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<p>Agriculture in Meghalaya faces increasing exposure to climate risks, primarily due to its dependence on rain-fed systems within ecologically fragile hill topography and inadequate supporting infrastructure. This study evaluates district-level agricultural vulnerability across 11 districts using a composite index derived from 14 biophysical and socioeconomic indicators. A top-down, indicator-based framework was employed, with Principal Component Analysis applied to assign data-driven weights, ensuring methodological transparency and objectivity in the absence of direct stakeholder consultations. Indicators were normalized according to their functional association with vulnerability, and the resulting weighted scores were aggregated to calculate a district-wise Vulnerability Index (VI). The findings reveal pronounced inter-district disparities, with East Jaintia Hills (VI:0.784), South West Khasi Hills (0.778), and West Khasi Hills (0.674) identified as the most vulnerable, while West Garo Hills (0.428) and South West Garo Hills (0.245) emerge as the least vulnerable districts. Key drivers include limited access to institutional credit, poor road and market connectivity, and a low livestock-to-human ratio. The study aligns its findings with traditional agricultural knowledge and the objectives of SDG 2 (Zero Hunger) and SDG 13 (Climate Action), thereby proposing a localized, evidence-driven framework for developing climate-resilient agricultural strategies. The results provide actionable guidance for policymakers toward enhancing adaptive capacity and long-term sustainability in Meghalaya’s agriculture sector.</p>

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Climate vulnerability assessment of Meghalaya’s agricultural sector at the district level

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年12月31日

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  • Marbakor Mary Lynrah,
  • Vivek Lyngdoh,
  • Evenstone Wahlang,
  • Amica L. Nongrang,
  • Nivanaliza Wahlang,
  • Albert Chiang,
  • Joram Beda

摘要

Agriculture in Meghalaya faces increasing exposure to climate risks, primarily due to its dependence on rain-fed systems within ecologically fragile hill topography and inadequate supporting infrastructure. This study evaluates district-level agricultural vulnerability across 11 districts using a composite index derived from 14 biophysical and socioeconomic indicators. A top-down, indicator-based framework was employed, with Principal Component Analysis applied to assign data-driven weights, ensuring methodological transparency and objectivity in the absence of direct stakeholder consultations. Indicators were normalized according to their functional association with vulnerability, and the resulting weighted scores were aggregated to calculate a district-wise Vulnerability Index (VI). The findings reveal pronounced inter-district disparities, with East Jaintia Hills (VI:0.784), South West Khasi Hills (0.778), and West Khasi Hills (0.674) identified as the most vulnerable, while West Garo Hills (0.428) and South West Garo Hills (0.245) emerge as the least vulnerable districts. Key drivers include limited access to institutional credit, poor road and market connectivity, and a low livestock-to-human ratio. The study aligns its findings with traditional agricultural knowledge and the objectives of SDG 2 (Zero Hunger) and SDG 13 (Climate Action), thereby proposing a localized, evidence-driven framework for developing climate-resilient agricultural strategies. The results provide actionable guidance for policymakers toward enhancing adaptive capacity and long-term sustainability in Meghalaya’s agriculture sector.