Stand density changes due to aging and thinning interventions. At the same time, the social status of trees develops and varies due to different genetic conditions as well as access to nutrients and light. Trees growing in diverse conditions gain their social status in the stand, which, in the end, influences their development and biomass allocation. The objective of this research was to discover if stand density or tree social status has an impact on a tree’s aboveground biomass allocation. The study was carried out in five premature and five mature pine stands, growing in the same soil conditions. The selected sample stands had a different growing density, from low to high. In each sample stand, 10 trees were selected to represent a different social status, according to the Schädelin classification. There were 100 trees felled in total (50 in the premature stands and 50 in the mature stands), for which the dry biomass of the stem, living and dead branches, needles, and cones was determined. The results showed that stand density only had an impact on the branches’ biomass fraction but not the stem and foliage fractions, while social status had an impact on all the fractions. Dominant and codominant trees, as well as those with developed crowns, had a smaller share of the stem and higher share of branches in comparison with trees of a lower social status.

We present diameter distribution models for black alder (Alnus glutinosa (L.) Gaertn.) derived from diameter measurements made at breast height in 844 circular sample plots set in 163 managed stands located in south-eastern Poland. A total of 22,530 trees were measured. Stand age ranged from six to 89 years. The model formulation was based on the two-parameter Weibull function and a non-parametric percentile-based method. Weibull function parameters were recovered from the first raw and second central moments estimated using the stand quadratic mean diameter. The same stand characteristic was used to predict values of 12 percentiles in the percentile-based method. The model performance was assessed using the k-fold cross-validation method. The goodness-of-fit statistics include the Kolmogorov–Smirnov statistic, mean error, root mean squared error, and two variants of the error index introduced by Reynolds. The percentile model developed, accurately predicted diameter distributions in 88.4% of black alder stands, as compared to 81.9% for the Weibull model (Kolmogorov–Smirnov test). Alternative statistical metrics assessing goodness-of-fit to empirical distributions suggested that the non-parametric percentile model was superior to the parametric Weibull model, especially in stands older than 20 years. In younger stands, the two models were accurate only in 57% of the cases, and did not differ significantly with respect to goodness-of-fit measures.

The aim of this study was to evaluate top height (TH) estimates for Norway spruce stands calculated according to different computational methods, and to assess the effects of stand density and plot size on TH estimation accuracy. Field data were collected from twelve 1 ha research plots located in even-aged spruce stands. Conventional estimates were found to generally overstate TH. The accuracy of TH estimation was dependent on sample plot size. TH estimation error decreased rapidly with increasing sample plot area, but only up to a certain cut-off point. Errors in TH estimation were also related to local stand density, with low and very high density levels leading to decreased accuracy. The most reliable TH estimates were obtained using the U-estimator method, which is resistant to changes in sample plot size.