Toward sustainable forest management indicators? A data mining approach to evaluate the impact of silvicultural practices on stand structure

Indicators are increasingly required to support a fine-tuning between sustainable forestry and multiple environmental targets. A data mining strategy was implemented in this study to assess the overall impact of traditional and innovative silviculture on stand structure in a sample of beech forests with varying dominant age, management history and stand structure in Italy. Harvesting intensity and stand sensitivity to treatment were investigated using a principal component analysis (PCA) run on a set of dendrometric and stand-structure variables measured before and after practice implementation at the scale of forest compartment. The PCA decomposed the overall impact of silviculture on forest structure in two manipulative effects: (i) structural changes between control and treatments, and (ii) the net manipulative effect of innovative versus traditional treatment. Our approach informs the sustainable management of forests, outlining between-site differences in stand structure and identifying a diversity gradient shaped by silvicultural practices. Multivariate analysis of forest indicators following practice’s implementation is a promising tool to design innovative silviculture coherent with conservation of forests’ structural diversity.