RII TRACK-4: Multiple Global Change Factors Control Forest Nitrogen Cycling - Remote Sensing and Machine Learning Identify Forest Function Across Developed Landscapes

RII TRACK-4：多种全球变化因素控制森林氮循环 - 遥感和机器学习识别已开发景观中的森林功能

• 批准号: 1832882
• 负责人: Tara Trammell
• 金额: $ 20.33万
• 依托单位: University of Delaware
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-10-01 至 2023-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1832882&HistoricalAwards=false
• 关键词: RII; TRACK; Multiple; Global; Change

Nontechnical DescriptionNitrogen (N), an essential element required by all life, moves through our environment in a very tight cycle. Human activity has more than doubled the amount of nitrogen that cycles through our environment, and yet our understanding of the global nitrogen cycle is about 50 years behind our understanding of the global carbon cycle. While large intact forests have the capacity to store excess N in substantial quantities, the majority of temperate deciduous forests in the U.S. are small forest patches due to expanding urban and suburban development. Small forests are more susceptible to consequences from human activities, such as excess N inputs and non-native invasive plant spread. This research seeks to understand the N sink potential of small forests embedded across developed landscapes that receive excess N from human activities and that experience altered N availability from non-native plant invasion. The fellowship makes new collaborations possible between the early-career PI at the University of Delaware and a senior scientist at the University of Wisconsin-Madison to utilize novel remote sensing techniques that enable large-scale study of forest N dynamics in the face of multiple global change factors, such as excess N inputs and non-native plant invasion. The outcome of this work will provide novel understanding of the source/sink potential of an important air/water pollutant (nitrogen). Technical DescriptionThe global nitrogen (N) cycle has changed dramatically over the last century through increases in reactive N worldwide due to anthropogenic activities. Temperate deciduous forests are an important sink for reactive N deposition unless N inputs exceed N demand and forests become an N source. Multiple facets of global change, such as invasive species spread and altered nutrient cycling can interact and feedback to alter forest structure and function, ultimately determining the ability of forests to act as an N sink. This project seeks to ascertain how multiple, co-occurring global changes alter N cycling in forests by utilizing innovative remote sensing and machine learning techniques to integrate forest canopy chemistry and hyperspectral imaging to determine forest health and nutrient status across heterogeneous landscapes. The research will leverage remote sensing techniques to assess how urbanization and invasion impact forest canopy N content and resorption, which are indicators of forest N availability. Forest canopy N dynamics will be evaluated across an urbanization gradient to determine N available for tree uptake in high N-deposition environments. Additionally, forest canopy N will be compared in invaded and uninvaded forests to determine whether plant invaders outcompete native trees for soil N. We will extend beyond the results of this work to forests in different regions across the US using a macroecology approach. The research from this fellowship will enhance our capability to estimate the N source vs sink potential of temperate deciduous forests, and will improve our predictive ability on the fate of global reactive N in forests.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.

非技术说明氮 (N) 是所有生命所需的基本元素，以非常紧密的循环在我们的环境中移动。人类活动使环境中循环的氮量增加了一倍多，但我们对全球氮循环的理解却比对全球碳循环的理解落后了大约 50 年。虽然大片完整的森林有能力储存大量过量的氮，但由于城市和郊区开发的扩大，美国的大多数温带落叶林都是小片森林。小森林更容易受到人类活动的影响，例如过量的氮输入和非本地入侵植物的蔓延。这项研究旨在了解嵌入发达景观中的小森林的氮汇潜力，这些森林从人类活动中吸收过量的氮，并因非本地植物入侵而改变氮的可用性。该奖学金使特拉华大学的早期职业研究员和威斯康星大学麦迪逊分校的高级科学家之间的新合作成为可能，利用新颖的遥感技术，在面临多种全球变化因素（例如过量的氮输入和非本地植物入侵）的情况下，实现对森林氮动态的大规模研究。这项工作的成果将为重要的空气/水污染物（氮）的源/汇潜力提供新的理解。技术说明由于人类活动导致全球活性氮的增加，全球氮 (N) 循环在上个世纪发生了巨大变化。温带落叶林是活性氮沉降的重要汇，除非氮输入超过氮需求并且森林成为氮源。全球变化的多个方面，例如入侵物种的传播和养分循环的改变，可以相互作用和反馈，从而改变森林的结构和功能，最终决定森林作为氮汇的能力。该项目旨在利用创新的遥感和机器学习技术，整合森林冠层化学和高光谱成像，以确定多种同时发生的全球变化如何改变森林中的氮循环，以确定异质景观中的森林健康和营养状况。该研究将利用遥感技术来评估城市化和入侵如何影响森林冠层氮含量和再吸收，这是森林氮可用性的指标。将在整个城市化梯度中评估森林冠层氮动态，以确定高氮沉积环境中树木吸收的可用氮。此外，还将对入侵和未入侵森林的森林冠层氮进行比较，以确定植物入侵者是否在土壤氮方面超越了本地树木。我们将使用宏观生态学方法将这项工作的结果扩展到美国不同地区的森林。该奖学金的研究将增强我们估计温带落叶林氮源与汇潜力的能力，并将提高我们对森林中全球活性氮命运的预测能力。该奖项反映了 NSF 的法定使命，并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，被认为值得支持。