Echoes of bat-pollinated bell-shaped flowers: conspicuous for nectar-feeding bats?
Zoological Institute, University of Erlangen, Staudtstr. 5, D-91058
Erlangen, Germany
Present address: School of Biological Sciences, University of Bristol,
Woodland Road, Bristol, BS8 1UG, UK
* Author for correspondence at present address: Max-Planck-Institut für Verhaltensphysiologie, D-82319 Seewiesen, Germany (e-mail: dghelv{at}biologie.uni-erlangen.de)
Accepted 20 December 2002
![]() |
Summary |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
Echoes of bell-shaped bat-pollinated flowers have characteristic features with respect to the echoes they reflect to a calling bat and differ from the echoes of leaves or other objects in their surroundings: the echoes are comparatively long and of complex spectral composition. Owing to the specific shape of the flowers, characteristic `spectral directional patterns' result when the spectra of the echoes are plotted against the angle of sound incidence.
We suggest that bats are able to recognize such flowers and probably other objects as well not only by a characteristic spectral composition of the echo but also by comparing sequential echoes, at the same time taking into account their exact calling position relative to the object.
Key words: bat-pollination, echolocation, plant echo, acoustic object recognition, glossophagine bat, chiropterophilous flower
![]() |
Introduction |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
To revisit known nectar sources, the bats use, above all, their excellent
spatial memory. This corresponds to the long flowering period of most
bat-pollinated plants, to the advantage of both: the bats can rely on the
nectar source, and the plants can rely on being found and pollinated. To find
new flowers, glossophagine bats use their well-developed senses of olfaction
(e.g. Vogel, 1968,
1969a
,b
;
Knudsen and Tollsten, 1995
;
v. Helversen et al., 2000
) and
vision (e.g. Suthers et al.,
1969
; J. Lopez, Y. Winter and O. v. Helversen, manuscript in
preparation) but, as in all microchiropteran bats, their orientation is mainly
guided by their highly developed echolocation system
(Griffin and Novick, 1955
;
Howell, 1974
). This enables
them to manoeuvre even in dense and clutter-rich vegetation. Typically, the
echolocation calls of glossophagine bats are very short (0.5-3 ms) and mostly
faint, which is why they have been described as `whispering bats'
(Griffin and Novick, 1955
). The
calls are multiharmonic, broadband, downward-modulated frequency sweeps. In
many of the smaller species like Glossophaga, the frequency
modulation starts at very high frequencies of about 140 kHz and ends at about
60 kHz (D.v.H., M.W.H. and O.v.H., unpublished observations).
Since the pioneering work of Donald Griffin, a large number of studies have
investigated how insectivorous, aerial-hawking bats can detect and locate
flying prey (for reviews, see Griffin,
1958; Neuweiler,
1989
,
1990
;
Schnitzler and Kalko, 1998
).
Bats can also discriminate among different prey objects presented in
uncluttered situations (Simmons et al.,
1974
; Simmons and Chen,
1989
; v. d. Emde and
Schnitzler, 1990
) using temporal as well as spectral cues of the
echoes (Simmons et al., 1990
;
Mogdans and Schnitzler, 1990
;
Schmidt, 1992
). However, it is
not yet understood how bats recognize motionless objects in clutter-rich
surroundings and to what extent they are able to find such objects. Many
observations in the field suggest that frugivorous and nectarivorous bats cope
excellently with this problem, and a small number of experimental studies have
demonstrated it (Bradbury,
1970
; Kalko and Condon,
1998
; v. Helversen and v.
Helversen, 1999
; Schmidt et
al., 2000
). However, recognition of motionless prey is severely
impeded by clutter-rich surroundings; trawling Myotis bats could
detect prey only on smooth surfaces that reflect away most of the sound energy
(Siemers et al., 2001
), and it
has even been claimed that other Myotis species are `acoustically
blind' to motionless prey in echo-cluttering habitats
(Arlettaz et al., 2001
).
Most bat-pollinated flowers can be assigned to one of two morphologically
different types: `pincushion-type' flowers, with long and numerous stamina,
and `bell-shaped' flowers. Bell-shaped flowers may differ widely in size,
ranging from very large, cup-like flowers to small flowers no bigger than a
`head mask' for the bat (Vogel,
1968,
1969a
,b
;
Dobat, 1985
). Large, cup-like
flowers, such as the flowers of the Balsa tree (Ochroma lagopus),
allow the bats to land and, typically, are visited by large unspecialized bat
species, while small, bell-shaped flowers can be exploited only by specialized
bats. Although the small glossophagine bats could easily land on the flowers
(and do so occasionally), they typically lick nectar while hovering in front
of them (v. Helversen and v. Helversen,
1975b
). Exploitation during hovering implies that the rapidly
approaching bat has to meet the entrance of a flower with its snout or tongue
or both, with the precision of a few millimetres, to gain access to the
nectar. This seems to be no easy task: indeed, in some of their approaches the
bats miss the target, as revealed by infrared video recordings in the field
(D.v.H. and O.v.H., unpublished observations).
While insects, as prey of insectivorous bats, should have evolved to produce inconspicuous echoes that are difficult to localize or that even mislead their predators, bat-pollinated plants, in competition for these effective pollinators, should have evolved acoustically conspicuous flowers that facilitate detection, thereby reducing the bat's foraging costs in terms of time, risk and energy. Therefore, to be easily detected, bat-pollinated flowers may be expected to have evolved shapes, textures and structures generating echoes that are distinctly different from the general echoes of the surrounding vegetation.
In this study, we investigated the echoes of some bell-shaped flowers of bat-pollinated plant species. We consider two questions: (1) do bell-shaped forms give rise to unique echoes, which allow them to be discriminated from those of other objects, and (2) are the echoes of bell-shaped flowers particularly suited to lead the bat to the nectar chamber?
![]() |
Materials and methods |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
Flowers of M. neurantha, V. gladioliflora and C. cujete were collected at the OTS (Organization for Tropical Studies) field station, La Selva, Costa Rica; the flowers of A. latifolia were kindly provided by Dr Günter Gerlach, Botanical Garden, Munich.
Artificial hollow forms
For comparison, we also investigated the echoes of three artificial concave
objects, all with the same circular opening diameter: a hollow hemisphere
(r=18 mm), a paraboloid (y=0.111x2, cut
at a height of y=36 mm) and an ellipsoid (a=44 mm,
b=20 mm), cut perpendicularly to the long axis so that a circular
opening with r=18 mm and a depth of 25 mm resulted. The three forms
were made of plastic (thickness, 0.5 mm) with an acoustic impedance
104 times as great as that of air thus absorption can be
neglected (Fletcher, 1992).
Echo measurements
The objects to be irradiated were impaled by a long, very thin insect pin
or a similarly thin palm prickle at the top of a thin holder mounted in the
centre of a small turntable. Revolving the turntable allowed irradiation of
the objects from all directions in one plane. The front view of the object was
adjusted to 0°. The loudspeaker and microphone were fixed at a distance of
20 cm from the target at the same height as the target object
(Fig. 1).
|
As temporal structure and spectral composition of an echo depend not only on the angle of sound incidence but also on the position of the microphone relative to the sound source, we tried to mimic the dimensions of a bat's mouth and ears, i.e. they had to be as small and close to each other as possible. We used a custom-built condenser speaker with a membrane of 15 mm diameter and 1/4'' microphones without protecting grid (either Brüel & Kjaer 4135 with sound level meter 2209 or GRAS 40BF with preamplifier 26AB and power module 12AA). The distance between the centres of the microphone and the loudspeaker was 18 mm. The microphone was placed coaxial to the loudspeaker, approximately 45° laterally above the horizontal with respect to the midpoint of the loudspeaker membrane. The frequency responses of the loudspeaker and microphone allowed measurements between 20 kHz and 140 kHz, which, on the whole, covered the frequency range of the echolocation calls used by most flower-visiting bats.
Impulse response
Echoes were measured as impulse response functions of the scattering
object, i.e. as the echo that the object would produce when irradiated with a
single click of very short duration (a Dirac impulse). The disadvantage of
such short impulses is that they contain relatively little energy. Because the
size of the loudspeaker had to be small in order to mimic the proportions of a
bat's head, we did not compensate this lack of energy by employing a larger
speaker but used the so-called `maximum length sequences' (MLS) method to
measure the impulse response function. The basis of the MLS method is the
playing of a predetermined sequence of impulses of variable length and
intervals instead of repeating only one single impulse. This results in a much
better signal-to-noise ratio. MLSs are designed to have no internal
periodicity and therefore show a perfectly narrow autocorrelation function.
The impulse response is not directly accessible from the recordings but can be
obtained from the recorded signal by combining it with the original MLS in a
`fast Hadamard transformation' (FHT). The impulse response of the object is
then selected in the time domain, and its frequency response (spectrum)
calculated from the impulse function using fast Fourier transformation (FFT;
window size 256 or 1024 samples for artificial forms and natural flowers,
respectively; rectangular window).
We used an MLS of 16 383 samples length with a duration of 32 766 ms. Replay and recording were sample-synchronous at a sampling rate of 500 kHz. The MLS signal was continuously replayed via the loudspeaker by a custom-built sound generator (USSY, Technische Hochschule Darmstadt). The microphone signal was digitized with 12-bit resolution and recorded by a custom-made hard disc recorder (Institut für Technische Elektronik, Universität Erlangen).
As the frequency response of the loudspeaker was not sufficiently flat, we first had to determine the impulse response of the loudspeaker alone. This is usually done with the microphone facing the loudspeaker. As we wished to keep the position of the loudspeaker and microphone constant throughout all measurements, we replaced the object with an even plate of metal directed perpendicularly to the angle of sound incidence. The plate was large enough to reflect the sound wave back to the microphone (plate diameter approximately 40 cm). Thus, we obtained the same impulse response as we would have if we had placed the microphone on the acoustic axis facing the loudspeaker at twice the distance from the flower (i.e. 40 cm). The frequency response (spectrum) of the loudspeaker was then calculated from its impulse response as above. The actual spectra of the flower echoes, without influence of the loudspeaker frequency characteristic, were calculated as the (complex) difference spectrum between the spectra of the loudspeaker and the echo. These spectra represent the `spectral target strength' for reasons given below. Finally, the actual impulse response of the object could be derived from this calibrated spectrum by employing inverse fast Fourier transformation (IFFT). All calculations were performed using the program Monkey Forest (Audio & Acoustics Consulting, Aachen, Germany).
Target strength
By definition, the target strength of an object is the reflected echo
amplitude measured at a reference distance relative to the incident amplitude
at the place of the object (e.g.
Møhl, 1988). When the
echo-generating object is regarded as a source of new spherically spreading
sound waves, a reference distance has to be defined. The reference distance
chosen was 10 cm. To ease the calculation of the target strength, the distance
between the object and the loudspeaker/microphone was set at double the
reference distance (20 cm): owing to spherical spreading loss, the echo
amplitudes recorded at 20 cm are attenuated by 6 dB compared with the
reference distance of 10 cm. As we measured the incident sound amplitude at an
effective distance of 40 cm, which was twice the distance between the
loudspeaker and the object, the recorded incident amplitude was also 6 dB
lower than at the position of the object. Because the target strength is
defined as the relationship between both, the two attenuations of 6 dB
cancelled each other, and the relationship of the measured values directly
indicated the target strength. This is also true for the calibrated spectrum
mentioned above, which can therefore be regarded as `spectral target
strength'.
Relative amplitude and duration of the impulse response
Signal amplitudes were calculated as the sum of the magnitudes of the
calibrated power spectrum between 20 kHz and 140 kHz. Defining a threshold
just above the noise level, we estimated the duration of the impulse response
for every direction of incidence.
![]() |
Results |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
|
|
|
|
|
Spectral directional pattern
Slightly revolving the turntable often resulted in a totally different
impulse response. A resolution of 2° turned out to be sufficient to detect
the minima and maxima. In principle, it would be necessary to measure the
echoes from all directions in three dimensions but for the sake of clarity and
to get a general idea we confined the measurements to the horizontal plane
coplanar to the long axis of the flower tube.
Measurements between -90° and +90° allowed us to depict an `acoustic fingerprint' of the flower. From the impulse response we derived the `directional pattern of duration', and from the amplitude spectra the `spectral directional pattern', by scaling the amplitudes as grey tone gradation over incidence angles (x-axis) and frequency (y-axis; Figs 3E, 4E, 5E, 6E).
Three of the flowers analysed in this way (Amphitecna, Markea and Crescentia) are similar in that they are exposed rather freely when blooming, which is brought about either by flagelliflory (Markea) or cauliflory (Amphitecna, Crescentia). The results presented in Figs 3,4,5,6 are measurements of the isolated flower without stem or peduncle, although in the two cauliflorous flowers (with a distance of 10-12 cm between the front of the flower and the stem) a partial overlap between the echoes of the flower and the stem might be expected in a natural situation.
In Vriesea gladioliflora, unlike other Vriesea species, which expose their flowers at the two opposite sides of a flat swordlike inflorescence, the flowers are not exposed freely but are embedded within the stalk, covered by their bracts. Even when the flowers are fully open, only the distal part of the flower's corolla is visible. As the bats will always experience the flower embedded in the stalk, we measured the echo of the flower together with a part of the stalk (approximately 15 cm long; Fig. 6A).
As may be expected, the overall echo amplitude in all four bell-shaped flowers showed a relative maximum at the position around 0°, when the opening of the bell was facing the speaker and microphone (Figs 3D, 4D, 5D, 6D). While Markea showed a prominent and rather narrow maximum, the range of angles with enhanced echo amplitudes was larger in Amphitecna and Crescentia.
Accordingly, the duration of the impulse response was also maximal at that frontal range (Figs 3B, 4B, 5B, 6B). In Figs 3C, 4C, 5C and 6C, the maxima (black) and minima (white) of the impulse function and their pattern can be seen as they change with the angle of the sound incidence. In all four examples, the first peaks deriving from the distal left and right edges of the flower can be traced with changing angle of incidence. Both the duration and the overall intensity of the echoes, of course, depend strongly on the shape of the bell.
The spectral directional pattern, the presentation of the spectral composition of the echoes as a function of sound incidence angle, is given in Figs 3E, 4E, 5E and 6E. In all four examples, in a range of approximately -60° to +60° relative to the opening of the bell, the echoes showed rapidly changing spectral compositions. In a single spectrum, sudden falls in intensity of more than 12 dB compared with the values for neighbouring frequencies were observed frequently at different frequencies and different angles of sound incidence. Thus, as a function of angle of sound incidence, the echoes differed in a characteristic manner with respect to their spectral composition, producing an acoustic fingerprint for every flower species.
In Vriesea, the echo was strongest when the stalk was ensonified from approximately -80° laterally on the side of the stalk from which the flower originated. The echo of this part was nearly constant over the whole frequency range because of a rather flat, leaf-like part of the bract that reflected the sound back to the microphone. The echoes recorded in a frontal area from approximately -60° to +60° were less intense, and their spectral composition varied for different angles of incidence. At 0°, there was also a strong echo but with a complicated spectral pattern resulting from interferences enhancing some frequencies and cancelling others.
Impulse response and echoes
Bats do not have the impulse function at their disposal in that they use
echolocation calls with a distinct duration and a distinct time course of the
frequency spectrum. The frequency range of glossophagine bat calls is mostly
within 140 kHz to 60 kHz. The echo of a call can be calculated by
finite-impulse-response-filtering (FIR) of the impulse function with the
amplitude function of the call. In Fig.
7, the sonagrams of two such impulse functions (at 0° and
-30°) treated with the amplitude function of a typical call of
Glossophaga give an impression of the echo as the bat would perceive
it.
|
Echoes of artificial hollow forms
The echoes of natural flowers, as shown above, are determined not only by
their shape but also by elastic properties, surface texture and other features
of the corolla, and it seems difficult to separate the different components
(see Hickling, 1967;
Bozma and Kuc, 1991
for
technical objects). Therefore, for a better understanding of the principal
pattern of the echoes of bell-shaped flowers, and to test our method, we
compared the directional patterns shown above with those of some simple
concave forms, measured in the same way as the flowers. We chose hollow forms
of a hemisphere, a paraboloid and an ellipsoid (see Materials and methods),
all with the same opening diameter of 36 mm. Results are shown in
Fig. 8.
|
As expected, in all three forms, the loudest echoes were received when the
concave side of the form was irradiated from (or from near) its main axis, but
this was much more marked in the paraboloid and the ellipsoid than in the
hemisphere. Furthermore, with each shape, typical bands of interference
occurred, resulting from multiple reverberations at the inner side of the
form. In the hollow hemisphere, due to the constant radius of curvature, the
bands of interference remained constant for all angles of incidence
(Fig. 8A), as expected from
theoretical analysis (e.g. Freedman,
1962). In the other two forms, which had continuously changing
radii of curvature, the bands of interference decreased in frequency with
increasing deviations from the 0° axis. To test whether properties other
than shape constituted the pattern of the echo fingerprint, we measured the
spectral directional patterns of the same parabolic form twice, once as a
shell of 0.5 mm thickness and then pressed in a solid cylinder of the same
diameter. As the two measurements turned out to be very similar, we are
confident that the directional spectral pattern of all three forms is due to
their shape.
![]() |
Discussion |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
Can flowers be recognized by their echoes?
The recognition of a small motionless object by an echolocating bat should
be easier the more the echo differs from the echoes of the surrounding
vegetation and other surrounding structures. Echoes of a single flat leaf
consist primarily of simple reflections of the calls without sudden drops in
intensity at certain frequencies and are not much longer than the echolocation
call. Echoes of trees and bushes have been shown to be highly unpredictable,
as the echoes of many different leaves superpose, but a statistical analysis
was able to unearth features that characterize, for example, different tree
species (Müller and Kuc,
2000). This is due to the different size, shape and configuration
of leaves and to the specific architecture of the plants.
In contrast to the simple echoes of flat leaves, the flowers described here generate complex but predictable echoes owing to their specific and constant shapes and textures. In particular, echoes of bell-shaped flowers are characterised by their duration, spectral composition and directional pattern (see below).
Duration
Depending on the length of the bell, the duration of the echo may be
increased relative to the echoes of leaves and other plane objects. Sound
invading a tube will undergo numerous reflections, and these higher order
reverberations will possibly further increase the duration of the echo in
addition to the time the sound has to travel into and out of the bell. Indeed,
our measurements corroborate this idea.
Spectral composition
Several experimental studies have demonstrated that the spectral
composition of an echo is important for detection and discrimination
(Bradbury, 1970; Simmons et
al., 1974
,
1990
;
Mogdans and Schnitzler, 1990
;
Schmidt, 1992
). In bell-shaped
flowers, multiple reflections of an echo interfere with each other, enhancing
some frequencies and erasing others. This gives rise to a `coloured' spectral
composition of the echo, which may be conspicuous in comparison with echoes of
leaves. Our measurements show that the echoes of a bell-shaped flower have
this `coloured' appearance and, basically, resemble those of simple hollow
forms, as demonstrated by the directional patterns
(Fig. 8).
Directional pattern
We have shown that the spectral composition of the echoes depends strongly
on the angle of incidence. Single echoes of different objects can be nearly
identical and would not contain enough information for discrimination.
Therefore, for recognition of specific forms, bats will have to evaluate the
echoes of sequential calls, while taking into account their own position
relative to the object. Besides learning the characteristic features of single
echoes, bats may also be able to detect and learn the rules of echo changes
determined by the shape of the flower. The actinomorphic symmetry of most
bell-shaped flowers probably reduces the multiplicity of echoes. That bats are
indeed able to compare successive echoes was shown in training experiments by
Moss and Surlykke (2001).
Can flower echoes help the bat to adjust its approach flight to the
entrance of the nectar chamber?
A flower must not only be detected and recognized as a nectar source: in
the next step, the bat has to find the nectar, and the approach flight must be
exactly directed towards the opening of the nectar chamber. As shown in the
Results, the target strength and the duration of the echo increase drastically
when the opening of a bell-shaped corolla faces the loudspeaker. A bat flying
around a bell-shaped flower could therefore detect the opening of the flower
by evaluating the target strength alone (as shown in Figs
3,4,5,6),
especially for the flowers of Markea and Vriesea. The echoes
generated inside the tube could well function as a `guiding beam', leading the
bat exactly to the flower opening. Thus, bell-shaped flowers, in particular
those with a long narrow tube, may `acoustically mark' the entrance where the
bat will find the nectar.
Adaptations for acoustic detection and recognition
The detectability of flowers by their echoes is probably reduced when other
echo-generating structures are in close vicinity and clutter echoes are
superimposed on the echoes of the flower. Most chiropterophilous flowers are
exposed freely and therefore not only allow hovering in front of a flower
(Vogel, 1968,
1969a
,b
;
Dobat, 1985
) but also
facilitate their detection and recognition by avoiding overlap with clutter
echoes. In many bat-pollinated plants, the typical exposition and the
structure of the whole inflorescence may also give rise to specific echoes
that can be detected from greater distances and thus guide the bat to the
smaller structures of the flowers, which can only be identified from a shorter
distance. For instance, the sword-like inflorescence of V.
gladioliflora is inclined by approximately 40° with respect to the
vertical and thus may be conspicuous even from a distance. The flowers open on
the lower side and can be found by the narrow echo beam they reflect when the
bat hovers along the inclined side of the stalk.
Cauliflorous flowers normally protrude at least several centimetres from
the stem and probably allow a temporal separation of the echoes of the flower
and those of the background. Where this is not so, as with some columnar
cacti, special adaptations can be found; these cacti often present their
flowers in the midst of a `cephalium', a region densely covered with hairs.
Besides the possible function of these cephalia to protect against heat and
desiccation, the dense hairs may also serve to attenuate the echoes generated
by the stem, thereby enhancing the contrast between flower and background
echoes. Possibly, this is their main function, as in many species of columnar
cacti the cephalium is restricted to the region where flowers are presented
(v. Helversen and Winter,
2003).
At present, we do not understand how bats, guided by their echolocation system, manage to manoeuvre through a dense jungle of leaves, to recognize objects like flowers and fruits and to adjust their fast approach flight exactly to within a few millimetres of the opening of a flower. Our measurements suggest that bats probably extract more information from the echo sequences than has been hitherto supposed and that they do this by comparing the echoes of successive calls during flight.
![]() |
Acknowledgments |
---|
![]() |
References |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
Arlettaz, R., Jones, G. and Racey, P. A. (2001). Effect of acoustic clutter on prey detection by bats. Nature 414,742 -745.[CrossRef][Medline]
Bozma, Ö. and Kuc, R. (1991). Characterizing pulses reflected from rough surfaces using ultrasound. J. Acoust. Soc. Am. 89,2519 -2531.
Bradbury, J. (1970). Target discrimination by the echolocating bat Vampyrum spectrum. J. Exp. Zool. 173, 23-46.[Medline]
Dobat, K. (1985). Blüten und Fledermäuse (Chiropterophilie). Frankfurt/M: Verlag Waldemar Kramer.
v. d. Emde, G. and Schnitzler, H.-U. (1990). Classification of insects by echolocating greater horseshoe bats. J. Comp. Physiol. A 167,423 -430.
Fletcher, N. H. (1992). Acoustic Systems in Biology. Oxford: Oxford University Press.
Freedman, A. (1962). The high frequency echo structure of some simple body shapes. Acoustica 12, 61-70.
Griffin, D. R. (1958). Listening in the Dark. New Haven: Yale University Press.
Griffin, D. R. and Novick, A. (1955). Acoustic orientation of Neotropical bats. J. Exp. Zool. 130,251 -299.
v. Helversen, D. and v. Helversen, O. (1975a). Glossophaga soricina (Phyllostomatidae) Nahrungsaufnahme. Publ. Wiss. Film E 1837,3 -10.
v. Helversen, D. and v. Helversen, O. (1975b). Glossophaga soricina (Phyllostomatidae) Flug auf der Stelle. Publ. Wiss. Film E 1838,10 -17.
v. Helversen, D. and v. Helversen, O. (1999). Acoustic guide in bat-pollinated flower. Nature 398,759 -760.[CrossRef]
v. Helversen, O., Winkler, L. and Bestmann, H. J. (2000). Sulphur-containing "perfumes" attract flower visiting bats. J. Comp. Physiol. A 186,143 -153.[CrossRef][Medline]
v. Helversen, O. and Winter, Y. (2003). Glossophagine bats and their flowers. Costs and benefits for plants and pollinators. In Bat Ecology (ed. T. Kunz and B. Fenton), pp. 346-397. Chicago: University of Chigaco Press.
Hickling, R. (1967). Echoes from spherical shells in air. J. Acoust. Soc. Am. 42,388 -390.
Howell, D. J. (1974). Acoustical behavior and feeding in glossophagine bats. J. Mamm. 55,293 -308.[Medline]
Kalko, E. K. V. and Condon, M. A. (1998). Echolocation, olfaction and fruit display: how bats find fruit of flagellichorous cucurbits. Funct. Ecol. 12,364 -372.[CrossRef]
Knudsen, J. T. and Tollsten, L. (1995). Floral scent in bat-pollinated plants: a case of convergent evolution. Bot. J. Linn. Soc. 119,45 -57.
Mogdans, J. and Schnitzler, H.-U. (1990). Range resolution and the possible use of spectral information in the echolocating bat, Eptesicus fuscus, J. Acoust. Soc. Am. 88,754 -757.[Medline]
Møhl, B. (1988). Target detection by echolocating bats. In Animal Sonar: Processes and Performance. NATO ASI series A vol. 156 (ed. P. E. Nachtigall and P. W. B. Moore), pp.435 -450. New York: Plenum Press.
Moss, C. F. and Surlykke, A. (2001). Auditory scene analysis by echolocation in bats. J. Acoust. Soc. Am. 110,2207 -2226.[CrossRef][Medline]
Müller, R. and Kuc, R. (2000). Foliage echoes: a probe into the ecological acoustics of bat echolocation. J. Acoust. Soc. Am. 108,836 -845.[CrossRef][Medline]
Neuweiler, G. (1989). Foraging, echolocation and audition in echolocating bats. Trends Ecol. Evol. 4, 160-166.
Neuweiler, G. (1990). Auditory adaptations for
prey capture. Physiol. Rev.
70,615
-641.
Schmidt, S. (1992). Perception of structured phantom targets in the echolocating bat, Megaderma lyra. J. Acoust. Soc. Am. 91,2203 -2223.[Medline]
Schmidt, S., Hanke, S. and Pillat, J. (2000). The role of echolocation in the hunting of terrestrial prey new evidence for an underestimated strategy in the gleaning bat, Megaderma lyra. J. Comp. Physiol. A 186,975 -988.[CrossRef][Medline]
Schnitzler, H.-U. and Kalko, E. K. V. (1998). How echolocating bats search and find food. In Bat biology and Conservation (ed. T. A. Kunz and P. A. Racey), pp.183 -196. Washington: Smithsonian Institution Press.
Siemers, B. M., Stilz, P. and Schnitzler, H.-U.
(2001). The acoustic advantage of hunting at low heights above
water: behavioural experiments on the European `trawling' bats Myotis
capaccinii, M. dasycneme and M. daubentonii. J. Exp.
Biol. 204,3843
-3854.
Simmons, J. A. and Chen, L. (1989). The acoustic basis for target discrimination by FM echolocating bats. J. Acoust. Soc. Am. 86,1333 -1350.[Medline]
Simmons, J. A., Lavender, W. A., Lavender, B. A., Doroshow, C. A., Kiefer, S. W., Livingston, R. and Scallet, A. C. (1974). Target structure and echo spectral discrimination by echolocating bats. Science 186,1130 -1132.[Medline]
Simmons, J. A., Moss, C. F. and Ferragamo, M. (1990). Convergence of temporal and spectral information into acoustic images of complex sonar targets perceived by the echolocating bat, Eptesicus fuscus. J. Comp. Physiol. A 166,449 -470.[Medline]
Suthers, R., Chase, J. and Braford, B. (1969). Visual form discrimination by echolocating bats. Biol. Bull. 137,535 -546.[Medline]
Vogel, S. (1958). Fledermausblumen in Südamerika. Österr. Bot. Z. 104,491 -530.
Vogel, S. (1968). Chiropterophilie in der neotropischen Flora. Neue Mitteilungen I. Flora 157,562 -602.
Vogel, S. (1969a). Chiropterophilie in der neotropischen Flora. Neue Mitteilungen II. Flora 158,185 -222.
Vogel, S. (1969b). Chiropterophilie in der neotropischen Flora. Neue Mitteilungen III. Flora 158,289 -323.
Winter, Y. and v. Helversen, O. (2001). Bats as pollinators: foraging energetics and floral adaptations. In Cognitive Ecology of Pollination (ed. L. Chittka and J. D. Thomson), pp. 148-170. Cambridge: Cambridge University Press.