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.

最近关于网络核查的工作必须同时处理以复杂方式相互作用的硬件和软件要素组成的大型网络的异质性，以及为了在网络规划和管理中实际使用而进行规模核查和综合。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80年里，这种作物的数量急剧减少，只有7种作物产生了全球80%的卡路里，考虑到不断增加的需求和不断变化的压力，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，以统一不同的数字农业方法，目的是在提高粮食系统的生产率和安全性的同时，促进大规模计算模拟农业生态系统的最新水平。作为这种大规模的结果，我们将开发新的技术来扩展网络验证，特别是在只有大致数据可用的情况下。本研究开发的创新成果将应用于大规模的网络验证、规划和供应。具体地说，该项目将引入一个涵盖精准农业和农业生态的数字农业计算框架。这一计算框架将使用一块土地及其上的生物地球化学元素的无限可能配置的基于网络验证的时空状态空间表示来进行农业生态系统的分析、模拟和理解。这一方法使人们能够考虑农业生态设计和管理系统，包括在常规方法中很少考虑的作物和种植制度的复杂混合；它同时使以前难以捉摸的农业生态方法得到严格分析。这一新框架将为人类管理的广大土地所面临的重大变化提供必要的指导。该项目将包括一个被称为农业生态转换功能的概念性状态空间框架和一个被称为计算农业生态学的实用软件系统框架。除了简单地促进对农业生态的理解，该项目还将通过探索状态空间探索，例如在网络验证中，在比以前更大的规模上推进网络系统研究，并通过这样做考虑在复杂物理环境中应用新型网络传感和驱动系统。这一框架将通过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化技术，包括尚未具有物理实例化的人类实践和技术。这项研究的成果将应用于网络系统研究的核心领域；具体地说，这项工作将通过将开发的状态空间框架在近似和混叠方面的改进来改进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和更广泛的影响审查标准进行评估，被认为值得支持。