The four variables of interest include the size of the resource system, the number of users, the amount of knowledge sharing among different resource user's mental models, and finally, the level of importance of the resource to each user. Of particular interest to us are four subsystem variables that scale the social and geographic dimensions of a decision making situation in different ways. In fact, sustainability science and environmental history have both shown through historical case studies that government intervention into the self-organizing capabilities of an otherwise resilient social-ecological system sometimes accelerates its deterioration ( Earle 1988).ġ.2 Ostrom ( 2009) highlighted ten subsystem variables explaining self-organizing behavior leading to a sustainable social-ecological system. Systems theorists have long held that complex systems exhibit the capacity to evolve internal control systems and essentially self-regulate ( Bennet and Chorley 1978). Based on extensive case studies, sustainability science finds that human resource users may sometimes self-organize as a control system to make sure that the social-ecological system of which they are a dependent part remains resilient in a way they prefer ( Ostrom 2009 Agrawal 2001). One of the interesting developments in sustainability science is the emergence of an alternate theory. The Three Domains of Sustainability: Sustainability Science, Sustainability Information Science, and Sustainability Managementġ.1 A widely accepted theory is that when people are left to their own devices they will simply consume the resources at their disposal and deteriorate their environment unless governments impose a control system to prevent an unavoidable tragedy of the commons.

Social Actors, Public Participation, Decision Making, Sustainability Management, Geodesign, Geographic Information Systems (GIS) We discuss the results of the experiment and conclude with prospects for research on the social and geographic dimensions of self-organizing behavior in social-ecological systems spanning wide regional areas.

The theory of self-organizing resource users does not specify how a group of social actors' preconceptions about a situation is interdependent with their social and geographic orientation to that situation. However, our expectations were not met by our findings, which we trace all the way back to our conceptual model and a theoretical gap in sustainability science. We expected that increasing the social and geographic distribution of agents and the diversity of their preconceptions would have a significant impact on agent consensus about which situations to change and which ones not to change. The three factors included 1) the social and geographic distribution of agents (local, regional, international levels), 2) abundance of agents (low, medium, high levels), and 3) diversity of preconceptions (blank slate, clone, social actor levels). We used a factorial research design to vary three interdependent factors each with three different levels. Geographically-distributed agents interacted through an online platform similar to that used in online field experiments with actual human subjects. As opposed to studying self-organizing behavior at the scale of a local 'commons', our interest was in how online technology supports the self-organizing behavior of agents distributed over a wide regional area, like a watershed or river basin. The goal of the simulation was for agents to reach consensus about which situations in their regional environment to change and which ones not to change as part of a geodesign process for improving water quality in the greater Puget Sound region.

Agents were modeled as socially intelligent actors who communicate using a system of symbols. This article reports on an agent-based simulation of public participation in decision making about sustainability management.

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