(1-2) , Nicholas C Coops (2) , Wojciech Ochal (1) The most widely accepted method of evaluating site productivity is site index. In spite of some important restrictions it is still a useful concept in both forest research and management. One of the most important challenges when using site index is an age trend manifested by a negative correlation between site index and stand age. Age trend may result from the inappropriateness of site index models. In this paper we develop a new approach for assessing age bias in site index models. Field data collected from 311 sample plots established in Norway spruce stands in the Polish region of the Carpathians formed the basis of this study. In the proposed approach the appropriateness of site index models is assessed by analyzing the existence of age trends in residuals of geocentric site index prediction models. Using the developed approach we demonstrated that when significant correlations exist between residuals of site index prediction models and stand age, it likely indicates the existence of an age trend and thus the inappropriateness of site index model. To remedy this situation, we demonstrated that the observed age trend can be quantified and utilized in new, non-biased, site index models.
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.
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.
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