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\begin{document}

\title{Genomics-informed conservation units reveal spatial variation in climate
vulnerability in a migratory bird}



\author[1]{Caitlin Miller}%
\author[1]{Christen Bossu}%
\author[2]{James Sarraco}%
\author[3]{David Toews}%
\author[4]{Clark Rushing}%
\author[5]{Amélie Roberto-Charron}%
\author[6]{Junior A. Tremblay}%
\author[4]{Richard Chandler}%
\author[1]{Matthew DeSaix}%
\author[7]{Cameron Fiss}%
\author[7]{Jeff Larkin}%
\author[6]{Samuel Haché}%
\author[8]{Silke Nebel}%
\author[1]{Kristen  Ruegg}%
\affil[1]{Colorado State University}%
\affil[2]{The Institute for Bird Populations}%
\affil[3]{Pennsylvania State University}%
\affil[4]{University of Georgia}%
\affil[5]{Government of Nunavut Department of the Environment}%
\affil[6]{Environment and Climate Change Canada}%
\affil[7]{Indiana University of Pennsylvania}%
\affil[8]{BirdsCanada}%


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  \date{June 16, 2024}


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\begin{abstract}
Identifying genetic conservation units (CUs) in threatened species is
critical for the preservation of adaptive capacity and evolutionary
potential in the face of climate change. However, delineating CUs in
highly mobile species remains a challenge due to high rates of gene flow
and genetic signatures of isolation by distance. Even when CUs are
delineated in highly mobile species, the CUs often lack key biological
information about what populations have the most conservation need to
guide management decisions. Here we implement a framework for rigorous
CU identification in the Canada Warbler (Cardellina canadensis), a
highly mobile migratory bird species of conservation concern, and then
integrate demographic modeling and genomic offset within a CU framework
to guide conservation decisions. We find that whole-genome structure in
this highly mobile species is primarily driven by putative adaptive
variation. Identification of CUs across the breeding range revealed that
Canada Warblers fall into two Evolutionarily Significant Units (ESU),
and three putative Adaptive Units (AUs) in the South, East and
Northwest. Quantification of genomic offset within each AU reveals
significant spatial variation in climate vulnerability, with the
Northwestern AU being identified as the most vulnerable to future
climate change based on genomic offset predictions. Alternatively,
quantification of past population trends within each AU revealed the
steepest population declines have occurred within the Eastern AU.
Overall, we illustrate that genomics-informed CUs provide a strong
foundation for identifying current and potential future regional threats
that can be used to manage highly mobile species in a rapidly changing
world.%
\end{abstract}%



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