Prey-capture success revealed by echolocation signals in pipistrelle bats (Pipistrellus pygmaeus)
Centre for Sound Communication, Institute of Biology, University of Southern Denmark, Odense Campusvej 55, DK-5230 Odense M, Denmark
* Author for correspondence (e-mail: ams{at}dou.dk)
Accepted 23 September 2002
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Summary |
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Key words: dat, Pipistrellus pygmaeus, echolocation, prey capture, post-buzz phase, biosonar signals
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Introduction |
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However, not all capture attempts are successful. Sometimes there is enough
light for visual inspection, as when bats hunt around street lights
(Acharya and Fenton, 1999) or
at high latitudes (Rydell,
1992
). These and other studies revealed that capture success is
nearly always considerably less than 100%, e.g. approx. 35% for Eptesicus
nilsonii attempting to catch ghost moths
(Rydell, 1998
;
Jensen et al., 2001
). In many
studies of batinsect interactions, the actual number of captures is
more interesting than the number of attempts. One obvious solution has been to
look for acoustic parameters in the bats' post-buzz signals that could reveal
if the capture attempt was successful.
Schnitzler et al. (1987)
suggested that the duration of the pause following the buzz was correlated
with success, with longer pauses after catches. Acharya and Fenton
(1992
) confirmed this for two
species of Lasiurus bats. Their data varied from year to year but,
for example, in 1989 they found average durations of post-buzz pauses of 165
and 265 ms after successes and 121 ms and 167 ms after unsuccessful attempts
for L. cinereus and L. borealis, respectively. Britton and
Jones (1999
) found a similar
correlation for Myotis daubentonii hunting in the laboratory but,
surprisingly, they found no effect on post-buzz pause in their field data.
They did find, however, a correlation with interpulse intervals (IPI) in the
post-buzz signals. IPIs were significantly longer after successful than after
unsuccessful capture attempts, both in the laboratory and in the field. In the
laboratory Britton and Jones
(1999
) also found that the
minimum frequency, Fmin, of the first signal emitted after
the post-buzz pause was higher after captures than after misses. However, this
difference was not seen in their field data.
The overlap between post-buzz pause distributions after successes and
misses and the general lack of consistency in the data make it difficult to
identify successful attacks unambiguously. Thus, the purpose of this study was
to extend the analysis to include not only temporal parameters, but also
frequency parameters in post-buzz signals, in an attempt to obtain a more
reliable assessment of bats' capture success. Prey size is another parameter
that is of importance for studies of feeding ecology and energetics. Acharya
and Fenton (1992) looked for
prey-size effects on buzz duration, and Britton and Jones
(1999
) inspected post-buzz
pauses and post-buzz IPI, but none of them found any significant effects of
size of the captured prey, although IPI showed a tendency to increase with
prey size. We analysed our data for any correlation of both frequency and
temporal parameters with prey size. We performed the experiments in the
laboratory, exploiting the inherent advantages of high quality sound
recordings combined with video monitoring, and we discuss our results in
relation to field recordings.
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Materials and methods |
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We used four different prey items: microworms (buffalo worms) Alphitobius diaperinus, 7-13 mm long and weighing 7-28 mg, mealworm larvae Tenebrio molitor, 14-27 mm long and weighing 44-15 mg, mealworm pupae, 13-18 mm long and weighing 64-145 mg, and moth bodies, wild-caught Orthosia species with wings and legs removed, 14-22 mm long and weighing 62-238 mg.
Flight cage and video recordings
The flight cage was a net tent (7 m long x 4.8 m wide x 2.4 m
high) placed in a large room. A curtain partly divided the cage
longitudinally, creating an oval flight track for the bats
(Fig. 1). Half way up one side
a custom-built mealworm catapult was placed on the floor. Two video cameras
were focused on the catch volume, which was approximately 45 cm x 30 cm
by 55 cm, centred 180 cm above the floor. One camera (Sony CXC-101P, connected
to a Panasonic AG-6200 video recorder) was placed at one end facing the bat,
when it approached the prey. We used this video recorder to store comments and
the bat detector output (divide-by-ten;
Andersen and Miller, 1977). The
other video camera (Panasonic NV-M10 camcorder) recorded the bat from the side
in the middle of the flight cage, where it captured the prey. This camera was
connected to a multiflash system to allow synchronized firing of the flashes
with the video recording. Thus, the `sync' pulse from the video camera
elicited one flash 1 ms long per video frame. The 30 µs synchronised pulses
were also recorded in the sound files together with the bats' sonar signals
(see below), to allow for synchronization between video and sound
recordings.
Sound recordings and analysis
A '' microphone (Brüel & Kjaer 4135, grid off) with
preamplifier (Brüel & Kjaer 2633) was placed at the end of the flight
cage facing the bat when it approached the capture area
(Fig. 1). The microphone was
180 cm above ground at approximately the same height as the bat's flight path
and a few cm above and in front of the Panasonic video camera. Recording of a
trial was started immediately after the bat passed the curtain on the short
side furthest away from the microphone and was stopped when the bat had passed
the curtain on the opposite short side next to the microphone. The microphone
signals were amplified (Brüel & Kjaer type 2607), high-pass filtered
(15 kHz) and mixed (custom-made signal mixer) with the synchronization pulses
from the flash system. The output from the signal mixer was digitised on-line
and stored in one file per trial on a personal computer using a Digital Signal
Processing (DSP) board (SPB2, Signal-Data, Copenhagen) and specially developed
software (S. Boel Pedersen, Centre for Sound Communication, Odense University
of Southern Denmark). The signals were A/D (Analogue-to-Digital) converted
(sample rate: 400 kHz) and stored in a ring-buffer (FirstInFirstOut, FIFO).
Up- and down-trigger levels were adjusted above the noise floor to detect the
beginning and end of all signals. The system digitised and stored the
microphone signal from 750 µs before the up-trigger to 750 µs after the
down-trigger to ensure that the low-amplitude beginning and end of the sonar
signals were included. Each signal was labelled with a time-stamp marking the
time of crossing the up-trigger level. Microphone output between bat
vocalisations was not stored. This not only saved around 90% data-storage
space, but also enabled us to scroll quickly from signal to signal within a
trial during analysis using a custom-made sound analysis program: BatViewer
(S. Boel Pedersen, Centre for Sound Communication, Odense University of
Southern Denmark).
Field recordings were done using the same microphone and amplifiers as above and stored on tape (Racal Store 4D). They were later digitized in one file per capture sequence using the same hard- and software as in the laboratory.
We determined signal duration, interpulse interval (IPI) and post-buzz pause (pbP) duration. The energy and power spectrum of each signal were calculated. The spectra were used to determine the maximum, minimum and peak frequency of the first harmonic. We also determined the BW-10dB (bandwidth measured 10 dB below the peak of the spectrum) and the number of harmonics of the signals.
The number of notches was counted in all signals in all analysed sequences. The spectra always contain notches caused by the frequency overlap between the first and second harmonic (approximately 110kHz for P. pygmaeus), but these were not included in the count. We only counted surplus notches in the first harmonic. Those mainly occurred after captures. We used BatSoundTM (Pettersson Electronic) to produce spectrograms (512 point FFT, Hann windows with 80% overlap) to display whole pursuit sequences for fast examination of notches in post-buzz signals. The notches were inspected more closely in power spectra of the signals (2048 point FFT, rectangular (uniform) window. A 2048 point window (5.12 ms) was longer than all signals recorded, and only notches that were at least 5 dB deep were included. If a signal had one or more surplus notches it was scored as `with notches', independent of the number of surplus notches. NOTCH in the following is the percentage of signals in a sequence (e.g. a post-buzz sequence) containing surplus notches.
Database
A `trial' was defined as one capture attempt of one prey item. Trials where
the bat made no obvious attack, trials where the batprey encounter took
place out of view of both cameras, and trials where the prey was clearly out
of the bat's reach (e.g. too low), were discarded from the analyses. A
`session' was defined as all trials conducted with one bat during a single
day. Each trial was classified as a wide (w), a touch (t) or a capture (c),
based on both immediate inspection and subsequent control using the video
recordings. Trials where the bat caught the prey and carried it away were
defined as `captures'. `Touches' were trials where the bat touched and
deflected the prey from its trajectory without getting hold of it. `Wides'
were trials where the bat made a clear attempt to capture the prey without
touching it. For some analyses touches and wides were pooled in the single
category `fail' (f).
The database included 50 successful capture trials with each bat and each
prey type plus the associated number of touches and wides, i.e. a total of
around 350 trials for each bat. These trials were used for calculating overall
capture success. 20 captures with each bat and each prey item and all
associated touches and wides were chosen for analysis of sonar sounds, giving
a total of 240 captures, 71 touches and 114 wides analysed for all three bats.
All together 4487 sonar signals from captures, and 1998 from fails, were
analysed, mainly from the post-buzz signals, but some search-phase signals
were also analysed. The search-phase was defined as the signals from the
beginning of a trial until the mealworm catapult was triggered, which was
itself defined as the start of the approach phase. An abrupt increase in pulse
repetition rate (PRR) indicated the transition from approach to buzz. The buzz
was subdivided in two phases, BuzzI and BuzzII (see
Griffin, 1958;
Surlykke et al., 1993
) and was
followed by the post-buzz pause, pbP. The signals after the pbP were defined
as post-buzz signals.
Using corresponding sound and video recordings we compared the duration of the acoustical post-buzz pause with the duration of the head-down stage seen in the video recordings.
Control without light
In most experiments two neon tubes were used to provide sufficient light
for video recordings. To rule out the possible use of visual cues, we
performed control trials without light using the two male bats. The outcome of
these trials was scored on the basis of sound cues. A trial was registered as
a fail if we heard the sound of a prey item falling to the ground, i.e. wides
and touches were pooled, because they sounded the same. Captures were
indicated by the lack of this sound and confirmed by the bat's chewing sounds.
None of the bats showed any hesitation or other signs of disturbance by the
lack of light. Further, their success rates were 88% and 90%, and thus not
reduced by the lack of light.
Statistical analyses
A number of parameters were analysed. Most distributions of temporal and
spectral parameters for all three bats and three capture outcomes (capture,
touch, wide) were normally distributed (D'Agostino-Pearson 2
test), but a few were not. However, removal of six outlying datapoints from a
total of 425 trials restored normality and two-way analysis of variance
(ANOVA) analysis was performed on all data to test for differences between
capture, touch and wide values in the post-buzz sequences. This was followed
by a Tukey's test when significant differences were found. A significance
level of 1% was employed (with Bonferroni correction for multiple
comparisons). For those parameters where significant differences were found
between post-buzz values of capture, touch and wide trials, the search
sequences of the particular trials were also tested for differences between
these parameters. Groups were compared pairwise using a
KruskalWallis/MannWhitney non-parametric test with Bonferroni
corrections.
The average pbP, IPI and NOTCH in post-buzz signals differed significantly between successful and non-successful capture attempts, but there were large overlaps between the distributions. To increase discriminability between groups we performed a canonical discriminant analysis (CANDISC, SAS statistical software package) on the data. This analysis constructs a new parameter, the first canonical discriminant function, CD1. CD1 is a linear combination of the original parameters (NOTCH, IPI and pbP) and provides maximal correlation with the capture categories.
Receiver operating characteristics (ROC) curves were constructed using the
three original parameters (NOTCH, IPI, pbP), as well as CD1. In each case the
data for the post-buzz signals of a trial were used to classify the trial as
either capture or fail (touches and wides were pooled). Depending on the
actual outcome of the trial the classification as a capture could be scored as
either a hit (correct identification of a capture) or a false alarm (incorrect
classification as capture, actual outcome a fail, i.e. touch or wide).
Similarly, classification as a fail could be a correct rejection (correct) or
a miss (incorrect; actual outcome was a capture). The terms hit, miss, false
alarm and correct rejection are used to retain consistent terminology with
classical signal detection theory (Green
and Swets, 1966; Ohl et al.,
2001
). Ten different criteria were used to produce ten
corresponding sets of hit and false alarm rates, which were then plotted in
four ROC curves, one for each of the three raw parameters and one for the CD1
parameter (Scheich et al.,
1998
; Tougaard,
1999
). Data from all three bats were pooled, for two reasons.
Firstly, the differences observed in the pooled data set were also always
consistent for all three bats tested individually. Secondly, pooled data are
most often what is experienced in the field, where one cannot be certain that
all recordings are from the same individual.
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Results |
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The bats captured the prey either with the tail (interfemoral) membrane,
the wing membrane or a combination of both. 81% of all captures were made
using only the tail membrane to intercept the prey items. The bat retrieved
the prey by bending the head into the tail pouch
(Fig. 2, frame 11). A few
recordings strongly indicated that the bats could seize prey directly by the
mouth, although the resolution and the frame rate of the video system were not
sufficient to establish this unequivocally. In these cases the video showed
the bat in a continuous straight flight before, during and after the capture
without doing a somersault. There was only 40 ms between video-frames. Kalko
(1995) gives 50 ms as the
minimum duration of the capture manoeuvre. Hence, it seems unlikely that the
normal wing- or tail-membrane capture could occur between two frames.
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The sonar signals emitted in the laboratory during pursuit sequences consisted of search, approach, buzz and post-buzz signals, as in the field. In each trial we recorded approx. 1.5 s of sonar signals centred on the catch (Fig. 3). The search-phase signals were 3-5 ms long, of broad bandwidth, with a first harmonic sweeping down from 110 kHz to end in a short tail at 55 kHz. A second harmonic was clearly seen. The IPI was approximately 70 ms, corresponding to a PRR of 14-15 Hz. During the approach, signal duration decreased and PRR increased to approximately 40 Hz, whereas the bandwidth remained unchanged. Signals in BuzzI and BuzzII of the terminal phase differed spectrally, with BuzzI signals being similar to the approach-phase signals and BuzzII signals characterized by a downward shift in frequency. The PRR increased gradually during BuzzI to reach a plateau of approximately 200 Hz throughout BuzzII. After a post-buzz pause the bat again produced search-like signals (Fig. 3).
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Capture success and spectral parameters
The recordings included between 3 and 22 post-buzz signals per trial. We
determined the relative number of signals with surplus notches fulfilling the
5 dB criterion in case of captures, touches and wides in search and post-buzz
signals, respectively. The search signal had very few notches
(Fig. 3). As expected, NOTCH in
search signals did not correlate with the outcome of the following capture
attempt (NOTCHc=6%, NOTCHt=4%, NOTCHw=7%)
(Table 1). Post-buzz signals in
general contained more notches than search signals, no matter whether they
came from capture, touch, or wide trials (P<0.001,
KruskalWallis/MannWhitney-test of search signals versus
post-buzz signals in case of all three outcomes: capture, touch and wide).
However, NOTCH in post-buzz signals was much higher following a capture than a
touch or wide (NOTCHc=67%, NOTCHt=39%,
NOTCHw=34%, two-way ANOVA with bat number and outcome as
independents; P<0.001) (Fig.
3). The difference was consistent for all three bats and there
were no significant differences in NOTCH between bats. The difference between
touches and wides was not significant (Fig.
4, Table 1).
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Capture success and temporal parameters
Capture success was correlated with significant changes in IPI and pbPs in
all three bats (Fig. 4,
Table 1). The mean IPI was
lengthened in post-buzz signals following captures. The IPI increase was
significant, both compared to IPI of search signals (P<0.001,
KruskalWallis/MannWhitney), as well as to IPI of post-buzz
signals following fails (IPIc=84.4 ms, IPIt=67.1 ms,
IPIw=66.1 ms; two-way ANOVA with bat number and outcome as
independents; P<0.001). The difference was again consistent for
all bats and there was no significant difference in IPI between bats. The
difference between touches and wides was not significant. In search sequences
(i.e. before a capture) there was, as expected, no significant difference
between the three outcomes (IPIc=67.9 ms, IPIt=70.5 ms,
IPIw=65.8 ms) (Table
1). The IPI-distributions did not show significant differences
between individual bats.
The pbP was longer following touches than wides, and even longer following captures than touches (pbPc=272.7 ms, pbPt=181.2 ms, pbPw=117.9 ms). The differences were significant for the pooled data for all bats as well as for individual data from the three bats (two-way ANOVA; P<0.001) (Fig. 4, Table 1). Thus, for this parameter there was a significant difference between the two unsuccessful outcomes: touch and wide. pbP was the parameter that varied most between the bats. Regardless of the outcome of the capture attempt, Bat V had significantly longer pauses (P<0.001) than the other bats (Table 1). However, the relative increase in pbP after touch or capture compared to wide was about the same for all three bats, approximately 150% and 230%, respectively (Table 1).
We used the best video recordings to determine the length of time that the
bat had its head in the tail pouch (`head-down stage'; see
Kalko, 1995) by counting the
number of video frames. Since each frame lasts 40 ms, three frames would
correspond to a head-down stage lasting from a minimum of 80 ms to a maximum
of 160 ms. The average duration of the head-down stage was determined from the
medium time, i.e. three frames was counted as 120 ms. Average head-down stage
in capture trials (N=62) lasted 214±81 ms (mean ±
S.D.), and average pbP in the same trials was 255±94 ms. In touches,
average head-down (N=27) was 166±71 ms, and pbP was
162±56 ms. Head-down in wides (N=31) was 107±61 ms on
average, and pbP was 113±54 ms.
To be on the safe side, when comparing video and sound recordings of individual trials, we used the maximum time the head-down stage could have lasted (i.e. in the example above: 160 ms for a head-down stage lasting three video frames). In a high proportion (>40%) of the successful capture trials the acoustic post-buzz pauses clearly lasted longer than the maximum time the bat had its head in the tail pouch. In touch and wide trials the proportion of trials where pbP outlasted the head-down stage was smaller, 15% and 20%, respectively (Fig. 5).
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Acoustic parameters unaffected by capture success
A number of acoustic characteristics of the post-buzz signals did not
correlate significantly with capture success. These included temporal
parameters as signal duration, and spectral parameters as maximum
(Fmax), minimum (Fmin) and peak
(Fpeak) frequencies of the first harmonic,
BW-10dB, and the harmonic structure of the signals.
Prey size
The prey type, but apparently not the prey size per se, had
significant influence on IPI, pbP and NOTCH in post-buzz signals following
captures (Fig. 6). After fails
there were no differences. The differences were consistent for all three bats.
The four types of prey affected NOTCH, IPI and pbP differently. For example,
capture of microworms resulted in long IPI and high NOTCH, but short pbP,
whereas capture of mealworms gave high NOTCH and long pbP, but only
intermediate IPI (Fig. 6).
Neither comparison to mass (Fig.
6) nor to length revealed any obvious correlation with prey size.
There was a considerable overlap between sizes of the four prey types.
Therefore, in addition to comparing to the average prey size (mass or length)
we also used data from 20 capture trials with each bat and each prey type to
look for a correlation with size of each individual prey item. Again, no size
dependence was found; all r2 for linear correlations were
below 0.3. None of the other acoustic parameters tested (duration, minimum,
maximum and peak frequency, bandwidth and harmonic structure) were correlated
with overall prey size. Hence, in spite of significant effects of prey type on
some acoustic parameters (IPI, pbP, NOTCH), no systematic relation to size
(neither mass nor length) was found within the range of prey sizes tested.
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Using post-buzz signals to evaluate capture success
To test how reliably the acoustic parameters reflect the capture success,
we categorized trials solely on basis of the acoustic recordings. The ease
with which the two distributions (capture and no-capture) can be separated is
reflected in the area below the ROC curve. The larger the area, the fewer
errors will be made in discrimination if a suitable criterion is chosen.
Capture success could be inferred with reasonable accuracy based on either a
NOTCH, IPI or pbP criterion, as seen in the ROC curves in
Fig. 7.
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The actual percentage of correctly classified trials depends on the criterion. Fig. 8 shows that all three original parameters can be used in classification, with 72-78% correct classifications at the optimal criteria. The range of NOTCH criteria providing success rates above 70% was broad: from 29% to 71% notches, with a maximum of 78% correct (Fig. 8). The ranges of optimal criteria were almost the same for the three individual bats, 22-64%, 37-72% and 28-79%, respectively. The overall best criterion both for the individual bats as well as the pooled set was 50% notches.
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If IPI was used to evaluate capture success, the criterion range 73-82 ms produced success rates above 70%, with a maximum of 72% correct. Thus, IPI was not as reliable a cue as NOTCH and had a more narrow range of useful criteria (Fig. 8). The three individual bats had best criterion ranges of 62-81 ms, 67-81 ms and 74-87 ms, respectively. The overall best criterion was approximately 75-78 ms IPI.
The pbP was better than IPI, but not as reliable as NOTCH. pbP criteria between 99 ms and 245 ms gave above 70% success in determining trial outcome, when used on the pooled data for all three bats (Fig. 8), with a maximum of 75% correct. Ranges for best criteria for the individual bats were 86-219 ms, 93-192 ms and 132-338, respectively. A best overall criterion is not evident, as this parameter displays the largest variation between bats. However, 160 ms seems a fair compromise.
Although all three parameters correlate well with capture success, they do
not correlate with each other, except for a weak, yet significant correlation
between NOTCH and IPI for captures (partial correlation: r=0.22,
Bonferroni-corrected P=0.002). We thus used a principal component
analysis to combine the infromation from the three useful parameters, NOTCH,
IPI and pbP, into a single new parameter, the first canonical discriminant
function, CD 1 (Fig. 9). All
three parameters contributed significantly, with weights of 0.629, 0.358 and
0.566 for NOTCH, IPI and pbP, respectively. This function could accommodate
98.5% of the total dispersion and is given as:
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Field data
We analysed five pursuit sequences from Danish P. pygmaeus
recorded in an open area where more bats were hunting in a group (courtesy of
Marianne E. Jensen) (Table 2).
Obviously, the field recordings are of more variable quality than laboratory
recordings, not the least because of the unpredictable position of the bats
relative to the microphones, and this is reflected in larger variations in the
acoustic parameters. The IPI values were generally longer in the field
recordings compared to our laboratory recordings, while pbP values were much
shorter in the field. Britton and Jones
(1999) also reported shorter
pbP values in field than laboratory for Myotis daubentonii. In four
of five sequences there was a clear increase in signals with notches (NOTCH)
after the buzz compared to pre-buzz signals.
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If we apply the laboratory criteria to the field recordings, we infer that none of the pursuits were successful, since all pbP values were short, as noted above, and below the criteria. However, they fell into two groups: two very short pbP values and three longer ones. Long pbP values were coupled to an increase in NOTCH in the post-buzz signals. Furthermore, the two with the longest pbP values had a large increase in IPI following the buzz, thus suggesting that at least those two were successful captures, indicating a success rate in the field data of 2/5 = 40%.
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Discussion |
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Capture behaviour
We used a laboratory set-up that allowed the bats to behave as naturally as
possible. From beginning to end of a session the bats were not handled by
humans. Sessions run without light indicated that the bats were neither
disturbed nor assisted by the light when hunting. The set-up provided some
clutter, but probably not much more than a pipistrelle bat might encounter in
the field when it hunts close to ground and vegetation
(Kalko, 1995;
Schnitzler and Kalko, 1998
).
Prey capture by the bats was probably facilitated by the fact that prey items
always occurred at the same general area in the room and were catapulted in a
predictable vertical arc rather than the fluttering flight path of most insect
prey. Added to this was an acoustic cue from the release of the catapult. In
spite of these unnatural circumstances, however, the capture technique closely
resembled those described previously from field studies
(Kalko, 1995
).
It has been speculated that the post-buzz pause could be used as a rough
measure of the time taken to retrieve the prey from the tail pouch
(Schnitzler et al., 1987).
Kalko and Schnitzler (1989a
)
suggested that the duration of the post-buzz pause corresponded to the
`head-down' stage in Myotis daubentonii, and Kalko
(1995
) proposed the same
hypothesis for three species of pipistrelle bats from her field recordings.
However, our results showed many examples where pbP was clearly longer than
the head-down stage, especially after successful captures, where more than 40%
of the trials had pbP values outlasting the head-down stage. The pause thus
represents a true pause in signal emission, and not just a `muffling' of the
sounds by the tail membrane.
Temporal cues of post-buzz signals
We found that the pulse interval was significantly longer after captures
than after fails, thus corroborating the general result of Britton and Jones
(1999). However, Britton and
Jones found that Myotis daubentonii doubled the interpulse intervals
(IPI) after successful captures. They recorded chewing sounds and suggested
that chewing replaced every second echolocation signal. Our results do not
support a similar explanation for P. pygmaeus, since the increase in
average IPI was only approximately 25%, and was due to a combination of
occasional skipping of a signal and a true elongation of interval between
pulses (see Fig. 3). In fact,
Britton and Jones' own field data also failed to show as large an increase in
IPI as found in the laboratory. Since signal emission seems closely related to
wing beat rate in all bats studied (Kalko,
1994
; Wong and Waters,
2001
), the implication of the reduced pulse repetition rate is
that they also beat their wings at a slower rate. Our video frame-rate was not
sufficiently fast to establish whether this was the case, but it was our
distinct impression that the flight speed was slower after captures. This
should be assessed in future studies. The flexibility of bats in adapting to
different habitat conditions, including the laboratory
(Surlykke and Moss, 2000
;
Obrist, 1995
), makes it likely
that bats have a fairly wide range of wing beat rates and concomitant pulse
emission rates.
The post-buzz pause following captures lasted significantly longer than
following touches, hence confirming the findings (laboratory, but not field)
of Britton and Jones (1999) for
Myotis daubentoni and of Acharya and Fenton
(1992
) for Lasiurus
borealis and L. cinereus in the field. However, the variation in
pbP values between the bats was quite substantial. Discrimination between
captures and fails (including both wides and touches) is further complicated
by the significant increase after touches, which probably also partly explains
why Britton and Jones (1999
)
reported high variability of pbP after unsuccessful capture attempts in the
laboratory and found no significant difference in the field. Individual
variation does not explain the large overlap between capture and fail
distributions as suggested by Acharya and Fenton
(1992
). Even if we restrict our
analysis to data from only one bat feeding on one prey type, there is still no
unambiguous threshold value. Thus, although the results show that pbP is
increased in case of a successful capture, neither our data, nor any of the
previous studies, indicate that it is possible to define an absolute threshold
value for any bat species that reliably can discriminate captures from fails
(as for example the 100 ms suggested for Pipistrellus kuhli in the
field; Schnitzler et al.,
1987
).
It is interesting that pbP increases by approximately 50% after touches. This may indicate that the mere touching of a prey initiates a fixed vocal (and behavioural) motor pattern or parts of it which the bat goes through even when it does not seize the prey.
Spectral cues of post-buzz signals
We found no differences in Fmin,
Fmax or Fpeak between captures,
touches and wides, and hence could not confirm the increase in
Fmin found in laboratory recordings of Myotis
daubentonii (Britton and Jones,
1999). Furthermore, none of these frequency parameters were
correlated with the length or mass of the prey, suggesting that even the
biggest prey (within the range tested) does not influence the frequency range
of the sonar signal in pipistrelle bats.
Although the overall bandwidth, Fmin and
Fmax were not affected by capture success, the occurrence
of excess notches after captures shows that a successful catch does affect the
spectrum of the signals. Surplus notches are seen in signals recorded from
bats hunting close over water (e.g. Myotis daubentonii). These
notches are due to the interference between the directly recorded signal and
the signal reflected from the water surface, with notch frequency determined
by the delay of the reflected signal
(Kalko and Schnitzler, 1989b).
In our set-up the general increase in number of notches in post-buzz signals
compared to search signals can probably also be explained by interference with
reflections from objects in the flight room. In the post-buzz phase the bats
were beyond the capture area and thus closer to the microphone and video
set-up and concrete pillars at the end of the flight track. However, a more
interesting change in notch occurrence is seen in post-buzz signals following
captures compared to fails (touches and wides). It seems likely that a
relatively large prey in the mouth will act as a frequency filter, changing
the outgoing signal, either directly or by affecting the sound-producing
mechanisms. The NOTCH effect serves as a reliable clue such that the outcome
of a trial attempt can be determined with approximately 75% success using a
NOTCH criterion alone.
Conclusions
The laboratory recordings revealed that three acoustic parameters in
post-buzz signals depended on capture success. Their correlation with success
was so strong that evaluations of the bats' success based only on those
acoustic parameters gave correct classification of trials in capture/fail in
up to 85% of the cases, when all three parameters were combined in a first
canonical discriminant factor. However, these are laboratory results and
comparative acoustic studies of bats in the laboratory and field do show
substantial differences (Britton and Jones,
1999; Surlykke and Moss,
2000
). Thus, one should be cautious when applying the laboratory
results to field data. Not only are acoustics different and more complicated
in the field, but the bats themselves produce different signals in the
confined laboratory space compared to the field
(Surlykke et al., 1993
). Bats
can learn to predict the trajectory of catapulted food
(Miller and Olesen, 1979
).
Besides, the prey we offered in the laboratory was of bigger size than most of
the natural prey of pipistrelle bats
(Swift and Racey, 1985
;
Barlow, 1997
), and none of the
laboratory prey items could perform evasive manoeuvres.
The high level of control in the laboratory revealed results that would be very difficult to determine in field studies, for example the increased post-buzz pause after touches or the fact that the post-buzz pause often outlasts the head-down stage substantially. The carefully controlled laboratory situation enabled the formation of the hypothesis, but laboratory recordings alone, and of only three bats, are not sufficient to determine classification criteria for field recordings. Before applying this acoustical method to field studies, it requires a substantial basis of good recordings, preferably from different types of hunting areas, to adjust the criteria to the particular recording situation.
Nevertheless, whilst noting those reservations, our laboratory results are quite clear-cut for the three bats and the types and sizes of prey. Furthermore, the acoustic capture behaviour of the bats in the laboratory resembles that in the field. Thus, we believe it is likely that evaluation of capture success based on similar acoustic methods will be possible in future field studies.
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