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Field Flight Dynamics of Hummingbirds during Territory Encroachment and Defense

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Hummingbirds are capable of extreme maneuverability and use this maneuverability to defend food resources from encroachment by conspecifics and other potential resource consumers. These competitive intraspecific interactions provide an opportunity to quantify the biomechanical aspects of hummingbird flight performance during ecologically relevant natural behavior. Here we used multi-camera videography to determine the three-dimensional flight trajectories of Ruby-throated Hummingbirds (Archilochus colubris) defending, being chased from and freely departing from a feeder and use these trajectories to compare natural flight performance to earlier laboratory measurements of maximum flight speed, flight force and power requirements. We found that the hummingbirds only rarely approached their maximum flight speeds from previously reported from wind tunnel tests and they never did so in level flight conditions, but rather used gravitational acceleration to boost flight speed. However, measures of acceleration and rates of change in kinetic and potential energy indicate that these hummingbirds likely operated near the maximum of their flight force and aerobic power capabilities. Finally, we found that although birds departing from the feeder while chased did so faster than freely-departing birds, they accomplished this by modulating their kinetic and potential energy gains (or losses) rather than increasing overall power output, trading altitude for speed during escape.
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RESEARCH ARTICLE
Field Flight Dynamics of Hummingbirds
during Territory Encroachment and Defense
Katherine M. Sholtis, Ryan M. Shelton, Tyson L. Hedrick*
Department of Biology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States
of America
*thedrick@bio.unc.edu
Abstract
Hummingbirds are known to defend food resources such as nectar sources from en-
croachment by competitors (including conspecifics). These competitive intraspecific inter-
actions provide an opportunity to quantify the biomechanics of hummingbird flight
performance during ecologically relevant natural behavior. We recorded the three-
dimensional flight trajectories of Ruby-throated Hummingbirds defending, being chased
from and freely departing from a feeder. These trajectories allowed us to compare natural
flight performance to earlier laboratory measurements of maximum flight speed, aerody-
namic force generation and power estimates. During field observation, hummingbirds
rarely approached the maximal flight speeds previously reported from wind tunnel tests
and never did so during level flight. However, the accelerations and rates of change in ki-
netic and potential energy we recorded indicate that these hummingbirds likely operated
near the maximum of their flight force and metabolic power capabilities during these com-
petitive interactions. Furthermore, although birds departing from the feeder while chased
did so faster than freely-departing birds, these speed gains were accomplished by modu-
lating kinetic and potential energy gains (or losses) rather than increasing overall power
output, essentially trading altitude for speed during their evasive maneuver. Finally, the
trajectories of defending birds were directed toward the position of the encroaching bird
rather than the feeder.
Introduction
The flight capabilities of animals have long interested researchers, leading to an extensive liter-
ature on the aerodynamics and flight capabilities of birds, bats and insects examined in a di-
verse array of laboratory experiments. For example, wind tunnel experiments have measured
flapping kinematics [1,2], cost of transport and power requirements for flight [35] and quan-
tified flow structures over the wing [6] and in the wake [7,8]. Maneuvering course experi-
ments [911] have revealed some of the turning capabilities of vertebrates engaged in low
speed flight. In contrast, studies of animal flight capabilities in natural environments are far
PLOS ONE | DOI:10.1371/journal.pone.0125659 June 3, 2015 1/20
OPEN ACCESS
Citation: Sholtis KM, Shelton RM, Hedrick TL (2015)
Field Flight Dynamics of Hummingbirds during
Territory Encroachment and Defense. PLoS ONE
10(6): e0125659. doi:10.1371/journal.pone.0125659
Academic Editor: David Carrier, University of Utah,
UNITED STATES
Received: October 2, 2014
Accepted: March 17, 2015
Published: June 3, 2015
Copyright: © 2015 Sholtis et al. This is an open
access article distributed under the terms of the
Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any
medium, provided the original author and source are
credited.
Data Availability Statement: All relevant data are
within the paper and its Supporting Information files.
Funding: This work was funded by Office of Naval
Research (http://www.onr.navy.mil) MURI
N000141010952 to TLH and 8 others and by National
Science Foundation (http://www.nsf.gov/) IOS-
1253276 to TLH. The funders had no role in study
design, data collection and analysis, decision to
publish, or preparation of the manuscript.
Competing Interests: The authors have declared
that no competing interests exist.
less common because of difficulties related to repeatability and of reliably obtaining precise,
quantitative kinematic data at high temporal resolution in the field. Thus, although much is
known about steady, level flight in controlled but highly artificial wind tunnel environments, it
is less certain how these capabilities relate to natural flight behavior, especially at timescales in
which turning, acceleration and deceleration occur and how they are used in day-to-day eco-
logical contexts. However, continual advances in camera, inertial sensing and data-logging
technologies now allow quantification of animal flight performance in the field at timescales of
less than a tenth of a second, using high speed videography with multiple, calibrated cameras
[1214] or on-board inertial sensing and data recording[15] for larger animals able to easily
lift the ~20 gram mass of current generation systems [16]. These new capabilities allow investi-
gation into how animals deploy their flight capabilities during typical foraging, display and
commuting behaviors.
Hummingbirds, whose small size and sustained ability to hover provide substantial physio-
logical and biomechanical challenges that have been the subject of much laboratory investiga-
tion [1720], are an excellent study system in which to examine how aerial maneuvering
abilities and locomotor performance measured in the laboratory relate to field behaviors. We
used high-speed videography to quantify the three-dimensional (3D) flight trajectories of free,
wild hummingbirds around a stationary, outdoor feeder. This provided repeatable, quantitative
observation of position as birds approached a feeder and departed from it either alone or while
being pursued by another hummingbird. From recorded trajectories, we also computed veloci-
ty, acceleration, mass-specific kinetic and gravitational potential energy, and mass-specific ki-
nematic (i.e. climb) power.
These data were then used to test the following hypotheses on how hummingbirds use
their flight capabilities in different behaviors. First, we expected that birds departing from
the feeder while being chased would exhibit greater accelerations, flight speeds and changes
in kinetic and potential energy than birds departing alone. Producing larger flight forces as-
sociated with acceleration and higher speed is aerodynamically costly, and birds are only ex-
pected to meet these costs when necessary. Second, the measured mass-specific kinematic
power output (i.e. rates of change in kinetic and potential energy) should be substantially
below laboratory measurements of aerodynamic power requirements in hummingbirds
since our field measurements do not include aerodynamic costs such as profile, parasite and
induced power which can only be measured in lab. Furthermore, we do not expect birds to
employ their maximal flight capabilities during typical behaviors such as those measured
here, following the results of intraspecific contests in Cliff Swallows [13]. For similar reasons,
the non-dimensional forces associated with acceleration in the field should be less than the
maximum lift forces recorded from hummingbirds in laboratory tests. Finally, we hypothe-
size that the highest flight speeds will be found in the birds defending the feeder because they
typically dive toward their target, using potential and muscle energy for locomotion, but that
these will not exceed flight speeds recorded in hummingbird mating displays [12]wherea
maximal display of flight capabilities may be particularly beneficial and stored potential en-
ergy is also used.
In addition to biomechanical measures, our results also provide some information on the
guidance and control used by the birds during these intraspecific interactions. Specifically, the
pursuing bird defending the feeder might either aim for the food resource or for the encroach-
ing bird. We hypothesize that the former is the preferred strategy because the food resource is
stationary, simplifying the flight control and targeting requirements for the defending bird and
might also be more readily defended by flying directly to it.
Field Flight Dynamics of Hummingbirds
PLOS ONE | DOI:10.1371/journal.pone.0125659 June 3, 2015 2/20
Materials and Methods
Ethics Statement
The hummingbird observation protocol was approved by the University of North Carolina at
Chapel Hill Institutional Animal Care and Use Committee, no government permits were re-
quired for field observation of the species studied here.
Hummingbird Recordings
Using multiple camera high-speed videography, we recorded freely-behaving wild Ruby-
throated Hummingbirds (Archilochus colubris, Linnaeus, 1758) during competitive interac-
tions on private land in Orange County, North Carolina, USA (36° 029N, 79° 551W) with
the permission of the landholder. The arena consisted of a wood deck with a single humming-
bird feeder filled with clear 25% sugar water, located adjacent to a wooded area and bordered
by a private residence (Fig 1). Video recording allowed sexing hummingbirds based on plum-
age in most cases. The hummingbird observation protocol was approved by the University of
North Carolina at Chapel Hill Institutional Animal Care and Use Committee, no government
permits were required.
Fig 1. Video recording setup and example flight trajectories. Panels A-C show images from each of the three cameras in a recording setup; panel D
shows a reconstruction of the 3D scene including the cameras, their positioning, their individual2D images of the scene, the trajectory of the two
hummingbirds in the 2D images as well as the 3D scene and triangulation rays identifying the 3D location of one bird at one instant from the 2D image
information. The defending bird information is magenta while the chased bird is cyan; photographs (not to scale) of a defending and chased bird are included
to show typical flight posture at the start of the interaction. Photo credit: Ellis Driver.
doi:10.1371/journal.pone.0125659.g001
Field Flight Dynamics of Hummingbirds
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We recorded on 14 separate mornings in the months of June, July, and August 2013 from
approximately 8a.m. to noon at this location. The location of the cameras changed over the
first two weeks to determine the best vantage points. Twenty-nine of the 51 videos analyzed
had a camera configuration similar to that seen in Fig 1. Eighty-three separate videos were re-
corded, including both two-bird competitive interactions and single-bird arrivals and depar-
tures from the feeder. Thirty-three two-bird competitive interactions included the full two-bird
interaction including pursuit by the defending bird and departure of the encroaching bird and
were thus suitable for analysis. In these trials, we have designated the birds as either the en-
croaching, chased bird or the defending, chasing bird. Eighteen one-bird trials began with the
bird hovering near the feeder then departing without provocation and were thus suitable for
comparison with the chased bird from the two-bird interaction recordings. As previously re-
ported for Ruby-throated Hummingbird competitive interactions [21], most defending and
freely-departing birds were male while most chased birds were female. Respective counts of
(male, female, undetermined) for the three behaviors were (31,2,0), (11,2,5), and (5,28,0). Note
that the male-female distribution of defending and chased birds may reflect a behavioral case
where the chase is the initial portion of a mating display rather than aggressive defense of a re-
source, though we did not observe any subsequent portions of the typical mating display se-
quence [22].
We used three synchronized high-speed cameras (N5r, Integrated Design Tools, Inc., Tal-
lahassee, Florida, USA) recording 2336 x 1728 pixel images, generally at a 300 Hz frame rate
for ~1.6 seconds. To provide longer observation durations, five trials were recorded at 200
Hz (~2.4 seconds of video) and one at 100 Hz (4.75 seconds of video). On these three cam-
eras we used one 28mm and two 20mm Nikon lenses (AF NIKKOR 20 mm f/2.8D and AF
NIKKOR 24 mm f/2.8 AIS, Nikon Inc., Melville,NY,USA).Inordertocollect3Dkinematic
data, we used a structure-from-motion camera calibration routine [23]. Calibrations were
obtained for each new setup at the start and end of each day's filming. Calibration sequences
used a 1m wand moved within the field of view of all three cameras, with 20 hand-digitized
wand points used in each calibration. The coordinate system z- axis was aligned to gravity
using an additional recording of a rock thrown in the scene. The origin and the x- and y-axes
were aligned to local environmental features ensuring a consistent reference frame for
all trials.
To measure the wind, we placed a digital anemometer (HHF142, OMEGA Engineering, Inc,
Stamford, Connecticut, USA) on the ground near the camera locations. To allow rotation
about the vertical axis, the anemometer was mounted on a gimbal. A custom data logger re-
corded wind velocity at 1 Hz intervals as well as recording compass direction, time, and loca-
tion. Only trials with a recorded wind speed of less than 1.5 m s
-1
were analyzed; we did not
include wind velocity in our kinematic analysis since it likely varied in magnitude and direction
through the volume traversed by the birds.
Video Analysis
After recording, the position of the birds in each video was digitized either by hand or using
specially-written autotracker routines implemented using a combination of Python, OpenCV
and MATLAB (The Mathworks, Natick, MA). Hand-digitizing via the MATLAB package
DLTdv5 [24] was used initially and in cases where the autotracker was unable to recognize the
birds for a short amount of time. Hand-digitizing was a slow task, averaging about two hours
per 475 video frames. As the number of organisms, number of cameras, and frame rate in-
crease, manual digitizing becomes a major challenge. Thus, the autotracker was developed to
allow timely analysis of a larger number of recordings.
Field Flight Dynamics of Hummingbirds
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The autotracker functioned as follows: the scene background of each camera view was sub-
tracted using a running average background subtractor configured to remove portions of the
image that changed slowly (time scale longer than about 20 frames). Potential hummingbirds
were then detected in each camera view using a Haar cascade [25] trained using data from the
hand-digitized trials. Detections from all three cameras were then combined into specific 3D
points along tracks by determining which pairwise and three-wise combinations of bounding
box centroids produced three-dimensional positions with acceptably small stereo reconstruc-
tion errors (26 pixels rmse). This eliminated false detections such as those due to moving fo-
liage and other sources of noise. Finally, all autodetected tracks were manually reviewed in
order to remove obvious errors, and to merge tracks if the autotracker momentarily lost contact
with the bird. The median rmse of all trials was 1.80 pixels, which corresponded to a median
spatial 95% confidence interval volume of 5.75x10
-7
m
3
. The effective recording volume was
347 m
3
, as measured by the minimum volume bounding box containing all hummingbird tra-
jectory data points.
To remove digitization noise, the raw 3D position data were processed with a quintic
smoothing spline implemented via the spaps function in MATLAB (The Mathworks, Natick,
MA). For each data point, the error variance was extracted from the 3D reconstruction uncer-
tainty and we iteratively increased the spline error tolerances, weighted by the error variances,
to effect a low pass filter at 2.0, 3.0, and 4.0 Hz. Varying the low pass filter frequency did not af-
fect any of our conclusions and produced only small variations in the data. Results presented
here are from the 3.0 Hz low pass filter unless otherwise noted. We estimated derivatives of po-
sition with respect to time from the quintic spline polynomial. Velocity (v) and acceleration (a)
were found by taking the first and second derivatives, respectively. We calculated the mass-
specific kinetic (KE) and gravitational potential energy (PE) of the hummingbirds at any given
time by:
KE
m¼1
2jvj2ð1Þ
PE
m¼gh ð2Þ
where mis body mass, gis gravitational acceleration and his elevation. We also computed
mass-specic kinematic (P
k
) (i.e. climb) power as:
Pk
m¼D1
2jvj2þgh

Dtð3Þ
where tis time. In addition to our trajectories and mass-specic power estimates, two measures
of maneuverability were computed: the angular velocity of the trajectory, i.e. the rate of change
in direction of the trajectory and the centripetal force developed by the bird. Angular velocity
was computed from instantaneous radius of curvature (r) directly from vand aby
r¼jvj3
ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
jvj2jaj2ðva
0Þ2
qð4Þ
where a0is the transpose of a. We then calculated angular velocity (w)by
w¼jvj
rð5Þ
Field Flight Dynamics of Hummingbirds
PLOS ONE | DOI:10.1371/journal.pone.0125659 June 3, 2015 5/20
Centripetal force (F) in body weights is then
F¼jvj2
gr :ð6Þ
and was adjusted to F, the force produced by the bird only, by removing the gravitational con-
tributions to Fas described in [13]. Note that because angular velocity is undened when ight
speed is equal to zero, we only computed this quantity when the speed of the trajectory was
greater than 1.0 m s
-1
.
Trajectory analysis
We began analysis of the individual flight trajectories by first dividing them into three groups:
trajectories from 1) freely-departing birds that approached the feeder and departed alone, 2)
birds that approached the feeder and were chased away from it by a defending bird and 3) the
defending birds. Next, members of each group were aligned to a common timebase with a start
time determined by group-specific features. For the freely-departing and chased birds, time-
base t
c
was established by setting t
c
= 0 to the instant at which the bird achieved a flight speed
of 0.4 m s
-1
during departure. Note that a flight speed of 0.0 m s
-1
was not used because not all
chased birds came to a complete stop. Two of the 33 chased birds never slowed to 0.4 m s
-1
and
these trajectories were not examined further.
Defending birds typically entered the recording volume from above at a substantial speed.
Timebase t
d
was established for these trajectories by setting t
d
= 0 to the instant at which the de-
fending bird passed through a horizontal plane approximately 0.75 meters above the feeder
and exactly 1.2 meters above the fixed rail where the feeder was mounted. This plane was cho-
sen by examination of the set of defending bird trajectories, which revealed a period of constant
slope descent which typically ended at this elevation (Fig 2). Once a common timebase was es-
tablished for each group, average trajectories for each of the three groups were constructed by
averaging the vertical and horizontal velocity and acceleration information of all the trials in
the group for each.
Finally, we examined the question of whether the defending bird flies towards the chased
bird or towards the feeder by computing the 3D angle between the trajectory of the defending
Fig 2. Defending bird trajectories and their classification. Circles indicate the starting position of the bird trajectory and diamonds its end position. Green
lines with solid markers represent defenders using the perch, which was not within the 3D reconstruction volume. The pink lines with open markers represent
other defender trajectories. A) A top-down view of the flight trajectories of the defending birds. B) A 3D view of the defendingbirds. The transparent blue plane
at Z = 1.2m represents the approximate end of the uniform descent period of defender trajectories.
doi:10.1371/journal.pone.0125659.g002
Field Flight Dynamics of Hummingbirds
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bird and the direction of the feeder along with the 3D angle between the trajectory and the po-
sition of the chased bird. We used a one-sample t-test of the average difference between these
3D angles during the sustained descent phase (time less than 0) described above to assess the
guidance decision of the defending bird.
Statistical analysis
Specific statistical comparisons of trajectory values among the different flight groups were
made by two-tailed, unpaired t-tests computed in MATLAB r2013b. Comparisons of defend-
ing and chased birds were by two-tailed, paired t-tests. Note that the identity of individual
birds could not be established from the video data, so our comparisons are of bird trajectories
rather than birds. A maximum of five birds were observed simultaneously in the vicinity of the
feeder, so the trajectories were likely produced by five or more individual animals but fewer
than the number of trajectories recorded, which was 18 to 33 depending on the behavior. The p
values reported in the tables use the number of trajectories in determining the degrees of free-
dom. The effect of a reduction in degrees of freedom due to multiple recordings from the same
bird can be estimated by assuming fewer degrees of freedom and examination of a table of t-
distribution critical values; a reduction to only 5 degrees of freedom in both cases leads to
roughly an order of magnitude increase in the p value.
Results in the text and tables are presented as mean ± standard deviation with a p value if a
statistical comparison is called for. In contrast, trajectory results in figures are typically pre-
sented as the mean trajectory with error bars giving the standard error. This approach was
taken because non-overlapping standard errors allow visual identification of cases likely to
prove significantly different in a t-test whereas overlapping (or non-overlapping) standard de-
viations provide no such information.
Results
Trajectory classes
Freely-departing bird trajectories were recorded from birds leaving the feeder without being
chased away. We acquired 18 videos of this class of trajectory; in 11 of these the hummingbird
was male, in two it was female, and in five videos the sex of the bird could not be identified.
These trajectories departed the feeder in a variety of directions, flying upward in 13 trials, flying
level in three trials, and flying downward in two trials.
We acquired 33 videos of two-bird competitive interactions, which capture the flight trajec-
tories of chased and defending birds. The videos start with the chased bird either approaching
the feeder (12 of 33 trials), or hovering near it. The defending bird starts above the feeder and
flies downward (in all but one trial) towards the chased bird while the chased bird is still ap-
proaching the feeder or while it is hovering nearby. The chased bird then departs from the feed-
er, flying downward in ten trials, flying level in 20 trials, and flying upward in three trials. For
the chased bird trajectories, there were five recordings where the bird was a male and 28 videos
where the bird was a female. For the defending bird trajectories, there were 31 videos where the
bird was a male and two videos where the bird was a female.
We observed that the defending birds used a specific perch more often than any other loca-
tion (16 out of 33 trials). This perch was located 6.5m above and 8.8m horizontal from the feed-
er, a total distance of 11.0m. In their initial approach to the feeder and chased bird, the
defending birds descended towards the feeder at approximately the same rate. This period of
uniform descent can be seen in Fig 2.
Field Flight Dynamics of Hummingbirds
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Flight Speed and Velocity
The feeder departure trajectories from chased birds showed a greater flight speed than those re-
corded from freely-departing birds (Fig 3,Table 1). For example, at 0.3 seconds after departure,
the mean speed of all chased bird trajectories was 3.9 ± 1.1 m s
-1
(mean ± standard deviation
here and elsewhere) while the mean speed of all freely-departing trajectories was 3.0 ± 0.8 m s
-1
(t-test, p = 0.0039). We found that defending trajectories originating at the typical perch (see
above) differed from those originating at other locations with respect to their velocity profile
(Fig 4,Table 2). Perch trajectories had greater overall flight speeds, with greater horizontal and
vertical velocities. For all defending trajectory velocity comparisons, the differences in velocity
between the two classes of defending trajectory lessened as the birds approached the feeder (Fig
4). Finally, maximum speeds recorded from defending bird trajectories were greater than those
recorded in the matching chased bird trajectory (Table 3).
Acceleration
We observed differences in acceleration between departures of chased bird trajectories and
freely-departing trajectories (Fig 5,Table 1). The chased trajectories exhibited a higher initial
acceleration during the first 0.25 seconds after departure, after which the two classes of depart-
ing birds had similar acceleration profiles. The initial accelerations were typically the largest
magnitude events in the trajectory, thus the chased bird trajectories had significantly higher
overall maximum accelerations compared to the freely-departing ones (t-test, p = 0.0025). The
overall maximum instantaneous acceleration found within a chased bird trajectory was 42.3 m
s
-2
compared to 19.6 m s
-2
for a freely-departing trajectory.
The two classes of defending bird trajectories, perch and non-perch, produced similar mag-
nitude accelerations when approaching the feeder, but perch trajectories began decelerating
earlier (Fig 6,Table 2). The maximum accelerations for non-perch and perch defending birds
were similar (Table 2) as were the deceleration magnitudes. In general, for the portion of the
Fig 3. Flight speed in departure trajectories. The red triangle markers represent the mean flight speed of
the chased bird after departing from the feeder. Error bars show the standard error (n = 31 trajectories at t
c
=
0 and n = 30 at t
c
= 0.29 seconds). The blue circle markers show the mean departure flight speed of freely-
departing hummingbirds (n = 18 trajectories). Measurements of the flight speeds of both classes of birds were
taken at different times after initial departure and a common timebase t
c
created with 0 as the instant where
the bird first reaches a speed of 0.4 m s
-1
.
doi:10.1371/journal.pone.0125659.g003
Field Flight Dynamics of Hummingbirds
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defending bird trajectories recorded in this study, the deceleration magnitudes are greater than
the acceleration magnitudes.
Changes in mass-specific energy state
Despite previously noted differences in acceleration profile, when comparing energy usage dur-
ing feeder departures from chased bird trajectories versus those from freely-departing cases, we
found that the two classes had similar overall mass-specific energy values (Fig 7,Table 1) al-
though these were partitioned differently among potential and kinetic energy. Thus, at 0.3 sec-
onds after departure, the mass-specific energies of the two classes of departing bird trajectory
were not statistically different (t-test, p = 0.6812), but the mass-specific potential energies were
significantly different (t-test, p<0.0001), as were the mass-specific kinetic energies (t-test,
p = 0.0046). The chased trajectories tended to trade potential energy for kinetic energy com-
pared to freely-departing cases by flying level or downward when departing from the feeder.
The freely-departing trajectories tended to fly upward, resulting in a potential energy gain but
lower flight speeds compared to chased bird trajectories.
We found that the two classes of defending bird trajectories, perch and non-perch, had simi-
lar mass-specific potential energy values (by definition in our timebase alignment), but had dif-
ferent mass-specific energy and kinetic energy values (Fig 8,Table 2). While approaching the
feeder, both classes of defending trajectory decreased in elevation at similar rates, which re-
sulted in potential energy decreasing uniformly upon descent. The perch trajectories were at
higher flight speeds and thus higher kinetic energies.
We also measured the kinematic power output of the trajectories (i.e. the mass-specific rate
of change in kinetic and potential energy). Chased and freely-departing trajectories had similar
kinematic power outputs over the 0.3 second duration after initial departure (t-test, p = 0.5050;
Table 1). The mean power output for chased birds was 20.3 ± 8.4 W kg
-1
, and the mean power
output found for non-chased birds was 18.6 ± 6.8 W kg
-1
. The respective maximum kinematic
power output found for the two classes was 39.4 W kg
-1
and 33.0 W kg
-1
.
Table 1. Departing bird trajectories.
Freelydeparting bird
trajectories (n = 18)
Chased bird trajectories
(n = 31)
Statistical comparison
(unpaired t-test)
Flight speed at t
c
= 0.3s 3.0 ±0.8 (mean ±s.d.) 3.9 ±1.1 p = 0.0039
Maximum ight speed (m s
-1
) 5.4 ±1.4 6.2 ±1.3 p = 0.0629
t
ma
:t
c
at maximum average acceleration, t
c
0.3s (s)
0.17 0.08 -
Acceleration magnitude at t
ma
(m s
-2
) 9.1 ±4.8 14.6 ±5.7 p = 0.0025
Overall maximum acceleration (m s
-2
) 19.6 42.3 -
Kinetic + potential energy at t
c
= 0.3s (J kg
-1
) 35.1 ±2.1 35.2 ±3.0 p = 0.6812
Kinetic energy at t
c
= 0.3s (J kg
-1
) 4.7 ±2.6 8.3 ±4.2 p = 0.0046
Potential energy at t
c
= 0.3s (J kg
-1
) 30.4 ±1.1 27.2 ±2.3 p <0.0001
Mean kinematic power at 0 t
c
0.3s (W kg
-1
) 18.6 ±6.8 20.3 ±8.4 p = 0.5050
Maximum mean kinematic power 0 t
c
0.3s
(W kg
-1
)
33.0 39.4 -
Maximum angular velocity (degrees s
-1
) 258.8 ±107.4 334.8 ±149.2 p = 0.0627
Flight speed at maximum angular velocity (m s
-1
) 1.5 ±0.7 2.2 ±1.4 p = 0.0556
Maximum gravity-adjusted centripetal force (body
weights)
0.9 ±0.3 1.6 ±0.7 p = 0.0002
Flight speed at maximum gravity-adjusted
centripetal force (m s
-1
)
3.1 ±1.7 4.2 ±1.5 p = 0.0242
doi:10.1371/journal.pone.0125659.t001
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Mean kinematic power output from the defending bird trajectories was found for the 0.2
second range prior to the end of uniform descent. Unlike the departing birds, the defending
birdskinematic power was typically negative during this time frame, usually by decreasing
both speed and elevation. There were significant differences between the power outputs of
perch and non-perch defending bird trajectory classes (t-test, p = 0.0156; Table 2). The mean
kinematic power output for perch defender trajectories was -72.1 ± 53.8 W kg
-1
, compared to
-26.9 ± 47.7 W kg
-1
for other defender trajectories.
Fig 4. Flight speed in defending trajectories. The green cross markers show the mean flight speed of
defending birds that approached the feeder from a frequently-used perch. Error bars show the standard error
(n = 16 trajectories at t
d
= 0 and n = 15 at t
d
= 0.11 seconds). The pink diamond markers show the mean flight
speed of all other defending trajectories (n = 17 at t
d
=0,n=15att
d
= 0.09 seconds, and n = 11 at t
d
= 0.11).
The black asterisk markers show the mean flight speed of all defending birds (n = 33 at t
d
=0,n=30att
d
=
0.09, and n = 26 at t
d
= 0.20 seconds). (A) Gives the overall flight speed while (B) shows speed in the
horizontal (XY) projection of the trajectories and (C) shows vertical velocity. Note that a positive vertical
velocity is downward toward the ground and feeder. The trajectories were combined using a common t
d
where 0 is the time at which the trajectory passed through Z = -1.2 m.
doi:10.1371/journal.pone.0125659.g004
Field Flight Dynamics of Hummingbirds
PLOS ONE | DOI:10.1371/journal.pone.0125659 June 3, 2015 10 / 20
Angular dynamics
Higher angular velocities in all trajectories tended to occur at lower speeds (Fig 9A). The maxi-
mum angular velocities of freely-departing and chased bird trajectories did not differ signifi-
cantly (t-test, p = 0.0627; Table 1), and neither did the flight speeds at which these maneuvers
occurred. However, differences appeared when these results were examined in terms of centrip-
etal force rather than angular velocity (Fig 9B,Table 1). The maximum centripetal forces from
freely-departing and chased trajectories differed significantly (t-test, p = 0.0002; Table 1) as did
the speeds at which the forces were produced. Defending birds were similar to chased birds in
their maximum angular velocities (Table 3), but differed in other measures of turning perfor-
mance. The largest average centripetal forces were observed in defending bird trajectories and
Table 2. Defending bird trajectories.
Trajectories beginning at the typical
perch (n = 16)
Other trajectories
(n = 17)
Statistical comparison
(unpaired t-test)
Flight speed at t
d
= 0 (m s
-1
) 9.2 ±1.5 7.7 ±1.6 p = 0.0085
Horizontal ight speed at t
d
= 0 (m s
-1
) 7.8 ±1.3 6.3 ±1.5 p = 0.0040
Vertical ight speed at t
d
= 0 (m s
-1
) 4.8 ±1.0 4.2 ±1.6 p = 0.1920
Mean of maximum ight speeds (m s
-1
) 10.1 ±0.7 8.2 ±1.7 p = 0.0003
Overall maximum ight speed (m s
-1
) 12.0 10.7 -
Mean acceleration at t
d
= -0.2 (m s
-2
) 3.8 ±3.8 3.5 ±2.9 p = 0.8110
Mean acceleration at t
d
= -0.1 (m s
-2
) -1.0 ±8.1 4.2 ±4.3 p = 0.0350
Mean of maximum accelerations (m s
-2
) 10.1 ±6.8 10.4 ±3.9 p = 0.8898
Overall maximum acceleration (m s
-2
) 30.1 17.7 -
Mean of maximum decelerations (m s
-2
) -19.5 ±9.1 -15.1 ±7.6 p = 0.1371
Overall of maximum deceleration (m s
-2
) -28.4 -26.6 -
Kinetic + potential energy at t
d
= -0.2s (J kg
-1
) 96.4 ±8.6 80.5 ±18.5 p = 0.0074
Kinetic energy at t
d
= -0.2s (J kg
-1
) 44.7 ±7.6 30.4 ±16.3 p = 0.0061
Mean kinematic power at -0.2 t
d
0s (W kg
-1
) -72.1 ±53.8 -26.9 ±47.7 p = 0.0156
Maximum mean kinematic power -0.2 t
d
0s
(W kg
-1
)
-10.9 29.9 -
Maximum angular velocity (degrees s
-1
) 342.2 ±161.1 304.1 ±124.2 p = 0.4510
Flight speed at maximum angular velocity (m s
-1
) 3.7 ±2.7 4.0 ±2.5 p = 0.7674
Maximum gravity-adjusted centripetal force (body
weights)
2.2 ±0.5 2.1 ±0.9 p = 0.7173
Flight speed at maximum gravity-adjusted
centripetal force (m s
-1
)
6.9 ±2.4 5.9 ±2.1 p = 0.2944
doi:10.1371/journal.pone.0125659.t002
Table 3. Defending vs. Chased bird trajectories.
Defending bird trajectories
(n = 31)
Chased bird trajectories
(n = 31)
Statistical comparison (paired
t-test)
Mean of maximum ight speeds (m s
-1
) 9.2 ±1.6 6.3 ±1.3 p <0.0001
Maximum angular velocity (degrees s
-1
) 322.6 ±142.4 334.8 ±149.2 p = 0.7383
Flight speed at maximum angular velocity (m s
-1
) 3.9 ±2.6 2.2 ±1.4 p = 0.0006
Maximum gravity-adjusted centripetal force (body
weights)
2.1 ±0.7 1.6 ±0.7 p = 0.0051
Flight speed at maximum gravity-adjusted
centripetal force (m s
-1
)
6.2 ±2.3 4.2 ±1.5 p <0.0001
doi:10.1371/journal.pone.0125659.t003
Field Flight Dynamics of Hummingbirds
PLOS ONE | DOI:10.1371/journal.pone.0125659 June 3, 2015 11 / 20
Fig 5. Acceleration in departing trajectories. The red triangle markers show the mean acceleration of the
chased bird after departing the feeder (n = 31 trajectories at t
c
= 0 and n = 30 at 0.29 seconds). The blue circle
markers represent the mean acceleration after departure for freely-departing bird trajectories (n = 15). Error
bars show the standard error at each time instant. Measurements of the flight speeds of both classes of birds
were taken at different times after initial departure and a common timebase t
c
created with 0 as the instant
where the bird first reaches a speed of 0.4 m s
-1
.
doi:10.1371/journal.pone.0125659.g005
Fig 6. Acceleration in defending trajectories. The green cross markers show the mean acceleration of
defending bird trajectories that approached the feeder from a specific perch (n = 16 trajectories at t
d
= 0 and
n = 15 at t
d
= 0.11 seconds) while pink diamond markers show mean acceleration of all other defending bird
trajectories (n = 17 at t
d
= 0, n = 15 at 0.09 seconds, and n = 11 at 0.20 seconds). The black asterisk markers
are the mean acceleration of all defending trajectories (n = 32 at t
d
= 0, n = 30 at 0.09 seconds, and n = 26 at
0.20 seconds). Error bars show the standard error about the mean for the perch and nonperch data only.
doi:10.1371/journal.pone.0125659.g006
Field Flight Dynamics of Hummingbirds
PLOS ONE | DOI:10.1371/journal.pone.0125659 June 3, 2015 12 / 20
the overall maximum centripetal force (3.9 body weights) was a defending bird turning at a
flight speed of 7.0 m s
-1
.
Guidance and targeting
During the rapid descent phase (see above), the mean of the time-averaged angle between the
defending bird trajectory and the feeder was 6.3 ± 4.8 degrees among trajectories while the
mean of the angle between the defending trajectory and the current position of the chased bird
was 3.1 ± 2.3 degrees. The mean of the difference between these angles was 3.2 ± 4.1 degrees,
significantly different from 0 (t-test; p = 0.0001). The significance of this result was not sensi-
tive to the elevation threshold used to identify the initial rapid descent phase.
Discussion
On the whole, our results from the free-flight trajectory kinematics of Ruby-throated Hum-
mingbirds support hypotheses of maximum speed, flight force, acceleration and kinematic
Fig 7. Kinetic and potential energy in departure trajectories. Here we show the (A) mass-specific energy,
(B) potential energy, and (C) kinetic energy of hummingbird trajectories departing from the feeder location
under different conditions. The red triangle markers show the chased bird after departing the feeder (n = 31
trajectories at t
c
= 0 and n = 30 at 0.29 seconds). The blue circle markers show trajectories from freely-
departing birds (n = 15). The starting positions of all departing trajectories were set to the same value (3m
above the ground) to provide a common point of comparison for changes in energy.
doi:10.1371/journal.pone.0125659.g007
Field Flight Dynamics of Hummingbirds
PLOS ONE | DOI:10.1371/journal.pone.0125659 June 3, 2015 13 / 20
power derived from prior laboratory studies. In two cases, maximum flight force and kinematic
power, the trajectories reveal that hummingbirds reach their laboratory maxima during typical
field behavior, suggesting that these are more relevant performance measures for natural be-
havior than maximum level flight speed, which was not reached. We also found that humming-
birds vary how they partition gains in speed and elevation in chased versus freely-departing
flights but do not vary their overall kinematic power output. This further supports power as a
limiting factor in these interactions, as is suggested by a broader assessment of competitive suc-
cess in a range of hummingbird species [26].
Fig 8. Kinetic and potential energy in defending trajectories. Here we show the (A) mass-specific energy,
(B) potential energy, and (C) kinetic energy of trajectories from hummingbirds defending the feeder. The
green cross markers show data from defending birds that approached the feeder from a specific perch (n = 16
trajectories at t
d
= 0 and n = 15 at -0.11 seconds). The pink diamond markers show all other defending
trajectories (n = 17 at t
d
= 0, n = 15 at -0.09 to -0.20 seconds, and n = 11 at -0.20 seconds). The black asterisk
marker represents all defending trajectories (n = 31 at time zero, n = 30 at -0.09 to -0.20 seconds, and n = 26
at -0.20 seconds). Error bars show the standard error about the mean for perch and nonperch trajectories.
Unlike our treatment of departing bird potential energy, in (B) the starting positions of the birds were not set to
a common identical initial value but are nevertheless quite similar.
doi:10.1371/journal.pone.0125659.g008
Field Flight Dynamics of Hummingbirds
PLOS ONE | DOI:10.1371/journal.pone.0125659 June 3, 2015 14 / 20
Kinematics of chased versus non-chased departures
We hypothesized that bird trajectories departing from the feeder while being chased should ex-
hibit greater accelerations, flight speeds, and changes in kinetic and potential energy than those
departing alone because high flight speeds and accelerations are aerodynamically costly, gener-
ating additional drag or elevating induced power requirements, and offer little apparent benefit
for freely-departing birds. The first two of these hypotheses were supported by the data while
the third, greater kinematic power expenditure, was not.
Despite differences in speed and acceleration (Figs 3,5and Table 1), chased birds and free-
ly-departing bird trajectories both used approximately the same amount of energy during de-
parture (Fig 7A), but partitioned kinetic and potential components differently (Fig 7B and 7C).
The chased trajectories appear to maximize kinetic energy over potential energy, while freely-
departing trajectories balance both. Thus, the chased birds appear to exhibit a strategy for rap-
idly achieving an escape speed without increasing their overall energy expenditure compared
to a free-departure trajectory.
Kinetic power output and flight force
Our measures of kinematic power output further support the energetic equivalence of freely-
departing and chased bird trajectories, with both classes having statistically identical average
kinematic power output. Our whole-bird mass-specific power results also provide some addi-
tional data for comparison to other measures of power output based on metabolic and aerody-
namic measurements from other studies. These studies quantify many costs beyond the
resultant change in kinematic and potential energy state measured here such as the cost of pro-
ducing lift, cost of drag and efficiency of the flight muscle. Thus, our whole-body power
Fig 9. Turning rates and forces from all trajectories. Panel (A) shows the maximum rate of change in heading (i.e. angular velocity) and (B) the maximum
centripetal force versus flight speed from the trajectories of hummingbirds defending the feeder and from those departing the feeder. The black asterisks are
the defending birds (n = 33), red triangles are the departures of chased birds (n = 33) and the blue circles are freely-departing birds (n = 18). In both cases we
identified the time in the trajectory where the maximum rate of change in flight direction (A) or maximum centripetal force (B) occurred and plotted the data
against the speed at that instant. Computations in both cases were also limited to data points with speed >1ms
-1
.
doi:10.1371/journal.pone.0125659.g009
Field Flight Dynamics of Hummingbirds
PLOS ONE | DOI:10.1371/journal.pone.0125659 June 3, 2015 15 / 20
measurements should be much less than these other common measures of muscle or aerody-
namic power. However, our kinematic power measures can help delineate what fraction of
metabolic power expenditure could be due to other factors. For example, the whole-body meta-
bolic power requirements of Ruby-throated Hummingbirds range from ~258 to 322 W kg
-1
when flying in variable density gas mixtures [27] whereas the aerodynamic power requirement
for hovering flight in the same species was reported as 55 W kg
-1
in a recent computational
fluid dynamics (CFD) study [28]. Our recordings revealed an average kinematic power output
of ~19 W kg
-1
for birds departing from the feeder location with a maximum instantaneous
power of ~40 W kg
-1
, similar to the ~44 W kg
-1
kinematic power for reported for male Annas
hummingbirds engaged in courtship displays [29]. When compared with the metabolic and
aerodynamic measurements noted above, these results support our expectation that kinematic
power observations should be much less than metabolic power. However, the difference be-
tween our average and peak kinematic power measurements is ~20 W kg
-1
, similar to the dif-
ference between peak and hovering metabolic power measurements given the 20% muscle
efficiency implied by the CFD result in conjunction with hovering metabolic data. Thus, hum-
mingbirds appear to regularly burst to near their maximum sustainable power during typical
flight behavior.
Kinematic power was quantified for many bird species during vertical escape flights follow-
ing capture [30]; the mean hummingbird feeder-departure power of ~19 W kg
-1
is similar to
that extrapolated from the linear regression of all vertical escape species mean responses. How-
ever, the maximum reported hummingbird value is substantially less than the extrapolated
maximum vertical escape value; this might reflect the absence of anaerobic muscle in hum-
mingbirds or differences in kinematic data analysis methods.
A second case where laboratory measurements of flight performance can be compared to
our free-flight data lies in flight force as quantified by load lifting tests in lab and acceleration
in the field. Hovering Ruby-throated Hummingbirds can support an additional load of approx-
imately one body weight [31], implying a flight force surplus sufficient to accelerate an un-
loaded bird at ~10 m s
-2
horizontally or ~20 m s
-2
if foregoing weight support. Furthermore,
wild-caught Red-billed Streamertail hummingbirds achieved linear accelerations of up to ~20
ms
-2
during startle escapes from a feeder [32]. In contrast, the freely-departing trajectories in
our field recordings reveal a rather constant linear acceleration of ~8 m s
-2
, beginning when
flight speed is still less than 1 m s
-1
. Chased birds achieved similar accelerations at this speed,
but also continued to increase speed while losing elevation. These results suggest that the hum-
mingbirds used most (~80%) of their available maximum flight force when departing from the
feeder, even when not chased but did not forego weight support.
Centripetal forces also provide another measure of flight force, but since maneuvering forces
were greatest at faster flight speeds in the bird trajectories recorded here and aerodynamic
forces theoretically scale proportional to the square of velocity, they cannot be compared to
hovering load tests or initial departure accelerations. However, the maximum centripetal forces
recorded here of 3.9 body weights is substantially less than the maximum reported in record-
ings of free flight in Cliff Swallows (7.8 body weights) [13] and also from the courtship dive ma-
neuvers of Annas Hummingbirds (~9 body weights)[12]. Thus, the competitive intraspecific
interactions recorded here from Ruby-throated Hummingbirds may not be a good model for
studying maximum forward flight maneuvering performance.
Maximum speeds
Our hypothesis that the highest flight speeds would be found in the bird defending the feeder
was supported. The average maximum speed for a defending bird was found to be 9.2 ± 1.6 m
Field Flight Dynamics of Hummingbirds
PLOS ONE | DOI:10.1371/journal.pone.0125659 June 3, 2015 16 / 20
s
-1
, whereas the average maximum speeds for non-chased birds and chased birds were 5.4 ± 1.4
ms
-1
and 6.2 ± 1.3 m s
-1
, respectively. The maximum speed recorded for a defending bird was
12.0 m s
-1
. This is less than the maximum speed of ~15 m s-1 reached by this species in wind
tunnel flights [33] and much less than the greater than 20 m s
-1
speeds achieved by diving
Annas Hummingbirds during mating displays [12], a more comparable case since the defend-
ing and displaying birds both take advantage of gravitational potential energy to power their
flights. The mean maximum speed reached by freely-departing birds here (5.4 m s
-1
) was well
within the flight range exhibited by Rufous Hummingbirds flying in a wind tunnel over a range
of speeds [34], but not at any well-defined minimum flapping frequency or minimum flapping
amplitude within the speed range.
Guidance and targeting
Our initial hypothesis, based on preliminary observation of hummingbird interactions and the
expected priority of defending the feeder over targeting the encroaching bird, was that the de-
fending bird would initially fly toward the feeder, not the encroaching and subsequently chased
bird, was not supported. Although the chased bird and feeder were in close proximity for much
of the initial descent phase, the flight trajectory of the defending bird was significantly closer to
the position of the chased bird than the feeder. We rarely recorded a maneuver by the defend-
ing bird to turn and follow the departing chased bird; most defending bird trajectories ended
with the bird returning to a level or slightly upward trajectory in approximately the same hori-
zontal direction as its initial descent.
Differences among sexes
Ruby-throated Hummingbirds are sexually dimorphic, with males having smaller body size,
more pointed wings and higher wingbeat frequencies. These differences are associated with dif-
ferences in flight performance in laboratory environments [35] which might also exist in field
flight behavior. However, the typical behavioral roles adopted by the birds in a natural environ-
ment make comparisons difficult since most defending birds are male as are most freely-
departing birds while most chased birds are female, potentially confounding the comparisons
of chased and freely departing birds if females prefer a descending departure trajectory while
males prefer an ascending one. The only case where a sufficient sample of both sexes was col-
lected to allow a statistical comparison was for chased birds, 28 of which were female while 5
were male. In this case, peak accelerations occurred at similar times with males exhibiting a
non-significantly greater maximum acceleration (15.6 ± 4.1 vs. 14.4 ± 4.1 m s
-2
, p = 0.6607)
and average kinematic power (23.3 ± 4.0 vs. 19.7 ± 9.0 W kg
-1
, p = 0.3988). Differences in aver-
age kinematic power during departure among chased and freely departing males approached
significance for the previously defined departure duration (23.3 ± 4.0 vs. 18.1 ± 5.0 W kg
-1
,
p = 0.0619), although not for slightly longer durations.
Limitations of the study
Interpretation of the results of this study faces two primary limitationsuse of data from only
one recording location and uncertainty regarding the behavioral motivations of the birds and
how these may vary by the sexes of the birds involved in a particular encounter. Use of only
one site limits the generality of some aspects of the results; for example a different study site
with a different set of perches available for a defending bird would produce different flight tra-
jectories and possibly energy profiles given a difference in potential energy available to a de-
fender. Furthermore, use of only one site restricts the number of birds studied and our data set
certainly contains repeated measurements of the same bird. Since the birds themselves were
Field Flight Dynamics of Hummingbirds
PLOS ONE | DOI:10.1371/journal.pone.0125659 June 3, 2015 17 / 20
not marked in an individually identifiable manner, we are not able to statistically correct for
this effect, so some of our findings may reflect idiosyncratic differences among individuals
rather than differences associated with the environment or behavior. For example, all record-
ings of a defender coming from the typical perch could be a single bird with a greater flight
speed than other, casual, defenders who used other starting points.
We also do not know the precise behavioral motivation underlying the different bird-bird
interactions we recorded. We analyzed our results in a resource competition framework where
birds are defending or encroaching upon the feeder, emphasizing the territorial aspects of
hummingbird behavior. However, it is also plausible that the typically male defenderis in
fact performing a limited mating display to the typically female encroachingbird. Ruby-
throated hummingbird mating displays do include a U-shapedplummet and climb [22]by
the male near a perched female; this behavior was observed only once at the site during a scout-
ing trip prior to the recording days but does bear some resemblance to the plummet and swoop
defending bird trajectory described here. Mating displays in the related Annas Hummingbird
(Calypte anna) do include a dive followed by a chase [36], again somewhat similar to what was
recorded here although we did not observe extended chases of females by males. We also found
no statistical evidence for differences in flight kinematics based on the sex of the birds involved,
but as noted above our statistical power to test for these effects was quite limited.
However, our overall findings that freely behaving hummingbirdswhatever their motiva-
tionuse flight speeds much less the maximum achieved in laboratory wind tunnels close to
their expected maximum power output and act to use stored potential energy to enhance the
power available for types of maneuver. Examination of the effects of local environment and dif-
ferences in performance among known individuals form interesting topics for further study
given the results presented here.
Supporting Information
S1 Dataset. Field Flight Dynamics of Hummingbirds dataset. This archive contains the 3D
trajectory data files used as the basis for the analysis described in the manuscript. The data are
provided in a directory hierarchy where each recording day has a separate directory and each
recording within the day a separate subdirectory. These subdirectories contain a v7 MATLAB
data file "dataOut.mat" with a single struct variable "data" containing fields with the camera re-
cording frequency, the raw xyz coordinates, filtered xyz coordinates, velocities and accelera-
tions. Note that GNU Octave and Python can read v7 MATLAB data files. Also provided are
files specifying the trials used for different comparisons and the 3D position of the feeder in
each recording.
(ZIP)
Acknowledgments
We wish to thank the Hedrick lab personnel in general and Amanda Lohmann in particular for
their assistance in collecting and analyzing the video data as well as Dennis Evangelista for de-
veloping the autotracker software. Comments and feedback from two referees greatly improved
the manuscript.
Author Contributions
Conceived and designed the experiments: RMS TLH. Performed the experiments: KMS RMS.
Analyzed the data: KMS RMS. Contributed reagents/materials/analysis tools: TLH RMS.
Wrote the paper: KMS TLH.
Field Flight Dynamics of Hummingbirds
PLOS ONE | DOI:10.1371/journal.pone.0125659 June 3, 2015 18 / 20
References
1. Brown RHJ. The flight of birds: The flapping cycle of the pigeon. J Exp Biol. 1948; 25: 322333. PMID:
18115869
2. Hedrick TL, Tobalske BW, Biewener AA. Estimates of circulation and gait change based on a three-
dimensional kinematic analysis of flight in cockatiels (Nymphicus hollandicus) and ringed turtle-doves
(Streptopelia risoria). J Exp Biol. 2002; 205: 13891409. PMID: 11976351
3. Tucker VA. Bird metabolism during flight: Evaluation of theory. J Exp Biol. 1973; 58: 689709.
4. Tobalske BW, Hedrick TL, Dial KP, Biewener AA. Comparative power curves in bird flight. Nature.
2003; 421: 363366. PMID: 12540899
5. Morris CR, Nelson FE, Askew GN. The metabolic power requirements of flight and estimations of flight
muscle efficiency in the cockatiel (Nymphicus hollandicus). J Exp Biol. 2010; 213: 27882796. doi: 10.
1242/jeb.035717 PMID: 20675549
6. Bomphrey RJ, Lawson NJ, Harding NJ, Taylor GK, Thomas ALR. The aerodynamics of Manduca
sexta: Digital particle image velocimetry analysis of the leading-edge vortex. J Exp Biol. 2005; 208:
10791094. PMID: 15767309
7. Spedding GR, Rosén M, Hedenström A. A family of vortex wakes generated by a thrush nightingale
in free flight in a wind tunnel over its entire natural range of flight speeds. J Exp Biol. 2003; 206:
23132344. PMID: 12796450
8. Hubel T, Hristov N, Swartz S, Breuer K. Time-resolved wake structure and kinematics of bat flight. Exp
Fluids. 2009; 46: 933-943-943. PMID: 22736891
9. Ros IG, Bassman LC, Badger MA, Pierson AN, Biewener AA. Pigeons steer like helicopters and gener-
ate down- and upstroke lift during low speed turns. P Natl Acad Sci USA. 2011; 108: 1999019995. doi:
10.1073/pnas.1107519108 PMID: 22123982
10. Hedrick TL, Biewener AA. Low speed maneuvering flight of the rose-breasted cockatoo (Eolophus
roseicapillus) I. Kinematic and neuromuscular control of turning. J Exp Biol. 2007; 210: 18971911.
PMID: 17515416
11. Witter MS, Cuthill IC, Bonser RHC. Experimental investigations of mass-dependent predation risk in
the European starling, Sturnus vulgaris. Anim Behav. 1994; 48: 201222.
12. Clark CJ. Courtship dives of Anna's hummingbird offer insights into flight performance limits. Proc Biol
Sci. 2009; 276: 30473052. doi: 10.1098/rspb.2009.0508 PMID: 19515669
13. Shelton RM, Jackson BE, Hedrick TL. The mechanics and behavior of cliff swallows during tandem
flights. J Exp Biol. 2014; 217: 27172725. doi: 10.1242/jeb.101329 PMID: 24855672
14. Bahlman JW, Swartz SM, Riskin DK, Breuer KS. Glide performance and aerodynamics of non-
equilibrium glides in northern flying squirrels (Glaucomys sabrinus). J R Soc Interface. 2013; 10.
15. Byrnes G, Lim NT- L, Spence AJ. Take-off and landing kinetics of a free-ranging gliding mammal, the
Malayan colugo (Galeopterus variegatus). Proc Biol Sci. 2008; 275: 10071013. doi: 10.1098/rspb.
2007.1684 PMID: 18252673
16. Portugal SJ, Hubel TY, Fritz J, Heese S, Trobe D, et al. Upwash exploitation and downwash avoidance
by flap phasing in ibis formation flight. Nature. 2014; 505: 399402. doi: 10.1038/nature12939 PMID:
24429637
17. Chai P, Dudley R. Limits to vertebrate locomotor energetics suggested by hummingbirds hovering in
heliox. Nature. 1995; 377: 722725.
18. Warrick DR, Tobalske BW, Powers DR. Aerodynamics of the hovering hummingbird. Nature. 2005;
435: 10941097. PMID: 15973407
19. Wells DJ. Muscle Performance in Hovering Hummingbirds. J Exp Biol. 1993; 178: 3957.
20. Stolpe M, Zimmer K. Der Schwirrflug des Kolibri im Zeitlupenfilm. J Ornithol. 1939; 87: 136155.
21. Rousseu F, Charette Y, Bélisle M. Resource defense and monopolization in a marked population of
ruby-throated hummingbirds (Archilochus colubris). Ecol Evol. 2014; 4: 776793. doi: 10.1002/ece3.
972 PMID: 24683460
22. Poole A. The birds of North America online. Cornell Laboratory of Ornithology, Ithaca. 2005.
23. Theriault DH, Fuller NW, Jackson BE, Bluhm E, Evangelista D, et al. A protocol and calibration method
for accurate multi-camera field videography. J Exp Biol. 2014; 217: 18431848. doi: 10.1242/jeb.
100529 PMID: 24577444
24. Hedrick TL. Software techniques for two- and three-dimensional kinematic measurements of biological
and biomimetic systems. Bioinspir Biomim. 2008; 3: 034001. doi: 10.1088/1748-3182/3/3/034001
PMID: 18591738
Field Flight Dynamics of Hummingbirds
PLOS ONE | DOI:10.1371/journal.pone.0125659 June 3, 2015 19 / 20
25. Viola P, Jones M (2001) Rapid object detection using a boosted cascade of simple features. Computer
Vision and Pattern Recognition, 2001 CVPR 2001 Proceedings of the 2001 IEEE Computer Society
Conference on. IEEE. pp. I-511I-518 vol. 511.
26. Altshuler DL. Flight Performance and Competitive Displacement of Hummingbirds across Elevational
Gradients. Am Nat. 2006; 167: 216229. PMID: 16670982
27. Chai P, Dudley R. Limits to flight energetics of hummingbirds hovering in hypodense and hypoxic gas
mixtures. J Exp Biol. 1996; 199: 22852295. PMID: 8896366
28. Song J, Luo H, Hedrick TL. Three-dimensional flow and lift characteristics of a hovering ruby-throated
hummingbird. J R Soc Interface. 2014; 11.
29. Clark CJ. The role of power versus energy in courtship: what is the energetic costof a courtship dis-
play? Anim Behav. 2012; 84: 269277.
30. Jackson BE. The allometry of bird flight performance. The University of Montana. 2009.
31. Chai P, Chen JSC, Dudley R. Transient hovering performance of hummingbirds under conditions of
maximal loading. J Exp Biol. 1997; 200: 921929. PMID: 9100364
32. Clark CJ. Effects of tail length on an escape maneuver of the Red-billed Streamertail. J Ornithol. 2011;
152: 397408.
33. Chai P, Dudley R. Maximum Flight Performance of Hummingbirds: Capacities, Constraints, and Trade
Offs. Am Nat. 1999; 153: 398411.
34. Tobalske BW, Warrick DR, Clark CJ, Powers DR, Hedrick TL, et al. Three-dimensional kinematics of
hummingbird flight. J Exp Biol. 2007; 210: 23682382. PMID: 17575042
35. Chai P, Harrykissoon R, Dudley R. Hummingbird hovering performance in hyperoxic heliox: effects of
body mass and sex. J Exp Biol. 1996; 199: 27452755. PMID: 9110957
36. Stiles FG. Aggressive and courtship displays of the male Anna's hummingbird. Condor. 1982:
208225.
Field Flight Dynamics of Hummingbirds
PLOS ONE | DOI:10.1371/journal.pone.0125659 June 3, 2015 20 / 20
... Among all natural and human-made fliers, hummingbird flight represents an extreme form of agility and controlled stability at low flight speed [5]. These tiny vertebrate fliers routinely execute a variety of aerobatic feats with swiftness, precision and astonishing control, which are put into full display when they fight to defend territories [6], dance in courtship display [7] or escape from threats [8,9]. A casual observer can easily distinguish hummingbirds from other fliers by their unique manoeuvres (table 1). ...
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Hummingbirds routinely execute a variety of stunning aerobatic feats, which continue to challenge current notions of aerial agility and controlled stability in biological systems. Indeed, the control of these amazing manoeuvres is not well understood. Here, we examined how hummingbirds control a sequence of manoeuvres within milliseconds, and tested whether and when they use vision during this rapid process. We repeatedly elicited escape flights in calliope hummingbirds, removed visible light during each manoeuvre at various instants and quantified their flight kinematics and responses. We show that the escape manoeuvres were composed of rapidly controlled sequential modules including evasion, reorientation, nose-down dive, forward flight and nose-up to hover. The hummingbirds did not respond to the light removal during evasion and reorientation until a critical light-removal time; afterwards, they showed two categories of luminance-based responses that rapidly altered manoeuvring modules to terminate the escape. We also show that hummingbird manoeuvres were rate-commanded and required no active braking (i.e. their body angular velocities were proportional to the change of wing motion patterns, a trait that probably alleviates the computational demand on flight control). This work uncovers key traits of hummingbird agility, which can also inform and inspire designs for next-generation agile aerial systems.
... For each of the 11 individuals in the current study, forward flight velocity varied from around 0.5 to 4.5 m s -1 . Hummingbirds are capable of flying much faster, well over 10 m s -1 in wind tunnels [48] or in the field [49], but do generally fly slower through narrow passages [50]. Moreover, hummingbirds can easily transition from forward flight to hovering, which we observed an average of 2 to 8 times per tunnel transit, depending on treatment (electronic supplementary material, figure S2). ...
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The detection of optic flow is important for generating optomotor responses to mediate retinal image stabilization, and it can also be used during ongoing locomotion for centring and velocity control. Previous work in hummingbirds has separately examined the roles of optic flow during hovering and when centring through a narrow passage during forward flight. To develop a hypothesis for the visual control of forward flight velocity, we examined the behaviour of hummingbirds in a flight tunnel where optic flow could be systematically manipulated. In all treatments, the animals exhibited periods of forward flight interspersed with bouts of spontaneous hovering. Hummingbirds flew fastest when they had a reliable signal of optic flow. All optic flow manipulations caused slower flight, suggesting that hummingbirds had an expected optic flow magnitude that was disrupted. In addition, upward and downward optic flow drove optomotor responses for maintaining altitude during forward flight. When hummingbirds made voluntary transitions to hovering, optomotor responses were observed to all directions. Collectively, these results are consistent with hummingbirds controlling flight speed via mechanisms that use an internal forward model to predict expected optic flow whereas flight altitude and hovering position are controlled more directly by sensory feedback from the environment.
... 55 However, compared to them, the method using computer vision algorithms was more convenient and low cost, and helped obtain objects' trajectories which were hard to place the device on, and also did not interfere with the original movement. 56,57 This method helps further investigation on animate motion and animacy perception. ...
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Humans can distinguish flying birds from drones based solely on motion features when no image information is available. However, it remains unclear which motion features of animate motion induce our animacy perception. To address this, we first analyzed the differences in centroid motion between birds and drones, and discovered that birds exhibit greater acceleration, angular speed, and trajectory fluctuations. We further determined the order of their importance in evoking animacy perception was trajectory fluctuations, acceleration, and speed. More interestingly, people judge whether a moving object is alive using a feature-matching strategy, implying that animacy perception is induced in a key feature-triggered way rather than relying on the accumulation of evidence. Our findings not only shed light on the critical motion features that induce animacy perception and their relative contributions but also have important implications for developing target classification algorithms based on motion features.
... First, we used a weight-lifting assay to assess burst power, which is a measure of flight performance in hummingbirds [34,35]. Burst power is the maximum energetic output during hummingbird flight [35,36] and is related to agility and the ability to perform aerial manoeuvres that are used in direct competition and territoriality such as chasing and aerial fighting [34,35,37,38]. Second, we measured wing loading (i.e. the ratio of body weight to wing area) via wing shape measures, which are associated with aspects of manoeuvrability such as in-flight rotations, turns and acceleration [34,39], in addition to other wing parameters. ...
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Female-limited polymorphisms, where females have multiple forms but males have only one, have been described in a variety of animals, yet are difficult to explain because selection typically is expected to decrease rather than maintain diversity. In the white-necked jacobin (Florisuga mellivora), all males and approximately 20% of females express an ornamented plumage type (androchromic), while other females are non-ornamented (heterochromic). Androchrome females benefit from reduced social harassment, but it remains unclear why both morphs persist. Female morphs may represent balanced alternative behavioural strategies, but an alternative hypothesis is that androchrome females are mimicking males. Here, we test a critical prediction of these hypotheses by measuring morphological, physiological and behavioural traits that relate to resource-holding potential (RHP), or competitive ability. In all these traits, we find little difference between female types, but higher RHP in males. These results, together with previous findings in this species, indicate that androchrome females increase access to food resources through mimicry of more aggressive males. Importantly, the mimicry hypothesis provides a clear theoretical pathway for polymorphism maintenance through frequency-dependent selection. Social dominance mimicry, long suspected to operate between species, can therefore also operate within species, leading to polymorphism and perhaps similarities between sexes more generally.
... This is high for a hummingbird engaged in a low-speed, horizontal maneuver; maximum linear accelerations during take-off reported in Tobalske et al. (2004) were 37.4 ± 10.1 m s -2 ; Clark (2010) reported maximal accelerations of approximately 25 m s -2 in a horizontal maneuver in response to a startle stimulus. Sholtis et al. (2015) reported average accelerations of 14.6 ± 5.7 m s -2 for hummingbirds chased during territorial disputes. ...
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Among size-dimorphic animals, a few clades such as hummingbirds show “reversed” sexual size dimorphism: females tend to be the larger sex. What selects for this pattern? Sexual selection for flight performance could drive the evolution of smaller, more agile males, either for male-male combat or female choice for aerial courtship displays. Alternately, natural selection can select for female fecundity (e.g., egg size influences female body size), or sex differences in foraging niche could favor body size differences. The sexual selection hypotheses predict that dimorphism extends to other aspects of flight morphology (e.g., flight muscle size) whereas the natural selection hypotheses predict that male and female flight morphologies are isometric, and the niche differentiation hypothesis predicts that bill dimorphism is correlated with size dimorphism. We tested these predictions through phylogenetic comparative analyses of flight morphology, wingbeat frequency, and courtship behaviors, focused on 30 species within the “bee” hummingbird clade (tribe Mellisugini). There is no correlation between bill morphology and dimorphism. Relative to females, males tend to be smaller, have proportionately shorter wings and higher hovering wingbeat frequencies, but also longer keels and larger flight muscles. Male wingbeat frequencies are greatly elevated during aerial displays, and the species with the greatest wingbeat frequencies have the greatest dimorphism. Of the four hypotheses for dimorphism, the data best support the hypothesis that female choice for courtship displays has selected for aerial agility and small size in male hummingbirds.
... For instance, competition between a dominant and a subordinate species resulted in the subordinate species being excluded from higher-quality food resources when densities were high (Pimm 1985). Competitively dominant hummingbird species may have relatively larger body size than their competitors (Stiles and Wolf 1970, Wolf et al. 1976, Lanna et al. 2017), but dominance can also be predicted by maneuverability (Stiles and Wolf 1970, Feinsinger 1976, Sholtis et al. 2015, Dakin et al. 2018 or foraging strategy (Feinsinger 1976, Feinsinger andColwell 1978), rather than body size. As an example of the latter, large-bodied traplining hummingbirds with long curved bills forage by traveling between isolated patches and feeding from high-quality flowers that they do not defend (Feinsinger and Colwell 1978, Gill 1988, Temeles et al. 2006). ...
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Specific factors that determine whether hummingbirds feed from flowers matching their bill morphology are not well understood. Here, we asked whether long-billed hummingbirds at tropical mid-elevations visit flowers that match their bill morphology more often when those flowers are more energetically profitable in terms of nectar concentration compared to short-corolla flowers. We measured visitation rates by hummingbirds in 3 experiments involving feeders with 5 flower morphologies and 2 nectar concentrations in the mountains of Costa Rica. Not surprisingly, all species tended to prefer higher nectar concentration when given the choice across all available flower morphologies. When nectar concentration was the same across all flower morphologies, hummingbirds with bills shorter than 28 mm generally avoided long-corolla flowers (30 mm) and fed more frequently from short-corolla flowers (10 mm), while species with longer bills did not show a preference. When nectar concentration was higher in long-corolla flowers compared to short-corolla flowers (30% vs 10% m/v), short-billed species showed the same visitation rates as above, but long-billed species (>28 mm) changed their visitation patterns and visited long-corolla flowers significantly more often than short-corolla flowers. Our results suggest that visitation rates of long-billed hummingbirds to long-corolla flowers might be influenced more by nectar properties than by flower morphology at mid-elevations in the tropics. Los factores especficos que determinan si los colibres se alimentan de flores que se ajustan a la morfologa de su pico no se conocen bien. Aqu, nos preguntamos si los colibres de pico largo en elevaciones medias tropicales visitan ms frecuentemente las flores que se ajustan a su morfologa de pico cuando stas son energticamente mas rentables en trminos de concentracin de nctar comparadas con flores de corola corta. Medimos la tasa de visitacin de colibres en 3 experimentos que involucraron comederos con 5 morfologas florales y 2 concentraciones de nctar en las montaas de Costa Rica. Sin que resultara sorprendente, todas las especies prefirieron concentraciones de nctar mas altas en todas las morfologas florales cuando se les dio la opcin. Cuando la concentracin de nctar fue la misma en todas las morfologas florales, los colibres con picos mas cortos que 28 mm generalmente evitaron flores de corola larga (30 mm) y se alimentaron mas frecuentemente de flores de corola corta (10 mm), mientras que colibres de pico mas largo no mostraron preferencia. Cuando la concentracin de nctar fue mas alta en flores de corola larga comparada con flores de corola corta (30 vs 10% m/v), las especies de pico corto mostraron los mismos patrones de visitacin mencionados arriba, pero las especies de pico largo (>28 mm) cambiaron los patrones de visitacin y visitaron las flores de corola larga significativamente con mas frecuencia que las flores de corola corta. Nuestros resultados sugieren que las tasas de visitacin de colibres de pico largo a flores de corola larga se pueden ver influenciadas ms por las propiedades del nctar que por la morfologa floral en elevaciones tropicales medias. Palabras clave: alimentacin de colibres, coevolucin, concentracin de nctar, flores artificiales, forma floral, sndrome de polinizacin.
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Animals exhibit an abundant diversity of forms, and this diversity is even more evident when considering animals that can change shape on demand. The evolution of flexibility contributes to aspects of performance from propulsive efficiency to environmental navigation. It is, however, challenging to quantify and compare body parts that, by their nature, dynamically vary in shape over many time scales. Commonly, body configurations are tracked by labelled markers and quantified parametrically through conventional measures of size and shape (descriptor approach) or non-parametrically through data-driven analyses that broadly capture spatiotemporal deformation patterns (shape variable approach). We developed a weightless marker tracking technique and combined these analytic approaches to study wing morphological flexibility in hoverfeeding Anna's hummingbirds (Calypte anna). Four shape variables explained >95% of typical stroke cycle wing shape variation and were broadly correlated with specific conventional descriptors like wing twist and area. Moreover, shape variables decomposed wing deformations into pairs of in- and out-of-plane components at integer multiples of the stroke frequency. This property allowed us to identify spatiotemporal deformation profiles characteristic of hoverfeeding with experimentally imposed kinematic constraints, including through shape variables explaining <10% of typical shape variation. Hoverfeeding in front of a visual barrier restricted stroke amplitude and elicited increased stroke frequencies together with in- and out-of-plane deformations throughout the stroke cycle. Lifting submaximal loads increased stroke amplitudes at similar stroke frequencies together with prominent in-plane deformations during the upstroke and pronation. Our study highlights how spatially and temporally distinct changes in wing shape can contribute to agile fluidic locomotion.
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The gas exchange function of the avian respiratory system is explained. The following important structural—and functional aspects are presented: the mechanisms of airflow through the airway (bronchial) system and the air sacs; the four-phase respiratory modus operandi of the avian respiratory system and the inspiratory and the expiratory aerodynamic valving mechanisms by which air is shunted across the airways; the physiological adaptations of coping with hypoxia and hypocapnia, especially during high altitude residence and flight; the functional significance of the physical strength of the avian lung, the air and the blood capillaries and the blood-gas barrier; the gas exchange designs, namely, the countercurrent, the crosscurrent, and the multicapillary serial arterialization systems of the avian lung and; the morphometric specializations of phylogenetically different species of birds and those that lead various lifestyles. The exceptional functional efficiency of the avian respiratory system is highlighted.
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All visual animals experience optic flow—global visual motion across the retina, which is used to control posture and movement. The midbrain circuitry for optic flow is highly conserved in vertebrates, and these neurons show similar response properties across tetrapods. These neurons have large receptive fields and exhibit both direction and velocity selectivity in response to large moving stimuli. Hummingbirds deviate from the typical vertebrate pattern in several respects. Their lentiformis mesencephali (LM) lacks the directional bias seen in other tetrapods and has an overall bias for faster velocities. This led Ibbotson to suggest that the hummingbird LM may be specialized for hovering close to visual structures, such as plants. In such an environment, even slight body motions will translate into high-velocity optic flow. A prediction from this hypothesis is that hummingbird LM neurons should be more responsive to large visual features. We tested this hypothesis by measuring neural responses of hummingbirds and zebra finches to sine wave gratings of varying spatial and temporal frequencies. As predicted, the hummingbird LM displayed an overall preference for fast optic flow because neurons were biased to lower spatial frequencies. These neurons were also tightly tuned in the spatiotemporal domain. We found that the zebra finch LM specializes along another domain: many neurons were initially tuned to high temporal frequencies followed by a shift in location and orientation to slower velocity tuning. Collectively, these results demonstrate that the LM has distinct and specialized tuning properties in at least two bird species.
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In view of the complexity of the wing-beat kinematics and geometry, an important class of theoretical models for analysis and prediction of bird flight performance entirely, or almost entirely, ignores the action of the wing itself and considers only the resulting motions in the air behind the bird. These motions can also be complicated, but some success has previously been recorded in detecting and measuring relatively simple wake structures that can sometimes account for required quantities used to estimate aerodynamic power consumption. To date, all bird wakes, measured or presumed, seem to fall into one of two classes: the closed-loop, discrete vortex model at low flight speeds, and the constant-circulation, continuous vortex model at moderate to high speeds. Here, novel and accurate quantitative measurements of velocity fields in vertical planes aligned with the freestream are used to investigate the wake structure of a thrush nightingale over its entire range of natural flight speeds. At most flight speeds, the wake cannot be categorised as one of the two standard types, but has an intermediate structure, with approximations to the closed-loop and constant-circulation models at the extremes. A careful accounting for all vortical structures revealed with the high-resolution technique permits resolution of the previously unexplained wake momentum paradox. All the measured wake structures have sufficient momentum to provide weight support over the wingbeat. A simple model is formulated and explained that mimics the correct, measured balance of forces in the downstroke- and upstroke-generated wake over the entire range of flight speeds. Pending further work on different bird species, this might form the basis for a generalisable flight model.
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The aggressive and courtship displays and vocalizations of the male Anna's Hummingbird (Calypte anna) are described in detail, and various types of evidence and observations are used to reconstruct the typical courtship sequence. Initial contact is made by the female flying to the male's territory and attempting to feed; she may have previously visited several other territories in order to evaluate territory quality. The well-known dive display is an aggressive maneuver by the male, although it may play a role very early in the courtship sequence. Following a lengthy chase towards the female's nesting area, she alights low in dense vegetation. The male then gives the displays most critical for courtship: a back-and-forth "shuttle" display and high-intensity song. These hitherto undescribed displays occur immediately preceding copulation, and are probably the most important isolating mechanisms for the species. Many of the elements of courtship in C. anna are widespread in hummingbirds. Practice and probably learning play a major role in the maturation of song and dive displays in the individual. The courtship sequence in this hummingbird probably represents the resultant of various selective pressures, some acting mainly on males and others on females.
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Resource defense behavior is often explained by the spatial and temporal distribution of resources. However, factors such as competition, habitat complexity, and individual space use may also affect the capacity of individuals to defend and monopolize resources. Yet, studies frequently focus on one or two factors, overlooking the complexity found in natural settings. Here, we addressed defense and monopolization of nectar feeders in a population of free-ranging ruby-throated hummingbirds marked with passive integrated transponder (PIT tags). Our study system consisted of a 44 ha systematic grid of 45 feeders equipped with PIT tag detectors recording every visit made at feeders. We modeled the number of visits by competitors (NVC) at feeders in response to space use by a focal individual potentially defending a feeder, number of competitors, nectar sucrose concentration, and habitat visibility. Individuals who were more concentrated at certain feeders on a given day and who were more stable in their use of the grid throughout the season gained higher exclusivity in the use of those feeders on that day, especially for males competing against males. The level of spatial concentration at feeders and its negative effect on NVC was, however, highly variable among individuals, suggesting a continuum in resource defense strategies. Although the apparent capacity to defend feeders was not affected by competition or nectar sucrose concentration, the level of monopolization decreased with increasing number of competitors and higher nectar quality. Defense was enhanced by visibility near feeders, but only in forested habitats. The reverse effect of visibility in open habitats was more difficult to interpret as it was probably confounded by perch availability, from which a bird can defend its feeder. Our study is among the first to quantify the joint use of food resource by overlapping individuals unconstrained in their use of space. Our results show the importance of accounting for variation in space use among individuals as it translated into varying levels of defense and monopolization of feeders regardless of food resource distribution.
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Cliff Swallows (Petrochelidon pyrrhonota) are highly maneuverable social birds that often forage and fly in large open spaces. Here we used multi-camera videography to measure the three dimensional kinematics of their natural flight maneuvers in the field. Specifically, we collected data on tandem flights, defined as two birds maneuvering together. These data permit us to evaluate several hypotheses on the high-speed maneuvering flight performance of birds. We found that high speed turns are roll-based, but that the magnitude of the centripetal force created in typical maneuvers varied only slightly with flight speed, typically reaching a peak of ~2 body weights. Turning maneuvers typically involved active flapping rather than gliding. In tandem flights the following bird copied the flight path and wingbeat frequency (~12.3 Hz) of the lead bird while maintaining position slightly above the leader. The lead bird turned in a direction away from the lateral position of the following bird 65% of the time on average. Tandem flights vary widely in instantaneous speed (1.0 to 15.6 m s(-1)) and duration (0.72 to 4.71 s), and no single tracking strategy appeared to explain the course taken by the following bird.
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The influence of mass on escape ability in the European starling was investigated with reference to aerial manoeuvrability and take-off ability. Experimental groups of higher body mass were less manoeuvrable. In the take-off experiments, manipulations of mass influenced predominantly trajectory rather than velocity or distance covered in a given time. The take-off strategies observed may represent a trade-off between maximizing rate of ascent and maximizing escape velocity. Under increased load, the birds appeared to 'defend' escape velocity at the expense of rate of ascent. It is argued that if these changes in escape performance are important determinants of predation risk then changes in body mass, or the effects of such changes, should be incorporated into decisions that might result in exposure to predation. Consistent with this proposition, manipulations of body mass influenced the decision to leave protective cover; alternative interpretations of this result are also considered. In a separate procedure, the hypothesis that perceived predation risk influences the amount of stored fat was investigated by varying the availability of protective cover. Where most cover was available, fat reserves, scored from visible subcutaneous fat deposits, were highest. There was no relationship, however, between wing loading (body weight/wing area) and protective cover, suggesting that other components of body mass may change in association with fat reserves. The relevance of these results for regulation of body mass and mass-allocation strategies is discussed.
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Highlights ► There are two widely used definitions of the ‘energetic cost’ of a display. ► Many ‘energetic’ displays do not cost many joules, if their duration is short. ► Short duration displays may entail high power output, and power output may be limited. ► Such displays may showcase the animal's motor performance, including power output capacity.