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Spectral ordering and biochronology of european fossil mammals

Published online by Cambridge University Press:  08 April 2016

Mikael Fortelius ,
Aristides Gionis ,
Heikki Mannila  and
Jukka Jernvall
Mikael Fortelius*
Affiliation:
Department of Geology and Institute of Biotechnology, Post Office Box 64, FIN-00014 University of Helsinki, Finland. E-mail: [email protected]
Aristides Gionis
Affiliation:
HIIT Basic Research Unit, Department of Computer Science, Post Office Box 68, FIN-00014 University of Helsinki, Finland
Heikki Mannila
Affiliation:
HIIT Basic Research Unit, Department of Computer Science, Post Office Box 68, FIN-00014 University of Helsinki, Finland
Jukka Jernvall
Affiliation:
Developmental Biology Program, Institute of Biotechnology, Post Office Box 56, FIN-00014 University of Helsinki, Helsinki, Finland Department of Ecology and Systematics, Post Office Box 65, FIN-00014 University of Helsinki, Finland
*
∗Corresponding author
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Abstract

Spectral algorithms have been shown to work well in a wide range of situations that involve the task of ordering. When applied to the localities of a set of European Neogene land mammal taxa, spectral ordering relies almost entirely on the most common genera, depends on connectivity more than on length of taxon lists, and is robust to noise from rarer and less connected taxa. The spectral coefficients for localities are highly correlated with known geochronological ages. Although elementary compared with more sophisticated biochronological tools, spectral ordering allows a fast and standardized way to generate biochronological ordering of localities when other information than faunal lists is lacking. Compared with the conventional mammal Neogene (MN) units, spectral ordering of localities appears to lack distinct temporal boundaries in taxon content and render a much lower count of Lazarus events. If, as seems to be the case, biochronology depends mainly on the most common taxa and if evolutionary change is also most clearly reflected in them, then the main evolutionary patterns should be detectable at a modest level of sampling.

Type
Articles
Information
Paleobiology , Volume 32 , Issue 2 , Spring 2006 , pp. 206 - 214
Copyright
Copyright © The Paleontological Society 

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References

Literature Cited

Alroy, J. 1992. Conjunction among taxonomic distributions and the Miocene mammalian biochronology of the Great Plains. Paleobiology 18:326–343.CrossRefGoogle Scholar
Alroy, J. 1994. Appearance event ordination: a new biochronologic method. Paleobiology 20:191–207.CrossRefGoogle Scholar
Alroy, J. 1998. Diachrony of mammalian appearance events: implications for biochronology. Geology 26:23–26.2.3.CO;2>CrossRefGoogle Scholar
Alroy, J. 2000. New methods for quantifying macroevolutionary patterns and processes. Paleobiology 26:707–733.2.0.CO;2>CrossRefGoogle Scholar
Alroy, J. J., Bernor, R. L., Fortelius, M., and Werdelin, L. 1998. The MN system: regional or continental? Mitteilungen der Bayerischen Staatssammlung von Paläontologie und historische Geologie 38:243–258.Google Scholar
Atkins, J. E., Boman, E. G., and Hendrickson, B. 1999. A spectral algorithm for seriation and the consecutive ones problem. SIAM Journal on Computing 28:297–310.CrossRefGoogle Scholar
Azanza, B., Alberdi, M. T., Cerdeño, E., and Prado, J. L. 1997. Biochronology from latest Miocene to middle Pleistocene in the western Mediterranean area: a multivariate approach. Pp. 567–574 in Aguilar, J.-P., Legendre, S., and Michaux, J., eds. Actes du Congrès BiochroM '97. Mémoires et Travaux de l'Institut de Montpellier, Montpellier.Google Scholar
Chung, F. R. K. 1997. Spectral graph theory. CBMS Regional Conference Series in Mathematics no. 92. American Mathematical Society, Providence, R.I. Google Scholar
De Bruijn, H., Daams, R., Daxner-Höck, G., Fahlbusch, V., Ginsburg, L., Mein, P., and Morales, J. 1992. Report of the RCMNS working group on fossil mammals, Reisensburg 1990. Newsletters in Stratigraphy 26(2/3):65–118.CrossRefGoogle Scholar
Duda, R., Hart, P., and Stork, D. 2001. Pattern classification. Wiley, New York.Google Scholar
Fahlbusch, V. 1976. Report on the International Symposium on Mammal Stratigraphy of the European Tertiary. Newsletters in Stratigraphy 5:160–167.CrossRefGoogle Scholar
Fahlbusch, V. 1991. The meaning of MN-zonation: considerations for a subdivision of the European continental Tertiary using mammals. Newsletters in Stratigraphy 24:159–173.CrossRefGoogle Scholar
Guex, J., and Davaud, E. 1984. Unitary associations method: the use of graph theory and computer algorithm. Computer and Geoscience 10:69–96.CrossRefGoogle Scholar
Hagen, L., and Kahng, A. B. 1992. New spectral methods for ratio cut partitioning and clustering. IEEE Transactions on Computed Aided Design 11:1074–1085, 1992.CrossRefGoogle Scholar
Halekoh, U., and Vach, W. 2004. A Bayesian approach to seriation problems in archaeology. Computational Statistics and Data Analysis 45:651–673.CrossRefGoogle Scholar
Hooker, J. J. 1996. Mammalian biostratigraphy across the Paleocene-Eocene boundary in the Paris, London and Belgian basins. In Knox, R. W. O. B., Corfield, R. M., and Dunay, R. E., eds. Correlation of the Early Paleogene in northwestern Europe. Geological Society of London Special Publication 101:205–218.CrossRefGoogle Scholar
Hooker, J. J., and Weidmann, M. 2000. The Eocene mammal faunas of Mormont, Switzerland. Schweizerische Paläontologische, Abhandlungen 120:1–143.Google Scholar
Jernvall, J., and Fortelius, M. 2002. Common mammals drive the evolutionary increase of hypsodonty in the Neogene. Nature 417:538–540.CrossRefGoogle ScholarPubMed
Koufos, G. 2004. Late Miocene mammal events and biostratigraphy in the Eastern Mediterranean. Pp. 343–372 in Reumer, J. W. F. and Wessels, W., eds. Distribution and migration of Tertiary mammals in Eurasia: a volume in honour of Hans de Bruijn. Deinsea, Utrecht, The Netherlands. Google Scholar
Lindsay, E., and Tedford, R. 1989. Development and application of land mammal ages in North America and Europe, a comparison. Pp. 601–624 in Lindsay, et al. 1989.Google Scholar
Lindsay, E. H., Fahlbusch, V., and Mein, P., eds. 1989. European Neogene mammal chronology. Plenum, New York.CrossRefGoogle Scholar
Martinez, J. N. 1995. Biochronologie et méthode de parcimonie. Bulletin de la Société Géologique de France 166:517–526.CrossRefGoogle Scholar
Mein, P. 1975. Résultats du groupe de travail des vertébrés: Biozonation du Neogène méditerranéen á partir des Mammifères. Pp. 78–81 in Senes, J., ed. Report on activity of the RCMNS Working Group (1971–1975). Bratislava.Google Scholar
Mein, P. 1989. Updating of MN zones. Pp. 73–90 in Lindsay, et al. 1989.Google Scholar
Savary, J., and Guex, J. 1991. BioGraph, un nouveau programme de construction des corrélations biochronologiques basées sur les associations unitaires. Bulletin du Laboratoire Géologique de la Université de Lausanne 313:317–340.Google Scholar
Savary, J., and Guex, J. 1999. Discrete biochronological scales and unitary associations: description of the BioGraph computer programme. Mémoires de Géologie (Lausanne) 34:1–282.Google Scholar
Sen, S., Koufos, G., Kostopoulos, D., and De Bonis, L. 2000. Magnetostratigraphy of late Miocene continental deposits of the Lower Axios valley, Macedonia, Greece. Geological Society of Greece Special Publication 9:197–206.Google Scholar
Spielman, D. A., and Teng, S.-H. 1996. Spectral partitioning works: planar graphs and finite element meshes. Proceedings of the 37th Annual Symposium on Foundations of Computer Science, pp. 96–105. ACM Press, New York.Google Scholar
Steininger, F. F. 1999. Chronostratigraphy, geochronology and biochronology of the Miocene “European Land Mammal Mega-Zones” (ELMMZ) and the Miocene “Mammal-Zones (MN-Zones).” Pp. 9–24 in Rössner, G. E. and Heissig, K., eds. The Miocene land mammals of Europe. Dr. Friedrich Pfeil, Munich.Google Scholar
Steininger, F. F., Bernor, R. L., and Fahlbusch, V. 1989. European Neogene marine/continental chronologic correlations. Pp. 15–46 in Lindsay, et al. 1989.Google Scholar
Steininger, F. F., Berggren, W. A., Kent, D. V., Bernor, R. L., Sen, S., and Agustí, J. 1996. Circum-Mediterranean Neogene (Miocene-Pliocene) marine-continental chronologic correlations of European mammal units. Pp. 7–46 in Bernor, R. L., Fahlbusch, V., and Mittmann, H.-W., eds. The evolution of western Eurasian Neogene mammal faunas. Columbia University Press, New York.Google Scholar
Thaler, L. 1966. Les rongeurs fossiles du Bas-Languedoc dans leur rapports avec l'histoire des faunes et la stratigraphie du Tertiaire d'Europe. Mémoires de la Muséum National d'Histoire Naturelle C 17:1–295.Google Scholar
Vermeij, G. J., and Herbert, G. S. 2004. Measuring relative abundance in fossil and living assemblages. Paleobiology 30:1–4.2.0.CO;2>CrossRefGoogle Scholar
Williams, H. S. 1901. Discrimination of time value in geology. Journal of Geology 9:570–585.CrossRefGoogle Scholar
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