فهرست مطالب soheila aghabeigi ami

Estimators of distance sampling methods based on random spatial pattern of trees are bias in non-random spatial pattern. The purpose of this study was to evaluate the effect of spatial pattern of oak trees on the results of quantitative characteristics estimation of three different stands by nearest-individual method estimators in Chaharzabar  forests in Islamabad, west of Kermanshah province. For this purpose, three stands were selected in the area and within each stand half one hectare plot was identified. After full callipering of trees in the stands, according to completely randomized design, 30 samples with  nearest-individual method in each stand carried out. Then, spatial pattern, density, canopy cover and tree height were calculated with nearest-individual sampling method. Results showed that from the three studied stands, two stands had random spatial pattern and one had clumped pattern. Of  five estimators of nearest –individual method based on acceptable accuracy criteria (range ± 10%) for estimate density of trees, the formula proposed by Byth and Ripley in the random spatial pattern and the formula suggested by Batcheler and Bell in aggregate pattern were the most appropriate estimators. In order to estimate trees canopy cover percentage, the formulas suggested by Byth and Ripley, Cottam et al. and Morisita in the random spatial pattern were appropriate. However,  none of them were appropriate to estimate the canopy percentage of trees in clumped spatial pattern. To estimate the height of the trees, since the height was calculated independently of the estimators, it was found that estimation of the tree height by this sampling method yielded good results in both random and clumped patterns. Finally, it can be concluded that the spatial pattern of the trees was effective on the estimators of the nearest-individual distance sampling method.