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Predictivity in taxonomy and the probability of a tree

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Abstract

The contribution ofJ. S. L. Gilmour to numerical taxonomy is reviewed. His important concept of natural classification, as being general-purpose classifications with high predictivity, led to the development of ideas of information content, unit characters and equal character-weighting. The concept of predicitivity is extended to taxonomic trees (phenograms or cladograms). Under certain assumption of random sampling of characters it is shown that the probability of recovering the correct tree topology or tree-form may be small if characters are few. There may be very many topologies or tree-forms, every one of which has individually a low probability. It is, however, possible to estimate the aggregate probability of trees which have more than some specified resemblance to the “correct” tree. The practical prospects of estimating the distribution of tree probabilities are discussed.

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References

  • Adanson, M., 1757: Histoire naturelle du Sénégal. — Paris: Bauche.

    Google Scholar 

  • —, 1763: Familles des plantes. — Paris: Vincent.

    Google Scholar 

  • Astolfi, P., Kidd, K. K., Cavalli-Sforza, L. L., 1981: A comparison of methods for reconstructing evolutionary trees. — Syst. Zool.30: 156–169.

    Google Scholar 

  • Beckner, M., 1959: The biological way of thought. — New York: Columbia University Press.

    Google Scholar 

  • Cain, A. J., 1958: Logic and memory inLinnaeus's system of taxonomy. — Proc. Linn. Soc. London, 169th session: 144–163.

  • —, 1958: An analysis of the taxonomist's judgement of affinity. — Proc. Zool. Soc. London131: 85–98.

    Google Scholar 

  • Cavalli-Sforza, L. L., Edwapds, A. F., 1967: Phylogenetic analysis: models and estimation procedures. — Evolution21: 550–570.

    Google Scholar 

  • Conover, W. J., 1971: Practical nonparametric statistics. — New York: John Wiley.

    Google Scholar 

  • Farris, J. S., 1973: A probability model for inferring evolutionary trees. — Syst. Zool.22: 250–256.

    Google Scholar 

  • —, 1977: On the phenetic approach to vertebrate classification. — InHecht, M. K., Goody, P. C., Hecht, B. M., (Eds.): Major patterns in vertebrate evolution, pp. 823–850. — New York: Plenum Press.

    Google Scholar 

  • Felsenstein, J., 1973: Maximum likelihood and minimum-steps methods for estimating evolutionary trees from data on discrete characters. — Syst. Zool.22: 240–249.

    Google Scholar 

  • —, 1983: Parsimony in systematics: biological and statistical issues. — Ann. Rev. Ecol. Syst.11: 333–358.

    Google Scholar 

  • —, 1985a: Confidence limits on phylogenies with a molecular clock. — Syst. Zool.35: 152–161.

    Google Scholar 

  • —, 1985b: Confidence limits on phylogenies: an approach using the bootstrap. — Evolution39: 783–791.

    Google Scholar 

  • Gilmour, J. S. L., 1936: Whither taxonomy? Text of a paper given to Section K (Botany) of the British Association for the Advancement of Science in Blackpool 1936, first published 1976 in The Classification Soc. Bull.3 (4): 3–9; and reprinted in the present volume.

    Google Scholar 

  • —, 1937: A taxonomic problem. — Nature (London)139: 1040–1042. — Reprinted in The Classification Soc. Bull., 1976,3 (4): 9–15; and in the present volume.

    Google Scholar 

  • —, 1940: Taxonomy and philosophy. — InHuxley, J., (Ed.): The new systematics, pp. 461–474. — Oxford: Oxford University Press.

    Google Scholar 

  • Gower, J. C., 1974: Maximal predictive classification. — Biometrics30: 643–654.

    Google Scholar 

  • Hartigan, J. A., 1967: Representation of similarity matrices by trees. — J. Amer. Statist. Ass.62: 1140–1158.

    Google Scholar 

  • Holmquist, R., 1979: The method of parsimony: an experimental test and theoretical analysis of the adequacy of molecular restoration studies. — J. Molec. Biol.135: 939–958.

    Google Scholar 

  • Jardine, N., Sibson, R., 1968: The construction of hierarchic and non-hierarchic classifications. — Computer J.11: 177–184.

    Google Scholar 

  • Kidd, K. K., Cavalli-Sforza, L. L., 1971: Number of charactes examined and error in reconstruction of evolutionary trees. — InHodson, F. R., Kendall, D. G., Tăutu, P., (Eds).: Mathematics in the archaeological and historical sciences, pp. 335–346. — Edinburgh: Edinburgh University Press.

    Google Scholar 

  • La Duke, J., Crawford, D. J., 1979: Character compatibility and phyletic relationships in several closely related species ofChenopodium of the Western United States. — Taxon28: 307–314.

    Google Scholar 

  • MacLaren, M. D., Marsaglia, G., 1965: Uniform random number generators. — J. Assoc. Comp. Mach.12: 83–89.

    Google Scholar 

  • Michener, C. D., Sokal, R. R., 1957: A quantitative approach to a problem in classification. — Evolution11: 130–162.

    Google Scholar 

  • Mill, J. S., 1843: A system of logic. 2 vols. — London: Parker.

    Google Scholar 

  • Penny, D., Hendy, M. D., 1985: The use of tree comparison metrics. — Syst. Zool.34: 75–82.

    Google Scholar 

  • Phipps, J. B., 1971: Dendrogram topology. — Syst. Zool.20: 306–308.

    Google Scholar 

  • Sackin, M. J., 1985: Comparisons of classifications. — InGoodfellow, M., Jones, D., Priest, F. G., (Eds.): Computer-assisted bacterial systematics, pp. 21–36. — London: Academic Press.

    Google Scholar 

  • Sneath, P. H. A., 1957: Some thoughts on bacterial classification. — J. Gen. Microbiol.17: 184–200.

    Google Scholar 

  • —, 1986: Significance tests for multivariate normality of clusters from branching patterns in dendograms. — Math. Geol.18: 3–32.

    Google Scholar 

  • —, 1985: Naturalness and predicitivity of classifications. — Biol. J. Linn. Soc.24: 217–231.

    Google Scholar 

  • —, 1973: Numerical taxonomy: the principles and practice of numerical classification. — San Francisco: Freeman.

    Google Scholar 

  • Sokal, R. R., Michener, C. D., 1958: A statistical method for evaluating systematic relationships. — Univ. Kansas Sci. Bull.38: 1409–1438.

    Google Scholar 

  • —, 1963: Principles of numerical taxonomy. — San Francisco: Freeman.

    Google Scholar 

  • Whewell, W., 1840: The philosophy of the inductive sciences, founded upon their history. 2 vols. — Cambridge: Deighton.

    Google Scholar 

  • Wichmann, B. A., Hill, I. D., 1982: Algorithm AS183: an efficient and portable pseudorandon number generator. — Appl. Statistics31: 188–190.

    Google Scholar 

  • Woodger, J. H., 1937: The axiomatic method in biology. — Cambridge: Cambridge University Press.

    Google Scholar 

  • —, 1945: On biological transformations. — InLe Gros Clark, W. E., Medawar, P. B., (Eds.): Assays on growth and form presented toD'Arcy Wentworth Thompson, pp. 94–120. — Oxford: Clarendon Press.

    Google Scholar 

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Dedicated to the memory of JohnS. L. Gilmour.

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Sneath, P.H.A. Predictivity in taxonomy and the probability of a tree. Pl Syst Evol 167, 43–57 (1989). https://doi.org/10.1007/BF00936546

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