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

EAGER：SAI：利用不确定性通信促进自然基础设施的恢复

• 批准号: 2122174
• 负责人: Lace Padilla
• 金额: $ 30万
• 依托单位: University of California - Merced
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2122174&HistoricalAwards=false
• 关键词: EAGER; SAI; Facilitating; Restoration; Natural

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.

加强美国基础设施（SAI）是NSF的一项计划，旨在促进以人为本的基础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改善生活质量奠定了坚实的基础。强大、可靠和有效的基础设施刺激私营部门创新，促进经济增长，创造就业机会，提高公共部门服务提供的效率，加强社区建设，促进机会平等，保护自然环境，增强国家安全，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的基础设施得以建设和维护，从而改善生活和社会，并建立在技术和工程进步的基础上。该项目研究了偏远山区流域的管理和恢复。管理工作可以降低这些地区发生严重野火的风险。然而，当地居民和利益攸关方可能对导致管理工作减少火灾风险的生态过程存在误解。正如在风险认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犹豫不决和无所作为。在这项研究中，研究人员研究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。使用实验的方法，该研究向参与者提供了不同程度的不确定性，恢复工作的预期结果，以确定这种变化如何影响决策分配资源管理。该项目通过确定利益攸关方就恢复工作作出决定所需的信息，为森林管理目标作出贡献。该项目还为一名研究生和一名博士后学者提供了培训机会，这项研究探讨了不确定的结果对偏远山区流域恢复工作的预期效益的影响。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场景，以确定不同的不确定性如何导致个人评估不同管理选项的好处。这项工作的重点是三种不同类型的不确定性，即直接，间接和感知的不确定性。直接不确定性假设事件的概率是完全已知的，而间接不确定性则是在相应的概率仅是不完全已知时产生的。感知的不确定性是指主观的不确定性感觉，通常会影响决策。本项目将理清不同类型的不确定性对风险评估和随后决策的各自影响。另一个目标是评估可视化技术在多大程度上可以重塑概念化的流域恢复的不确定性。这项研究测试的假设，现代不确定性可视化技术可以直观地沟通的不确定性和相关的生态processes.This奖项的关键方面，可以减少流域恢复的不确定性的复杂性反映了NSF的法定使命，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。