Using landscape genetics simulations for planting blister rust resistant whitebark pine in the US Northern Rocky Mountains

Erin L. Landguth, Zachary A. Holden, Mary F. Mahalovich, Samuel A. Cushman

Research output: Contribution to journalArticlepeer-review

26 Scopus citations

Abstract

Recent population declines to the high elevation western North America foundation species whitebark pine, have been driven by the synergistic effects of the invasive blister rust pathogen, mountain pine beetle (MPB), fire exclusion, and climate change. This has led to consideration for listing whitebark pine (WBP) as a threatened or endangered species under the Endangered Species Act, which has intensified interest in developing management strategies for maintaining and restoring the species. An important, but poorly studied, aspect of WBP restoration is the spatial variation in adaptive genetic variation and the potential of blister rust resistant strains to maintain viable populations in the future. Here, we present a simulation modeling framework to improve understanding of the long-term genetic consequences of the blister rust pathogen, the evolution of rust resistance, and scenarios of planting rust resistant genotypes of whitebark pine. We combine climate niche modeling and eco-evolutionary landscape genetics modeling to evaluate the effects of different scenarios of planting rust-resistant genotypes and impacts of wind field direction on patterns of gene flow. Planting scenarios showed different levels for local extirpation of WBP and increased population-wide blister rust resistance, suggesting that the spatial arrangement and choice of planting locations can greatly affect survival rates of whitebark pine. This study presents a preliminary, but potentially important, framework for facilitating the conservation of whitebark pine.

Original languageEnglish
Article number9
JournalFrontiers in Genetics
Volume8
Issue numberFEB
DOIs
StatePublished - Feb 10 2017

Keywords

  • Assisted migration
  • CDMetaPOP
  • Computer simulations
  • Ecological niche modeling
  • Genotype-environment associations
  • Landscape genomics
  • Wind resistance

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