Bat Echolocation Researc h - Bat Conservation International

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and efficiency of survey methods]. Nyctalus (N.F.) 8:159-178. [German, English summary] LUTZ, K., P. BOYE, and H. HAUPT. 2000. Zur Entstehungsgeschichte des AEWA [The history of the AEWA]. Schriftenreihe fuer Landschaftspflege und Naturschutz 60:7-12. [German with English abstract] MITCHELL-JONES, A. J., and A. P. MCLEISH (EDS.). 1999. The Bat Workers’ Manual, 2 nd ed. Joint Nature Conservation Committee, Peterborough, United Kingdom. MITCHELL-JONES, A. J., ET AL. 1999. The Atlas of European Mammals. Poyer Natural History, London, United Kingdom. PAOLETTI, M.G. 1999. Using bioindicators based on biodiversity to assess landscape sustainability. Agriculture, Ecosystems and Environment 74:1-18. PETERSEN, B. 2000. Welche Schutzverpflichtungen bestehen für die Arten der FFH-Richtlinie? [Which obligations for protection exist for species of the habitats directive?] Schriftenreihe fuer Landschaftspflege und Naturschutz 68:17- 30. [German with English summary] PLACHTER, H., D. BERNOTAT, R. MÜSSNER, and U. RIECKEN (EDS.). 2002. Entwicklung und Festlegung von Methodenstandards im Naturschutz [Developing methodology standards in nature conservation]. Schriftenreihe fuer Landschaftspflege und Naturschutz 70, Bundesamt fuer Naturschutz, Bonn, Germany. [German with English summary] TAYLOR, R.J., and N. DORAN. 2001. Use of terrestrial invertebrates as indicators of the ecological sustainability of forest management under the Montreal Process. Journal of Insect Conservation 5:221-231. GEOGRAPHIC VARIATION IN THE ECHOLOCATION CALLS OF BATS: A COMPLICATION FOR IDENTIFYING SPECIES BY THEIR CALLS ROBERT M. R. BARCLAY* AND R. MARK BRIGHAM *Department of Biological Sciences, University of Calgary, Calgary, AB, Canada T2N 1N4 and Department of Biology, University of Regina, Regina, SK, Canada S4S 0A2. Variation in the echolocation calls of bats in different populations of the same species (i.e. geographic variation) may complicate attempts to use echolocation to identify free-flying bats to species. Such variation occurs in several species. Variation in echolocation calls is correlated with variation in body size and is also associated with differences in habitat type on a local level. Factors such as environmental conditions (e.g., relative humidity), prey types (e.g., size and defense mechanisms), foraging behavior (e.g., gleaning versus aerial hawking), and the presence of other bats may also translate into variation at larger geographic scales. We suggest ways to account for potential call variation when using a reference library to identify bats to species. Key words: Body size, Chiroptera, foraging, habitat, prey, survey techniques *Correspondent: barclay@ucalgary.ca 144 INTRODUCTION The echolocation calls of free-flying microchiropteran bats have proven to be extremely useful for studying the ecology and behavior of these otherwise elusive animals. For decades, systems that detect echolocation calls have been used for various purposes, some of which require assigning calls to particular species or species groups. Bat detectors have been used to address both basic and applied issues, including questions about the relative abundance of different species in an area, the diversity of species and how diversity varies geographically, the ecological or morphological structure of bat communities, the presence of rare or endangered species, the use or selection of particular foraging habitats by different species, and the determination of critical habitats. There is also the potential for identifying cryptic species by their echolocation calls (e.g., Jones Bat Echolocation Research: tools, techniques & analysis
and van Parijs 1993). Early studies using bat detectors indicated that different species of bats use different echolocation calls, thus suggesting that free-flying individuals could be identified on the basis of their calls (Ahlén 1981; Fenton and Bell 1981). However, one problem in using echolocation calls to identify species of bats is that the characteristics of the calls of each species (e.g., duration, bandwidth, frequency, harmonic structure) vary. To address questions requiring species identification, researchers rely on the fact that variation in call structure is generally greater among species than within species. Within many bat communities, the calls of some species are distinctive (Fig. 1A), and even though there is variation within each species, calls can be assigned unambiguously to particular species. In most cases, however, the call characteristics of various species overlap because on average the calls of different species are very similar to one another, or because there is greater variation in the calls of each species (Fig. 1B). Assigning calls to a particular species is less certain under these circumstances. Calls that fall within the zone of overlap (Fig. 1B) may be assigned to a species with a probability less than one, with the probability increasing the closer the combination of traits is to the mean value for that species. By definition, there is error involved in making such classifications. Often, multivariate statistical techniques such as discriminant function analysis (DFA) or neural networks are used to determine the probability of assignment (e.g., Jones et al. 2000; Parsons and Jones 2000; Vaughan et al. 1997). Variation in the echolocation-call characteristics of a particular species of bat clearly increases the uncertainty of identifying calls of unknown, free-flying individuals to that species. Such variation occurs for a number of reasons, including variation within a population related to characteristics of the individual, such as age, gender, and body mass (Betts 1998; Brigham et al. 1989; Jones et al. 1992; Jones and Ransome 1993; Obrist 1995). Some Section 4: Resources, Research and Study Figure 1: Variation in two characteristics of echolocation calls within and between two species of bats. A: Variation within each species, depicted as the shaded circles, is relatively small and calls can be unambiguously assigned to one species or the other. B: The mean values for the two call variables are the same as in A, for each species, but there is greater within-species variation. This means that there is overlap among the calls of the two species. Calls with characteristics in the zone of overlap cannot be assigned to a particular species with 100% certainty. of these factors may cause variation in calls from different locations (e.g., body mass), while others will not (e.g., age and gender), unless population structure varies (e.g., Barclay 1991). The purpose of this review is to consider geographic variation, especially among populations within a species, and to make recommendations as to how to account for it when conducting studies that depend on identifying bats by their echolocation calls. By geographic variation we mean variation in the structure of echolocation calls of individuals of the same species recorded in different locations. It is a potential problem if call characteristics from one population are used to identify the calls of unknown individuals from another population (Law et al. 2002). Most studies rely on a set of calls from known individuals (a reference library) to establish the characteristics used to identify unknown bats recorded by the monitoring system. Suppose there are two species in our study area and we base species identification on the call characteristics determined from another location (Fig. 2). Suppose further that the characteristics of the calls of the two species are distinct, but call characteristics from individuals in our study populations differ from those in the reference library. Such geographic variation could result in the inability to identify some calls and misidentification of others, depending on the amount of geographic variation (Fig. 2). While geographic variation is most commonly thought of on a large scale, an analogy being the dialects of humans and birds, there is relatively little information regarding this for the echolocation calls of bats. A large part of the problem is a lack of consistency in recording techniques and equipment among studies. There are, however, considerable data regarding smaller-scale geographic variation and variation caused by other factors that may result in large-scale geographic differences. We thus examine these sorts of variation, make predictions Figure 2: Potential problems associated with geographic variation in the characteristics of the echolocation calls of two species of bats. Characteristics from the reference library for each species (shaded circles) are distinctive, but differ from the characteristics of the calls from the study populations (open circles). Because of this, some calls will be unidentifiable (they do not fall within either reference set), and others will be misidentified (they fall within the reference set of the other species). 145
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Bat Echolocation R esearc h tools,
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TABLE OF CONTENTS CO N T R I B U T
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CONTRIBUTING AUTHORS Ingemar Ahlén
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I N T R O D U C T I O N Bat Echoloc
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BAT NATURAL HISTORY AND ECHOLOCATIO
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species (Thies et al. 1998). Before
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y the African bat Cardioderma cor (
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participants in this symposium. Sin
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INTRODUCTION Bat detectors convert
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less sensitive than a heterodyne de
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14 advanced computer software made
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COMMUTING AND FORAGING BEHAVIOR Fig
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NIGHTLY ACTIVITY BASED ON CAPTURE W
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20 Recordings of echolocation calls
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22 and analyzing echolocation calls
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24 Resource partitioning in rhinolo
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Section 2 ACOUSTIC INVENTORIES ULTR
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f tuned = f bat . As an example, wi
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The chance of detection also depend
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ent species. But in the field, it i
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Section 2: Acoustic Inventories Fig
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Suchflug und Richtungskarakteristik
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Journal N Percentage of total (%) A
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ential power of data. Hayes (1997)
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For instance, we recorded a single
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KALCOUNIS, M. C., K. A. HOBSON, R.
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and McCracken (this volume) discuss
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using other methods (Fig. 4). Ident
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Figure 6: Schematic diagram of diff
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AMPLITUDE-RELATED PARAMETERS Loudne
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tereri. Hand netting on the followi
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flight in bats. Pp. 93-108 in Bat b
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difficult to understand why the aut
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Figure 5: Call sequence showing the
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function analysis and artificial ne
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species identifications. Echolocati
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tially from calls emitted in the op
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LITERATURE CITED BARCLAY, R. M. R.,
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HETERODYNE AND TIME-EXPANSION METHO
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74 QUANTIFYING SOUND FEATURES To qu
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Figure 14: Pulse rhythm diagrams fo
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A FINAL WORD Figure 21: Heterodyne
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80 INTRODUCTION Ultrasonic detector
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82 munity was uncovered when ultras
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84 INTRODUCTION Being nocturnal, ba
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A Figure 2: Surveys of bat activity
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LITERATURE CITED Figure 5A: Pipistr
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90 In order to set a foundation for
Page 97 and 98: 92 diagram, e.g., a spectrogram, fo
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Page 101 and 102: 96 detail is not helpful for specie
Page 103 and 104: tification, providing the immediate
Page 105 and 106: spectrum, which is a graph of the e
Page 107 and 108: since there is no evidence that the
Page 109 and 110: 104 Figure 5: Different modes in se
Page 111 and 112: currently the case. Even at the sim
Page 113 and 114: 108 INTRODUCTION Much of our knowle
Page 115 and 116: Figure 1: On-axis search call recor
Page 117 and 118: 112 SUMMARY To summarize, flight-ca
Page 119 and 120: 114 SIGNAL PROCESSING TECHNIQUES FO
Page 121 and 122: al a situation as possible. Ideally
Page 123 and 124: For all networks, correct identific
Page 125 and 126: ety of London 69:111-128. JONES, G.
Page 127 and 128: eveal species-specific vocal signat
Page 129 and 130: Figure 6: Comparison of Myotis cili
Page 131 and 132: ity of the two Myotis spp. calls (F
Page 133 and 134: Section 4 RESOURCES, RESEARCH, AND
Page 135 and 136: A The data extracted from the diffe
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Page 139 and 140: ple, will not show individual calls
Page 141 and 142: Figure 10: Fast Fourier transform p
Page 143 and 144: ACKNOWLEDGEMENTS I thank the organi
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Page 151 and 152: Figure 5: Variation in the echoloca
Page 153 and 154: 47:60-69. JONES, G., and R. D. RANS
Page 155 and 156: RECORDING TECHNIQUES Section 4: Res
Page 157 and 158: monly observed with such broadband
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Page 161 and 162: ences between Myotis californicus a
Page 163 and 164: intensity). Our ability to detect m
Page 165 and 166: • The detector is kept stationary
Page 167 and 168: the number of bat passes in real ti
Page 169 and 170: SHERWIN, R. E., W. L. GANNON, and S
Page 171: tion trends, while they also raise
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