ABSTRACT Forests provide vital ecosystem services, particularly as carbon sinks for nature-based climate solutions. However, the impact of elevated atmospheric carbon dioxide (CO2) levels on

carbon and nitrogen interactions of forests remains poorly quantified. We integrate experimental observations and biogeochemical models to elucidate the synergies between enhanced nitrogen

and carbon cycling in global forests under elevated CO2. Elevated CO2 alone increases net primary productivity (+27%; 95% CI: 23–31%) and leaf C/N ratio (+26%; 95% CI: 16–39%), while

stimulating biological nitrogen fixation (+25%; 95% CI: 0–56%) and nitrogen use efficiency (+32%; 95% CI: 5–65%) according to a global meta-analysis. Under the elevated CO2 middle-road

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BENEFITS GAINED THROUGH REDUCTIONS IN NITROGEN AND SULFUR DEPOSITION Article Open access 10 May 2024 THE ENDURING WORLD FOREST CARBON SINK Article 17 July 2024 WARMING EXACERBATES GLOBAL

INEQUALITY IN FOREST CARBON AND NITROGEN CYCLES Article Open access 24 October 2024 DATA AVAILABILITY All data supporting the findings of this study are openly available, and their sources

are detailed in the Methods and Supplementary Information. A global database of elevated CO2 simulation experiments was established by extracting data from site-based manipulation studies.

Climate data for our study sites were sourced from the WorldClim database (https://worldclim.org/data/index.html#). Soil data were obtained primarily from publications or supplemented with

data from the Global Land Data Assimilation System (GLDAS) (https://ldas.gsfc.nasa.gov/gldas/soils). Future forest areas under different socioeconomic pathways were projected using the

Global Change Analysis Model. National carbon prices were obtained from a World Carbon Pricing Database, while fertilizer price data were sourced from the UN Comtrade Database

(https://comtrade.un.org/). Source data are provided with this paper and are available via Zenodo at https://doi.org/10.5281/zenodo.10731367 (ref. 73). CODE AVAILABILITY The code used in the

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& Gu, B. Database of eCO2 experiments in forests and global analysis (v1.0). _Zenodo_ https://doi.org/10.5281/zenodo.10731367 (2024). Download references ACKNOWLEDGEMENTS This study was

supported by the National Natural Science Foundation of China (42325707 and 42261144001, B.G.), National Key Research and Development Project of China (2022YFE0138200, B.G.) and Postdoctoral

Fellowship Program of China Postdoctoral Science Foundation (CPSF) (GZC20232311, J.C.). We thank H. Chen for assistance in meta-data collection. AUTHOR INFORMATION AUTHORS AND AFFILIATIONS

* College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, China Jinglan Cui, Miao Zheng, Xiuming Zhang, Ziyue Qiu, Jianming Xu & Baojing Gu * Policy Simulation

Laboratory, Zhejiang University, Hangzhou, China Jinglan Cui * Center for Earth System Science and Global Sustainability, Schiller Institute for Integrated Science and Society, Department of

Earth and Environmental Sciences, Boston College, Chestnut Hill, MA, USA Zihao Bian, Naiqing Pan & Hanqin Tian * School of Geography, Nanjing Normal University, Nanjing, China Zihao

Bian * Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, Zhejiang University, Hangzhou, China Jianming Xu * Ministry of Education Key Laboratory of Environment

Remediation and Ecological Health, Zhejiang University, Hangzhou, China Baojing Gu Authors * Jinglan Cui View author publications You can also search for this author inPubMed Google Scholar

* Miao Zheng View author publications You can also search for this author inPubMed Google Scholar * Zihao Bian View author publications You can also search for this author inPubMed Google

Scholar * Naiqing Pan View author publications You can also search for this author inPubMed Google Scholar * Hanqin Tian View author publications You can also search for this author inPubMed

 Google Scholar * Xiuming Zhang View author publications You can also search for this author inPubMed Google Scholar * Ziyue Qiu View author publications You can also search for this author

inPubMed Google Scholar * Jianming Xu View author publications You can also search for this author inPubMed Google Scholar * Baojing Gu View author publications You can also search for this

author inPubMed Google Scholar CONTRIBUTIONS B.G. and J.C. designed the study. J.C. analysed the data and wrote the first draft of the paper. All authors contributed to the discussion and

revision of the paper. M.Z. provided support for meta-data collection and visualization. Z.B., N.P. and H.T. provided modelling support for DLEM. X.Z. provided support for CHANS model and

impact assessment. Z.Q. provided support for meta-data collection. J.X. contributed to the discussion of the study. CORRESPONDING AUTHOR Correspondence to Baojing Gu. ETHICS DECLARATIONS

COMPETING INTERESTS The authors declare no competing interests. PEER REVIEW PEER REVIEW INFORMATION _Nature Climate Change_ thanks César Terrer, Kevin Van Sundert and the other, anonymous,

reviewer(s) for their contribution to the peer review of this work. ADDITIONAL INFORMATION PUBLISHER’S NOTE Springer Nature remains neutral with regard to jurisdictional claims in published

maps and institutional affiliations. EXTENDED DATA EXTENDED DATA FIG. 1 MODELLING FRAMEWORK. We establish a database of elevated atmospheric CO2 (eCO2) experiments conducted across forest

sites. A global synthesis is then performed to quantify the impacts of eCO2 on nitrogen and carbon cycles. We utilize the Dynamic Land Ecosystem Model (DLEM) and the Coupled Human and

Natural Systems (CHANS) model to simulate global forest carbon and nitrogen budgets under multiple scenarios. Finally, the carbon and nitrogen budgets are fed into the impact assessment

module, facilitating the monetization of elevated CO2 impacts on forest assets. EXTENDED DATA FIG. 2 RELATIONSHIP BETWEEN THE RESPONSE RATIO TO ECO2 FOR SELECTED VARIABLES AND MODERATORS.

(A) Response ratio of NPP against the squared mean annual precipitation (MAP) in FACE Experiments. (B) Response ratio of BNF against soil C:N ratio. (C) Response ratio of DOC against MAP.

(D) Response ratio of Rs against MAP in FACE Experiments. The regression lines illustrate the mean response of observations using mixed-effects meta-regression models. The gray shading

denotes the 95% confidence intervals for the mean. The sizes of bubbles in the scatter plots are proportional to the weights of response ratios for each individual observation. Source data

EXTENDED DATA FIG. 3 RELATIONSHIP BETWEEN THE RESPONSE RATIO TO ECO2 OF SELECTED VARIABLES AND MANIPULATION MAGNITUDE (ΔCO2). Regressions between NUE (A), WUE (B), N2O (C) against ΔCO2. The

regression lines illustrate the mean response of observations using mixed-effects meta-regression models. The gray shading denotes the 95% confidence intervals for the mean. The sizes of

bubbles in the scatter plots are proportional to the weights of response ratios for each individual observation. Source data EXTENDED DATA FIG. 4 THE NITROGEN ACCUMULATION OF GLOBAL FORESTS

AND THE CHANGES BETWEEN ECO2 SSP2-4.5 MIDDLE-ROAD SCENARIO AND BASELINE SCENARIO IN 2050. Nitrogen accumulation in baseline scenario (A), eCO2 scenario (B), and Δaccumulation (eCO2-induced

change) (C). NUE in baseline scenario (D), eCO2 scenario (E), and ΔNUE (eCO2-induced change) (F). Values in the legend reflect the average annual N budget from forests within a grid cell

(0.5° × 0.5°). The base map is from GADM data. Source data EXTENDED DATA FIG. 5 THE ECO2 IMPACT ON CARBON SINK AND UNCERTAINTIES IN GLOBAL FORESTS UNDER ECO2 SSP2-4.5 MIDDLE-ROAD SCENARIO

FOR 2050. (A) The eCO2–induced changes in carbon sink per square meter of forest area. (B) The absolute uncertainties of ΔC sink in Fig. 2 based on the standard deviations of the model

ensembles derived from Monte Carlo simulations. Values of uncertainties in the legend reflect the annual values from forests within one grid cell (0.5° × 0.5°). The base map is from GADM

data. Source data EXTENDED DATA FIG. 6 THE NITROGEN INPUT OF GLOBAL FORESTS AND THE CHANGES BETWEEN ECO2 SSP2-4.5 MIDDLE-ROAD SCENARIO AND BASELINE SCENARIO IN 2050. Biological nitrogen

fixation (BNF) in baseline scenario (A), eCO2 scenario (B), and ΔBNF (eCO2-induced change) (C); nitrogen deposition in baseline scenario (D), eCO2 scenario (E), and ΔDeposition (F); nitrogen

fertilizer in baseline scenario (G), eCO2 scenario (H), and Δfertilizer (I). Values in the legend reflect the average annual nitrogen budget from forests within a grid cell (0.5° × 0.5°).

The base map is from GADM data. Source data EXTENDED DATA FIG. 7 UNCERTAINTIES OF ECO2–INDUCED CHANGES IN NITROGEN BUDGETS IN GLOBAL FORESTS UNDER ECO2 SSP2-4.5 MIDDLE-ROAD SCENARIO FOR

2050. (A) ΔN input; (B) ΔN products; (C) ΔNr loss. The absolute uncertainties are based on the standard deviations of the model ensembles derived from Monte Carlo simulations. Values in the

legend reflect the annual values from forest within a grid cell (0.5° × 0.5°). The base map is from GADM data. Source data EXTENDED DATA FIG. 8 THE REACTIVE NITROGEN LOSS OF GLOBAL FORESTS

AND THE CHANGES DUE TO ELEVATED CO2 UNDER ECO2 MIDDLE ROAD SCENARIO (SSP2-4.5) RELATIVE TO BASELINE SCENARIO IN 2050. NH3 emissions in baseline scenario (A), eCO2 scenario (B), and ΔNH3

(eCO2-induced change) (C); N2O emissions in baseline scenario (D), eCO2 scenario (E), and ΔN2O (F); NOx emissions in baseline scenario (G), eCO2 scenario (H), and ΔNOx (I); NO3− in baseline

scenario (J), eCO2 scenario (K), and ΔNO3− (L). Values in the legend reflect the average annual nitrogen budget from forest within a grid cell (0.5° × 0.5°). The base map is from GADM data.

Source data EXTENDED DATA FIG. 9 A PRISMA (PREFERRED REPORTING ITEMS FOR SYSTEMATIC REVIEWS AND META-ANALYSES) FLOW DIAGRAM OF OUR META-ANALYSIS. It delineates the flow of information,

indicating the number of relevant publications at various stages of the meta-analysis process, encompassing ‘Identification’, ‘Screening & Eligibility’, and ‘Included’. SUPPLEMENTARY

INFORMATION SUPPLEMENTARY INFORMATION Supplementary Figs. 1–6, Tables 1–3, Discussion, Terminology used in the study and references. REPORTING SUMMARY SOURCE DATA SOURCE DATA FIG. 1

Statistical source data. SOURCE DATA FIG. 2 Statistical source data. SOURCE DATA FIG. 3 Statistical source data. SOURCE DATA FIG. 4 Statistical source data. SOURCE DATA FIG. 5 Statistical

source data. SOURCE DATA EXTENDED DATA FIG. 2 Statistical Source Data SOURCE DATA EXTENDED DATA FIG. 3 Statistical source data. SOURCE DATA EXTENDED DATA FIG. 4 Statistical source data.

SOURCE DATA EXTENDED DATA FIG. 5 Statistical source data. SOURCE DATA EXTENDED DATA FIG. 6 Statistical source data. SOURCE DATA EXTENDED DATA FIG. 7 Statistical source data. SOURCE DATA

EXTENDED DATA FIG. 8 Statistical source data. RIGHTS AND PERMISSIONS Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a

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agreement and applicable law. Reprints and permissions ABOUT THIS ARTICLE CITE THIS ARTICLE Cui, J., Zheng, M., Bian, Z. _et al._ Elevated CO2 levels promote both carbon and nitrogen cycling

in global forests. _Nat. Clim. Chang._ 14, 511–517 (2024). https://doi.org/10.1038/s41558-024-01973-9 Download citation * Received: 08 September 2023 * Accepted: 05 March 2024 * Published:

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