Participatory Simulation Platforms for Data-Scarce Complex Social-Ecological Systems

Ciobanu & Saysel’s work on participatory modeling in the Ikel Watershed highlights the need for stakeholder-driven approaches in data-poor contexts. This research idea combines participatory simulation with recent advances in surrogate modeling (e.g., LTC neural networks from Farlessyost & Singh, 2024) and system dynamics (Turner et al., 2016). The platform would allow stakeholders to co-design and interact with models, while machine learning components fill data gaps and calibrate system behavior based on limited local knowledge and available data. This hybrid approach uniquely empowers communities to explore “what-if” scenarios, adaptively refine model structure, and build collective understanding of resilience strategies—addressing both technical and socio-political gaps in climate adaptation research.

References:

1. Resilience Dynamics in Coupled Natural-Industrial Systems: A Surrogate Modeling Approach for Assessing Climate Change Impacts on Industrial Ecosystems. William R. Farlessyost, Shweta Singh (2024). arXiv.org.
2. How Participatory and Computer Modeling Enhances Climate Resilience Policy Design in Data-Scarce Social-Ecological Systems: Lessons from the Ikel Watershed. Dr. Natalia Ciobanu, Prof. Ali Kerem, Saysel (None).
3. System dynamics modeling for agricultural and natural resource management issues: Review of some past cases and forecasting future roles. B. Turner, H. Menendez, R. Gates, L. Tedeschi, A. Atzori (2016).