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Vulnerability to climate change refers to the degree to which a system, community, or region is susceptible to and unable to cope with the adverse effects of climate variability and change. Analysing vulnerability is a crucial step for developing adaptation strategies, prioritising resources, and implementing sustainable policies. Vulnerability assessments integrate scientific, socio-economic, and policy dimensions, making use of both qualitative and quantitative tools. The methods for analysing vulnerability to climate change are diverse, ranging from indicator-based approaches to participatory frameworks, and each method provides insights into exposure, sensitivity, and adaptive capacity of systems at risk. One of the most widely used approaches is the indicator-based method. This method employs quantitative indicators such as temperature variability, precipitation anomalies, water availability, poverty levels, literacy rates, and health infrastructure to construct indices that represent vulnerability. These indices are often developed through composite measures like the Climate Vulnerability Index (CVI) or the Livelihood Vulnerability Index (LVI). The advantage of indicator-based approaches lies in their ability to integrate multiple dimensions of vulnerability into a single metric, enabling comparisons across regions. However, they often face challenges in data availability, standardisation, and weighting of indicators, which can influence the accuracy and objectivity of the results. Another key method is participatory vulnerability assessment (PVA), which emphasises the involvement of local communities in identifying risks, exposures, and coping mechanisms. PVA includes participatory rural appraisal techniques such as mapping, seasonal calendars, focus group discussions, and storytelling. This method acknowledges that local populations possess valuable knowledge about climate risks and their impacts on livelihoods. By engaging stakeholders directly, PVA ensures that vulnerability analysis is context-specific and _______ _________ ____ ___ ____.
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