Moskva, Russian Federation
UDK 630 Лесное хозяйство. Лесоводство
Scots pine is one of the main forest-forming species in the Kostroma region, therefore it is necessary to have tools that allow one to make informed decisions on managing the forest growing process, planning forest management, designing forest management activities and increasing the efficiency of forest stands performing environmental functions. The purpose of the study is to develop a dynamic model of growth and yield of pine stands in the Unzhensky Lowland (Kostroma region) based on repeated observations on permanent trial plots. The data for modeling the growth and yield of pine stands were materials from repeated censuses on 21 permanent trial plots of the Chernolukhovsky experimental forestry enterprise and 3 permanent trial plots of the Manturovo section of the Kologrivsky Forest Nature Reserve. To model growth by average height and average diameter, 15 dynamic equations based on 9 basic functions were analyzed, and to model thinning of forest stands, 14 dynamic equations were analyzed. The resulting regression equations for predicting the dynamics of average heights and diameters, thinning together form a model of growth and yield of pine forest stands, which belongs to the category of empirical models for predicting stand characteristics at the level of an individual forest stand, and its advantages are the invariance of the relative base age and the ability to give forecasts over a wide range of initial parameter values. The developed model can serve as an alternative to traditional tables of course of growth when designing and justifying forestry activities, when forests inventory using the updating method, as well as for making management decisions when managing pine forests. In combination with additional equations, it can be part of more complex models that allow predicting the structure of forest stands, commercial and carbon sequestration potential, and the impact of forestry activities.
Scots pine, Pinus sylvestris L., forest stand growth model, repeated observations, permanent trial plot
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