Why Models?

Why are models essential in science, and why we are using them in citizen science?

Our desire to focus on models stems from what practitioners do in ecology, environmental and science education, and natural resource management. Ecologist work to solve problems and develop explanations driven by a question. To do so, a scientist will generate explanations or accounts of particular happenings in the natural world using evidence, and then seek further evidence that supports or refutes these explanations. Environmental educators endeavor to help citizens understand and solve problems in society related to environmental issues. These educators aim to provide learners with authentic contexts by which learners can engage with the messiness of natural data sets. To do so, they teach learners how to generate explanations for various observations using supporting evidence gathered by systematic investigation. New approaches in environmental resource management and decision-making require individuals to think across large spatial and temporal scales to reason about complex environmental phenomena in both social and ecological systems.

We define a model as a representation of scientific phenomena occurring in broad or narrow contexts that may or may not be observable. Such representations enable the testing of ideas, for example, through simulation or as a hypothesis or conception of how the world works. These representations can exist as mental models (i.e., the intricate ideas we hold in our heads to explain the world around us). They can also exist as visual, conceptual, or mathematical representations, or depictions of socially generated models. It is the explicit consideration of not only of the final model but also the means by which the model is formatively generated that is of value in developing our understanding of environmental systems.

Moving beyond representation and communication, models allow for simulation and the testing of scientific ideas. Scientific inquiry is about developing explanations about the world through collecting data, relying on using them as evidence, and using logic to develop evidence-based conclusions. Models can be used as tools for predicting and explaining, and models change and are revised as understanding improves.

There is evidence, however, that the public at large fails to understand the purpose of scientific models, or to appreciate the nature of models and modeling, in particular, as a tool for inquiry. We argue, however, that an ability to understand environmental issues across large spatial and temporal scales can result in the public having an incomplete and narrow image of how science, as it pertains to environmental problems, is done. In this project, we are not only providing modeling tools to help citizens communicate and test ideas on both local and regional scales, but we also want to know if these modeling tools make your stewardship easier. (Modified from Crawford and Jordan (In press))