CNH2-L: Developing adaptive capacity in wildfire-prone regions

近几十年来，野火造成的社会和环境代价急剧增加，需要更多信息来了解社区如何在这种日益增长的危险面前进行自我重组。该项目探索火灾多发地区的行动者建立适应性社会网络的潜力，以提高他们应对日益扩大和激烈的野火的能力。这首先是通过探索和总结美国西部四个研究领域的关键适应经验教训，并通过利益相关者理事会进行审查来实现的。接下来，来自这些研究领域的最有前途的社交网络结构将在一个有充分记录的重点区域进行测试，在那里，许多替代未来将在差异很大的未来气候情景下进行模拟。然后，与领先的国家和州野火学习网络一起召开利益相关者理事会，在年轻的下一代科学领袖的参与下提炼、考虑和传播研究结果。最后，整个方法被捕获在一个首创的计算机模型中，扩展和共享工具，以便其他人可以使用它们来扩大其他地方的适应努力。将传播经验和成果，通过与学生、教育工作者、利益相关者、政策制定者和资源管理者的合作参与，在面对日益严重的野火时创造更具弹性的景观和社区。该项目探索社会网络拓扑结构如何塑造受野火影响地区的社区的自适应重组能力，以应对比人们以前经历的更严重的火灾。主要目标是确定可复制的网络构建块，以增强在各种容易发生火灾的环境中的适应能力。一旦这些网络结构被识别，它们就被用来验证一个创新的计算平台，该平台连接了自适应社会网络、生物物理和基于代理的模拟模型。然后，将建模系统应用于焦点区域景观及其野火参与者(例如，土地所有者、组织和政策制定者)的动态地图表示，以测试不同社会网络拓扑的限制，以响应不断加剧的野火制度。总而言之，这些努力使得(1)创建了一种可概括的理论，即在经历不断加剧的火灾制度的易发生野火的社会环境系统中，何时、何地、为什么以及如何通过社会网络重组产生适应性变化；2)综合经验和建模见解，提取个人和组织关系的表征，提高对野火的适应能力；以及3)探索和测试已确定的关系如何在预测的未来干扰制度下随时间演变，以改变适应能力并限制与野火有关的风险。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The social and environmental costs of wildfires have grown dramatically in recent decades, and more information is needed to understand how communities can reorganize themselves in the face of this growing hazard. This project explores the potential for adaptive social networks of actors in fire-prone regions to improve their ability to cope with increasingly large and intense wildfires. This is achieved first by exploring and summarizing key adaptation lessons from four western US study areas and vetting them via a stakeholder council. Next, the most promising social network structures from these study areas are tested in a well-documented focal area, where many alternative futures are simulated under widely varying future climate scenarios. A stakeholder council is then convened with leading national and state wildfire learning networks to distill, consider, and disseminate findings with the participation of young, next-generation science leaders. Finally, the entire approach is captured in a first-of-its-kind computer model, extending and sharing the tools so that others may use them to expand adaptation efforts elsewhere. Lessons and outcomes will be disseminated to create more resilient landscapes and communities in the face of increasing wildfires through collaborative engagement with students, educators, stakeholders, policymakers, and resource managers.This project explores how social network topology shapes the ability of communities in regions affected by wildfires to adaptively reorganize in response to fires that are more severe than people have previously experienced. The main goal is to identify replicable network building blocks that can enhance adaptive capacity in a variety of fire-prone landscapes. Once these network structures have been identified, they are used to validate an innovative computational platform linking adaptive social network, biophysical, and agent-based simulation models. The modeling system is then applied in dynamic, mapped representations of the focal area landscape and its wildfire actors (e.g., landowners, organizations, and policy makers) to test the limits of different social network topologies to respond to intensifying wildfire regimes. Together, these efforts enable (1) the creation of a generalizable theory of when, where, why, and how adaptive changes arise through social network reorganization in wildfire-prone social-environmental systems experiencing intensifying fire regimes; 2) the synthesis of empirical and modeling insights to distill representations of people's and organization's relationships that increase adaptive capacity with respect to wildfires; and 3) exploration and testing of how the identified relationships may evolve over time under projected future disturbance regimes to alter adaptive capacity and constrain risk in relation to wildfires.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.