Relationships between alpha plant diversity and environmental factors in the dedeg?l mountain (Yenisarbademli) district

This study was performed to investigate the relationships between environmental factors and alpha diversity (?) and woody plant species in region of the Dedeg?l Mountain (Yeni?arbademli). The diversity components was calculated by the data obtained from 103 sample area of the field inventory method. During the field studies, coverage classes of woody plant species and environmental factors were recorded in each sample plot. The climate variables of sample plots are obtained from the worldclim.org. Then, the variability coefficients of some of the variables recorded in the sample plots were calculated and new variables were determined by using digital elevation model (DEM). Multiple regression analysis (MLR) was applied to model dependent variables. As a result of multiple regression analysis (MLR), elevation variability was identified as the most important variable.Clustering analysis (CA) was used to group of the sample plots over the vegetation data matrix. In the study, regression analysis (RA) and detrended correspondence analysis (DCA) were applied to the vegetation matrix to determine the gradual distribution of sample plots over the ordination axes. As a result of applied regression analysis, it was determined that surface roughness variable is the environmental factor showing the highest correlation. In the same way, correlation analyzes between DCA axis values and environmental factors were applied. As a result, it has been determined that surface roughness is an important environmental variable on vegetation distribution. In addition, canonical compliance analysis (CCA) was applied in the last stage of study. As a result of this process, the most suitable environmental variables were obtained with surface roughness, BIO4 (temperature seasonality) and BIO12 (annual precipitation) variables. Shannon-Wiener index were found to be the most effective index, and surface roughness and elevation variables are the most important explanatory variables for alpha species diversity in the study area.