JOURNAL ARTICLE

Species-specific ecological traits, phylogeny, and geography underpin vulnerability to population declines for North American birds.

  • Published In: Ornithological Applications, 2024, v. 126, n. 1. P. 1 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Stevens, Henry C.; Smith, Adam C.; Buechley, Evan R.; Şekercioğlu, Çağan H.; Shirey, Vaughn; Rosenberg, Kenneth V.; Sorte, Frank A. La; Tallamy, Douglas; Marra, Peter P. 3 of 3

Abstract

This article investigates how species-specific ecological traits, phylogeny (evolutionary relationships), and geography influence vulnerability to population declines among 380 North American bird species. Using Bayesian hierarchical models and data from the Breeding Bird Survey, the study finds that multiple ecological traits—including migration distance, body mass, insect dependence, habitat and dietary breadth, clutch size, and reproductive periods—alongside phylogeny and breeding geography, explain variation in regional population trends. Notably, longer migration distances and larger clutch sizes correlate with more negative trends, while greater habitat and dietary breadth and larger body mass associate with more positive trends. The study also reveals that the relative influence of these factors varies among bird orders, with migration distance strongly affecting songbirds and geography more strongly influencing shorebirds, underscoring the need for species- and group-specific conservation strategies rather than one-size-fits-all regional plans.

Additional Information

  • Source:Ornithological Applications. 2024/02, Vol. 126, Issue 1, p1
  • Document Type:Article
  • Subject Area:Zoology
  • Publication Date:2024
  • ISSN:2732-4621
  • DOI:10.1093/ornithapp/duad046
  • Accession Number:175735723
  • Copyright Statement:Copyright of Ornithological Applications 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.)

Looking to go deeper into this topic? Look for more articles on EBSCOhost.