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Objective choice of phylogeographic models.
- Source :
-
Molecular phylogenetics and evolution [Mol Phylogenet Evol] 2017 Nov; Vol. 116, pp. 136-140. Date of Electronic Publication: 2017 Sep 05. - Publication Year :
- 2017
-
Abstract
- Phylogeography seeks to discover the evolutionary processes that have given rise to organismal and genetic diversity. This requires explicit hypotheses (i.e., models) to be evaluated with genetic data in order to identify those hypotheses that best explain the data. In recent years, advancements in the model-based tools used to estimate phylogeographic parameters of interest such as gene flow, divergence time, and relationships among groups have been made. However, given the complexity of these models, available methods can typically only compare a handful of possible hypotheses, requiring researchers to specify in advance the small set of models to consider. Without formal quantitative approaches to model selection, researchers must rely on their intuition to formulate the model space to be explored. We explore the adequacy of intuitive choices made by researchers during the process of data analysis by reanalyzing 20 empirical phylogeographic datasets using PHRAPL, an objective tool for phylogeographic model selection. We show that the best models for most datasets include both gene flow and population divergence parameters, and that species tree methods (which do not consider gene flow) tend to be overly simplistic for many phylogeographic systems. Objective approaches to phylogeographic model selection offer an important complement to researcher intuition.<br /> (Copyright © 2017 Elsevier Inc. All rights reserved.)
- Subjects :
- Animals
Genetic Variation
Phylogeny
Probability
Models, Genetic
Phylogeography
Subjects
Details
- Language :
- English
- ISSN :
- 1095-9513
- Volume :
- 116
- Database :
- MEDLINE
- Journal :
- Molecular phylogenetics and evolution
- Publication Type :
- Academic Journal
- Accession number :
- 28887148
- Full Text :
- https://doi.org/10.1016/j.ympev.2017.08.018