Collaborative Research: Navigating Disturbance Regimes in the New Arctic

合作研究：驾驭新北极的干扰制度

基本信息

批准号：
1928048
负责人：
Mark Lara
金额：
$ 38.31万
依托单位：
University of Illinois at Urbana-Champaign
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2020
资助国家：
美国
起止时间：
2020-03-01 至 2025-02-28
项目状态：
未结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1928048&HistoricalAwards=false
关键词：
Collaborative Research Navigating Disturbance Regimes

项目摘要

The Arctic has experienced unprecedented warmth over the past several decades. These areas have also experienced increased disturbances due to wildfires, permafrost degradation, and shrub expansion. Evidence suggests dynamic interactions and feedbacks exist among Arctic disturbance regimes. However, the interdependence of these disturbances makes quantifying their impact challenging. Overcoming this challenge is the first step in improving our capacity to predict future disturbance regimes in the face of climate change. To achieve this goal, researchers will evaluate the vulnerability of Arctic tundra regions in northern Alaska to disturbances over decadal to centennial-time scales. Successful completion of this work will facilitate our ability to predict impacts to local indigenous communities, regional Arctic infrastructure, and global carbon and energy dynamics. Outreach to 20 indigenous Arctic communities will communicate results and develop knowledge to assist these communities adapt to and mitigate impacts.The objective of this research is to investigate decadal to centennial time-scale interactions between climate, disturbances, and the physical environment across the Alaskan tundra. This will be achieved by examining permafrost degradation, tall shrub expansion, and potential biophysical and biogeochemical feedbacks during disturbances induced by climate change. Historical observations of permafrost degradation and tall shrub expansion will be used to project future landscape evolution. Spatial heterogeneity will be represented by spatially disaggregating the landscape into key state factors that are subdivided into terrain categories and disturbance types. Sophisticated machine learning algorithms will be used to assess decadal patterns of land cover change using high resolution aerial and satellite imagery. These will be used to determine the primary drivers of change to landscape evolution. Paleoecological reconstructions (2,000+ years) of climate, wildfire, permafrost degradation, and shrub expansion will be derived from lake sediment cores and linked with satellite observations to capture patterns of land-cover change spanning decadal to centennial timescales. Together, these results will provide an independent test of the historical drivers of landscape evolution under a range of disturbance regimes. The biogeophysical implications of landscape evolution will be estimated using surveys of vegetation and soil properties, linked with empirical land-cover change models. This project will reconcile several fundamental knowledge gaps that currently limit global climate change projections. In addition, results will help Arctic communities anticipate and adapt to environmental change.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.

在过去的几十年中，北极经历了空前的温暖。由于野火，多年冻土降解和灌木的扩张，这些区域还经历了增加的干扰。有证据表明，北极干扰方案中存在动态相互作用和反馈。但是，这些干扰的相互依赖性使量化其影响具有挑战性。克服这一挑战是提高我们在气候变化时预测未来干扰制度的能力的第一步。为了实现这一目标，研究人员将评估阿拉斯加北部北极苔原地区的脆弱性，以期在衰老到百年纪念尺度上的干扰。这项工作的成功完成将有助于我们预测对当地土著社区，区域北极基础设施以及全球碳和能源动态的影响的能力。向20个土著北极社区进行宣传，将传达结果并发展知识，以帮助这些社区适应并减轻影响。这项研究的目的是调查际际气候，骚乱，骚乱和阿拉斯加Tundra的物理环境之间的百年纪念时间尺度相互作用。这将通过检查在气候变化引起的干扰期间检查多年冻土降解，高灌木膨胀以及潜在的生物物理和生物地球化学反馈。对多年冻土降解和高灌木扩张的历史观察将用于投射未来的景观进化。空间异质性将通过空间将景观分为关键状态因素来表示，这些状态被细分为地形类别和干扰类型。精致的机器学习算法将用于使用高分辨率的空中和卫星图像来评估土地覆盖变化的年代际模式。这些将用于确定变化对景观演变的主要驱动力。古生物学重建（2,000多年）的气候，野火，多年冻土降解和灌木的膨胀将源自湖泊沉积物核心，并与卫星观测值联系起来，以捕获跨越阶层的衰老到百年纪念时间标准的土地覆盖模式。这些结果将共同对景观演变的历史驱动因素提供独立的测试。将使用植被和土壤特性的调查来估算景观演化的生物地球物理意义，并与经验的土地覆盖变化模型有关。该项目将调和一些目前限制全球气候变化预测的基本知识差距。此外，结果将有助于北极社区的预期并适应环境变化。该奖项反映了NSF的法定任务，并使用基金会的知识分子优点和更广泛的影响审查标准，被视为值得通过评估来提供支持。

项目成果

期刊论文数量（14）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Alaska Peatland Map (2019-2021)

阿拉斯加泥炭地地图（2019-2021）

DOI：
10.18739/a2nk3667m
发表时间：
2023
期刊：
NSF Arctic Data Center
影响因子：
0
作者：
Lara, Mark J.;Michaelides, Roger;Anderson, Duncan;Chen, Wenqu;Hall, Emma;Ludden, Caroline;Schore, Aiden;Mishra, Umakant;Scott, Sarah
通讯作者：
Scott, Sarah

Topographical Controls on Hillslope‐Scale Hydrology Drive Shrub Distributions on the Seward Peninsula, Alaska

地形对山坡的控制——尺度水文驱动阿拉斯加苏厄德半岛的灌木分布

DOI：
10.1029/2020jg005823
发表时间：
2021
期刊：
Journal of Geophysical Research: Biogeosciences
影响因子：
0
作者：
Mekonnen, Zelalem A.;Riley, William J.;Grant, Robert F.;Salmon, Verity G.;Iversen, Colleen M.;Biraud, Sébastien C.;Breen, Amy L.;Lara, Mark J.
通讯作者：
Lara, Mark J.

Multisensor UAS mapping of Plant Species and Plant Functional Types in Midwestern Grasslands