Modeling the natural regeneration of Cedrus libani A. Richard in Slenfeh, Syria, using binary logistic regression

Abstract

Species distributions and abundances are undergoing rapid changes worldwide. This highlights the significance of reliable, integrated information for guiding and assessing actions and policies aimed at managing and sustaining the many functions and benefits of species. Mapping and monitoring of forest extent is a common requirement of regional forest inventories and public land natural resource management which requires generation of an accurate database on spatial forest structure distribution and environmental variables. Remote Sensing and Geographic Information Systems (GIS) technology is an effective tool in modern management programs for forest ecosystems. The environmental factors which probably affect in the natural regeneration of Cedrus libani A. Richard in its natural distribution forest in Slenfeh, Syria, were modeled using the binary logistic regression (BLR) model. The effect of environmental factors (spatial and forest structure factors, topographic factors, and spectral indicators) was studied, each one as single set and then their combined effect with each other on the probability of the presence of C. libani seedlings in Slenfeh. The accuracy of the model was clearly improved by studying the effect of environmental factors combined together (84%), while the accuracy of the other studied models did not exceed 70%. The results showed that the forest cover (Cedrus libani, broad leaved except oaks, mixed) is considered a good condition for natural regeneration of C. libani, while the lack of soil moisture in summer was a negative factor in the possibility of the presence of C. libani seedlings in Slenfeh.