Echo-intensity compensation in echolocating bats (<i>Pipistrellus abramus</i>) during flight measured by a telemetry microphone

Hiryu, Shizuko; Hagino, Tomotaka; Riquimaroux, Hiroshi; Watanabe, Yoshiaki

doi:10.1121/1.2431337

Cited by 82 publications

(79 citation statements)

References 30 publications

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“…Returning echoes also vary in amplitude as a result of varying distances to objects. Bats compensate for these changes by adapting the amplitude of the successive calls to prevent echo intensities from exceeding an optimal level (38)(39)(40). Additionally, echolocating bats that use frequency-modulated (FM) sonar pulses for echolocation shift their call frequencies upon receiving ambiguous echoes (41).…”

Section: Discussionmentioning

confidence: 99%

Ambient noise induces independent shifts in call frequency and amplitude within the Lombard effect in echolocating bats

Hage

Jiang

Berquist

et al. 2013

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

126

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The Lombard effect, an involuntary rise in call amplitude in response to masking ambient noise, represents one of the most efficient mechanisms to optimize signal-to-noise ratio. The Lombard effect occurs in birds and mammals, including humans, and is often associated with several other vocal changes, such as call frequency and duration. Most studies, however, have focused on noisedependent changes in call amplitude. It is therefore still largely unknown how the adaptive changes in call amplitude relate to associated vocal changes such as frequency shifts, how the underlying mechanisms are linked, and if auditory feedback from the changing vocal output is needed. Here, we examined the Lombard effect and the associated changes in call frequency in a highly vocal mammal, echolocating horseshoe bats. We analyzed how bandpassfiltered noise (BFN; bandwidth 20 kHz) affected their echolocation behavior when BFN was centered on different frequencies within their hearing range. Call amplitudes increased only when BFN was centered on the dominant frequency component of the bats' calls. In contrast, call frequencies increased for all but one BFN center frequency tested. Both amplitude and frequency rises were extremely fast and occurred in the first call uttered after noise onset, suggesting that no auditory feedback was required. The different effects that varying the BFN center frequency had on amplitude and frequency rises indicate different neural circuits and/or mechanisms underlying these changes.A ny transmission of signals between sender and receiver faces the challenge of being subjected to masking by noise. For acoustic signals, for example, animals have evolved several strategies that aid in increasing the signal-to-noise ratio, thus facilitating signal transmission. One of the most efficient mechanisms is the socalled Lombard effect, i.e., the involuntary rise in call amplitude in response to masking ambient noise (1). This effect was first described in human communication a century ago (2) and has since been found in several species of birds (3-11) and various mammals (12-17), including bats (18). In human speech, several vocal changes, such as a rise in fundamental frequency (19) or lengthening in word duration (20), are often accompanied with the Lombard effect; combined, these changes are referred to as Lombard speech (21). Vocal changes associated with the Lombard effect have rarely been analyzed in animal species. So far, noisedependent changes in call frequency have been observed in birds (8,11,22), and changes in call duration in birds and monkeys (8,12).Most animal studies, however, have focused on noise-dependent changes in call amplitude and do not examine other possible vocal changes (2-5, 7, 9, 10, 15-17). It is therefore still largely unknown how the adaptive changes in call amplitude relate to frequency shifts or call elongation and how the underlying mechanisms are linked. It is also unknown if auditory feedback from the changing vocal output is needed to drive the Lombard effect in general.Over...

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Section: Discussionmentioning

confidence: 99%

Ambient noise induces independent shifts in call frequency and amplitude within the Lombard effect in echolocating bats

Hage

Jiang

Berquist

et al. 2013

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

126

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“…abramus during natural foraging emits long (9-11 ms) shallowsweeping frequency-modulated (FM) sounds, with energy concentrated in the terminal sweep frequency of the fundamental component around 40 kHz (15,25). The bat decreases the pulse duration and interpulse interval (IPI) while approaching target prey (16,30) and slightly extends the constant-frequency (CF) portion of the pulse just before approaching a prey item (16).…”

Section: Methodsmentioning

confidence: 99%

“…A parameter set was defined as a success when the bat closed to capture prey 1 and then prey 2 in sequence. The distance at which the bat was considered to capture prey was within 10 cm from the bat, which corresponds to the wing length of P. abramus (25), without losing the location of the immediate target (inside the bat's sonar beam). A simulation trial was considered a failure when prey 1 located outside the sonar beam before capture, or when prey 2 located outside the sonar beam after the capture of prey 1.…”

Section: Methodsmentioning

confidence: 99%

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Echolocating bats use future-target information for optimal foraging

Fujioka

Aihara

Sumiya

et al. 2016

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

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When seeing or listening to an object, we aim our attention toward it. While capturing prey, many animal species focus their visual or acoustic attention toward the prey. However, for multiple prey items, the direction and timing of attention for effective foraging remain unknown. In this study, we adopted both experimental and mathematical methodology with microphone-array measurements and mathematical modeling analysis to quantify the attention of echolocating bats that were repeatedly capturing airborne insects in the field. Here we show that bats select rational flight paths to consecutively capture multiple prey items. Microphone-array measurements showed that bats direct their sonar attention not only to the immediate prey but also to the next prey. In addition, we found that a bat's attention in terms of its flight also aims toward the next prey even when approaching the immediate prey. Numerical simulations revealed a possibility that bats shift their flight attention to control suitable flight paths for consecutive capture. When a bat only aims its flight attention toward its immediate prey, it rarely succeeds in capturing the next prey. These findings indicate that bats gain increased benefit by distributing their attention among multiple targets and planning the future flight path based on additional information of the next prey. These experimental and mathematical studies allowed us to observe the process of decision making by bats during their natural flight dynamics.bat sonar | aerial capture | microphone array | mathematical modeling | flight dynamics S electively focusing attention on a particular target allows us to effectively extract information (1-4). Animals spatially focus their attention toward prey for suitable foraging (5, 6). During prey pursuit, most animals direct their visual attention toward it [e.g., tiger beetle (7), dragonfly (8), and falcon (9)]. Specifically, for example, dragonflies maintain a prey item at a constant retinal position during approaching it so that they steer an interception flight path (interception strategy) (10). However, for multiple prey items, the direction and timing of attention for effective foraging remain unknown.Echolocating bats actively emit sonar signals to obtain surrounding information and adaptively change the characteristics of the emissions depending on the situation (11). Therefore, their attention in terms of the sonar (sonar attention) is characterized as the direction to which bats emit their sonar beams (12-14). When echolocating bats approach an airborne insect, the sonar attention directs toward the prey (12, 13). During natural foraging, the sonar attention of bats alternately shifts from their flying direction to the side (15). Additionally the wild bats are capable of capturing two prey items within the short interval of 1 s (16).We predicted that bats localize multiple prey items by distributing their attention between them and then select an efficient flight path to successively capture the multiple prey. To test this prediction, ...

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“…Bat buzz production generally stops at the time of prey capture or slightly before (Griffin et al, 1960; Kalko and Schnitzler, 1989;Hartley, 1992b; Kalko, 1995;Moss and Surlykke, 2001;Hiryu et al, 2007). After a buzz, bats generally pause echolocation click production for a period of several hundred milliseconds to several seconds (Griffin et al, 1960; Kalko and Schnitzler, 1989;Hartley, 1992b; Kalko, 1995;Moss and Surlykke, 2001;Hiryu et al, 2007). The mean duration of the post-buzz pause is often longer after successful captures than after unsuccessful ones (Acharya and Fenton, 1992; Britton and Jones, 1999; .…”

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confidence: 99%

Echolocation-based foraging by harbor porpoises and sperm whales, including effects of noise and acoustic propagation

DeRuiter¹

2008

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In this thesis, I provide quantitative descriptions of toothed whale echolocation and foraging behavior, including assessment of the effects of noise on foraging behavior and the potential influence of ocean acoustic propagation conditions on biosonar detection ranges and whale noise exposure. In addition to presenting some novel basic science findings, the case studies presented in this thesis have implications for future work and for management.In Chapter 2, I describe the application of a modified version of the Dtag to studies of harbor porpoise echolocation behavior. The study results indicate how porpoises vary the rate and level of their echolocation clicks during prey capture events; detail the differences in echolocation behavior between different animals and in response to differences in prey fish; and show that, unlike bats, porpoises continue their echolocation buzz after the moment of prey capture.Chapters 3-4 provide case studies that emphasize the importance of applying realistic models of ocean acoustic propagation in marine mammal studies. These chapters illustrate that, although using geometric spreading approximations to predict communication/target detection ranges or noise exposure levels is appropriate in some cases, it can result in large errors in other cases, particularly in situations where refraction in the water column or multi-path acoustic propagation are significant.Finally, in Chapter 5, I describe two methods for statistical analysis of whale behavior data, the rotation test and a semi-Markov chain model. I apply those methods to test for changes in sperm whale foraging behavior in response to airgun noise exposure. Test results indicate that, despite the low-level exposures experienced by the whales in the study, some (but not all) of them reduced their buzz production rates and altered other foraging behavior parameters in response to the airgun exposure. Sincere thanks also to the many other people who have helped with data collection and analysis over the course of my graduate work, and also to everyone who offered comments on drafts of this thesis. More detailed acknowledgments can be found at the end of each chapter, but here I would especially like to thank the following. Thesis Objectives and Chapter 1 OverviewThe goal of my thesis research has been to provide quantitative descriptions of toothed whale echolocation and foraging behavior (Chapters 2 and 5), including assessment of the effects of noise on foraging behavior (Chapter 5) and the potential influence of ocean acoustic propagation conditions on biosonar detection ranges (Chapter 3) and whale noise exposure (Chapter 4). I have focused on two study species, the harbor porpoise (Phocoena phocoena, Chapters 2-3) and the sperm whale (Physeter macrocephalus, Chapters 4-5).The following sections present background information relevant to the research presented in the rest of the thesis, beginning with a review of previous research on the use of echolocation by foraging animals. This review is followed by b...

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Echo-intensity compensation in echolocating bats (Pipistrellus abramus) during flight measured by a telemetry microphone

Cited by 82 publications

References 30 publications

Ambient noise induces independent shifts in call frequency and amplitude within the Lombard effect in echolocating bats

Ambient noise induces independent shifts in call frequency and amplitude within the Lombard effect in echolocating bats

Echolocating bats use future-target information for optimal foraging

Echolocation-based foraging by harbor porpoises and sperm whales, including effects of noise and acoustic propagation

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