Fresenius Environmental Bulletin, cilt.30, sa.1, ss.406-413, 2021 (SCI Expanded İndekslerine Giren Dergi)
Modeling the niches and distributions of the species using machine learning technique has be-come one of the effective tools of conservation planning today. Analyzing how the main species of our country will be affected by climate change is of great importance for planning about these species. Quercus coccifera which is one of the important evergreen oak species in Turkey, is easily selected by goats and constitutes a high proportion of their diets.
In this study, it is aimed to determine the po-tential distribution area of Quercus coccifera and how it will be affected by climate change. Biocli-mate layers with a resolution of approximately 1 km2 (30 arc seconds) obtained from the WorldClim database with the presence data of the species were cut within the specified limits and processed with the Maximum Entropy algorithm to determine the potential distribution area of the species in today's conditions.
In addition, the potential distribution area in 2050 and 2070 was modeled according to the cli-mate scenarios in RCP 2.6, RCP 4.5, RCP 6.0 and RCP 8.5 in order to determine how the distribution area of the species will be affected by climate change. According to the CCSM4 climate change scenario, it is seen that there are losses in potential distribution areas of the species in the future. The result of the study shows that the current and future spread areas of Quercus coccifera, which is spread in a very limited area, will gradually narrow.