Effects of Spatial Distribution of Trees on Density Estimation by Nearest Individual Sampling Method: Case Studies in Zagros Wild Pistachio Woodlands and Simulated Stands

Distance methods and their estimators of density may have biased measurements unless the studied stand of trees has a random spatial pattern. This study aimed at assessing the effect of spatial arrangement of wild pistachio trees on the results of density estimation by using the nearest individual sampling method in Zagros woodlands, Iran, and applying a correction factor based on the spatial pattern of trees. A 45 ha clumped stand of wild pistachio trees was selected in Zagros woodlands and two random and dispersed stands with similar density and area were simulated. Distances from the nearest individual and neighbour at 40 sample points in a 100 × 100 m grid were measured in the three stands. The results showed that the nearest individual method with Batcheler estimator could not calculate density correctly in all stands. However, applying the correction factor based on the spatial pattern of the trees, density was measured with no significant difference in terms of the real density of the stands. This study showed that considering the spatial arrangement of trees can improve the results of the nearest individual method with Batcheler estimator in density measurement.