Collaborative Research: MRA: Seasonality of Photosynthesis of Temperate and Boreal Conifer Forests Across North America

合作研究：MRA：北美温带和北方针叶林光合作用的季节性

• 批准号: 1925992
• 负责人: Barry Logan
• 金额: $ 12.32万
• 依托单位: Bowdoin College
• 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: 2020-01-01 至 2024-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1925992&HistoricalAwards=false
• 关键词: Collaborative; Research; MRA; Seasonality; Photosynthesis

The climate of the Earth is warming due to increased carbon dioxide (CO2) in the atmosphere, a result primarily of combustion of fossil fuels to provide energy for human activities. Forests worldwide are helping to mitigate the atmospheric increase. Forests absorb more CO2 now than in prior decades, slowing the increase and benefiting society. In response to warming, the timing and magnitude of photosynthesis by land plants is changing in many locations, making it difficult to predict how forest carbon cycle feedbacks may affect future climate. Satellite remote sensing indicates that deciduous forests across North America have generally responded to environmental change by extending their growing season, with earlier spring leaf flush and later fall leaf drop. However, we do not understand how evergreen coniferous forests respond to warming because of limitations of traditional remote sensing techniques. Scientists also need better understanding of physiological processes that allow conifers to withstand cold winters. This study will link observations of reflected and emitted light from conifer forests at scales from leaf to forest canopy to satellite, to focus on seasonality of photosynthesis by conifer forests in space and time. The research will utilize cutting-edge scientific infrastructure built by the National Ecological Observatory Network (NEON) in forests from Florida to Alaska. This work will document the variations in physiology that occur in forests experiencing winters of varying severity, to refine and test models of photosynthesis to predict the critically important role of forests in mitigating future environmental change. This project will benefit ecological scientists by improving techniques in satellite remote sensing to quantify seasonality of conifer photosynthesis across North America. The project will engage the public by conducting science outreach efforts at the Natural History Museum of Utah, providing interactive resources to help visitors connect changes observed in their backyard to similar ecosystems across the continent.Plants are frequently exposed to more sunlight than they can use for photosynthesis, even when weather conditions are favorable, and without protective mechanisms, tissue damage would result. Plants have evolved elaborate physiological processes to safely dissipate excess sunlight energy. During the growing season, this involves light-dependent, reversible cycling of carotenoid pigments of the xanthophyll cycle, a highly-conserved photoprotective process across the plant kingdom. However, during cold winters, the xanthophyll pigments participate in an alternate, poorly-understood light-independent process, remaining in photoprotective mode during both the day and the night. Both photoprotective types involve seasonal pigment and physiological changes that alter leaf color, and affect fluorescence emission by chlorophyll molecules. Using a variety of tower- and satellite-based instruments, these physiological changes can be detected via light reflected from vegetation (as the photochemical reflectance index, the chlorophyll/carotenoid index, and others) and via solar-induced fluorescence. The project's overall objective is to quantify spatial and temporal variability in forest photosynthetic capacity of conifer forests across North America, using NEON and other infrastructure. We will link observations of vegetation reflectance and fluorescence with high temporal and spatial resolution (tower-based spectroscopy) to tower-based carbon fluxes, conifer-needle-level photosynthesis and pigment composition. These data will be assimilated to refine and test models of seasonal forest photosynthesis and provide new tools to launch a continental-scale observational framework to quantify photosynthetic response to environmental change over the 30-year NEON lifetime.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.

由于大气中二氧化碳（CO2）的增加，地球的气候正在变暖，这主要是化石燃料燃烧为人类活动提供能量的结果。全世界的森林正在帮助减缓大气层的增加。森林现在吸收的二氧化碳比过去几十年多，减缓了增长，造福社会。为了应对气候变暖，许多地方的陆地植物光合作用的时间和强度正在发生变化，因此很难预测森林碳循环反馈如何影响未来的气候。卫星遥感显示，北美各地的落叶林普遍对环境变化作出反应，延长了生长季节，春季落叶较早，秋季落叶较晚。然而，由于传统遥感技术的局限性，我们并不了解万年青针叶林对气候变暖的反应。科学家们还需要更好地了解针叶树抵御寒冬的生理过程。这项研究将从针叶林的反射和发射光的观测从树叶到森林冠层到卫星的尺度联系起来，重点关注针叶林光合作用在空间和时间上的季节性。这项研究将利用国家生态观测网络（氖）在从佛罗里达到阿拉斯加的森林中建立的尖端科学基础设施。这项工作将记录在经历不同严重程度的冬季的森林中发生的生理变化，以改进和测试光合作用模型，预测森林在减轻未来环境变化方面的至关重要的作用。该项目将通过改进卫星遥感技术来量化北美针叶树光合作用的季节性，从而使生态科学家受益。该项目将通过在犹他州自然历史博物馆开展科学推广活动，吸引公众参与，提供互动资源，帮助游客将他们后院观察到的变化与整个大陆的类似生态系统联系起来。植物经常暴露在比它们用于光合作用的阳光更多的阳光下，即使天气条件有利，如果没有保护机制，组织损伤也会导致。植物已经进化出复杂的生理过程来安全地耗散多余的阳光能量。在生长季节，这涉及叶黄素循环的类胡萝卜素色素的光依赖性可逆循环，这是植物界高度保守的光保护过程。然而，在寒冷的冬季，叶黄素色素参与了一个交替的，不太清楚的光独立的过程，在白天和夜晚都保持在光保护模式。这两种光保护类型都涉及季节性色素和生理变化，改变叶片颜色，并影响叶绿素分子的荧光发射。利用各种塔上和卫星上的仪器，这些生理变化可以通过植被反射的光（如光化学反射指数、叶绿素/类胡萝卜素指数等）和通过太阳引起的荧光来检测。该项目的总体目标是利用氖和其他基础设施，量化北美针叶林光合能力的空间和时间变异。我们将把高时空分辨率的植被反射率和荧光观测（基于塔的光谱学）与基于塔的碳通量、针叶级光合作用和色素成分联系起来。这些数据将被吸收，以完善和测试模型的季节性森林光合作用，并提供新的工具，推出一个大陆规模的观测框架，以量化光合作用对环境变化的反应，在30年的氖lifest.This奖项反映了NSF的法定使命，并已被认为是值得支持，通过评估使用基金会的知识价值和更广泛的影响审查标准。

项目成果

Wide variation of winter-induced sustained thermal energy dissipation in conifers: a common-garden study

冬季引起的针叶树持续热能耗散的广泛变化：一项普通花园研究

• DOI: 10.1007/s00442-021-05038-y
• 发表时间: 2021
• 期刊: Oecologia
• 影响因子: 2.7
• 作者: Walter-McNeill, A.;Garcia, M. A.;Logan, B. A.;Bombard, D. M.;Reblin, J. S.;Lopez, S.;Southwick, C. D.;Sparrow, E. L.;Bowling, D. R.
• 通讯作者: Bowling, D. R.

Accounting for canopy structure improves hyperspectral radiative transfer and sun-induced chlorophyll fluorescence representations in a new generation Earth System model

• DOI: 10.1016/j.rse.2021.112497
• 发表时间: 2021-05-13
• 期刊: REMOTE SENSING OF ENVIRONMENT
• 影响因子: 13.5
• 作者: Braghiere, Renato K.;Wang, Yujie;Frankenberg, Christian
• 通讯作者: Frankenberg, Christian

Tower‐Based Remote Sensing Reveals Mechanisms Behind a Two‐phased Spring Transition in a Mixed‐Species Boreal Forest

基于塔的遥感揭示了混合物种北方森林两阶段春季转变背后的机制

• DOI: 10.1029/2020jg006191
• 发表时间: 2021
• 期刊: Journal of Geophysical Research: Biogeosciences
• 作者: Pierrat, Zoe;Nehemy, Magali F.;Roy, Alexandre;Magney, Troy;Parazoo, Nicholas C.;Laroque, Colin;Pappas, Christoforos;Sonnentag, Oliver;Grossmann, Katja;Bowling, David R.
• 通讯作者: Bowling, David R.