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Composite Time Lines: A Means to Leverage Resolving Power from Radioisotopic Dates and Biostratigraphy

Published online by Cambridge University Press:  21 July 2017

Peter M. Sadler*
Affiliation:
Department of Earth Science University of California Riverside, California 92521 USA, peter.sadler@ucr.edu
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Abstract

Species origination and extinction events far outnumber radioisotopically dated events in the ancient stratigraphic record. In order to calibrate rapid rates of Mesozoic and Paleozoic change and to estimate the ages of paleobiologic events it would be ideal to have multiple dated events in single stratigraphic sections. This condition is rarely realized and the practical alternative is to build composite sections that combine information from many different locations. The compositing process takes advantage of all available evidence of relative age to produce high resolution time lines; i.e. ordered sequences of individual events whose average spacing is much finer than the duration of biostratigraphic zones and can approach the uncertainty intervals of the highest precision radioisotopic dates. Dated events are included in the compositing process from the outset. As a result the sequencing procedure is more efficient and the dated events find their optimal positions in the time line independent of any biostratigraphic zonal schemes. The sequencing procedures follow simple logical rules that may be learned from tiny data sets. When usefully large numbers of events are involved, however, the sequencing must be undertaken by computer and there is seldom a unique solution that best fits the field data. The range of positions in sequence that an event may occupy across the full set of equally best-fit solutions is a measure of the resolving power of the event. As new high-precision dates and detailed range charts continue to become available, the quality of the time lines will improve and they will become increasingly viable alternatives to zonal time scales in the older parts of the Phanerozoic.

Type
Research Article
Copyright
Copyright © by the Paleontological Society 

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References

Agterberg, F. P. 1990. Automated stratigraphic correlation. Developments in Palaeontology and Stratigraphy, 13:1424.Google Scholar
Agterberg, F. P., and Gradstein, F. M. 1999. The RASC method for ranking and scaling of biostratigraphic events. Earth Science Reviews, 46:125.CrossRefGoogle Scholar
Agterberg, F. P., and Nel, L. D. 1982. Algorithms for the ranking of stratigraphic events. Computers and Geosciences, 8:6990.Google Scholar
Alroy, J. 1992. Conjunction among taxonomic distributions and the Miocene mammalian biochronology of the Great Plains, Paleobiology, 18:326–43.CrossRefGoogle Scholar
Alroy, J. 1994. Appearance event ordination: a new biochronological method. Paleobiology, 20:191207.Google Scholar
Alroy, J. 2000. New methods for quantifying macroevolutionary patterns and processes. Paleobiology, 26:707–33.2.0.CO;2>CrossRefGoogle Scholar
Baadsgaard, H., Lerbekmo, J. F., Wijbrans, J. R., Swisher, C. C., and Fanning, M. 1993. Multi-method radiometric age for a bentonite near the top of the Baculites reesidei zone of southwestern Saskatchewan (Campanian-Maastrichtian stage boundary?), Canadian Journal of Earth Science, 30:769775.Google Scholar
Blackham, M. 1998. The unitary association method of relative dating and its application to archaeological data. Journal of Archaeological Method and Theory, 5:165207.Google Scholar
Clark, R. M. 1985. A FORTRAN program for constrained sequence-slotting based on minimum combined path length. Computers and Geoscience, 11:605–17.Google Scholar
Clark, R. M. 1995. Depth-matching using PCSLOT version 1.6. Newsletter of the INQUA Working Group for Data-Handling Methods 13. http://kv.geo.uu.se/in-qua/news12/n13-mc.htm Google Scholar
Cooper, R.A., Crampton, J. S., Raine, J.I., Gradstein, F. M., Morgans, H. E. G., ET AL. 2001. Quantitative biostratigraphy of the Taranaki Basin, New Zealand: a deterministic and probabilistic approach. American Association of Petroleum Geologists Bulletin, 85:1469–98.Google Scholar
Cooper, R. A., and Sadler, P. M. 2004. The Ordovician Period, p. 165187 in Gradstein, F., Ogg, J. and Smith, A. (eds.) A Geologic Time Scale 2004. Cambridge University Press.Google Scholar
Dell, R. F., Kemple, W. G., and Tovey, C. A. 1992. Heuristically solving the stratigraphic correlation problem. Proceedings of the 1st. Industrial Engineering Research Conference, 1:293–97Google Scholar
Edwards, L. E. 1978. Range charts and no-space graphs. Computers and Geosciences, 4:247255 Google Scholar
Edwards, L. E. 1982. Quantitative biostratigraphy: the methods should suit the data, p. 4560. in Cubitt, J. M., and Reyment, R. A. (eds.). Quantitative stratigraphic correlation, Chichester, Wiley.Google Scholar
Gardner, T. W., Jorgensen, D. W., Shuman, C., and Lemieux, C. R. 1987. Geomorphic and tectonic process rates: effects of measured time interval, Geology, 15:259261.Google Scholar
Gingerich, P. D. 1983. Rates of evolution: effects of time and temporal scaling, Science, 222:159161.CrossRefGoogle ScholarPubMed
Gingerich, P. D. 2001. Rates of evolution on the time scale of the evolutionary process, Genetics, 112/113:127144.Google Scholar
Gordon, A. D., and Reyment, R. A. 1979. Slotting of borehole sequences, Mathematical Geology, 11:309–27.Google Scholar
Gradstein, F. M., and Agterberg, F. P. 1998. Uncertainty in stratigraphic correlation, p. 929, in Gradstein, F. M. and Sandvik, K. O. (eds.), Sequence Stratigraphy: concepts and applications, Norwegian Petroleum Society Special Publication 8.Google Scholar
Gradstein, F., Ogg, J., and Smith, A. 2004. A Geologic Time Scale 2004. Cambridge University Press, 589p.Google Scholar
Guex, J. 1977. Une nouvelle méthode d'analyse biochronologique. Bulletin Laboratoire Géologique Lausanne, 224:309–22Google Scholar
Guex, J. 1991. Biochronological Correlations, Springer Verlag, 252 p.Google Scholar
Hammer, O and Harper, D. A. T. 2005. Paleontological Data Analysis. Blackwell, 368 p.CrossRefGoogle Scholar
Hicks, J. F., Obradovich, J. D., and Tauxe, L. 1999. Magnetostratigraphy, isotopic age calibration and intercontinental correlation of the Redbird section of the Pierre Shale, Niobrara County, Wyoming, USA. Cretaceous Research, 20:127.Google Scholar
Hood, K. C. 1986. GRAPHCOR - Interactive graphic correlation software, version 2.2: copyright 1986–1995, KC Hood.Google Scholar
Kemple, W. G., Sadler, P. M., and Strauss, D. J. 1995. Extending graphic correlation to many dimensions: stratigraphic correlation as constrained optimization, P. 6582, in Mann, K. O., and Lane, H. R. (eds.) Graphic Correlation. Special Publications of the Society of Economic Paleontologists and Mineralogists, 53.CrossRefGoogle Scholar
Macellari, C. E. 1984. Late Cretaceous stratigraphy, sedimentology, and macropaleontology of Seymour Island, Antarctic Peninsula, , The Ohio State University, 598 p.Google Scholar
Macellari, C. E. 1986. Late Campanian-Maastrichtian ammonite fauna from Seymour Island (Antarctic Peninsula). Paleontological Society Memoir 18:155.Google Scholar
Macleod, N., and Sadler, P. M. 1995. Estimating the line of correlation, p. 5164, in Mann, K. O. and Lane, H. R., (eds.) Graphic Correlation. Special Publications of the Society of Economic Paleontologists and Mineralogists, 53.Google Scholar
Mann, K. O., and Lane, H. R. 1995. Graphic correlation: a powerful stratigraphic technique comes of age. p. 313, in Mann, K. O. and Lane, H. R. (eds.) Graphic Correlation. Special Publications of the Society of Economic Paleontologists and Mineralogists, 53.Google Scholar
Melchin, M. J., Cooper, R. A., and Sadler, P. M. 2004. The Silurian Period, p. 188201 in Gradstein, F., Ogg, J. and Smith, A. (eds.) A Geologic Time Scale 2004. Cambridge University Press.Google Scholar
Obradovich, J. D. 1988. A different perspective on glauconite for geologic time scale studies. Paleoceanography, 3:757770.CrossRefGoogle Scholar
Obradovich, J. D. 1993. A Cretaceous time scale, p. 379396, in Caldwell, W. G. E. and Kauffman, E. G. (eds.), Evolution of the Western Interior Basin. Geological Association of Canada, Special Paper 39.Google Scholar
Obradovich, J. D., and Cobban, W. A. 1975. A time scale for the Late Cretaceous of the Western Interior of North America, p. 3154, in Caldwell, W. G. E., (ed.), The Cretaceous system in the Western Interior of North America, Geological Association of Canada Special Paper 13.Google Scholar
Reineck, H.-E. 1960. Über Zeitlücken im Rezenten Flachsee Sedimenten. Geologische Rundschau, 49:149161.CrossRefGoogle Scholar
Reznick, D. N., Shaw, F. H., Rodd, F. H., and Shaw, R. G. 1997. Evaluation of the rate of evolution in natural populations of guppies (Poecilia reticulata), Science, 275:19341937.CrossRefGoogle ScholarPubMed
Ryan, P. D., Ryan, M. D. C., and Harper, D. A. T. 1999. A new approach to sedation, p. 433–49, in Harper, D. A. T. (ed.) Numerical Palaeobiology: computer-based modeling and analysis of fossils and their distributions, Chichester, UK: Wiley Google Scholar
Sadler, P. M. 1981. Sediment accumulation rates and the completeness of stratigraphic sections, Journal of Geology, 89:569584.Google Scholar
Sadler, P. M. 1993. Time scale dependence of the rates of unsteady geologic processes, p. 221228 in Armentrout, J. M., Bloch, R., Olsen, H. C., and Perkins, B. F. (eds.), Rates of Geologic Processes, SEPM Gulf Coast Section Annual Research Conference, 14.Google Scholar
Sadler, P. M. 1999. The influence of hiatuses on sediment accumulation rates, p. 1540, in Bruns, P. and Haas, H. C. (eds.), On the Determination of Sediment Accumulation Rates, Trans Tech Publications, 5.Google Scholar
Sadler, P. M. 2004. Quantitative Biostratigraphy - achieving finer resolution in Global Correlation. Annual Reviews of Earth and Planetary Sciences, v. 32, p. 187213.Google Scholar
Sadler, P. M. 2006. Constrained optimization approaches to the paleobiologic correlation and seriation problems: a users' guide and reference manual to the Conop family of programs, version 7.0, copyright 1998–2006, P. M. Sadler Google Scholar
Sadler, P. M., and Cooper, R. A. 2003 Best-fit intervals and consensus sequences: comparison of the resolving power of traditional biostratigraphy and computer-assisted correlation. in Harries, P. (ed.) High Resolution Stratigraphic Approaches in Paleontology. Kluwer-Academic Press.Google Scholar
Sadler, P. M., and Cooper, R. A., 2004, Calibration of the Ordovician Time Scale, in Webby, B., Paris, F., Droser, M.L., and. Percival, I. G. (eds.), The Great Ordovician Biodiversification Event, Columbia University Press (Critical Moments and Perspectives in Earth History and Paleobiology Series) p. 4851.Google Scholar
Savary, J., and Guex, J. 1991. Biograph: un nouveau programme de construction des correlations biochronologique basées sur les associations unitaires. Bull. Lab. Géol. Univ. Lausanne 313:317–40.Google Scholar
Savary, J., and Guex, J. 1999. Discrete biochronological scales and unitary association: description of the BioGraph computer program. Mémoire Géologique Lausanne, 34:1281.Google Scholar
Shaw, A. B. 1964. Time in Stratigraphy. New York: McGraw Hill. 365 pp.Google Scholar
Tipper, J. C. 1988. Techniques for quantitative stratigraphic correlations: a review and annotated bibliography. Geological Magazine, 125:475–94Google Scholar
Webster, M., Sadler, P. M., Kooser, M. A., and Fowler, E. 2003. Combining stratigraphic sections and museum collections to increase biostratigraphic resolution: application to Lower Cambrian trilobites from southern California, in Harries, P. (ed.) High Resolution Stratigraphic Approaches in Paleontology. Kluwer-Academic Press.Google Scholar
Zhang, T., and Plotnick, R. E. 2001. Deter-mining the line of correlation using genetic algorithms. Geological Society of America Abstracts with Programs 33(6):141 (Abstr.).Google Scholar