Bat Echolocation Researc h - Bat Conservation International

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Figure 11A: Nightly flight activity of adult female, and B: juvenile cave myotis (Myotis velifer) captured with a two frame harp trap placed in the open doorway of a barn in south-central Kansas (after Kunz 1974). Brigham 1991; Clark et al. 1993, Fuhrmann and Seitz 1992; Gumbert et al. 2002; Jones and Morton 1992; Jones et al. 1995; Krull et al. 1991; Kunz et al. 1998). Radio transmitters that include mercury switches make it possible to determine when bats are flying or roosting. In some cases, it is possible to determine activity based on the modulated signals when bats are in flight. With access to computers, GPS units, data loggers, and specialized software, radiotelemetry can be used to infer roosting habits, home range, foraging behavior, and time budgets of individual bats. Field Observations and Recordings of Echolocation Calls Based on field observations, several investigators have classified bats into different foraging strategies (e.g., Kalko and Schnitzler 1998; Neuweiler 1989; Norberg and Rayner 1987). These foraging strategies are based on unique echolocation signals and the relative Section 1: Bat Detector Limitations and Capabilities Figure 12: Doppler radar images of Brazilian free-tailed bats (Tadarida brasiliensis) dispersing from a maternity roost in south-central Texas. The first image (A) shows the radar reflectivity shortly after the first emergence. The second and third images show the changing patterns of dispersal 15 and 30 minutes later, respectively (T.H. Kunz unpublished). amount of physical clutter present (Kalko and Schnitzler 1998). Making direct observations of flying bats in concert with recording echolocation calls is essential for a full understanding of foraging (Limpens this volume). 19
20 Recordings of echolocation calls synchronized with multi-flash, 3-dimensional photography or videography can provide valuable data on the behavior and echolocation-call structure associated with prey capture (Kalko, this volume). Multi-flash photographic sequences of aerial captures of insects by echolocating bats suggest a shift from a search mode to a target-oriented approach, immediately after bats detect potential prey (Kalko and Schnitzler 1998). Multi-flash recordings in open habitats indicate that bats often approach their prey from behind, moving into optimal positions immediately above the insect being pursued. In contrast, gleaning bats usually fly directly towards their prey, making captures by pouncing on the prey (Kalko and Schnitzler 1998). FROM ECHOLOCATION TO FORAGING Captive Studies Much of what has been learned about the foraging habits of insectivorous bats has come from laboratory studies of echolocation and prey capture. In his classic book, Listening in the Dark, Griffin (1958) eloquently summarized what had been learned from recordings of echolocation calls in the laboratory during the early period of discovery (reviewed in Griffin, this volume). In the intervening years, enormous progress has been made, especially in the development and use of bat detectors for recording echolocation calls and the refinement of specialized software for analysis (Corben, this volume; Pettersson, this volume; Szewczak, this volume). Some of the most promising research on foraging by insectivorous bats has combined studies of behavior in captivity with observations in the field (see Jones, this volume; Seimers, this volume; Kalko, this volume). Future studies on foraging habits that combine laboratory and field-based research on echolocation promise to provide revealing insights with respect to how bats actually navigate and forage in different environments. Habitat Use Based on Bat Detector Surveys One of the current applications of bat detectors is to assess the composition of local assemblages and characterize nightly activity patterns. To accomplish these goals requires reliable species identification. Unfortunately, many efforts to date have been hampered by inappropriate sample design and uncertainties about species identity (e.g., Hayes 1997; Hayes 2000). Until these uncertainties and protocols can be addressed, bat detectors for general surveys will provide little useful information with respect to how and when insectivorous bats commute and forage in different habitats. Direct Observations In some instances, it may be possible to visually Figure 13: Infrared thermal image of Brazilian free-tailed bats (Tadarida brasiliensis) foraging over an open field. Trajectories of bats are depicted by trailing wing prints (T.H. Kunz and J. Frank unpublished). observe bats as they forage in open habitats, especially near sunset and at high latitudes with extended period of twilight (e.g., Nyholm 1965; Rydell 1986). At most other times and places, however, opportunities to directly observe and record the foraging behavior of insectivorous bats requires artificial illumination (Rydell and Racey 1995). ADVANCED IMAGING TECHNOLOGIES Doppler Radar Where NEXRAD Doppler radar installations exist, this technology can be used to quantify nightly behavior of bats as they disperse and forage. For example, the Brazilian free-tailed bat (Tadarida brasiliensis) in the southwestern United States forms enormous colonies that often disperse upwards of 70 km from their daily refuges. These movements can be monitored by recording the reflectivity of the dispersing animals using NEXRAD Doppler radar (Fig. 12). These data are available from the U.S. government and some private organizations and can be downloaded for quantitative analysis of time, direction, and density of dispersing bats (J. Horn and T.H. Kunz, unpublished). This technology offers a powerful tool for quantifying the nightly dispersal and foraging activity of species that form large colonies, which is not otherwise possible. Infrared Thermal Imaging Infrared thermal-imaging cameras also offer opportunities to record the nightly emergence and feeding behavior of bats independent of natural or artificial illumination. Infrared thermal cameras are designed to detect heat emitted by objects as long as they are warmer than the background. Coupled to computers, infrared thermal images has been used successfully to census bats as emerge from roost sites (Frank et al. 2003; Sabol and Hudson 1995) and to document flight trajectories during foraging bouts (Fig. 13). Bat Echolocation Research: tools, techniques & analysis
Page 1 and 2: Bat Echolocation R esearc h tools,
Page 3 and 4: TABLE OF CONTENTS CO N T R I B U T
Page 5 and 6: CONTRIBUTING AUTHORS Ingemar Ahlén
Page 7 and 8: I N T R O D U C T I O N Bat Echoloc
Page 9 and 10: BAT NATURAL HISTORY AND ECHOLOCATIO
Page 11 and 12: species (Thies et al. 1998). Before
Page 13 and 14: y the African bat Cardioderma cor (
Page 15 and 16: participants in this symposium. Sin
Page 17 and 18: INTRODUCTION Bat detectors convert
Page 19 and 20: less sensitive than a heterodyne de
Page 21 and 22: 14 advanced computer software made
Page 23 and 24: COMMUTING AND FORAGING BEHAVIOR Fig
Page 25: NIGHTLY ACTIVITY BASED ON CAPTURE W
Page 29 and 30: 22 and analyzing echolocation calls
Page 31 and 32: 24 Resource partitioning in rhinolo
Page 33 and 34: Section 2 ACOUSTIC INVENTORIES ULTR
Page 35 and 36: f tuned = f bat . As an example, wi
Page 37 and 38: The chance of detection also depend
Page 39 and 40: ent species. But in the field, it i
Page 41 and 42: Section 2: Acoustic Inventories Fig
Page 43 and 44: Suchflug und Richtungskarakteristik
Page 45 and 46: Journal N Percentage of total (%) A
Page 47 and 48: ential power of data. Hayes (1997)
Page 49 and 50: For instance, we recorded a single
Page 51 and 52: KALCOUNIS, M. C., K. A. HOBSON, R.
Page 53 and 54: and McCracken (this volume) discuss
Page 55 and 56: using other methods (Fig. 4). Ident
Page 57 and 58: Figure 6: Schematic diagram of diff
Page 59 and 60: AMPLITUDE-RELATED PARAMETERS Loudne
Page 61 and 62: tereri. Hand netting on the followi
Page 63 and 64: flight in bats. Pp. 93-108 in Bat b
Page 65 and 66: difficult to understand why the aut
Page 67 and 68: Figure 5: Call sequence showing the
Page 69 and 70: function analysis and artificial ne
Page 71 and 72: species identifications. Echolocati
Page 73 and 74: tially from calls emitted in the op
Page 75 and 76: LITERATURE CITED BARCLAY, R. M. R.,
Page 77 and 78:
HETERODYNE AND TIME-EXPANSION METHO
Page 79 and 80:
74 QUANTIFYING SOUND FEATURES To qu
Page 81 and 82:
Figure 14: Pulse rhythm diagrams fo
Page 83 and 84:
A FINAL WORD Figure 21: Heterodyne
Page 85 and 86:
80 INTRODUCTION Ultrasonic detector
Page 87 and 88:
82 munity was uncovered when ultras
Page 89 and 90:
84 INTRODUCTION Being nocturnal, ba
Page 91 and 92:
A Figure 2: Surveys of bat activity
Page 93 and 94:
LITERATURE CITED Figure 5A: Pipistr
Page 95 and 96:
90 In order to set a foundation for
Page 97 and 98:
92 diagram, e.g., a spectrogram, fo
Page 99 and 100:
ecording time of the cassette. When
Page 101 and 102:
96 detail is not helpful for specie
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tification, providing the immediate
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spectrum, which is a graph of the e
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since there is no evidence that the
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104 Figure 5: Different modes in se
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currently the case. Even at the sim
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108 INTRODUCTION Much of our knowle
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Figure 1: On-axis search call recor
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112 SUMMARY To summarize, flight-ca
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114 SIGNAL PROCESSING TECHNIQUES FO
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al a situation as possible. Ideally
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For all networks, correct identific
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ety of London 69:111-128. JONES, G.
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eveal species-specific vocal signat
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Figure 6: Comparison of Myotis cili
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ity of the two Myotis spp. calls (F
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Section 4 RESOURCES, RESEARCH, AND
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A The data extracted from the diffe
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used. This theoretically makes it p
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ple, will not show individual calls
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Figure 10: Fast Fourier transform p
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ACKNOWLEDGEMENTS I thank the organi
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munity (now called the European Uni
Page 147 and 148:
staff to collect all of the require
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and van Parijs 1993). Early studies
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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
Page 159 and 160:
ple sonograms and power spectra can
Page 161 and 162:
ences between Myotis californicus a
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intensity). Our ability to detect m
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• 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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