Nitrogen and phosphorus constrain the CO2 fertilization of global plant biomass


Elevated CO2 (eCO2) experiments provide critical information to quantify the effects of rising CO2 on vegetation1,2,3,4,5,6. Many eCO2 experiments suggest that nutrient limitations modulate the local magnitude of the eCO2 effect on plant biomass1,3,5, but the global extent of these limitations has not been empirically quantified, complicating projections of the capacity of plants to take up CO27,8. Here, we present a data-driven global quantification of the eCO2 effect on biomass based on 138 eCO2 experiments. The strength of CO2 fertilization is primarily driven by nitrogen (N) in ~65% of global vegetation and by phosphorus (P) in ~25% of global vegetation, with N- or P-limitation modulated by mycorrhizal association. Our approach suggests that CO2 levels expected by 2100 can potentially enhance plant biomass by 12 ± 3% above current values, equivalent to 59 ± 13 PgC. The global-scale response to eCO2 we derive from experiments is similar to past changes in greenness9 and biomass10 with rising CO2, suggesting that CO2 will continue to stimulate plant biomass in the future despite the constraining effect of soil nutrients. Our research reconciles conflicting evidence on CO2 fertilization across scales and provides an empirical estimate of the biomass sensitivity to eCO2 that may help to constrain climate projections.

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Fig. 1: Soil C:N and soil P are key plant resources driving the CO2 fertilization effect on above-ground biomass.
Fig. 2: Potential above-ground biomass enhancement in terrestrial ecosystems under elevated CO2.
Fig. 3: Comparison of the global effect of elevated CO2 with existing independent approaches.

Data availability

The biomass data from CO2 experiments summarized in Supplementary Fig. 2 supporting the findings of this study are available in published papers, and soil and climate data required to upscale CO2 effects are available in published datasets (Supplementary Table 2). Raw data can be obtained from the corresponding author on reasonable request.

Code availability

The R code used in the analysis presented in this paper is available online and can be accessed at


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We thank C. Körner, R. Norby, M. Schneider, Y. Carrillo, E. Pendall, B. Kimball, M. Watanabe, T. Koike, G. Smith, S.J. Tumber-Davila, T. Hasegawa, B. Sigurdsson, S. Hasegawa, A.L. Abdalla-Filho and L. Fenstermaker for sharing data and advice. This research is a contribution to the AXA Chair Programme in Biosphere and Climate Impacts and the Imperial College initiative Grand Challenges in Ecosystems and the Environment. Part of this research was developed in the Young Scientists Summer Program at the International Institute for Systems Analysis, Laxenburg (Austria) with financial support from the Natural Environment Research Council (UK). C.T. also acknowledges financial support from the Spanish Ministry of Science, Innovation and Universities through the María de Maeztu programme for Units of Excellence (grant no. MDM-2015-0552). I.C.P. acknowledges support from the European Research Council under the European Union’s Horizon 2020 research and innovation programme (grant no. 787203 REALM). S.V. and K.v.S. acknowledge support from the Fund for Scientific Research, Flanders (Belgium). T.F.K. acknowledges support by the Director, Office of Science, Office of Biological and Environmental Research of the US Department of Energy under contract DE-AC02-05CH11231 as part of the RuBiSCo SFA. J.P. acknowledges support from the European Research Council through Synergy grant no. ERC-2013-SyG-610028 ‘IMBALANCE-P’. T.F.K. and J.B.F. were supported in part by NASA IDS Award no. NNH17AE86I. J.B.F. was also supported by the US Department of Energy, Office of Science, Office of Biological and Environmental Research. J.B.F. contributed to this research from Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration. California Institute of Technology. N.A.S. was supported by Vidi grant no. 016.161.318 by the Netherlands Organization for Scientific Research. This paper is a contribution to the Global Carbon Project.

Author information

The study was originally conceived and developed by C.T., with ideas and contributions by R.J., I.C.P., O.F., T.F.K., P.B.R., C.K., S.V, B.S. and J.B.F. Data from DGVMs were analysed by T.F.K. Analysis of drivers was done by C.T and P.B.R. Statistical analysis was carried out by C.T., C.J.v.L. and W.V. Spatial analysis was done by C.T. and I.M. P.B.R., B.A.H., L.A.C., A.F.T., P.C.D.N., M.J.H., D.M.B., C.M., K.W., C.B.F., M.R.H., M.W., T.K., H.W.P. and many others ran the experiments. The initial manuscript was written by C.T. with input from all authors.

Correspondence to César Terrer.

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Peer review information: Nature Climate Change thanks Shu Kee Lam, Bassil El Masri and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Supplementary Discussion, Figs. 1–8, Tables 1–5 and references.

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