Subjects

Abstract

The response of the terrestrial carbon cycle to climate change is among the largest uncertainties affecting future climate change projections1,2. The feedback between the terrestrial carbon cycle and climate is partly determined by changes in the turnover time of carbon in land ecosystems, which in turn is an ecosystem property that emerges from the interplay between climate, soil and vegetation type3,4,5,6. Here we present a global, spatially explicit and observation-based assessment of whole-ecosystem carbon turnover times that combines new estimates of vegetation and soil organic carbon stocks and fluxes. We find that the overall mean global carbon turnover time is  years (95 per cent confidence interval). On average, carbon resides in the vegetation and soil near the Equator for a shorter time than at latitudes north of 75° north (mean turnover times of 15 and 255 years, respectively). We identify a clear dependence of the turnover time on temperature, as expected from our present understanding of temperature controls on ecosystem dynamics. Surprisingly, our analysis also reveals a similarly strong association between turnover time and precipitation. Moreover, we find that the ecosystem carbon turnover times simulated by state-of-the-art coupled climate/carbon-cycle models vary widely and that numerical simulations, on average, tend to underestimate the global carbon turnover time by 36 per cent. The models show stronger spatial relationships with temperature than do observation-based estimates, but generally do not reproduce the strong relationships with precipitation and predict faster carbon turnover in many semi-arid regions. Our findings suggest that future climate/carbon-cycle feedbacks may depend more strongly on changes in the hydrological cycle than is expected at present and is considered in Earth system models.

Access optionsAccess options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

References

  1. 1.

    et al. Climate-carbon cycle feedback analysis: results from the (CMIP)-M-4 model intercomparison. J. Clim. 19, 3337–3353 (2006)

  2. 2.

    et al. in Climate Change 2013: The Physical Science Basis (eds et al.) 465–570 (Cambridge Univ. Press, 2013)

  3. 3.

    , & The potential response of terrestrial carbon storage to changes in climate and atmospheric CO2. Clim. Change 35, 199–227 (1997)

  4. 4.

    et al. Evaluation of ecosystem dynamics, plant geography and terrestrial carbon cycling in the LPJ dynamic global vegetation model. Glob. Change Biol. 9, 161–185 (2003)

  5. 5.

    Age of soil organic matter and soil respiration: radiocarbon constraints on belowground C dynamics. Ecol. Appl. 10, 399–411 (2000)

  6. 6.

    et al. Carbon residence time dominates uncertainty in terrestrial vegetation responses to future climate and atmospheric CO2. Proc. Natl Acad. Sci. USA. 111, 3280–3285 (2014)

  7. 7.

    et al. in Climate Change 2007: The Physical Science Basis (eds et al.) 499–587 (Cambridge Univ. Press, 2007)

  8. 8.

    & Terrestrial ecosystem carbon dynamics and climate feedbacks. Nature 451, 289–292 (2008)

  9. 9.

    et al. Evaluating the land and ocean components of the global carbon cycle in the CMIP5 earth system models. J. Clim. 26, 6801–6843 (2013)

  10. 10.

    in Global Biogeochemical Cycles (eds , , & ) Ch. 4 (Academic, 1992)

  11. 11.

    , , & in Amazonia and Global Change (eds , , & ) 355–372 (American Geophysical Union, 2009)

  12. 12.

    Carbon respired by terrestrial ecosystems — recent progress and challenges. Glob. Change Biol. 12, 141–153 (2006)

  13. 13.

    in The Carbon Cycle and Atmospheric CO: Natural Variations, Archean to Present (eds & ) 5–59 (American Geophysical Union, 1985)

  14. 14.

    , , & Temperature dependence of organic matter decomposition: a critical review using literature data analyzed with different models. Biol. Fertil. Soils 27, 258–262 (1998)

  15. 15.

    & Temperature sensitivity of soil carbon decomposition and feedbacks to climate change. Nature 440, 165–173 (2006)

  16. 16.

    & Temperature-associated increases in the global soil respiration record. Nature 464, 579–582 (2010)

  17. 17.

    & Nutrient additions to a tropical rain forest drive substantial soil carbon dioxide losses to the atmosphere. Proc. Natl Acad. Sci. USA 103, 10316–10321 (2006)

  18. 18.

    Revised estimates of the annual net flux of carbon to the atmosphere from changes in land use and land management 1850–2000. Tellus B 55, 378–390 (2003)

  19. 19.

    et al. Large-scale impoverishment of Amazonian forests by logging and fire. Nature 398, 505–508 (1999)

  20. 20.

    , , & The role of fire disturbance for global vegetation dynamics: coupling fire into a dynamic global vegetation model. Glob. Ecol. Biogeogr. 10, 661–677 (2001)

  21. 21.

    & Constraints on global fire activity vary across a resource gradient. Ecology 92, 121–132 (2011)

  22. 22.

    Micro-site effects of trees and shrubs in dry savannas. J. Veg. Sci. 3, 337–344 (1992)

  23. 23.

    & How tree cover influences the water-balance of Mediterranean rangelands. Ecology 74, 570–582 (1993)

  24. 24.

    Influences of trees on savanna productivity — tests of shade, nutrients, and tree-grass competition. Ecology 75, 922–932 (1994)

  25. 25.

    et al. The biogeochemistry of carbon at Hubbard Brook. Biogeochemistry 75, 109–176 (2005)

  26. 26.

    et al. Modelling the role of agriculture for the 20th century global terrestrial carbon balance. Glob. Change Biol. 13, 679–706 (2007)

  27. 27.

    et al. Causes of variation in soil carbon simulations from CMIP5 Earth system models and comparison with observations. Biogeosciences 10, 1717–1736 (2013)

  28. 28.

    & Permafrost-carbon complexities. Nature Geosci. 6, 675–676 (2013)

  29. 29.

    et al. On the formation of high-latitude soil carbon stocks: Effects of cryoturbation and insulation by organic matter in a land surface model. Geophys. Res. Lett. 36, L21501 (2009)

  30. 30.

    et al. Reduction of forest soil respiration in response to nitrogen deposition. Nature Geosci. 3, 315–322 (2010)

  31. 31.

    , , & Traceable components of terrestrial carbon storage capacity in biogeochemical models. Glob. Change Biol. 19, 2104–2116 (2013)

  32. 32.

    , & Global soil carbon projections are improved by modelling microbial processes. Nature Clim. Change 3, 909–912 (2013)

  33. 33.

    FAO/IIASA/ISRIC/ISSCAS/JRC. Harmonized World Soil Database v 1. 2 (2012)

  34. 34.

    & The vertical distribution of soil organic carbon and its relation to climate and vegetation. Ecol. Appl. 10, 423–436 (2000)

  35. 35.

    , , & How accurately can soil organic carbon stocks and stock changes be quantified by soil inventories? Biogeosciences 8, 1193–1212 (2011)

  36. 36.

    , & Global Soil Texture and Derived Water-Holding Capacities (Webb et al.) (Oak Ridge National Laboratory Distributed Active Archive Center, 2000)

  37. 37.

    A World Soil File for Global Climate Modelling. Report No. 87802 (NASA Goddard Institute for Space Studies, 1986)

  38. 38.

    et al. The Northern Circumpolar Soil Carbon Database: spatially distributed datasets of soil coverage and soil carbon storage in the northern permafrost regions. Earth Syst. Sci. Data 5, 3–13 (2013)

  39. 39.

    et al. Soil organic carbon pools in the northern circumpolar permafrost region. Glob. Biogeochem. Cycles 23, GB2023 (2009)

  40. 40.

    et al. Benchmark map of forest carbon stocks in tropical regions across three continents. Proc. Natl Acad. Sci. USA 108, 9899–9904 (2011)

  41. 41.

    et al. Carbon stock and density of northern boreal and temperate forests. Glob. Ecol. Biogeogr. 23, 297–310 (2014)

  42. 42.

    et al. in Proc. ESA Living Planet Symp. SP-722 (CD-ROM, ESA Communication Office, 2013)

  43. 43.

    The McCree-de Wit-Penning de Vries-Thornley respiration paradigms: 30 years later. Ann. Bot. (Lond.) 86, 1–20 (2000)

  44. 44.

    et al. Global patterns of land-atmosphere fluxes of carbon dioxide, latent heat, and sensible heat derived from eddy covariance, satellite, and meteorological observations. J. Geophys. Res. Biogeosci. 116, G00J07 (2011)

  45. 45.

    , , & Exploiting synergies of global land cover products for carbon cycle modeling. Remote Sens. Environ. 101, 534–553 (2006)

  46. 46.

    New, low estimate for carbon stock in global forest vegetation based on inventory data. Silva Fenn. 37, 451–457 (2003)

  47. 47.

    in Global Biogeochemical Cycles (eds , , & ) 55–72 (Academic, 1992)

  48. 48.

    in Russell’s Soil Conditions and Plant Growth (ed. ) 564–607 (Longman Scientific and Technical, 1988)

  49. 49.

    in Soils and Global Change Vol. 25 (eds , , & ) 9–25 (CRC/Lewis Publishers, 1995)

  50. 50.

    The retention of organic-matter in soils. Biogeochemistry 5, 35–70 (1988)

  51. 51.

    , & A latitudinal gradient in carbon turnover times in forest soils. Nature 381, 143–146 (1996)

  52. 52.

    A historical meta-analysis of global terrestrial net primary productivity: are estimates converging? Glob. Change Biol. 17, 3161–3175 (2011)

  53. 53.

    , , & From Miami to Madison: investigating the relationship between climate and terrestrial net primary production. Glob. Biogeochem. Cycles 21, GB3004 (2007)

  54. 54.

    et al. Global potential net primary production predicted from vegetation class, precipitation, and temperature. Ecology 89, 2117–2126 (2008)

  55. 55.

    in Primary Productivity of the Biosphere (eds & ) 237–263 (Springer, 1975)

  56. 56.

    & in Publications in Climatology (ed. ) 37–46 (C.W. Thornthwaite Associates, 1972)

  57. 57.

    Productivity and global climate revisited: the sensitivity of tropical forest growth to precipitation. Ecology 84, 1165–1170 (2003)

  58. 58.

    et al. The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q. J. R. Meteorol. Soc. 137, 553–597 (2011)

  59. 59.

    et al. Harmonized European long-term climate data for assessing the effect of changing temporal variability on land-atmosphere CO2 fluxes. J. Clim. 27, 4815–4834 (2014)

  60. 60.

    et al. Creation of the WATCH forcing data and its use to assess global and regional reference crop evaporation over land during the twentieth century. J. Hydrometeorol. 12, 823–848 (2011)

  61. 61.

    et al. Statistical bias correction of global simulated daily precipitation and temperature for the application of hydrological models. J. Hydrol. (Amst.) 395, 199–215 (2010)

  62. 62.

    , & Introduction to Bivariate and Multivariate Analysis (1980)

  63. 63.

    Relative importance for linear regression in R: the package relaimpo. J. Stat. Softw. 17, 1–27 (2006)

  64. 64.

    , , & Kernel-based conditional independence test and application in causal discovery. Computing Res. Repos. (arXiv, 2012)

  65. 65.

    , & An Overview of Cmip5 and the Experiment Design. Bull. Am. Meteorol. Soc. 93, 485–498 (2012)

  66. 66.

    et al. in Climate Change 2001: The Scientific Basis (eds et al.) 183–237 (Cambridge Univ Press, 2001)

  67. 67.

    et al. Terrestrial gross carbon dioxide uptake: global distribution and covariation with climate. Science 329, 834–838 (2010)

  68. 68.

    , , , & World map of the Koppen-Geiger climate classification updated. Meteorol. Z. (Berl.) 15, 259–263 (2006)

  69. 69.

    et al. The resilience and functional role of moss in boreal and arctic ecosystems. New Phytol. 196, 49–67 (2012)

  70. 70.

    , & Global and regional importance of the tropical peatland carbon pool. Glob. Change Biol. 17, 798–818 (2011)

  71. 71.

    et al. Annual Global Automated MODIS Vegetation Continuous Fields (MOD44B) at 250 m Spatial Resolution for Data Years Beginning Day 65, 2000 - 2010, Collection 5 Percent Tree Cover (University of Maryland, 2011)

Download references

Acknowledgements

We would like to thank C. Jones for comments that improved the manuscript. We are grateful to A. Ito, D. Zaks and S. Del Grosso for sharing their NPP data sets with us. We thank S. Schott for figure editing. We acknowledge support by the European Union (FP7) through the projects GEOCARBON (283080), CARBONES (242316) and EMBRACE (283201) and an ERC starting grant QUASOM (ERC-2007-StG-208516).

Author information

Affiliations

  1. Max Planck Institute for Biogeochemistry, Hans Knöll Strasse 10, 07745 Jena, Germany

    • Nuno Carvalhais
    • , Matthias Forkel
    • , Myroslava Khomik
    • , Martin Jung
    • , Mirco Migliavacca
    • , Martin Thurner
    • , Ulrich Weber
    • , Bernhard Ahrens
    • , Christian Beer
    •  & Markus Reichstein
  2. Departamento de Ciências e Engenharia do Ambiente, DCEA, Faculdade de Ciências e Tecnologia, FCT, Universidade Nova de Lisboa, 2829-516 Caparica, Portugal

    • Nuno Carvalhais
  3. School of Geography and Earth Sciences, McMaster University, Hamilton, Ontario L8S 4K1, Canada

    • Myroslava Khomik
  4. Institute of Biological and Environmental Sciences, School of Biological Sciences, University of Aberdeen, Aberdeen AB24 3UU, UK

    • Jessica Bellarby
  5. Lancaster Environment Centre, Lancaster University, Bailrigg, Lancaster LA1 4YQ, UK

    • Jessica Bellarby
  6. Remote Sensing of Environmental Dynamics Lab, DISAT, University of Milano-Bicocca, Piazza della Scienza 1, 20126 Milan, Italy

    • Mirco Migliavacca
  7. Department of Earth System Science, University of California Irvine, Irvine, California 92697, USA

    • Mingquan Μu
    •  & James T. Randerson
  8. Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California 91109, USA

    • Sassan Saatchi
  9. Gamma Remote Sensing, Worbstrasse 225, 3073 Gümligen, Switzerland

    • Maurizio Santoro
  10. Department of Applied Environmental Science and Bolin Centre for Climate Research, Stockholm University, Svante Arrhenius väg 8, 10691 Stockholm, Sweden

    • Christian Beer
  11. European Commission, Joint Research Centre, Institute for Environment and Sustainability, Climate Risk Management Unit, Via E. Fermi, 2749, I-21027 Ispra, Italy

    • Alessandro Cescatti

Authors

  1. Search for Nuno Carvalhais in:

  2. Search for Matthias Forkel in:

  3. Search for Myroslava Khomik in:

  4. Search for Jessica Bellarby in:

  5. Search for Martin Jung in:

  6. Search for Mirco Migliavacca in:

  7. Search for Mingquan Μu in:

  8. Search for Sassan Saatchi in:

  9. Search for Maurizio Santoro in:

  10. Search for Martin Thurner in:

  11. Search for Ulrich Weber in:

  12. Search for Bernhard Ahrens in:

  13. Search for Christian Beer in:

  14. Search for Alessandro Cescatti in:

  15. Search for James T. Randerson in:

  16. Search for Markus Reichstein in:

Contributions

N.C. and M.R. designed the study and are responsible for the integrity of the work as a whole. N.C., M.F. and M. Migliavacca performed analysis and calculations. N.C. and M.R. mainly wrote the manuscript. M.K. and J.B. contributed to interpreting and processing the soil databases. M.T., M.S. and S.S. contributed to the vegetation carbon stocks datasets and interpretation. M.J. contributed to the GPP datasets and interpretation. C.B., M. Mu, M.T. and U.W. contributed to data provision, analysis or data processing. A.C., B.A., M.F., M.J. and J.T.R. contributed to analysis design and interpretation. All authors discussed and commented on the manuscript.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Nuno Carvalhais.

Extended data

Supplementary information

PDF files

  1. 1.

    Supplementary Information

    This file contains Supplementary Text and Data 1-6, Supplementary References, Supplementary Tables 1-7 and Supplementary Figures 1-13. Please note that you can download the Supplementary Data, relating to this paper, at the following link: http://www.bgc-jena.mpg.de/geodb/BGI/tau.php

About this article

Publication history

Received

Accepted

Published

DOI

https://doi.org/10.1038/nature13731

Further reading

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.