Rooted in Crisis, Growing Solutions: Economic Impacts and Adaptive Pathways for Fiji's Climate-Threatened Sugarcane Industry

Shifadjzic Khan¹Byung-Wook Yun^1,2*

• ¹The Graduate School, Department of Food Security and Agricultural Development, Kyungpook National University, Daegu, Republic of Korea
• ²Laboratory of Plant Molecular Pathology and Functional Genomics, Department of Applied Biosciences, Kyungpook National University, Daegu, Republic of Korea

Small Island Developing States (SIDS) are increasingly exposed to climate hazards that threaten agricultural productivity. Fiji's sugarcane sector, vital for rural incomes and foreign exchange, faces floods, droughts, cyclones, and irregular rainfall alongside rising input costs. Understanding farm-level climate vulnerability is critical for guiding adaptation. A convergent mixed-methods approach was employed, combining surveys of 100 smallholder farmers, panel regression to estimate hazard-specific yield elasticities, and AI-assisted scenario modeling integrated with ADB climate projections. Sampling was stratified to capture variation in farm size, location, and cooperative membership, and survey reliability was ensured through cross-validation with production records. Floods, droughts, and rainfall variability reduced yields by 12–28%, with droughts showing the highest sensitivity (β = -0.23, p < 0.01). Socio-institutional constraints, including limited cooperative support, inadequate extension services, and low youth engagement, amplified vulnerability. Integration of AI-assisted scenarios provided validated, farm-level projections and highlighted priority adaptation strategies. Targeted water management and accelerated varietal upgrading are critical to sustaining productivity. Coordinated investments in drainage, stress-tolerant varieties, and collaborative farmer-extension programs can narrow adaptation gaps in Fiji. While centered on Fiji, the analysis provides a globally relevant framework for assessing climate-induced yield elasticities and AI-validated adaptation scenarios in coastal smallholder cane systems. Our findings offer transferable lessons for coastal smallholder sugarcane systems across tropical Asia, Africa, and the Caribbean. This combined empirical–AI approach offers a replicable template for climate-resilience analysis across tropical agriculture.