Modelling the Adaptation of Some Cultural Plants Produced in Thrace Region to Climate Change

Today, the effects of climate change have started to be experienced and will continue to be experienced. It is estimated that many sectors will be affected by climate change. The agricultural sector is one of these sectors. Thrace Region is one of our important regions that contribute to wheat, canola, and sunflower production in Turkey. Therefore, when unpredictable situations arise with climate change, it is very important to accurately determine how the cultivation areas of these three plants, which have an important role in the agriculture and food sector, will change in the future against climate change. First of all, it is necessary to predict precisely how the climate will change, and then to determine what precautions should be taken by making plans. The aim of this study is to predict how climate change will affect the geographical distributions of wheat, canola and sunflower plants grown in the Thrace Region in the future, using a plant suitability model. For this purpose, the suitability of wheat, canola and sunflower plants for the current period (1950-2000) in the Thrace Region was determined using the Ecocrop module included in the DIVA-GIS program, and then in line with the results of the HADGEM2_ES model RCP4.5 and RCP8.5 scenarios for the next period, in the 2050s, suitability estimates were made for these three plants by using the Ecocrop module. Current and future prediction results are compared with each other. As a result, in the TR21 Thrace Region in the 2050s, in the HADGEM2_ES model RCP4.5 scenario for wheat, suitable, very suitable, and excellent areas will be replaced by not suited, very marginal, marginal areas, respectively. This will be more severe under RCP8.5 scenario. For canola, suitable and very suitable areas will be replaced by suitable and excellent areas, respectively, in the 2050s, and this positive situation will occur more in the RCP4.5 scenario. In sunflower, on the other hand, it has been predicted that the areas that are excellent current will not change in the future. It is recommended that producers, decision makers and practitioners direct the future in line with these results while planning.