Doctoral Dissertation Improvement Award: Sustainable Agricultural Practices

该项目的目标是审查过去农业系统的可持续性以及这些活动对当地环境的长期影响。随着人口急剧增加，社会又在努力增加粮食产量，简单地扩大现有农业系统将不足以满足需求。有必要研究旨在实现长期持久性和恢复力的替代方案。这不仅包括技术创新，还包括导致继续使用农业系统并导致可持续性的社会机制。很少有农业研究具有检验可持续性假设所需的时间深度，但这对于负责任的农业景观管理至关重要。考古学非常适合通过研究一个系统的整个生命周期来解决这些问题，并有能力观察农业成功和失败的具体实例。过去的人类找到了培育多种不同景观的方法，随着干旱和土壤质量的下降减少了可用的肥沃土地的数量，这种知识将变得越来越重要。该项目将调查围绕非传统农业系统建设和种植的环境和社会条件。将通过审查导致过去农业成功或失败的具体当地条件，重点放在这些方法用于现代实施的可行性上。将研究一个长期的史前系统。通过将土壤分析、地下地球物理和遥感相结合，这一数据集将允许对这些古老的农业系统进行多尺度分析。这些数据将被用来确定创建凸起田地的动机，它们是由当地管理的还是通过州一级组织管理的，以及这些景观修改如何影响土壤的长期性质。这项研究的目的是区分代表古代人类活动的土壤条件与最近的过程，这是考古学研究中需要的区别。本文所使用的多传感器地球物理方法的集成具有推动遥感方法发展的潜力，并提出了一种用于农业应用的低成本热成像的新方法。这一数据集将有助于了解干旱沿海环境中的粮食安全知识，并有助于理解未来如何有效地培育类似的环境。这一奖项反映了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。

The goal of this project is to examine the sustainability of past agricultural systems and the long-term impacts of these activities on the local environment. As population drastically increases and societies struggle to increase food production in turn, simply expanding existing agriculture systems will not be enough to meet demands. It is necessary to investigate alternative options that are designed for long-term persistence and resilience. This includes not only technological innovation, but the social mechanisms that cause the continued use of agricultural systems, leading to sustainability. Few agricultural studies have the time-depth necessary to test assumptions of sustainability, yet this is essential to the responsible management of agricultural landscapes. Archaeology is uniquely well-suited to addressing these questions through study of the entire lifespan of a system, and the ability to look at specific instances of agricultural success and failure. Past humans found ways to cultivate many diverse landscapes, and this knowledge will be increasingly vital as aridification and waning soil quality decrease the amount of available fertile land. This project will investigate the environmental and social conditions surrounding the construction and cultivation of non-traditional agricultural systems. Focus will be placed on the feasibility of these approaches for modern implementation by examining specific local conditions that contributed to past agricultural success or failure. One long term prehistoric system will be studied. Through the integration of soil analyses, subsurface geophysics, and remote sensing, this dataset will allow for multiscalar analyses of these ancient agricultural systems. This data will be used to determine what motivated the creation of raised fields, whether they were managed locally or through state-level organization, and how these landscape modifications affected long-term soil properties. This research is designed to differentiate soil conditions that represent ancient human activity from recent processes, a distinction needed in archaeological studies. The integration of multi-sensor geophysical methods used here has the potential to advance remote sensing approaches, and a new method of low-cost thermal imagery for agricultural applications is proposed. This dataset will contribute to knowledge of food security in arid coastal environments and help to understand how similar environments can be effectively cultivated in the future.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.