The effects of climate change on growth and stand dynamics of trojan fir (Abies nordmanniana subsp. bornmulleriana Mattf.) forests in the Ilgaz mountain

In this research, which was carried out as a doctoral thesis in the pure and natural Uludağ fir (Abies nordmanniana subsp. bornmülleriana Mattf.) forests (Gcd3) located on the border of natural forest and trees of Ilgaz Forestry Directorate, the growth, dynamics and natural limits of global climate change (global warming) in fir forests. As a preliminary assessment, it is aimed to provide some basic and applied information on the subject to practitioners and future academic studies. In the sample areas taken from the stands at the natural forest line in the study area, the mean height breast diameter is between 25.4-40.3 cm, the mean height is between 13.8-22.6m, and the mean number of trees is 45.3 in pure fir stands with an mean age of 67-97 years. It was determined that it varied between -53.6 units. In addition, it was determined that 5 of the 10 stands where measurements and determinations were made were selected and 5 were pure fir forests that turned into a one layered establishment. In the study, the changes in the diameters of the fir colonies at the tree line were tried to be determined by measurements. Accordingly, the mean diameter of natural fir juvenility colonies was 1,328m in 2019, 1,407m in 2020 and 1,492m in 2021. In the research, the mean colony length of the youth colonies, which were measured by years, was determined as 1.51 m in 2019, 1.53 m in 2020 and 1.55 m in 2021. The distances of natural fir juvenility colonies to the natural tree line were also measured over the years. The mean distance values of fir juvenility colonies from the natural tree line were determined as 1,846 m in 2019, 1,901 m in 2020 and 1,913 m in 2021. The mean height values of juvenility fir individuals of different ages in fir juvenility colonies located on the natural tree line were determined as 5.3 cm in 2019, 6.4 cm in 2020 and 7.2 cm in 2021. After the evaluations, the mean root collar diameter of fir juvenility of different ages was determined as 15.6 mm in 2019, 18.9 mm in 2020 and 22.4 mm in 2021. The mean number of fir juvenility of different ages in the colonies per square meter was determined as 15.73 pieces/m2 in 2019, 12.46 pieces/m2 in 2020 and 9.38 pieces/m2 in 2021. As a result of the annual ring analyzes carried out in the research, it was revealed that the trend consistency between the sample data and the measurements taken on a yearly basis was high (0.79-1.00). A chronology of 96 years (from 1926 to 2020) growth ring widths of fir with a mean sensitivity value of 0.220 was established. The common interval analysis statistics of the chronologies determined that the mean correlation between trees and the signal-to-noise ratio were 0.677 and 7.412, respectively. It has been determined that the precipitations in spring and summer have a positive effect on annual ring development in Uludağ fir individuals at the forest line of Ilgaz Mountain, but the extreme temperatures especially in the late spring and summer seasons and the dry periods caused by these have a negative effect on annual ring development. The effects of global warming in the research area were also evaluated according to the SSPs245 and SSPs585 scenarios. According to the SSPs245 climate scenario, if the average temperature increases by 2.5ºC, 6102.9 hectares of forests in the research area will switch to "Semi-Arid" climate type in 2060 and 9652.7 hectares in 2100. In case of an increase of .8ºC, it is estimated that there will be a significant decrease in forest areas in "Humid" and "Semi-humid" climate types in 2060, while the areal distribution in forest areas in "Semi-Arid" climate type is expected to be quite high. Again, according to the same climate scenario, the possibility that the forest area with a size of 4841.6 ha, which had never existed in the research area before in 2100, will transition to the "Arid" climate type, and again in 2100, according to the same scenario, Uludağ fir in the "Humid" climate type has emerged. It is predicted that all of the forest belts that it dominates will disappear. In the research, using the findings obtained from the measurements made in the quantitative characters of the fir individuals in the experimental areas and their youth and the results obtained by the application of the WorldClim scenarios in the research, in determining the changes due to global climate change and the most important factors causing these changes, it is now used in statistics and in multidimensional decision-making processes. widely used kNN (K-Nearest Neighbors), LVQ (Learing Vector Quantization), SVM (Support Vector Machine), RPART (Decision Trees) and RF (Random Forest) mechanical learning algorithms have been applied. In terms of mechanical learning algorithms applied for this purpose, the best estimating algorithm was the "Random Forest (RF)" algorithm with accuracy levels and degrees of 76.62%, 77.93% and 79.76% as of 2019, 2020 and 2021. This algorithm was followed by kNN, LVQ, SVM and RPART mechanical learning algorithms, respectively. In the estimation studies made with these algorithms, the most important variables were the highest temperature (0.983), the lowest precipitation (0.945) and relative humidity (0.892), according to factor loads.