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\begin{document}

\title{Gene flow and migration routes in Salmo trutta L.: toward developing
protected area systems in the English Channel}



\author[1]{Mathieu Vanhove}%
\author[2]{R. Andrew King}%
\author[1]{Lisa Meslier}%
\author[1]{Anne-Laure Besnard}%
\author[3]{Jamie Stevens}%
\author[4]{Sophie Launey}%
\affil[1]{INRAE, Institut Agro, IFREMER}%
\affil[2]{Exeter University}%
\affil[3]{University of Exeter}%
\affil[4]{INRAE, Institut Agro, IFREMER, }%


\vspace{-1em}



  
  \date{May 23, 2024}


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\begin{abstract}
Understanding gene flow can help biodiversity to mitigate habitat
changes by contributing to inform and design protected areas. The brown
trout, Salmo trutta, displays a multitude of life-history strategies and
represents an ideal model for applications in conservation genetics.
Using a panel of 185-single nucleotide polymorphism markers, the present
study aimed to explore the population structure of the brown trout and
in the English Channel. The genotypes of 2,729 individual trout from 88
rivers were obtained across England and France. Population structure
revealed the presence of genetic clusters following an east/west
gradient. The maximum threshold distance between genetic distance and
geographic distance was 344 km. The measure appeared relative to the
studied spatial environment and reflected Salmo trutta capacity to
achieve long migration distances. A machine-learning framework derived
from a gradient forest analysis was used to generate a resistance
surface using changes in allelic frequencies and environmental
predicators. The resulting surface identified areas limiting gene flow.
On the British coast, a genetic break was observed along the Jurassic
coast, whereas the Cotentin peninsula acted as a physical barrier among
French coastal populations. Salmo trutta populations appeared to be
differently affected by environmental factors reflecting demes
preference to specific breeding ground. Using our resistance map, the
distance of maximum correlation using cost distance were computed
allowing the pruning of our genetic graph. The resulting least cost path
connections were mapped to reveal the main dispersal routes. Finally, a
prioritization analysis using connectivity surface was implemented to
design potential protected areas.%
\end{abstract}%



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\textbf{Hosted file}

\verb`Vanhove_2024_Salmo_trutta_ME.doc`  available at \url{https://authorea.com/users/485201/articles/723547-gene-flow-and-migration-routes-in-salmo-trutta-l-toward-developing-protected-area-systems-in-the-english-channel}

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