До методики актуалізації основних таксаційних показників деревостанів твердолистяних деревних видів України

Abstract

Continuous forest inventory, as one of the methods of forest management of the country, in contrast to the basic inventory, has a number of advantages, which primarily provide the opportunity to obtain the most complete and reliable information about the current state of the forest, as it provides annual updates of main stands parameters of forest found on Ukraine. Hardwood tree species (oak, ash, beech, hornbeam, etc.) occupy a special place among all that grow in Ukraine and occupy almost 44 % of the forest area covered with forest vegetation. According to the latest state forest inventory as of 01.01.2011, hardwood tree species are dominated by oak stands - 62.6 % of the area of all hardwood tree species, forest beech - 20.2 %, hornbeam - 3.2 % and ash ordinary, forming mainly mixed stands with oak. A systematic approach to the effective solution of the problem of continuous forest inventory requires the development of objective methods and mathematical models for updating the main stands parameters of forests. In Ukraine, for actualization main stands parameters, two methods have been developed to forecast their growth. The first is based on modeling the percentage of current increment by average height and wood stock, the second - on the developed dynamic site index curves and yield tables for modal stands. The aim of the work is to improve the methodological approaches to modeling the growth prognosis of the main stands parameters by the second method. To achieve these goals used the method of nonlinear regression using IBM SPSS Statistics. As a result of the conducted researches it was offered to model a new unified ratio of the stands parameter a year ahead to the same stands parameter now multiplied by the age of the stand to model the growth prognosis for all stands parameters. This made it possible during the simulation to describe the changes in growth by the main stands parameters with almost absolute accuracy (the coefficient of determination of the obtained models is 1.0). The equation obtained for growth prognosis has the same form for stands of all tree species, of different origin, composition and site index classes.