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Heterogeneous pressure on croplands from land-based strategies to meet the 1.5 °C target

Nature Climate Change volume 15, pages 420–427 (2025)Cite this article

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An Author Correction to this article was published on 06 May 2025

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Abstract

Achieving the 1.5 °C target outlined in the Paris Agreement necessitates coordinated global efforts, particularly in the form of ambitious climate pledges. While current discussions primarily focus on energy and emissions pathways, the fine-scale, ___location-specific consequences for agriculture, land systems and sustainability remain uncertain. Here we evaluate global land-system responses at 5-km2 resolution in pursuit of the 1.5 °C target through recent country-specific climate pledges. Contrary to previous studies predicting cropland expansion under a 1.5 °C scenario, we reveal a 12.8% reduction in cropland area when accounting for cross-sectoral impacts of climate pledges and land-use intensity. The reduction is most pronounced in South America (23.7%), with the global south comprising 81% of the countries worldwide expected to experience cropland loss. Food security in the Global South faces additional pressure due to a projected 12.6% reduction in export potential from the global north.

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Fig. 1: Global land-system map for 2015 and land-system-type transformations from 2005 to 2015.
Fig. 2: Global land-system map for 2100 and land-system-type transformations from 2015 to 2100 under the 1.5 °C scenario.
Fig. 3: Cropland changes by 2100 under the 1.5 °C scenario compared to the reference year 2015 at the continental scale.
Fig. 4: Cropland loss by 2100 under the 1.5 °C scenario, compared to the reference year 2015, at the country scale.

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Data availability

The detailed trade matrix of the FAO is available at https://www.fao.org/faostat/en/#data/TM. The agricultural inventory data are available at http://www.earthstat.org/harvested-area-yield-175-crops/. The FAO corporate statistical database can be accessed at https://www.fao.org/faostat/en/#definitions. The ___location characteristics are archived at https://www.cell.com/cms/10.1016/j.isci.2023.106364/attachment/d3fdb890-f27c-423d-9e44-ed4a90c6b22c/mmc2.xlsx. The administrative boundaries data come from https://data.humdata.org/dataset/global-edge-matched-subnational-boundaries-humanitarian and https://cloudcenter.tianditu.gov.cn/administrativeDivision. The boundary data for the 235 basins in the GCAM can be downloaded at https://github.com/JGCRI/moirai/blob/master/indata/Global235_CLM_5arcmin.bil.

Code availability

The GCAM is an open-source model available at https://github.com/JGCRI/gcam-core/releases. The version of the GCAM and additional input files associated with this study are available via Zenodo at https://doi.org/10.5281/zenodo.7069066 (ref. 50). The land-change model was adopted from Gao et al.51, and its source code is available at https://github.com/gaoyifan2021/Land-N2N-v1.

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Acknowledgements

This study was supported by the National Natural Science Foundation of China (grant nos. 42230106 and 42271418). H.M. was supported by the National Research Foundation of Korea (grant no. RS-2024-00467678). Y.O. was supported by the National Natural Science Foundation of China (grant no. 72474002). P.G. thanks L. Chen and J. Lv for their help with the experiments. G.I. is also affiliated with Pacific Northwest National Laboratory, which did not provide specific support for this paper. The views and opinions expressed in this paper are those of the authors alone and do not necessarily state or reflect those of the affiliated organizations or the governments of the United States, Korea and China, and no official endorsement should be inferred.

Author information

Authors and Affiliations

  1. State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing, China

    Peichao Gao, Yifan Gao, Sijing Ye, Xiaofan Yang & Changqing Song

  2. College of Environmental Sciences and Engineering, Peking University, Beijing, China

    Yang Ou

  3. Institute of Carbon Neutrality, Peking University, Beijing, China

    Yang Ou

  4. Graduate School of Green Growth & Sustainability, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea

    Haewon McJeon

  5. Center for Global Sustainability, University of Maryland, College Park, MD, USA

    Gokul Iyer

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  1. Peichao Gao
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Contributions

P.G., H.M. and C.S. designed the research; P.G. led the experiments and wrote the first draft; Y.G. performed the land-change modelling module; Y.O., H.M. and G.I. performed the GCAM module; S.Y. and X.Y analysed part of the results; P.G., Y.O. and H.M. led the revisions.

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Correspondence to Haewon McJeon or Changqing Song.

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Nature Climate Change thanks Gerd Angelkorte, Yujun Yi and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Global land system map for 2100 and land system type transformations from 2015 to 2100 under the baseline scenario.

a, Global land system map for 2100. It retains the same spatial and thematic resolutions as the base maps. b, A comparison of the global land system map between 2015 and 2100. The blank areas represent regions that have not changed from 2015 to 2100. The colorful areas represent land system types in 2100 that have changed from 2015 to 2100. c, Summary of pixel-by-pixel transformations from 2015 to 2100. Water basin boundaries data from ref. 42.

Extended Data Fig. 2 Global land system map for 2100 and land system type transformations from 2015 to 2100 under the 2 °C scenario.

a, Global land system map for 2100. It retains the same spatial and thematic resolutions as the base maps. b, A comparison of the global land system map between 2015 and 2100. The blank areas represent regions that have not changed from 2015 to 2100. The colorful areas represent land system types in 2100 that have changed from 2015 to 2100. c, Summary of pixel-by-pixel transformations from 2015 to 2100. Water basin boundaries data from ref. 42.

Extended Data Fig. 3 Cropland loss by 2100 under the baseline scenario compared to reference year 2015 at the country scale.

a, Relative cropland loss by 2100. The blank areas represent the countries or regions where no cropland loss, while the colorful areas represent the countries or regions with cropland loss. b-c, Category of land systems in 2100 at hotpots. The colorful areas represent the regions that were cropland in 2015 but are no longer retained in 2100. The blank areas represent the regions that were cropland in 2015 and retain so in 2100, or that were not cropland in 2015. Administrative boundaries data from refs. 43,44.

Extended Data Fig. 4 Primary sources (top 10) of cropland product imports for Korea in 2015.

These sources are USA, Brazil, Chinese mainland, Ukraine, Argentina, Australia, Indonesia, Russia, Malaysia and Romania.

Extended Data Fig. 5 Primary sources (top 10) of cropland product imports for Vietnam in 2015.

These sources are Brazil, Argentina, USA, Australia, Chinese mainland, Malaysia, Indonesia, Canada, India and the United Arab Emirates.

Extended Data Fig. 6 Primary sources (top 10) of cropland product imports for Korea in 2100 under the 1.5 °C scenario.

These sources are USA, Brazil, Ukraine, Chinese mainland, Argentina, Australia, Indonesia, Russia, India and Malaysia.

Extended Data Fig. 7 Primary sources (top 10) of cropland product imports for Vietnam in 2100 under the 1.5 °C scenario.

These sources are Argentina, Brazil, USA, Australia, Chinese mainland, Indonesia, Malaysia, Canada, India and the United Arab Emirates.

Extended Data Fig. 8 Overall framework of the land system-based approach to leverage GCAM results.

a, Process of generating land system maps. b, Mechanism of downscale. c, Five modules of GCAM.

Supplementary information

Supplementary Information

Supporting text, Supplementary Tables 1–35, Figs. 1–5 and References

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Gao, P., Gao, Y., Ou, Y. et al. Heterogeneous pressure on croplands from land-based strategies to meet the 1.5 °C target. Nat. Clim. Chang. 15, 420–427 (2025). https://doi.org/10.1038/s41558-025-02294-1

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