SURFACE: detecting convergent evolution from comparative data by fitting Ornstein-Uhlenbeck models with stepwise Akaike Information Criterion


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  1. We present a method, ‘SURFACE’, that uses the Ornstein-Uhlenbeck stabilizing selection model to identify cases of convergent evolution using only continuous phenotypic characters and a phylogenetic tree.
  2. SURFACE uses stepwise Akaike Information Criterion first to locate regime shifts on a tree, then to identify whether shifts are towards convergent regimes. Simulations can be used to test the hypothesis that a clade contains more convergence than expected by chance.
  3. We demonstrate the method with an application to Hawaiian Tetragnatha spiders, and present numerical simulations showing that the method has desirable statistical properties given data for multiple traits.
  4. The r package surface is available as open source software from the Comprehensive R Archive Network.