Collaborative Research: SitS: Improving Rice Cultivation by Observing Dynamic Soil Chemical Processes from Grain to Landscape Scales

合作研究：SitS：通过观察从谷物到景观尺度的动态土壤化学过程来改善水稻种植

• 批准号: 2226649
• 负责人: Daniel Sousa
• 金额: $ 17.25万
• 依托单位: San Diego State University Foundation
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-01-01 至 2025-12-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2226649&HistoricalAwards=false
• 关键词: Collaborative; Research; SitS; Improving; Rice

This award was made through the "Signals in the Soil (SitS)" solicitation, a collaborative partnership between the National Science Foundation and the United States Department of Agriculture National Institute of Food and Agriculture (USDA NIFA). According to the US Center for Disease Control, arsenic (As) is the highest priority contaminant due to its prevalence and association with numerous chronic diseases, including heart disease, cancer, and diabetes. Hundreds of millions of people are chronically exposed to high levels of naturally occurring As through both drinking water and food. Paddy rice fields, which cover 12% of all arable land and provide 20% of human caloric intake, contain abundant iron oxides that retain natural As. Iron reduction in paddy fields mobilizes this As into water where it can be absorbed into rice crops. Humans are exposed to this toxic As when they consume this rice, and the As also reduces overall rice yields because it is toxic to rice too. Thus, As release from rice paddy soils poses a human health risk and threatens farming communities and the supply of one of the world’s most important crops. This collaborative research team from Columbia University, Union College, and San Diego State University aims to identify how rice cultivation practices, along with climate, affect where and when As is released from rice paddy soils and how this ultimately translates into absorption into the rice crop. Findings from this work will use real-time data from field and satellite measurements to help predict areas of greatest risk of As in the rice crop and to identify rice cultivation practices that minimize As uptake by the rice crop. This information will be shared with farming communities in the project study areas of Cambodia and Texas as well as with the broader scientific community to help promote better rice cultivation practices. The goal of this research is to develop a mechanistic understanding of the environmental factors that control the dissolved As concentration and speciation in rice paddy soils, and to use this information to develop effective management solutions. This research goal is well-suited to SitS because this multidisciplinary research team fuses frequent and dense measurements of soil geochemistry, mineralogy, microbiology, and hydrology collected with in situ sensors, remote sensing, and sampling in rice paddy soils to observe, model, and predict arsenic solid-solution partitioning and uptake into rice. High-resolution remote sensing data will be used to upscale pore-scale observations to field and landscape scales. The research will test three hypotheses examining the development of anaerobic conditions, iron (Fe) reduction and As release, and rice uptake of As: 1) External controls including climate, irrigation and fertilization drive the timing, location and depth of the redox gradients, and ultimately regulate As uptake in rice; 2) Steep near-surface gradients in dissolved As result from overlapping Fe and sulfate reduction, and create transient thioarsenic complexes that decouple As solubility from Fe reduction; and 3) When integrated with process-based models, remotely sensed indicators of water and nutrient stress can accurately scale field observations of redox gradients and rice uptake to larger landscapes. Field sites will be selected from working rice farms in Cambodia where rice-As levels frequently exceed safe levels. These sites will be extensively characterized throughout the year to measure changes in the composition, mineralogy, and redox state of Fe, As, and other key elements in the paddy soil and controls, the microbiological communities and metabolisms that facilitate those transformations, and their relationship to surface water hydrology, water balance, and irrigation regimens. Quantitative models will be constructed to test potential reaction networks and to establish the kinetic and thermodynamic controls affecting redox gradients in rice paddies. Novel machine learning, probabilistic models, and remotely sensed indicators of inundation, water, and nutrient stress will be used to predict the spatial and temporal distribution of redox processes, aqueous As, and rice-As levels more widely, and at a fine spatial scale. This integrated approach will provide new and powerful insight into the mechanism and dynamics of redox processes and environmental controls on As uptake by rice that will be tested with field sampling in Texas, where rice-As is also variable and frequently elevated. Broader Impacts activities include training of graduate and undergraduate students, and also research experiences for underrepresented and first-generation high school students.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.

据美国疾病中心称，该奖项是通过“土壤中的信号（SitS）”征集获得的，该征集是美国国家科学基金会与美国农业部国家食品和农业研究所（USDA NIFA）之间的合作伙伴关系。砷 (As) 是最重要的污染物，因为它普遍存在，并且与许多慢性疾病有关，包括心脏病、癌症和糖尿病。数亿人通过饮用水长期接触高含量的天然砷。稻田占耕地面积的 12%，提供人类热量摄入的 20%，其中含有丰富的铁氧化物，可以保留稻田中的天然砷，而稻田中的铁还原会将砷转移到水中，从而被水稻吸收。人类在食用这种稻米时会接触到这种有毒的砷，而且砷也会降低稻米的总产量，因为它对稻米也有毒，因此，稻田土壤中砷的释放会对人类健康造成威胁，并威胁农业社区和农作物。哥伦比亚大学、联合学院和圣地亚哥州立大学的合作研究小组旨在确定水稻种植实践以及气候如何影响稻田土壤中砷的释放时间和地点。以及这最终如何转化为水稻作物的吸收。这项工作的结果将使用来自田间和卫星测量的实时数据来帮助预测水稻作物中砷风险最大的区域，并确定最大限度地减少砷吸收的水稻种植方法。该信息将与水稻作物共享。柬埔寨和德克萨斯州项目研究地区的农业社区以及更广泛的科学界，以帮助促进更好的水稻种植实践。这项研究的目标是对控制溶解砷浓度和形态的环境因素有一个机械的认识。并利用这些信息开发有效的管理解决方案，该研究目标非常适合 SitS，因为这个多学科研究团队融合了现场收集的土壤地球化学、矿物学、微生物学和水文学的频繁而密集的测量。传感器、遥感和稻田土壤采样，以观察、模拟和预测水稻中砷固溶体的分配和吸收，将用于将孔隙尺度观测升级到田间和景观尺度。将测试三个假设，检查厌氧条件的发展、铁 (Fe) 还原和砷释放以及水稻对砷的吸收： 1) 包括气候、灌溉和施肥在内的外部控制驱动着厌氧条件的时间、位置和深度。氧化还原梯度，并最终调节水稻中的 As 吸收；2) 由于 Fe 和硫酸盐还原重叠而导致溶解 As 中的陡峭近表面梯度，并产生瞬时硫代砷复合物，使 As 溶解度与 Fe 还原脱钩；3) 当与过程集成时基于模型，水和养分胁迫的遥感指标可以准确地将氧化还原梯度和水稻吸收的实地观测扩展到更大的景观。田间地点将从柬埔寨的水稻农场中选择，那里种植着水稻。这些地点将在一年中进行广泛的表征，以测量稻田土壤中铁、砷和其他关键元素的成分、矿物学和氧化还原状态的变化，并控制促进微生物群落和新陈代谢的变化。将构建这些转化及其与地表水水文、水平衡和灌溉方案的关系，以测试潜在的反应网络并建立影响稻田氧化还原梯度的动力学和热力学控制。概率模型以及洪水、水和营养胁迫的遥感指标将用于更广泛地、在精细的空间尺度上预测氧化还原过程、水体砷和稻米砷水平的空间和时间分布。将为稻米吸收砷的氧化还原过程和环境控制的机制和动态提供新的、强有力的见解，这些将在德克萨斯州进行实地采样测试，那里的稻米砷也存在变化并且经常升高。更广泛的影响活动包括研究生培训。和本科生，该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Mapping multi-decadal wetland loss: Comparative analysis of linear and nonlinear spatiotemporal characterization

• DOI: 10.1016/j.rse.2023.113969
• 发表时间: 2024-03
• 期刊: Remote Sensing of Environment
• 影响因子: 13.5
• 作者: Margot Mattson;Daniel Sousa;Amy Quandt;Paul Ganster;Trent Biggs

Spectral Characteristics of the Dynamic World Land Cover Classification

动态世界土地覆盖分类的光谱特征

• DOI: 10.3390/rs15030575
• 发表时间: 2023
• 期刊: Remote Sensing
• 影响因子: 5
• 作者: Small, Christopher;Sousa, Daniel
• 通讯作者: Sousa, Daniel

The effect of agricultural land retirement on pesticide use

• DOI: 10.1016/j.scitotenv.2023.165224
• 发表时间: 2023-07-03
• 期刊: SCIENCE OF THE TOTAL ENVIRONMENT
• 影响因子: 9.8
• 作者: Larsen，Ashley E.;Quandt，Amy;Sousa，Daniel
• 通讯作者: Sousa，Daniel

Robust Cloud Suppression and Anomaly Detection in Time-Lapse Thermography

• DOI: 10.3390/rs16020255
• 发表时间: 2023-11
• 期刊: Remote. Sens.
• 作者: Christopher Small;D. Sousa

Scalable Early Detection of Grapevine Viral Infection with Airborne Imaging Spectroscopy

利用机载成像光谱对葡萄病毒感染进行可扩展的早期检测

• DOI: 10.1094/phyto-01-23-0030-r
• 发表时间: 2023
• 期刊: Phytopathology®
• 作者: Galvan, Fernando E.;Pavlick, Ryan;Trolley, Graham;Aggarwal, Somil;Sousa, Daniel;Starr, Charles;Forrestel, Elisabeth;Bolton, Stephanie;Alsina, Maria del;Dokoozlian, Nick
• 通讯作者: Dokoozlian, Nick