Assessment and prediction of oak trees decline using logistic regression model (Case study: Bivareh forest, Malekshahi-Ilam)

Document Type : Research Paper

Authors

1 Associate professor, Forestry Department, University of Ilam

2 M.Sc. of Forestry, University of Ilam

3 Ph.D. Student of Forestry, Sari University of Agriculture Sciences and Natural Resources

Abstract

    Stresses caused by recent droughts and fine dust lead to physiological weakness of oak trees as the insect outbreaks and pathogens lead to oak tree decline in the Zagros forests. To evaluate the effect of physiographic factors (terrain relief), forest cover density and soil on the amount and distribution of dead standing oak trees, a logistic regression model was used. An area of 540 ha of oak forests in the Bivareh region from Malekshahi country in Ilam province was selected. Global positioning system was used for recording all dead standing oak trees. Then, using the recorded points of dead standing trees and digital elevation model, different required maps of the study area like distribution map of dead standing oak trees, elevation classes map, aspect and slope percentage maps, forest density map and soil map were developed. In order to understand the relationship of each factor with dead standing oak trees a logistic regression model was used, with the maps of aforementioned factors as independent variables and the map of location of dead standing oak trees as the dependent variable. The results showed that with increasing altitude in the western and southern aspects, increasing forest cover density and in areas with shallow soils and steep terrain the amount and distribution of dead standing oak trees were increased. Finally, based on the current position map of dead standing oak trees, the effects of independent variable probability maps of dead standing oak trees for the future was produced. 

Keywords

References

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Iranian Journal of Forest and Range Protection Research
Volume 13, Issue 1 - Serial Number 1
September 2015
Pages 20-33

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History

  • Receive Date: 14 August 2014
  • Revise Date: 22 September 2015
  • Accept Date: 08 June 2015

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