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Genetic Structure of the Polymorphic Metrosideros (Myrtaceae) Complex in the Hawaiian Islands Using Nuclear Microsatellite Data

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Abstract

  • Background
    Five species of Metrosideros (Myrtaceae) are recognized in the Hawaiian Islands, including the widespread M. polymorpha, and are characterized by a multitude of distinctive, yet overlapping, habit, ecological, and morphological forms. It remains unclear, despite several previous studies, whether the morphological variation within Hawaiian Metrosideros is due to hybridization, genetic polymorphism, phenotypic plasticity, or some combination of these processes. The Hawaiian Metrosideros complex has become a model system to study ecology and evolution; however this is the first study to use microsatellite data for addressing inter-island patterns of variation from across the Hawaiian Islands. Methodology/Principal Findings
    Ten nuclear microsatellite loci were genotyped from 143 individuals of Metrosideros. We took advantage of the bi-parental inheritance and rapid mutation rate of these data to examine the validity of the current taxonomy and to investigate whether Metrosideros plants from the same island are more genetically similar than plants that are morphologically similar. The Bayesian algorithm of the program structure was used to define genetic groups within Hawaiian Metrosideros and the closely related taxon M. collina from the Marquesas and Austral Islands. Several standard and nested AMOVAs were conducted to test whether the genetic diversity is structured geographically or taxonomically. Conclusions/Significance
    The results suggest that Hawaiian Metrosideros have dynamic gene flow, with genetic and morphological diversity structured not simply by geography or taxonomy, but as a result of parallel evolution on islands following rampant island-island dispersal, in addition to ancient chloroplast capture. Results also suggest that the current taxonomy requires major revisions in order to reflect the genetic structure revealed in the microsatellite data.

Publication Date

  • 2009

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