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Abstract Detail


Biogeography

Harris, AJ [1], Thomas, David [1], Xiang, Jenny Qiu-Yun [1].

Inferring Biogeography in the Face of Phylogenetic Uncertainty: An example using Aesculus L.

Reconstructing the biogeographic history of a taxon and developing hypotheses regarding the events responsible for its current distribution typically requires a well-supported, bifurcating phylogenetic tree. Biogeographic reconstructions normally involve some method of mapping ancestral distribution areas as characters across all nodes of a single phylogenetic tree. In the real world of systematics, phylogenies are not always well-supported nor does the data always produce perfectly bifurcating trees. We propose that biogeographic information about taxa or lineages of interest need not be restricted to reconstruction across tree topology. Here, biogeographic analysis using DIVA (Dispersal Vicariance Analysis) software is repeated for a set of randomly sampled Bayesian trees generated using MrBayes. We define a node as the hypothesized ancestor of a specific lineage and its unspecified sister (x). For each node, the probability of each possible ancestral range is calculated as follows: [(1/S)T1 +(1/S)Tr] / N; where 1 indicates that a range was proposed by DIVA, S is the number of optimal ranges given by DIVA for a node on a tree (T), and Tr is one of N randomly sampled trees. Thus, ranges for each node are reported as a set of probabilities from which biogeographic hypotheses may be developed and tested. This approach obviates the need to use a single tree, for which the relationships between taxa are well-supported, to infer ancestral ranges of taxa or lineages of interest. The utility of this approach was tested using Aesculus L.


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1 - North Carolina State University, Department of Botany, Campus Box 7612, Raleigh, North Carolina, 27695-7612, USA

Keywords:
Biogeography
Disjunct Taxa
DIVA
MrBayes
Aesculus L..

Presentation Type: Oral Paper:Papers for Topics
Session: CP01
Location: Boulevard B/Hilton
Date: Monday, July 9th, 2007
Time: 9:15 AM
Number: CP01006
Abstract ID:763


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