Abstract: Among the challenges of successful forest plantations is to determine where they are suitable to be established. In this work, MaxEnt, a machine learning Species Distribution Model (SDM) based on the principles of Maximum Entropy, was applied for Falcata plantation suitability modeling and mapping in Caraga Region, Mindanao, Philippines. The model was found to have acceptable model performance based on the average training and test Area Under the Curve (AUC) values of 0.78 and 0.76. A 1 km x 1 km Falcata suitability map was generated using the model. It was also used to determine the relative contributions of various environmental variables to Falcata suitability distribution.
