Collaborative Research: MSA: Tree crown economics: testing and scaling a functional trait-based theory

合作研究：MSA：树冠经济学：测试和扩展基于功能性状的理论

• 批准号: 2106080
• 负责人: Brenden McNeil
• 金额: $ 25万
• 依托单位: West Virginia University Research Corporation
• 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: 2021-06-15 至 2025-05-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2106080&HistoricalAwards=false
• 关键词: Collaborative; Research; MSA; Tree; crown

Climate change is subjecting trees to new environmental conditions and it is increasingly important to understand how trees respond to these changes. While ecologists have long known that tree crown architecture (the arrangement and orientation of leaves within a tree crown) can be an important way that trees adapt and acclimate to environmental change, there is not well-established theory or techniques for measuring crown architecture. This study tests novel theory and applies new technologies for measuring crown architecture, including from automated cameras mounted to nine National Ecological Observation Network (NEON) towers in the eastern USA, and from accompanying laser ranging (LiDAR) measurements from the NEON Airborne Observation Platform (AOP). By testing how measured differences in crown architecture relate to coincident airborne and satellite measurements of tree productivity, the research can inform ecological models and forest management techniques aimed at maximizing sustainable forest growth. The research team includes students from West Virginia University (WVU) participating in a research experience for undergraduates (REU) program, as well as hundreds of sixth-graders and their teachers making tree architecture and productivity measurements from a “Sustainability Treehouse” used by the WVU Science Adventure School.Complementing the successful theory of leaf economics, the research develops a trait-based theory of crown economics. First, by measuring the trait of mean leaf angle from new time-lapse cameras mounted to nine NEON towers and the Sustainability Treehouse, and traits of crown density and rugosity from NEON AOP LiDAR data, the researchers assess theory positing that economic tradeoffs drive co-variation in these three crown traits. Second, the researchers examine the role of crown traits in driving patterns of near-infrared reflectance from vegetation (NIRv), as measured by: (1) tower-mounted phenocams, (2) NEON AOP spectral data, and (3) Landsat phenology metrics of peak NIRv reflectance and the rate of NIRv “greendown” within a growing season. The research team uses spatial variability within and across the sites to test that the annual peak of NIRv (and correlated rates of water, carbon, and albedo fluxes) is higher in denser, but less rugose, crowns that have more horizontal leaf angles. And, the team uses temporal variability to gauge the degree to which rates of NIRv greendown are driven by increasingly vertical leaf angles through the growing season. Thus, by analyzing these relationships among crown traits and NIRv, the research can demonstrate how predictions of crown economic theory can elucidate new mechanisms controlling local- to continental-scale responses of forests to climate 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.

气候变化使树木面临新的环境条件，了解树木如何应对这些变化变得越来越重要。虽然生态学家早就知道树冠结构（树冠内树叶的排列和方向）可能是树木适应和适应环境变化的重要方式，但目前还没有成熟的理论或技术来测量树冠结构。这项研究测试新的理论，并应用新技术来测量树冠结构，包括安装在美国东部9个国家生态观测网络（氖）塔上的自动相机，以及来自氖机载观测平台（AOP）的激光测距（LiDAR）测量。通过测试树冠结构的测量差异与树木生产力的同步航空和卫星测量之间的关系，该研究可以为生态模型和森林管理技术提供信息，旨在最大限度地提高森林的可持续增长。 该研究团队包括来自西弗吉尼亚大学（WVU）参加本科生研究体验（REU）项目的学生，以及数百名六年级学生和他们的老师，他们在WVU科学冒险学校使用的“可持续性树屋”中进行树木结构和生产力测量。该研究补充了叶经济学的成功理论，开发了基于性状的树冠经济学理论。首先，通过测量安装在9个氖塔和Sustainability Treehouse上的新延时相机的平均叶片角度特征，以及氖AOP LiDAR数据的树冠密度和粗糙度特征，研究人员评估了假设经济权衡驱动这三个树冠特征的协变的理论。其次，研究人员研究了树冠特征在驱动植被近红外反射率（NIRv）模式中的作用，这些模式通过以下方式测量：（1）安装在塔上的phenocams，（2）氖AOP光谱数据，以及（3）Landsat物候学指标峰值NIRv反射率和生长季节内NIRv“变绿”的速率。 研究小组使用站点内部和站点之间的空间变异来测试NIRv的年度峰值（以及水，碳和水通量的相关速率）在密度更高，但皱纹更少的树冠中更高，这些树冠具有更多的水平叶角。而且，该团队使用时间变异性来衡量NIRv变绿率在生长季节中受到越来越多的垂直叶片角度驱动的程度。因此，通过分析树冠性状和NIRv之间的关系，研究可以证明树冠经济理论的预测如何阐明控制地方到大陆尺度森林对气候变化的反应的新机制。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。