The timber complex of the Russian Federation occupies an important place in the country’s economy.
Russian forests are one of the most valuable renewable natural resources. They constitute more
than a quarter of world reserves of wood biomass and perform significant environmental and
protective functions. The existing forest resources in Russian both provide current and future
domestic demand for timber and processed products, and significantly expand exports of forest
products. But at the same time long-term extensive forest exploitation aimed at withdrawal of
stocks of softwood carried out without due attention to the issue of the replacement of coniferous
species with soft-wooded broadleaved species, has led to the fact that over the past ninety years,
the share of coniferous forests decreased from 90 to 50 %. The solution to the commodity issue
requires increased attention to the issues of forest restoration. Given the fact that the real result of
all activities on forest restoration expressed both in quantitative and qualitative composition of the
forest cover, can be achieved only after several decades, a comprehensive solution to the problem
seems difficult to achieve without creating a scientifically proven system of decision-making support
which is expected to be implemented with the use of a system of agent-based models. The article
describes general principles of agent-based models, including the description of the algorithm
of agent’s choice of behavior pattern. We developed a context diagram and a general functional
scheme of a forest restoration model. We identify the main agents acting in the model; describe
their main characteristics, including their goals, motives and behavior scenarios, the interaction of
agents with each other and the external environment. Further model development implies detailed
elaboration and specification of agents’ characteristics, conditions of scenario choice, assessment of
mutual influence of this choice on the environment and agents’ characteristics
Keywords
timber complex, agent-based modeling, forest restoration, decision-making support system