Skip to main content
SpringerLink
Log in

Radiocarbon Nomenclature, Theory, Models, and Interpretation: Measuring Age, Determining Cycling Rates, and Tracing Source Pools

  • Chapter
  • First Online:
Radiocarbon and Climate Change

Abstract

This chapter introduces the processes that cause isotopes of carbon (C) to be distributed among different Earth system components. This chapter reviews commonly used nomenclature for reporting radiocarbon (14C) data, which differ according to the application. Finally, theory and models are introduced that are commonly used for interpreting 14C data in terms of its three major uses: (1) determining the time elapsed since C in a closed system was isolated from the atmosphere; (2) estimating the rate of exchange of C between reservoirs in open systems; and (3) estimating the contributions of different C sources to a mixture.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 139.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 179.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 179.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Bronk Ramsey, C., Dee, M., Lee, S., Nakagawa, T., and Staff, R. (2010). Developments in the calibration and modelling of radiocarbon dates. Radiocarbon 52(3): 953–961.

    Google Scholar 

  • Bruun, S., J. Six, and L.S. Jensen. 2004. Estimating vital statistics and age distributions of measurable soil organic carbon fractions based on their pathway of formation and radiocarbon content. Journal of Theoretical Biology 230: 241–250.

    Article  Google Scholar 

  • Coplen, T.B., W.A. Brand, M. Gehre, M. Gröning, H.A. Meijer, B. Toman, and R.M. Verkouteren. 2006. New guidelines for δ 13C measurements. Analytical Chemistry 78: 2439–2441.

    Article  Google Scholar 

  • Dioumaeva, I., S. Trumbore, E.A.G. Schuur, M.L. Goulden, M. Litvak, and A.I. Hirsch. 2002. Decomposition of peat from upland boreal forest: temperature dependence and sources of respired carbon. Journal of Geophysical Research-Atmospheres 108.

    Google Scholar 

  • Donahue, D.J., T.W. Linick, and A.J.T. Jull. 1990. Isotope ratio and background corrections for accelerator mass spectrometry radiocarbon measurements. Radiocarbon 32: 135–142.

    Google Scholar 

  • Dorrepaal, E., S. Toet, R.S.P. van Logtestijn, E. Swart, M.J. van de Weg, T.V. Callaghan, and R. Aerts. 2009. Carbon respiration from subsurface peat accelerated by climate warming in the subarctic. Nature 460: 616-U679.

    Article  Google Scholar 

  • Dutta, K., E.A.G. Schuur, J.C. Neff, and S.A. Zimov. 2006. Potential carbon release from permafrost soils of northeastern Siberia. Global Change Biology 12: 2336–2351.

    Article  Google Scholar 

  • Eriksson, E. 1971. Compartment models and reservoir theory. Annual Review of Ecology and Systematics 2: 67–84.

    Article  Google Scholar 

  • Faure, G. 1986. Principles of Isotope Geology, 2nd ed. New York: Wiley.

    Google Scholar 

  • Galli, I., S. Bartalini, S. Borri, P. Cancio, D. Mazzotti, P. De Natale, and G. Giusfredi. 2011. Molecular gas sensing below parts per trillion: radiocarbon-dioxide optical detection. Physical Review Letters 107: 270802.

    Article  Google Scholar 

  • Gaudinski, J.B., S.E. Trumbore, E.A. Davidson, and S. Zheng. 2000. Soil carbon cycling in a temperate forest: radiocarbon-based estimates of residence times, sequestration rates and partitioning fluxes. Biogeochemestry 51: 33–69.

    Article  Google Scholar 

  • Godwin, H. 1962. Half-life of radiocarbon. Nature 195: 984.

    Article  Google Scholar 

  • Hoefs, J. 2009. Stable Isotope Geochemistry. 6th edition. Springer.

    Google Scholar 

  • IAEA 2001. Environmental Isotopes in the Hydrological Cycle: Principles and Applications, vol. 1, p. 97, Fig. 7.5.

    Google Scholar 

  • Kendall, C., and J.J. McDonnell (eds.). 1998. Isotope tracers in catchment hydrology. Amsterdam: Elsevier Science.

    Google Scholar 

  • Levin, I., T. Naegler, B. Kromer, M. Diehl, R.J. Francey, A.J. Gomez-Pelaez, L.P. Steele, D. Wagenbach, R. Weller, and D.E. Worthy. 2010. Observations and modelling of the global distribution and long-term trend of atmospheric 14CO2. Tellus B 62: 26–46.

    Article  Google Scholar 

  • Manzoni, S., G.G. Katul, and A. Porporato. 2009. Analysis of soil carbon transit times and age distributions using network theories. Journal of Geophysical Research 114.

    Google Scholar 

  • Mook, W.G., Jc Bommerso, and Wh Staverma. 1974. Carbon isotope fractionation between dissolved bicarbonate and gaseous carbon dioxide. Earth and Planetary Science Letters 22: 169–176.

    Article  Google Scholar 

  • Mook, W.G.E. 2000. Environmental Isotopes in the Hydrological Cycle: Principles and Applications, Vol I, Introduction, Theory, and Methods. Page 291 in I. H. Programme, editor. UNESCO/IAEA, Paris.

    Google Scholar 

  • Moore, J.W., and B.X. Semmens. 2008. Incorporating uncertainty and prior information into stable isotope mixing models. Ecology Letters 11: 470–480.

    Article  Google Scholar 

  • Olsson, I. 1970. The use of oxalic acid as a standard. Page 17 in Radiocarbon Variations and Absolute Chronology, Nobel Symposium.

    Google Scholar 

  • Parnell, A.C., R. Inger, S. Bearhop, and A.L. Jackson. 2010. Source partitioning using stable isotopes: coping with too much variation. Plos One 5.

    Google Scholar 

  • Phillips, D.L. 2001. Mixing models in analyses of diet using multiple stable isotopes: a critique. Oecologia 127: 166–170.

    Article  Google Scholar 

  • Phillips, D.L., and J.W. Gregg. 2001. Uncertainty in source partitioning using stable isotopes. Oecologia 127: 171–179.

    Article  Google Scholar 

  • Phillips, D.L., and J.W. Gregg. 2003. Source partitioning using stable isotopes: coping with too many sources. Oecologia 136: 261–269.

    Article  Google Scholar 

  • Phillips, D.L., S.D. Newsome, and J.W. Gregg. 2005. Combining sources in stable isotope mixing models: alternative methods. Oecologia 144: 520–527.

    Article  Google Scholar 

  • Reimer, P.J. 2013. IntCal13 and Marine13 radiocarbon age calibration curves 0-50,000 years CAL BP. Radiocarbon 55: 1869–1887.

    Article  Google Scholar 

  • Reimer, P.J., M.G.L. Baillie, E. Bard, A. Bayliss, J.W. Beck, P.G. Blackwell, C.B. Ramsey, C.E. Buck, G.S. Burr, R.L. Edwards, M. Friedrich, P.M. Grootes, T.P. Guilderson, I. Hajdas, T.J. Heaton, A.G. Hogg, K.A. Hughen, K.F. Kaiser, B. Kromer, F.G. McCormac, S.W. Manning, R.W. Reimer, D.A. Richards, J.R. Southon, S. Talamo, C.S.M. Turney, J. van der Plicht, and C.E. Weyhenmeye. 2009. IntCal09 and Marine09 radiocarbon age calibration curves, 0-50,000 years cal bp. Radiocarbon 51: 1111–1150.

    Google Scholar 

  • Rodhe, H. 2000. Modeling Biogeochemical Cycles. In International geophysics, eds. R.J.C.H.R. Michael C. Jacobson and H.O. Gordon. Academic Press.

    Google Scholar 

  • Rundel, P.W., J.R. Ehleringer, and K.A. Nagy (eds.). 1989. Stable isotopes in ecological research. New York: Springer.

    Google Scholar 

  • Schuur, E.A.G., S.E. Trumbore, M.C. Mack, and J.W. Harden. 2003. Isotopic composition of carbon dioxide from a boreal forest fire: inferring carbon loss from measurements and modeling. Global Biogeochemical Cycles 17.

    Google Scholar 

  • Semmens, B.X., J.W. Moore, and E.J. Ward. 2009. Improving Bayesian isotope mixing models: a response to Jackson et al. (2009). Ecology Letters 12:E6–E8.

    Google Scholar 

  • Sierra, C.A., M. Muller, and S.E. Trumbore. 2012. Models of soil organic matter decomposition: the SoilR package, version 1.0. Geoscientific Model Development 5: 1045–1060.

    Article  Google Scholar 

  • Stuiver, M., and H.A. Polach. 1977. Reporting of C-14 data—discussion. Radiocarbon 19: 355–363.

    Google Scholar 

  • Stuiver, M., and P.D. Quay. 1981. Atmospheric C-14 changes resulting from fossil fuel CO2 release and cosmic ray flux variability. Earth and Planetary Science Letters 53: 349–362.

    Article  Google Scholar 

  • Torn, M.S., C.W. Swanston, C. Castanha, and S.E. Trumbore. 2009. Storage and turnover of organic matter in soil. In Biophysico-chemical processes involving natural nonliving organic matter in environmental systems, 219–272. Wiley.

    Google Scholar 

  • Urton, E.J.M., and K.A. Hobson. 2005. Intrapopulation variation in gray wolf isotope (delta N-15 and delta C-13) profiles: implications for the ecology of individuals. Oecologia 145: 317–326.

    Article  Google Scholar 

  • Wang, Y., R. Amundson, and S. Trumbore. 1994. A model for soil (CO2)-C14 and its implications for using C-14 to date pedogenic carbonate. Geochimica et Cosmochimica Acta 58: 393–399.

    Article  Google Scholar 

  • Wanninkhof, R. 1985. Kinetic fractionation of the carbon isotopes C-13 and C-12 during transfer of CO2 from air to seawater. Tellus Series B-Chemical and Physical Meteorology 37: 128–135.

    Article  Google Scholar 

  • Ward, E.J., B.X. Semmens, and D.E. Schindler. 2010. Including source uncertainty and prior information in the analysis of stable isotope mixing models. Environmental Science and Technology 44: 4645–4650.

    Article  Google Scholar 

  • Yu, S.Y., J. Shen, and S.M. Colman. 2007. Modeling the radiocarbon reservoir effect in lacustrine systems. Radiocarbon 49: 1241–1254.

    Google Scholar 

  • Zare, R.N. 2012. Analytical chemistry: ultrasensitive radiocarbon detection. Nature 482: 312–313.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Max Planck Institute for Biogeochemistry, Jena, Germany

    S. E. Trumbore & C. A. Sierra

  2. Department of Earth System Science, University of California Irvine, Irvine, CA, USA

    S. E. Trumbore

  3. Department of Biology, University of Florida, Gainesville, FL, USA

    C. E. Hicks Pries

  4. Climate and Ecological Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA

    C. E. Hicks Pries

Authors
  1. S. E. Trumbore
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. C. A. Sierra
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. C. E. Hicks Pries
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Cetr for Ecosys Sci & Society and Dept, Northern Arizona University, Gainesville, Florida, USA

    Edward A.G. Schuur

  2. Earth System Science, University of California Irvine, Irvine, California, USA

    Ellen Druffel

  3. Max Planck Inst for Biogeochemistry, Jena, Germany

    Susan E. Trumbore

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this chapter

Cite this chapter

Trumbore, S.E., Sierra, C.A., Hicks Pries, C.E. (2016). Radiocarbon Nomenclature, Theory, Models, and Interpretation: Measuring Age, Determining Cycling Rates, and Tracing Source Pools . In: Schuur, E., Druffel, E., Trumbore, S. (eds) Radiocarbon and Climate Change. Springer, Cham. https://doi.org/10.1007/978-3-319-25643-6_3

Download citation

Publish with us

Policies and ethics

Search

Navigation