Unlocking the Habitat Suitability of Wild Olive to Improve Its industrial Potential: A Comprehensive Distribution Modeling Study

Abstract

Wild olive (Olea europaea L.) is a highly significant forest tree species, both in Türkiye and globally. Its oil and other extracts from the fruits and leaves are vital to various industries, including culinary, cosmetics, pharmaceuticals, and healthcare, making it a valuable non-timber forest product. However, its natural distribution is restricted to Mediterranean climates, emphasizing the need for conservation efforts to support its growth and expansion. Potential distribution modelling is one of the best studies to be done to protect a species and ensure its survival. In this study, the MaxEnt method, which relies exclusively on presence data, was used to generate a potential distribution map for wild olive. The environmental variables to be included in the modeling method were determined using the Analytic Hierarchy Process (AHP), one of the multi-criteria decision-making methods. From an initial set of 29 variables, AHP selected the top 11 for the final model. The resulting model demonstrated high accuracy, with an AUC value of 0.922, successfully identifying and mapping the potential distribution areas for wild olive across Türkiye.