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31 December 2022 Inferring Ancestry and Divergence Events in a Forest Pest Using Low-Density Single-Nucleotide Polymorphisms
Jasmine K. Janes, James R. P. Worth, Philip D. Batista, Felix A. H. Sperling
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Abstract

Phylogeography infers patterns of migration, demography, and historical relationships from genetic data. Such studies have been particularly useful in understanding vicariance and colonization processes in pest species. Using a low-density single-nucleotide polymorphism (SNP) data set we investigated the range-wide phylogeography of mountain pine beetle (Dendroctonus poderosae Hopk., Coleoptera: Curculionidae) in North America using approximate Bayesian computation (ABC) methods. Our data suggest early divergence events occurred to the south and east of the Great Basin Desert, with populations further west and north of the Great Basin Desert arising later. Further, high levels of genetic differentiation among populations on either side of the basin appear consistent with previous studies. Above the Great Basin Desert, several populations exhibit high rates of migration and admixture. These data further support the idea that Canadian populations have spread from multiple source populations and suggest that small populations of mountain pine beetle may have been present in northern Canada for many decades. These findings further our understanding of the spatiotemporal history of mountain pine beetle in North America and suggest that the species is capable of continued, rapid range expansion from relatively few founding individuals.

© The Author(s) 2018. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Jasmine K. Janes, James R. P. Worth, Philip D. Batista, and Felix A. H. Sperling "Inferring Ancestry and Divergence Events in a Forest Pest Using Low-Density Single-Nucleotide Polymorphisms," Insect Systematics and Diversity 2(6), 1-9, (31 December 2022). https://doi.org/10.1093/isd/ixy019
Received: 7 April 2018; Accepted: 23 October 2018; Published: 31 December 2022
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KEYWORDS
ADMIXTURE
DIYABC
evolutionary history
migration
TreeMix
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