Understanding climate change effects on integrated agricultural livelihoods: a PCA-based vulnerability assessment in Gosaba Block, West Bengal, India

The Indian Sundarban region, situated along the Bay of Bengal coast, stands out as a significant climate vulnerability hotspot, particularly prone to cyclones and coastal or river flooding. Climate change has notably impacted the livelihoods of numerous developing nations, particularly those reliant on agriculture. This study delves into the climate change-induced Integrated Agricultural Vulnerability within Gosaba Block of South 24 Parganas District, West Bengal. An Integrated Agricultural Livelihood Vulnerability Index (IALVI) was meticulously crafted, integrating 38 sub-components across nine principal domains, encompassing exposure, sensitivity, and adaptive capacity to climate change. Principal component analysis was utilized to discern key indicators associated with each IALVI component. The study unveiled noteworthy spatial variations in vulnerability across villages. Chhota Molla Khali and Pakhiralay villages secured the highest IALVI scores (0.696), while Pathankhali village recorded the lowest (0.261). The first twelve principal components (PCs) explained a substantial majority (93.54%) of the observed variance. Spearman's rho analysis revealed a notable positive correlation between exposure (0.510, p 0.000) and sensitivity (0.368, p 0.009) with agricultural livelihood vulnerability, while adaptive capacity dimensions (- 0.467, p 0.001) exhibited a negative correlation with the IALVI. Additionally, the study emphasized that exposure emerged as the strongest dimension (0.687), followed by adaptive capacity (0.640) and sensitivity (0.577). Notably, villages such as Chhota Molla Khali, Pakhiralay, Chimta, Kumirmari, Tentultala, and Sonagar displayed markedly high vulnerability levels to climate change, with IALVI values exceeding 0.607. Conversely, villages like Radhanagar Purba, Ramnagarar, Mitrapur, Bally, Manmathanagar, Chandipur, Battali, Jhaukhali, Gopalkata, Hamilton Abad, and Pathankhali demonstrated notably low vulnerability, with index values below 0.408. These insights will prove invaluable for policymakers in formulating effective strategies to address climate risks within the study area.