72 Bat Echolocation Research: tools, techniques & analysis

IN T R O D U C T I O N

Beginning in the late 1970s, ultrasound detectorshave been used for identification and field studies of batsin Europe with new techniques being continuouslydeveloped (e.g., Ahlén 1981, 1990; Ahlén and Baagøe1999; Ahlén and Pettersson 1985; Andersen and Miller1977; Limpens and Roschen 1995; Miller and Degn1981; Weid 1988; Weid and von Helversen 1987; Zingg1990) Technological improvements and experience withdifferent systems have led to an expanding knowledge ofdifferent species, including how they can be identifiedand observed in nature. The purpose of this paper is todescribe two ultrasound-conversion systems, heterodyneand time expansion, and evaluate the advantages andlimitations of each system.

FE AT U R E S O F T H E HE T E R O D Y N E SY S T E M

The heterodyne system is sensitive and enables long-range detection of bats. Therefore, it is perhaps the bestsystem to detect the most bats. The narrow frequencyband that is transposed to audible sound must be tunedto the sounds made by the bat. This means that there isa risk of missing a bat even at short range. Careful tun-ing will allow an observer to determine whether there isa constant-frequency or near- c o n s t a n t - f re q u e n c ycomponent (tonal quality) in the sound and at approxi-

mately which frequency. FM sweeps can be described asdry clicks, while quasi-constant frequency componentssound like smacking or drops of water, and longerc o n s t a n t - f requency components sound tonal orwhistling. A number of other sound qualities can beheard using a heterodyne system but all are difficult orimpossible to measure. Using most heterodyne detectorsit is impossible to save frequency information other thanremembering the tuning. Therefore, a combination ofheterodyne and frequency-division system (Andersenand Miller 1977) represent a solution to that problem,and were commonly used until time expansion becameavailable.

The heterodyne system enables sampling of longsequences of pulses which, when displayed as oscillo-grams, allow analyses of pulse repetition or rhythm.

FE AT U R E S O F T H E TI M E- EX PA N S I O N SY S T E M

The time-expansion system preserves the unchangedoriginal sound with the high frequencies and harmonics.It can be played back at a slower speed, typically 10times slower (20 times for very high frequencies). Inprinciple this makes the whole spectrum of bat soundsaudible, and it is simple to save by using a relativelyinexpensive recorder. For the best results, one has tolearn how to choose the right moment to trigger the sys-tem; thereby saving the best signals and avoiding over-

HETERODYNE AND TIME-EXPANSION METHODSFOR IDENTIFICATION OF BATS IN THE FIELD

AND THROUGH SOUND ANALYSIS

INGEMAR AHLÉN

Department of Conservation Biology, SLU, Box 7002, SE-750 07 Uppsala, Sweden

In Europe, ultrasound detectors are used to conduct various types of fieldwork on bats, including ecologicalresearch, area surveys, and monitoring of populations. The heterodyne system has been used extensively duringthe last 25 years and is still the most common. To enable the recording of information about frequencies, the fre-quency-division system was commonly used in Europe, singly or in combination with heterodyne. In 1985, timeexpansion became available, and this system is now widely used in combination with the heterodyne system foridentifying bat species in the field. In this paper, I assess the utility and limitations of the heterodyne and time-expansion systems using examples from work on the European bat fauna. The advantage of the two systems incombination is improved detection of bats, instant identification of species, and the ability to subsequently ana-lyze recordings. Further, I illustrate the importance of sampling species-specific sequences and being aware of vari-ous limitations and pitfalls. Even the most skilled observers need to accept that it is not always possible to identifyspecies. Separating similar species often requires long periods of observation during which bats can be heard (andseen) hunting or performing characteristic behaviors. Therefore, in many studies, some species must be pooledinto groups, e.g., using line transects when there is limited time for each observation.

Key words: bat detectors, Chiroptera, European bat species, field identification, frequency division, heterodyne, monitoring,surveys, time expansion, ultrasoundCorrespondent:Ingemar.Ahlen@nvb.slu.se

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load. All information on frequencies and relative ampli-tude is preserved, as well as the shape and other featuresof the single sound pulses. This is an excellent system forrecording short samples of sounds to be analyzed after-w a rds. This advantage was recognized immediately

when the system became available. However, even towell-trained observers, the value of using time expansionfor species identification in the field has only been slow-ly recognized.

SO N A R CH A R A C T E R I S T I C S O F EU R O P E A N B AT S

The 35 bat species found in Europe use many differ-ent types of vocalizations for sonar and social communi-cation. As far as we know, no two species use identicalvocalizations, but species can be grouped according tothe general features of sound. One way to group them isto use the sonar components that are most useful forspecies identification, namely CF (constant frequency),FM (frequency modulation), and QCF (quasi constantfrequency, quasi = L. as if, almost; Table 1).

The grouping perhaps represents an oversimplifica-tion, because members of all three groups use FM sweepsand even true-CF bats occur in the third group. Thenames represent the most common components used fororientation. Social calls are variable in structure and aremuch more complicated to describe or classify, eventhough they are of great use for identifying species. Figs.1-6 provide examples of sonar sounds produced bymembers of the three groups.

Section 3: Ultrasound Species Identification

Groups Genera No. ofspecies

CF Rhinolophus 5

FM Myotis 10

Plecotus 4

QCF Nyctalus 4

Eptesicus 3

Vespertilio 1

Pipistrellus 5

Tadarida 1

Miniopterus 1

Barbastella 1

Table 1:Number ofspecies inEurope belong-ing to thesonar groupsCF, FM andQCF.

Figure 1: Heterodyne representationof CF sonar call from Rhinolophusferrumequinum. Upper diagram A isan oscillogram, lower diagram B is asound spectrogram, Note thatfrequency varies due to Dopplershifts when the bat is flying.

Figure 2: Time-expansion repre-sentation of CF sonar call from Rhi-nolophus ferrumequinum. Upperdiagram A is an oscillogram, lowerdiagram B is a sound spectrogram(sonagram).

Figure 3: Heterodyne representa-tion of FM sonar from Myotismystacinus (A = oscillogram, B =sound spectrogram).

Figure 4: Time-expansion represen-tation of FM sonar from Myotis

mystacinus (A = oscillogram, B =sound spectrogram).

Figure 5: Heterodyne representa-ton of QCF sonar from Nyctalus

lasiopterus (A = oscillogram, B =sound spectrogram).

Figure 6: Time-expansion repre-sentaton of QCF sonar from Nyc-

talus lasiopterus (A = oscillogram,B = sound spectrogram).

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QU A N T I F Y I N G SO U N D FE AT U R E S

To quantify characteristics of sounds heard directlythrough detectors or from recordings, it is necessary tomake measurements. The following remarks are impor-tant in the context of taking measurements to identifyspecies.

With a heterodyne detector, one can only turn aknob and read a scale or display to assess frequency. Thevalues are not saved. This means that it is difficult tocheck afterwards if the tuning was correctly made. Also,some very common bat sounds with near-CF endings(QCF-type), may have a broad band of frequencies (5kHz or more) where the heterodyned signal soundsexactly the same. Indeed, some observers who use het-erodyne argue about bats being 1 or 2 kHz too low orhigh! Added to this uncertainty is the Doppler effectthat may change the frequency by 1 or 2 kHz.

With a time-expansion system, the CF and near-CF-frequencies can be heard and perceived immediatelyafter recording. Workers with absolute pitch abilities candifferentiate frequencies within a few kHz, that is, withbetter precision than with heterodyne tuning. With asound-analysis program, the sounds can be inspectedand measured. Even with the best recordings and dia-grams, however, there are some uncertainties that mustbe kept in mind when characterizing species and makingcomparisons.

Some uncertainties are due to changes in sound thatoccur as calls travel from the bat to the detector, orchanges produced by the instruments themselves. Pulselength or maximum frequency is often variable becausethe first low-intensity part of the pulse can easily be lostin the recording. These measurements are seldom ofdiagnostic value. The frequency at maximum amplitude,the power spectrum peak (whole or part of pulse), fre-quency at the QCF-ending, and the so-called best-lis-tening frequency (using heterodyne) are examples ofrepeatable measurements. Biologically, the most signifi-cant frequency in such pulses is perhaps the part thatcreates the most powerful echoes, which are easily seenin some sonagrams. This frequency is usually the laststrong part of the QCF-ending and typically corre-sponds to the best-listening frequency in heterodyne

tuning where the sound is most drop-like. This frequen-cy typically coincides with the frequency at maximumamplitude (Fig. 7). The power spectrum peaks lookexact, but this can be misleading because both amplitudeand duration create the spectrum.

For obvious reasons, the different means to measurepulse features often cause confusion when the methodsare not specified. It is, therefore, absolutely necessary todefine how measurements are taken before meaningfulcomparisons can be made.

When following a flying bat using a heterodynedetector, considerable data on pulse repetition can becollected. Bats flying straight in free space tend to use apulse repetition rate correlated with the respiratorycycle or wing beat frequency, which in turn is related tosize and flight speed. However, when bats make maneu-vers or circles, e.g., when they fly in confined spaces,such as indoors or between branches, the pulse repeti-tion rate varies with no clear regularity to intervallengths. Analyzing interval lengths from straight flightusually shows one or more distinct peaks if the numberof intervals is plotted against interval length. If there ismore than one peak, this can be explained by a basic ratemixed with longer intervals where pulses have beenskipped. This mixture of rates forms a rhythm that canbe very specific and can be used as a species “finger-print.”

ID E N T I F I C AT I O N WI T H I N T H E CF GR O U P

There are five Rhinolophus species (Fig. 8); three ofthem, R. ferrumequinum, R. blasii, and R. euryale, are easilyseparated based on frequency alone as they have almostno overlap (Heller and von Helversen 1989; Ahlén1990). This is easily determined using a heterodynedetector in the field, but time-expansion recordings areuseful for verification and self-testing. R. mehelyi and R.hipposideros overlap in frequency but differ in pulse length(Ahlén 1988, 1990), which can be perceived with het-erodyne by experienced observers. This can be con-firmed by analyzing time-expanded sounds. In addition,these species differ in size and behavior (Heller and vonHelversen 1989), therefore using a light or night-visiondevice is recommended. R. euryale and R. mehelyi overlapin frequencies in different areas of Italy (Russo and Jones2001). The overlap is mainly between juvenile R. mehelyi

Bat Echolocation Research: tools, techniques & analysis

Rhinolophus spp

R. ferrumequinumR. blasiiR. euryale

R. mehelyiR. hipposideros

Figure 7: Two single pulses of the same pulse train from a passing E ptesicus bot ta e.The diffe rence illustrates pulse-to-pulse va riation, with the dominant ech o - p ro d u c-ing fre quency being constant (A, C = oscillograms, B, D = sound spectro gra m s ) .

Figure 8: TheCF sonargroup andcriteria usedto identifyspecies.

Frequency

Rhythm +Size & behavior

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and R. euryale of all ages. Many rhinolophid bats emitlower frequencies as juveniles than as adults (e.g., Joneset al. 1992; Jones and Ransome 1993), and these age-related (and sex-related; Jones et al. 1992) effects shouldbe considered when attempting to identify rhinolophidbats by the frequency of their echolocation calls.

ID E N T I F I C AT I O N WI T H I N T H E FM G R O U P

This group includes 10 Myotis and 4 Plecotus species(Fig. 9), which offer the most difficult identificationproblems in the European bat fauna. In most cases fre-quency can be used to separate them into groups. M.myotis, M. blythii, and M. dasycneme as a group have a fre-quency at maximum amplitude of about 35 kHz. Theremaining Myotis species form a group with peak fre-quencies of about 45 kHz. However, M. nattereri some-times has higher frequencies and the Plecotus species usu-ally employ even higher peak frequencies (about 55kHz). To separate them, behavior and rhythm and pulseshapes must be used. Three bats usually hunt over watersurfaces – M. dasycneme, M. daubentonii, and M. capaccinii.

M. dasycneme, apart from its lower frequency, can be rec-ognized by a curved middle part to the sweep, some-times extending to a long, almost-CF part. This is easilyheard in heterodyne as drop-like sounds at about 35kHz, but should be confirmed using time expansionrecordings. The other Myotis species are almost impossi-ble to identify, at least during normal field observationsituations and time expansion and sound analysis are oflimited help. I suggest that observers become familiarwith behaviors that are specific to all of these species butonly exhibited in special situations, such as hunting innatural habitats. This requires considerable experienceand skill, combined with extensive periods of time to fol-low, listen, and watch bats hunting. When working witha species, the observer gradually becomes familiar withthe relationship between behaviors and sounds. Thebat’s sounds indicate what it is doing. Perception andrhythm memory can provide a ‘fingerprint’ image of aspecies. It is possible to use these subtle differences toseparate some difficult cryptic species, such as Myotisbrandtii and M. mystacinus. The Plecotus species are beingre-evaluated with regard to taxonomy and distribution.However, there are clear differences in behavior andpulse shape that can be used, at least to separate P. auri-tus and P. austriacus.

In summary, most species in the FM group can beidentified, but in surveys and monitoring where eachobservation is of short duration, many of these must belumped into groups.

ID E N T I F I C AT I O N WI T H I N T H E QCF G R O U P

Seven genera represented by a total of 16 speciesoccur in the QFC group (Fig. 10). They can all be iden-tified, although there are some problems and pitfalls tobe aware of. Two species are special and, in principal,

Section 3: Ultrasound Species Identification

Figure 9: TheFM sonar groupand criteria used to identifyspecies (orgroups ofspecies).

Figure 10:The QCFsonar groupand criteriaused toidentifyspecies.

Figure 11: H et-e rodyne re p re-s e n tation ofB a r b a s tella bar-b a s te l l u s s o n a r.In the re g u l a r l ya l t e rn a t i n gr hythm, the sec-ond weak pulseis difficult buts o m etimes pos-sible to det e c tusing a het e ro-dyne det e c to r(see zoomedp o rt i o n ) .

Figure 12: T i m e -expansion re p re-s e n tation of B a r-b a s tella barbaste l-lus s o n a r. The re g-ularly altern a t i n gr hythm with a sec-ond weak pulse iseasily heard usingtime expansion.

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easy to identify, namely Tadaridateniotis and Barbastella barbastellus.Tadarida has an intense call anduses frequencies much lowerthan other species. B a r b a s t e l l abarbastellus is difficult to detectwith heterodyne and probablyimpossible with a fre q u e n c ydivision detector. The alternat-ing pulses are more regular thanin any other bat and often used during the search phasein feeding habitats (Ahlén 1981). The two pulses consistof one strong and compact pulse with peak frequency atabout 33 kHz and a weak pulse that has most energy atabout 44 kHz, with similar pulse intervals between pulsetypes. Time expansion clearly reveals this, making thecalls unmistakable. With heterodyne, the sonar consistsof dry clicks, but at close range a rattling or frizzlingnoise is produced by the second pulse type. At longerranges, this cannot be perceived. When analyzing these“rattling” portions of a heterodyne recording using anoscillogram, it is possible to see the second pulse thatfollows the strong pulse. Experience suggests that Bar-bastella is difficult to identify without this knowledge, butafter training, field workers quickly become skilled atfinding this rare bat. I feel it is necessary to use a combi-nation of heterodyne and time expansion to detect thisspecies (Figs. 11 and 12).

The three genera Nyctalus, Vespertilio, and Eptesicus,with 8 species altogether, are easy to separate providedthey are performing typical flight in free space (Ahlén1981, 1990; Ahlén and Baagøe 1999). However, whenthey leave their roosts, fly among dense trees, or huntinsects around street lamps, they are difficult if notimpossible to identify. This is because they vary the callrepetition rate and do not call with the pulse types andrhythm that is typical and species-specific in free space(large openings or above the canopy). The same effecton vocalizations occurs when bats are released afterbeing captured or when kept captive indoors.

To secure re c o rdings that allow identification byinstant observation or analysis, it is important to selectsituations when bats emit species-specific sounds andavoid situations and locations where the behavior and

sound characteristics vary toomuch.

To identify Nyctalus species,the alternating pulses can beused even if they are more orless pronounced in the differentspecies and in different situa-tions. Frequencies and shapes ofthe shallowest QCF pulses arethe best features to listen for oranalyze. The rhythm differs be-tween larger and smaller species.

Ve s p e rt i l i o and E p t e s i c u s do notuse regularly alternating pulses.E p t e s i c u s species can be separatedusing the frequency of the end-ing QCF part which does notv a ry much. Ve s p e rt i l i o uses morevariable frequencies, all ofwhich are possible to identify iff requency reading or measure sa re combined with data onrhythm. Peaks in pulse rh y t h mdiagrams compiled from straight

flight in open air are species specific (Figs. 13, 14). Puls-es are best analyzed from time expansion re c o rd i n g swhile rhythm data are better measured from long het-e rodyne re c o rd i n g s .

Pipistrellus species can all be identified but there areoverlapping features such as terminal or QCF frequencyand rhythm (Ahlén and Baagøe 2001). In the case ofoverlapping frequencies, e.g., P. pipistrellus and P. nathusii,a difference in pulse rhythm is the key to identification.Whereas the basic rhythm is only slightly slower in thelarger species, P. nathusii, this bat commonly uses longerintervals when hunting insects in open spaces of the for-est (Figs. 15, 16). Miniopterus uses calls similar to Pipistrel-lus pygmaeus but can be separated on the basis of rhythm,which is a function of the bat’s behavior. Confusion mayoccur among observers, and experience is required.

IM P O RTA N C E O F S O C I A L C A L L S

In addition to their sonar characteristics, it is also pos-sible to identify bats by their social calls. The advantageto using sonar is that for flying European bats it is alwayson. In contrast, social calls are more sporadic in occur-rence. Some species emit social calls or territorial songsregularly and thereby advertise their identity. A goodexample is Ve s p e rtilio murinus, where males perf o rm a terr i-torial flight while repeating a complicated song, fourtimes per second, when they fly near high buildings oralongside steep mountains (Ahlén 1981; Ahlén andBaagøe 2001; Baagøe 2001). Many, but not all, social callsa re specific enough to be useful for identification (Figs.17-20). Species identification of P i p i s t re l l u s species can beachieved using social calls (Ahlén 1981, 1990; Ahlén andBaagøe 1999; Jones et al. 2000; Russo and Jones 1999).

Bat Echolocation Research: tools, techniques & analysis

Figure 13: Single pulses of Eptesicus seroti-nus (A), E. nilssonii (B), and Vespertiliomurinus (C) represented as sound spectro-grams.

Figure 14: Pulse rhythm diagrams forEptesicus serotinus (A), E. nilssonii (B),

and Vespertilio murinus (C).

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CO N C L U S I O N S A B O U T HE T E R O D Y N E A N DTI M E- EX PA N S I O N SY S T E M S F O R ID E N T I F I C AT I O N

A heterodyne and time-expansion system is an excel-lent combination for field situations that require speciesidentification. Heterodyne is a sensitive system suitablefor searching for bats and allows for long-distance detec-tion. The transformed signals provide information aboutthe sounds for immediate perception but not for analy-sis. Tuned frequencies cannot be assessed exactly norcan they be saved. Heterodyne systems are useful forsampling and analyzing data on rhythm. To record andsave high-quality unchanged sound segments, time-expansion systems are best. They allow both immediateidentification in the field and the ability to perform sub-sequent analysis of recordings. The use of time expan-sion has enabled identification far beyond heterodynealone and provides the best combination with hetero-dyne (Fig. 21). Time expansion cannot be used in realtime, and another limitation is that using longer memo-ry can block the recording of new signals during play-

back. Listening and recording with both systems in com-bination involves the use of both ears and stereo chan-nels on the recorder (e.g., left for heterodyne and rightfor time expansion).

CO N C L U D I N G RE M A R K S

The beginner needs to make many recordings andanalyze sounds as part of the training process. Withincreasing experience and skill, the need to make record-ings is reduced to situations when identification must beverified. This is either to test oneself or to produce directand verifiable evidence of observations.

Section 3: Ultrasound Species Identification

Figure 16: Pulserhythm diagramsof hunting Pip-istrellus nathusii(A) and P. pip-strellus (B).

Figure 15: S i n gle pulses of P i p i s t rellus nathusii (A), P. p i p s t re l l u s (B) and P. pyg m a e u s (C) re p resented assound spectro gra m s .

Figure 17:Territorial callof Pipistrellusnathusii.Three sonarpulses atabout 43 kHzin the spectro-gram are froma secondindividual.

Figure 18: Social calls inserted bet ween sonar calls of E pte s i c u snilssonii.

Figure 20: Territorial song of Vespertilio murinus.

Figure 19:Social call ofNyctalusazoreum.

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An interesting phenomenon is the fact that experi-enced people use criteria for identifying some speciesdifferently from the ones they teach their students. Thereason is that teaching must show what is possible tom e a s u re and what differs significantly between thespecies. With experience, the observer becomes familiarwith other “fingerprints” of a species, such as rhythm ortonal qualities, that are easily heard but more difficult toquantify or pinpoint. Still, it is possible to recognizemany species immediately, in a manner analogous to thesubconscious manner in which our brains enable voicerecognition on the telephone.

With experience teaching the art of identifying batsunder natural conditions, I have found substantial indi-vidual variation in learning ability (Fig. 22). While thismay be due to variation in training or the dedication ofstudents; innate ability and disposition are also impor-tant. The perception of subtle sound differences is asophisticated activity that requires practice and skill.When identification of bats using ultrasound detectorsstarted, some scientists argued that the method was notreliable. Most now dismiss this idea, but there are stilldifferent views on the usefulness of ultrasound detectors(Barclay 1999, O’Farrell et al. 1999).

Learning how to identify bats by their calls is difficultand requires more practice than to identify birds fromsong. Especially when beginning, it is important to workwith experienced colleagues. One way to increase skill isto work in a limited area with a few known species.When familiar with those species, their sonar types andbehaviors in various situations, then the study area canbe expanded to where additional species occur.

Bat detector courses or workshops which combine amixture of theory and practical training in the field willimprove skills rapidly. However, continual practice andtraining are usually needed to maintain skills and pro-mote self-development.

A FI N A L WO R D

Most European bat species can be identified acousti-cally using a combination of heterodyne and time-expansion detectors (Ahlén and Baagøe 1999). Thismethod is efficient and reliable provided that the fol-lowing three considerations are respected:

(1) Use the best available equipment with the high-est sound quality.

(2) Sample species-specific sequences for most reli-able identification.

(3) A well-developed sound memory and musical earare prerequisites for skillful observations.

Some difficult cases, especially among the Myotisspecies, require long and careful studies until character-istic ‘fingerprints’ of sounds or behavior are learned.Such species must be grouped during surveys and moni-toring.

AC K N O W L E D G M E N T S

I thank H. J. Baagøe, L. Pettersson, and J. de Jong forvaluable suggestions to an earlier version of this paper. Iam also grateful for a number of improvements suggest-ed by G. Jones, H. Limpens, and M. Brigham whenreviewing the manuscript.

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Bat Echolocation Research: tools, techniques & analysis

Figure 22: Individual variation inlearning ability.

Figure 21: H et e rodyne (A) and time expansion (B) of E ptesicus nilssoniis h owing how a time segment containing a buzz is tri g ge red and re p l aye d.

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O´FARRELL, C., W. L. GANNON, and B. MILLER. 1999. Con-fronting the dogma: a reply. Journal of Mammalogy80: 297-302.

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RUSSO, D., and G. JONES. 2001. Influence of age, sex and bodysize on echolocation calls of Mediterranean andMehely’s horseshoe bats, Rhinolophus euryale and R.m e h e l y i ( C h i roptera: Rhinolophidae). Mammalia65:429-436.

WEID, R. 1988. Bestimmungshilfe für das Erkennen europäis-cher Fledermäuse - insbesondere anhand derOrtungsrufe. Schriftenreihe Bayerisches Landesamtfür Umweltschutz 81:63-72.

WE I D, R., and O. V O N HE LV E R S E N. 1987. Ort u n g s ru f eEuropäischer Fledermäuse beim Jagdflug im Freiland.Myotis 25:5-27.

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Section 3: Ultrasound Species Identification

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Brigham, R. M., et al., eds. 2004. Bat EcholocationResearch: tools, techniques and analysis. Bat Conser-

vation International. Austin, Texas

Bat Echolocation Researc htools, techniques and analysis

Information on obtaining copies of this report (depending on supply) may be obtained from:Bat Conservation International

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© 2004 Bat Conservation International

Bat Echolocation Research: tools, techniques & analysis 82

CO N T R I B U T I N G AU T H O R S v

DE D I C AT I O N viIN T R O D U C T I O N vii

R. Mark Brigham

BAT DE T E C T O R LI M I TAT I O N S A N D CA PA B I L I T I E SApplications for bat re s e a rc h

Bat Natural History and Echolocation 2M. Brock Fenton

The Past and Future History of Bat Detectors 6Donald R. Griffin

The Properties of Sound and Bat Detectors 9Lars Pettersson

Foraging Habits of North American Bats 13Thomas H. Kunz

AC O U S T I C IN V E N T O R I E SUltrasound Detection: Basic Concepts

Choosing a Bat Detector: Theoretical and Practical Aspects 28Herman J. G. A. Limpens and Gary F. McCracken

Are Acoustic Detectors a ‘Silver Bullet’ for Assessing Habitat Use by Bats? 38William L. Gannon and Richard E. Sherwin

Field Identification: Using Bat Detectors to Identify Species 46Herman J. G. A. Limpens

Acoustic Surveys And Non-Phyllostomid Neotropical Bats:How Effective Are They? 58Bruce W. Miller

Neotropical Leaf-Nosed Bats (Phyllostomidae):“Whispering” Bats as Candidates For Acoustic Surveys? 63Elisabeth K. V. Kalko

ULT R A S O U N D SP E C I E S ID E N T I F I C AT I O NField and Laboratory Applications

Heterodyne and Time-Expansion Methods for Identification of Bats in the Field and through Sound Analysis 72Ingemar Ahlén

Designing Monitoring Programs Using Frequency-Division Bat Detectors: Active Versus Passive Sampling 79Eric R. Britzke

Bat Echolocation Research: tools, techniques & analysis

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