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First published online April 17, 2009
Journal of Experimental Biology 212, 1392-1404 (2009)
Published by The Company of Biologists 2009
doi: 10.1242/jeb.027045
Adaptive echolocation behavior in bats for the analysis of auditory scenes
Department of Psychology, Neuroscience and Cognitive Science Program, University of Maryland, College Park, MD 20742, USA
* Author for correspondence (e-mail: chiuc{at}umd.edu)
Accepted 23 February 2009
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Summary |
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 TOP Summary INTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONReferences |
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Key words: bats, echolocation, adaptive vocal behavior, flexibility, call design, auditory scene analysis, conspecifics
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INTRODUCTION |
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TOPSummaryINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONReferences |
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; Hulse,
2002). For example, when a sentence spoken by one person, together
with background noise from the environment, arrives at a listener's ear, the
listener must process the acoustic signals, integrate meaningful segments and
separate these sounds from background noise. The ability to analyze auditory
scenes is exhibited by humans and other animal species, such as birds and
frogs, which rely heavily on acoustic communication
(Hulse, 2002).
Bregman provides numerous examples demonstrating that a human listener can
separate and identify auditory objects by listening to differences in the
pitch, timbre, melody and temporal pattern of a sound sequence
(Bregman, 1990). Auditory
signals that fall in different frequency bands, for example, can provide a cue
for a human listener to segregate sounds into separate auditory streams. A
listener tends to segregate acoustic signals with large frequency differences
into separate auditory streams, and to group those with small differences in
frequency into the same auditory stream
(Carlyon, 2004;
Darwins, 1997;
Moore and Gockel, 2002).
Spectral or temporal cues used by human listeners can be applied to the
understanding of auditory scene analysis in animal models as well. Previous
studies have demonstrated that frequency separations and differences in
temporal patterns of acoustic stimuli are important factors that affect
auditory stream segregation in fish, anurans and birds. Goldfish can segregate
two sequences of pulses according to the differences in repetition rates and
spectral features (Fay, 1998;
Fay, 2000). Separation in
spectral features of vocalizations and call timing are crucial factors that
affect acoustic behavior in frogs (Farris
et al., 2005; Greenfield and
Rand, 2000; Narins,
1992; Schwartz,
1993) and birds (Hulse et al.,
1997; Wisniewsky and Hulse,
1997).
It is particularly important for echolocating bats to perceive and interpret auditory scenes, because they generate sonar pulses and listen to the features of echoes reflected from objects to perceive their surroundings. Their ability to orient, capture prey and avoid obstacles all depend on correctly grouping and segregating echoes from sonar targets in a complex environment and on differentiating their own calls/echoes from those produced by other bats in their surroundings.
Background noise and calls/echoes from other animals may influence a bat's
perception of auditory objects. Past studies have reported that bats modify
the spectral–temporal features of their vocalizations in response to the
presence of conspecifics. Field recordings have shown that bats flying in
groups produce calls with different frequencies and/or temporal patterns than
those flying alone (Obrist,
1995; Ulanovsky et al.,
2004). A playback experiment showed that Tadarida
brasiliensis raised the end frequency of the frequency modulated (FM)
sweep in response to playback jamming signals, whose frequencies were equal to
the average end frequencies of this species' sonar calls
(Gillam et al., 2007). It has
been hypothesized that the bat modifies its call design in order to avoid
interference from the vocalizations of conspecifics and improve localization
of auditory objects.
Most studies of echolocation behavior in the presence of conspecifics have
been conducted in the field and lack records of the 3-D positions of the bats
and call design changes in identified individuals. Differences in call design
measured in most previous studies could have been evoked by the presence of
conspecifics but could also have been pre-existing inter-individual
differences prior to the introduction of conspecifics. Only one study so far
has demonstrated a shift of the bat's call frequency in response to the
broadcast of jamming signals in unidentified bats in the field
(Gillam et al., 2007).
We paired bats in a large flight room, presented a single prey item and recorded each bat's echolocation calls before (baseline) and during (two-bat) pairing. Recordings from ultrasound-sensitive microphones and high-speed stereo video enabled us to track vocalizations and flight trajectories in individual bats. We hypothesize that bats adjust features of their echolocation calls when flying in the same air space in order to analyze auditory scenes and avoid signal jamming. This leads us to predict that the amount of call modification may be related to the similarity in baseline call design of individual bats, the relative position between paired bats and the timing of successive vocalizations. We report here the first detailed study to address changes in sonar call design of identified free-flying echolocating bats in response to vocalizing conspecifics. Results of this study extend our understanding of the echolocating bat's active vocal control in the analysis of auditory scenes.
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MATERIALS AND METHODS |
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TOPSummaryINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONReferences |
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Experimental setup
All eight bats were first trained to fly and capture a tethered mealworm
Tenebrio molitor Linnaeus in a large anechoic flight room
(7x6x2.5 m) (LxWxH) equipped with synchronized audio
and high-speed stereo video equipment. After each bat reached the success
capture rate of 80%, we began to record its echolocation calls and flight
paths. During data recording, only long-wavelength lighting (>650 nm) was
available, preventing the bat from using visual cues to localize the target
and conspecifics (Hope and Bhatnagar,
1979).
Bats were tested in two experimental conditions, baseline and two-bat conditions, with 10–20 trials per day in each condition. Baseline data were recorded when a bat flew and captured a tethered mealworm alone in the room. Two-bat data were collected when paired bats flew and competed to capture a single tethered mealworm. Paired bats were released simultaneously from the same spot in the flight room and the releasing spot was always the same in baseline and two-bat conditions. Baseline and two-bat data were recorded on different test days. Ten trials per day over four test days were recorded in the baseline condition, yielding at least 40 baseline trials for each bat. Fifteen trials per day over a minimum of three test days, yielding at least 45 two-bat trials per bat pair, were recorded in the two-bat condition after completely finishing collecting baseline data. Between 20 and 30 trials per individual/pair with high-quality audio and video recordings from each condition were selected for further analysis.
Data recordings
Audio data were recorded with three ultrasound-sensitive microphones
(UltraSound Advice, London, UK) on the floor, and video data were recorded
with two high-speed digital video cameras (Kodak MotionCorder Analyzer, Model
1000, 240 frames s–1; San Diego, CA, USA) mounted in two
adjacent corners of the flight room, permitting the 3-D reconstruction of the
bat's flight path. The frequency response of all three microphones was flat
within ±3 dB for frequencies between 20–90 kHz. The sensitivity
dropped by 10 dB for frequencies between 90 and 100 kHz. An eight second
circulating buffer of audio and video recordings was end-triggered
synchronously by the investigator when the bat made contact with the tethered
worm in each trial. The audio and video data from each trial were analyzed
off-line using two custom MATLAB programs (Mathworks, Natick, MA, USA) (see
below).
Data analysis
A custom MATLAB program was used to analyze audio data, and five parameters
were applied to characterize the call design of an FM sonar vocalization.
These five parameters are duration (ms), bandwidth (kHz), start and end
frequencies of the FM sweep (kHz) and sweep rate (kHz ms–1),
all taken from the fundamental. Sweep rate is calculated by dividing bandwidth
by duration and describes the slope of the FM call. Data analysis of video
recordings was accomplished by digitizing the position of each bat and
microphone and reconstructing the 3-D flight path via another custom
MATLAB program.
Data analysis for audio recording in the two-bat condition was different
from the one-bat condition, because the ultrasound-sensitive microphones on
the floor recorded the vocalizations from both bats, and it was necessary to
associate a given echolocation call with the individual bat that produced it.
For the two-bat condition, we first visually inspected all echolocation calls
in the three audio recording channels, and assigned calls manually to each bat
according to differences in signature using the same custom MATLAB program
employed to analyze the baseline audio data. Each call's onset times in two
different microphones were marked in order to calculate the actual audio delay
(Fig. 1). Because the
microphones were positioned at different locations in the room, a call that
was produced by a bat would reach these microphones at different times. The
actual audio delay of one call refers to the difference of the recorded
signal's onset time between two microphones. The position of these two
microphones and paired bats were already established by video data analysis.
The estimated audio delay was computed by measuring the distance of each bat
to the microphones and estimating the acoustic signal travel time differences
of the calls at each of these microphones. When we assigned a given call to
the vocalizing individual, we confirmed that the actual and estimated audio
delays were the same. Therefore, by comparing the values of actual and
estimated audio delay, we could unambiguously associate each echolocation call
to the bat that vocalized. Detailed analysis methods are reported in Chiu et
al. (Chiu et al., 2008).
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RESULTS |
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TOPSummaryINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONReferences |
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Analysis of sequential calls produced by paired bats
The most common flight behavior of paired bats in this study was following
flight, which is defined as one bat flying behind the other bat and both bats
heading toward a similar direction (the angle between paired bats' headings is
acute). About 66% of the time in this study one bat followed the other one,
10% of the time two bats flew toward each other and another 24% of the time
bats flew away from each other (Chiu et
al., 2008). Individual bats usually showed differences in call
design and these differences may be used to avoid call interference from
neighboring conspecifics. Fig.
2 shows the flight trajectories, relative positions and call
design measurements of each bat in a pair from two selected trials. One bat
was following another bat in the first example and gradually shortened its
distance to the other animal (Fig.
2A,B). The separation in start frequency between the sonar calls
of paired bats increased as the inter-bat distance decreased. Small
separations were observed in their sonar call end frequencies, and changes in
the inter-bat spacing did not appear related to these separations. These two
bats maintained a small separation in call duration and sweep rate but the
separation also did not change with inter-bat spacing. Bats in the second
example were flying almost in parallel at the beginning of the segment and
subsequently one bat fell behind the other bat before their flight paths
diverged (Fig. 2C,D). These two
bats maintained a small amount of separation in call frequency as they flew in
close proximity. Separation in call duration was similar to that in the first
example but separations in call sweep rate were smaller than those in example
No. 1. This example does not show any systematic increase in call design
separation with decreasing inter-bat distance but all the data presented come
from distances of less than 85 cm.
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Similarity in baseline call frequency was also related to how the bat adjusted its call frequency in response to nearby conspecifics. We calculated the proportion of one bat's vocalizations with higher start/end frequencies than the other bat in a pair, and selected the proportion belonging to the individual with higher baseline call frequency to plot as a function of the baseline frequency separation (Fig. 6). A positive correlation between these two measurements means that the individual with the higher start frequency maintained this higher frequency in the two-bat condition for those bat pairs with greater start frequency separations in the baseline condition. The same relationship also applies to call end frequency. Therefore, whether the bat called at a higher frequency than the other bat in the two-bat condition or not depended on baseline call frequency design.
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Temporal separation of successive calls
Temporal separation in sonar calls could also be a factor affecting the
echolocation call design adjustments of paired bats. Bats dynamically varied
the interval between successive calls and timed their sonar vocalizations to
avoid overlap with the other bat's calls. In this study, only 9.41% of calls
produced by paired bats overlapped for any portion of the signal duration. The
effect of temporal separation between successive calls produced by different
bats was examined by comparing the call design separation of paired bats as a
function of the time window separating their calls. We divided successive
calls into two groups; one with a short time window (
5 ms) separating the
signals of the two bats and one with a longer time window (>5 ms)
separating the signals of the two bats. As the relative position of the bats
and microphones was recorded in this study, we were able to calculate each
bat's vocalization time and the time this call arrived at the other bat's
ears. Therefore, the temporal separation of calls produced by two bats is
defined here by the interval between the time when the call of one animal
reached the ears of the other (listening) animal and the time when the
listening animal produced its next call. We applied an independent sample
t-test to examine whether the time window separating the sequential
calls of the two bats influenced design adjustments in the features of calls.
When the time window between the call received by one bat and its next sonar
call was less than 5 ms, the magnitude of separation between call features was
significantly greater than when this time window was greater than 5 ms (for
all five parameters, P<0.05).
Analysis of global call adjustments by individual bats
Sequential call analysis reveals the dynamic and short-term call design
changes in paired bats. Here we examine differences in vocalizations between
baseline and two-bat conditions in each bat in a pair to determine the general
pattern of call structure adjustments in individual bats.
Direction and magnitude of call feature adjustments across bat pairs
Call design in the two-bat condition minus that in the baseline condition
represented the amounts of change from the baseline condition, and all bats
modified at least one call parameter when paired with another bat
(Fig. 8). Call design changes
in different pairs analyzed by one-sample t-tests revealed a
significant decrease in start frequency and bandwidth in all individuals,
except one bat in pair 5. This particular individual in pair 5 only modified
its sweep rate when paired with another bat but the other individual in pair 5
modified its start frequency, bandwidth and sweep rate. No consistent change
pattern was observed in the direction of sonar call end frequency, duration
and sweep rate but most bats made either spectral or temporal adjustments in
their call designs when paired with another individual. Five individuals did
not show a significant increase in the end frequency of their vocalizations
when paired, and both bats in pairs 2 and 5 did not change the end frequency
of their calls. When one individual in a pair shifted its call design, the
other bat did not always modify its call design in the opposite direction.
Most bats adjusted their start frequency and bandwidth in the two-bat
condition, and end frequency was the call parameter that exhibited the fewest
changes.
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Call adjustment depends on pulse interval
Call design adjustment by an individual bat varied with the rate at which
it produced sonar calls. The magnitude of call design adjustment refers to the
absolute difference between each individual bat's call design in baseline and
two-bat conditions and it is plotted as a function of pulse intervals in
Fig. 9. Pulse intervals were
divided into five time bins of 5 ms intervals. Pulse intervals below 10 ms
were excluded from this analysis to eliminate feeding buzzes. Differences in
magnitude of call adjustment were significantly influenced by pulse interval
(one-way ANOVA, P<0.05 for all five parameters). The
Scheffé test was used for post-hoc comparisons to determine
whether call parameter adjustments differed across pulse interval bins. The
magnitude of start/end frequencies, bandwidth and sweep rate adjustment
decreased as pulse intervals increased, and the magnitude of duration
adjustment showed the reversed trend. When pulse intervals were less than 30
ms, the magnitude of start frequency and bandwidth adjustment was the largest.
Big brown bats showed the largest change in call sweep rate from baseline
producing sounds with intervals between 10 and 15 ms. The magnitude of sweep
rate adjustment decreased for longer pulse intervals.
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DISCUSSION |
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TOPSummaryINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONReferences |
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; Hulse,
2002). This study explores how the echolocating bat orients in a
dark flight room in the presence of another individual whose sonar signals are
similar to its own. Results show that bats modified their call design
significantly in the two-bat condition, and paired bats enlarged the
differences between the time–frequency structures of their
vocalizations. These differences in call design were affected by the spatial
separation between paired bats and by the similarity in baseline call design
of individual bats. Distinct spectral features or temporal patterns can help
bats integrate and segregate auditory streams in a complex environment
(Moss and Surlykke, 2001). The
results of this study suggest possible acoustic cues, arising from call design
differences, which could allow echolocating bats to segregate echoes from
their own sonar vocalizations from the sonar signals of nearby
conspecifics.
Rule one for signal modification: individual signature and similarity in call design
Signals with individual signature have been discovered in active sensing
animals and one possible advantage of these personal signals is for animals to
segregate their signals from those of conspecifics. Wave-type weakly electric
fish produce an individual-specific electric organ discharge (EOD) frequency
and are capable of discriminating signals generated by different individuals
(McGregor and Westby, 1992).
Adult female bats can identify their own pups when many other pups are calling
in the background simultaneously. Each pup produces isolation calls with
spectral and temporal features distinct from others, and female bats may use
individual-specific isolation calls to help identify their own offspring
(Balcombe, 1990;
Gelfand and McCracken, 1986;
Knörnschild et al.,
2007). A psychoacoustic experiment shows that female greater
spear-nosed bats, Phyllostomus hastatus, are capable of
discriminating a specific pup's isolation calls from others
(Bohn et al., 2007).
Not only do pups show individual signatures in their isolation calls but so
also do adult bats. Inter-individual differences in call design have been
observed in several bat species (Siemers
et al., 2005; Siemers and
Kerth, 2006). Echolocation calls of E. fuscus show
individual identity, age and group variation
(Masters et al., 1995), and
female bats of this species recognize the gender of other bats by listening to
their vocalizations (Kazial et al.,
2001). Other bat species, such as Molossus molossus, Myotis
lucifugus, Nycticeius cubanus and Otomops martiensseni, also
produce distinct echolocation calls for those individuals from different
groups (Fenton et al., 2004;
Kössl et al., 1999;
Mora et al., 2005;
Pearl and Fenton, 1996).
Previous studies have demonstrated that conspecific bats often produce calls with different design features, and bats are capable of discriminating call design differences at the individual level. Differences in these individual-specific calls may be enough for the auditory system to segregate different acoustic sources. The correlation between the similarity in call features of bats flying alone and the magnitude of change when paired indicates that echolocating bats can use personal signals to avoid call jamming from conspecifics, as long as the differences in these individual-specific signals are discriminable. In this study, each individual in a pair increased differences in calling frequencies or bandwidth if baseline vocalizations showed similar spectral features to the bat it was paired with. Paired bats, whose calls already showed considerable design feature separation in the baseline condition, did not increase their differences in start/end frequencies and bandwidth. For those pairs with less similar baseline calling frequencies, the bat with the higher frequency vocalizations tended to maintain higher calling frequencies.
The estimated amount of separation required for paired bats to distinguish
their own calls/echoes from those of a conspecific can be inferred from this
study. The mean separations in call design of paired bats when flying together
were 13.51 kHz for start frequency, 4.62 kHz for end frequency, 1.83 ms for
duration, 12.05 kHz for bandwidth and 6.11 kHz ms–1 for sweep
rate. These mean values provide an estimate of discriminable spectral and
temporal feature separations in call design of paired big brown bats. Two
pipistrelle bats, Pipistrellus pipistrellus and Pipistrellus
pygmaeus, produce calls with peak frequencies of 45 and 55 kHz,
respectively. Their call design changed when they flew with conspecifics but
their calls remained the same when flying with heterospecifics
(Bartonicka et al., 2007). The
authors of this previous study suggested that call difference between these
two pipistrelle species, which is 10 kHz, is enough to avoid jamming among
heterospecifics. Separation of 10 kHz in the peak frequencies of pipistrelle
bats is between the mean start frequency (13.51 kHz) and end frequency (4.62
kHz) separation in the present study. The constant frequency component of
lesser mouse-tailed bat's (Rhinopoma hardwickei) echolocation calls
tend to fall into one of three different frequency bands (30, 32.5, 35 kHz)
when they fly in a group (Habersetzer,
1981). This result suggests that a 2.5–5 kHz separation in
call frequency is enough for R. hardwickei to discriminate
differences between its own echolocation call and the calls of conspecifics.
These findings suggest a reference for conducting further psychoacoustic
experiments on the bat's ability to discriminate signals with different
time–frequency structures.
Rule two for signal modification: spatial separation
We analyzed in detail vocal changes the bat made in response to the
presence of another bat at a particular spatial separation, because recording
and analysis methods permitted us to associate each call with an identified
individual and its 3-D position with respect to the animal. Short-term changes
in vocalizations can be detected by a sequential call analysis, as one bat may
enlarge differences between its calls and those of the other bat for a short
period of time when call interference is large. We discovered that separation
in call design is dependent on the inter-bat distance. Start/end frequencies,
duration and bandwidth of the FM sweep showed the largest differences between
paired bats when the inter-bat distance was shorter than 0.5 m. The magnitude
of call interference became high when paired bats flew close to each other and
one bat in a pair sometimes stopped vocalizing for more than 0.2 s, possibly
to avoid signal jamming from conspecifics. Silence has been observed in paired
echolocating bats competing for a single food item, and it has been
hypothesized that silence is a strategy used by bats to avoid call
interference (Chiu et al.,
2008). When both bats vocalized at short inter-bat distances, the
separation of their call features increased as well. Our data suggest that
bats increased their call feature separations to avoid interference caused by
another bat nearby, and greater inter-bat distances could help bats resolve
the problem of conspecific sonar interference. Other animal species have been
found to maintain spatial separation among individuals when communicating in
complex acoustic environments, potentially to avoid call interference. For
example, male frogs typically maintain a minimum distance in a chorus
(Gerhardt and Huber,
2002).
Rule three for call modification: temporal separation of successive calls
In this study, only occasionally did vocalizations of paired bats overlap
in time. Instead, there were temporal gaps between the calls of individual
bats, and the intervals between calls varied over the course of each trial.
Two bird species, the red-eyed vireo (Vireo olivaceus) and the least
flycatcher (Empidonax minimus), modify temporal patterns of their
songs to avoid signal overlap (Ficken et
al., 1974). Male singing nightingales (Luscinia
megarhynchos) sing preferentially during the silent windows between
heterospecific songs in order to transmit their songs more efficiently
(Brumn, 2006). The cotton-top
tamarins (Saguinus oedipus) can adjust their vocalizing time to fall
into the silent windows between white noises
(Egnor et al., 2007). The
tropical frog, Eleutherodactylus coqui, also adjusts the timing of
its mating calls to fall in gaps between the vocalizations of neighboring
frogs (Narins, 1992;
Zelick and Narins, 1983). The
echolocating bat could apply the same principle by listening to the other
bat's vocalizations to select its call timing, and when intervals between the
calls of paired bats are short enough to create interference, this may drive
further adjustments to sonar signal design. Support for this comes from our
present finding that the largest call design separations occurred when one bat
vocalized less than 5 ms after the other bat's vocalizations. The increases in
call design differences for closely timed calls imply that the big brown bat
actively controls timing and call features to avoid call interference from
conspecifics. As elaborated below, behavioral studies of echo ranging by
echolocation in bats have reported that interfering signals disrupt distance
discrimination, and the acoustic feature and temporal separation between
jamming signals and echoes affects the magnitude of interference
(Masters and Raver 1996;
Møhl and Surlykke 1989;
Roverud, 1989;
Roverud and Grinnell, 1985a;
Roverud and Grinnell,
1985b).
Global signal adjustments in the presence of conspecifics
Big brown bats changed features of their echolocation calls when flying
with conspecifics. The question of whether the observed differences in call
features are the result of active jamming avoidance or simply due to
individual-specific call design can be resolved here by comparing calls in the
two-bat condition with baseline vocalization data. In our study, most
individuals flying in pairs showed significant changes in each call parameter
compared with the calls produced in baseline recordings when each flew alone,
suggesting that the presence of the conspecific elicited vocal adjustments.
Call design separation was affected by the spatial distance between paired
bats and baseline similarity in call design, which further suggests that the
bat actively adjusts its call design to avoid signal interference from
conspecifics.
Several bat species, including R. hardwickei, Balantiopteryx plicata,
T. brasiliensis and Tadarida teniotis, have been reported to
adjust their call frequencies when flying in groups
(Bartonicka et al., 2007;
Habersetzer, 1981;
Ibánez et al., 2004;
Ratcliffe et al., 2004;
Ulanovsky et al., 2004). Some
bat species modified temporal features rather than spectral features of their
vocalizations to avoid call interference from conspecifics
(Obrist, 1995). Ulanovsky et
al. (Ulanovsky et al. 2004)
and Gillam et al. (Gillam et al.,
2007) have reported end frequency adjustments in vocalizations of
two bat species, T. brasiliensis and T. teniotis, when
flying with conspecifics. Although big brown bats, E. fuscus, in the
present study also showed call modification in end frequency, adjustments in
start frequency were larger than end frequency. This finding is consistent
with another study that reported a larger call frequency separation in start
frequency than in end frequency in E. fuscus and Lasiurus
cinerus but not in Lasiurus borealis and Euderma
maculatum (Obrist, 1995).
Previous and present research findings suggest that inter-specific variation
exists in call modification of echolocating bats.
Research on other animal species has also reported modification in spectral
and temporal features in the presence of conspecifics. Wave-type electric
fish, which also rely on active sensing for orientation, shift their EOD
frequencies to avoid signal jamming with conspecifics
(Bullock et al., 1972;
Watanabe and Takeda, 1963).
Pulse-type electric fish increase or decrease the discharge rate of their
electric organ to avoid signal overlap with another fish
(Heiligenberg, 1991). Similar
temporal and spectral modifications in signals used as a strategy to avoid
signal interference have also been reported in other animals, which do not
rely on active sensing (Egnor et al.,
2007; Farris et al.,
2005; Ficken et al.,
1974; Greenfield and Rand,
2000; Serrano and Terhune,
2002).
Animals adopt different strategies to achieve a separation in signals and
avoid jamming. Previous reports on electric fish have described how two fish
adjust their EODs to increase differences between their signals. For example,
wave-type electric fish modify their EOD frequencies, and the one with the
higher frequency increases its frequency and the other shifts its frequency in
the opposite direction (Bullock et al.,
1972; Watanabe and Takeda,
1963). No similar rule has been reported so far about how two or
more bats adjust their call design to reach a sufficient separation to
minimize interference from the signals of conspecifics. Past research has
reported an overall upward shift or downward shift in call frequencies of
several bat species in response to neighboring conspecifics
(Habersetzer, 1981;
Ibánez et al., 2004;
Kössl et al., 1999;
Miller and Degn, 1981;
Ratcliffe et al., 2004;
Surlykke and Moss, 2000). Gray
sac-winged bats, B. plicata, shifted their peak frequencies slightly
upward when flying in groups
(Ibánez et al., 2004)
and T. brasiliensis shifted their end frequencies upward when
playback bat calls were broadcast (Gillam
et al., 2007). Bates et al. reported that the big brown bat,
performing in a two-alternative forced-choice detection task, shifted calling
frequencies upward when lower jamming frequencies were broadcast and shifted
calls downward when higher jamming frequencies were broadcast
(Bates et al., 2008). By
contrast, the present study reports an overall downward shift in start
frequency and bandwidth of the big brown bats' vocalizations when they flew in
pairs, except one individual in pair 5 maintained the same baseline start
frequency and bandwidth. No clear modification pattern was found in three
other call parameters, end frequency, duration and sweep rate. Although no
clear overall vocal adjustment pattern was found when comparing each
individual's call design changes in baseline and two-bat conditions, paired
bats were still able to establish a large enough separation of its signals
from another bat to avoid interference by dynamically changing call structure.
The fact that paired big brown bats did not collide with each other or show
any sign of disorientation demonstrates that this species employs successful
strategies to avoid signal jamming from conspecifics.
The overall start frequency drop could be the consequence of detecting a
nearby object (another flying bat in this case) at a close distance, as bats
using FM signals tend to employ lower start frequency and shorter bandwidth
calls when approaching a target
(Schnitzler et al., 2003;
Simmons et al., 1979). A
possible explanation is that the bat may deliberately lower its call intensity
to avoid call interference when flying with conspecifics and therefore our
recording devices did not receive the high frequency parts of calls due to the
excess attenuation of high frequency sounds
(Lawrence and Simmons, 1982).
Call intensity decrease due to the presence of conspecifics could be another
vocal adjustment strategy the bat uses to avoid signal jamming. A calibrated
measurement of the bat's call intensity is required in the future to confirm
whether bats decrease their call intensity to avoid signal jamming.
Echolocating bats generate pulses with short intervals when attempting to
capture their prey or approaching obstacles and produce sonar pulses with low
repetition rate when searching for targets or orienting in space. It has been
inferred that bats use high repetition rate calls to acquire precise
information from targets and use low repetition rate calls when no target of
interest is shown in the vicinity
(Schnitzler and Kalko, 2001).
Big brown bats in this study increased the magnitude of adjustment in
start/end frequencies, bandwidth and sweep rate when pulse intervals
decreased, which suggests that the bat modifies features of its sonar calls
the most when it needs to stream detailed information from target echoes at
short distance.
Auditory stream segregation
Gestalt psychologists suggest that several principles, such as similarity,
proximity and closure, influence human visual perception. For instance, humans
tend to group visual objects together according to similar characteristics,
such as color or shape. Bregman suggests that the same principles can be
applied to auditory scene analysis
(Bregman, 1990). The principle
of similarity enables the auditory system to segregate and integrate complex
sound patterns. Echolocating bats may apply these principles to distinguish
its own emissions/echoes from those of others and to track echoes from moving
target in a complex acoustic environment
(Moss and Surlykke, 2001).
Increase in call design separation when flying with another bat provides a
demonstration that the bat may use the principle of similarity in call design
to integrate its own signals/echoes and segregate them from a conspecific's
signals/echoes. Sweep rate separation increased in the two-bat condition,
suggesting that the big brown bat changed the slope of its FM sweep to
maximize differences from calls of conspecifics. Consistent with this
suggestion are the results of psychophysical experiments on target ranging by
echolocating bats. In one such experiment, the big brown bat's range
discrimination performance deteriorated when a phantom target echo of the
bat's own call was replaced by signals of other bats with different call
designs (Master and Raver,
1996). In a follow-up study, they found that FM sweep curvature
changes in sonar signals compromised the bat's ranging ability
(Masters and Raver, 2000).
As noted above, interference signals can also affect sonar ranging by bats.
Masters and Raver (Masters and Raver,
1996) report that interference signals degraded target range
discrimination performance of the big brown bat, and the magnitude of
interference depended on the similarity between target echoes and interference
signals. Another study in P. pipistrellus reported that clicks from
arctiid moth species did not affect the bat's range discrimination ability
when broadcast randomly with respect to echo arrival times
(Surlykke and Miller, 1985).
However, the big brown bat's range discrimination performance deteriorated
only when the click of ruby tiger moth (Phragmatobia fuliginosa) was
broadcast within 1.5 ms before the echo return
(Miller, 1991), in a time
window when the click may have served as a forward masker of the echo playback
stimulus (Moss and Schnitzer,
1995). Results from these studies suggest that calls sharing
similar time–frequency structure disrupt the bat's ranging ability the
most. Therefore, minimizing the similarity in call design from conspecifics
seems to be a successful strategy for the bat to avoid sonar jamming from the
signals of nearby conspecifics.
Two jamming avoidance strategies: vocal adjustment and silence
Recent research has uncovered that paired big brown bats tend to cease
vocalizing at short inter-bat distances
(Chiu et al., 2008). The
present study on the same species with an identical experimental setup reveals
that big brown bats also tend to adjust their vocalizations in order to
increase call design separations. Both studies demonstrated that similarity in
call design and spacing between paired bats are two important factors to
affect the big brown bats' employment of silence and vocal adjustment
strategies. These two factors also influence the interference level of
vocalizations from conspecifics; therefore, silence and/or call design
adjustment appear to function to minimize signal interference from
conspecifics.
An echolocating bat shows signs of disorientation when its hearing is
disrupted (Griffin, 1958) but
it avoids collisions with another flying animal when it goes silent
(Chiu et al., 2008). A silent
bat can still listen to environmental sounds, including the calls and echoes
of conspecifics in the vicinity, and passive localization of these sound
sources presumably guides its orientation in the environment. The listener
needs to be close to the vocalizing animal in order to use the other's
vocalization for orientation (Kuc,
2002; Xitco and Roitblat,
1996). As the vocalizing bat can fly unexpectedly out of `ear
shot' of the passively listening bat, an echolocating bat risks disorientation
when it shuts off its echolocation. Many conditions would therefore favor a
bat's vocal adjustment strategy over a silence strategy. However, the bat may
encounter difficulties finding a transmission channel that is free from
overlap with other individuals when employing a vocal adjustment strategy for
jamming avoidance, particularly when it exits/enters its roost with many
dozens of conspecifics. Under such conditions, vocal adjustment may prove of
little use and other strategies would be needed. Silence is one potential
strategy for a bat to employ when many conspecifics are flying in close
proximity.
Detailing the factors that drive silent and vocal adjustment behaviors in
echolocating bats is a subject for future research. As a starting hypothesis,
we propose that silence is a strategy the big brown bat employs primarily to
avoid potentially disabling interference under conditions when its
localization accuracy requirements are not high, e.g. avoiding obstacles. In
this context, it is important to note that the big brown bat always produces
sonar calls as it prepares to intercept prey, when the timing of vocalizations
and returning echoes is used for precise target localization
(Chiu et al., 2008). Vocal
adjustment, as reported in the present study, may be used when it is difficult
for the bat to use the signals of a conspecific or localization accuracy
requirements are high, e.g. during prey capture.
Conclusions
The big brown bat (E. fuscus) encounters and interacts with
conspecifics frequently in nature (Simmons
et al., 2001). Flying with other bats does not disrupt the ability
of E. fuscus to use echolocation for spatial orientation, indicating
that this bat species must employ strategies to cope with possible signal
interference from conspecifics. Results reported in this study show increases
in sonar signal call design separation of E. fuscus flying in pairs,
and the magnitude of signal changes depends on the baseline similarity between
call features of individual bats flying alone. These data are consistent with
the hypothesis that the big brown bat utilizes call design modifications to
avoid call interference from neighboring conspecifics. We propose that
dissimilarity in time–frequency signal structure enables the big brown
bat to segregate auditory streams of its calls and echoes from those of
neighboring conspecifics.
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Footnotes |
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References |
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TOPSummaryINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONReferences |
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