Doctoral Dissertation Research: Predicting the spread of Rapid Ohia Death and detecting resistant varieties of Metrosideros polymorpha

博士论文研究：预测快速奥伊亚死亡病的传播并检测Metrosideros polymorpha的抗性品种

• 批准号: 2218932
• 负责人: Gregory Asner
• 金额: $ 3.14万
• 依托单位: Arizona State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-15 至 2024-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2218932&HistoricalAwards=false
• 关键词: Doctoral; Dissertation; Research; Predicting; spread

This project develops mitigation strategies to lessen the ecological, economic, and social consequences of forest pathogens. Tools that allow forest managers to accurately monitor disease spread across large spatial scales and identify hosts resistant to forest pathogens are critical to controlling disease outbreaks. This project uses remote sensing to develop a monitoring system for Rapid Ohia Death, a problematic pathogen affecting native forest areas, and a means of identifying resistant hosts to assist in the design of conservation strategies. Discovered in 2010, Rapid Ohia Death has led to widespread declines of the keystone species, Metrosideros polymorpha, though the extent of its effect is unknown due to the lack of precise monitoring systems. M. polymorpha accounts for over eighty percent of the biomass across forests, provides habitat to many endemic plants and animals, is vital for groundwater recharge, and is culturally and economically significant to local communities. As a result, many conservation agencies seek to understand and mitigate the threat of Rapid Ohia Death. This project contributes to efforts to conserve native forests by spatially mapping M. polymorpha, its four genetic varieties, and Rapid Ohia Death spread across using state-of-the-art remote sensing technologies. Existing forest species maps are over 20 years old and rely on remote sensing instruments with coarse spatial and spectral resolution. Not only does this award update these M. polymorpha spatial maps, but it also improves upon their accuracy and precision by using high resolution remote sensing data from an airborne imaging spectrometer. This award goes further than species mapping by developing novel landscape-scale spatial data of the four described M. polymorpha subspecies. By fusing maps and data from multispectral satellites, this project tracks Rapid Ohia Death spread through time. These datasets provide the foundation for understanding disease spread and host resistance. Combined, these data products and resulting information will expedite the process of restoring forests with Rapid Ohia Death-resistant M. polymorpha individuals. This research focuses on the needs of federal, State, and private organizations, and resulting data products will be integrated into their mitigation strategies. This project contributes to forest conservation by developing novel methods and datasets to understand the spatial ecology of disease spread regarding host resistance.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.

该项目制定缓解战略，以减轻森林病原体的生态，经济和社会后果。使森林管理人员能够准确监测疾病在大空间范围内的传播并确定对森林病原体有抵抗力的宿主的工具，对于控制疾病爆发至关重要。该项目利用遥感技术开发一个监测系统，监测影响原生森林地区的一种有问题的病原体-Ohia快速死亡病，并开发一种查明抗性宿主的手段，以协助制定保护战略。在2010年发现的快速Ohia死亡导致了关键物种Metrosideros polymorpha的广泛下降，尽管由于缺乏精确的监测系统，其影响程度尚不清楚。M. polymorpha占整个森林生物量的80%以上，为许多地方性植物和动物提供栖息地，对地下水补给至关重要，对当地社区具有文化和经济意义。因此，许多保护机构试图了解和减轻快速Ohia死亡的威胁。该项目通过对M.多形藻、其四个遗传变种和奥希亚快速死亡利用最先进的遥感技术传播。现有的森林物种图已有20多年的历史，依赖于空间和光谱分辨率较低的遥感仪器。这个奖项不仅更新了这些M。该系统不仅提供了多形物空间地图，而且还通过使用机载成像光谱仪的高分辨率遥感数据提高了其准确性和精确度。该奖项通过开发四种描述的M.多形亚种通过融合来自多光谱卫星的地图和数据，该项目跟踪了随着时间的推移而传播的快速Ohia死亡。这些数据集为了解疾病传播和宿主抗性提供了基础。结合起来，这些数据产品和产生的信息将加快快速Ohia抗死亡M恢复森林的过程。polymorpha个体这项研究的重点是联邦，州和私人组织的需求，由此产生的数据产品将被纳入其缓解战略。该项目通过开发新的方法和数据集来了解与宿主抗性有关的疾病传播的空间生态学，为森林保护做出了贡献。该奖项反映了NSF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。