Acoustic Identification of Bats in the Eastern United States: A Comparison of Parametric and Nonparametric Methods
Ultrasonic detectors are widely used to survey bats in ecological studies. To evaluate efficacy of acoustic identification, we compiled a library of search phase calls from across the eastern United States using the Anabat system. The call library included 1,846 call sequences of 12 species recorded...
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| Published in | The Journal of wildlife management Vol. 75; no. 3; pp. 660 - 667 |
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| Main Authors | , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Hoboken, USA
The Wildlife Society
01.04.2011
John Wiley & Sons, Inc Blackwell Publishing Ltd |
| Subjects | |
| Online Access | Get full text |
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| Abstract | Ultrasonic detectors are widely used to survey bats in ecological studies. To evaluate efficacy of acoustic identification, we compiled a library of search phase calls from across the eastern United States using the Anabat system. The call library included 1,846 call sequences of 12 species recorded from 14 states. We determined accuracy rates using 3 parametric and 4 nonparametric classification functions for acoustic identification. The 2 most flexible classification functions also were the most accurate: neural networks (overall classification accuracy = 0.94) and mixture discriminant analysis incorporating an adaptive regression model (overall classification accuracy = 0.93). Flexible nonparametric methods offer substantial benefits when discriminating among closely related species and may preclude the need to group species with similar calls. We demonstrate that quantitative methods provide an effective technique to acoustically identify bats in the eastern United States with known accuracy rates. |
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| AbstractList | Ultrasonic detectors are widely used to survey bats in ecological studies. To evaluate efficacy of acoustic identification, we compiled a library of search phase calls from across the eastern United States using the Anabat system. The call library included 1,846 call sequences of 12 species recorded from 14 states. We determined accuracy rates using 3 parametric and 4 nonparametric classification functions for acoustic identification. The 2 most flexible classification functions also were the most accurate: neural networks (overall classification accuracy = 0.94) and mixture discriminant analysis incorporating an adaptive regression model (overall classification accuracy = 0.93). Flexible nonparametric methods offer substantial benefits when discriminating among closely related species and may preclude the need to group species with similar calls. We demonstrate that quantitative methods provide an effective technique to acoustically identify bats in the eastern United States with known accuracy rates. Abstract Ultrasonic detectors are widely used to survey bats in ecological studies. To evaluate efficacy of acoustic identification, we compiled a library of search phase calls from across the eastern United States using the Anabat system. The call library included 1,846 call sequences of 12 species recorded from 14 states. We determined accuracy rates using 3 parametric and 4 nonparametric classification functions for acoustic identification. The 2 most flexible classification functions also were the most accurate: neural networks (overall classification accuracy = 0.94) and mixture discriminant analysis incorporating an adaptive regression model (overall classification accuracy = 0.93). Flexible nonparametric methods offer substantial benefits when discriminating among closely related species and may preclude the need to group species with similar calls. We demonstrate that quantitative methods provide an effective technique to acoustically identify bats in the eastern United States with known accuracy rates. © 2011 The Wildlife Society. Ultrasonic detectors have improved conservation efforts by providing increased knowledge of bat ecology. Numerous researchers have used detectors to conduct species surveys and assess habitat use, and the method is especially valuable for species that are difficult to capture (Ahlen 1999, Murray et al. 1999, OTarrell and Gannon 1999, Duffy et al. 2000, Russo and Jones 2003). Calls can be identified qualitatively based on the researcher's experience and judgment (O'Farrell et al. 1999) or quantitatively by comparing measured attributes of previously recorded species to those of newly recorded calls (Krusic and Neefus 1996, Parsons and Jones 2000, Russo and Jones 2002, Britzke 2003, Preatoni et al. 2005). Ultrasonic detectors are widely used to survey bats in ecological studies. To evaluate efficacy of acoustic identification, we compiled a library of search phase calls from across the eastern United States using the Anabat system. The call library included 1,846 call sequences of 12 species recorded from 14 states. We determined accuracy rates using 3 parametric and 4 nonparametric classification functions for acoustic identification. The 2 most flexible classification functions also were the most accurate: neural networks (overall classification accuracy = 0.94) and mixture discriminant analysis incorporating an adaptive regression model (overall classification accuracy = 0.93). Flexible nonparametric methods offer substantial benefits when discriminating among closely related species and may preclude the need to group species with similar calls. We demonstrate that quantitative methods provide an effective technique to acoustically identify bats in the eastern United States with known accuracy rates. © 2011 The Wildlife Society. |
| Author | Swihart, Robert K. Duchamp, Joseph E. Murray, Kevin L. Britzke, Eric R. Robbins, Lynn W. |
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| Copyright | 2011 The Wildlife Society. Copyright© 2011 The Wildlife Society Copyright © The Wildlife Society, 2011 Copyright Allen Press Publishing Services 2011 |
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| Snippet | Ultrasonic detectors are widely used to survey bats in ecological studies. To evaluate efficacy of acoustic identification, we compiled a library of search... Abstract Ultrasonic detectors are widely used to survey bats in ecological studies. To evaluate efficacy of acoustic identification, we compiled a library of... Ultrasonic detectors have improved conservation efforts by providing increased knowledge of bat ecology. Numerous researchers have used detectors to conduct... |
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| SubjectTerms | Acoustic echoes acoustic identification Acoustics Anabat Animal communication Bats Biological taxonomies Classification Comparative studies Discriminant analysis discriminant function analysis echolocation Habitat conservation Habitat utilization Libraries Mammals Neural networks quantitative identification Regression analysis Species ultrasonic detectors Ultrasonics Vocalization behavior Wildlife conservation Wildlife management |
| Title | Acoustic Identification of Bats in the Eastern United States: A Comparison of Parametric and Nonparametric Methods |
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