. 11. Two kinematic modes observed during lunges. Kinematics of the body and
fluke are largely conserved among all individuals for both regular lunges (A)
and lateral lunges (B). Maxima, minima and zero values for kinematic
parameters follow the definitions from Fig.
9. Note that for regular lunges the body is not rolled, but level
as the body experiences its greatest deceleration.
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© The Company of Biologists Ltd 2006
), and about the x-axis,
roll (
). An axis oriented parallel to gravity would result in 1.0
g recorded by the accelerometer, whereas an axis perpendicular
to gravity would produce a 0.0 g accelerometer signal.
Small-scale, dynamic oscillations detected by the x-axis were
interpreted as fluking. The R/P FLIP, visible on the horizon, served
as a research platform for visual and acoustic marine mammal monitoring
operations.