Diameter distributions in Pinus sylvestris L. stands: evaluating modelling approaches including a machine learning technique

Abstract The diameter distribution of trees in a stand provides the basis for determining stand’s ecological and economic value, its structure stability appropriate management practices. Scots pine ( Pinus sylvestris L.) is one most common important conifers Turkey, so well-planned schedule critical. Diameter models to accurately describe help improve strategies, but developing reliable requires deep understanding growth, output constraints forests. information derived by primary data on horizontal each class trees: basal area volume per unit area. These predictions are required estimate range products predicted yield from forest stand. Here, construct an accurate, model natural stands Türkmen Mountain region, we used Johnson’s S B represent empirical distributions using ground-based measurements 55 sample plots that included 1219 zones As alternative, nonparametric approach, which does not require any predefined function, artificial intelligence was constructed based support vector machine methodology. An error index calculated evaluate results. Overall, both probability density function with three-parameter recovery approach regression methodology provided estimates these stands.