title: Characterization of the diversity in bat biosonar beampatterns with spherical harmonics power spectra.
abstract: The biosonar beampatterns found across different bat species are highly diverse in terms of global and local shape properties such as overall beamwidth or the presence, location, and shape of multiple lobes. It may be hypothesized that some of this variability reflects evolutionary adaptation. To investigate this hypothesis, the present work has searched for patterns in the variability across a set of 283 numerical predictions of emission and reception beampatterns from 88 bat species belonging to four major families (Rhinolophidae, Hipposideridae, Phyllostomidae, Vespertilionidae). This was done using a lossy compression of the beampatterns that utilized real spherical harmonics as basis functions. The resulting vector representations showed differences between the families as well as between emission and reception. These differences existed in the means of the power spectra as well as in their distribution. The distributions were characterized in a low dimensional space found through principal component analysis. The distinctiveness of the beampatterns across the groups was corroborated by pairwise classification experiments that yielded correct classification rates between ~85 and ~98%. Beamwidth was a major factor but not the sole distinguishing feature in these classification experiments. These differences could be seen as an indication of adaptive trends at the beampattern level.
authors.affiliation: Department of Mechanical Engineering, Virginia Tech, Blacksburg, Virginia 24061.
authors.forename: Mohammad
authors.initials: M
authors.lastname: Motamedi
authors.affiliation: Department of Mechanical Engineering, Virginia Tech, Blacksburg, Virginia 24061.
authors.forename: Rolf
authors.initials: R
authors.lastname: Müller
mesh_terms: D000162:Acoustics; D000818:Animals; D002685:Chiroptera / Q000145:classification / Q000502:physiology*; D003198:Computer Simulation; D004455:Echolocation; D009038:Motion; D009716:Numerical Analysis, Computer-Assisted; D010363:Pattern Recognition, Automated; D012815:Signal Processing, Computer-Assisted; D013016:Sound; D013018:Sound Spectrography; D014828:Vocalization, Animal