HIGHLY INHERITABLE VARIABLE COMPONENTS IN THE CLONAL PLANTATION OF SCOTS PINE

The variability of the data on elemental composition of needles from the clonal population of Scots pine Pinus sylvestris L., established on the long­term field experiment, was studied by principal components extraction from the normalized data matrix, and broad­sense heritability Н2, i.e. the contribution of clones to the total data variance was calculated both for the original variables and principal components. To find the linear combinations of variables with the highest heritability the discriminant analysis was performed. The results suggest the importance of multivariate statistics for forest genetics and selection in targeting search for genetic marker traits in the populations of woody plants, in assessing genetic differentiation among populations, identification of the best genotypes via their phenotypes, etc.