Foraging ecology and audition in echolocating bats

Foraging ecology and audition in echolocating bats

TREE vol. 4, no. 6, June ..~ ForagingEcologyandAuditionin Echoititing Bats Gerhard Neuweiler The types of echolocation signal and the auditory capac...

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TREE vol. 4, no. 6, June


ForagingEcologyandAuditionin Echoititing Bats Gerhard Neuweiler The types of echolocation signal and the auditory capacities of echolocating Guts are adapted to specific acoustical constraints of the foraging areas. Bats hunting insects above the canopy use low frequencies for echolocation; this is an adaptation to prey detection over long distances. Bats foraging close to and within foliage avoid masking of insect echoes by specializing on ‘fluttering target’ detection. ‘Gleaning’ bats are adapted to the auditory detection of very faint noisesgenerated by ground-dwelling prey, and are capable of anafysing fine changes in the echo spectrum, which may indicate a stationary prey changing its posture on a su6strate. This review of recent research demonstrates that, in bats, foraging ecology and audition are intricately interrelated and interdependent.

Bats are distributed worldwide and live in tropical rain forests as well as in tundras close to the Arctic Circle, and in deserts as well as in cities. There are more than 900 chiropteran species; about 750 of them belong to the echolocating Microchiroptera, and the others to the frugivorous and non-echolocating Megachiroptera (flying foxes) of the tropical and subtropical Old World. Because of their specific capacities for echolocation and manoeuverable flight, Microchiroptera have gained access to the rich resources of nocturnal, aerial insects for which hardly any other predators are competing. It is believed that other echolocating bats have radiated from these insectivorous ancestors. In the tropical New World many phyllostomid bats are flower visitors that live on pollen and nectar. Other tropical species live on fruits, and others have become carnivorous. The three species of vampires in South America are the only vertebrates that subsist exclusively on blood meals. However, most microchiropteran species (some 600-700 species) are insectivorous. GerhardNeuweiieris at the Zoologisches lnstitut der Universitat Miinchen, Luisenstrasse 14, 8 Miinchen 2, FRG. 160

The ecological radiation of echolocating bats has been mainly considered in terms of thermoregulation and hibernation, water and energy balances, and variations in resource capacities’. This traditional approach underrates the significant constraints to the accessibility of a habitat exerted by the sensory outfit and differentiations of a species. Hearing is the main channel through which an echolocating bat perceives its external world during its nocturnal foraging excursions and in the darkness of its roosting sites. Bats vocalize through their mouths or nostrils, producing brief sounds of high frequencies, and they listen to the echoes bouncing back from objects of their surroundings. The auditory system of bats has to detect the echoes among external noises and to locate the echo-reflecting target. Bats determine the distance to a target by measuring the travel time between onset of vocalization and arrival of the echoes at the ears2, and derive the direction from which the echo returns by interaural cues and directional effects of the pinnae. However, bats not only echo‘locate’ a target but also identify or differentiate its nature, at least to the extent that they are able to determine whether the target is a potential prey to be pursued or non-prey to be avoided or ignored. The auditory detectability of small objects, such as flying midges or spiders moving on a substrate, may be strongly degraded by the echoes reflected from the background vegetation and substrate. These background echoes will overlap and interfere with the echo of interest. Such unwanted echoes are called echo clutter. Thus, the acoustical and sound-reflecting properties of the foraging sites, as well as the animal’s auditory capacities, will be important features that determine the foraging area exploitable by a bat species. This interdependence between prey catching sites and audition may have been a powerful driving force for evolutionary specialization. 01989


Foraging habitats and echolocation signals In recent years an increasing quantitative field number of studies on the foraging behaviour of echolocating bats has shown that different bat species do not forage opportunistically everywhere. Most species have distinct preferred foraging areas, which they abandon only when seasonal insect scarcities or major changes in prey populations force them to move to a different foraging habitat?. Bats emit different types of echolocation signal4 (Fig. I). Frequency modulated (FM) signals, that cover a frequency band of about one octave or more, are the most widespread signal type for pursuing and catching detected prey. FM sounds are very brief, so that the returning echo never overlaps with the emitted sound. For seeking prey, narrow band signals or constant frequency (CF) signals over IO ms long are often emitted, either alone or combined with FM components. As shown in Fig. I, the types of echolocation signal are correlated with the main foraging habitat of the bat species. Habitat use also correlates with flight pattern and wing morphology5s6. The following six foraging areas have emerged from the field studies of the last ten years (Fig. 2).

( I 1 The atmosphere above vegetation Many species of molossids, emballonurids and vespertilionids fly in long sweeps and at high speeds (9-15 m s-1) in search and pursuit of flying insects high above the ground, where there are no obstacles. Because of this foraging behaviour these species are also called ‘the swallows of the night’. In pursuit of prey, they may occasionally come down and fly low over open grassland or ponds. Most species foraging high above vegetation emit pure tones or shallowly frequency modulated echolocation sounds, 8-30 ms long, as they search for insects. The frequencies of these search signals are low and are often audible to the human ear. After detecting a potential prey, the signals shorten to brief ( l-3 ms) FM sounds sweeping through at least a full octave (e.g. from 80 to 40 kHz; Fig. I). (2) Open spaces between vegetation Many vespertilionids and other


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species hunt flying insects on the wing in open spaces between trees, around tree tops, along forest edges, in parks and around buildings or street lights. During their search flights they stay 1-2 m from the canopy and avoid close contact with bushes and trees. Some of these species also emit pure tones or narrow band signals, or extend the end of a frequency modulated sound to a pure tone ‘tail’ of medium to low ultrasonic frequency while searching for insects. Other species only emit brief FM signals when seeking prey. ( 3 ) Over water surfaces Air spaces over lakes, ponds, streams and rivers are usually rich in insects, and some bat species commonly forage over water. These bats fly low over the water surface and capture flying insects out of the air with the mouth or the tail membrane7. Some of these species have enlarged feet with curved and pointed claws for gaffing arthropods from the water surface. The ‘fishing bats’ Noctiiio leporinus and Myotis vivesi even catch small fishes when they touch or protrude above the water surfaces. Bats foraging over water use various types of echolocation signal, and there is no consistent correlation between type of sound and this foraging pattern. (4) Aroundand within densefoliage Rhinolophids, many small hipposiderids and a few other species pursue flying insects around the canopies of trees and bushes or within dense foliage. Such bats also frequently forage by a sit-and-wait strategy. The rufous horseshoe bat (Rhinolophus rouxi), for instance, spends most of the night within the forest in an individual foraging area of about 300 m2 (Ref. 9). The horseshoe bat perches at the end of barren twigs protruding below the canopy and persistently scans its close surroundings by echolocation signals, while continuously turning its body in an almost full circle. When an insect flies close by (within about 5 m) the bat takes off, catches the insect and returns to its vantage point. On average, a horseshoe bat performs 16 catching flights per hour. Horseshoe bats and hipposiderids invariably emit signals domi-

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Fig. I. Types of echolocation signal emitted in different foraging areas. Schematized sonagrams show the echolocation signals that are emitted when the bats search for prey (s), and when they are catching prey (c). The encircled numbers refer to the foraging areas depicted in Fig. 2. FM, frequency modulated signal; CF, constant frequency or pure tone signal. Note that brief FM sounds are the most generally emitted echolocation signals.

nated by a pure tone component. In hipposiderid bats the pure tone lasts about IO ms and terminates with an FM sweep (CF/FM signal). In horseshoe bats the pure tone component lasts 1O-l 20 ms; during flight this signal is preceded by an upward FM sweep and terminated by a downward modulated component (FMICFIFM signal; Fig. I). (5) Foliage and (6) Ground gleaning Some species specialize on prey from leaves and from the ground. The best known foliage gleaner is the long-eared bat (Plecotus auritus)lO, which slowly flies along foliage and even hovers up and down along windows to pick up insects that are attracted to the glass by indoor lights. Carnivorous



bats like Megaderma or Nycteris frequently use a sit-and-wait strategy for foragingrr. They perch on bushes, trees or rocks and listen to the ground in search of any prey of suitable size, e.g. frogs, lizards, mice, birds, bats and larger arthropods. They may hover over a prey for some time before they swoop down, seize the prey in their mouth and return with it to the vantage site. They also search over ponds and rivers, and even fish bones have been found in the stomach of false vampires (Megaderma 1y1-a)~~. Others, such as the vespertilionid Antrozous pallidus, also fly low over open ground and pick up large insects like grasshoppers and cricketsr3. The gleaning bats that have been

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Fig. 2. Foraging areas and their correlation to the frequency range of best audition of echolocating bats. Encircled numbers: (I ) foraging above canopy; (2) open spaces between canopy; (3) over water surfaces; (4) close to and within foliage; (5) foliage gleaning; (6) ground gleaning. The thick lines below the abscissa demarcate the approximate frequency range of best audition in various bat species foraging in the area given by the encircled number. Modified from Ref. 38.



dependence of signal type and foraging habitat suggests that auditory constraints play a decisive role in resource selection and therefore in the ecology of the different bat species.

studied are the so-called ‘whispering bats’, which emit very brief (0.21.5 ms) signals of low intensities (sound pressure levels of < 80 dB) and broad band-width (Fig. I). The six different foraging areas may be classed as areas free of echo clutter (above vegetation and in open spaces), or areas with echo clutter (close to or within vegetation, or near to ground or water surfaces). Echolocation in clutter conditions is a more sophisticated task, and this review focuses on bats foraging in such habitats.

Auditory adaptation to echolocationin open spaces Bats foraging in open spaces (areas I and 2 in Fig. I ) will have no problems detecting echoes reflected from prey. Echoes from insects flying at a distance of more than half a meter away from foliage will usually not overlap with echo clutter from the background and insect echoes will be heard as single events. For bats hunting insects well above the vegetation, where no background is present, any echo will indicate a potential prey; differentiation between clutter and prey echoes is unnecess-

Echolocation systems adapted to different foraging sites The above description of the foraging habitats and behaviour of bats shows a significant, though not very strict, correlation between preferred foraging area and type of signa14. This interecholocation

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Fig. 3. Pure tone signals lCFl are well adapted for wing-beat detection in echo-cluttering habitats. Sonagrams (upper graphs) and spectrograms (lower graphs) of a brief frequency modulated (FM, upper two rows1 and long-lasting pure tone ICF, lower two rows) echolocation signal and their echoes reflected from foliage and wing-beating insects. Note that the structure of the CF signal is not changed in the echoes from foliage, even when it is moving in wind. The wing beats of an insect, however, are distinctly encoded in the CF echo by marked ‘glints’. In contrast, the time course and spectrum of FM echoes from foliage are changed and wing beats do not show up clearly in an echo returning from a flying insect. FM echoes from foliage and insects may be difficult to differentiate whereas CF signals are well suited to detecting flying insects in front of foliage, even when it is moving in the wind. Sonagrams ofechoes from flying insects adapted from R. Kober, PhD thesis, University of Ttibingen, 1988.



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As Fig. I shows, the best auditory frequency in an echolocating bat is a good indicator of its preferred foraging area: long distance echolocation in the ‘open atmospheric sea’ is achieved by low sound frequencies, whereas echolocation around and within foliage is performed at high frequencies. The inverse correlation between best auditory frequency and the range to be scanned by echolocation (expressed as height of the preferred foraging area above ground in Fig. 2) may be explained by sound energy absorption in air, which is stronger the higher the sound frequency and the higher the air temperature and humidity. For instance, a 30 kHz signal will be attenuated by 80 dB (by a factor of lO-4) when returning from an ideal reflector 7 m away from the bat, and a 120 kHz signal will be attenuated by the same amount at a target distance of only 4 m (air temperature 25°C relative humidity 50%)‘4. Sound absorption severely curtails echolocation over long distances. However, those species that frequently forage far above vegetation at high speeds will have to echolocate over long distances, since insect density is usually not high in the upper levels of the air. For compensating sound absorption these bats use low ultrasonic frequencies and trade long distance detection for spatial resolution, which is higher for smaller wavelengths, i.e. higher frequencies. Sound absorption does not explain why bats seeking insects in open spaces emit long, narrow band signals. A long-lasting narrow band sound has a high spectral energy, which would increase the range of echolocation under the assumption that the neuronal system integrates its auditory input over the full duration of the echo signal. Alternatively, these bats may use the narrow band signal as a sensitive detector for wingbeating targets (see below). Auditory adaptations to foraging sites producing echo clutter The auditory situation is entirely different for bats hunting prey close to foliage or on the ground. Even when the echolocation signal is as brief as I ms, echoes will overlap from targets less than I6 cm apart.

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Moreover, leaves and the ground are extended objects compared to the size of insects and therefore may reflect louder echoes than the potential prey. Yet, bats that pick up insects from leaves or from grassland and catch flying insects within the canopy have overcome this clutter problem. Bats have solved the problem of echo-clutter rejection in at least three ways: (a) specialization on fluttering target detection, (b) detection of changing echo colours, and (c) listening to prey-generated noises. Fluttering target detection:the caseof fiorseshoebuts Horseshoe bats and hipposiderid bats invariably emit stereotyped echolocation signals dominated by pure tone components. If one looks at echoes returning from leaves, the advantage of a pure tone signal for echolocation in dense foliage becomes apparent. As Fig. 3 shows, FM signals are altered in the spectral domain due to interference, and in the time domain due to time smearing of the multiple echoes reflected from the foliage. In contrast, the pure tone signal maintains its structure unchanged even when the leaves are moved by windspeeds of up to 3 m s-1. However, when a fluttering target such as a flying insect is introduced into the foliage, the pure tone echo will carry distinct acoustical glints (brisk changes in intensity and spectral content); these occur whenever the wing moves through the position normal to the sound beam’5v16. In other words, beating wings create ‘echo signatures’ which pop out of pure tone echoes returning from foliage (Fig. 31, whereas in FM signals the glints are masked by the interference patterns caused by the foliage structure. Therefore, a pure tone would be a better signal for detecting flying insects around foliage than an FM echolocation sound. Indeed, in Sri Lankan forests we observed rufous horseshoe bats foraging only on flying insects, either on the wing close to trees and bushes or in a sit-and-wait strategy below or within the canopyg. Behavioural experiments revealed that horseshoe bats are alerted by wing-beating targets, and do not detect non-flying


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Fig. 4. Wing-beat detection and the auditory fovea in horseshoe bats and hipposiderid bats. (a) A schematic illustration of echolocation in dense vegetation by CF signals. Left horseshoe bat: the structure of the echo returning from foliage is not significantly different from that of the emitted signal. Right horseshoe bat: when the emitted signal is reflected from a fluttering insect, wing beats are encoded in the echo as distinct modulations (74 f 1.5 kHz) of the emitted signal frequency (74 kHz). (b) Frequency map on the basilar membrane of the cochlea in a horseshoe bat (horizontal projectionl. The frequency range of the CF echo signal (72-77 kHz) is represented in the inner ear on a widely expanded scale (fovea), whereas lower and higher frequencies are represented on a compressed logarithmic scale. (cl Audiogram of a horseshoe bat which shows the auditory fovea as a narrow filter sharply tuned to the individual echo frequency (arrow). (d) Within the ascending auditory pathway in the brain, the fovea1 frequency range (72-77 kHz, shaded areas) is again enormously overrepresented within the tonotopic order of neuronal frequency representation. In each brain center (NC. cochlear nucleus; LL, nuclei of the lateral lemniscus; IC, inferior colliculus; AC, auditory cortex) the hatched area indicates that portion of the neuronal tissue that represents the narrow frequency range of the auditory fovea. In the inferior colliculus, for instance, the representation of the fovea1 frequency range, which is only 5 kHz wide, covers more than the ventral half of the IC. whereas the non-fovea1 frequency range from 9 to 70 kHz is compressed into the dorsalmost layers. (e) Neurons tuned to the fovea1 frequency range often respond poorly to the CF signal alone, and respond vigorously to each glint in the CF echo reflected from a wing-beating insect. Adapted from Refs 9, 16 and 1s. _ -

horseshoe insects17. Echolocating bats are highly sensitive to wing beats and even a single wing movement will elicit a catching flight. The auditory system of horseshoe bats and hipposiderid bats is uniquely adapted to reject clutter from the background and to enhance detection of glints (Fig. 4). In the cochleae of these bats there is an auditory filter that is narrowly tuned to the frequency of the pure tone component of the echo16. The central frequency of the cochlear filter not only matches the speciesspecific range of frequencies but is precisely locked to the individual frequency emitted by the bat (Fig. 4~). For instance, rufous horseshoe bats from South India emit pure tone frequencies around 84 kHz, whereas those from Sri Lanka emit 73-79 kHz (Ref. 18). Males of the Sri Lankan horseshoe bat emit frequencies from 73.5 to 77 kHz and females from 76.5 to 79 kHz (Ref. 9). Each individual bat may maintain its own private frequency with a

precision of f50 Hz or a variability of only 0.06%. These bats have individually tuned echolocation systemsIs. The narrowly tuned private auditory filter rejects all signals except the ‘personal’ echo signal marked by its matching frequency. As demonstrated in recordings from many auditory neurons, the filter also renders the auditory brain extremely sensitive to small and brisk frequency modulations of the pure tone echo as they occur in echoes reflected from wing-beating insects16f19,20 (Fig. 4e). Each wing beat is distinctly coded in these neurons and even modulations as small as 10 Hz or 0.01% are detected*‘. This specific auditory filter is based on a so-called auditory fovea: the narrow frequency range of a few kHz around the frequency of the echo pure tone is represented on the cochlear basilar membrane in a greatly expanded fashion (Fig. 4b)l8. In Rhinolophus 163

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rouxi the frequency range from 72 to 77 kHz covers about one quarter of the full length of the basilar membrane, or the same length that is otherwise used for the representation of a full octave (e.g. from 35 to 70 kHz). In the same way as the fovea1 region of the retina is overrepresented in the visual brain, the overrepresentation of the fovea1 frequency range is maintained throughout all stages of the auditory brain. For instance, in the midbrain auditory nucleus, the inferior colliculus, about two-thirds of the neuronal volume is dedicated to the narrow frequency range from 72 to 77 kHz, and representation of the frequencies from 72 to about 9 kHz is compressed into thin dorsal layers (Fig. 4c; unpublished data). This indicates that even minor frequency variations around the individual echo frequency activate different and large pools of neurons, which allow an extremely finegraded frequency analysis. Therefore the bats might use pure tone echolocation not only for detecting, but also for identifying wingbeating insects by analysing the spectrum of the glints22. For echolocation in flying horseshoe bats a problem arises. Since sender (the nostril) and receiver (the ears) are moving, the emitted signal and the reflected echo will experience a Doppler shift of its frequency, the amount of which is correlated with the bat’s flight speed. In rufous horseshoe bats the frequency of the echo will be about 2.2 kHz higher than the emitted signal at a flight speed of 5 m s-1, meaning that the echo, then, no longer matches the fovea1 frequency of the ears. The bats avoid this mismatch by lowering the emitted frequency by an amount equivalent to the Doppler shift of the echo frequency23. By such Doppler-shift compensation the bat uncouples its movementsensitive echolocation system from its own flight speed. In the New World just one species, the moustached bat (fteronotus parnelli), uses this flutter-sensitive echolocation system24. Comparative studies have shown that the mechanisms for the tuned auditory fovea are different from those of horseshoe bats. Therefore, the phylogeneti-


tally unrelated moustached bats and horseshoe bats demonstrate a remarkable convergent evolution of a highly specialized sensory system25. The sophisticated echolocation system with pure tone signals and tuned auditory fovea allows the detection of small nocturnal insects flying in and around dense foliage, but it does not detect nonfluttering targets. In our study area in Madurai, South India, 68 species of nocturnal moths caught in light traps could hear ultrasonic frequencies. Many moth species stay motionless and frozen when they hear echolocation signals and thus effectively reduce predation by bats26. Detection of prey by changing echo colours? Auditory specialization on wingbeat detection has given access to insect prey flying within dense vegetation, a resource difficult to exploit for other bat species. However, there are bats in the same habitat that do not rely on wingbeat detection. For instance, the long-eared bat (Plecotus auritus)27 or the notch-eared bat (Myotis emarginatusP pick up insects from leaves, twigs, bark, walls and even well-lit windows. It is difficult to conceive how a bat might use echolocation to differentiate such small stationary targets from the substrate. The surface structure of the insect combined with that of the substrate will reflect an echo with a highly complex spectrum when insonified with a broad band signal (for instance, see the echo of an FM signal from foliage in Fig. 3). In analogy to reflected sunlight, such spectral qatterns may be called echo colours: the broad band signal emitted by a bat is like a ‘white’ signal containing all frequencies, whereas an echo that features missing and highlighted frequencies due to interference at the reflecting surface is ‘coloured’. A recent behavioural experiment has shown that bats differentiate surface textures. The Indian false (Megacferma lyra), which vampire emits a ‘white’ signal containing frequencies from 120 to 20 kHz, discriminated sandpaper textures with an average grain size of 0.4 mm from those of 2.5 mm. Experiments on target depth resolution, with

two electronically simulated transposed planes, disclosed that these bats may acoustically resolve the depth of the surface structure with a precision of 0.2 mm (Ref. 29). For instance, a change of target depth from 1.3 mm to 1.5 mm shifts the frequency of the ‘notch of interference’ in the echo spectrum (a narrow frequency band eliminated from the echo spectrum due to interferences between the echoes reflected from the surface and the bottom of the target) from 64.4 kHz to 55.7 kHz. Apparently, the bats hear these shifts in the spectral pattern of the echoes. In the behavioural task they must have learnt and memorized the rewarded spectral echo pattern (echo colour) and compared this pattern with those of other echoes. If an echolocating bat used this capacity of echo-colour discrimination for the detection of motionless insects, it would face the problem of how to discriminate animate stationary structures from inanimate ones. This would place very great demands on the capacity for echo generalization and memorization. However, as demonstrated in the above experiment, a slight change in the sound-reflecting texture will cause considerable shifts in the spectral echo pattern; an insect moving or changing its posture on a supporting substrate should therefore be immediately recognizable by a changing spectral echo pattern or echo colour. Casual observations, behavioural studies and the analysis of highspeed movies suggest that the long-eared bat does detect and successfully attack insects after they had moved on the substrate (R. Coles, pers. commun.). Therefore, changing echo colours could be highly sensitive indicators that an echolocating bat is apparently listening to echoes reflected from a substrate that comprises an animate object. Experiments will have to determine whether the hypothesis of prey detection by changing echo colours is correct. At present, the possibility that bats also discriminate absolutely motionless prey from substrates cannot be excluded28. The capacity to detect changing echo colours should be available in most bats, if they emit short, broad

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band signals. Therefore the use of the resource-niche ‘insects on substrates’, which is only occupied by a minor fraction of the bat order, is probably less limited by auditory constraints than by flight manoeuverability. If, however, foliagegleaning bats not only detect their prey by changing echo colours but also by prey-generated noises, audition would be a decisive selection parameter for exploiting this niche. In fact, the extreme sensitivity to low frequencies (12 kHz) in the long-eared bat (Plecotus auritus)30 suggests that this species also listens to noises as a means of detecting insects on substrates.


wing-beat detection. Behavioural and neuronal audiograms ir36 disclose that these bats are extremely sensitive to frequency ranges below those of their echolocation calls (Fig. 5). In the frequency band from 12 to 25 kHz, auditory thresholds may be as low as -27 dB SPL, i.e. 22 times more sensitive than the human ear under optimal conditions. Apparently, the bats’ audition is tuned to the energy spectrum of rustling noises of all sorts,


which contain considerable sound energy in this frequency band33.

Megadermatids have the highest auditory sensitivity so far measured in mammals. They owe this unsurpassable sensitivity partly to their Listeningto prey-generatednoises huge pinnae (Fig. 51, which act as It is conceivable that insects amplifiers in the 12-35 kHz fremight sometimes occur so densely quency band. As in all mammals, on flowering or fruiting trees that a the pinnae also serve as directional Myra, for insearch in an energetically costly antennae. Megadema slow or hovering flight around and stance, lateralizes a 20 kHz sound within the foliage pays off for a bat. source with a precision of 2”, which The situation is different for large is one of the best spatial resolground-gleaning bats (area 6 in Fig. utions measured in any animal 2): continuous searching flights low except owls (1”). In Megadenna Myra, neuronal over ground might have a low chance of success since prey indiauditory adaptations have also viduals frequently stay or move been studied, and they are even under cover. Megadermatids and more striking than the peripheral nycterids often use a sit-and-wait adaptations of the pinnae31. In the strategy from a suitable vantage midbrain inferior colliculus, through point, such as rock faces or wigs of which all auditory information bushes and trees, and listen to the reaching the auditory cortex is fed, ground with their large pinnae31a32. there is an abundance of neurons Field observations and experithat are tuned to the low frequency ments have shown that mega- band of rustling noises (up to 25 dermatids33 and some nycterids32, kHz). Neurons that are tuned to if not all ground-gleaning bats, frequencies of the echolocation detect and localize their groundcalls occupy less space than those dwelling prey by listening to tuned to lower frequencies. In adprey-generated noises and not by dition, many neurons sensitive to echolocation. The ‘frog-eating bat’ frequencies from 15 to 40 kHz have (Trachops cirrhosus) even differenso-called upper thresholds .and no tiates poisonous frogs from edible longer respond to signals louder ones by listening to the speciesthan 40-50 dB SPL (a sound pressspecific frog callous. The Australian ure level corresponding to that of a ghost bat (Macroderma gigas) is normal conversation in a living immediately attracted to and vig- room). Apparently, such pools of orously attacks a gadget imitating neurons are specialized on faint bird calls. Interestingly, megaderauditory signals31. matids do not react to frog calls and Even more strikingly, in the rostral part of the inferior colliculus we are only alerted by noises generated when the frogs move33s35. found neurons that did not reFaint, rustling noises are best spond, or reacted only poorly, to any sound signal (e.g. pure tones, suited to alerting these bats. sounds) Audition in ground-gleaning bats frequency modulated is as intricately adapted to listening other than noises. Most effective to faint noises (i.e. acoustical sig- were very faint rustling noises, as nals containing at random frequenfor instance the noise produced cies over a broad range) as audition when the experimenter gently in horseshoe bats is tailored for brushed over his beard or when he

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Fig. 5. Low frequency and faint sound sensitivity in three different gleaning bats (Ma, Macroderma gigas; Me, Megadema lyra; P, Plecotus au&us). Upper graph: Audiograms of the three bat species show that they are most sensitive to frequencies below the frequency range of their echolocation sounds (frequency range of the echolocation sounds indicated by horizontal bars). The minimal thresholds are -25 dB SPL between IO and 25 kHZ (0 dB SPL is the minimal threshold of the human ear at optimal conditions, and a change of the sound pressure level by 20 dB means a ten-fold increase or decrease in signal intensity); these thresholds are among the lowest found in the animal kingdom. Data from Refs 30,3/ and 39. Lower graph: Extreme sensitivity to low frequencies lyra, is due to gains by the pinnae. In Megadema auditory sensitivity is considerably reduced when the pinnae are deflected to the head. The difference between the audiogram with pinnae in normal position (continuous line) and that with pinnae deflected (dashed line) demonstrates severe losses of sensitivity in the frequency range from I5 to 40 kHz and 55 to 75 kHz, when the pinnae are eliminated as sound collectors to the eardrum.

exhaled31. Apparently, that part of the auditory brain in Megadema Myrais wired in such a way that only auditory signals that indicate potential prey are filtered out. Such neurons are true feature detectors. The sensitivity of these noisesensitive neurons surpasses that of any technical instrument available to date. By this specific auditory outfit the false vampire is exquisitely armed for the detection and location of concealed, grounddwelling prey in complete darkness. 165

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Conclusions Noise-sensitive neurons, as described above, were first discovered in echolocating bats in 1969 (Ref. 37). Since they do not fit into the concept of echolocation and (until recently) nothing was known about the acoustical ecology of the bats, these neurons were not discussed. This illustrates a fundamental point: in the world of senses, neuronal characterizations will be correctly understood only if one knows the behavioural ecology of the species under study. It then makes sense, for example, that horseshoe bats have an acoustical fovea tuned to their own private carrier frequency, and neurons that prefer to respond to minor modulations of that carrier frequency, since horseshoe bats have specialized on catching wing-beating insects in dense, echo-cluttering vegetation. Finally, if the experimenter did not know how Megadenna lyra catches ground-dwelling prey, he might have overlooked or discarded as ‘unwanted noise’ those specific ‘faint-noise detectors’ in the midbrain of this bat species. A neurobiologist without a knowledge of the behavioural ecology of his animal under study will be blind. Similarly, an ecologist will perhaps never realize why a species sticks to a very specific habitat unless he knows the specific sensory and neuronal adaptations that may tie a species to a distinct habitat. The studies in echolocation show that the sensory brain plays a decisive role in the capacity of a species to occupy and

survive in a particular habitat. This review should demonstrate that combined studies in neurobiology and behavioural ecology will give answers to the questions not only of why but also of how and to which limits natural selection has shaped the species. Such studies are still on a largely descriptive level. Intriguing problems, such as the ontogeny of these adaptive specializations, their plasticity in a rapidly changing and anthropocentric environment or their dependency on individual experience have hardly been addressed.

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