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Diversity associations as stochastic variables

Published online by Cambridge University Press:  08 April 2016

Charles A. F. Smith III*
Affiliation:
Department of the Geophysical Sciences, University of Chicago, Chicago, IL 60637

Abstract

Diversity data from stochastic phylogenies and from uniformly spaced Gaussian curves were subjected to Q-mode factor analysis in order to determine whether a few factors would account for a large percentage of the original variance. In both analyses, a small number of factors show systematic variations in time and account for more than 90% of original data variance. To further study the question of evolutionary pulsations, turnover rates were calculated between successive samples. These turnover rates indicate that stochastic phylogenies have pulses similar to those recorded in the fossil record. Large scale environmental changes are not required to explain such pulses. Therefore the observed existence in the real world of biologic diversity associations and evolutionary pulsations can as equally well be accounted for in a stochastic world (in which each species is an independent variable) as in a deterministic world. This supports the notion that there may be stochastic laws in paleontology akin to the gas laws of chemistry.

Type
Research Article
Copyright
Copyright © The Paleontological Society 

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References

Literature Cited

Flessa, K. and Imbrie, J. 1973. Evolutionary pulsations: Evidence from Phanerozoic diversity patterns. pp. 247285. In: Tarling, D. H. and Runcorn, S. K., eds. Implications of Continental Drift to the Earth Sciences. Academic Press; London.Google Scholar
Flessa, K. and Levinton, J. 1975. Phanerozoic diversity patterns: Tests for randomness. J. Geol. 83:239248.CrossRefGoogle Scholar
Horst, P. 1965. Factor Analysis of Data Matrices. 739 pp. Holt, Rinehart and Wilson; New York.Google Scholar
Klovan, J. 1975. R- and Q-mode factor analysis. pp. 2169. In: McCammon, R. B., ed. Concepts in Geostatistics. Springer-Verlag; New York.CrossRefGoogle Scholar
Klovan, J. and Imbrie, J. 1971. An algorithm and FORTRAN-IV program for large-scale Q-mode factor analysis and calculation of factor scores. Math. Geol. 3:6177.Google Scholar
Mulaik, S. 1972. The Foundations of Factor Analysis. 453 pp. McGraw-Hill; New York.Google Scholar
Newell, N. D. 1952. Periodicity in invertebrate evolution. J. Paleontol. 26:371385.Google Scholar
Raup, D. M., Gould, S. J., Schopf, T. J. M. and Simberloff, D. S. 1973. Stochastic models of phylogeny and the evolution of diversity. J. Geol. 81:525542.Google Scholar
Simpson, G. G. 1952. Periodicity in vertebrate evolution. J. Paleontol. 26:359370.Google Scholar