Methods of inference edit

 
Angiosperm phylogeny of orders based on classification by the Angiosperm Phylogeny Group. The figure shows the number of inferred independent origins of C3-C4 photosynthesis and C4 photosynthesis in parentheses.

Phylogenetic reconstruction and ancestral state reconstruction proceed by assuming that evolution has occurred without convergence. Convergent patterns may, however, appear at higher levels in a phylogenetic reconstruction, and are sometimes explicitly sought by investigators. The methods applied to infer convergent evolution depend on whether pattern-based or process-based convergence is expected. Pattern-based convergence is the broader term, for when two or more lineages independently evolve patterns of similar traits. Process-based convergence is when the convergence is due to similar forces of natural selection.[1]

Pattern-based convergence measures edit

Earlier methods for measuring convergence incorporate ratios of phenotypic and phylogenetic distance by simulating evolution with a Brownian motion model of trait evolution along a phylogeny.[2][3] More recent methods also quantify the strength of convergence.[4] One drawback to keep in mind is that these methods can confuse long-term stasis with convergence due to phenotypic similarities. Stasis occurs when there is little evolutionary change among taxa.[1]

Distance-based measures assess the degree of similarity between lineages over time. Frequency-based measures assess the number of lineages that have evolved in a particular trait space.[1]

Process-based convergence measures edit

Methods to infer process-based convergence fit models of selection to a phylogeny and continuous trait data to determine whether the same selective forces have acted upon lineages. This uses the Ornstein-Uhlenbeck (OU) process to test different scenarios of selection. Other methods rely on an a priori specification of where shifts in selection have occurred. [5]

References edit

  1. ^ a b c Stayton, C. Tristan (2015). "The definition, recognition, and interpretation of convergent evolution, and two new measures for quantifying and assessing the significance of convergence". Evolution. 69 (8): 2140–2153. doi:10.1111/evo.12729. ISSN 1558-5646.
  2. ^ Stayton, C. Tristan. "Is convergence surprising? An examination of the frequency of convergence in simulated datasets". Journal of Theoretical Biology. 252 (1): 1–14. doi:10.1016/j.jtbi.2008.01.008.
  3. ^ Muschick, Moritz; Indermaur, Adrian; Salzburger, Walter. "Convergent Evolution within an Adaptive Radiation of Cichlid Fishes". Current Biology. 22 (24): 2362–2368. doi:10.1016/j.cub.2012.10.048.
  4. ^ Arbuckle, Kevin; Bennett, Cheryl M.; Speed, Michael P. (2014-07-01). "A simple measure of the strength of convergent evolution". Methods in Ecology and Evolution. 5 (7): 685–693. doi:10.1111/2041-210X.12195.
  5. ^ Ingram, Travis; Mahler, D.Luke (2013-05-01). "SURFACE: detecting convergent evolution from comparative data by fitting Ornstein-Uhlenbeck models with stepwise Akaike Information Criterion". Methods in Ecology and Evolution. 4 (5): 416–425. doi:10.1111/2041-210X.12034. ISSN 2041-210X.