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Phylogeographic analysis delimits three evolutionary significant units of least chipmunks in North America and identifies unique genetic diversity within the imperiled Peñasco population.

Emily E PuckettSean M MurphyGideon S Bradburd
Published in: Ecology and evolution (2021)
Although least chipmunks (Neotamias minimus) are a widely distributed North American species of least concern, the southernmost population, N. m. atristriatus (Peñasco least chipmunk), is imperiled and a candidate for federal listing as a subspecies. We conducted a phylogeographic analysis across the N. minimus range to assess genomic differentiation and distinctiveness of the N. m. atristriatus population. Additionally, we leveraged the historical component of sampling to conduct a temporal analysis of N. minimus genetic diversity and also considered climate change effects on range persistence probability by projecting a species distribution model into the IPCC5 RCP 2.6 and 8.5 scenarios. We identified three geographically structured groups (West, North, and South) that were supported by both mitochondrial and nuclear data. N. m. atristriatus grouped within a unique South subclade but were not reciprocally monophyletic from N. m. operarius, and nuclear genome analyses did not separate N. m. atristriatus, N. m. caryi, and N. m. operarius. Thus, while least chipmunks in the Southwest represent an evolutionary significant unit, subspecies distinctions were not supported and listing of the Peñasco population as a Distinct Population Segment of N. m. operarius may be warranted. Our results also support consideration of populations with North and West mitogenomes as two additional evolutionary significant units. We found that N. minimus genetic diversity declined by ~87% over the last century, and our models predicted substantial future habitat contraction, including the loss of the full contemporary ranges of N. m. atristriatus, N. m. arizonensis, and N. m. chuskaensis.
Keyphrases
  • genetic diversity
  • climate change
  • genome wide
  • dna methylation
  • tertiary care
  • big data
  • artificial intelligence
  • current status
  • neural network