Automated echolocation classifiers vary in accuracy for northeastern U.S. bat species
Acoustic surveys of bat echolocation calls are an important management tool for determining presence and probable absence of threatened and endangered bat species. In the northeastern United States, software programs such as Bat Call Identification (BCID), Kaleidoscope Pro (KPro), and Sonobat can au...
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Published in | PloS one Vol. 19; no. 6; p. e0300664 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
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United States
Public Library of Science
03.06.2024
Public Library of Science (PLoS) |
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Abstract | Acoustic surveys of bat echolocation calls are an important management tool for determining presence and probable absence of threatened and endangered bat species. In the northeastern United States, software programs such as Bat Call Identification (BCID), Kaleidoscope Pro (KPro), and Sonobat can automatically classify ultrasonic detector sound files, yet the programs' accuracy in correctly classifying calls to species has not been independently assessed. We used 1,500 full-spectrum reference calls with known identities for nine northeastern United States bat species to test the accuracy of these programs using calculations of Positive Predictive Value (PPV), Negative Predictive Value (NPV), Sensitivity (SN), Specificity (SP), Overall Accuracy, and No Information Rate. We found that BCID performed less accurately than other programs, likely because it only operates on zero-crossing data and may be less accurate for recordings converted from full-spectrum to zero-crossing. NPV and SP values were high across all species categories for SonoBat and KPro, indicating these programs' success at avoiding false positives. However, PPV and SN values were relatively low, particularly for individual Myotis species, indicating these programs are prone to false negatives. SonoBat and KPro performed better when distinguishing Myotis species from non-Myotis species. We expect less accuracy from these programs for acoustic recordings collected under normal working conditions, and caution that a bat acoustic expert should verify automatically classified files when making species-specific regulatory or conservation decisions. |
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AbstractList | Acoustic surveys of bat echolocation calls are an important management tool for determining presence and probable absence of threatened and endangered bat species. In the northeastern United States, software programs such as Bat Call Identification (BCID), Kaleidoscope Pro (KPro), and Sonobat can automatically classify ultrasonic detector sound files, yet the programs' accuracy in correctly classifying calls to species has not been independently assessed. We used 1,500 full-spectrum reference calls with known identities for nine northeastern United States bat species to test the accuracy of these programs using calculations of Positive Predictive Value (PPV), Negative Predictive Value (NPV), Sensitivity (SN), Specificity (SP), Overall Accuracy, and No Information Rate. We found that BCID performed less accurately than other programs, likely because it only operates on zero-crossing data and may be less accurate for recordings converted from full-spectrum to zero-crossing. NPV and SP values were high across all species categories for SonoBat and KPro, indicating these programs' success at avoiding false positives. However, PPV and SN values were relatively low, particularly for individual Myotis species, indicating these programs are prone to false negatives. SonoBat and KPro performed better when distinguishing Myotis species from non-Myotis species. We expect less accuracy from these programs for acoustic recordings collected under normal working conditions, and caution that a bat acoustic expert should verify automatically classified files when making species-specific regulatory or conservation decisions. Acoustic surveys of bat echolocation calls are an important management tool for determining presence and probable absence of threatened and endangered bat species. In the northeastern United States, software programs such as Bat Call Identification (BCID), Kaleidoscope Pro (KPro), and Sonobat can automatically classify ultrasonic detector sound files, yet the programs’ accuracy in correctly classifying calls to species has not been independently assessed. We used 1,500 full-spectrum reference calls with known identities for nine northeastern United States bat species to test the accuracy of these programs using calculations of Positive Predictive Value (PPV), Negative Predictive Value (NPV), Sensitivity (SN), Specificity (SP), Overall Accuracy, and No Information Rate. We found that BCID performed less accurately than other programs, likely because it only operates on zero-crossing data and may be less accurate for recordings converted from full-spectrum to zero-crossing. NPV and SP values were high across all species categories for SonoBat and KPro, indicating these programs’ success at avoiding false positives. However, PPV and SN values were relatively low, particularly for individual Myotis species, indicating these programs are prone to false negatives. SonoBat and KPro performed better when distinguishing Myotis species from non- Myotis species. We expect less accuracy from these programs for acoustic recordings collected under normal working conditions, and caution that a bat acoustic expert should verify automatically classified files when making species-specific regulatory or conservation decisions. |
Audience | Academic |
Author | Solick, Donald I Chenger, John Newman, Christian M Hopp, Bradley H |
AuthorAffiliation | 1 Electric Power Research Institute, Palo Alto, California, United States of America Bowling Green State University, UNITED STATES 2 Vesper Bat Detection Services, Fort Collins, Colorado, United States of America 3 Bat Conservation and Management, Carlisle, Pennsylvania, United States of America |
AuthorAffiliation_xml | – name: Bowling Green State University, UNITED STATES – name: 1 Electric Power Research Institute, Palo Alto, California, United States of America – name: 2 Vesper Bat Detection Services, Fort Collins, Colorado, United States of America – name: 3 Bat Conservation and Management, Carlisle, Pennsylvania, United States of America |
Author_xml | – sequence: 1 givenname: Donald I surname: Solick fullname: Solick, Donald I organization: Vesper Bat Detection Services, Fort Collins, Colorado, United States of America – sequence: 2 givenname: Bradley H orcidid: 0009-0006-7539-5133 surname: Hopp fullname: Hopp, Bradley H organization: Electric Power Research Institute, Palo Alto, California, United States of America – sequence: 3 givenname: John surname: Chenger fullname: Chenger, John organization: Bat Conservation and Management, Carlisle, Pennsylvania, United States of America – sequence: 4 givenname: Christian M surname: Newman fullname: Newman, Christian M organization: Electric Power Research Institute, Palo Alto, California, United States of America |
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Copyright | Copyright: © 2024 Solick et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. COPYRIGHT 2024 Public Library of Science 2024 Solick et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. 2024 Solick et al 2024 Solick et al |
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SubjectTerms | Accuracy Acoustic properties Acoustics Agreements Animals Automation Bats Biology and Life Sciences Chiroptera - classification Chiroptera - physiology Classification Computer and Information Sciences Datasets Echolocation Echolocation - physiology Ecology and Environmental Sciences Endangered & extinct species Endangered species Engineering and Technology Management decisions Myotis New England Physical Sciences Population decline Research and Analysis Methods Sensors Social Sciences Software Species Specificity Threatened species Ultrasonic testing Vocalization, Animal - physiology Wildlife conservation Wind power Working conditions |
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Title | Automated echolocation classifiers vary in accuracy for northeastern U.S. bat species |
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