Modeling, learning, and planning together: An application of participatory agent-based modeling to environmental planning

INTRODUCTION Planning for complex human-environmental systems requires that decision makers are able to make sense of system complexity. A system is complex when its parts (e.g., residents, developers, farmers, biophysical features) interact selectively with each other through direct actions and through reactive feedbacks, creating dynamic and spatial interdependence (Holland 1995, Miller and Page 2007). Because present interactions change the way in which interactions may occur in the future, uncertainty is inherent in complex systems (Axelrod and Cohen 1999). Planning can effectively prepare us to adapt to a range of plausible futures by understanding and building on this complexity, allowing it to inform a community's intentions about what combination of policy goals to adopt and use. The predominant planning approach to environmental problems involves forming diverse stakeholder committees, focusing on fair representation of different viewpoints--a critical aspect of any democratic process. Less attention, however, is placed on understanding the various layers of complexity they face. The first layer is the complexity of the system they are planning for. Individual use of a shared resource interacts with use by others, making it hard to trace causal impacts through the web of interactions, especially when the shared resource also is complex and responds in uncertain ways to human-induced stresses (e.g., groundwater). Cumulative effects can appear mysterious. The second layer is the social complexity generated by members' own diversity of backgrounds, beliefs, interests, perceptions, and data, which informs the way that they interact with each other for collective decision making. Self-interest and partial understanding of the system they are planning for often leads stakeholders to focus exclusively on individual impacts, exaggerating their salience, and overlooking critical interactions. Policy makers may focus prevention or mitigation efforts on a single type of user or use (e.g., farmers) that does not remedy systemic depletion pressure from other sources (e.g., residential subdivision growth). Anticipating these difficulties, stakeholders may use a variety of visualization tools to estimate and display potential future effects of different plans. Popular and easy-to-use tools often mislead stakeholders when applied to complex problems. Less familiar and more demanding simulation tools may better estimate future interaction effects of different plan-related policies and expectations, but they require hiring expert modelers to collect high-quality data to inform the models, build the models, conduct the simulations, and interpret their results. Outside expertise relies on stakeholders' trust, but because stakeholders do not understand the simulation of future effects in their own terms, their confidence flows from professional reputation, not understanding. Off-loading plan simulation onto outside experts does not allow for stakeholder examination of policy goals and alternative plans in light of their implications for the future. Planning theorists and analysts have made the case for collaborative plan making when confronting complex problems, the argument being that collaboratives can better learn to conceive, assess, and choose among options for the future (Innes and Booher 2010). Most studies focus on the design of plan-making institutions and stakeholder involvement to reconcile the complexity of social and political goals (Innes et al. 2007, Susskind and Cruickshank 1987). Others study the methods and tools used to improve the quality of collaboration (Forester 1999, 2010). In this article, we add to this area of inquiry by studying how agent-based modeling can contribute as a participatory modeling tool for collaborative planning, examining how it affects the learning processes underpinning the ability to explore complex environmental problems. Participatory Modeling and Collaborative Planning Participatory model building involves not only expert modelers but also stakeholders and public officials in conceptualizing and building models, interpreting their results, and using them to support decision making. …