Document Type : Research Paper
Authors
1 PhD Graduated in Foresty, Faculty of Natural Resources, University of Tehran, Karaj, Iran
2 Professor, Faculty of Natural Resources, University of Tehran, Iran
3 Associated Professor, Faculty of Natural Resources, University of Tehran, Karaj, Iran
Abstract
Beech forests in midland areas of Hyrcanian forests of Iran are the most important forests having the highest degree of naturalness. These forests are the valuable source of wood production and other forest products. One of the most important characteristics of plant communities is the spatial pattern of trees. Ecological process in forest ecosystems are directly influenced by the spatial patterns of trees and environmental constraints. Quantifying of spatial structure is an important component in describing natural ecosystems and their biodiversity. For appropriate management of forest ecosystems informative indices with minimum cost and time are needed. The aim of this study is to analyze the stand structure and spatial pattern in mixed beech forests. Data were collected from a 48 ha compartment in the educational and experimental forests of University of Tehran. Species and DBH of all trees with DBH > 7.5 cm were recorded and also the position of each tree was determined using azimuth and distance in order to prepare a tree position map. Using the K-Ripely function, the spatial patterns of Fagusorientalis, Carpinusbetulus, Acer velotinum and Alnussubcordata were determined as clustered. Results of the K-Ripely function were compared and confirmed with nearest neighbor of Clark & Evans index, which was considered as a control index. This research emphasizes on the spatial statistics application for tree spatial pattern investigation and the applied index and function in it provide useful information for sustainable forest management. Indeed, to be aware of natural process in forest ecosystems, forest managers need to evaluate natural forest structure and use the values of structure indices and function as reference for sustainable and close to nature management.
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