CNH-L: Visualizing Forest Futures Under Climate Uncertainty: Integrating Indigenous Knowledge into Decision-Support Tools for Collaborative Decision Making

这个跨学科的研究项目将研究人类的价值观和实践如何影响人们对自然系统的偏好，以及如何影响有关森林资源和可持续性的决策中的权衡取舍。该项目将集中于两个总体主题：自然-人类系统中反馈的重要性以及仅由知识系统无法充分捕获的价值体系和习惯做法的重要性。它将提供关于森林生态系统结构和功能的变化如何导致人类与森林物种和服务之间的新关系以及森林管理做法如何影响生态系统的新见解和信息。该项目还将促进对价值观和实践（包括土著人民的传统知识）与个人和社区决策之间复杂的相互关系的理解。此外，该项目将增进对个人和社区持有的文化、精神、伦理和审美价值以及从事传统知识系统未充分掌握的森林习俗的程度的了解。由于该项目的参与者包括梅诺米尼民族学院，该项目将为美国原住民学生提供在基础研究和创新技术使用方面的教育和培训机会，包括虚拟现实软件和设备。将为研究生和博士后学者提供跨学科科学行为方面的其他教育和培训机会。该项目将促进该地区教育工作者、科学家和管理人员之间的合作，并将为目前以土著人民和部落知识为重点的环境评估活动提供信息。该项目还将提供明确的途径，将价值观和与森林的关系纳入最先进的优化程序，从而有助于加强部落社区适应环境变化的决策，并将帮助森林管理者和社区成员在决策时共同评估权衡。来自土著文化的传统知识在环境评估中被认为是重要的，但在景观一级的规划中没有得到充分的利用。由部落社区管理的森林正受到日益严重的昆虫破坏的威胁，这已经是北美地区空间范围最广的森林干扰，每年影响约2 000万公顷森林，估计损失15亿美元。森林的重大变化可能对许多部落社区所依赖的森林工业产生不利影响，并可能改变部落特性。研究人员将使用关于未来森林条件的最先进的可视化和虚拟现实体验，以获取关于未来森林条件情景的更广泛的人类价值。这些结果将用于模拟森林管理活动中的偏好，并确定有关森林管理的经济和其他基于价值的决策之间的权衡和协同作用。调查人员将采用人类学、伦理学、基于过程和沉浸式的手段来探索影响人们和社区在面临相当大的不确定性时如何做出决定和评估不同目标之间的权衡的复杂因素。研究人员将测试一系列假设，包括沉浸式虚拟现实可以增强对环境变化的情感和认知感知的命题，以及当前的管理活动可以通过将价值结构整合到强大的决策分析中来改进。价值观和实践将被纳入共识心理模型，这将通过沉浸式虚拟现实和生态系统建模提供信息，研究人员将增强决策支持算法，以评估结果的权衡。沉浸式虚拟现实体验将包括交互式2-D和3-D景观地图，360度替代森林结构的描绘，以及穿越时间的交互式地图。决策分析方法将促进对一系列广泛的可持续性指标的权衡分析，并将有助于在不确定的未来条件下测试替代战略的表现。研究人员将描述反映文化、生态和经济福祉的竞争价值之间的权衡和协同作用，并协助确定哪些选择导致可持续的解决方案。本项目由美国国家科学基金会自然与人类系统耦合动力学（CNH）项目资助。

This interdisciplinary research project will examine how human values and practices impact preferences about natural systems and influence the trade-offs made in decision making about forest resources and sustainability. The project will focus on two overarching themes: the importance of feedbacks in natural-human systems and the importance of value systems and customary practices that are not adequately captured by knowledge systems alone. It will provide new insights and information regarding how changes in forest ecosystem structure and function result in new relationships between humans and forest species and services as well as how forest-management practices influence ecosystems. The project also will advance understanding of the complex reciprocal relationships among values and practices, including traditional knowledge of indigenous people, and decision making by individuals and communities. Furthermore, the project will enhance understanding of the degree to which individuals and communities hold cultural, spiritual, ethical, and aesthetic values and engage in customary forests practices that are not adequately captured by conventional knowledge systems. Because the project's participants include the College of the Menominee Nation, the project will provide opportunities for Native American students to have education and training opportunities with respect to both basic research and to the use of innovative technologies, including virtual reality software and devices. Other education and training opportunities in the conduct of interdisciplinary science will be provided for graduate students and post-doctoral scholars. The project will promote collaborations among educators, scientists, and managers in the region and will inform ongoing environmental assessment activities focused on indigenous peoples and tribal knowledge. The project also will contribute to enhanced decision making for environmental change adaptation in tribal communities by providing clear routes by which values and relationships with forests can be embedded within state-of-the-art optimization procedures, and it will assist forest managers and community members in working together to evaluate trade-offs when making decisions.Traditional knowledge from indigenous cultures is recognized as important in environmental assessments but has not been adequately captured in landscape-level planning. Forests managed by tribal communities are under threat from increasing insect damage, which is already the most spatially extensive forest disturbance in North America, affecting approximately 20 million hectares of forest per year with an estimated cost of $1.5 billion. Significant changes to forests could adversely impact the forest industries upon which many tribal communities depend and could alter tribal identity. The investigators will use state-of-the-art visualization and virtual reality experiences about future forest conditions to access a broader range of human values about scenarios of future forest conditions. These outcomes will be used to model preferences in forest-management activities and determine trade-offs and synergies among economic and other value-based decisions about forest management. The investigators will employ anthropological, ethical, process-based, and immersive means to explore the complex factors that influence how people and communities make decisions and evaluate trade-offs among diverse objectives when faced with considerable uncertainty. The investigators will test a set of hypotheses, include the propositions that immersive virtual reality can enhance emotive and cognitive perceptions of environmental changes and that current management activities can be refined through the incorporation of value structures into a robust decision making analysis. Values and practices will be incorporated into consensus mental models, which will inform information available via immersive virtual reality and ecosystem modeling, and the investigators will enhance a decision support algorithm to assess trade-offs in outcomes. The immersive virtual reality experiences will include interactive 2-D and 3-D landscape maps, 360-degree depictions of alternative forest structures, and interactive maps through time. The decision-analytics approach will facilitate analysis of trade-offs across a broad set of sustainability metrics and will help test the performance of alternative strategies under uncertain future conditions. The investigators will characterize and tradeoffs and synergies among competing values that reflect cultural, ecological, and economic well-being and assist in determination of what choices lead to sustainable solutions. This project is supported by the NSF Dynamics of Coupled Natural and Human Systems (CNH) Program.