Biology & Philosophy

, Volume 26, Issue 4, pp 567–581 | Cite as

Constraining prior probabilities of phylogenetic trees



Although Bayesian methods are widely used in phylogenetic systematics today, the foundations of this methodology are still debated among both biologists and philosophers. The Bayesian approach to phylogenetic inference requires the assignment of prior probabilities to phylogenetic trees. As in other applications of Bayesian epistemology, the question of whether there is an objective way to assign these prior probabilities is a contested issue. This paper discusses the strategy of constraining the prior probabilities of phylogenetic trees by means of the Principal Principle. In particular, I discuss a proposal due to Velasco (Biol Philos 23:455–473, 2008) of assigning prior probabilities to tree topologies based on the Yule process. By invoking the Principal Principle I argue that prior probabilities of tree topologies should rather be assigned a weighted mixture of probability distributions based on Pinelis’ (P Roy Soc Lond B Bio 270:1425–1431, 2003) multi-rate branching process including both the Yule distribution and the uniform distribution. However, I argue that this solves the problem of the priors of phylogenetic trees only in a weak form.


Bayesian epistemology Multi-rate branching process Phylogenetic trees Phylogenetics Principal Principle Prior probabilities Yule process 


  1. Aldous DJ (1996) Probability distributions on cladograms. In: Aldous DJ, Permantle R (eds) Random discrete structures. Springer, New York, pp 1–18Google Scholar
  2. Aldous DJ (2001) Stochastic models and descriptive statistics for phylogenetic trees. Statist Sci 16:23–34CrossRefGoogle Scholar
  3. Alfaro ME, Holder MT (2006) The posterior and the prior in bayesian phylogenetics. Annu Rev Ecol Evol Syst 37:19–42CrossRefGoogle Scholar
  4. Dennett DC (1995) Darwin’s dangerous idea: evolution and the meanings of life. Simon and Schuster, New YorkGoogle Scholar
  5. Earman J (1992) Bayes or bust? A critical examination of bayesian confirmation theory. MIT Press, CambridgeGoogle Scholar
  6. Edwards WH, Lindman H, Savage LJ (1963) Bayesian statistical inference for psychological research. Psychol Rev 70:193–242CrossRefGoogle Scholar
  7. Eldredge N, Gould SJ (1972) Punctuated equilibria: an alternative to phyletic gradualism. In: Schopf TJM (ed) Models in paleobiology. Freeman Cooper, San Francisco, pp 82–115Google Scholar
  8. Felsenstein J (2004) Inferring phylogenies. Sinauer, SunderlandGoogle Scholar
  9. Gillies D (2000) Philosophical theories of probability. Routledge, LondonGoogle Scholar
  10. Guyer C, Slowinski J (1993) Adaptive radiation and the topology of large phylogenies. Evolution 47:253–263CrossRefGoogle Scholar
  11. Heard SB (1992) Patterns in tree balance among cladistic, phenetic, and randomly generated phylogenetic trees. Evolution 46:1818–1826CrossRefGoogle Scholar
  12. Howson C, Urbach P (2006) Scientific reasoning: the bayesian approach, 3rd edn. Open Court, ChicagoGoogle Scholar
  13. Huelsenbeck JP, Rannala B (2004) Frequentist properties of bayesian posterior probabilities of phylogenetic trees under simple and complex substitution models. Syst Biol 53:904–913CrossRefGoogle Scholar
  14. Huelsenbeck JP, Ronquist F (2001) MR BAYES: bayesian inference of phylogenetic trees. Bioinformatics 17:754–755CrossRefGoogle Scholar
  15. Jaynes ET (1983) In: Rosenkrantz R (ed) Papers on probability, statistics, and statistical physics. Reidel, DordrechtGoogle Scholar
  16. Keynes JM (1921) A treatise on probability. MacMillan, New YorkGoogle Scholar
  17. Levins R (1966) The strategy of model building in population biology. Am Sci 54:421–431Google Scholar
  18. Lewis D (1980) A subjectivist’s guide to objective chance. In: Jeffrey R (ed) Studies in inductive logic and probability vol II. University of California Press, Berkeley, pp 263–293Google Scholar
  19. Maddison W, Slatkin M (1991) Null models for the number of evolutionary steps in a character on a phylogenetic tree. Evolution 45:1184–1197CrossRefGoogle Scholar
  20. McMullin E (1985) Galilean idealization. Stud Hist Philos Sci 16:247–273CrossRefGoogle Scholar
  21. Mellor DH (2005) Probability: a philosophical introduction. Routledge, LondonGoogle Scholar
  22. Pinelis I (2003) Evolutionary models of phylogenetic trees. P Roy Soc Lond B Bio 270:1425–1431CrossRefGoogle Scholar
  23. Rannala B, Yang Z (1996) Probability distribution of molecular evolutionary trees: a new method of phylogenetic inference. J Mol Evol 43:304–311CrossRefGoogle Scholar
  24. Simmons MP, Pickett KM, Miya M (2004) How meaningful are bayesian support values? Mol Biol Evol 21:188–199CrossRefGoogle Scholar
  25. Steel M, McKenzie A (2001) Properties of phylogenetic trees generated by Yuletype speciation models. Math Biosci 170:91–112CrossRefGoogle Scholar
  26. Sterelny K (2007) Dawkins vs. Gould: survival of the fittest. Icon Books, ThriplowGoogle Scholar
  27. Suppes P (1966) A bayesian approach to the paradoxes of confirmation. In: Hintikka J, Suppes P (eds) Aspects of inductive logic. North-Holland, Amsterdam, pp 198–207CrossRefGoogle Scholar
  28. Velasco JD (2008) The prior probabilities of phylogenetic trees. Biol Philos 23:455–473CrossRefGoogle Scholar
  29. Weisberg M (2006) Robustness analysis. Philos Sci 73:730–742CrossRefGoogle Scholar
  30. Williamson J (2007) Motivating objective bayesianism: from empirical constraints to objective probabilities. In: Harper WL, Wheeler GR (eds) Probability and inference: essays in honor of Henry E. Kyburg Jr. College Publications, London, pp 155–183Google Scholar
  31. Wimsatt WC (1981) Robustness, reliability, and overdetermination. In: Brewer M, Collins B (eds) Scientific enquiry and the social sciences. Jossey-Boss, San Francisco, pp 124–163Google Scholar
  32. Yang Z (2006) Computational molecular evolution. Oxford University Press, OxfordCrossRefGoogle Scholar
  33. Yule GU (1924) A mathematical theory of evolution, based on the conclusions of Dr. JC Willis, FRS. P Roy Soc Lond B Bio 213:21–87Google Scholar

Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  1. 1.Department of Philosophy, Logic and Scientific Method, London School of Economics and Political ScienceLondonUK

Personalised recommendations