We use the Minimal Spanning Tree to characterize the aggregation level of
given sets of points. We test 3 distances based on the histogram of the MST
edges to discriminate between the distributions. We calibrate the method by
using artificial sets following Poisson, King or NFW distributions. The
distance using the mean, the dispersion and the skewness of the histogram of
MST edges provides the more efficient results. We apply this distance to a
subsample of the ENACS clusters and we show that the bright galaxies are
significantly more aggregated than the faint ones. The contamination provided
by uniformly distributed field galaxies is neglectible. On the other hand, we
show that the presence of clustered groups on the same cluster line of sight
masked the variation of the distance with the considered magnitude.Comment: 9 pages, 7 postscript figures, LateX A\{&}A, accepted in A\{&}
