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Evaluating the accuracy of biodiversity changes through geologic times: from simulation to solution

Published online by Cambridge University Press:  15 August 2017

Corentin Gibert  and
Gilles Escarguel
Corentin Gibert
Affiliation:
Université de Lyon, Laboratoire de Géologie de Lyon, UMR 5276 CNRS, Université Lyon 1, ENS de Lyon, 2 rue Raphaël Dubois, 69622 Villeurbanne Cedex, France, and Laboratoire d’Ecologie des Hydrosystèmes Naturels et Anthropisés, UMR 5023 CNRS, Université Lyon 1, ENTPE, 6 rue Raphaël Dubois, 69622 Villeurbanne, France. E-mail: [email protected], [email protected]
Gilles Escarguel
Affiliation:
Université de Lyon, Laboratoire d’Ecologie des Hydrosystèmes Naturels et Anthropisés, UMR 5023 CNRS, Université Lyon 1, ENTPE, 6 rue Raphaël Dubois, 69622 Villeurbanne, France. E-mail: [email protected]
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Abstract

Estimating biodiversity and its variations through geologic time is a notoriously difficult task, due to several taphonomic and methodological effects that make the reconstructed signal potentially distinct from the unknown, original one. Through a simulation approach, we examine the effect of a major, surprisingly still understudied, source of potential disturbance: the effect of time discretization through biochronological construction, which generates spurious coexistences of taxa within discrete time intervals (i.e., biozones), and thus potentially makes continuous- and discrete-time biodiversity curves very different. Focusing on the taxonomic-richness dimension of biodiversity (including estimates of origination and extinction rates), our approach relies on generation of random continuous-time richness curves, which are then time-discretized to estimate the noise generated by this manipulation. A broad spectrum of data-set parameters (including average taxon longevity and biozone duration, total number of taxa, and simulated time interval) is evaluated through sensitivity analysis. We show that the deteriorating effect of time discretization on the richness signal depends highly on such parameters, most particularly on average biozone duration and taxonomic longevity because of their direct relationship with the number of false coexistences generated by time discretization. With several worst-case but realistic parameter combinations (e.g., when relatively short-lived taxa are analyzed in a long-ranging biozone framework), the original and time-discretized richness curves can ultimately show a very weak to zero correlation, making these two time series independent. Based on these simulation results, we propose a simple algorithm allowing the back-transformation of a discrete-time taxonomic-richness data set, as customarily constructed by paleontologists, into a continuous-time data set. We show that the reconstructed richness curve obtained this way fits the original signal much more closely, even when the parameter combination of the original data set is particularly adverse to an effective time-discretized reconstruction.

Type
Methods in Paleobiology
Information
Paleobiology , Volume 43 , Issue 4 , November 2017 , pp. 667 - 692
Copyright
Copyright © 2017 The Paleontological Society. All rights reserved 

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References

Literature Cited

Ager, D. V. 1976. The nature of the fossil record. Proceedings of the Geologists’ Association 87:131–159.CrossRefGoogle Scholar
Alroy, J. 1996. Constant extinction, constrained diversification, and uncoordinated stasis in North American mammals. Palaeogeography, Palaeoclimatology, Palaeoecology 127:285–311.CrossRefGoogle Scholar
Alroy, J. 1998. Equilibrial diversity dynamics in North American mammals. Pp. 233–287 in M. L. McKinney and J. A. Drake, eds. Biodiversity dynamics: turnover of populations, taxa and communities. Columbia University Press, New York.Google Scholar
Alroy, J. 2008. Dynamics of origination and extinction in the marine fossil record. Proceedings of the National Academy of Sciences USA 105:11536–11542.Google Scholar
Alroy, J. 2010a. Fair sampling of taxonomic richness and unbiased estimation of origination and extinction rates. Quantitative methods in paleobiology. Paleontological Society Papers 16:55–80.CrossRefGoogle Scholar
Alroy, J. 2010b. The shifting balance of diversity among major marine animal groups. Science 329:1191–1193.Google Scholar
Alroy, J. 2014. Accurate and precise estimates of origination and extinction rates. Paleobiology 40:374–397.Google Scholar
Alroy, J. 2015. A more precise speciation and extinction rate estimator. Paleobiology 41:633–639.Google Scholar
Alroy, J., Marshall, C. R., Bambach, R. K., Bezusko, K., Foote, M., Fürsich, F. T., Hansen, T. A., Holland, S. M., Ivany, L. C., Jablonski, D., Jacobs, D. K., Jones, D. C., Kosnik, M. A., Lidgard, S., Low, S., Miller, A. I., Novack-Gottshall, P. M., Olszewski, T. D., Patzkowsky, M. E., Raup, D. M., Roy, K., Sepkoski, J. J., Sommers, M. G., Wagner, P. J., and Webber, A.. 2001. Effects of sampling standardization on estimates of Phanerozoic marine diversification. Proceedings of the National Academy of Sciences USA 98:6261–6266.Google Scholar
Alroy, J., Aberhan, M., Bottjer, D. J., Foote, M., Fürsich, F. T., Harries, P. J., Hendy, A. J. W., Holland, S. M., Ivany, L. C., Kiessling, W., Kosnik, M. A., Marshall, C. R., McGowan, A. J., Miller, A. I., Olszewski, T. D., Patzkowsky, M. E., Peters, S. E., Villier, L., Wagner, P. J., Bonuso, N., Borkow, P. S., Brenneis, B., Clapham, M. E., Fall, L. M., Ferguson, C. A., Hanson, V. L., Krug, A. Z., Layou, K. M., Leckey, E. H., Nürnberg, S., Powers, C. M., Sessa, J. A., Simpson, C., Tomašových, A., and Visaggi, C. C.. 2008. Phanerozoic trends in the global diversity of marine invertebrates. Science 321:97–100.Google Scholar
Bambach, R. K. 1977. Species richness in marine benthic habitats through the Phanerozoic. Paleobiology 3:152–167.Google Scholar
Bambach, R. K. 1999. Energetics in the global marine fauna: a connection between terrestrial diversification and change in the marine biosphere. Geobios 32:131–144.CrossRefGoogle Scholar
Barry, J. C. 1995. Patterns of faunal turnover and diversity in the Neogene Siwaliks of Northern Pakistan. Palaeogeography, Palaeoclimatology, Palaeoecology 115:209–226.Google Scholar
Benson, B. J., Butler, R. J., Lindgren, J., and Smith, A. S.. 2009. Mesozoic marine tetrapod diversity: mass extinctions and temporal heterogeneity in geological megabiases affecting vertebrates. Proceeding of the Royal Society B 277:829–834.Google Scholar
Benton, M. J. 1993. The fossil record 2. Chapman & Hall, London.Google Scholar
Benton, M. J. 2010. Naming dinosaur species: the performance of prolific authors. Journal of Vertebrate Paleontology 30:1478–1485.CrossRefGoogle Scholar
Benton, M. J., and Ayala, F. J.. 2003. Dating the tree of life. Science 300:1698–1700.Google Scholar
Benton, M. J., Dunhill, A. M., Graeme, G. T., and Marx, F. G.. 2011. Assessing the quality of the fossil record: insight from vertebrates. Geological Society of London Special Publication 358:63–94.CrossRefGoogle Scholar
Buckman, S. S. 1893. The Bajocian of the Sherborne District: its relation to subjacent and superjacent strata. Quarterly Journal of the Geological Society 49:479–522.Google Scholar
Caley, M. J., and Schluter, D.. 1997. The relationship between local and regional diversity. Ecology 78:70–80.Google Scholar
Cope, J. C. W. 1993. High resolution biostratigraphy. Geological Society of London Special Publication 70:257–265.Google Scholar
Cope, J. C. W. 1994. The nature and resolution of Jurassic Ammonite biozones. Geobios 17:127–132.Google Scholar
Crampton, J. S., Beu, A. G., Cooper, R. A., Jones, C. M., Marshall, B., and Maxwell, P. A.. 2003. Estimating the rock volume bias in paleobiodiversity studies. Science 301:358–360.Google Scholar
d’Orbigny, A. 1842–1849. Paléontologie française, Vol 1. Terrains jurassiques. Victor Masson, Paris.Google Scholar
Escarguel, G., and Bucher, H.. 2004. Counting taxonomic richness from discrete biochronozones of unknown duration: a simulation. Palaeogeography, Palaeoclimatology, Palaeoecology 202:181–208.Google Scholar
Escarguel, G., and Legendre, S.. 2006. New methods for analysing deep-time meta-community dynamics and their application to the Paleogene mammals from the Quercy and Limagne area (Massif Central, France). Strata 13:245–273.Google Scholar
Escarguel, G., Legendre, S., and Sigé, B.. 2008. Unearthing deep-time biodiversity changes: the Palaeogene mammalian metacommunity of the Quercy and Limagne area (Massif Central, France). Comptes Rendus Geoscience 340:602–614.Google Scholar
Escarguel, G., Fara, E., Brayard, A., and Legendre, S.. 2011. Biodiversity is not (and never has been) a bed of roses!. Comptes Rendus Biologies 334:351–359.Google Scholar
Foote, M. 1994. Temporal variation in extinction risk and temporal scaling of extinction metrics. Paleobiology 20:424–444.Google Scholar
Foote, M. 2000. Origination and extinction components of taxonomic diversity: general problems. Paleobiology 26:74–102.Google Scholar
Foote, M. 2001. Inferring temporal patterns of preservation, origination, and extinction from taxonomic survivorship analysis. Paleobiology 27:602–630.Google Scholar
Foote, M. 2005. Pulsed origination and extinction in the marine realm. Paleobiology 31:6–20.Google Scholar
Foote, M. 2007. Extinction and quiescence in marine animal genera. Paleobiology 33:261–272.Google Scholar
Guex, J. 1991. Biochronological correlations. Springer-Verlag, Berlin.Google Scholar
Gradstein, F. M., Ogg, J. G., Schmitz, M., and Ogg, G., eds. 2012. The geologic time scale 2012. Elsevier, Amsterdam.Google Scholar
Hallam, A., and Wignall, P. B.. 1997. Mass extinctions and their aftermath. Oxford University Press, New York.Google Scholar
Harland, W. B., Holland, C. H., House, M. R., Hughes, N. F., Reynolds, A. B., Rudwick, M. J. S., Satterthwaite, G. E., Tarlo, L. B. H., and Willey, E. C.. 1967. The fossil record; a symposium with documentation. Geological Society of London, London.Google Scholar
Hedberg, H. D., ed. 1976. International stratigraphic guide. Wiley, New York.Google Scholar
Huber, B. T. 1992. Biogeographic patterns in the Cretaceous Ocean paleobiogeography of Campanian–Maastrichtian foraminifera in the southern high latitudes. Palaeogeography, Palaeoclimatology, Palaeoecology 92:325–360.Google Scholar
Jablonski, D. 1986. Background and mass extinctions: the alternation of macroevolutionary regimes. Science 231:129–133.Google Scholar
Jablonski, D. 2005. Mass extinctions and macroevolution. Paleobiology 31:192–210.CrossRefGoogle Scholar
Janis, C. M., Scott, K. M., and Jacobs, L. L., eds. 1998. Evolution of Tertiary mammals of North America, Vol. 1. Terrestrial carnivores, ungulates, and ungulate like mammals. Cambridge University Press, New York.Google Scholar
Janis, C. M., Gunnell, G. F., and Uhen, M. D., eds. 2008. Evolution of Tertiary mammals of North America, Vol. 2. Small mammals, xenarthrans, and marine mammals. Cambridge University Press, New York.Google Scholar
Koch, C. F. 1978. Bias in the published fossil record. Paleobiology 4:367–372.Google Scholar
Lu, P. J., Yogo, M., and Marshall, C. R.. 2006. Phanerozoic marine biodiversity dynamics in light of the incompleteness of the fossil record. Proceedings of the National Academy of Sciences USA 103 :2736–2739.Google Scholar
O’Dogherty, L., Carter, E. S., Dumitrica, P., Goriččan, Š., Wever, P. D., Hungerbühler, A., Bandini, A. N., and Takemura, A.. 2009a. Catalogue of Mesozoic radiolarian genera. Part 1: Triassic. Geodiversitas 31:213–270.Google Scholar
O’Dogherty, L., Carter, E. S., Dumitrica, P., Goriččan, Š., Wever, P. D., Bandini, A. N., Baumgartner, P. O., and Matsuoka, A.. 2009b. Catalogue of Mesozoic radiolarian genera. Part 2: Jurassic–Cretaceous. Geodiversitas 31:271–356.Google Scholar
Oppel, A. 1856–1858. Die Juraformation Englands, Frankreichs und südwestlichen Deutschlands. Württemberger Naturforschende Jahreshefte 12–14. Ebner & Seubert, Stuttgart.Google Scholar
Phillips, J. 1860. Life on the Earth: its origin and succession. Macmillan, Cambridge.Google Scholar
Raup, D. M. 1972. Taxonomic diversity during the Phanerozoic. Science 177:1065–1071.Google Scholar
Raup, D. M. 1976. Species diversity in the Phanerozoic: an interpretation. Paleobiology 2:289–297.Google Scholar
Raup, D. M. 1991a. A kill curve for Phanerozoic marine species. Paleobiology 17:37–48.CrossRefGoogle ScholarPubMed
Raup, D. M. 1991b. Extinction: bad genes or bad luck?. New York: Norton.Google ScholarPubMed
Raup, D. M., and Sepkoski, J. J.. 1984. Periodicity of extinctions in the geologic past. Proceedings of the National Academy of Sciences USA 81:801–805.Google Scholar
Rey, J. 1997. Stratigraphie, terminologie française. Bulletin Centres Recherche Exploration-Production 19.Google Scholar
Ricklefs, R. E. 1987. Community diversity: relative roles of local and regional processes. Science 235:167–171.Google Scholar
Ricklefs, R. E. 2004. A comprehensive framework for global patterns in biodiversity. Ecology Letters 7:1–15.Google Scholar
Rosenzweig, M. L. 1995. Species diversity in space and time. Cambridge University Press, Cambridge.Google Scholar
Sadler, P. M., and Cooper, R. A.. 2008. Best-fit intervals and consensus sequences. Comparison of the resolving power of traditional biostratigraphy and computer-assisted correlation. P. J. Harries, ed. High-resolution approaches in stratigraphic paleontology 21:49–94. Springer, Netherlands.Google Scholar
Sepkoski, J. J. 1978. A kinetic model of Phanerozoic taxonomic diversity I. Analysis of marine orders. Paleobiology 4:223–251.Google Scholar
Sepkoski, J. J. 1981. A factor analytic description of the Phanerozoic marine fossil record. Paleobiology 7:36–53.Google Scholar
Sepkoski, J. J. 1993. Ten years in the library: new data confirm paleontological patterns. Paleobiology 19:43–51.Google Scholar
Sepkoski, J. J. 2002. A compendium of fossil marine animal genera. Bulletins of American Paleontology 363.Google Scholar
Sepkoski, J. J., Bambach, R. K., Raup, D. M., and Valentine, J. W.. 1981. Phanerozoic marine diversity and the fossil record. Nature 293:435–437.Google Scholar
Signor, P. W. 1978. Richness in the Phanerozoic: an investigation of sampling effects. Paleobiology 4:394–406.Google Scholar
Signor, P. W., and Lipps, J. H.. 1982. Sampling bias, gradual extinction patterns and catastrophes in the fossil record. Geological Society of America Special Paper 190:291–296.Google Scholar
Smith, A. B. 2001. Large–scale heterogeneity of the fossil record: implications for Phanerozoic biodiversity studies. Philosophical Transactions of the Royal Society of London B 356:351–367.CrossRefGoogle ScholarPubMed
Smith, W. 1816. Strata identified by organized fossils. Giuseppe Castrovilli, London.Google Scholar
Van Valen, L. 1973. A new evolutionary law. Evolutionary Theory 1:1–30.Google Scholar
Wiens, J. A. 1989. Spatial scaling in ecology. Functional Ecology 3:385–397.Google Scholar
Woodburne, M. O. 2012. Late Cretaceous and Cenozoic mammals of North America: biostratigraphy and geochronology. Columbia University Press, New York.Google Scholar