THE SPATIAL PATTERN OF A FOREST ECOSYSTEM

Statistical analysis of stands of trees as a whole need suitable metho ds of spatial statistics. Obviously, trees within a stand affect devel opment and survival of their neighbours. They interact and therefore h ave to be considered as a system of dependent random variates from an unknown stochastic process. One such statistical model which considers the spatial dependence among trees in a forest and their characterist ics is a marked point process. The 'points', called events in spatial statistics, are the tree positions and the 'marks' are tree characteri stics such as crown lengths or tree species. A minimal prerequisite fo r any serious attempt to model an observed pattern is to test the hypo thesis of complete spatial randomness (CSR). Concerning the fitting of parametric models to spatial point patterns, a class of models which seems potentially useful for describing the present type of data is th e class of marked Gibbs (pairwise interaction) point processes. Essent ially, these processes characterise the interaction between events by some parametrically specified function of distance. In this paper seve ral statistical methods to test CSR are described and marked Gibbs pro cesses are used to fit a model in two different forest ecosystems. (C) 1998 Elsevier Science B.V. All rights reserved.