JOURNAL ARTICLE
Prey selection by Chordeiles minor (Common Nighthawk) does not reflect differences in prey availability between breeding and nonbreeding grounds.
Published In: Ornithology (Oxford University Press), 2025, v. 142, n. 1. P. 1 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Stein, Eliza D; Fariña, Nestor; Villalba, Olga; Cockle, Kristina L; Zubarán, Gastón E; Snider, Allison M; Baldo, Diego; Cox, James A; Taylor, Sabrina S 3 of 3
Abstract
This article investigates the diet composition and prey selection of the Common Nighthawk (Chordeiles minor), a long-distance migratory aerial insectivore experiencing population declines, across breeding grounds in Florida, USA, and nonbreeding grounds in Corrientes Province, Argentina. Using DNA metabarcoding of fecal samples and aerial insect trapping, the study found that despite significant differences in prey abundance and diversity between sites, C. minor exhibited similar diet richness, diversity, and prey preferences year-round, consistently favoring nutrient-rich Hemiptera (true bugs) and Hymenoptera (ants). Notably, Lepidoptera (moths) were preferred on the nonbreeding grounds but less consumed by adults on the breeding grounds, likely because adults provisioned these prey to their young. The findings suggest limited diet flexibility in C. minor relative to optimal foraging theory predictions, indicating potential vulnerability to changes in prey communities throughout their annual cycle.
Additional Information
- Source:Ornithology (Oxford University Press). 2025/01, Vol. 142, Issue 1, p1
- Document Type:Article
- Subject Area:Geography and Cartography
- Publication Date:2025
- ISSN:2732-4613
- DOI:10.1093/ornithology/ukae054
- Accession Number:182904894
- Copyright Statement:Copyright of Ornithology (Oxford University Press) is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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