Modeling is the language of scientific discovery. Whether modeling the social interactions of individuals within a community in anthropology, the trade-offs of foraging behaviors in ecology, or describing the influence of warming ocean temperatures on circulation patterns in oceanography, the ability to represent empirical or theoretical understanding through modeling provides scientists with a semi-standardized language to explain how we think the world works. In fact, modeling is such a basic part of human reasoning and communication that the formal practice of scientific modeling has been recently extended to include non-scientists, especially as a way to understand complex and poorly understood socio-environmental dynamics and to improve research and decision-making.

Although the field of “participatory modeling” (PM) has grown in recent years, there are still considerable questions about how different software tools common to PM can be used to facilitate communication and learning among diverse groups, which approaches are more or less suitable (given the nature of a community or environmental issue), and whether these approaches lead to action-oriented outcomes.