Simulating spatial distributions of forest trees by using data from fixed area plots

Cost is a critical factor for managing ecosystems. Common forest inventories are usually carried out at regular time intervals (e.g. every 10 years) and are the basis for management planning. This study investigated the potential of utilizing the data of common forest inventories for simulating the spatial distribution of forest tree locations. Fixed area plot sample data were taken from the University Forest of Pertouli, which is an uneven-aged Abies borisii regis Matf. forest. Using as criterion the index of dispersion, the tree spatial distribution was characterized as aggregated. The Neyman Type A distribution, a typical distribution of aggregated populations, was a good fit to the data, while tree locations simulation was based on the Poisson cluster process. The simulations resulting from the application of fixed area plot sampling do not incorporate information about the real distances between the trees, but they can describe adequately the spatial patterns of their locations in two-dimensional space and seem to be useful tools for managers of forest ecosystems. For similar populations the detection of their aggregation seems not to be affected by a considerable decrease of the number (up to 36) and the size (up to 125 m2) of sample fixed-area plots. This method is cost effective and its use, potentially in combination with other methods, could be further investigated for its advantages.