Markers in time and space: A review of the last decade of plant phylogeographic approaches. Issue 10 (May 2018)

• Record Type: Journal Article
• Authors: Morris, Ashley B.; Shaw, Joey
• Is Part Of: Molecular ecology. Volume 27:Issue 10(2018)
• Page Start: 2317
• Page End: 2333
• Publication Date: 2018-05
• Subjects: chloroplast DNA -- divergence time estimation -- ecological niche modelling -- plant phylogeography; Molecular ecology -- Periodicals; Molecular population biology -- Periodicals; 576
• DOI: 10.1111/mec.14695
• Languages: English
• ISSNs: 0962-1083

Abstract

Abstract: Plant studies comprise a relatively small proportion of the phylogeographic literature, likely as a consequence of the fundamental challenges posed by the complex genomic structures and life history strategies of these organisms. Comparative plastomics (i.e., comparisons of mutation rates within and among regions of the chloroplast genome) across plant lineages has led to an increased understanding of which markers are likely to provide the most information at low taxonomic levels. However, the extent to which the results of such work have influenced the literature has not been fully assessed, nor has the extent to which plant phylogeographers explicitly analyse markers in time and space, both of which are integral components of the field. Here, we reviewed more than 400 publications from the last decade of plant phylogeography to specifically address the following questions: (i) What is the phylogenetic breadth of studies to date? (ii) What molecular markers have been used, and why were they chosen? (iii) What kinds of markers are most frequently used and in what combinations? (iv) How frequently are divergence time estimation and ecological niche modelling used in plant phylogeography? Our results indicate that chloroplast DNA sequence data remain the primary tool of choice, followed distantly by nuclear DNA sequences and microsatellites. Less than half (42%) of all studies use divergence time estimation, while even fewer use ecological niche modelling (14%). We discuss the implications of our findings, as well as the need for community standards on data reporting.