Ecological systems modeling
Tetiana Cherniavska; Andrii Onyshchenko, Volodymyr Kudin, Olena Lytvyn, Halyna Kashcheieva, Valerii Samsonkin, Iuliia Bulgakova, Oksana Yurchenko, Roza Mammadova, Turkan Hasanova, Matanat Aliyeva, Bohdan Cherniavskyi, Viktoriia Petrenko, Alla Karnaushenko, Kateryna Melnykova, Masuma Mammadova, Tetyana Baydyk, Zarifa Jabrayilova, Huseyn Gasimov, Turkan Alibeyli, Lesia Kononenko, Yuliia Hlavatska, Nataliia Sysolina, Iryna Sysolina, Viktor Nadtochii, Anatolii Nadtochyi, Dmytro Lomonosov, Robert Cieślak, Artur Zimny, Alla Rusnak, Iryna Nadtochii, Inna Naida, Mykola Skarzhynskyi
The collective monograph ECOLOGICAL SYSTEMS MODELING presents an interdisciplinary inquiry that integrates the methodology of ecological and socio-economic modeling with digital instruments for governing sustainable development and territorial recovery. The central concern is the balance between the economy and the natural environment through the lens of the Sustainable Development Goals (SDGs) and the Paris Agreement.
The concept of transition to a balanced sustainable development model
This chapter elaborates a methodology for reconciling economic and environmental constraints within the logic of the SDGs and the Paris Agreement, grounded in inter-industry eco-economic input–output models and the Method of Basis Matrices (MBM). The authors set out an approach to solving both forward and inverse problems to identify a preferred development pathway and to iteratively retune the model under alternative sustainability scenarios. The resulting trajectories are recommended for long-term planning and for improving policy at national and international levels.
Cost assessment of climate change impacts on a railway company
This section proposes a practice-oriented framework for accounting for and attributing climate-related costs (incidents, maintenance, passenger behavior) in the railway sector. Emphasis is placed on separating climate-attributable expenditures from ordinary costs, avoiding double counting, and building a structured repository of baseline and climate-linked data. The chapter underscores the need for further research on passenger behavioral responses to extreme weather.
Ecological state of modern soil cover in agrocenoses of the Greater Caucasus Sheki region
This chapter offers an in-depth analysis of climatic and soil-microbiological data (2023–2024) for agrocenoses in the Sheki district, including moisture, humus content, actinomycete abundance, and dominant micromycete taxa. The effects of reforestation are documented, as is the role of long-lived stand fractions in accumulating organic matter (21.5–32.7 kg·m⁻²). The study demonstrates the significance of microbiological indicators—such as colony-forming units (CFU) and microbial biomass C—for monitoring and rational use of gray forest soils.
Information technologies in scenario-based modeling of post-conflict territory remediation: from express sanitation to sustainable recovery
The author proposes a hybrid architectural model (ML + GIS + IoT) and optimization algorithms for scenario-driven remediation management across the I–S–R phases (Invasion–Stabilization–Recovery) in Ukrainian territories affected by military activity. Case studies from Kherson, Zaporizhzhia, and Kharkiv substantiate prioritized measures (hydro-ecological monitoring, radiation control, pollution mapping, and soil/water remediation). Validation matrices and heat maps are employed to select digital components, thereby accelerating the transition from rapid clean-up to sustainable recovery.
Sustainable development policy for post-conflict recovery in Ukraine: the role of environmental indicators in decision-making
By the collective of authors of the monographic study, on the basis of a survey of >16,000 residents of 42 de-occupied communities of southern Ukraine, five indicators (TPMA, DNES, IHWI, ANR, BPHP) are presented. The authors propose to use heat maps and a structural model of managerial decisions for the purposes of ranking “hot spots” and forming local strategies (monitoring, reclamation, waste management, education). A structural model of management of decisions has been formed and sources of financing are indicated (donors, national funds, PPP); directions of future research have been outlined, including a national index of environmental sustainability of post-conflict territories.
Development of models and methods for assessing green skills in the labor market ecologization environment
This chapter presents an intelligent approach to aligning supply and demand for “green” occupations using fuzzy multi-criteria methods and pattern recognition. Scenarios are provided for matching competencies to vacancy-specific requirements, and the method’s invariance is demonstrated across diverse segments of the green economy.
Shared use of transport as a component of the circular economy in relation to achieving sustainable development goals
The chapter examines the applicability of shared-mobility models (car-sharing) in rural communities as a tool of the circular economy and the SDGs. Using the Adzhamka territorial community as a case, it substantiates the viability of local car-sharing (−13.68 t CO₂ per year and savings of 27,000–43,000 UAH per user annually), conditional on sufficient digital readiness and a cooperative model. Scaling barriers (digital divide, limited engagement) are identified, directions for integrating “smart mobility” are outlined, and vectors for future research are proposed.
Organizational and structural modeling of the integration of marine robotics into multilevel environmental and ecological monitoring systems
Here the authors advance an organizational model for integrating marine robotics into multilevel eco- and hydromonitoring, grounded in systems thinking, cybernetics, and ecosystemology. Ten principles (goal-orientation, adaptability, crisis resilience, interoperability, etc.) are formalized mathematically; the model operates through three contours – physical, informational, and managerial. Simulation experiments highlight the decisive role of adaptability and resource efficiency in ensuring system sustainability.
Social entrepreneurship as a driver of green remediation and revitalization of affected territories: digital modeling and decision support systems
The team develops an integrated DSS architecture in which social entrepreneurship acts as a change agent; the TBL→ESG linkage ensures measurability of effects, while LegalTech codifies compliance and auditing of smart contracts. For the Kharkiv region, six scenarios are modeled using cluster dendrograms, PCP, and a “butterfly chart,” demonstrating feasible trajectories for employment, soil/water clean-up, and risk reduction under transparent pay-for-performance arrangements. A seamless pipeline—data → analytics → decision → contract → KPI-based payments → verified impact—is proposed for scalable project finance. A pilot for Kharkiv (H2-2026→2030) shows gains in employment and training, progress in soil/water remediation, and improved governability; the visualization tools support priority-setting by cluster.
How to cite paper:
Cherniavska, T., Onyshchenko, A., Kudin, V., Lytvyn, O., Kashcheieva, H., Samsonkin, V. et al.; Cherniavska, T. (Ed.) (2025). Ecological systems modeling. Tallinn: Scientific Route OÜ, 236. https://doi.org/10.21303/978-9908-9706-6-0