CAREER: Ensuring Co-Sustainability of Food Production and Environmental Quality in the U.S. Midwest Agroecosystems

职业：确保美国中西部农业生态系统食品生产和环境质量的共同可持续性

• 批准号: 1847334
• 负责人: Kaiyu Guan
• 金额: $ 50.99万
• 依托单位: University of Illinois at Urbana-Champaign
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-07-01 至 2024-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1847334&HistoricalAwards=false
• 关键词: CAREER; Ensuring; Co; Sustainability; Food

The past 200 years have seen the US Midwest be transformed from natural prairie/wetlands to fertile croplands that currently produce about one third of the world?s corn and soybean. This landscape was transformed by human activities through extensive subsurface "tiling" (drainage piping) and intensified uses of fertilizer and other inputs. However, this transformation has also created important questions about environmental sustainability. With further stress from climate change, can the US Midwest remain as the global food basket for the next 100 years? How can food production and environmental quality both be sustained in this landscape? In the US Midwest agroecosystem, carbon (e.g. crop growth), hydrology (both water quantity and quality), and nutrient cycles are all closely intertwined across scales, from the field/headwater scale to the whole river (greater Mississippi river basin) network and continental scales. Any human activities and practices do not just affect one component, rather the complete set of interconnections. Thus, a "system" analysis of the complex feedbacks and interactions is required to assess potential adaptations in the US Midwest agroecosystem. This project adopts a system view to holistically model and quantify the coupled "food-water-nutrient nexus" for the US Midwest agroecosystem. These models will significantly advance the understanding of the processes and predict agroecosystem behavior under current and future climate conditions. Two promising management practices (i.e. controlled drainage, and nutrient management) to achieve co-sustainability of food production and environmental quality will be assessedThe ultimate goal of the research is to establish an advanced understanding of how crop growth, hydrology, and nutrient cycles interact under different human management and climate conditions in the setting of the US Midwest agroecosystem. The project will develop a coupled land-river model and a model-data fusion approach, and integrate field-level collected data and remote sensing measurements. Specifically, tile drainage extent and drainage strength will be estimated in a spatially explicit manner at the regional scale for the three key states in the US Midwest, by a new model-data fusion approach based on ecohydrological processes. This dataset of tile drainage will then be used to develop a coupled land-river network model (ecosys-THREW) to quantify feedbacks/interactions among the water cycle, nitrogen cycle, and crop production across spatial scales in this agroecosystem, as well as to assess the potential of promising human management practices to allow co-sustainability of food production and environment quality in the US Midwest. Simulation results from the coupled ecosys-THREW model are expected to be used by policy makers and farmer communities to assess the agroecosystem conditions and potential impacts of various conservation practices at the regional scale.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.

过去 200 年来，美国中西部从天然草原/湿地转变为肥沃的农田，目前生产世界约三分之一的玉米和大豆。人类活动通过广泛的地下“铺瓦”（排水管道）以及化肥和其他投入的强化使用，改变了这一景观。 然而，这种转变也引发了有关环境可持续性的重要问题。随着气候变化带来的进一步压力，美国中西部能否在未来 100 年继续成为全球粮食篮？如何在这一景观中维持粮食生产和环境质量？ 在美国中西部农业生态系统中，碳（例如作物生长）、水文学（水量和水质）和养分循环在各个尺度上都紧密交织在一起，从田地/水源尺度到整个河流（大密西西比河流域）网络和大陆尺度。 任何人类活动和实践不仅仅影响一个组成部分，而是影响整个相互联系的集合。 因此，需要对复杂的反馈和相互作用进行“系统”分析，以评估美国中西部农业生态系统的潜在适应性。该项目采用系统视图对美国中西部农业生态系统的耦合“食物-水-营养关系”进行整体建模和量化。 这些模型将显着促进对过程的理解并预测当前和未来气候条件下的农业生态系统行为。 将评估两种有前途的管理实践（即控制排水和养分管理），以实现粮食生产和环境质量的共同可持续性。该研究的最终目标是深入了解美国中西部农业生态系统中不同人类管理和气候条件下作物生长、水文和养分循环如何相互作用。该项目将开发陆地-河流耦合模型和模型-数据融合方法，并整合现场收集的数据和遥感测量。具体而言，将通过基于生态水文过程的新模型数据融合方法，在区域尺度上以空间明确的方式估计美国中西部三个关键州的排水范围和排水强度。然后，该瓦片排水数据集将用于开发耦合的陆地-河流网络模型（ecosys-THREW），以量化该农业生态系统中跨空间尺度的水循环、氮循环和作物生产之间的反馈/相互作用，并评估有前途的人类管理实践的潜力，以实现美国中西部粮食生产和环境质量的共同可持续性。耦合的 ecosys-THREW 模型的模拟结果预计将被政策制定者和农民社区用来评估区域范围内的农业生态系统条件和各种保护实践的潜在影响。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

Assessing the impacts of cover crops on maize and soybean yield in the U.S. Midwestern agroecosystems

• DOI: 10.1016/j.fcr.2021.108264
• 发表时间: 2021-11
• 期刊: Field Crops Research
• 影响因子: 5.8
• 作者: Ziqi Qin;K. Guan;Wang Zhou;B. Peng;M. Villamil;Zhenong Jin;Jinyun Tang;R. Grant;L. Gentry;A. Margenot;G. Bollero;Ziyi Li

Assessing the impacts of pre-growing-season weather conditions on soil nitrogen dynamics and corn productivity in the U.S. Midwest

评估生长季前天气条件对美国中西部土壤氮动态和玉米生产力的影响

• DOI: 10.1016/j.fcr.2022.108563
• 发表时间: 2022
• 期刊: Field Crops Research
• 影响因子: 5.8
• 作者: Li, Ziyi;Guan, Kaiyu;Zhou, Wang;Peng, Bin;Jin, Zhenong;Tang, Jinyun;Grant, Robert F.;Nafziger, Emerson D.;Margenot, Andrew J.;Gentry, Lowell E.
• 通讯作者: Gentry, Lowell E.

High-resolution spatially explicit land surface model calibration using field-scale satellite-based daily evapotranspiration product

• DOI: 10.1016/j.jhydrol.2020.125730
• 发表时间: 2020-11
• 期刊: Journal of Hydrology
• 影响因子: 6.4
• 作者: Yi Yang;K. Guan;B. Peng;M. Pan;Chongya Jiang;T. Franz

Challenges and opportunities in precision irrigation decision-support systems for center pivots

• DOI: 10.1088/1748-9326/abe436
• 发表时间: 2021-04
• 期刊: Environmental Research Letters
• 影响因子: 6.7
• 作者: Jingwen Zhang;K. Guan;B. Peng;Chongya Jiang;Wang Zhou;Yi Yang;M. Pan;T. Franz;D. Heeren;D. Rudnick;O. Abimbola;H. Kimm;Kelly K. Caylor;S. Good;M. Khanna;J. Gates;Yaping Cai

Assessing the benefit of satellite-based Solar-Induced Chlorophyll Fluorescence in crop yield prediction

• DOI: 10.1016/j.jag.2020.102126
• 发表时间: 2020-08-01
• 期刊: INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
• 影响因子: 7.5
• 作者: Peng, Bin;Guan, Kaiyu;Kohler, Philipp
• 通讯作者: Kohler, Philipp