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Title: Leveraging genomics to understand threats to migratory birds
Abstract

Understanding how risk factors affect populations across their annual cycle is a major challenge for conserving migratory birds. For example, disease outbreaks may happen on the breeding grounds, the wintering grounds, or during migration and are expected to accelerate under climate change. The ability to identify the geographic origins of impacted individuals, especially outside of breeding areas, might make it possible to predict demographic trends and inform conservation decision‐making. However, such an effort is made more challenging by the degraded state of carcasses and resulting low quality of DNA available. Here, we describe a rapid and low‐cost approach for identifying the origins of birds sampled across their annual cycle that is robust even when DNA quality is poor. We illustrate the approach in the common loon (Gavia immer), an iconic migratory aquatic bird that is under increasing threat on both its breeding and wintering areas. Using 300 samples collected from across the breeding range, we develop a panel of 158 single‐nucleotide polymorphisms (SNP) loci with divergent allele frequencies across six genetic subpopulations. We use this SNP panel to identify the breeding grounds for 142 live nonbreeding individuals and carcasses. For example, genetic assignment of loons sampled during botulism outbreaks in parts of the Great Lakes provides evidence for the significant role the lakes play as migratory stopover areas for loons that breed across wide swaths of Canada, and highlights the vulnerability of a large segment of the breeding population to botulism outbreaks that are occurring in the Great Lakes with increasing frequency. Our results illustrate that the use of SNP panels to identify breeding origins of carcasses collected during the nonbreeding season can improve our understanding of the population‐specific impacts of mortality from disease and anthropogenic stressors, ultimately allowing more effective management.

 
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Award ID(s):
1837940 1942313
NSF-PAR ID:
10450683
Author(s) / Creator(s):
 ;  ;  ;  ;  ;  ;  ;  ;  ;  
Publisher / Repository:
Wiley-Blackwell
Date Published:
Journal Name:
Evolutionary Applications
Volume:
14
Issue:
6
ISSN:
1752-4571
Page Range / eLocation ID:
p. 1646-1658
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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