Using automated sound recording and analysis to detect bird species‐at‐risk in southwestern Ontario woodlands
ABSTRACT We conducted a field study to compare the effectiveness of acoustic recordings coupled with automated sound recognition versus traditional point counts in terms of their relative abilities to detect 3 bird species‐at‐risk in southwestern Ontario, Canada. The comparison was made in 50 woodlo...
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| Format: | Article |
| Language: | English |
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Wiley
2014-09-01
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| Series: | Wildlife Society Bulletin |
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| Online Access: | https://doi.org/10.1002/wsb.421 |
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| _version_ | 1846120329672392704 |
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| author | Stephen B. Holmes Kenneth A. McIlwrick Lisa A. Venier |
| author_facet | Stephen B. Holmes Kenneth A. McIlwrick Lisa A. Venier |
| author_sort | Stephen B. Holmes |
| collection | DOAJ |
| description | ABSTRACT We conducted a field study to compare the effectiveness of acoustic recordings coupled with automated sound recognition versus traditional point counts in terms of their relative abilities to detect 3 bird species‐at‐risk in southwestern Ontario, Canada. The comparison was made in 50 woodlots, each of which contained a standard Forest Bird Monitoring Program plot of 5 point‐count stations. An automated recording device was present at one of the point‐count stations. We found that the automated recording and analysis system worked at least as well as the more traditional point‐count method in identifying woodlots containing acadian flycatcher (Empidonax virescens) and cerulean warbler (Setophaga cerulea), but that both methods combined performed better than either method alone. The automated system also required considerably less effort in the field (a difference of 140 min/woodlot) with very little additional effort identifying vocalizations in the lab (approx. 22.5 min/woodlot, for all 3 species combined). The automated system was not as effective in detecting prothonotary warbler (Protonotaria citrea), possibly because the species is much less common in southern Ontario than the other 2 species. © 2014 The Wildlife Society. |
| format | Article |
| id | doaj-art-fabeee43e4414bf98fce9a34c18ad2e4 |
| institution | Kabale University |
| issn | 2328-5540 |
| language | English |
| publishDate | 2014-09-01 |
| publisher | Wiley |
| record_format | Article |
| series | Wildlife Society Bulletin |
| spelling | doaj-art-fabeee43e4414bf98fce9a34c18ad2e42024-12-16T12:21:07ZengWileyWildlife Society Bulletin2328-55402014-09-0138359159810.1002/wsb.421Using automated sound recording and analysis to detect bird species‐at‐risk in southwestern Ontario woodlandsStephen B. Holmes0Kenneth A. McIlwrick1Lisa A. Venier2Natural Resources CanadaCanadian Forest Service1219 Queen Street E, Sault Ste.MarieONP6A 2E5CanadaNatural Resources CanadaCanadian Forest Service1219 Queen Street E, Sault Ste.MarieONP6A 2E5CanadaNatural Resources CanadaCanadian Forest Service1219 Queen Street E, Sault Ste.MarieONP6A 2E5CanadaABSTRACT We conducted a field study to compare the effectiveness of acoustic recordings coupled with automated sound recognition versus traditional point counts in terms of their relative abilities to detect 3 bird species‐at‐risk in southwestern Ontario, Canada. The comparison was made in 50 woodlots, each of which contained a standard Forest Bird Monitoring Program plot of 5 point‐count stations. An automated recording device was present at one of the point‐count stations. We found that the automated recording and analysis system worked at least as well as the more traditional point‐count method in identifying woodlots containing acadian flycatcher (Empidonax virescens) and cerulean warbler (Setophaga cerulea), but that both methods combined performed better than either method alone. The automated system also required considerably less effort in the field (a difference of 140 min/woodlot) with very little additional effort identifying vocalizations in the lab (approx. 22.5 min/woodlot, for all 3 species combined). The automated system was not as effective in detecting prothonotary warbler (Protonotaria citrea), possibly because the species is much less common in southern Ontario than the other 2 species. © 2014 The Wildlife Society.https://doi.org/10.1002/wsb.421acoustic recordingautomated recognitionbird songbird species‐at‐riskpoint countssouthwestern Ontario |
| spellingShingle | Stephen B. Holmes Kenneth A. McIlwrick Lisa A. Venier Using automated sound recording and analysis to detect bird species‐at‐risk in southwestern Ontario woodlands Wildlife Society Bulletin acoustic recording automated recognition bird song bird species‐at‐risk point counts southwestern Ontario |
| title | Using automated sound recording and analysis to detect bird species‐at‐risk in southwestern Ontario woodlands |
| title_full | Using automated sound recording and analysis to detect bird species‐at‐risk in southwestern Ontario woodlands |
| title_fullStr | Using automated sound recording and analysis to detect bird species‐at‐risk in southwestern Ontario woodlands |
| title_full_unstemmed | Using automated sound recording and analysis to detect bird species‐at‐risk in southwestern Ontario woodlands |
| title_short | Using automated sound recording and analysis to detect bird species‐at‐risk in southwestern Ontario woodlands |
| title_sort | using automated sound recording and analysis to detect bird species at risk in southwestern ontario woodlands |
| topic | acoustic recording automated recognition bird song bird species‐at‐risk point counts southwestern Ontario |
| url | https://doi.org/10.1002/wsb.421 |
| work_keys_str_mv | AT stephenbholmes usingautomatedsoundrecordingandanalysistodetectbirdspeciesatriskinsouthwesternontariowoodlands AT kennethamcilwrick usingautomatedsoundrecordingandanalysistodetectbirdspeciesatriskinsouthwesternontariowoodlands AT lisaavenier usingautomatedsoundrecordingandanalysistodetectbirdspeciesatriskinsouthwesternontariowoodlands |