EAGER: SAI: Facilitating Restoration of Natural Infrastructure Using Uncertainty Communication

Strengthening American Infrastructure (SAI) is an NSF Program seeking to stimulate human-centered fundamental and potentially transformative research that strengthens America’s infrastructure. Effective infrastructure provides a strong foundation for socioeconomic vitality and broad quality of life improvement. Strong, reliable, and effective infrastructure spurs private-sector innovation, grows the economy, creates jobs, makes public-sector service provision more efficient, strengthens communities, promotes equal opportunity, protects the natural environment, enhances national security, and fuels American leadership.

To achieve these goals requires expertise from across the science and engineering disciplines. SAI focuses on how knowledge of human reasoning and decision making, governance, and social and cultural processes enables the building and maintenance of effective infrastructure that improves lives and society and builds on advances in technology and engineering.

This project examines the management and restoration of watersheds in remote, mountainous regions. Management efforts can reduce the risk of severe wildfires in these regions. Among local residents and stakeholders, however, there may be misunderstandings about the ecological processes that lead management efforts to reduce the risks of fires.

As seen more generally in studies of risk perception, the resulting uncertainties can result in indecision and inaction. In this study, the researchers examine how uncertainties in evaluating risks lead people to prioritize different management opportunities. Using experimental methods, the study presents participants with varying degrees of uncertainty about anticipated outcomes of restoration efforts to determine how this variation affects decisions to allocate resources toward management.

The project contributes to goals of forest management by identifying the information that stakeholders need to make decisions about restoration efforts. The project also provides training opportunities for a graduate student and a postdoctoral scholar.

This study addresses the effects of uncertain outcomes on the perceived benefits of restoration efforts in remote, mountainous watersheds. Drawing on methods and theory from cognitive psychology, the researchers experimentally pose scenarios to participants to determine how varying uncertainty leads individuals to evaluate the benefits of different management options.

This work focuses on three distinct types of uncertainty, namely direct, indirect, and perceived uncertainty. Direct uncertainty assumes that the probabilities of events are known completely whereas indirect uncertainty arises when the respective probabilities are known only incompletely. Perceived uncertainty refers to subjective feelings of uncertainty, which are commonly influential in decision-making.

This project disentangles the respective effects of the different types of uncertainty on assessments of risk and subsequent decisions. An additional objective is to assess the extent to which visualization techniques can reshape conceptualizations of watershed-restoration uncertainties. This study tests the hypothesis that modern uncertainty-visualization techniques can reduce the complexity of watershed restoration uncertainties by intuitively communicating the uncertainties and key aspects of relevant ecological processes.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.