Journal of Comparative Physiology A

, Volume 197, Issue 5, pp 515–530

Click-based echolocation in bats: not so primitive after all

Review

DOI: 10.1007/s00359-011-0639-4

Cite this article as:
Yovel, Y., Geva-Sagiv, M. & Ulanovsky, N. J Comp Physiol A (2011) 197: 515. doi:10.1007/s00359-011-0639-4

Abstract

Echolocating bats of the genus Rousettus produce click sonar signals, using their tongue (lingual echolocation). These signals are often considered rudimentary and are believed to enable only crude performance. However, the main argument supporting this belief, namely the click’s reported long duration, was recently shown to be an artifact. In fact, the sonar clicks of Rousettus bats are extremely short, ~50–100 μs, similar to dolphin vocalizations. Here, we present a comparison between the sonar systems of the ‘model species’ of laryngeal echolocation, the big brown bat (Eptesicus fuscus), and that of lingual echolocation, the Egyptian fruit bat (Rousettus aegyptiacus). We show experimentally that in tasks, such as accurate landing or detection of medium-sized objects, click-based echolocation enables performance similar to laryngeal echolocators. Further, we describe a sophisticated behavioral strategy for biosonar beam steering in clicking bats. Finally, theoretical analyses of the signal design—focusing on their autocorrelations and wideband ambiguity functions—predict that in some aspects, such as target ranging and Doppler-tolerance, click-based echolocation might outperform laryngeal echolocation. Therefore, we suggest that click-based echolocation in bats should be regarded as a viable echolocation strategy, which is in fact similar to the biosonar used by most echolocating animals, including whales and dolphins.

Keywords

BiosonarActive sensingSignal designEgyptian fruit bat (Rousettus aegyptiacus)Big brown bat (Eptesicus fuscus)

Abbreviations

FM

Frequency modulated

CF–FM

Constant frequency–frequency modulated

ACRF

Auto-correlation function

WBAF

Wideband ambiguity function

SPL

Sound pressure level

SNR

Signal-to-noise ratio

Copyright information

© Springer-Verlag 2011

Authors and Affiliations

  • Yossi Yovel
    • 1
  • Maya Geva-Sagiv
    • 1
    • 2
  • Nachum Ulanovsky
    • 1
  1. 1.Department of NeurobiologyWeizmann Institute of ScienceRehovotIsrael
  2. 2.Interdisciplinary Center for Neural ComputationThe Hebrew University of JerusalemJerusalemIsrael