Skip to main content

Model uncertainty in ancestral area reconstruction: A parsimonious solution?

Buy Article:

$14.41 plus tax (Refund Policy)

Abstract:

Increasingly complex likelihood-based methods are being developed to infer biogeographic history. The results of these methods are highly dependent on the underlying model which should be appropriate for the scenario under investigation. Our example concerns the dispersal among the southern continents of the grass subfamily Danthonioideae (Poaceae). We infer ancestral areas and dispersals using likelihood-based Bayesian methods and show the results to be indecisive (reversible-jump Markov chain Monte Carlo; RJ-MCMC) or contradictory (continuous-time Markov chain with Bayesian stochastic search variable selection; BSSVS) compared to those obtained under Fitch parsimony (FP), in which the number of dispersals is minimised. The RJ-MCMC and BSSVS results differed because of the differing (and not equally appropriate) treatments of model uncertainty under these methods. Such uncertainty may be unavoidable when attempting to infer a complex likelihood model with limited data, but we show with simulated data that it is not necessarily a meaningful reflection of the credibility of a result. At higher overall rates of dispersal FP does become increasingly inaccurate. However, at and below the rate observed in Danthonioideae multiple dispersals along branches are not observed and the correct root state can be inferred reliably. Under these conditions parsimony is a more appropriate model.

Keywords: BAYESIAN STOCHASTIC SEARCH VARIABLE SELECTION; BIOGEOGRAPHY; DANTHONIOIDEAE; FITCH PARSIMONY; LONG-DISTANCE DISPERSAL; REVERSIBLE-JUMP MARKOV CHAIN MONTE CARLO; WEST WIND DRIFT

Document Type: Research Article

Affiliations: 1: Institute of Systematic Botany, University of Zurich, Switzerland, Department of Biochemistry, University of Stellenbosch, Private Bag X1, Stellenbosch, South Africa (current address);, Email: mike_pirie@hotmail.com 2: Institute of Systematic Botany, University of Zurich, Switzerland, Imperial College London, Division of Biology, Silwood Park Campus, Ascot, Berkshire, U. K. (current address) 3: Institute of Systematic Botany, University of Zurich, Switzerland, Gothenburg Botanical Garden, Carl Skottsbergs gata 22A, Göteborg, Sweden (current address) 4: Institute of Systematic Botany, University of Zurich, Switzerland, Botany Department, Trinity College, Dublin, Republic of Ireland (current address) 5: Institute of Systematic Botany, University of Zurich, Switzerland

Publication date: 2012-06-13

  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
X
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more