Ecology and life history affect different aspects of the population structure of 27 high-alpine plants

Patrick G. Meirmans*, Jerome Goudet, IntraBioDiv Consortium, Oscar Eduardo Gaggiotti

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

38 Citations (Scopus)

Abstract

A plant species' genetic population structure is the result of a complex combination of its life history, ecological preferences, position in the ecosystem and historical factors. As a result, many different statistical methods exist that measure different aspects of species' genetic structure. However, little is known about how these methods are interrelated and how they are related to a species' ecology and life history. In this study, we used the IntraBioDiv amplified fragment length polymorphisms data set from 27 high-alpine species to calculate eight genetic summary statistics that we jointly correlate to a set of six ecological and life-history traits. We found that there is a large amount of redundancy among the calculated summary statistics and that there is a significant association with the matrix of species traits. In a multivariate analysis, two main aspects of population structure were visible among the 27 species. The first aspect is related to the species' dispersal capacities and the second is most likely related to the species' postglacial recolonization of the Alps. Furthermore, we found that some summary statistics, most importantly Mantel's r and Jost's D, show different behaviour than expected based on theory. We therefore advise caution in drawing too strong conclusions from these statistics.

Original languageEnglish
Pages (from-to)3144-3155
Number of pages12
JournalMolecular Ecology
Volume20
Issue number15
Early online date20 Jun 2011
DOIs
Publication statusPublished - Aug 2011

Keywords

  • AFLP
  • DISTANCE
  • TRAITS
  • Alps
  • GENETIC DIVERSITY
  • ALPS
  • COLONIZATION
  • dispersal
  • glacial refugia
  • genetic structure
  • MULTILOCUS GENOTYPES
  • G(ST)
  • MARKERS
  • F-ST
  • redundancy analysis
  • MOUNTAIN PLANTS

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