{
  "abstract": "Extreme climate events may increasingly undermine the stability of regional grain supply in China. Yet systematic evidence remains limited on where composite climate hazards coincide with strong regional grain supply performance and how individual climate extremes are nonlinearly associated with such performance. Using a prefecture-level panel for 2000–2024, we construct a comprehensive extreme climate hazard index (CECHI) encompassing extreme heat, extreme cold, extreme precipitation, persistent drought, and compound events. We then integrate spatiotemporal analysis, quantile-based spatial matching, and an XGBoost–SHAP framework to characterize hazard–supply performance configurations, identify climate variables with relatively high explanatory importance, and detect empirical breakpoints in their statistical associations with regional grain supply performance (RGSP). The results indicate that: (1) CECHI declined overall with substantial temporal fluctuations, while its broad spatial pattern remained relatively stable. Composite climate hazards were persistently higher in western and northeastern China than in eastern and central China. Climate hazard and RGSP did not exhibit a simple inverse spatial relationship; high-hazard–high-RGSP areas were concentrated in Northeast China, Inner Mongolia, and the Hexi Corridor. (2) The annual minimum daily minimum temperature (TNn), tropical nights (TR), and frost days (FD) showed the largest explanatory contributions to variation in RGSP, while the relative importance of persistent drought and compound dry-cold and dry-hot events increased over time. (3) Most climate indicators exhibited nonlinear, asymmetric, and region-dependent statistical associations with RGSP, and the highest-importance climate variables varied across prefecture-level cities and the nine agricultural regions. These findings indicate that food-security planning should consider not only regions with relatively weak grain supply performance but also major grain-supplying regions exposed to comparatively high levels of climate hazard, while adaptation measures should be tailored to region-specific climatic constraints.",
  "abstract_shown": true,
  "affiliations": [
    "Jiangsu Academy of Agricultural Sciences, Nanjing 210014, China; Jiangsu Rural Revitalization Research Institute, Nanjing 210014, China",
    "Jiangsu Academy of Agricultural Sciences, Nanjing 210014, China; Jiangsu Rural Revitalization Research Institute, Nanjing 210014, China; Corresponding author at: Jiangsu Academy of Agricultural Sciences, Nanjing 210014, China."
  ],
  "article_type": null,
  "arxiv": null,
  "author_total": 2,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Dapeng Zhou"
    },
    {
      "affs": [
        1
      ],
      "name": "Honghua Huan"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/c70f4p2skm994.bib",
  "cited_by": 0,
  "doi": "10.1016/j.ecolind.2026.115746",
  "fulltext_url": "http://www.sciencedirect.com/science/article/pii/S1470160X26011489",
  "id": "c70f4p2skm994",
  "issns": [
    "1470-160X",
    "1872-7034"
  ],
  "landing_url": "https://doi.org/10.1016/j.ecolind.2026.115746",
  "language": "en",
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "lcc",
      "QH540-549.5"
    ],
    [
      "openalex",
      "1105|Climate change impacts on agriculture"
    ]
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  "openalex": "W7223254330",
  "pdf_url": null,
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-30",
  "publisher": "Elsevier",
  "ris": "https://research.draconitic.com/paper/c70f4p2skm994.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T13:44:29Z",
      "native_id": "3221f0cc3994497c9767147a10011cba",
      "source": "doaj",
      "url": "https://doi.org/10.1016/j.ecolind.2026.115746"
    }
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  "subjects": [
    {
      "field": "biology",
      "origin": "openalex:1105|Climate change impacts on agriculture",
      "subfield": "ecology"
    }
  ],
  "title": "Nonlinear associations between comprehensive extreme climate hazard and regional grain supply performance in China: evidence from explainable XGBoost–SHAP models",
  "title_text": "Nonlinear associations between comprehensive extreme climate hazard and regional grain supply performance in China: evidence from explainable XGBoost–SHAP models",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T13:44:29Z",
  "url": "https://research.draconitic.com/paper/c70f4p2skm994",
  "venue": "Ecological Indicators",
  "versions": []
}