Introduction

In this chapter, we will present and discuss methods designed to examine the spatial pattern of groups of species or of whole plant communities. While it is true that plant communities are made up of individual species, we do not expect to be able to capture the essential features of the spatial structure of the whole community by compiling information on the spatial patterns of single species. Similarly, while we tend to think of species interactions as being pairwise, we know that the relationship between two species, A and B, can be modified by the presence and absence of other species (Dale et al. 1991). We cannot, therefore, in studies of plant communities, restrict our examination of species interactions only to pairs. In stead, we must find ways to look at the spatial structure and pattern of vegetation more holistically, by looking at many species simultaneously.

In Chapter 3, we described how the spatial pattern of a single species can be studied using methods that examine the effects of distance or block size on a calculated variance, with low variance indicating similarity and high variance indicating dissimilarity. In analyzing the spatial pattern of a single species using the data from a string of contiguous quadrats, the information for each quadrat is a single value, either some measure of the species' density, or simply 0 for absence and 1 for presence. A technique like two-term local quadrat variance (TTLQV) combines the quadrats into blocks of a range of sizes to determine which block size maximizes the difference between adjacent blocks of quadrats.