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<p>Agriculture faces increasing climate, financial, environmental, and social challenges, which bring into question its ability to withstand shocks and pressures. Strengthening agricultural resilience can effectively address these issues. Reasonably evaluating agricultural resilience and improving it based on climate-smart agriculture practices is particularly important to agricultural sustainability. This research utilized the cloud model and the dynamic fuzzy set Qualitative Comparative Analysis approach to evaluate agricultural resilience levels, grounded in the Drive-Pressure-State-Impact-Response framework, across 30 Chinese provinces from 2011 to 2022. It seeks paths to achieve high resilience from CSA technology, climatic productive potential, digitization, and agricultural fiscal expenditure, and analyzes path selection under different grain production areas and levels of digital inclusive finance. Key findings include: (1) Agricultural resilience has shown a gradual upward trend, transitioning from low levels (2011–2014) to moderate (2015–2018) and medium-high (2019–2022) resilience. (2) Three driving pathways for agricultural resilience were identified: the digitalization-technology linkage, digitalization-technology-financial support enhancement, and digitalization-technology-climate resource hybrid approach. (3) Digitization and CSA technologies serve as core pillars, with their integration alongside fiscal spending or climate production potential further boosting agricultural resilience. (4) From the perspective of major grain-producing areas, CSA practices should be customized based on their unique natural conditions and socio-economic environments to enhance agricultural resilience. The path to agricultural resilience also varies under different levels of DIF. The importance of agricultural fiscal expenditure gradually weakens at higher levels of DIF, while digitalization and CSA technologies become key factors at moderate levels of DIF. At lower levels of DIF, digitization, climate production potential, and agricultural fiscal expenditure become strong supports.</p>

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Evaluation and pathways for achieving agricultural resilience under the framework of climate-smart agriculture

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年12月27日

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  • Yi Huang,
  • Feiwu Ren,
  • Yanwei Wang

摘要

Agriculture faces increasing climate, financial, environmental, and social challenges, which bring into question its ability to withstand shocks and pressures. Strengthening agricultural resilience can effectively address these issues. Reasonably evaluating agricultural resilience and improving it based on climate-smart agriculture practices is particularly important to agricultural sustainability. This research utilized the cloud model and the dynamic fuzzy set Qualitative Comparative Analysis approach to evaluate agricultural resilience levels, grounded in the Drive-Pressure-State-Impact-Response framework, across 30 Chinese provinces from 2011 to 2022. It seeks paths to achieve high resilience from CSA technology, climatic productive potential, digitization, and agricultural fiscal expenditure, and analyzes path selection under different grain production areas and levels of digital inclusive finance. Key findings include: (1) Agricultural resilience has shown a gradual upward trend, transitioning from low levels (2011–2014) to moderate (2015–2018) and medium-high (2019–2022) resilience. (2) Three driving pathways for agricultural resilience were identified: the digitalization-technology linkage, digitalization-technology-financial support enhancement, and digitalization-technology-climate resource hybrid approach. (3) Digitization and CSA technologies serve as core pillars, with their integration alongside fiscal spending or climate production potential further boosting agricultural resilience. (4) From the perspective of major grain-producing areas, CSA practices should be customized based on their unique natural conditions and socio-economic environments to enhance agricultural resilience. The path to agricultural resilience also varies under different levels of DIF. The importance of agricultural fiscal expenditure gradually weakens at higher levels of DIF, while digitalization and CSA technologies become key factors at moderate levels of DIF. At lower levels of DIF, digitization, climate production potential, and agricultural fiscal expenditure become strong supports.