Patterns in species associations in plant communities: the importance of scale

. Present discussions on competitive interactions and the occurrence of predictable patterns in species composition – including assembly rules – are likely to benefit from appropriate analyses of the spatial structure in plant communities. We suggest such an analysis when we specifically want to detect scale regions where fine‐scale local processes may affect the spatial pattern of species composition. We combine indirect ordination in the form of Detrended Correspondence Analysis (DCA) and geostatistics in the form of variography. The species abundance data in the sampled quadrats are summarized as positions on the axes in the ordination. Each axis is used as a regionalized variable in the variography to obtain the spatial dependence of the quadrats. The spatial pattern found will suggest the relevant scale region in which to perform an analysis of species associations. A significant spatial dependence (the ‘range’ in geostatistical jargon) will define the size of a sampling plot that will minimize both the problem of being too small and thus having the risk of oversampling of e.g. clonal individuals and of being too large which will risk including individuals that do not interact. We also suggest that plots are spaced at least a ‘range’ apart to insure spatial and statistical independence. Comparisons of species compositions in such plots will reveal any positive or negative associations between species on a scale where these should reflect species‐species interactions. To illustrate the method it is applied to three different data sets from two different plant communities.