Krasnoyarsk, Krasnodar, Russian Federation
Krasnoyarsk, Krasnoyarsk, Russian Federation
Krasnoyarsk, Krasnoyarsk, Russian Federation
Krasnoyarsk, Krasnoyarsk, Russian Federation
Krasnoyarsk, Krasnoyarsk, Russian Federation
The study of the structure was based on a series of distribution by the steps of the thickness. Measurements were carried out in forest shelter belts of the southern part of Central Siberia. Plots were laid on the territory of the Republic of Khakassia (Ust- Abakan, Bay, Shirinsky, Shushensky districts), Krasnoyarsk territory (Minusinsk district) and the Republic of Tuva (Kyzylskiy district). Approximation of distribution rows by diameter has been implemented by two functions: normal distribution and Weibull distribution. With respect to protective forest belts for most forest stands, structure by diameter is more adequately approximated by normal distribution, indicating the symmetry rows. But at this, function of Weibull is characterized by high correlation of its ratios with parameters of plantations, in particular with average diameter and normalized variability. Based on the study of the structure of the plantings in diameter, the optimal agro-technical indicators for the cultivation of plantations presented a variety of wood species, were revealed. It is recommended to divide rows into two groups, before forecasting the series. The first category reflects the influence of the internal (growth) processes: growth, mortality, movement of trees on the steps. These rows can be predicted taking into account the average diameter of tree stand and theoretical density (square of nutrition of individual tree). The second group of rows was formed under the influence of external factors (supplement, renewal, felling, and forest fires).These rows are forecasted using the average diameter and standard deviation of trees. For the prediction of the structure of the stands of Siberian larch, silver birch, Siberian elm and black poplar, model based on the Weibull function, were obtained.
forest belts, structure on diameter, agronomic indicators, forecasting.
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