A practical approach to the study of spatial structure in simple cases of heterogeneous vegetation

Spatial heterogeneity is a characteristic of most natural ecosystems which is difficult to handle analytically particularly in the absence of knowledg e about the exogenous factors responsible fur this heterogeneity. While cla ssical methods for analysis of spatial point patterns usually require the h ypothesis of homogeneity, we present a practical approach for partitioning heterogeneous vegetation plots into homogeneous subplots in simple cases of heterogeneity without drastically reducing the data. It is based on the de tection of endogenous variations of the pattern using meal density and seco nd-order local neighbour density functions that allow delineation of irregu larly shaped subplots that could be considered as internally homogeneous. S patial statistics, such as Ripley's K-function adapted to analyse plots of irregular shape, can then be computed for each of the homogeneous subplots. Two applications to forest ecological field data demonstrate that the meth od, addressed to ecologists, can avoid misinterpretations of the spatial st ructure of heterogeneous vegetation stands.