دورية أكاديمية
A large-scale assessment of eastern whip-poor-will (Antrostomus vociferus) occupancy across a gradient of forest management intensity using autonomous recording units.
| العنوان: | A large-scale assessment of eastern whip-poor-will (Antrostomus vociferus) occupancy across a gradient of forest management intensity using autonomous recording units. |
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| المؤلفون: | Larkin JT; University of Massachusetts Amherst, 160 Holdsworth Way, Amherst, MA, 01003, USA. Electronic address: larkinjeff16@gmail.com., McNeil DJ; University of Kentucky, 104 T.P. Cooper Building, Lexington, KY, 40546, USA., Chronister L; University of Pittsburgh, 103 Clapp Hall Fifth and Ruskin Avenues, Pittsburgh, PA, 15260, USA., Akresh ME; University of Massachusetts Amherst, 160 Holdsworth Way, Amherst, MA, 01003, USA; Antioch University New England, 40 Avon Street, Keene, NH, 03431, USA., Cohen EB; University of Maryland Center for Environmental Science, Appalachian Laboratory, 301 Braddock Road, Frostburg, MD, 21532, USA., D'Amato AW; University of Vermont, 204E Aiken Center, 81 Carrigan Drive, Burlington, VT, 05405, USA., Fiss CJ; State University of New York, College of Environmental Science and Forestry, Syracuse, NY, 13210, USA., Kitzes J; University of Pittsburgh, 103 Clapp Hall Fifth and Ruskin Avenues, Pittsburgh, PA, 15260, USA., Larkin JL; Indiana University of Pennsylvania, Weyandt Hall, Room 114, 975 Oakland Avenue, Indiana, PA, 15705, USA; American Bird Conservancy, 8255 E. Main Street, Suites D & E, Marshall, VA, 20115, USA., Parker HA; Indiana University of Pennsylvania, Weyandt Hall, Room 114, 975 Oakland Avenue, Indiana, PA, 15705, USA., King DI; University of Massachusetts Amherst, 160 Holdsworth Way, Amherst, MA, 01003, USA; USDA Forest Service-Northern Research Station, 201 Holdsworth Hall, Amherst, MA, 01003, USA. |
| المصدر: | Journal of environmental management [J Environ Manage] 2024 Aug; Vol. 366, pp. 121786. Date of Electronic Publication: 2024 Jul 10. |
| نوع المنشور: | Journal Article |
| اللغة: | English |
| بيانات الدورية: | Publisher: Academic Press Country of Publication: England NLM ID: 0401664 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1095-8630 (Electronic) Linking ISSN: 03014797 NLM ISO Abbreviation: J Environ Manage Subsets: MEDLINE |
| أسماء مطبوعة: | Original Publication: London ; New York, Academic Press. |
| مواضيع طبية MeSH: | Forests* , Conservation of Natural Resources*/methods , Ecosystem*, Animals |
| مستخلص: | Conservationists spend considerable resources to create and enhance wildlife habitat. Monitoring how species respond to these efforts helps managers allocate limited resources. However, monitoring efforts often encounter logistical challenges that are exacerbated as geographic extent increases. We used autonomous recording units (ARUs) and automated acoustic classification to mitigate the challenges of assessing Eastern Whip-poor-will (Antrostomus vociferus) response to forest management across the eastern USA. We deployed 1263 ARUs in forests with varying degrees of management intensity. Recordings were processed using an automated classifier and the resulting detection data were used to assess occupancy. Whip-poor-wills were detected at 401 survey locations. Across our study region, whip-poor-will occupancy decreased with latitude and elevation. At the landscape scale, occupancy decreased with the amount of impervious cover, increased with herbaceous cover and oak and evergreen forests, and exhibited a quadratic relationship with the amount of shrub-scrub cover. At the site-level, occupancy was negatively associated with basal area and brambles (Rubus spp.) and exhibited a quadratic relationship with woody stem density. Implementation of practices that create and sustain a mosaic of forest age classes and a diverse range of canopy closure within oak (Quercus spp.) dominated landscapes will have the highest probability of hosting whip-poor-wills. The use of ARUs and a machine learning classifier helped overcome challenges associated with monitoring a nocturnal species with a short survey window across a large spatial extent. Future monitoring efforts that combine ARU-based protocols and mappable fine-resolution structural vegetation data would likely further advance our understanding of whip-poor-will response to forest management. Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. (Copyright © 2024 Elsevier Ltd. All rights reserved.) |
| فهرسة مساهمة: | Keywords: Forest management; Machine learning classifier; Nightjar; Oak; Passive acoustic monitoring; Private lands conservation |
| تواريخ الأحداث: | Date Created: 20240711 Date Completed: 20240806 Latest Revision: 20240806 |
| رمز التحديث: | 20240806 |
| DOI: | 10.1016/j.jenvman.2024.121786 |
| PMID: | 38991338 |
| قاعدة البيانات: | MEDLINE |
Full Text Finder | تدمد: | 1095-8630 |
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| DOI: | 10.1016/j.jenvman.2024.121786 |