Modeling the Spatial Distribution of Arabica Coffee in Thailand by Environmental Factors

This research utilized the Maxent model to study suitable environmental parameters and
geographical regions for Arabica coffee cultivation in Chiang Rai. Occurrence coffee data in
2024, nineteen bioclimatic variables spanning 1950–2000, slope, and soil pH were collected. The
dataset was partitioned into a 70% training subset and a 30% testing subset. The model
demonstrated robust predictive performance with a high Area Under the Curve (AUC) score of
0.915. Based on analysis of variable contributions, Precipitation of Wettest Quarter was the most
influential factor (38.43%), followed by Mean Diurnal Range (24.53%), and Min Temperature of
Coldest Month (5.64%). Areas identified as having high suitability for Arabica coffee cultivation
constituted 2.04% of the study area, predominantly located in highland regions. Projections under
future climate scenarios (2021–2040) indicated an anticipated decline in cultivation suitability.
These findings are crucial for informing sustainable planning strategies for Arabica coffee
cultivation in the region.