Establishing the intensity of interventions in young beech (Fagus sylvatica L.) stands based on a spline regression mathematical model
DOI:
https://doi.org/10.15835/nbha52414021Keywords:
average crown diameter, cubic spline regression, Fagus sylvatica L., forest management practices, sustainable forest managementAbstract
The purpose of this work is to establish the optimal intensity of interventions in young beech stands. The study was carried out in the north-western part of Romania, in Zalău Forest District, Răstolţ Production Unit. Statistical-mathematical inventories were carried out on circular sample plots of 300 m2, adopting a coverage probability of p = 90% and a tolerance of t = 10%. The number of sample plots was established according to the area of the stand S(ha), volume variation coefficient sv(%), p(%) and t(%). The optimal intensity of interventions is determined by using the average diameter of crowns on each stand. The average diameter of crown was determined for the stands under study based on a spline regression mathematical model which represents the main objective of the current study. The stands, wherein no forest interventions have been applied, have a relatively high stocking and a relatively small spacing. Consequently, the intensity of selective combined thinning must be weak to moderate, and the periodicity shorter of 4-5 years. Another objective of the present paper is the determination of the allometric relationships between the diameter of the crowns and the heights of trees, in three young beech stands with or without any forest interventions, specific to the stage of development. From the analysis of experimental data, it turned out that the most suitable law of dependence is the linear regression, with a positive slope, representing the allometric relationship between the diameter of the crowns and the height of trees.
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Copyright (c) 2024 Ghiţă C. CRAINIC, Mircea CURILĂ, Sorin CURILĂ, Cristian ONEŢ, Anamaria SUPURAN, Alexandru M. BICA, Eugenia ŞERBAN, Flavia M. CIOFLAN, Flavius IRIMIE

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