Model based mapping of potantial distribution and productivity for of brutian pine (Pinus brutia ten.) in the Gaziantep district

This study was carried out with the aim of modeling and mapping the potential distribution and productivity of the Red pine (Pinus brutia TEN.) by investigating the ecological characteristics of the species in the forests of the Gaziantep district. Data were collected from 163 plots for the potential distribution (presence-absence data) and 62 plots for the productivity (site index) of the species in the study area. While Logistic Regression Analysis and Classification Tree Technique were used to obtain the potential distribution model of the Red Pine, Multiple Regression Analysis and Regression Tree Technique were used for the productivity modeling. The 6th Model of Logistic Regression Analysis (training data ROC: 0.880, test data ROC: 0.886) gives the most descriptive results for the potential distribution of the Red Pine species in the district, while the most affective results for the productivity of the species were obtained from the 3rd Model of the Multiple Regression Analysis (training data ROC: 0.762, test data ROC: 0.736). As a result of Logistic Regression Analysis, the variables in the potential species distribution model were the precipitation of warmest quarter and the distance from the sea. The alluvium, the precipitation of warmest quarter and the heat index were found as the variables that affect the productivity of the species in the district, respectively. Potential distribution and productivity maps of the Red pine species at the regional scale were obtained by using the models in the Geographical Information Systems (GIS). Finally, the areas where the potential distribution estimate value of the species is over 0.5 and the productivity map were overlapped, and the optimum areas in terms of productivity were mapped again as the most suitable potential distribution areas of the species. In addition, as a result of the Interspecific Correlation Analysis, Cedrus libani Rich., Rosa canina L. and Quercus cerris L. species were determined as negative indicators for the potential distribution areas of the Red pine in the district. As a result of the Spearman Correlation Analysis, Quercus coccifera L. was the only statistically significant positive indicator of the Red pine productivity in the district. As a result, the model information and final maps obtained from this study are important in determining the priority areas in the afforestation studies to be carried out at the regional scale for this species. Key Words: Distribution, Gaziantep, Mapping, Red Pine, Modeling, Productivity 2020, 94 pages