4.7 Article

Using regional comparative phylogeographic data from snake lineages to infer historical processes in Middle America

Journal

ECOGRAPHY
Volume 33, Issue 2, Pages 343-354

Publisher

WILEY
DOI: 10.1111/j.1600-0587.2010.06281.x

Keywords

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Funding

  1. National Inst. of Health [LM009451]
  2. National Science Foundation (NSF) Collaborative Research [DEB-0416000]
  3. NSF [DEB-0613802, DEB-9705277, DEB-0416160]
  4. Inst. Bioclon

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Understanding how historical processes have either similarly, or differentially, shaped the evolution of lineages or biotic assemblages is important for a broad spectrum of fields. Gaining such understanding can be particularly challenging, however, especially for regions that have a complex geologic and biological history. In this study we apply a broad comparative approach to distill such regional biogeographic perspectives, by characterizing sets of divergence times for major biogeographic boundaries estimated from multiple codistributed lineages of snakes. We use a large combined (mitochondrial gene sequence) phylogeographic/phylogenetic dataset containing several clades of snakes that range across Middle America - the tropical region between Mexico and northwestern South America. This region is known for its complex tectonic history, and poorly understood historical biogeography. Based on our results, we highlight how phylogeographic transition zones between Middle and South America and the Nicaragua Depression appear to have undergone multiple episodes of diversification in different lineages. This is in contrast to other examples we find where apparently a single vicariant period is shared across multiple lineages. We specifically evaluate the distributions of divergence time estimates across multiple lineages and estimate the number of temporal periods of lineage diversification per biogeographic break. Overall, our results highlight a great deal of shared temporal divergence, and provide important hypotheses for yet unstudied lineages. These multi-lineage comparisons across multiple spatial and temporal scales provide excellent predictive power for identifying the roles of geology, climate, ecology and natural history in shaping regional biodiversity.

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