Collaborative Research: RAPID: Forest productivity and expression in a low-emissions present: A RAPID response to the COVID-19 Emissions Reduction Event

合作研究：RAPID：低排放情况下的森林生产力和表现：对 COVID-19 减排事件的快速响应

• 批准号: 2135360
• 负责人: Nathan Swenson
• 金额: $ 9.19万
• 依托单位: University of Notre Dame
• 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: 2021-03-01 至 2023-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2135360&HistoricalAwards=false
• 关键词: Collaborative; Research; RAPID; Forest; productivity

State and federal policies have significantly limited human activities to keep the U.S. population safe during the COVID-19 pandemic. This has resulted in a significant decrease of atmospheric inputs from the reduction in automobile and air travel. The unprecedented and dramatic reduction in traffic in major metropolitan areas where emissions are consistently high is transforming the atmosphere, even at continental scales. The COVID-19 event presents a unique, ephemeral, and rare opportunity to study how forests would respond to dramatically cleaner air in the United States. This award will explore how North American forests that have experienced a life-time of the byproducts of human transportation respond by examining responses from the genetic and molecular levels to the forest scale. The research will be conducted at a large forest plot near the Washington DC metropolitan area with a long history of forest research and adjacent to a National Ecological Observatory Network (NEON) tower. These linkages provide opportunities to scale the molecular research to potential ecosystem responses to emissions reduction efforts. The Education Office at Smithsonian Environmental Research Center (SERC), which works with thousands of high school students and their teachers every year will incorporate results into classroom activities at the SERC Education Center. Knowing how trees and forested ecosystems respond to a transformed atmosphere is critical for providing projections of the Earth system under ongoing global change. This proposal provides a unique opportunity to explore the potential consequences of future policy by evaluating what could happen if emissions were dramatically reduced. The project provides an unprecedented opportunity to study the impacts from the genomic, physiological, population, community, ecosystem level given the ongoing research at these levels and leveraging existing infrastructure and data provided by the Smithsonian (Forest GEO), US Forest Service (FIA plots), and NSF (NEON). The research will focus on gene expression profiles of two species (beech and red maple) to explore whether they will exhibit parallel shifts favoring maximal growth in all size classes compared to pre-Covid-19 conditions. The research will examine how leaf chlorophyll content at the end of the growing season will predict gene expression differences. The research will also explore gene pathways that deal with reactive oxidative stress (ROS) reactions, repair, and stress signaling and the physiological responses for growth and reproduction for this and next growing seasonThis 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.

州和联邦政策大大限制了人类活动，以确保美国人口在COVID-19大流行期间的安全。 由于汽车和航空旅行的减少，这导致大气输入量大幅减少。在排放量一直很高的主要大都市地区，交通量前所未有地大幅减少，这正在改变大气层，甚至在大陆范围内也是如此。COVID-19事件提供了一个独特的，短暂的，难得的机会来研究森林将如何应对美国显著清洁的空气。该奖项将通过研究从遗传和分子水平到森林规模的反应，探索经历了人类运输副产品一生的北美森林如何作出反应。这项研究将在华盛顿大都会区附近的一个大型森林地块进行，该地块具有悠久的森林研究历史，毗邻国家生态观测网络（氖）塔。这些联系为将分子研究扩展到减排努力的潜在生态系统响应提供了机会。史密森环境研究中心（SERC）的教育办公室每年与数千名高中学生及其教师合作，将把结果纳入SERC教育中心的课堂活动中。了解树木和森林生态系统如何应对变化的大气层，对于在持续的全球变化下预测地球系统至关重要。这一提议提供了一个独特的机会，通过评估如果排放量大幅减少会发生什么来探索未来政策的潜在后果。该项目提供了一个前所未有的机会，研究基因组，生理，人口，社区，生态系统水平的影响，考虑到这些水平正在进行的研究，并利用史密森尼（森林GEO），美国林务局（FIA地块）和NSF（氖）提供的现有基础设施和数据。该研究将重点关注两个物种（山毛榉和红枫）的基因表达谱，以探索与2019冠状病毒病前相比，它们是否会在所有大小类别中表现出有利于最大生长的平行变化。该研究将研究生长季节结束时叶片叶绿素含量如何预测基因表达差异。该研究还将探索基因途径，处理反应性氧化应激（ROS）反应，修复和应激信号以及本生长季节和下一生长季节的生长和繁殖的生理反应。该奖项反映了NSF的法定使命，并被认为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来支持。