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 Echolocation by Insect-Eating Bats Author(s): HANS-ULRICH SCHNITZLER and ELISABETH K. V. KALKO Reviewed work(s): Source: BioScience, Vol. 51, No. 7 (July 2001), pp. 557-569 Published by: University of California Press on behalf of the American Institute of Biological Sciences Stable URL: http://www.jstor.org/stable/10.1641/0006- 3568%282001%29051%5B0557%3AEBIEB%5D2.0.CO%3B2 . Accessed: 10/02/2012 18:15 Your use of the JSTOR archive indicates your acceptance of the Terms & Conditions of Use, available at  . http://www.jstor.org/page/info/about/policies/terms.jsp JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact [email protected]. University of California Press and American Institute of Biological Sciences  are collaborating with JSTOR to digitize, preserve and extend access to  BioScience. http://www.jstor.org

Echolocation by Insect-Eating Bats(1)

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  • Echolocation by Insect-Eating BatsAuthor(s): HANS-ULRICH SCHNITZLER and ELISABETH K. V. KALKOReviewed work(s):Source: BioScience, Vol. 51, No. 7 (July 2001), pp. 557-569Published by: University of California Press on behalf of the American Institute of Biological SciencesStable URL: http://www.jstor.org/stable/10.1641/0006-3568%282001%29051%5B0557%3AEBIEB%5D2.0.CO%3B2 .Accessed: 10/02/2012 18:15

    Your use of the JSTOR archive indicates your acceptance of the Terms & Conditions of Use, available at .http://www.jstor.org/page/info/about/policies/terms.jsp

    JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range ofcontent in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new formsof scholarship. For more information about JSTOR, please contact [email protected].

    University of California Press and American Institute of Biological Sciences are collaborating with JSTOR todigitize, preserve and extend access to BioScience.

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  • July 2001 / Vol. 51 No. 7 BioScience 557

    Articles

    Bats (order Chiroptera) are ecologically more diversethan any other group of mammals. Numerous mor-phological, physiological, and behavioral adaptations of sen-sory and motor systems permit bats access to a wide range ofhabitats and resources at night. The more than 750 species ofthe suborder Microchiroptera occupy most terrestrial habi-tats and climatic zones and exploit a great variety of foods,ranging from insects and other arthropods, small vertebrates,and blood to fruit, leaves, nectar, flowers, and pollen. Echolo-cation is one of the adaptations that make bats so successful.

    Echolocating animals emit signals of high frequency (mostlyultrasonic) and analyze the returning echoes to detect, char-acterize, and localize the reflected objects. Sophisticatedecholocation systems have evolved only in the bat suborderMicrochiroptera and in dolphins. Less efficient systems havebeen reported for a few species of the bat suborder Megachi-roptera and for some birds (Henson and Schnitzler 1980). Batsuse echolocation for orientation in space, that is, for deter-mining their position relative to the echo-producing envi-ronment. In addition, many bats, especially those that huntfor flying insects, use echolocation to detect, identify, andlocalize prey.

    Bats use a wide variety of species-specific signal types dif-fering in frequency structure, duration, and sound pressurelevel (SPL). In addition, signal structure varies dependingon the echolocation task confronting the bat. Search signalsthat are emitted when bats search for prey differ from approachsignals that are emitted when they approach prey.

    The echolocation signals and hearing systems of bats arewell adapted for gathering behaviorally relevant informa-tion (e.g., Schnitzler and Henson 1980, Neuweiler 1989, Fen-ton 1990, Denzinger et al. forthcoming). In this article we de-scribe the echolocation behavior of insect-eating bats and showhow differing circumstances such as habitat type, foragingmode, and diet favor different signal types. To demonstraterelationships between echolocation and ecological condi-tions, we outline the perceptual tasks that must be performedby foraging bats and discuss the suitability of typical ele-ments of echolocation signals for solving such problems. Wethen define habitat types according to the problems they im-pose on bats and relate the observed variability in signalstructure to ecological constraints set by habitat type andforaging mode.

    Perceptual problems for foraging batsForaging bats confront a multitude of problems when flyingto their hunting grounds and searching for prey. These prob-lems differ depending on where bats hunt, what they eat,and how they acquire their food. For example, bats huntingfor insects in the open encounter conditions different fromthose that search for prey near the edges of vegetation, in veg-etation gaps, in dense forest, or near the ground. The prob-lems also differ depending upon whether they capture mov-ing prey in flight (aerial mode) or mostly stationary preyfrom surfaces such as leaves or ground (gleaning mode) or wa-ter (trawling mode).

    Foraging bats must detect, classify, and localize an insect anddiscriminate between echoes of prey and echoes of unwantedtargets such as twigs, foliage, or the ground, referred to as clut-ter echoes, or simply clutter.For many bats echolocation de-livers all of the information they need to catch an insect.

    Hans-Ulrich Schnitzler (e-mail: Hans-Ulrich.Schnitzler@uni-tuebin-

    gen.de) is professor and head of the Lehrstuhl Tierphysiologie of the

    University of Tbingen, Auf der Morgenstelle 28, D-72076 Tbingen,

    Germany. Elisabeth Kalko is professor and head of the Abteilung Ex-

    perimentelle kologie of the University of Ulm, Albert Einstein Allee

    11, D89069 Ulm. E. Kalko is a staff member and H.-U. Schnitzler

    is a research associate of the Smithsonian Tropical Research Insti-

    tute, Panama. E. Kalko is also a research associate at the National

    Museum of Natural History in Washington, DC. 2001 American In-

    stitute of Biological Sciences.

    Echolocation by Insect-Eating BatsHANS-ULRICH SCHNITZLER AND ELISABETH K. V. KALKO

    WE DEFINE FOUR DISTINCT FUNCTIONAL

    GROUPS OF BATS AND FIND DIFFERENCES

    IN SIGNAL STRUCTURE THAT

    CORRELATE WITH THE TYPICAL ECHOLO-

    CATION TASKS FACED BY EACH GROUP

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    However, some bats rely partly or entirely on other sensorysystems, such as passive hearing, to detect prey-generatedsignals (e.g., calls and rustling sounds of insects) to find theirprey. Independent of specific foraging conditions, all batsmust perform the following basic perceptual tasks:

    Detection.A bat must decide whether or not it has receivedan echo of its own echolocation signal or has heard, seen,smelled, or felt something that indicates prey or othertargets of interest. However, it is difficult to conceptualizedetection independent of classification and localization.

    Classification. Bats categorize targets by means of specificecho information (Ostwald et al. 1988) or other featuresthat reveal their nature. Target properties such as size,shape, material, and texture are encoded in the complextemporal and spectral parameters of an echo.Rhythmical amplitude and frequency modu-lations in the echo reveal movements of preysuch as the beating wings characteristic of afluttering insect (Schnitzler 1987).

    Localization. Echolocation reveals the positionof a target by its range and by its horizontal andvertical spatial angles. The time delay betweenemitted signal and returning echo encodesrange. Binaural echo cues describe the hori-zontal angle, and monaural spectral cues thevertical angle. For moving bats, the flow fieldof reflected sound delivers additional infor-mation that may be used for target localization(Lee et al. 1992, Mller and Schnitzler 1999,2000). Bats using other sensory cues must lo-calize the actual position of the source of aprey-generated sensory signal.

    Interfering factors, such as internal and exter-nal noise, clutter echoes, and signals from otherbats, set limits on the echolocation processes in-volved in detecting, classifying, and localizing apreferred target. Masking effects between targetecho and clutter, and between target echo andemitted signal, notably restrict the processing ofrelevant information.

    The restricted range of echolocation sets spa-tial limits on where bats can find their prey. Thesound pressure level, or SPL, of echoes decreasessharply with increasing target distance because ofgeometric and atmospheric attenuation of soundtraveling in air. Additionally, the echo SPL is re-duced because of the target strength, which de-pends on the size and the form of a target. Batsreceive detectable echoes from flying insects onlyover rather short distances. In an environmentwith a temperature of 20C, a relative humidity of50%, and a realistic detection threshold of about

    15 dB, a bat with a signal SPL of 112 dB 40 cm in front of itshead, with a signal frequency of 20 kHz, can detect a flutter-ing insect with a wing length of 2.5 cm at a detection rangeof not more than 10.5 m. Under similar conditions, a spherewith a diameter of 2.5 cm cannot be detected beyond 7 m. Themaximum detection distance decreases still more with in-creasing signal frequency, humidity, temperature, and de-creasing prey size (Kober and Schnitzler 1990). Thus, echolo-cation is a system that works only over short distances. Forlong-distance orientation, bats must use other sensory systems,such as vision.

    Signals adapted for specific tasksEcological constraints exert strong selection pressure on sig-nal structure, leading to species-specific signals that areadapted for specific tasks. To better understand these

    Figure 1. Search and approach signals of foraging bats. (ae) Signals ofbats that captured a flying insect at the end of the sequence. (f, g) Signalsof bats that gleaned insects from a surface at the end of the sequence, (f)out of continuous search flight and (g) after the prey has been detectedfrom a perch. In all sequences the increase in repetition rate and thereduction of sound duration indicate the switching from search toapproach phase. Note the distinct terminal phase in bats that capturedflying insects (ae).

  • adaptations, we first discuss the kinds of information thatcan be carried by individual elements in the echolocationsignals of bats.

    Most echolocation signals of microchiropterans consistof narrowband or broadband components, or combinationsof these (Figure 1). Narrowband components comprise twosubtypes: quasi-constant frequency (QCF) elements withfrequency changes of a few kHz between the onset and the endof the component (shallow modulation), and long constantfrequency (CF) elements with frequency changes of a fewhundred Hz within the component. Broadband componentsnormally consist of a downward frequency-modulated (FM)element of large bandwidth (steep modulation). These signalelements differ in absolute frequency, bandwidth, harmonicstructure, duration, and SPL, creating the wide variety ofsignal types found in echolocating bats (reviewed in Pye1980, Schnitzler and Henson 1980, Simmons and Stein 1980,Neuweiler 1989, Fenton 1990). For the classification of signalcomponents according to their bandwidth, it is necessary todefine why a signal is classified as narrowband or broad-band.We propose that in narrowband signals the most promi-nent harmonic sweeps over less than half an octave (startingfrequency of the sweep is less than 141% of the terminal fre-quency), whereas in broadband signals it covers more thanhalf an octave.

    The information that can be extracted from the echoes ofvarious elements of a signal depends on their physical struc-ture and on the performance of the bats auditory system. Asa rough approximation, the input stage of the auditory sys-tem of most bats (with the exception of bats with long CF sig-nals) can be described as a bank of neuronal filters with sim-ilar Q values (the best frequency, or the frequency at whichneural responses have the lowest threshold, divided by band-width). Depending on its absolute frequency, bandwidth,and SPL, a signal element evokes neuronal activity in oneor more of the frequency-selective filters. The longer a signalstays within the response range of a filter, the higher theneuronal activity.

    Narrowband signals. Signal elements such as CF or shal-low-modulated QCF components are well suited for detec-tion of echoes because they activate the neuronal filters tunedto the corresponding frequency band during the entire echo.Narrowband signals, especially those of long duration, also canbe used for target classification if bats evaluate the amplitudeand frequency modulations in the echoes arising from char-acteristic target movements.When a signal hits a fluttering in-sect at the favorable instant when the insects wings are per-pendicular to the impinging sound wave, a short and veryprominent amplitude peak in the echo, an acoustic glint, re-veals the fluttering insect target. This glint, which can be upto 2030 dB stronger than an echo from the body of the in-sect, also increases the probability of detection (Kober andSchnitzler 1990, Moss and Zagneski 1994). The probability ofreceiving such a glint depends on the duty cycle (the percentageof time in which signals are emitted) of the bat and the wing-

    beat rate of the insect. For example, a duty cycle of 10% andan insect wingbeat rate of 60 Hz produce an average perceivedglint rate of 6 glints/s.

    Narrowband signals are less suited for precisely localizinga target when bats must accurately measure range as well ashorizontal and vertical angles. Range is encoded in the timedelay between an emitted signal and its returning echo. Foraccurate range determination, bats must determine the exactinstant of sound emission and echo reception. Narrowbandsignals are rather imprecise time markers because they per-sist within the corresponding neuronal filter for an extendedtime, thus diminishing range accuracy. The horizontal angleis encoded in binaural echo cues, and the vertical angle inmonaural echo cues. Narrowband signals, with their small fre-quency range, activate only a few channels that deliver suchcues, thus reducing a precise angle determination.

    Broadband signals. Signals such as steep-modulated FMsignals are less suited for the detection of weak echoes. Thesesignals sweep rapidly through the tuning areas of the corre-sponding neuronal filters so that each detector is activated onlyfor a very short time. Frequency-modulated signals of broadbandwidth are well suited for exact target localization whererange and angle must be measured accurately. Steep-modu-lated broadband FM signals activate each filter for only avery short instant, producing the precise time markers neededfor an exact determination of the time delay that encodes therange. Large signal bandwidths activate more neuronal filters,improving the accuracy of range determination if, as is indi-cated by behavioral experiments, the range information is av-eraged over all activated channels (Moss and Schnitzler 1995).The activation of many channels also improves the accuracyof angle determination with increasing bandwidth.

    Frequency-modulated signals of large bandwidth also de-liver spectral cues that can be used for target classification. Tar-get features such as texture (which affects the absorption ofsound at different frequencies) and depth structure (whichcauses an interference pattern due to overlapping multi-wave-front echoes) are somehow reflected in the echo spec-trum, thus encoding information about the character of a tar-get (Ostwald et al. 1988). In the laboratory, bats learn to usesuch spectral differences to discriminate among targets, so itis assumed that broadband FM signals allow spectral char-acterization of prey (Neuweiler 1989, 1990). However, this istrue only if the spectral signature of echoes is so specificthat, independent of aspect angle, it is possible for the echofrom an insect to be distinguished from clutter echoes.

    Long CF signals with Doppler-shift compensa-tion. Long CF signals, like other narrowband signals, are wellsuited for the detection of weak echoes and less well suited forthe exact localization of targets. In combination with Doppler-shift compensation (see below) and a specialized hearingsystem, the long CF signals facilitate the detection and clas-sification of fluttering insects in a cluttered environment.The beating wings of insects produce a rhythmical pattern of

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  • amplitude and frequency modulations that encode wingbeatrate, wing size, and other species-specific information. Themost prominent flutter features are the very short and strongamplitude peaks of acoustic glints, produced when the wingsare perpendicular to the impinging sound waves (Kober andSchnitzler 1990). Transmitters and receivers of the echoloca-tion systems of bats emitting CF signals are especially adaptedto process this kind of information (Schnitzler and Ostwald1983, Neuweiler 1990). By lowering emission frequency, thesebats compensate for Doppler shifts caused by their own flightmovement. Thus, the frequency of the CF component of in-sect echoes is kept within an expectation window.A corre-sponding analysis windowis established in the hearing sys-tem by a specialized cochlea with a highly expanded frequencyrepresentation in the range of the insect echoes. This acousticfovea leads to an over-representation of sharply tuned neu-rons with special response characteristics throughout the au-ditory pathway. With these specific adaptations, bats using CFsignals can discriminate the modulated insect echo fromoverlapping unmodulated clutter echoes and classify insectsaccording to their prey-specific modulationpattern (vd Emde and Schnitzler 1990).

    Detection versus localization trade-off. Narrowbandsignals are good for target detection but less well suited for tar-get localization. Broadband FM signals, however, aregood for localization but less well suited for detec-tion. This trade-off between detectability and accuracyof localization is reflected in the structure of search sig-nals in some bats. Bats that have to perform several taskssimultaneously combine suitable signal elements. Typ-ical combinations of broadband and narrowbandcomponents are found in FMQCF, QCFFM, andCFFM signals, and also in FM signals with changingsteepness. For instance, bats of the genus Myotis (Ves-pertilionidae) flying in the open often produce signalsin which the steep initial part of the signal is followedby a shallower part that ends in a steeper segment. Thesteeper FM components are well suited for localization,and the shallow component improves detection byintroducing more signal energy into the correspond-ing neuronal filters.

    The masking problemThe separation of target echo from interfering signalsis an important task facing echolocating bats. Theevaluation of sonar echoes from a target is hamperedwhen the neuronal activity evoked by clutter echoes andby the bats own emitted signal interferes with theactivity evoked by the target echo. Interfering signalsthat precede the target echo, such as the emittedsignal, produce a forward-masking effect. Interferingsignals that follow the target echo, such as clutterechoes, produce a backward-masking effect. Depend-ing on the signal type, several strategies are used toavoid masking.

    Field and laboratory studies indicate that bats (with the ex-ception of those using long CFFM signals) normally avoidan overlap of the target echo with clutter echoes and also withtheir own emitted signal (Kalko and Schnitzler 1989, 1993).This avoidance of overlap suggests that all signal types exceptfor CF elements are sensitive to overlap. Due to overlap in-terference, the ability of bats to evaluate insect echoes dependson the position of an insect relative to the bat and to clutterecho producing background targets. When an insect flies soclose to a bat that the returning echo overlaps the emitted sig-nal, forward-masking effects interfere with the evaluation ofthe insect echo. Therefore forward masking reduces the prob-ability of detection in the zone in front of the bat where over-lap occurs. The width of this signal-overlap zone depends onsignal duration (Figure 2). For example, with a signal dura-tion of 10 ms the overlap zone is 1.70 m wide at a speed ofsound of 340 m/s. If undisturbed detection is only possiblebeyond this signal-overlap zone, signal duration sets a min-imum detection distance. Each ms of signal duration adds 17cm to this minimum detection distance.

    When an insect flies so close to clutter that its echoes over-lap the clutter echoes, backward masking reduces the prob-ability of detection in this clutter-overlap zone. The width ofthis clutter-overlap zone is determined also by signal duration.Only insects flying far away from the bat and from the clut-

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    Figure 2. Schematic diagram of the masking situation for a batforaging near vegetation and emitting signals with a duration of 6 ms.The prey echo overlaps the emitted signal when the insect flies in thesignal-overlap zone, and it overlaps the clutter echoes when it flies inthe clutter-overlap zone. No overlap occurs when the insect flies in theoverlap-free window. At a distance of 2 m the overlap-free window isclosed, and for the given signal duration the bat has reached theminimum gap size where overlap-free echolocation is impossible.

  • ter-producing background where no overlap occurs can be de-tected without interference. By our definition, these insects flyin an overlap-free window (Figure 2). The forward- andbackward-masking effects strongly depend on signal structure,on the SPL of prey echo and masking signals, and on their tem-poral relationship. Therefore the definition of an overlapzone as an area where masking effects interfere with theevaluation of the echo is only a rough approximation of theeffective masking zones. Depending on the signal type usedby a bat, the masking zone may be smaller than the overlapzone calculated from sound duration. For example, a studyon Myotis nattereri, a bat that searches for prey using wide-band FM signals very close to vegetation, indicates that thesebats tolerate some overlap between prey and clutter echoes(Siemers and Schnitzler 2000). Nevertheless, the calculationof the overlap zone is a useful tool to judge the dangerof masking.

    In bats with long CF signals, the CF component of the emit-ted signal and that of the returning echo often overlap (Fig-ure 3d). This overlap produces no masking effect, becauseDoppler-shift compensation keeps the target echo in therange of the extremely sharply tuned neurons of the acousticfovea, whereas the emitted signal is lower in frequency and fallsin a range where the auditory threshold is high (Schnitzler andOstwald 1983, Neuweiler 1990). Therefore, long CF compo-nents of Doppler-compensating bats are not vulnerable tooverlap.

    Foraging habitats defined by clutter conditionsComparative studies reveal that for foraging bats, clutterconditions are the most important ecological constraints.They can be used to define various foraging habitats (Schnit-zler and Kalko 1998, Denzinger et al. forthcoming). Clutterconditions are described by the proximity of the desired preyitem to clutter such as vegetation or ground. Such clutterrepresents perceptual as well as mechanical problems for bats(Fenton 1990). Perceptually, bats are constrained by theirsensory capacities (e.g., echolocation, vision, olfaction, pas-sive listening) to detect, classify, and locate prey in the vicin-ity of clutter-producing background targets. Mechanically, batsare constrained by their motor capacities, such as flight abil-ities (Norberg and Rayner 1987). For instance, bats that for-age near clutter need special maneuverability (e.g., adaptationsin wing morphology) to intercept insects while also avoidingcollisions. Here we discuss only the perceptual problem, andwe define three habitat types according to clutter conditions(Figures 3 and 4).

    Uncluttered space. For bats that forage for insects inuncluttered spacein open spaces, high above the ground andfar from vegetationclutter echoes from the backgroundare so far from the emitted signal and target echoes that theyplay no role in the echolocation process (Figures 3a and 4).In these bats a returning echo generally indicates a flyinginsect.

    Background-cluttered space. For bats that forage forinsects in background-cluttered spacenear the edges ofvegetation, in vegetation gaps, or near ground or water sur-facesthe pulseinsect echo pair is followed by clutter echoesfrom the background (Figures 3b and 4). These bats must solvetwo problems. First, they must recognize the insect echo andseparate it from the echoes of background clutter. Second, theymust characterize the clutter-producing background targetsto identify landmarks for navigation and to avoid collision.

    The border between background-cluttered and unclut-tered space is indicated in many species of bats by theirecholocation behavior (Kalko and Schnitzler 1993, Schnitzlerand Kalko 1998, Jensen and Miller 1999). In uncluttered

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    Figure 3. Schematic diagram of the input into theauditory system of bats that forage in different cluttersituations. The emitted pulse and the returning insectecho are depicted in black. (a) In uncluttered space, thepulse echopair is far from clutter echoes. (b) Inbackground-cluttered space, the pulseecho pair isfollowed by clutter echoes (depicted in white). (c, d) Inhighly cluttered space, the target echo is buried inoverlapping clutter echoes. Sound duration and envelopeform correspond to search signals typical for the differentspaces: (a) QCF signal of an open-space forager; (b)broadband FMQCF signal of an edge and gap forager;(c) broadband FM signal of a narrow-space FMforager; (d) long CFFM signal of a narrow-space CFforager; the echo shows amplitude modulations, or glints,created by the beating wings of an insect.

  • space bats often use relatively long search signals of narrowbandwidth and mostly emit a search signal only every secondor third wingbeat. In background-cluttered space most batsemit one search signal of larger bandwidth at every wingbeat,thus indicating that echoes from the clutter-producing back-ground also guide bats behavior. When crossing the borderbetween the two spaces, bats change their echolocationbehavior (see signals of Pipistrellus in Figures 4 and 5). Thebest indicator for the switch between the two spaces is thechange in the rhythm of sound emission.

    Highly cluttered space. For bats that forage for flyinginsects in highly cluttered spacevery close to surfaces suchas leaves or groundand for bats gleaning stationary food (sit-ting insects, other animals, fruit, leaves, nectar, blood) fromsurfaces, two situations occur. For gleaning bats that useshort broadband FM signals, echoes from food items areburied in clutter (Figure 3c) so that masking hampers theirevaluation. For bats using long CF signals to detect flying in-sects, the overlapping pulseecho pair also overlaps clutterechoes (Figure 3d). Bats foraging in highly cluttered space have

    the problem of discriminating between echoes from the fooditem and overlapping clutter echoes. Moreover, they have tonavigate along landmarks and to avoid collisions. The relationbetween insect echoes and masking clutter echoes definesthe border between highly cluttered and background-clutteredspace. A bat forages in highly cluttered space when the preyis situated in the clutter-overlap zone, where clutter echoesoverlap prey echoes. In the few species that tolerate someoverlap between prey and clutter, highly cluttered space cor-responds more precisely to the zone where the prey echo ismasked by the clutter echoes. Furthermore, bats flying par-allel to clutter may be able to reduce the masking effect of clut-ter echoes by spatial clutter rejection. However, to facilitatecomparison between species, we propose to define the highlycluttered space as the area where insect echo and clutterechoes overlap as a first approximation to describe the mask-ing problem.

    Guild structure of batsComparative studies have revealed that bats foraging in sim-ilar habitats with similar foraging modes for similar diets

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    Figure 4. Schematic diagram of the foraging habitats of bats according to the clutter situation, with flight silhouettes andsearch signals of representative species. In uncluttered space, bats forage for prey far away from vegetation and the ground.In background-cluttered space, bats hunt for insects flying near obstacles (e.g., at edges of vegetation, near the ground orwater surfaces, and in gaps between and in vegetation). In highly cluttered space, bats forage for prey flying close to orsitting on vegetation or the ground. The bats depicted are not sympatric. The border between uncluttered and background-cluttered space is defined by the echolocation behavior of bats. When entering the uncluttered space from background-cluttered space, foragers switch from broadband signals to narrowband signals, and vice versa (e.g., Pipistrellus kuhli). Inthis diagram this border is about 5 m away from vegetation and the ground as described for pipistrelles. The border betweenbackground and highly cluttered space is determined by the beginning of the clutter-overlap zone in which insect echoesoverlap clutter echoes.

  • encounter similar ecological constraints and share similaradaptations of sensory and motor systems. In this context,arranging assemblages of species into guilds, that is, groupsof species that live under similar ecological conditions (Root1967), has proven a useful approach toward understandingadaptations of sensory and motor systems. Habitat type, for-aging mode, and diet characterize our proposed guilds for bats(Kalko et al. 1996, Schnitzler and Kalko 1998).

    To categorize habitats we use the three clutter spaces as de-fined above. For foraging modes we distinguish bats thatcapture insects in the air (aerial mode) from those that gleaninsects and other food from solid surfaces (gleaning mode)or from water (trawling mode). According to their preferreddiet we categorize bats as insectivores, carnivores, piscivores,sanguivores, frugivores, nectarivores, or omnivores. Theseguilds characterize ecological constraints as sets of tasks im-posed on sensory as well as on motor systems. The catego-rization presented here differs somewhat from that in formerpublications (Schnitzler and Kalko 1998). In light of newdata (Boonman et al. 1998, Rydell et al. 1999), we propose anadditional foraging mode (trawling) and introduce a newguild background-cluttered space trawling insectivore/pis-civore, which replaces the former guild highly clutteredspace gleaning piscivore (Table 1).

    Search signals of insect-eating batsIn describing the echolocation behavior of insect-eating bats,we will show that bats belonging to the same guild sharemany similarities in echolocation behavior, especially in thestructure of search signals, which are intimately linkedto habitat type and foraging mode. Search signals areemitted when bats are searching for prey, or when theycommute from one place to another and do not approach aspecific target.

    Aerial insectivores in uncluttered space. Bats hunt-ing in open, uncluttered space, high above the ground orcanopy and far from obstacles, are found mainly in four fam-ilies: free-tailed bats (Molossidae, e.g., Molossus, Promops,Tadarida), mouse-tailed bats (Rhinopomatidae, Rhinopoma),sheath-tailed bats (Emballonuridae, e.g., Diclidurus, Per-opteryx, Taphozous), and evening bats (Vespertilionidae, e.g.,Lasiurus, Nyctalus; Figures 1a and 1b, 4, and 5a).When search-ing for insects, these bats have no masking problem as longas the emitted signal does not overlap the returning insect echo.However, they often have the problem of rather small prey be-ing sparsely distributed in a large space. In that case, a bat mustcover a large search area to find an insect. This and the ratherlow SPL of insect echoes make it difficult to detect potentialprey. Thus, echolocation signals should be optimized fordetection.

    Typically, bats flying in the open emit overlap-sensitive, nar-rowband search signals of ratherlong duration (approximetely825 ms) with a low frequency (half an octave) signals of intermediate duration (approx-imetely 310 ms), with a medium frequency narrowbandcomponent (approximately 3060 kHz). Signal emission isusually correlated in a 1:1 ratio with wingbeat. Pulse intervalis shorter (approximetely 70150 ms) than that produced byaerial insectivores in uncluttered space.

    The narrowband components of the mixed signals greatlyfacilitate detection of prey, and the broadband FM compo-nents are well suited for the localization and characterizationof extended background targets necessary for recognizinglandmarks and avoiding collisions. Because of the sensitivityto overlap, bats foraging near edges mainly search for and de-tect prey within the overlap-free window, where the preyecho is not masked by the emitted call (forward-masking ef-fect) and where echoes from the background do not interferewith the prey echo (backward-masking effect). Field studiesshow that the shorter the signals, the closer to vegetation a batcan hunt (e.g., Kalko and Schnitzler 1993).

    Some bats are highly flexible in their foraging and echolo-cation behavior and switch between uncluttered and back-ground-cluttered space. In uncluttered space the echolocationbehavior does not change depending on distance to back-ground targets, whereas in background-cluttered space batsreact to the background targets. The border between thosespaces is defined by changes in the echolocation behavior ofthe bats. For instance, pipistrelles hunting for insects in openspaces emit rather long, shallow-modulated, narrowbandsignals (QCF), whereas those hunting within less than 5 m ofclutter-producing background switch to shorter signalsand add a steep-modulated, broadband component(FMQCF). Some preliminary field data from the big brownbat (Eptesicus fuscus) and the noctule bat (Nyctalus noctula)suggest that the transition distance between spaces isspecies specific.

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  • A special group within background-cluttered space insec-tivores consists of bats that catch insects in the trawling modefrom calm and uncluttered water surfaces (e.g., Myotis dauben-tonii). They do not receive clutter echoes from the water (butfrom background targets such as the shore) because a calmsurface is like a mirror that reflects the emitted signals awayfrom the bat (Rydell et al. 1999). Therefore these trawling batscan be categorized as background-cluttered space trawlinginsectivores(Table 1). When foraging for insects sitting onor flying close to duckweed or rippled water, bats have diffi-culty perceiving prey as the prey echo is buried in clutterechoes (Boonman et al. 1998). The two species of bulldog bats(Noctilionidae), one of which, Noctilio leporinus, is wellknown for its fishing habits (Schnitzler et al. 1994, Kalko andSchnitzler 1998), also forage for insects close to or drifting onthe water surface while emitting high-intensity CF and CFFMsignals of medium duration that are rather similar to theQCFFM signals of mormoopid bats.

    Aerial insectivores in highly cluttered space. Batssearching for and catching fluttering insects in highly clutteredspace close to vegetation or the ground include all horse-shoe and Old World leaf-nosed bats (Rhinolophidae, Hip-posideridae; Figures 1e, 4, and 5f) and the New World mus-tached bat, Pteronotus parnellii (Mormoopidae). All of thesebats must cope with a situation in which insect echoes areburied in background clutter (Figure 3d). Only if the echoesare so unique that they can be distinguished from the clutterechoes can these bats detect, classify, and localize prey byecholocation alone. Moreover, these bats must also knowtheir exact spatial position to navigate and to avoid collision.

    Bats in the guild highly cluttered space aerial insectivoressolve their problems by using long-duration (approximately10100 ms), medium to high frequency (> 30 kHz) CF orCFFM signals. They emit mostly one search signal per wing-beat. The CF component is overlap insensitive, but the FMcomponent is not. Groups of several search signals per wing-beat have also been recorded.

    Because of the long duration of signals and the proximityof background targets, bats using CFFM signals almost ex-clusively forage for insects flying in the clutter-overlap zone.Special adaptations of the echolocation system, such asDoppler-shift compensation, an auditory fovea in the cochlea,and a highly modified processing area in the auditory cortex,enable bats using CFFM signals to distinguish insect echoesmodulated in the rhythm of the wingbeat from the overlap-ping, unmodulated emitted signals and clutter echoes. As inother bats, the overlap-sensitive FM component is used for pre-cise localization of targets. With these adaptations, the signalsare especially adapted to forage for insects in highly clut-tered environments.

    The mustached bat (Pteronotus parnellii) forages contin-uously on the wing, whereas others (Hipposideros, Rhino-lophus) sometimes also hunt from perches in a flycatcherstyle. They capture fluttering insects, mainly in the air, but theysometimes also glean them from surfaces.

    Gleaning insectivores in highly cluttered space.Bats gleaning their prey from surfaces of vegetation or theground forage in highly cluttered space. They are mainlyfound among ghost-faced bats (Megadermatidae), slit-facedbats (Nycteridae), New World leaf-nosed bats (Phyllostomi-dae), and evening bats (Vespertilionidae; Figures 1f and 1g,4, 5d and 5e). Like bats in the highly cluttered space aerialinsectivore guild, they must cope with a situation in which preyechoes are buried in background clutter (Figure 3c). Onlyif the echoes have a prey-specific signature that canbe distinguished from clutter echoes can the bats find theirprey by echolocation. Moreover, they also face the problemthat they must know their exact spatial position andthe position of landmarks for navigation and collisionavoidance.

    Bats of the highly cluttered space gleaning insectivoresandall other gleaners use broadband, overlap-sensitive uni- or mul-tiharmonic calls of short duration (approximately 13 ms),often at a very low SPL (whispering bats). Depending on thedistance from clutter targets, the bats emit either a single sig-nal or groups of two or more signals per wingbeat. Theechoes of their mostly stationary insect prey are buried in clut-ter, making the use of echolocation for detection, localization,and classification difficult if not impossible. In laboratory stud-ies, narrow-space, gleaning, FM-emitting foragers have learnedto discriminate various targets according to spectral differencesin the echoes (summarized in Ostwald et al. 1988), and it hasbeen suggested that bats can use spectral cues to distinguishstationary prey from clutter (Simmons and Stein 1980,Neuweiler 1990). However, to date no one has been able todemonstrate that spectral cues in echoes from nonflying in-sects are specific enough for bats to recognize them usingbroadband FM signals under normal field conditions in ahighly cluttered situation.

    Many gleaners that emit broadband FM signals use prey-generated acoustic cues (e.g., calls of insects and frogs orrustling noises of insects walking on leaf litter) for detec-tion, classification, and localization of prey (Tuttle and Ryan1981, Belwood and Morris 1987, Faure and Barclay 1994).Many gleaners are characterized by large ears that facilitate pas-sive acoustic localization of prey. All gleaners always emitecholocation signals in flight to determine the position of thesite with food, to navigate, and to avoid collisions. The low SPLof the calls may prevent overloading of the hearing system withloud clutter echoes.

    The use of prey-generated acoustic cues for the detection,localization, and classification of prey does not exclude the pos-sibility of a gleaning bat using echolocation to find its prey un-der favorable conditions. Learning in a context-specific situ-ation may play an important role. For example, if we offer aMyotis myotis individual a noisy insect sitting on a screen, itfirst uses the prey-generated sounds for passive localization,approach, and capture of the insect. After some experience,the bat learns that echolocation cues from a protruding tar-get indicate a sitting insect and thus also approaches silent in-sects. Bats make such a transfer to echolocation only if, in a

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  • specific place, some kind of echolocation cues can be associ-ated with prey. In other places they do not react to similarecholocation cues.

    Other meaningful categorizations of batsSimilar ecological constraints exert similar selective pres-sures on signal design, resulting in a coherent and distinctiveclass of characters in the search signals of bats that live undersimilar conditions. This intimate linkage allows one to clas-sify bats into functional groups such as guilds. The prerequisitefor the categorization of bats into meaningful groups is thedefinition of habitats. Fenton (1990) summarizes suchapproaches and distinguishes three main habitat types: open,edge, and closed habitat. We use a rather similar classificationand define explicit borders between the habitat types(Schnitzler and Kalko 1998). We propose that bats foragingmainly in one of the three defined habitat types, unclutteredspace, background-cluttered space, or highly cluttered space,can be categorized as open-space foragers, edge and gap foragers,and narrow-space foragers, respectively. With open-spaceforagers and with edge and gap foragers,the grouping matches the correspondingguilds uncluttered aerial or trawling in-sectivoresand background-cluttered aer-ial or trawling insectivores. The group ofnarrow-space foragers covers all the guildsof bats that forage in highly cluttered space,gleaning their prey from surfaces or cap-turing aerial prey close by. In both situa-tions, the prey echo overlaps with the clut-ter echo from the substratum.

    This overlap is likely to mask importantinformation, and to solve this problemtwo behavioral strategies have evolved.The preferred foraging habitats, behav-ioral strategies, and the associated signaltypes are used to categorize two subgroupsof narrow-space foragers. To avoid misin-terpretation (Fenton 1999) and to makeclear that the cited signal types indicate aspecific behavioral strategy, the abbrevia-tions of these signal types appear in quo-tation marks (Schnitzler et al. forthcom-ing). The group of narrow-spaceflutter-detecting CFforagers correspondsto the guild highly cluttered space aerial in-sectivores. By Doppler-shift compensa-tion and specialized hearing systems, theyseparate the long CFFM emitted signalfrom the overlapping returning echoes inthe frequency domain, and they evaluateflutter information. The group of narrow-space gleaning FM foragers represents allguilds that include gleaning bats (with theexception of the trawling bats), includingthe guild highly cluttered space gleaning in-

    sectivores described above. It makes sense to categorize allgleaners into one group, as they have to solve rather similarproblems when searching for food. While flying in narrowspaces, these bats mainly use prey-generated cues to detect,localize, and classify their prey, and they use their broadbanduni- or multiharmonic FM signals of short duration andlow SPL mainly for orientation.

    Fenton proposes another categorization to describe theecholocation behavior of bats and the approach an animaltakes to foraging (summarized in Fenton 1999). He distin-guishes between high and lowduty cycle bats based on therelative amount of time signals are emitted. The highdutycycle bats correspond to the narrow-space flutter-detectingCF foragers, whereas the lowduty cycle bats cover all theremaining foragers and unite groups as different as open-space,edge and gap, and narrow-space gleaning FM foragers. Ad-ditionally, Fenton differentiates between low and highsig-nal intensity bats under the premise that this classification dis-tinguishes aerial insectivores from gleaning bats. We prefer tocategorize bats into meaningful groups according to their

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    Figure 6. Approach flight and capture maneuver, with the corresponding searchand approach signal sequence, of a Pipistrellus pipistrellus capturing an insect.The numbers allow a correlation between hunting and echolocation behavior(small numbers indicate the position of the insect). At points 14 the bat is inapproach flight, at 5 it extends one wing toward the insect and moves its tail intoa capture position (tail down), at 6 the bat bends its head into a pouch formed bythe tail membrane to retrieve the insect (head down), and at 7 the bat straightensits body and resumes its search flight. In the sequence of echolocation signals,arrows indicate the following phases in echolocation behavior: SP, search phase;AP, approach phase; BI, buzz I; BII, buzz II; P, pause.

  • main foraging habitat and behavioral strategy, not accordingto less distinctive signal parameters such as duty cycle and thehighly variable signal intensity.

    Approach signals of insect-eating batsAfter insect-eating bats have detected prey, they approachand capture it (Figure 6). Depending on how these bats for-age, they face echolocation problems of varying difficulty. Batsthat approach a target or a landing site emit a sequence of ap-proach signals. These signals have the function of guiding thebat to the chosen target or site. The sequence of approach sig-nals is less dominated by the habitat type than by the move-ment of the chosen target (see Kalko and Schnitzler 1998).

    Insectivorous bats that capture prey in the air need to con-tinuously determine the position of prey while closing in onit. Because these bats rely on echolocation to locate and trackmoving insects, we describe this foraging mode as the activemode. By comparison, gleaning bats that take prey from sur-faces or the ground mostly evaluate prey-generated acousticcues to detect, classify, and localize their usually stationary prey.Because gleaners largely do not use echolocation to find theirprey, we describe this foraging mode as the passive mode.

    In a few cases, bats do not use echolocation or other sen-sory cues directly to find distant prey but screen known or pre-sumed feeding sites based on previous experience.Accordingly,these bats forage in a random mode (Schnitzler et al. 1994,Schnitzler and Kalko 1998).

    Aerial or trawling insectivores. From photographic se-quences of aerial captures by bats in the field and in the lab-oratory, and from synchronized sound recordings, we foundthat when aerial or trawling insectivorous bats detect an in-sect, they immediately switch from search flight to a target-oriented approach flight, with head and ears pointing to-ward the insect. Simultaneously, the bats change theirecholocation behavior from the search phase, with corre-sponding search signals, to the approach phase or approachsequence, with distinctive approach signals (Figures 1aeand 6; Griffin et al. 1960).

    In the approach phase, bats emit signals in groups corre-lated with wingbeat and respiratory cycles. The start of the ap-proach is characterized by a change in signal parameters.With a few exceptions, signal duration and pulse interval arereduced throughout the approach phase, which ends in theterminal phase, or buzz, prior to capturing an insect. The ter-minal phase is characterized by a series of short signals at ahigh repetition rate (up to 180200 Hz), usually in one butsometimes in two or more groups. Typically, the terminalphase of pipistrelles and some vespertilionids (Pipistrellus,Myotis) consists of two parts: buzz I (BI) and buzz II (BII;Kalko and Schnitzler 1989). Buzz II signals are reduced inbandwidth and lower in frequency than buzz I signals(Figure 6).

    In contrast to the various types of search signals foundamong insectivorous bats, approach signals are remarkablysimilar. Evening bats (Vespertilionidae) and free-tailed bats

    (Molossidae) emit broadband FM signals. Narrowband com-ponents are eliminated. Similarity in call design reflects asimilar challenge: the exact localization and tracking of amoving target in space. Short FM signals are well suited forthis task. Moreover, the high repetition rate enhances the in-formation flow needed to control last-instant changes in theinsects position in space.

    Sheath-tailed bats (Emballonuridae) and mouse-tailedbats (Rhinopomatidae) enlarge the bandwidth of the domi-nant harmonic less strongly than seen in the FM approach sig-nals of vespertilionids and molossids. They maintain the ba-sic structure of their search signals and increase the amplitudeof other harmonics (Figure 1d). This change may increase theoverall bandwidth of calls of these species.

    With the exception of narrow-space flutter-detecting CFforagers, aerial insectivorous bats avoid an overlap betweenapproach signals and prey echoes by reducing sound durationand pulse interval to keep the insect in the overlap-free win-dow. It has been shown for pipistrelles that sound emissionactually stops several centimeters before the bat reaches theprey (Kalko 1995).

    Narrow-space flutter-detecting CF foragers reduce thesound duration of the FM portion of their calls but maintaina rather long CF component throughout the approach se-quence. As in search phase, the CF component of the echooverlaps with the emitted signal. This has no masking effect,because the emitted CF component does not mask theDoppler-shifted CF component of the echo due to the acousticfovea and sharply tuned neurons in this frequency range.Presumably, most narrow-space flutter-detecting CFforagersneed the CF component also during approach to discriminatethe fluttering prey from the background. The FM component,however, is reduced and is used for localization.

    Gleaning insectivores. Echolocation is used by gleaninginsectivorous bats for orientation in space and to guide thebat to the site with prey. After the detection of prey-generatedsignals, narrow-space gleaning FM foragers fly toward thesound source and, nearing the site with food, switch to an ap-proach sequence in which they increase the repetition rate andreduce the signal duration (Figures 1f and g). However, in con-trast to aerial insectivores, gleaning bats do not produce a dis-tinct terminal phase when they are close to the site with food.By comparison, the repetition rate remains much lower. Thisbehavioral discrepancy reflects the major difference betweengleaners, which approach mostly stationary prey, and aerialinsectivores, which track moving prey and constantly need toupdate the information about an insects position to suc-cessfully intercept it.

    Flexibility in foraging and echolocation behaviorBats are highly variable in their foraging and echolocation be-havior (Fenton 1990). Some bats hunt in more than onehabitat, or they may use both aerial and gleaning modes.Some species that mainly glean insects from surfaces in highly

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  • cluttered space in the passive mode also catch insects in theaerial mode in background-cluttered space or even in un-cluttered space (e.g., Plecotus). Increasingly, field studies showthat many bats that forage mainly in background-clutteredspace also search for insects in uncluttered space (e.g., Pip-istrellus).

    Flexibility in foraging behavior correlates with plasticity inecholocation behavior, such as switching from mixed signalswith a broadband FM component in background-clutteredspace to narrowband signals in uncluttered space (e.g., Pip-istrellus). Another strategy is switching from short multihar-monic FM signals of low intensity when gleaning in highlycluttered space to much louder and longer uniharmonic FMsignals with a distinct shallow-modulated component whenforaging in background-cluttered space (e.g., Plecotus). Manygleaners use louder signals when they fly more in the open.Therefore signal intensity is not a good parameter to catego-rize bats into meaningful groups. However, there are limits tosuch behavioral plasticity. Bats that are especially adaptedfor hunting in uncluttered space (e.g., Tadarida) are usuallyrestricted to this habitat and cannot search for insects inbackground-cluttered and highly cluttered space. Bats that aremainly adapted for background-cluttered space do not exploithighly cluttered space. Thus, the access of bats from theirspecific habitat to a less-cluttered space is possible, but the re-verse is not. Fenton (1990) explained this restriction based onperceptual problems (ability to detect prey in clutter) and me-chanical problems (ability to fly close to clutter). Limitationsof the motor system, particularly flight performance deter-mined by wing shape, largely prevent access to habitats witha more difficult clutter situation. Sensory abilities, or at leastthe ability to produce the suitable echolocation signals, shouldbe less restrictive, as all bats can produce the short FM signalsnecessary in cluttered situations.

    Flexibility creates exceptions and can make it difficult toclearly define boundaries between guilds and to assign indi-vidual species to a particular guild. However, in such cases wewould classify bats into guilds according to their dominant sen-sory and motor adaptation and assign them to the habitat typewhere they face the more difficult clutter situation. For in-stance, bats that hunt in background-cluttered and unclutteredspace would be assigned to background-cluttered space.

    The comparison of the echolocation behavior of insecteating bats reveals that bats foraging in similar habitats withsimilar foraging modes for similar diets share similar adap-tations in their echolocation systems.When moving from onehabitat to another, bats change their echolocation behavior andemit the habitat-specific search calls (Figure 5). Therefore, theecholocation behavior of bats and especially the structure ofsearch signals are good indicators of the ecological constraintsunder which bats search for food.

    AcknowledgmentsSome of the ideas of this paper have been stimulated by thework of people who cannot all be cited due to limited space.We thank them all, in particular Don Griffin, Brock Fenton,

    Gerhard Neuweiler, and their coworkers.We also thank I. Kaipffor technical assistance in the laboratory and in the field.This article has benefited greatly from the comments of An-nette Denzinger, Charles Handley, Jo Ostwald, Cindy Moss,and Allen Herre. Our field work has been supported by grantsfrom the Deutsche Forschungsgemeinschaft (SFB 307, SPPMechanismen zur Aufrechterhaltung tropischer Diversitt;SFB 550) and Smithsonian trust funds. We also acknowl-edge the excellent working conditions of the SmithsonianTropical Research Institute in Panama.

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