Predicting the Distribution of Taxus baccata L. in Morocco Under Climate Change Using MaxEnt: Implications for Conservation and Sustainable Management

Abstract

Taxus baccata is a rare conifer species that occurs as isolated individuals or in small patches in Morocco and is listed in the National List of Protected Flora. To predict its current and future distribution areas, based on 41 occurrence records and 11 bioclimatic variables, the Maxent model was applied using cross-validation (1000 replicates) with logistic outputs under current climate conditions and the SSP1-2.6, SSP2-4.5, and SSP5-8.5 future climate scenarios. Our results indicate high-performing models (AUC > 0.966, TSS > 0.862). The bioclimatic factors that most influence the current potential geographic distribution of yew are the Mean Temperature of Driest Quarter (Bio9) and Isothermality (Bio3). The spatial distribution indicates that the current potential range of yew is discontinuous, with a current suitable area not exceeding 4602 km2. Predictive modeling identifies a decline of the predicted suitable habitat under the SSP1-2.6 and SSP2-4.5 scenarios, fueled by both climate change and human activities. Given the species’ limited dispersal and the ongoing fragmentation of its habitat, immediate conservation actions, both in situ and ex situ, are urgently needed. This study demonstrates the vital role of predictive modeling in identifying these vulnerabilities to guide long-term sustainability efforts.