The sonar beam pattern of a flying bat as it tracks tethered insects

Ghose, Kaushik; Moss, Cynthia F.

doi:10.1121/1.1589754

Cited by 151 publications

(164 citation statements)

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“…The ratio of silent to vocal times decreased as the inter-bat angle increased for a given inter-bat distance for pairs engaged in following flight, demonstrating that silent behavior is affected by the angular separation of paired bats' flight directions. Large angular separations in flight direction between bats reduce acoustic interference between individuals, as both sonar transmission and reception are directional (8)(9)(10)(11).…”

Section: Discussionmentioning

confidence: 99%

“…In addition, the sonar radiation pattern (8,9) and receiver (10,11) are directional. Thus, the angle between two bats' heading directions would also be expected to impact interference level and concomitant adjustments in sonar behavior.…”

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confidence: 99%

“…Audio recordings were acquired by 3 ultrasound sensitive microphones (UltraSound Advice) on the floor, amplified (UltraSound Advice) and stored digitally (Wavebook, IOTech), sampled at 250 kHz/channel) and a 16 microphone array positioned on 3 walls of the room (8). Video recordings were taken by 2 high-speed cameras (Kodak MotionCorder Analyzer, Model 1000, 240 frames/s) mounted in 2 corners of the room, permitting off-line 3D reconstruction of the bats' flight paths.…”

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confidence: 99%

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Flying in silence: Echolocating bats cease vocalizing to avoid sonar jamming

Chiu

Xian

Moss

2008

Proc. Natl. Acad. Sci. U.S.A.

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104

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Although it has been recognized that echolocating bats may experience jamming from the signals of conspecifics, research on this problem has focused exclusively on time-frequency adjustments in the emitted signals to minimize interference. Here, we report a surprising new strategy used by bats to avoid interference, namely silence. In a quantitative study of flight and vocal behavior of the big brown bat (Eptesicus fuscus), we discovered that the bat spends considerable time in silence when flying with conspecifics. Silent behavior, defined here as at least one bat in a pair ceasing vocalization for more than 0.2 s (200 ms), occurred as much as 76% of the time (mean of 40% across 7 pairs) when their separation was shorter than 1 m, but only 0.08% when a single bat flew alone. Spatial separation, heading direction, and similarity in call design of paired bats were related to the prevalence of this silent behavior. Our data suggest that the bat uses silence as a strategy to avoid interference from sonar vocalizations of its neighbor, while listening to conspecific-generated acoustic signals to guide orientation. Based on previous neurophysiological studies of the bat's auditory midbrain, we hypothesize that environmental sounds (including vocalizations produced by other bats) and active echolocation evoke neural activity in different populations of neurons. Our findings offer compelling evidence that the echolocating bat switches between active and passive sensing to cope with a complex acoustic environment, and these results hold broad implications for research on navigation and communication throughout the animal kingdom.echolocation ͉ jamming avoidance ͉ passive listening ͉ spatial hearing A ctive sensing enables a wide range of animal species to orient and forage under conditions where light levels are low or absent (1). Self-produced acoustic or electric signals give rise to information about the environment that is used to guide a variety of behaviors. Echolocating animals produce ultrasonic signals and determine the direction, distance, and features of objects in the environment from the arrival time, amplitude, and spectrum of sonar reflections (2). Electric fish generate discharges from an electric organ in the tail, and sense the location and features of nearby objects from amplitude and phase changes in the electric field (3).With the benefits of active sensing also come challenges, namely the potential for interference from signals produced by neighboring conspecifics. Past research has uncovered strategies by which echolocating bats and electric fish avoid jamming through active adjustments in the signals they produce to probe the environment. Wave-type weakly electric fish modify the electric organ discharge frequency, and pulse-type weakly electric fish change the timing of electric organ discharge to avoid interference from the signals of neighbors (3). In echolocating bats, spectral and/or temporal adjustments in the characteristics of sonar vocalizations, which yield acoustic separation between s...

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Section: Discussionmentioning

confidence: 99%

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confidence: 99%

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confidence: 99%

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Flying in silence: Echolocating bats cease vocalizing to avoid sonar jamming

Chiu

Xian

Moss

2008

Proc. Natl. Acad. Sci. U.S.A.

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113

104

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“…The directionality of the sonar beam restricts the spatial extent from which the bat's sonar system can gather information. The sonar beam direction of a bat, in analogy to gaze in visual animals, can be considered a component of acoustic gaze (Ghose and Moss, 2003), because it defines the region of space from which the animal's sensory system can acquire information. The sonar beam pattern of the echolocating bat enables us to measure the gaze direction of an animal, which relies on audition as its primary distal sense.…”

Section: Methodsmentioning

confidence: 99%

“…Images from two high-speed video cameras (CCD-based cameras operating at 240 frames per second, synchronized to 1/2 frame accuracy; Kodak MotionCorder; Eastman Kodak, San Diego, CA) were used to reconstruct the three-dimensional flight path of the bat and the trajectory of the prey. Simultaneously, a U-shaped array of 16 microphones (Ghose and Moss, 2003) recorded horizontal cross sections of the sonar beam pattern emitted by the bat.…”

Section: Methodsmentioning

confidence: 99%

Steering by Hearing: A Bat’s Acoustic Gaze Is Linked to Its Flight Motor Output by a Delayed, Adaptive Linear Law

Ghose

Moss²

2006

J. Neurosci.

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108

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Adaptive behaviors require sensorimotor computations that convert information represented initially in sensory coordinates to commands for action in motor coordinates. Fundamental to these computations is the relationship between the region of the environment sensed by the animal (gaze) and the animal's locomotor plan. Studies of visually guided animals have revealed an anticipatory relationship between gaze direction and the locomotor plan during target-directed locomotion. Here, we study an acoustically guided animal, an echolocating bat, and relate acoustic gaze (direction of the sonar beam) to flight planning as the bat searches for and intercepts insect prey. We show differences in the relationship between gaze and locomotion as the bat progresses through different phases of insect pursuit. We define acoustic gaze angle, gaze , to be the angle between the sonar beam axis and the bat's flight path. We show that there is a strong linear linkage between acoustic gaze angle at time t [ gaze (t)] and flight turn rate at time t ϩ into the future [ . flight (t ϩ )], which can be expressed by the formula . flight (t ϩ ) ϭ k gaze (t). The gain, k, of this linkage depends on the bat's behavioral state, which is indexed by its sonar pulse rate. For high pulse rates, associated with insect attacking behavior, k is twice as high compared with low pulse rates, associated with searching behavior. We suggest that this adjustable linkage between acoustic gaze and motor output in a flying echolocating bat simplifies the transformation of auditory information to flight motor commands.

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Estimating population density of insectivorous bats based on stationary acoustic detectors: A case study

Milchram

Suarez‐Rubio

Schröder

et al. 2020

Ecology and Evolution

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Automated recording units are commonly used by consultants to assess environmental impacts and to monitor animal populations. Although estimating population density of bats using stationary acoustic detectors is key for evaluating environmental impacts, estimating densities from call activity data is only possible through recently developed numerical methods, as the recognition of calling individuals is impossible. We tested the applicability of generalized random encounter models (gREMs) for determining population densities of three bat species (Common pipistrelle Pipistrellus pipistrellus, Northern bat Eptesicus nilssonii, and Natterer's bat Myotis nattereri) based on passively collected acoustical data. To validate the results, we compared them to (a) density estimates from the literature and to (b) Royle–Nichols (RN) models of detection/nondetection data. Our estimates for M. nattereri matched both the published data and RN‐model results. For E. nilssonii, the gREM yielded similar estimates to the RN‐models, but the published estimates were more than twice as high. This discrepancy might be because the high‐altitude flight of E. nilssonii is not accounted for in gREMs. Results of gREMs for P. pipistrellus were supported by published data but were ~10 times higher than those of RN‐models. RN‐models use detection/nondetection data, and this loss of information probably affected population estimates of very active species like P. pipistrellus. gREM models provided realistic estimates of bat population densities based on automatically recorded call activity data. However, the average flight altitude of species should be accounted for in future analyses. We suggest including flight altitude in the calculation of the detection range to assess the detection sphere more accurately and to obtain more precise density estimates.

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The sonar beam pattern of a flying bat as it tracks tethered insects

Cited by 151 publications

References 16 publications

Flying in silence: Echolocating bats cease vocalizing to avoid sonar jamming

Flying in silence: Echolocating bats cease vocalizing to avoid sonar jamming

Steering by Hearing: A Bat’s Acoustic Gaze Is Linked to Its Flight Motor Output by a Delayed, Adaptive Linear Law

Estimating population density of insectivorous bats based on stationary acoustic detectors: A case study

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