Predicting suitable habitats of the major forest trees in the Saïda region (Algeria): A reliable reforestation tool

Abstract

Abstract Modeling potential habitat for plant species is an appropriate approach to maintain biodiversity, developing proper reforestation campaigns, and rehabilitating ecosystems. In this study, we investigated the potential distributions of four forest species, namely, Quercus faginea Lam.; Q. ilex L.; Tetraclinis articulata (Vahl) Mast.; and Pistacia atlantica Desf. In the north-western Algeria at Saïda region. The MAXENT method was used to model the habitats of these species using topographic data as predictive variables at a resolution of 100 m. Moreover, the model evaluation process was achieved using the area under the operating characteristic curve of the receiver (AUC) and Jackknife test. The generated models were found to be accurate. AUC results are ranging between 0.98 and 0.91 for the training set and 0.87 and 0.97 for the testing set. The results of the distribution probability of this study provide a useful tool for the local decision-makers of reforestation campaigns.