Genetic network analysis uncovers spatial variation in diversity and connectivity of a species presenting a continuous distribution

• Published in: Global Ecology and Conservation
• Main Authors: Cory Fournier, Micheline Manseau, Bridget Redquest, Leon Andrew, Allicia Kelly, Dave Hervieux, Troy Hegel, Gigi Pittoello, Vicki Trim, Dennis Brannen, Paul Wilson
• Format: Article in Journal/Newspaper
• Language: English
• Published: Elsevier 2024
• Subjects: Caribou; Conservation genetics; Genetic connectivity; Genetic diversity; Genetic networks; Population structure; Ecology; QH540-549.5; Rangifer tarandus
• Online Access: https://doi.org/10.1016/j.gecco.2024.e03119; https://doaj.org/article/652364b0bb074cd398dd5569930d1f41

The conservation of genetic diversity and connectivity is essential for the long-term persistence and adaptive ability of a species. Recent calls have been made for the inclusion of genetic diversity and differentiation measures in the assessment, management, and conservation of species. However, the literature often lacks direction on how to do so for species with continuous distributions or no distinct breaks in genetic connectivity. There are many considerations to overcome when investigating genetic diversity and connectivity of such species. We combine multiple genetic network methodologies with more traditional population genetic analyses within a single framework to address the challenges of investigating population structure and quantifying variation in genetic diversity and connectivity of wide-ranging species with continuous distributions. We demonstrate the efficacy and applicability of our framework through a study on woodland caribou (Rangifer tarandus) occupying the boreal forest of Canada; a species of significant conservation concern. The dataset consisted of 4911 unique individuals genotyped at 9 microsatellite loci, which were subsequently partitioned into 103 spatial nodes to create a population-based genetic network. The Walktrap community detection algorithm was used to detect hierarchical population genetic structure within the study area and node-based network metrics such as mean inverse edge weight and clustering coefficient were used to quantify the variation in genetic connectivity across the range. Lastly, genetic diversity was assessed by calculating allelic richness and heterozygosity of the nodes making up the network. The community detection analysis identified two communities at the coarsest scale to nine communities at the optimal partition. A strong pattern of Isolation by Distance (IBD) was found across the range at multiple scales. Furthermore, signs of genetic erosion along the study area’s southern boundaries were depicted by nodes presenting low genetic diversity and low ...