Realizing the Potential of Community-Led, Science-Driven Participatory Complex Systems Modeling

Why It Matters

By embedding community voices directly into rigorous modeling, cities can craft resilient policies that reflect real‑world priorities, accelerating climate‑adaptation and sustainable planning outcomes.

Key Takeaways

• Participatory modeling bridges science and community perspectives effectively
• Stage three involves stakeholders co‑creating and testing scenarios
• Simplicity in models enhances accessibility and decision‑making trust
• New platform lets users prioritize concerns and visualize trade‑offs
• Funding and trust-building remain critical for mainstream adoption

Summary

The video features Dr. Moira Zellner’s presentation on community‑led, science‑driven participatory modeling for socio‑ecological challenges such as climate hazards and urban planning. She frames the approach as the third stage of reasoning about complex systems, where stakeholders move beyond merely acknowledging complexity to co‑creating models and exploring intervention trade‑offs.

Zellner outlines three reasoning stages: recognizing complexity, analyzing it with traditional tools, and finally engaging stakeholders in participatory modeling. She argues that without stakeholder involvement, models remain abstract and decision‑making stays disconnected from lived experience. The framework emphasizes simple yet realistic models, rapid scenario testing, and visualizations that surface diverse values and priorities.

A memorable quote from the talk is, “We have to go at the speed of trust,” underscoring the need for relationship‑building before technical work can succeed. Zellner demonstrates a prototype platform that lets users assign weighted concerns, collaborate on a shared map, and run flood‑risk simulations with green‑infrastructure interventions. The demo shows how different stakeholder groups—public officials, hydrologists, residents—prioritize investment, infiltration, or runoff differently, and how the tool visualizes those divergent outcomes.

The implications are clear: participatory modeling can democratize scientific insight, improve the durability of urban‑planning decisions, and foster collective learning. However, scaling the approach requires sustained funding, interdisciplinary facilitation skills, and institutional willingness to adopt simpler, more transparent models.

Original Description

Moira Zellner

Participatory modeling (PM) is particularly well-suited to address complex socio-environmental problems like climate hazards and their implications for sustainable resource management and landscape planning. Despite its potential to inform planning and policy, particularly in conflictive contexts, PM has yet to become a mainstream practice for decision-making. While most PM research and development has focused on modeling tools and engagement techniques, multiple other dimensions must be recognized and articulated for impactful planning support. I present a PM platform, Fora.ai, that supports the iterative steps in PM: problem definition and goal setting, preference elicitation, collaborative scenario-building, simulation, tradeoff deliberation, and solution-building. I demonstrate the platform's effectiveness when embedded in a stakeholder-led process that integrates diverse knowledge, data sources, and values in pursuit of impactful green infrastructure (GI) planning to address flooding. I show how the combination of specific facilitation practices and platform features leverages the power of data, computational modeling, and social complexity to contribute to collaborative learning, creative and convergent solution-building for urban sustainability and climate resilience.

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