8.S: Fitting models of discrete character evolution (Summary)

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    8.S: Fitting models of discrete character evolution (Summary)

    In this chapter I describe how Felsenstein’s pruning algorithm can be used to calculate the likelihoods of Mk and extended-Mk models on phylogenetic trees. I have also described both ML and Bayesian frameworks that can be used to test hypotheses about character evolution. This chapter also includes a description of the “total garbage” test, which will tell you if your data has information about evolutionary rates of a given character.

    Analyzing our example of lizard limbs shows the power of this approach; we can estimate transition rates for this character over macroevolutionary time, and we can say with some certainty that transitions between limbed and limbless have been asymmetric. In the next chapter, we will build on the Mk model and further develop our comparative toolkit for understanding the evolution of discrete characters.

    References

    Bergmann, P. J., and D. J. Irschick. 2012. Vertebral evolution and the diversification of squamate reptiles. Evolution 66:1044–1058. Wiley Online Library.

    Brandley, M. C., J. P. Huelsenbeck, and J. J. Wiens. 2008. Rates and patterns in the evolution of snake-like body form in squamate reptiles: Evidence for repeated re-evolution of lost digits and long-term persistence of intermediate body forms. Evolution. Wiley Online Library.

    Felsenstein, J. 2004. Inferring phylogenies. Sinauer Associates, Inc., Sunderland, MA.

    Felsenstein, J. 1973. Maximum likelihood and minimum steps methods for estimating evolutionary trees from data on discrete characters. Syst. Biol. 22:240–249. Oxford University Press.

    Pyron, R. A., F. T. Burbrink, and J. J. Wiens. 2013. A phylogeny and revised classification of squamata, including 4161 species of lizards and snakes. BMC Evol. Biol. 13:93. bmcevolbiol.biomedcentral.com.

    Rosindell, J., and L. J. Harmon. 2012. OneZoom: A fractal explorer for the tree of life. PLoS Biol. 10:e1001406.


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