EAGER: Computational Agroecology: A Systems Approach

EAGER：计算农业生态学：系统方法

• 批准号: 2138292
• 负责人: Barath Raghavan
• 金额: $ 30万
• 依托单位: University of Southern California
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-01-01 至 2024-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2138292&HistoricalAwards=false
• 关键词: EAGER; Computational; Agroecology; Systems; Approach

Recent work on network verification has had to deal simultaneously with the heterogeneity of large networks of hardware and software elements that interact in complex ways and with scaling verification and synthesis for practical use in network planning and management. These challenges mirror the challenges in applying computing coherently to new challenges in agriculture. The last eighty years have seen a dramatic narrowing to just 7 crops that produce 80% of global calories, a situation that is insecure given increasing demands and changing pressures. This project will introduce a new computational framework extending and expanding recent networking research techniques to unify the disparate approaches to Digital Agriculture, with an aim to yield both greater productivity and greater security in the food system while advancing the state of the art in modeling agroecosystems computationally at large scale. As a result of this large scale, we will develop new techniques for scaling network verification, especially in settings where only approximate data is available. The innovations developed in this research will be applicable back to large-scale network verification, planning, and provisioning.Specifically, this project will introduce a computational framework for Digital Agriculture that subsumes both precision agriculture and agroecology. This computational framework will proceed to root the analysis, simulation, and understanding of agroecosystems using a network-verification-based space-time state-space representation of the infinite possible configurations of a piece of land and the biogeochemical elements on it. This approach enables consideration of agroecological designs and systems of management, including complex mixtures of crops and cropping systems, that are seldom considered in conventional approaches; it simultaneously enables rigorous analysis of formerly inscrutable agroecological methods. This new framework will provide essential guidance for the critical changes facing vast human-managed lands. This project will consist of a conceptual state-space framework called Agroecological Transition Functions and a practical software systems framework called Computational Agroecology. Beyond simply advancing agroecological understanding, this project will advance networked systems research by exploring state-space exploration, such as in network verification, at much larger scale than before, and by doing so considering the application of new types of networked systems of sensing and actuation in a complex physical environment. This framework will be instantiated through new abstractions for programming cyberinfrastructure to explore new engineered technologies in sensing and actuation, including human practices and technologies that do not yet have physical instantiations. The outputs of this research will apply back to core areas of networked systems research; specifically, this work will enable improved scaling of network verification and synthesis through improvements in approximation and aliasing via the state-space framework that will be developed.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.

最近的网络验证工作必须同时处理以复杂方式交互的大型硬件和软件元素网络的异构性，以及在网络规划和管理中实际使用的扩展验证和综合。 这些挑战反映了将计算连贯地应用于农业新挑战的挑战。在过去的八十年里，产生全球热量 80% 的作物急剧减少到只有 7 种，鉴于需求不断增加和压力不断变化，这种情况是不安全的。该项目将引入一个新的计算框架，扩展和扩展最新的网络研究技术，以统一数字农业的不同方法，旨在提高粮食系统的生产力和安全性，同时推进农业生态系统计算建模的最先进水平大规模。 由于规模如此之大，我们将开发用于扩展网络验证的新技术，特别是在只有近似数据可用的情况下。 这项研究中开发的创新将适用于大规模网络验证、规划和配置。具体来说，该项目将引入一个包含精准农业和农业生态学的数字农业计算框架。该计算框架将使用基于网络验证的时空状态空间表示来对一块土地及其上的生物地球化学元素的无限可能配置进行分析、模拟和理解。这种方法能够考虑农业生态设计和管理系统，包括传统方法中很少考虑的作物和耕作系统的复杂混合物；它同时能够对以前难以理解的农业生态方法进行严格分析。这一新框架将为广阔的人类管理土地所面临的重大变化提供重要指导。 该项目将包括一个名为“农业生态转换函数”的概念状态空间框架和一个名为“计算农业生态学”的实用软件系统框架。除了简单地推进农业生态学理解之外，该项目还将通过探索状态空间探索（例如网络验证）来推进网络系统研究，其规模比以前大得多，并考虑新型传感和驱动网络系统的应用在复杂的物理环境中。 该框架将通过用于编程网络基础设施的新抽象来实例化，以探索传感和驱动方面的新工程技术，包括尚未物理实例化的人类实践和技术。 这项研究的成果将应用回网络系统研究的核心领域；具体来说，这项工作将通过将开发的状态空间框架改进近似和混叠，从而提高网络验证和综合的规模。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力优势进行评估，被认为值得支持以及更广泛的影响审查标准。