International Research Fellowship Program: Spectral and Geographic Analysis of Soil Carbon in East Africa

0202582布朗大学国际研究奖学金计划使美国科学家和工程师能够在国外进行三到二十四个月的研究。 该计划的奖项提供了联合研究的机会，并使用独特或互补的设施，专业知识和国外的实验条件。该奖项将支持为期三个月的研究奖学金由博士大卫J布朗与博士基思D。Shepherd和Markus沃尔什在肯尼亚内罗毕的国际农林研究中心（ICRAF）说，有机质（以碳含量衡量）在土壤功能中起着至关重要的作用，随着人们对气候变化的日益关注，人们越来越关注土壤作为全球大气二氧化碳的重要来源或汇。 针对这些问题，PI建议：1）结合联合收割机地形和反射率信息，为肯尼亚选定的流域建立土壤有机碳垂直和地理分布模型; 2）使用反射率数据改进表征土壤碳的统计方法。 肯尼亚等国（以及美国）的土地退化、粮食安全和淡水沉积评估与土壤中有机物的类型、数量和分布密切相关。 科学界对改进区域和全球土壤碳的估计以及确定潜在的碳固存地点的研究有着重大的兴趣。 东道主率先使用反射光谱分析来表征土壤特性。 他们在野外或实验室里使用光谱仪，就像游客拍摄当地文化的照片一样，“抓拍”土壤样本--只不过他们的“相机”以数字方式捕捉从红外线到可见光谱的数百个波段的光反射。 最终，这项研究将使科学家能够利用卫星图像绘制表层土壤图，为土地退化提供早期预警，并精确测量全球碳库。 该项目将通过实验室和现场维度来补充这项工作。 在实验室中，PI将依次剥离无机，不稳定和非不稳定的碳;在过程的每一步扫描土壤材料。 通过这些扫描，他可以分离出不同组分对土壤整体光谱特征的贡献，并根据光谱数据改进预测土壤碳的模型。 在该领域，他将采用数字地形模型结合光谱分析来预测地下土壤碳分布。 坡度、曲率和其他更复杂的地形指数可以预测侵蚀、沉积、渗透和地下水位的深度-所有这些因素都有助于有机物的积累。

0202582BrownThe International Research Fellowship Program enables U.S. scientists and engineers to conduct three to twenty-four months of research abroad. The program's awards provide opportunities for joint research, and the use of unique or complementary facilities, expertise and experimental conditions abroad.This award will support a three month research fellowship by Dr. David J. Brown to work with Drs. Keith D. Shepherd and Markus Walsh, at the International Centre for Research in Agroforestry (ICRAF) in Nairobi, Kenya.Organic matter (measured as carbon content) plays a vital role in soil functioning and with a growing concern about climate change there has been increased attention paid to soil as an important source or sink for global atmospheric carbon dioxide. Addressing these concerns, the PI proposes to 1) combine terrain and reflectance information to model the vertical and geographic distribution of soil organic carbon for a selected watershed in Kenya; and 2) refine statistical methods for characterizing soil carbon using reflectance data. Land degradation, food security, and fresh water sedimentation assessments in countries like Kenya (and in the United States) can be closely linked to the type, amount, and distribution of organic matter in the soil. The scientific community has a vital interest in research that improves the estimates of regional and global soil carbon, and the identification of potential sites for carbon sequestration. The hosts are pioneering the use of reflectance spectral analysis to characterize soil properties. Using a spectrometer in the field or lab, they "snap" a soil sample just as a tourist snaps photos of local culture - except that their "camera" digitally captures light reflection over hundreds of bands from infrared through the visible light spectrum. Ultimately, this research will allow scientists to map surface soil using satellite imagery - providing early warnings of land degradation and precise measurements of global carbon pools. This project will complement this work with lab and field dimensions. In the lab the PI will sequentially strip away inorganic, labile and non-labile carbon; scanning the soil material at each step of the process. With these scans, he can then isolate the contributions of the various fractions to the overall spectral signature of the soil, and refine models predicting soil carbon from spectral data. In the field, he will employ digital terrain models in conjunction with spectral analysis to predict subsurface soil carbon distributions. Slope, curvature and other more complex terrain indices can predict erosion, deposition, infiltration and depth to the water table - all factors that contribute to organic matter accumulation.