The potential distribution of the ecological features of dog rose (Rosa canina L.) in modeling and mapping the Gaziantep region of Nur mountain

This study was carried out in order to make potential distribution modeling of dog rose (Rosa canina L.) species found naturally in Nur Mountain, Gaziantep. In this study Data obtained from 79 sample sites used. Interspecific correlation analysis (ICA) was applied to define indicator species of dog rose. The results of the applied ICA, showed that Abies cilicica Carr., Pinus nigra Arnold. and Rubus caesius L. were positively associated with dog rose whereas Pinus brutia Ten. became negative its indicator species. Classification and regression tree technique (CART) and maximum entropy approach (MAXENT) have been used to obtain the distribution models of the species. Binary data was used as a response data while applying CART. As for MAXENT, response data became presence-only data. Climatic, topographical variables and bedrock formation were used as explanatory data during the modeling processes. The optimum model obtained from CART was built by altitude, aspect and heat index. The variables found in the MAXENT model were altitude, slope % and topographical position index. According to the results of ten-fold cross validations, ROC values of the models were found more than 80 %. Geographical information systems were used for visualizations of the models. The obtained model based maps pointed out that habitat as the most suitable sites of dog rose are the lower and middle parts of the valleys found in the upper zone of the Nur Mountains. The results obtained by this study are fundamental for any kind of planning and implementation activities for the species of dog rose in Nur Mountain and its close environs.