
%0 Journal Article
%A Walker, J 
%A Noy-Meir, I 
%A Anderson, DJ 
%A Moore, RM 
%T Multiple Pattern Analysis of a Woodland in South Central Queensland. I. The Original Trees and Shrubs
%J Australian Journal of Botany
%D 1972/04/01
%V 20
%N 1
%P 105-118
%K 
%R https://doi.org/10.1071/BT9720105
%U https://www.publish.csiro.au/paper/BT9720105 
%X Multivariate analyses of vegetation data are normally restricted to a single scale of sampling, but since the pattern of species populations may vary over a range of scales, restriction to a single scale can result in a loss of potentially useful information. It is possible to examine spatial variation for a single species or pairs of species by block size variance (or covariance) analysis, but this is a somewhat cumbersome procedure when more than a few species are involved. A method which combines block size variance analysis with a multivariate (principal components) analysis is described and applied to a woodland community in south central Queensland. Contiguous site data, recorded as density scores for all tree and shrub species along a transect 512 m by 20 m, were grouped into successively larger blocks. Variance covariance matrices at each block size were calculated and added to form a combined covariance matrix. This was subjected to a principal components analysis to obtain species and sites coordinates. Each characteristic root was subsequently partitioned into contributions from the various block sizes, and the partitioned roots plotted against block size as in conventional pattern analysis. The first two components represented macro-variation in the vegetation of the transect (at scales of 120-250 m) and separated three macrocommunities which were associated with soil types. Two subsequent components expressed compositional differences at smaller scales (30-60 m) within these macrocommunities. 
