Uncovering Breeding Habitat Use of an Uncommon Songbird in Pennsylvania Using Large Scale Acoustic Data

ABSTRACT The Canada Warbler ( Cardellina canadensis ) population has declined by over 60% across its range since 1966. Knowledge of breeding habitat use is crucial to the conservation of songbird species but is missing for significant portions of the breeding range of the Canada Warbler's genetically distinct eastern population. We used a large‐scale deployment of autonomous recording units (ARUs) to record Canada Warbler song across north‐central and southwestern Pennsylvania. We deployed ARUs at 664 locations in forested ecosystems, setting them to record for 2 h each morning from mid‐May to mid‐June. We used classifier‐assisted listening to detect Canada Warbler song and generate detection histories. Our occupancy models revealed six significant habitat associations. We highlight forest conditions that can be targeted for the conservation of steeply declining eastern Canada Warbler populations. Our study is an example of the gains in statistical power allowed by ARUs and machine learning methods.

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Publication Details

Journal
Wildlife Letters
Published
2024-12-01
DOI
https://doi.org/10.1002/wll2.12052
Citations
3
Primary Topic
Wildlife Ecology and Conservation
Type
article
Field-Weighted Citation Impact
1.38

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article

Uncovering Breeding Habitat Use of an Uncommon Songbird in Pennsylvania Using Large Scale Acoustic Data

Cameron J. Fiss, Lauren M. Chronister, Justin Kitzes, Jeffery L. Larkin et al.
3 citations
Wildlife Letters
Wildlife Ecology and Conservation
1.38
article

Uncovering Breeding Habitat Use of an Uncommon Songbird in Pennsylvania Using Large Scale Acoustic Data

Cameron J. Fiss, Lauren M. Chronister, Justin Kitzes, Jeffery L. Larkin, Chapin Czarnecki
article en
3 citations

Abstract

ABSTRACT The Canada Warbler ( Cardellina canadensis ) population has declined by over 60% across its range since 1966. Knowledge of breeding habitat use is crucial to the conservation of songbird species but is missing for significant portions of the breeding range of the Canada Warbler's genetically distinct eastern population. We used a large‐scale deployment of autonomous recording units (ARUs) to record Canada Warbler song across north‐central and southwestern Pennsylvania. We deployed ARUs at 664 locations in forested ecosystems, setting them to record for 2 h each morning from mid‐May to mid‐June. We used classifier‐assisted listening to detect Canada Warbler song and generate detection histories. Our occupancy models revealed six significant habitat associations. We highlight forest conditions that can be targeted for the conservation of steeply declining eastern Canada Warbler populations. Our study is an example of the gains in statistical power allowed by ARUs and machine learning methods.

Wildlife LettersVol. 2(4)
The Nature Conservancy (US), State University of New York (US), SUNY College of Environmental Science and Forestry (US), University of Pittsburgh (US), Indiana University of Pennsylvania (US), York University (US), American Bird Conservancy
National Science Foundation, Gordon and Betty Moore Foundation, Pennsylvania Department of Conservation and Natural Resources, National Fish and Wildlife Foundation, University of Pittsburgh, Pennsylvania Game Commission, Directorate for Biological Sciences, Division of Environmental Biology
Openalex Percentile: Top 17%
Wildlife Ecology and Conservation
1.38
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