Modeling the Degradation of Hyrcanian Forests Using Logestic Regression Method (Case Study: Shenrood Forests, Guilan)

Abstract

Having accurate quantitative and qualitative information about the state of forest stands, is necessary for any basic management and planning, to reduce the effects of forest degradation. The current study aimed to model the destruction of Hyrcanian forests under the effects of density and volume (per hectare) variables, using logistic regression. In total, 252 plots of 1000 m2 area were measured. In each sample plot, species name, Diameter at Breast Height (DBH), height, density, volume and the presence or absence of forest degradation were measured and recorded. To model forest degradation, logistic regression model was utilized and Omnibus test, log-likelihood and pseudo r-square (Cox&Snell and Nagelkerke) coefficients were used to evaluate the model. Results showed that the mean of density and volume of trees were 136.8 tree and 239.9 m3/ha, respectively. In addition, the results indicated that 46.82% of the study area was degraded. The results of correlation test showed that there was a srtong negative correlation between quantitative variables and the forest degradation. The independent variables of density and volume of trees were respectively explained 61.6 to 82.3% of the variance of the dependent variable (forest degradation). Among the input variables of the regression model, the effects of density and volume were significant on the forest degradation and it was possible to predict the changes of dependent variables (presence or absence of forest degradation).

Keywords

• degradation modeling
• logestic regression
• structure changes
• shenrood forests of guilan