Declining suitability for conversion of drylands to paddy fields in Northeast China: Impact of future climate and socio-economic changes

Abstract

Conversion of dryland to paddy fields (CDPF) is an effective way to transition from rain-fed to irrigated agriculture, helping to mitigate the effects of climate change on agriculture and increase yields to meet growing food demand. However, the suitability of CDPF is spatio-temporally dynamic but has often been neglected in previous studies. To fill this knowledge gap, this research developed a novel method for quantifying the suitability of CDPF, based on the MaxEnt model for application in Northeast China. We explored the spatiotemporal characteristics of the suitability of CDPF under the baseline scenario (2010–2020), and future projections (2030–2090) coupled with climate change and socioeconomic development scenarios (SSP126, SSP245, and SSP585), and revealed the driving factors behind it. Based on this, we identified potential priority areas for future CDPF implementation. The results show that the suitability of CDPF projects implemented in the past ten years is relatively high. Compared with the baseline scenario, the suitability of CDPF under the future scenarios will decline overall, with the lightest decrease in the RCP585 and the most severe decrease in the RCP245. The key drivers affecting the suitability of CDPF are elevation, slope, population count, total nitrogen, soil organic carbon content, and precipitation seasonality. The potential priority areas for the future CDPF range from 6,284.61 km² to 37,006.02 km². These findings demonstrate the challenges of CDPF in adapting to climate change and food security, and provide insights for food-producing regions around the world facing climate crises.

Keywords

Cropland conversion / Food security / Suitability / Climate change / Machine learning model / Northeast China

CRediT authorship contribution statement

Jiacheng Qian: Writing – review & editing, Writing – original draft, Software, Methodology, Data curation, Conceptualization. Huafu Zhao: Writing – review & editing, Supervision, Resources. Xiaoxiao Wang: Software, Data curation. Tao Wang: Software. Zhe Feng: Supervision, Conceptualization. Congjie Cao: Data curation. Xiao Li: Methodology. Aihui Zhang: Resources.

Declaration of competing interests

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

This work was supported by the Ministry of Education of Humanities and Social Science project, China (Grant No. 21YJA630121) and the National Key Technology R&D Program of Ministry of Science and Technology of China (Grant No. 2023YFD1500103) and the Tsinghua Rural Studies PhD Scholarship (Grant No. 202323) and 2023 Graduate Innovation Fund Project of China University of Geosciences, Beijing (Grant No. ZD2023YC043) and National Social Science Fund of China (Grants No. 19ZDA096 and 20&ZD090). We sincerely thank the editor and two anonymous reviewers for their help in improving the quality of the manuscript. Thanks to Dr. Xiaoliang Li for providing advice on the use of the MaxEnt model.

Supplementary materials

Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.geosus.2024.05.004.

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