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

加强美国基础设施（SAI）是美国国家科学基金会的一个项目，旨在促进以人为本的基础研究和潜在的变革性研究，以加强美国的基础设施。有效的基础设施为社会经济活力和广泛的生活质量改善提供了坚实的基础。强大、可靠和有效的基础设施刺激私营部门的创新，发展经济，创造就业机会，使公共部门提供的服务更有效率，加强社区，促进机会平等，保护自然环境，加强国家安全，并推动美国的领导地位。为了实现这些目标，需要来自科学和工程学科的专业知识。SAI侧重于人类推理和决策、治理以及社会和文化过程的知识如何使有效基础设施的建设和维护成为可能，从而改善生活和社会，并以技术和工程的进步为基础。该项目考察了偏远山区流域的管理和恢复。管理工作可以减少这些地区发生严重野火的风险。然而，在当地居民和利益相关者中，可能对导致管理工作减少火灾风险的生态过程存在误解。正如在风险感知研究中更普遍看到的那样，由此产生的不确定性可能导致优柔寡断和无所作为。在这项研究中，研究人员考察了评估风险的不确定性如何导致人们优先考虑不同的管理机会。通过实验方法，本研究向参与者展示了不同程度的恢复工作预期结果的不确定性，以确定这种变化如何影响向管理部门分配资源的决策。该项目通过确定利益相关者在做出恢复工作决策时所需的信息，有助于实现森林管理目标。该项目还为一名研究生和一名博士后提供培训机会。本研究解决了不确定结果对偏远山区流域恢复工作的感知效益的影响。利用认知心理学的方法和理论，研究人员通过实验向参与者提出不同的场景，以确定不同的不确定性如何导致个人评估不同管理方案的好处。这项工作着重于三种不同类型的不确定性，即直接的，间接的和感知的不确定性。直接不确定性假设事件的概率是完全已知的，而间接不确定性则产生于各事件的概率只是不完全已知的情况。感知不确定性是指对不确定性的主观感受，它通常会影响决策。这个项目理清了不同类型的不确定性对风险评估和随后的决策的各自影响。另一个目标是评估可视化技术在多大程度上可以重塑流域恢复不确定性的概念。本研究验证了现代不确定性可视化技术可以通过直观地传达相关生态过程的不确定性和关键方面来降低流域恢复不确定性的复杂性的假设。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

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.