The efficiency of distance- and density-based indices in estimating the spatial pattern of trees in forests (Case study: Wild Pistachio Research Forest, Fars province, Iran)

Abstract

It is so important to know about biological and ecological characteristics of trees of a stand, in forest management. The first step to achieve this knowledge is to recognize the spatial pattern of trees. So it is necessary to apply suitable methods to have a reliable and quick estimation of the spatial distribution of trees. This research was aimed to compare the important and mostly applied distance- and density-based indices, utilized to estimate the spatial pattern of trees. For this purpose, a pure wild pistachio stand was full-callipered in Fars Wild Pistachio Research Forest, Iran. The true spatial pattern of the trees was determined by nearest neighbor method. The efficiency of each index was then evaluated by estimating the spatial distribution of the trees, utilizing the indices. The true spatial pattern of the wild pistachio trees in the studied stand was clumped. The results showed that only the two density-based indices of “dispersion” and “heterogeneity factor” could not detect the clumped pattern of wild pistachio trees among the investigated indices. The two distance-based indices of “Eberhardt” and “Hines” could estimate the clumped pattern of the wild pistachio trees among the applied indices as well. In general, the density-based indices performed much better than the distance-based indices in this research and this conclusion should be considered in the future studies on pure wild pistachio stands

Keywords

• Spatial pattern
• wild pistachio
• density-based indices
• distance-based indices