CREST-PRF: Identifying Zones of Biological Activity Using a Spatially Distributed Metabolism Model in an Aridland River

CREST-PRF：使用干旱河中的空间分布代谢模型识别生物活动区域

• 批准号: 1914778
• 负责人: Betsy Summers
• 金额: $ 20万
• 依托单位: Summers, Betsy Marie
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-01-15 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1914778&HistoricalAwards=false
• 关键词: CREST; PRF; Identifying; Zones; Biological

The Centers of Research Excellence in Science and Technology-Postdoctoral Research Fellowship (CREST-PRF) track within the CREST program supports beginning CREST Center investigators with significant potential and provides them with training and research experiences that will broaden perspectives, facilitate interdisciplinary interactions and establish them in positions of leadership within the scientific community. This CREST-PRF project is aligned with the research focus of the CREST Center for Water and the Environment (CWE) at the University of New Mexico. The goal of this research is to measure the extent of time and space variability in primary production and ecosystem respiration in an aridland river system. Aridland rivers have characteristic zones of primary production at the river edges (i.e., bathtub ring) that provides a substantial food source to consumer organisms. Yet, metabolism of these systems is likely underestimated when applying common methods for whole-system metabolism. Addressing space variation into metabolism models will offer new insight on methods for quantifying gross primary production (GPP) and ecosystem respiration (ER) and understanding of drivers of metabolism. The following objectives focus on a 9 km study reach in the middle Rio Grande, New Mexico: Objective 1 is to identify space and time variability of gross primary production and ecosystem respiration; Objective 2 is to compare methodology used to quantify metabolism; and Objective 3 is to explore the influence of changing discharge on the zone of biological productivity. The knowledge gained is transferrable to other river systems and can be used as a tool to inform managers on environmental flows that are most effective at restoring aquatic habitat, ecosystem function and survival of endangered species. Dryland rivers, which encompasses aridland rivers, are poorly studied systems in the field of metabolism; yet, are the most vulnerable systems regarding changing climate conditions. Spatiotemporal information learned about metabolic rates in an aridland river network can be integrated into estimates of regional and global carbon budgets analyzed by the Intergovernmental Panel on Climate Change. Common methods of whole-system metabolism assume estimates of GPP and ER are representative of the whole reach. However, stream metabolism is not homogeneous and varies spatially in aridland rivers. The level of spatial and temporal complexity analyzed in this research project will advance fundamental knowledge in controls on carbon processes at multiple scales. This project integrates multiple sources of longterm, high resolution environmental data collected by several entities and leverages robust computational resources to process big data. Taking a holistic approach, this research will contribute to the basic understanding of the productivity of aridland rivers and the role in regional carbon budgets. Moreover, this research site is germane to engineered river systems undergoing reductions and alterations of streamflow and subsequent degradation of water quality and nutrient pollution downstream. Modeling methods and results will be transferable to large river systems.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.

Crest计划中科学和技术研究卓越研究卓越研究中心轨道支持了具有巨大潜力的首发中心调查人员，并为他们提供了培训和研究经验，这些培训和研究经验将扩大观点，并促进跨学科的互动并建立它们并建立它们在科学界的领导地位。 这个Crest-PRF项目与新墨西哥大学的Crest Water与环境中心（CWE）的研究重点保持一致。这项研究的目的是衡量阿里德兰河系统中初级生产和生态系统呼吸的时间和空间变化的程度。阿里德兰河流在河边缘（即浴缸环）的主要生产区域，为消费生物提供了大量食物来源。然而，在将共同方法应用于全系统代谢时，这些系统的代谢可能会被低估。 解决新陈代谢模型中的空间变化将为量化大量生产（GPP）和生态系统呼吸（ER）的方法提供新的见解，并了解代谢驱动力的驱动因素。以下目标着重于新墨西哥州里奥格兰德市的9公里研究范围：目标1是确定总生产和生态系统呼吸的空间和时间变化；目标2是比较用于量化新陈代谢的方法。目标3是探索出排出对生物生产力区域的影响。获得的知识可转移到其他河流系统，可以用作工具，以告知管理人员有关恢复水生栖息地，生态系统功能和濒危物种生存最有效的环境流。包含阿里德兰河流的旱地河流在代谢领域的研究很少。然而，关于改变气候条件的最脆弱的系统是最脆弱的系统。关于在阿里德兰河网络中代谢率的时空信息可以集成到由政府间气候变化小组分析的区域和全球碳预算的估计中。全系统代谢的常见方法假设GPP和ER的估计值代表了整个覆盖范围。但是，流媒体的新陈代谢不是均匀的，在阿里德兰河流中的空间变化。该研究项目中分析的空间和时间复杂性水平将在多个尺度的碳过程控制方面提高基本知识。该项目集成了多个由多个实体收集的长期，高分辨率环境数据的来源，并利用强大的计算资源来处理大数据。采用一种整体方法，这项研究将有助于基本了解阿里德兰河的生产力以及在区域碳预算中的作用。此外，该研究地点对经过降低和变化的工程河流系统以及随后的水质和下游营养污染的降解。建模方法和结果将可以转移到大型河流系统中。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛影响的审查标准来评估值得支持的。