Introduction: Oil palm productivity is influenced by climate variability through biological time lag effects due to its long reproductive cycle. Objective: This study aimed to analyze historical climate characteristics, evaluate the effects of macroclimatic variables on oil palm productivity using a time lag approach, develop the best regression model, and estimate the impacts of climate change under RCP 4.5 and RCP 8.5 scenarios at PT Kumala Jambi Prakasa. Method: Monthly data on rainfall, temperature, humidity, and Fresh Fruit Bunch (FFB) productivity during 2016–2025, along with bias-corrected Global Climate Model (GCM) projections, were analyzed using Pearson correlation with time lag (0–24 months) and multiple linear regression. Results and Discussion: The results showed that rainfall and humidity significantly affected productivity at an 8-month lag, while temperature had a significant effect at a 4-month lag. The developed multiple linear regression model explained 29.23% of the variation in oil palm productivity. Climate projections under RCP 4.5 and RCP 8.5 indicated declining productivity through 2035, with maximum reductions of 48.97% and 45.92%, respectively. These findings highlight the importance of adaptive strategies, including improved water management, climate-resilient varieties, and climate-based production planning. Conclusion: Oil palm productivity responds to climate variability through delayed physiological processes, and understanding these time lag effects is essential for developing long-term adaptation strategies under future climate change conditions.
Copyrights © 2026