The effect of forest stratification on precision estimation of quantitative features of trees by using N-tree sampling method in the forests of West Iran (Case Study: Dorood Lorestan province)

Quantitative and qualitative information of forest structure is the most important for forest management in Zagros forests. This study was done in order to investigate of effect forest stratification approach on the precision estimation of the quantitative features of trees in N- tree sampling methods (one, two, four, six and eight trees) in Dorood forest, Lorestan province. For this purpose, 141 2500 m2 (50 × 50 m) sample plots were selected in an area ca. 42 hectares and full-calipering inventory was done. Within each plot, the number of trees, diameter at breast height and canopy of each tree (largest/smallest crown diameter) were recorded for all trees with DBH ≥ 7.5 cm. The N-trees sampling methods were then designed in GIS software and according to the scale of the map were implemented in the forest. The forest was then stratified into three types ( 250 trees per hectare) by using the density (number per hectare). The statistical parameters for the number of trees per hectare, basal area per hectare and canopy cover percentage per hectare were calculated before and after the stratification. Results showed that with the implementation of the stratification in the N-tree sampling method, the estimated mean of the characteristics was closer to the real mean. It also eliminates the heterogeneity in the study area and reduces the standard deviation and the coefficient of variation. As well as stratification improved the heterogeneity in the study area and standard deviation and coefficient of variation were reduced. This increases the precision of the N-tree sampling method (one, two, four, six and eight trees) in Dorood forest. Therefore implementation of stratification in N-tree sampling method was positively assessed.