Evaluation of probability-statistical functions in order to fit canopy classes of trees in Chartagh forests

Subject Areas : natural resorces

Mehrdad Mirzaei ¹ , Ismaeil Moradi Emamgheysi ² , Amir Eslam Bonyad ³ , Iraj Hassanzad Navroodi ⁴

1 - PhD Graduated in Forestry, Faculty of Natural Resources, University of Guilan, Guilan, Iran.*(Corresponding Author)
2 - M.Sc. Student in Forestry, Faculty of Natural Resources, University of Guilan, Guilan, Iran.
3 - Professor, Faculty of Natural Resources, University of Guilan, Guilan, Iran.
4 - Associate Professor, Faculty of Natural Resources, University of Guilan, Guilan, Iran.

Received: 2016-05-27 Accepted : 2017-03-01 Published : 2022-05-22

Keywords: Zagros, Probability distribution functions, quantitative variables, modelling,

Abstract :

Background and Objective: The distribution of canopy classes is the most important structural characteristics of Zagros forest stands. Determining the fitting pattern of canopy classes in Zagros forests shows that, the overall status of these forests from the destruction process and ecological sequence points of view at different times. The aim of this research was to evaluate of probability-statistical functions in order to fit canopy classes of trees in Chartagh forests of Ardal city, Chaharmahal ve Bakhtiari, Iran.Material and Methodology: For this purpose, an area of 50 hectares in Ardal forests was selected (3157 trees) were fully callipered and statistically analyzed. Exponential, Gamma, Normal, Beta, Weibull and Log-normal probability distribution patterns were fitted to crown canopy classes. Characteristics of distribution patterns were estimated using maximum likelihood method. Kolmogorov-Smirnov, Anderson-Darling and Chi-square tests were used for comparing of actual probability and probability which derived from functions.Findings: The results of fitting tests showed that log-normal probability distribution was suitable for canopy classes modelling in Chartagh forests.  Discussion and Conclusion: Log-normal probability distributions can be used for those who want to simulate changes of forests

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