V.S. Chernyshenko1, A.A. Davlekanova2, T.Yu. Moldovsky3

1–3 Financial University under the Government of the Russian Federation (Moscow, Russia)
1 vschernyshenko@fa.ru, 2 azzalliiya@gmail.com, 3 moldovskiitimur@gmail.com

Problem Statement. Forest fires in Russia, which threaten global ecosystems and climate balance, require in-depth analysis to develop effective management strategies. The increase in their frequency and intensity due to climate change challenges the sustainability of the world's largest boreal forests, which are critical to the carbon cycle.

Objective. The study aims to assess forest survival under fire conditions, analyze temporal characteristics of fire occurrence and risk, and integrate historical and spatial data to predict and prevent ecological threats.

Results. The application of statistical methods (including the Kaplan–Meier method) and artificial intelligence technologies allowed the development of integrated models that take into account regional characteristics. This provides fire forecasting and assessment of the effectiveness of measures for their localization.

Practical significance. The results of the study contribute to the optimization of forest resources management, minimization of ecological damage and preservation of climatic stability. Implementation of the models will help to reduce economic losses and improve preventive strategies.

Chernyshenko V.S., Davlekanova A.A., Moldovsky T.Y. Temporal analysis of wildfire risks to carbon sequestration in russian forests. Dynamics of complex systems. 2025. V. 19. № 5 P. 104−109. DOI: 10.18127/j19997493-202505-12 (in Russian).

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