Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Letter
  • Published:

Nutrient availability as the key regulator of global forest carbon balance

Nature Climate Change volume 4, pages 471–476 (2014)Cite this article

Subjects

A Corrigendum to this article was published on 25 March 2015

An Addendum to this article was published on 25 June 2014

This article has been updated

Abstract

Forests strongly affect climate through the exchange of large amounts of atmospheric CO2 (ref. 1). The main drivers of spatial variability in net ecosystem production (NEP) on a global scale are, however, poorly known. As increasing nutrient availability increases the production of biomass per unit of photosynthesis2 and reduces heterotrophic3 respiration in forests, we expected nutrients to determine carbon sequestration in forests. Our synthesis study of 92 forests in different climate zones revealed that nutrient availability indeed plays a crucial role in determining NEP and ecosystem carbon-use efficiency (CUEe; that is, the ratio of NEP to gross primary production (GPP)). Forests with high GPP exhibited high NEP only in nutrient-rich forests (CUEe = 33 ± 4%; mean ± s.e.m.). In nutrient-poor forests, a much larger proportion of GPP was released through ecosystem respiration, resulting in lower CUEe (6 ± 4%). Our finding that nutrient availability exerts a stronger control on NEP than on carbon input (GPP) conflicts with assumptions of nearly all global coupled carbon cycle–climate models, which assume that carbon inputs through photosynthesis drive biomass production and carbon sequestration. An improved global understanding of nutrient availability would therefore greatly improve carbon cycle modelling and should become a critical focus for future research.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Only nutrient-rich forests substantially increase carbon sequestration with increasing carbon uptake.
Figure 2: The coupling between ecosystem respiration (Re) and gross primary production (GPP) is weak in nutrient-rich forests and very strong in nutrient-poor forests.
Figure 3: Relative contribution of predictor variables in the model explaining variability in net ecosystem production (NEP).

Similar content being viewed by others

Change history

  • 28 May 2014

    In the version of this Letter originally published, the following text was omitted from the acknowledgements section: 'We also thank all site investigators, their funding agencies, the various regional flux networks (Afriflux, AmeriFlux, AsiaFlux, CarboAfrica, CarboEurope-IP, ChinaFlux, Fluxnet-Canada, KoFlux, LBA, NECC, OzFlux, TCOS-Siberia, USCCC), the Office of Science (BER) and US Department of Energy (for funding the development of measurement and data submission protocols), and the Fluxnet project, whose work and support is essential for obtaining the measurements without which the type of integrated analyses conducted in this study would not be possible.' This has been corrected in the online versions of the Letter.

  • 13 March 2015

    In the version of this Letter originally published, in the final paragraph, the section of text including 'Earth system models should … nutrient cycling)' was misleading and should have been: "Models simulating the dynamics of the terrestrial biosphere currently consider the effects of nitrogen on vegetation and soils25,26 but they still do not consider the effects of other nutrients such as phosphorus or potassium. Future models should consider the interactions of nitrogen as well as these other nutrients with the entire forest carbon balance. The relationship between GPP and NEP appears to be so strongly controlled by the nutrient status of the forest that terrestrial biosphere models may be unable to accurately predict the carbon balance of forest ecosystems without information on background nutrient availability27—soil nitrogen, phosphorous, potassium, pH—and on changes in soil and plant nutrient cycling resulting from human activities (such as nitrogen deposition, climate change and elevated CO2)." To accommodate these changes, the original ref. 27 (W. De Vries and M. Posch, M. Environ. Pollut. 159, 2289-2299; 2011) was removed and the remaining references renumbered. The original references numbered 31–33 have been moved to the Supplementary Information, as they are uncited in the main text.

References

  1. Dixon, R. K. et al. Carbon pools and flux of global forest ecosystems. Science 263, 185–90 (1994).

    Article  CAS  Google Scholar 

  2. Vicca, S. et al. Fertile forests produce biomass more efficiently. Ecol. Lett. 15, 520–526 (2012).

    Article  CAS  Google Scholar 

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

    Article  CAS  Google Scholar 

  4. Valentini, R. et al. Respiration as the main determinant of carbon balance in European forests. Nature 404, 861–865 (2000).

    Article  CAS  Google Scholar 

  5. Kato, T. & Tang, Y. Spatial variability and major controlling factors of CO2 sink strength in Asian terrestrial ecosystems: Evidence from eddy covariance data. Glob. Chang. Biol. 14, 2333–2348 (2008).

    Article  Google Scholar 

  6. Piao, S. et al. Footprint of temperature changes in the temperate and boreal forest carbon balance. Geophys. Res. Lett. 36, L07404 (2009).

    Article  Google Scholar 

  7. De Vries, W. et al. The impact of nitrogen deposition on carbon sequestration by European forests and heathlands. For. Ecol. Manage. 258, 1814–1823 (2009).

    Article  Google Scholar 

  8. Fernández-Martínez, M. et al. Spatial variability and controls over biomass stocks, carbon fluxes and resource-use efficiencies in forest ecosystems. Trees Struct. Funct. 28, 597–611 (2014).

    Article  Google Scholar 

  9. Luyssaert, S. et al. CO2 balance of boreal, temperate, and tropical forests derived from a global database. Glob. Chang. Biol. 13, 2509–2537 (2007).

    Article  Google Scholar 

  10. Hijmans, R. J., Cameron, S. E., Parra, J. L., Jones, P. G. & Jarvis, A. Very high resolution interpolated climate surfaces for global land areas. Int. J. Climatol. 25, 1965–1978 (2005).

    Article  Google Scholar 

  11. Reichstein, M. et al. On the separation of net ecosystem exchange into assimilation and ecosystem respiration: Review and improved algorithm. Glob. Chang. Biol. 11, 1424–1439 (2005).

    Article  Google Scholar 

  12. Vickers, D., Thomas, C. K., Martin, J. G. & Law, B. Self-correlation between assimilation and respiration resulting from flux partitioning of eddy-covariance CO2 fluxes. Agric. For. Meteorol. 149, 1552–1555 (2009).

    Article  Google Scholar 

  13. Lasslop, G., Reichstein, M., Detto, M., Richardson, A. D. & Baldocchi, D. D. Comment on Vickers et al: Self-correlation between assimilation and respiration resulting from flux partitioning of eddy-covariance CO2 fluxes. Agric. For. Meteorol. 150, 312–314 (2010).

    Article  Google Scholar 

  14. Litton, C. M., Raich, J. W. & Ryan, M. G. Carbon allocation in forest ecosystems. Glob. Chang. Biol. 13, 2089–2109 (2007).

    Article  Google Scholar 

  15. Manzoni, S., Taylor, P., Richter, A., Porporato, A. & Agren, G. I. Environmental and stoichiometric controls on microbial carbon-use efficiency in soils. New Phytol. 196, 79–91 (2012).

    Article  CAS  Google Scholar 

  16. Shan, J., Morris, L. A. & Hendrick, R. L. The effects of management on soil and plant carbon sequestration in slash pine plantations. J. Appl. Ecol. 38, 932–941 (2002).

    Article  Google Scholar 

  17. Goulden, M. L. et al. Patterns of NPP, GPP, respiration, and NEP during boreal forest succession. Glob. Chang. Biol. 17, 855–871 (2011).

    Article  Google Scholar 

  18. Chapin, F. S. The mineral nutrition of wild plants. Annu. Rev. Ecol. Syst. 11, 233–260 (1980).

    Article  CAS  Google Scholar 

  19. Burton, A., Pregitzer, K., Ruess, R., Hendrick, R. & Allen, M. Root respiration in North American forests: Effects of nitrogen concentration and temperature across biomes. Oecologia 131, 559–568 (2002).

    Article  CAS  Google Scholar 

  20. Lee, S. C. et al. A protein phosphorylation/dephosphorylation network regulates a plant potassium channel. Proc. Natl Acad. Sci. USA 104, 15959–15964 (2007).

    Article  CAS  Google Scholar 

  21. Keith, H., Mackey, B. G. & Lindenmayer, D. B. Re-evaluation of forest biomass carbon stocks and lessons from the world’s most carbon-dense forests. Proc. Natl Acad. Sci. USA 106, 11635–11640 (2009).

    Article  CAS  Google Scholar 

  22. Cotrufo, M. F., Wallenstein, M. D., Boot, C. M., Denef, K. & Paul, E. The Microbial Efficiency-Matrix Stabilization (MEMS) framework integrates plant litter decomposition with soil organic matter stabilization: Do labile plant inputs form stable soil organic matter? Glob. Chang. Biol. 19, 988–995 (2013).

    Article  Google Scholar 

  23. Peñuelas, J., Sardans, J., Rivas-ubach, A. & Janssens, I. A. The human-induced imbalance between C, N and P in earth’s life system. Glob. Chang. Biol. 18, 3–6 (2012).

    Article  Google Scholar 

  24. Peñuelas, J. et al. Human-induced nitrogen–phosphorus imbalances alter natural and managed ecosystems across the globe. Nature Commun. 4, 2934 (2013).

    Article  Google Scholar 

  25. Zaehle, S. & Friend, A. D. Carbon and nitrogen cycle dynamics in the O-CN land surface model: 1 model description, site-scale evaluation, and sensitivity to parameter estimates. Glob. Biogeochem. Cycles 24, GB1005 (2010).

    Google Scholar 

  26. Zaehle, S., Friedlingstein, P. & Friend, A. D. Terrestrial nitrogen feedbacks may accelerate future climate change. Geophys. Res. Lett. 37, L01401 (2010).

    Article  Google Scholar 

  27. Piao, S. et al. Evaluation of terrestrial carbon cycle models for their response to climate variability and to CO2 trends. Glob. Chang. Biol. 19, 2117–2132 (2013).

    Article  Google Scholar 

  28. R Core Team R: A language and environment for statistical computing. R Found. Stat. Comput. 1, 409 (2013).

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

    Article  Google Scholar 

Download references

Acknowledgements

This research was supported by the Spanish Government projects CGL2010-17172 and Consolider Ingenio Montes (CSD2008-00040), by the Catalan Government Grants SGR 2009-458 and FI-2013 and by the European Research Council Synergy grant 610028, P-IMBALANCE. S.V. and M.C. are postdoctoral fellows of the Research Foundation - Flanders (FWO). S.L. was financially supported by ERC Starting Grant 242564 and received additional financial support from FWO Vlaanderen. We appreciate the financial support of the GHG-Europe project. We also thank all site investigators, their funding agencies, the various regional flux networks (Afriflux, AmeriFlux, AsiaFlux, CarboAfrica, CarboEurope-IP, ChinaFlux, Fluxnet-Canada, KoFlux, LBA, NECC, OzFlux, TCOS-Siberia, USCCC), the Office of Science (BER) and US Department of Energy (for funding the development of measurement and data submission protocols), and the Fluxnet project, whose work and support is essential for obtaining the measurements without which the type of integrated analyses conducted in this study would not be possible.

Author information

Authors and Affiliations

  1. CSIC, Global Ecology Unit, CREAF-CSIC-UAB, Cerdanyola del Vallès, 08193 Barcelona, Catalonia, Spain

    M. Fernández-Martínez, J. Sardans & J. Peñuelas

  2. CREAF, Cerdanyola del Vallès, 08193 Barcelona, Catalonia, Spain

    M. Fernández-Martínez, J. Sardans, F. Rodà & J. Peñuelas

  3. Department of Biology, Research Group of Plant and Vegetation Ecology, University of Antwerp, 2610 Wilrijk, Belgium

    S. Vicca, I. A. Janssens & M. Campioli

  4. LSCE CEA-CNRS-UVSQ, Orme des Merisiers, F-91191 Gif-sur-Yvette, France

    S. Luyssaert & P. Ciais

  5. Institute of Arctic Biology, University of Alaska Fairbanks, Fairbanks, Alaska 99775, USA

    F. S. Chapin III

  6. Environmental Change Institute, School of Geography and the Environment, University of Oxford, Oxford OX1 3QY, UK

    Y. Malhi

  7. International Institute for Applied Systems Analysis, Schlossplatz 1, 2361 Laxenburg, Austria

    M. Obersteiner

  8. DIBAF, University of Tuscia, 01100 Viterbo, Italy

    D. Papale

  9. College of Urban and Environmental Sciences, Peking University, Beijing 100871, China

    S. L. Piao

  10. Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100085, China

    S. L. Piao

  11. Max Planck Institute for Biogeochemistry, 07745 Jena, Germany

    M. Reichstein

  12. Department of Animal Biology, Plant Biology and Ecology, Universitat Autònoma de Barcelona, 08193 Barcelona, Catalonia, Spain

    F. Rodà

Authors
  1. M. Fernández-Martínez
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. S. Vicca
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. I. A. Janssens
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. J. Sardans
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. S. Luyssaert
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. M. Campioli
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. F. S. Chapin III
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. P. Ciais
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Y. Malhi
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. M. Obersteiner
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. D. Papale
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. S. L. Piao
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. M. Reichstein
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. F. Rodà
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. J. Peñuelas
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

M.F-M., S.V., I.A.J. and J.P. conceived the paper and analysed the data. All authors contributed substantially to the discussion and the text writing.

Corresponding author

Correspondence to M. Fernández-Martínez.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Rights and permissions

Reprints and permissions

About this article

Cite this article

Fernández-Martínez, M., Vicca, S., Janssens, I. et al. Nutrient availability as the key regulator of global forest carbon balance. Nature Clim Change 4, 471–476 (2014). https://doi.org/10.1038/nclimate2177

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nclimate2177

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing