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Updated: Jan 10, 2026

Author Spotlight: Unraveling Plant Responses to Abiotic Stresses Using the PlantScreen Robotic Platform
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District-level climate vulnerability assessment in Meghalaya using an IPCC AR5 framework.

Vivek Lyngdoh1, Marbakor Mary Lynrah1, Evenstone Wahlang1

  • 1Meghalaya Climate Change Centre, Meghalaya Basin Development Authority (MBDA), Planning, Investment Promotion and Sustainable Development Department, Government of Meghalaya, Shillong, Meghalaya, 793003, India.

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|November 27, 2025
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Climate change vulnerability is high in Meghalaya

Keywords:
AdaptationAdaptive capacityDriversIndicatorsSensitivitySusceptibility

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Area of Science:

  • Environmental Science
  • Climate Change Adaptation
  • Socio-economic vulnerability assessment

Background:

  • Climate change presents significant risks to vulnerable regions like Meghalaya in the Indian Himalayas.
  • Assessing district-level climate vulnerability is crucial for targeted adaptation strategies.

Purpose of the Study:

  • To assess and compare climate vulnerability across Meghalaya districts.
  • To identify key drivers of vulnerability and inform adaptation planning.
  • To develop a replicable framework for vulnerability assessment in data-scarce mountainous areas.

Main Methods:

  • An indicator-based framework using eight biophysical and socio-economic indicators (2020-2024).
  • Data normalization, expert-assigned indicator weights, and Composite Vulnerability Indices (CVI) generation.
  • Geographic Information System (GIS)-based spatial analysis to attribute indicator contributions.

Main Results:

  • West Khasi Hills and East Garo Hills identified as most vulnerable districts.
  • Vulnerability drivers include steep slopes, forest degradation, and high poverty.
  • East Jaintia Hills and South West Khasi Hills show lower vulnerability due to adaptive capacities.

Conclusions:

  • Enhancing forest conservation and livelihood diversification is critical for high-risk districts.
  • Strengthening social protection mechanisms is essential for reducing climate vulnerability.
  • The study provides a replicable model for rapid vulnerability assessment in data-scarce mountainous regions.