Collaborative Research: Links Between Long-Term Soil Carbon Storage and Canopy Properties in Tropical Forests

大气中的二氧化碳(CO2)一直在增加，导致了地球气候的变化，但目前还不清楚有多少二氧化碳可以被地球的生态系统吸收并储存在土壤和植物中。该项目的重点是了解二氧化碳的减少和储存过程，特别侧重于热带森林，这是地球上碳含量最丰富的生态系统之一。新的空间技术最近提高了利用卫星遥感测量植物碳储量的能力。然而，很大一部分碳储存在土壤中，在那里死亡的植物材料可以比活的植物储存更长的时间。这项研究使用新的遥感技术和基于野外的测量将植物和土壤的碳储量联系起来。该项目通过一个新的预测框架整合了这两种类型的测量，以扩大跨空间和跨时间的理解。该项目的更广泛影响包括对几名本科生和一名研究生(加州大学洛杉矶分校)进行尖端地理和生态技术方面的培训，以及为拉丁美洲大学生和社区成员创建现场技术员培训计划，以扩大科技工作队伍。在广泛的尺度上，这项研究还将提高热带森林生态系统碳储量的可预测性，为碳封存的管理提供见解。土壤碳(C)动态是全球碳循环模型中最大的不确定性来源之一，热带森林土壤包含一些最大的陆地碳储量。必须更好地了解植物对地上碳的吸收、这种碳向森林地面的转移以及随后这种碳在土壤中的损失或储存之间的相互作用，以预测气候变化可能如何改变大规模和长期的土壤碳储存。这项研究将通过跨地质和降雨梯度的建模、遥感和现场测量的交叉，重点关注树冠和土壤属性之间的联系，来促进对潮湿和季节性热带生物群的理解。这项研究将包括使用冠层荧光遥感测量方法测量进入森林的碳的总通量，并使用这些测量方法，结合地质学和土壤养分知识来预测土壤碳储量。中心假设是：反映地质和稀缺土壤养分可获得性的冠层特性的空间变化与热带森林土壤长期碳储存的景观尺度模式直接相关。将对土壤磷、降雨量和树冠物种组成进行评估，以确定它们在驱动土壤碳储存方面的作用。该方法的范围从土壤中的纳米有机矿物质组合到3平方公里的森林植物生长。这项研究将与史密森热带研究所合作，在巴拿马的各种热带森林中进行。为了更好地了解世界各地的热带森林如何储存碳，除了实地研究的空间和时间尺度外，还将把这些措施整合到现有的生态系统模型中。

Atmospheric carbon dioxide (CO2) has been increasing, leading to changes in Earth's climate, but it is unclear how much of that CO2 can be drawn back down by the planet's ecosystems and stored in soils and plants. This project focuses on understanding that CO2 draw-down and storage process with particular focus on tropical forests, which are one of the most carbon-rich ecosystems on Earth. New space technologies have recently improved the ability to measure plant carbon storage using satellite remote sensing. However, a large proportion of carbon storage occurs in soils, where dead plant material can be stored for much longer periods than in live plants. This study uses new remote sensing technologies and field-based measurements to link plant and soil carbon storage. The project integrates these two types of measurements through a new predictive framework to broaden understanding across space and time. Broader impacts for this project include the training of several undergraduate students and a graduate student (UCLA) in cutting-edge geographic and ecological technologies, and creation of a Field Technician Training Program for Latin American college students and community members to expand the work force in science and technology. At the broad scale, this research will also improve predictability of carbon storage across tropical forest ecosystems, providing insights for management of carbon sequestration.Soil carbon (C) dynamics present one of the largest sources of uncertainty in global C cycle models, with tropical forest soils containing some of the largest terrestrial C stocks. The interactions between aboveground C uptake by plants, transfer of this C to the forest floor, and subsequent loss or storage of this C in soils must be better understood to predict how climate change may alter large-scale and long-term soil C storage. This research will advance understanding of humid and seasonal tropical biomes through the intersection of modeling, remote sensing, and in situ field measurements across geological and rainfall gradients, focusing on the links between canopy and soil properties. The research will include measures of the total fluxes of C into forests using remote sensing measures of canopy fluorescence, and use these measures, together with knowledge of geology and soil nutrients, to predict soil C storage. The central hypothesis is that: Spatial variation in canopy properties, which reflect geology and the availability of scarce soil nutrients, are directly linked to landscape-scale patterns of long-term soil C storage in tropical forests. Soil phosphorus, rainfall, and canopy species composition will be assessed for their roles in driving soil C storage. The approach spans scales from nanometer organo-mineral associations in soils, to 3 km2 measures of forest plant growth. The study will be conducted in a variety of tropical forests in Panama in collaboration with the Smithsonian Tropical Research Institute. To better understand how tropical forests around the world store carbon, beyond the spatial and temporal scales of the field study, measures will also be integrated into an existing ecosystem model.