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Gradual or pulsed evolution: when should punctuational explanations be preferred?

  • Gene Hunt (a1)

Abstract

The problem of gradual versus punctuated change within phyletic lineages can be understood in terms of the homogeneity of evolutionary dynamics. Hypotheses of punctuated change imply that the rules governing evolutionary change shift over time such that the normal dynamics of stasis are temporarily suspended, permitting a period of net evolutionary change. Such explanations are members of a larger class of models in which evolutionary dynamics are in some way heterogeneous over time. In this paper, I develop a likelihood-based statistical framework to evaluate the support for this kind of evolutionary model. This approach divides evolutionary sequences into nonoverlapping segments, each of which is fit to a separate evolutionary model. Models with heterogeneous dynamics are generally more complex—they require more parameters to specify—than uniform evolutionary models such as random walks and stasis. The Akaike Information Criterion can be used to judge whether the greater complexity of punctuational models is offset by a sufficient gain in log-likelihood for these models to be preferred.

I use this approach to analyze three case studies for which punctuational explanations have been proposed. In the first, a model of punctuated evolution best accounted for changes in pygidial morphology within a lineage of the trilobite Flexicalymene, but the uniform model of an unbiased random walk remains a plausible alternative. Body size evolution in the radiolarian Pseudocubus vema was neither purely gradual nor completely pulsed. Instead, the best-supported explanation posited a single, pulsed increase, followed later by a shift to an unbiased random walk. Finally, for the much-analyzed claim of “punctuated gradualism“ in the foraminifera Globorotalia, the best-supported model implied two periods of stasis separated by a period of elevated but not inherently directional evolution. Although the conclusions supported by these analyses generally refined rather than overturned previous views, the present approach differs from those prior in that all competing interpretations were formalized into explicit statistical models, allowing their relative support to be unambiguously compared.

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Akaike, H. 1974. A new look at the statistical model identification. IEEE Transactions on Automatic Control 19:716723.
Anderson, D. R., Burnham, K. P., and Thompson, W. L. 2000. Null hypothesis testing: problems, prevalence, and an alternative. Journal of Wildlife Management 64:912923.
Bookstein, F. L. 1987. Random walk and the existence of evolutionary rates. Paleobiology 13:446464.
Bookstein, F. L., Gingerich, P. D., and Kluge, A. G. 1978. Hierarchical linear modeling of the tempo and mode of evolution. Paleobiology 4:120134.
Brett, C. E., and Baird, G. C. 2002. Revised stratigraphy of the Trenton Group in its type area, central New York State: sedimentology and tectonics of a Middle Ordovician shelf-to-basin succession. Physics and Chemistry of the Earth 27:231263.
Burnham, K. P., and Anderson, D. R. 2004. Multimodel inference. Understanding AIC and BIC in model selection. Sociological Methods and Research 33:261304.
Butler, M. A., and King, A. A. 2004. Phylogenetic comparative analysis: a modeling approach for adaptive evolution. American Naturalist 164:683695.
Charlesworth, B. 1984. Some quantitative methods for studying evolutionary patterns in single characters. Paleobiology 10:308318.
Cisne, J. L., and Rabe, B. D. 1978. Coenocorrelation: gradient analysis of fossil communities and its applications to stratigraphy. Lethaia 11:341364.
Cisne, J. L., Chandlee, G. O., Rabe, B. D., and Cohen, J. A. 1980. Geographic variation and episodic evolution in an Ordovician trilobite. Science 209:925927.
Eldredge, N., and Gould, S. J. 1972. Punctuated equilibria: an alternative to phyletic gradualism. Pp. 82115 in Schopf, T. J. M., ed. Models in paleobiology. Freeman, Cooper, San Francisco.
Eldredge, N., Thompson, J. N., Brakefield, P. M., Gavrilets, S., Jablonski, D., Jackson, J. B. C., Lenski, R. E., Lieberman, B. S., McPeek, M. A., and Miller, W. I. 2005. The dynamics of evolutionary stasis. In Vrba, E. S. and Eldredge, N., eds. Macroevolution: diversity, disparity, contingency. Paleobiology 31(Suppl. to No. 2):133145.
Erwin, D. H., and Anstey, R. L. 1995. Speciation in the fossil record. Pp. 1138 in Erwin, D. H. and Anstey, R. L., eds. New approaches to speciation in the fossil record. Columbia University Press, New York.
Estes, S., and Arnold, S. J. 2007. Resolving the paradox of stasis: models with stabilizing selection explain evolutionary divergence on all timescales. American Naturalist 169:227244.
Forster, M. 2001. The new science of simplicity. Pp. 83119 in Zellner, A., Keuzenkamp, A., and McAleer, M., eds. Simplicity, inference and modelling. Cambridge University Press, Cambridge.
Forster, M., and Sober, E. 1994. How to tell when simpler, more unified or less ad hoc theories will provide more accurate predictions. British Journal of the Philosophy of Science 45:135.
Fortey, R. A. 1985. Gradualism and punctuated equilibria as competing and complementary theories. Special Papers in Palaeontology 33:1728.
Gingerich, P. D. 1985. Species in the fossil record: concepts, trends, and transitions. Paleobiology 11:2741.
Gingerich, P. D. 1993. Quantification and comparison of evolutionary rates. American Journal of Science 293-A:453478.
Gould, S. J. 2002. The structure of evolutionary theory. Belknap Press of Harvard University Press, Cambridge.
Gould, S. J., and Eldredge, N. 1977. Punctuated equilibria: the tempo and mode of evolution reconsidered. Paleobiology 3:115151.
Gradstein, F. M., Ogg, J. G., and Smith, A. G., eds. 2004. A geological time scale 2004. Cambridge University Press, Cambridge.
Hannisdal, B. 2006. Phenotypic evolution in the fossil record: numerical experiments. Journal of Geology 114:133153.
Hannisdal, B. 2007. Inferring phenotypic evolution in the fossil record by Bayesian inversion. Paleobiology 33:98115.
Hansen, T. F. 1997. Stabilizing selection and the comparative analysis of adaptation. Evolution 51:13411351.
Hansen, T. F., and Martins, E. P. 1996. Translating between microevolutionary process and macroevolutionary patterns: the correlation structure of interspecific data. Evolution 50:14041417.
Hoffman, A. 1989. Arguments on evolution. Oxford University Press, New York.
Hunt, G. 2004. Phenotypic variation in fossil samples: modeling the consequences of time-averaging. Paleobiology 30:426443.
Hunt, G. 2006. Fitting and comparing models of phyletic evolution: random walks and beyond. Paleobiology 32:578601.
Hunt, G. 2007. The relative importance of directional change, random walks, and stasis in the evolution of fossil lineages. Proceedings of the National Academy of Sciences USA 104:1840418408.
Hunt, G. 2008. PaleoTS: modeling evolution in paleontological time-series, Version 0.3–1.
Hunt, G., Bell, M. A., and Travis, M. P. 2008. Evolution toward a new adaptive optimum: phenotypic evolution in a fossil stickleback lineage. Evolution 62:700710.
Hurvich, C. M., and Tsai, C.-L. 1989. Regression and time series model selection in small samples. Biometrika 76:297307.
Jackson, J. B. C., and Cheetham, A. H. 1999. Tempo and mode of speciation in the sea. Trends in Ecology and Evolution 14:7277.
Kalinowski, S. T., and Taper, M. L. 2005. Likelihood-based confidence intervals of relative fitness for a common experimental design. Canadian Journal of Fisheries and Aquatic Science 62:693699.
Kellogg, D. E. 1975. The role of phyletic change in the evolution of Pseudocubus vema . Paleobiology 1:359370.
Kitchell, J. A., Estabrook, G., and MacLeod, N. 1987. Testing for equality of rates of evolution. Paleobiology 13:272285.
Levinton, J. S. 2001. Genetics, paleontology, and macroevolution. Cambridge University Press, Cambridge.
Link, W. A., and Barker, R. J. 2006. Model weights and the foundations of multimodel inference. Ecology 87:26262635.
Lovy, D. 1996. WinDig, Version 2. 5.
MacLeod, N. 1991. Punctuated anagenesis and the importance of stratigraphy to paleobiology. Paleobiology 17:167188.
Malmgren, B. A., Berggren, W. A., and Lohmann, G. P. 1983. Evidence for punctuated gradualism in the Late Neogene Globorotalia tumida lineage of planktonic foraminifera. Paleobiology 9:377389.
Martins, E. P., Diniz-Filho, J. A. F., and Housworth, E. A. 2002. Adaptive constraints and the phylogenetic comparative method: a computer simulation test. Evolution 56:113.
Meeker, W. Q., and Escobar, L. A. 1995. Teaching about approximate confidence regions based on maximum likelihood estimation. American Statistician 49:4853.
R Development Core Team. 2007. R: a language and environment for statistical computing, Version 2.6.1. R Foundation for Statistical Computing, Vienna.
Roopnarine, P. D. 2001. The description and classification of evolutionary mode: a computational approach. Paleobiology 27:446465.
Roopnarine, P. D., Byars, G., and Fitzgerald, P. 1999. Anagenetic evolution, stratophenetic patterns, and random walk models. Paleobiology 25:4157.
Sheets, H. D., and Mitchell, C. E. 2001. Why the null matters: statistical tests, random walks and evolution. Genetica 112–113:105125.
Wagner, P. J. 2000. Likelihood tests of hypothesized durations: determining and accommodating biasing factors. Paleobiology 26:431449.

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Gradual or pulsed evolution: when should punctuational explanations be preferred?

  • Gene Hunt (a1)

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