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Nelder’s systematic design enables studies of tree plantation spacing in relatively small areas, which is of great interest for forest planning. However, dependence between observations can arise with this method, making it difficult to use classic statistics for evaluating an experiment. Therefore, our aims were to: evaluate the relationship between dendrometric variables (tree diameter, height and volume) and the available growing area; evaluate autocorrelation among the observations; and use multivariate analysis of the profiles of the clones for comparisons of the dendrometric variables. The data are from an experiment with four Nelder wheel plots of different  Eucalyptus  species clones of different ages, in the state of Tocantins, Brazil. Spearman’s rank correlation was applied to evaluate the relationship between the estimates of the studied variables and respective available growing area. Autocorrelation between the observations was evaluated with Moran’s I index. To analyse the profile behaviour of the clones, three questions were proposed: (1) Are there statistical differences between the estimations made for the different clones? (2) Are there differences between treatments applied in the experiment with the clones? (3) Is there interaction between clones and spacings? The main results show that multivariate profile analysis solved the autocorrelation problem in Nelder’s systematic design. Furthermore, we obtained answers as to differences between the growth variables diameter, volume and height among the clones at different spacings, whether there is a difference between the spacings for these variables, and whether there is an interaction between clones and spacings. The analysis method used for repeated measures is appropriate to evaluate trees in Nelder wheel trials.

Density effect on growth variables of eucalypt clones in a Nelder wheel experiment