Prediction by maximum entropy of potential habitat of the cork oak (Quercus suber L.) in Maamora Forest, Morocco

Abstract

In this paper, the maximum entropy (MaxEnt) algorithm was applied to estimate the current and potential distributions of cork oak (Quercus suber L.) in the Maarmora forest of Morocco to provide a basis for its conservation under climate change conditions in the Mediterranean basin. A total of 1,428 field-based spatial records of cork oak locations were used (altitude and 19 bioclimatic environmental variables) to model the potential distribution of the cork oak. The adjusted model had a good predictive quality (area under the curve=0.81). Precipitation during the wettest quarter of the year, seasonality in precipitation, altitude, and seasonal variations in temperature were the key factors determining the distribution of the cork oak in the Maamora forest. Most areas with currently suitable conditions for cork oak were located in the western and central Maamora forest regions, which enjoy a humid bioclimate and receive significant sea spray from the Atlantic Ocean. Moving away from the ocean, the humidity decreases, and the temperature increases, such that the cork oak faces difficulties in adapting and regenerating. The results can be used to identify the high-priority areas for cork oak restoration and conservation of this s ecies a ainst the ex ected im act of climate chan e