THE INFLUENCE OF SAMPLING DESIGN ON SPECIES TREE INFERENCE: A NEW RELATIONSHIP FOR THE NEW WORLD CHICKADEES (AVES: POECILE)
Article first published online: 24 OCT 2013
© 2013 The Author(s). Evolution © 2013 The Society for the Study of Evolution.
Volume 68, Issue 2, pages 501–513, February 2014
How to Cite
Harris, R. B., Carling, M. D. and Lovette, I. J. (2014), THE INFLUENCE OF SAMPLING DESIGN ON SPECIES TREE INFERENCE: A NEW RELATIONSHIP FOR THE NEW WORLD CHICKADEES (AVES: POECILE). Evolution, 68: 501–513. doi: 10.1111/evo.12280
- Issue published online: 28 JAN 2014
- Article first published online: 24 OCT 2013
- Accepted manuscript online: 2 OCT 2013 09:49AM EST
- Manuscript Accepted: 19 SEP 2013
- Manuscript Received: 11 APR 2013
- Coalescent theory;
- gene flow;
In this study, we explore the long-standing issue of how many loci are needed to infer accurate phylogenetic relationships, and whether loci with particular attributes (e.g., parsimony informativeness, variability, gene tree resolution) outperform others. To do so, we use an empirical data set consisting of the seven species of chickadees (Aves: Paridae), an analytically tractable, recently diverged group, and well-studied ecologically but lacking a nuclear phylogeny. We estimate relationships using 40 nuclear loci and mitochondrial DNA using four coalescent-based species tree inference methods (BEST, *BEAST, STEM, STELLS). Collectively, our analyses contrast with previous studies and support a sister relationship between the Black-capped and Carolina Chickadee, two superficially similar species that hybridize along a long zone of contact. Gene flow is a potential source of conflict between nuclear and mitochondrial gene trees, yet we find a significant, albeit low, signal of gene flow. Our results suggest that relatively few loci with high information content may be sufficient for estimating an accurate species tree, but that substantially more loci are necessary for accurate parameter estimation. We provide an empirical reference point for researchers designing sampling protocols with the purpose of inferring phylogenies and population parameters of closely related taxa.