Опыт оценки состояния и прогнозирования социо-эколого-экономической системы: к вопросу устойчивого развития региона

Abstract

A review of various cognitive models for the region developed by the authors is proposed. To assess the opportunities for sustainable development of the region — the White Sea and the watershed, a set of cognitive models that reflect the dynamics of economic characteristics, the state and change of the environment, climate, agriculture and forestry and the social sphere are developed. Four models of the ecological-socio-economic system of the region are presented, which are used to determine different targets aimed at assessing the possibilities of improving the of living standard of the population, rational use and protection of the environment, the development of certain sectors of the economy and social sphere of the region which important for sustainable development of the region. In the first cognitive model for the region, the main objective function was considered to ensure the best possible development of all subregions (constituent entities of the Russian Federation) included in the watershed. The ratio of the magnitude of investments in the development of subregions and the demographic characteristics of the population to achieve comfortable living conditions was estimated. The second model was developed in order to study the possibilities of improving the living standards of the population using fisheries — a traditional occupation of the local Pomor’s population. The third model solved the multi-criteria problems of determining such a regime of control actions that would ensure the achievement of the maximum living standard of the population under different scenarios of the state of the economy and climate change. The fourth model took into account previous developments, is built on a hierarchical principle and can be used for various management purposes. The model is intended for prognostic assessments at a qualitative level of ongoing changes in a complex socio-ecological-economic system under various scenarios of economy, environmental management and climate change. The results can serve as the basis for constructing a system of quantitative models necessary for the development of management decision support systems.