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Ageing threatens sustainability of smallholder farming in China

Nature volume 616, pages 96–103 (2023)Cite this article

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Abstract

Rapid demographic ageing substantially affects socioeconomic development1,2,3,4 and presents considerable challenges for food security and agricultural sustainability5,6,7,8, which have so far not been well understood. Here, by using data from more than 15,000 rural households with crops but no livestock across China, we show that rural population ageing reduced farm size by 4% through transferring cropland ownership and land abandonment (approximately 4 million hectares) in 2019, taking the population age structure in 1990 as a benchmark. These changes led to a reduction of agricultural inputs, including chemical fertilizers, manure and machinery, which decreased agricultural output and labour productivity by 5% and 4%, respectively, further lowering farmers’ income by 15%. Meanwhile, fertilizer loss increased by 3%, resulting in higher pollutant emissions to the environment. In new farming models, such as cooperative farming, farms tend to be larger and operated by younger farmers, who have a higher average education level, hence improving agricultural management. By encouraging the transition to new farming models, the negative consequences of ageing can be reversed. Agricultural input, farm size and farmer’s income would grow by approximately 14%, 20% and 26%, respectively, and fertilizer loss would reduce by 4% in 2100 compared with that in 2020. This suggests that management of rural ageing will contribute to a comprehensive transformation of smallholder farming to sustainable agriculture in China.

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Fig. 1: Population ageing and farm size in China.
Fig. 2: SEM of ageing impacts on agriculture.
Fig. 3: Impact of ageing on agricultural sustainability across China’s provinces in 2019.
Fig. 4: Comparison of smallholder and new farming models on agricultural indicators in 2019.
Fig. 5: Relative changes of agricultural sustainability owing to ageing under SSP scenarios by 2100.

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Data availability

Rural household survey data supporting this study are openly available at http://ssec.zju.edu.cn/dataset/CRHPS/. Source data are provided with this paper.

Code availability

All analyses were performed using Stata version 12.0. The codes are available in Supplementary Information, which allows the estimates to be reproduced.

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Acknowledgements

This study was supported by the National Natural Science Foundation of China (42261144001, 42061124001 and 71925005), National Key Research and Development Project of China (2022YFD1700700) and Pioneer, Leading Goose R&D Program of Zhejiang (2022C02008) and the China Agriculture Research System (CARS-01). This work is a contribution from Activity 1.4 to the ‘Towards the International Nitrogen Management System’ project (INMS, http://www.inms.international/) funded by the Global Environment Facility (GEF) through the United Nations Environment Programme (UNEP).

Author information

Author notes

  1. These authors contributed equally: Chenchen Ren, Xinyue Zhou

Authors and Affiliations

  1. College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, China

    Chenchen Ren, Chen Wang, Yaolin Guo, Yu Diao, Sisi Shen, Jianming Xu & Baojing Gu

  2. Department of Land Management, Zhejiang University, Hangzhou, China

    Chenchen Ren

  3. Policy Simulation Laboratory, Zhejiang University, Hangzhou, China

    Chenchen Ren & Chen Wang

  4. School of Management, Zhejiang University, Hangzhou, China

    Xinyue Zhou & Wanyue Li

  5. UK Centre for Ecology & Hydrology, Penicuik, UK

    Stefan Reis

  6. University of Exeter Medical School, Truro, UK

    Stefan Reis

  7. School of Chemistry, University of Edinburgh, Edinburgh, UK

    Stefan Reis

  8. Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, Zhejiang University, Hangzhou, China

    Baojing Gu

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Contributions

B.G. designed the study. C.R. conducted the research. B.G. and C.R. wrote the first draft of the paper. S.R. revised the paper. C.W., Y.G., Y.D., S.S. and W.L. processed the raw data. X.Z. and J.X. contributed to the discussion of the paper.

Corresponding author

Correspondence to Baojing Gu.

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Nature thanks Bazyli Czyżewski, Ken Giller and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

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Extended data figures and tables

Extended Data Fig. 1 Changes of agricultural sustainability with ageing in 2019.

(a) Total agricultural input; (b) Agricultural output; (c) Labour productivity; (d) Fertilizer use; (e) Manure use; (f) Fertilizer loss ratio; (g) Per capita disposable income from agricultural sector; (h) Farm size; (i) Machine input. (a)-(c), (d)-(e), (g)-(i) show the economic, environmental and social impacts of agricultural sustainability, respectively. The predicted means the counterfactual value with ageing ratio equivalent to 1990. The observed means the observed value in 2019. The input, output, fertilizer, manure and machine are all weighted with the total cultivated area on province-level. Labour productivity is weighted with the total labour input on province-level. Farm size and income are arithmetic averages. Acronyms for 31 provinces, autonomous regions, and municipalities directly under the Central Government are listed in Table S4. Shanghai, Tibet and Xinjiang are not depicted due to data limitation.

Source Data

Extended Data Fig. 2 Demographic and socioeconomic changes in China under different scenarios by 2100.

(a) Ageing ratio; (b) Adult labour ratio; (c) Average education years; (d) Total population; (e) Urban population ratio; (f) Gross domestic product per capita (PGDP). SSP1–4 refers to Shared Socioeconomic Pathways (SSPs) scenarios. Urbanization in SSP1 is consistent with it in SSP4 in panel (e). Data are from SSP Database.

Source Data

Extended Data Fig. 3 Future agricultural sustainability changes due to ageing under SSP scenarios by 2100.

(a) Total agricultural input; (b) Agricultural output; (c) Labour productivity; (d) Fertilizer use; (e) Manure use; (f) Fertilizer loss ratio; (g) Per capita disposable income from agricultural sector; (h) Farm size; (i) Machine input. (a)-(c), (d)-(e), (g)-(i) show the economic, environmental and social impacts of agricultural sustainability, respectively. The Baseline assumed no changes in the future. SSP1–4 refers to Shared Socioeconomic Pathways (SSPs) scenarios. NF is the abbreviation of new farming. The input, output, fertilizer, manure and machine are all weighted with the total cultivated area. Labour productivity is weighted with the total labour input. Farm size and income are arithmetic averages.

Source Data

Extended Data Fig. 4 Abandoned cropland changes under SSP scenarios by 2100.

(a) Abandoned cropland ratio change; (b) Relative change of abandoned cropland ratio compared to 2020. Abandoned cropland ratio is abandoned cropland area to the total cropland area across the whole country. Relative change is carried out in percentage terms. NF, New farming. SSP1–4 refers to Shared Socioeconomic Pathways (SSPs) scenarios. The Baseline assumed no changes in the future.

Source Data

Extended Data Table 1 Summary of the structural equation model shown in Fig. 2
Full size table
Extended Data Table 2 New farming mitigates ageing and its impacts on agriculture
Full size table

Supplementary information

Supplementary Information

This file contains Supplementary Text, Tables 1–7, Figs. 1–6, Methods, Code and References.

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Ren, C., Zhou, X., Wang, C. et al. Ageing threatens sustainability of smallholder farming in China. Nature 616, 96–103 (2023). https://doi.org/10.1038/s41586-023-05738-w

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