Assessing rural farmers’ climate vulnerability in Gambia: A PCA‑based index for sustainable development

Abstract

Purpose. This paper assesses the climate vulnerability of 400 smallholder farming households in rural Gambia by integrating exposure, sensitivity, and adaptive capacity into a composite vulnerability index, providing policy-relevant insights for climate-resilient development. Methodology. Household survey data from three rural regions (North Bank, Central River, Upper River) are analyzed using Principal Component Analysis (PCA) to derive data-driven weights for 23 indicators. The index is validated through associations with NGO support, government assistance, insurance, credit access, and agricultural extension. Results. North Bank exhibits the highest vulnerability (VI = -6.37) driven by low adaptive capacity despite minimal climate exposure. Upper River shows lower vulnerability (VI = +1.56) despite high climate exposure, owing to better socio-economic conditions. Validation reveals that NGO support and insurance reduce vulnerability (r = -0.82, -0.94), whereas government support paradoxically correlates positively (r = 0.79), likely reflecting endogenous targeting. Theoretical contribution. The study advances vulnerability assessment literature by applying PCA-based weighting to household-level data in a low-income African context, demonstrating that adaptive capacity is more decisive than biophysical exposure. Practical implications. Findings emphasize prioritizing investments in education, infrastructure, credit, and insurance over exposure-focused interventions. The index supports policy prioritization under Gambia’s Nationally Determined Contributions and National Adaptation Plans, enabling regional differentiation of adaptation strategies. Sustainable Development Goals (SDGs): SDG 1: No Poverty, SDG 2: Zero Hunger, SDG 13: Climate Actio