Modeling with citizen scientists: Using community-based modeling tools to develop citizen-science projects resulting in resource management outcomes

Submitted for symposium: Improving the Influence of Citizen Science on Environmental decision-making. Although model-based reasoning is often at the center of scientific investigation, the process of constructing, refining and... [ view full abstract ]

Submitted for symposium: Improving the Influence of Citizen Science on Environmental decision-making. Although model-based reasoning is often at the center of scientific investigation, the process of constructing, refining and empirically validating scientific models is not often made explicit to participants in many citizen science programs. The lack of attention that modeling receives in citizen science programs is likely attributable to resource constraints, given that scientific modeling often requires considerable training and the software tools that scientists use are not easily accessible to members of the general public. This limitation can also present difficulties in communicating ideas in the decision-making process. To address these issues, we present the development and use of a fuzzy-logic cognitive mapping software called Mental Modeler (http://www.mentalmodeler.org/), embedded within a citizen science web portal that allows scientists, environmental managers and citizen scientists to collaboratively develop semi-quantitative conceptual models of environmental problems that are then used as a basis to structure citizen science projects. We suggest that highlighting the role that model-based reasoning plays in scientific investigation and engaging citizens in iterative computer-based modeling and scenario activities: (1) allows citizen groups to collaboratively design their own community-based projects that are of local interest and concern; (2) fosters model-based reasoning in citizen science project participants and (3) serves as a novel measurement tool for citizen science researchers to understand conceptual change as participants engage in these projects. Using data collected from four community groups that worked with professional scientists and land managers to develop local projects in Virginia, we first outline architecture of the modeling software and web portal. We then describe participant interaction with the modeling tool and review the data and projects that were generated. Finally, we discuss the benefits and limitations of incorporating model-based reasoning and modeling tools into the development of resource management projects.