Situational modeling of opportunities for achieving strategic goals by Russian agriculture: analysis at the national and regional levels

Ivan Yu. Ryabov, Elena V. Ponkina, Anton S. Strokov

Altai state university, Center for agrifood policy of the Russian Presidential academy of national economy and public administration (RANEPA)

Situational modelling makes it possible to analyze and predict the “behavior” of organizational systems under different conditions. One of the key tools in this area are models of the dynamics of socio-economic systems. Models describing the processes of Land Use Change (LUC) allow us to study both the dynamics of regional development under certain climatic and socio-economic scenario conditions and the prospects and possible consequences of achieving long-term strategic goals of agricultural development. We employed a recursive model of agricultural land use dynamics “GLOBIOM” for situational modelling of the achievement of carbon neutrality by Russian agriculture in the case of two scenarios: inertial socio-economic development under the SSP2 scenario without special taxes on greenhouse gas (GHG) emissions and with the introduction of a tax per unit of GHG emissions. The results of the situational modelling provide an informational basis for understanding the prospects of achieving carbon neutrality of the Russian agriculture under the considered interventions, which is relevant for the development of the national agricultural policy. In addition, modelling at the regional level allows us to reveal the possible consequences for regional agriculture, in particular changes in agricultural production, land use, and farmland distribution. Among the Russian regions, the study focused on the Greater Altai regions (Altai Krai, Altai Republic, and Tyva Republic), where Altai Krai represents a large agro-industrial region with the largest carbon footprint from agricultural production in the country, and Altai and Tyva are ethnic republics with less pronounced agricultural potential and a greater focus on livestock development. The modelling period is 2030-2050.

situational modeling, scenario analysis, agricultural development, GLOBIOM, carbon tax, land use

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