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Estimating Rates and Probabilities of Origination and Extinction Using Taxonomic Occurrence Data: Capture-Mark-Recapture (CMR) Approaches

Published online by Cambridge University Press:  21 July 2017

Lee Hsiang Liow  and
James D. Nichols
Lee Hsiang Liow
Affiliation:
Centre for Ecological and Evolutionary Synthesis, Department of Biology, University of Oslo, Oslo Norway
James D. Nichols
Affiliation:
Patuxent Wildlife Research Center, U.S. Geological Survey, Laurel, Maryland, U.S.A.
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Abstract

We rely on observations of occurrences of fossils to infer the rates and timings of origination and extinction of taxa. These estimates can then be used to shed light on questions such as whether extinction and origination rates have been higher or lower at different times in earth history or in different geographical regions, etc. and to investigate the possible underlying causes of varying rates. An inherent problem in inference using occurrence data is one of incompleteness of sampling. Even if a taxon is present at a given time and place, we are guaranteed to detect or sample it less than 100% of the time we search in a random outcrop or sediment sample that should contain it, either because it was not preserved, it was preserved but then eroded, or because we simply did not find it. Capture-mark-recapture (CMR) methods rely on replicate sampling to allow for the simultaneous estimation of sampling probability and the parameters of interest (e.g. extinction, origination, occupancy, diversity). Here, we introduce the philosophy of CMR approaches especially as applicable to paleontological data and questions. The use of CMR is in its infancy in paleobiological applications, but the handful of studies that have used it demonstrate its utility and generality. We discuss why the use of CMR has not matched its development in other fields, such as in population ecology, as well as the importance of modelling the sampling process and estimating sampling probabilities. In addition, we suggest some potential avenues for the development of CMR applications in paleobiology.

Type
Taxonomic Data
Information
The Paleontological Society Papers , Volume 16: Quantitative Methods in Paleobiology , October 2010 , pp. 81 - 94
Copyright
Copyright © 2010 by the Paleontological Society 

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References

Literature Cited

Akaike, H. 1973. Information theory and an extention of the maximum likelihood principle. Second International Symposium on Information Theory:267–281.Google Scholar
Alroy, J. 2000. New methods for quantifying macroevolutionary patterns and processes. Paleobiology, 26:707–733.Google Scholar
Alroy, J. 2008. Dynamics of origination and extinction in the marine fossil record. Proceedings of the National Academy of Sciences of the United States of America, 105:11536–11542.CrossRefGoogle ScholarPubMed
Alroy, J., Aberhan, M., Bottjer, D. J., Foote, M., Fursich, 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., Borrow, 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., Nurnberg, S., Powers, C. M., Sessa, J. A., Simpson, C., Tomasovych, A., and Visaggi, C. C. 2008. Phanerozoic trends in the global diversity of marine invertebrates. Science, 321:97–100.Google Scholar
Alroy, J., Marshall, C. R., Bambach, R. K., Bezusko, K., Foote, M., Fursich, 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 of the United States of America, 98:6261–6266.Google Scholar
Barry, J. C., Morgan, M. L. E., Flynn, L. J., Pilbeam, D., Behrensmeyer, A. K., Raza, S. M., Khan, I. A., Badgley, C., Hicks, J., and Kelley, J. 2002. Faunal and environmental change in the late Miocene Siwaliks of northern Pakistan. Paleobiology Memoirs, 3:1–71.Google Scholar
Brownie, C., Anderson, D. R., Burnham, R. J., and Robson, D. R. 1985. Statistical inferences from band recovery data - A handbook. United States Department of the Interior, Fish and Wildlife Service, 156.Google Scholar
Burnham, K. P., and Anderson, D. R. 2002. Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach. Springer, New York.Google Scholar
Burnham, R. J., Anderson, D. R., White, G. C., Brownie, C., and Pollock, K. H. 1987. Design and analysis of methods for fish survival experiments based on release-recapture. American Fisheries Society Monographs, 5:1–437.Google Scholar
Carothers, A. D. 1973. Effects of unequal catchability on Jolly-Seber Estimates. Biometrics, 29:79–100.Google Scholar
Carothers, A. D. 1979. Quantifying unequal catchability and its effect on survival estimates in an actual population. Journal of Animal Ecology, 48:863–869.Google Scholar
Chen, X., Melchin, M. J., Sheets, H. D., Mitchell, C. E., and Fan, J. X. 2005. Patterns and processes of latest Ordovician graptolite extinction and recovery based on data from south China. Journal of Paleontology, 79:842–861.Google Scholar
Cherns, L., and Wright, V. P. 2009. Quantifying the impacts of early diagenetic aragonite dissolution on the fossil record. Palaios, 24:756–771.Google Scholar
Connolly, S. R., and Miller, A. I. 2001a. Global Ordovician faunal transitions in the marine benthos: proximate causes Paleobiology, 27:779–795.Google Scholar
Connolly, S. R., and Miller, A. I. 2001b. Joint estimation of sampling and turnover rates from fossil databases: Capture-Mark-Recapture methods revisited. Paleobiology, 27:751–767.Google Scholar
Connolly, S. R., and Miller, A. I. 2002. Global Ordovician faunal transitions in the marine benthos: ultimate causes. Paleobiology, 28:26–40.Google Scholar
Conroy, M. J., and Nichols, J. D. 1984. Testing for variation in taxonomic extinction probabilities: A suggested methodology and some results. Paleobiology, 10:328–337.Google Scholar
Cooch, E., and White, G. 2006. Program Mark: A Gentle Introduction (http://www.phidot.org/software/mark/docs/book/).Google Scholar
Cormack, R. M. 1964. Estimates of survival from sightings of marked animals. Biometrika, 51:429 CrossRefGoogle Scholar
Crosbie, S. F., and Manly, B. F. J. 1985. Parsimonious modeling of Capture-Mark-Recapture studies. Biometrics, 41:385–398.CrossRefGoogle Scholar
Foote, M. 1988. Survivorship analysis of Cambrian and Ordovician trilobites. Paleobiology, 14:258–271.Google Scholar
Foote, M. 1994. Temporal Variation in Extinction Risk and Temporal Scaling of Extinction Metrics. Paleobiology, 20:424–444.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. 2003. Origination and extinction through the Phanerozoic: A new approach. Journal of Geology, 111:125–148.Google Scholar
Foote, M., and Raup, D. M. 1996. Fossil preservation and the stratigraphic ranges of taxa. Paleobiology, 22:121–140.Google Scholar
Gilinsky, N. L., and Good, I. J. 1991. Probabilities of origination, persistence, and extinction of families of marine invertebrate life Paleobiology, 17:145–166.Google Scholar
Jolly, G. M. 1965. Explicit estimates from capture-recapture data with both death and immigration-stochastic model. Biometrika, 52:225–247.CrossRefGoogle ScholarPubMed
Kidwell, S. M., and Holland, S. M. 2002. The quality of the fossil record: Implications for evolutionary analyses. Annual Review of Ecology and Systematics, 33:561–588.Google Scholar
Krug, A. Z., Jablonski, D., and Valentine, J. W. 2009. Signature of the End-Cretaceous Mass Extinction in the Modem Biota. Science, 323:767–771.CrossRefGoogle Scholar
Kroger, B. 2005. Adaptive evolution in Paleozoic coiled cephalopods. Paleobiology, 31:253–268.Google Scholar
Kurtén, B. 1954. Population dynamics: A new method in paleontology. Journal of Paleontology, 28:286–292.Google Scholar
Lebreton, J. D., Burnham, K. P., Clobert, J., and Anderson, D. R. 1992. Modeling survival and testing biological hypotheses using marked animals - a unified approach with case-studies. Ecological Monographs, 62:67–118.CrossRefGoogle Scholar
Link, W. A., and Barker, R. J. 2005. Modeling association among demographic parameters in analysis of open population capture-recapture data. Biometrics, 61:46–54.Google Scholar
Link, W. A., and Barker, R. J. 2006. Model weights and the foundations of multimodel inference. Ecology, 87:2626–2635.Google Scholar
Link, W. A., and Barker, R. J. 2010. Bayesian Inference with Ecological Applications. Academic press, London, Burlington, San Diego.Google Scholar
Liow, L. M., Fortelius, M., Bingham, E., Lintulaakso, K., Mannila, H., Flynn, L., and Stenseth, N. C. 2008. Higher origination and extinction rates in larger mammals. Proceedings of the National Academy of Sciences of the United States of America, 105:6097–6102.Google Scholar
Mackenzie, D., Nichols, J., Royle, A., Pollock, K., Bailey, L., and Mines, J. 2006. Occupancy Estimation and Modeling: Inferring Patterns and Dynamics of Species Occurrence Academic Press, 324 p.Google Scholar
Mackenzie, D. I. 2006. Modeling the probability of resource use: The effect of, and dealing with, detecting a species imperfectly. Journal of Wildlife Management, 70:367–374.CrossRefGoogle Scholar
Mackenzie, D. I., Nichols, J. D., Mines, J. E., Knutson, M. G., and Franklin, A. B. 2003. Estimating site occupancy, colonization, and local extinction when a species is detected imperfectly. Ecology, 84:2200–2207.Google Scholar
Mackenzie, D. I., Nichols, J. D., Lachman, G. B., Droege, S., Royle, J. A., and Langtimm, C. A. 2002. Estimating site occupancy rates when detection probabilities are less than one. Ecology, 83:2248–2255.CrossRefGoogle Scholar
Nichols, J. D., Morris, R. W., Brownie, C., and Pollock, K. H. 1986. Sources of variation in extinction rates, turnover, and diversity of marine invertebrate families during the Paleozoic. Paleobiology, 12:421–432.Google Scholar
Nichols, J. D., and Pollock, K. H. 1983. Estimating taxonomic diversity, extinction rates, and speciation rates from fossil data using capture-recapture models. Paleobiology, 9:150–163.Google Scholar
O'Brien, S., Bourou, R., and Tiandry, H. 2005. Consequences of violating the recapture duration assumption of mark-recapture models:a test using simulated and empirical data from an endangered tortoise population. Journal of Applied Ecology, 42:1096–1104.Google Scholar
Otis, D. L., Burnham, K. P., White, G. C., and Anderson, D. R. 1978. Statistical inference from capture data on closed animal populations. Wildlife Monographs, 63:3–135.Google Scholar
Pease, C. M. 1992. On the Declining Extinction and Origination Rates of Fossil Taxa. Paleobiology, 18:89–92.Google Scholar
Peters, S. E., and Ausich, W. I. 2008. A sampling-adjusted macroevolutionary history for Ordovician-Early Silurian crinoids. Paleobiology, 34:104–116.Google Scholar
Pollock, K. H., Hines, J. E., and Nichols, J. D. 1985. Goodness-of-fit tests for open capture-recapture models. Biometrics, 41:399–410.Google Scholar
Pollock, K. H., Nichols, J. D., Brownie, C., and Hines, J. E. 1990. Statistical inference for capture-recapture experiments. Wildlife Monographs(107):1–97.Google Scholar
Pollock, K. H., Solomon, D. L., and Robson, D. S. 1974. Tests for mortality and recruitment in a K-sample tag-recapture experiment. Biometrics, 30:77–87.Google Scholar
Pradel, R. 1996. Utilization of capture-mark-recapture for the study of recruitment and population growth rate. Biometrics, 52:703–709.Google Scholar
Raup, D. M. 1978. Cohort Analysis of Generic Survivorship. Paleobiology, 4:1–15.Google Scholar
Raup, D. M., and Boyajian, G. E. 1988. Patterns of generic extinction in the fossil record. Paleobiology, 14:109–125.Google Scholar
Royle, J. A., and Dorazio, R. M. 2008. Hierarchical Modeling and Inference in Ecology: The Analysis of Data from Populations, Metapopulations and Communities Academic Press, London, Amsterdam, Oxford, Burlington and San Diego.Google Scholar
Schwarz, C. J., and Arnason, A. N. 1996. A general methodology for the analysis of capture-recapture experiments in open populations. Biometrics, 52:860–873.Google Scholar
Seber, G. A. F. 1965. A note on multiple-recapture census. Biometrika, 52:249–259.Google Scholar
Simpson, G. G. 1953. The Major Features of Evolution. Simon and Schuster, New York, 434 p.Google Scholar
Smith, D. R., and Anderson, D. R. 1987. Effects of lengthy ringing periods on estimators of annual survival. Acta Ornithologica, 23:69–76.Google Scholar
Stanley, S. M. 2009. Evidence from ammonoids and conodonts for multiple Early Triassic mass extinctions. Proceedings of the National Academy of Sciences of the United States of America, 106:15264–15267.Google Scholar
Van Valen, L. 1973. A new evolutionary law. Evolutionary Theory, 1:1–30.Google Scholar
Wagner, P. J., Aberhan, M., Hendy, A., and Kiessling, W. 2007. The effects of taxonomic standardization on sampling-standardized estimates of historical diversity. Proceedings of the Royal Society B-Biological Sciences, 274:439–444.Google Scholar
White, G. C., and Burnham, K. P. 1999. Program MARK: survival estimation from populations of marked animals. Bird Study, 46:120–139.Google Scholar
Williams, B. K., Nichols, J., and Conroy, M. J. 2002. Analysis and Management of Animal Populations. Academic Press, San Diego, San Francisco, New York, Boston, London, Sydney, Tokyo, 817 p.Google Scholar