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 计划中的科学技术卓越研究中心 - 博士后研究奖学金 (CREST-PRF) 项目为具有巨大潜力的 CREST 中心研究人员提供支持，并为他们提供培训和研究经验，从而拓宽视野，促进跨学科互动，并使他们在科学界占据领导地位。 该 CREST-PRF 项目与新墨西哥大学 CREST 水与环境中心 (CWE) 的研究重点一致。本研究的目的是测量干旱河流系统初级生产和生态系统呼吸的时间和空间变异程度。干旱地区的河流在河边有特征性的初级生产区（即浴盆环），为消费生物体提供大量食物来源。然而，当应用通用方法进行全系统代谢时，这些系统的代谢可能被低估。 将空间变化纳入代谢模型将为量化总初级生产（GPP）和生态系统呼吸（ER）的方法以及理解代谢驱动因素提供新的见解。以下目标侧重于新墨西哥州格兰德河中部 9 公里的研究范围： 目标 1 是确定总初级生产和生态系统呼吸的空间和时间变异性；目标 2 是比较用于量化代谢的方法；目标3探讨流量变化对生物生产力区的影响。获得的知识可以转移到其他河流系统，并可以用作向管理者通报环境流量的工具，这些流量对于恢复水生栖息地、生态系统功能和濒危物种的生存最有效。旱地河流，包括干旱地区的河流，是新陈代谢领域研究较少的系统；然而，它们是在气候条件变化方面最脆弱的系统。关于干旱地区河流网络代谢率的时空信息可以纳入政府间气候变化专门委员会分析​​的区域和全球碳预算的估计中。全系统代谢的常用方法假设 GPP 和 ER 的估计值代表整个范围。然而，干旱地区河流的河流代谢并不均匀，并且在空间上存在差异。该研究项目分析的空间和时间复杂性水平将增进多尺度碳过程控制的基础知识。该项目集成了多个实体收集的长期、高分辨率环境数据的多个来源，并利用强大的计算资源来处理大数据。这项研究采用整体方法，将有助于对干旱地区河流的生产力及其在区域碳预算中的作用的基本了解。此外，该研究地点与工程化的河流系统密切相关，这些系统正在经历水流的减少和改变以及随后的水质退化和下游营养物污染。建模方法和结果将可应用于大型河流系统。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。