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Addressing alpine plant phylogeography using integrative distributional, demographic and coalescent modeling.

Dennis J LarssonDa PanGerald M Schneeweiss
Published in: Alpine botany (2021)
Phylogeographic studies of alpine plants have evolved considerably in the last two decades from ad hoc interpretations of genetic data to statistical model-based approaches. In this review we outline the developments in alpine plant phylogeography focusing on the recent approach of integrative distributional, demographic and coalescent (iDDC) modeling. By integrating distributional data with spatially explicit demographic modeling and subsequent coalescent simulations, the history of alpine species can be inferred and long-standing hypotheses, such as species-specific responses to climate change or survival on nunataks during the last glacial maximum, can be efficiently tested as exemplified by available case studies. We also discuss future prospects and improvements of iDDC.
Keyphrases
  • climate change
  • electronic health record
  • current status
  • big data
  • molecular dynamics
  • network analysis
  • machine learning
  • genetic diversity
  • gene expression
  • human health
  • dna methylation
  • deep learning
  • free survival