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

CREST项目中的科学和技术卓越研究中心-博士后研究奖学金(CREST-PRF)轨道为CREST中心具有巨大潜力的初学者提供支持，并为他们提供培训和研究经验，这些培训和研究经验将拓宽视野，促进跨学科互动，并使他们在科学界处于领导地位。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。这项研究的目的是测量旱地河流系统初级生产力和生态系统呼吸的时间和空间变异程度。旱地河流在河流边缘具有初级生产区的特点(即浴缸环)，为消费者生物体提供了大量的食物来源。然而，当应用常见的全系统新陈代谢方法时，这些系统的新陈代谢可能被低估了。解决代谢模型中的空间差异将为量化总初级生产力(GPP)和生态系统呼吸(ER)的方法提供新的见解，并理解新陈代谢的驱动因素。以下目标侧重于新墨西哥州里奥格兰德河中部9公里的研究范围：目标1是确定初级生产总值和生态系统呼吸的空间和时间变异性；目标2是比较用于量化新陈代谢的方法；目标3是探讨流量变化对生物生产力区域的影响。所获得的知识可转移到其他河流系统，并可用作向管理人员通报在恢复水生生境、生态系统功能和濒危物种生存方面最有效的环境流动的工具。包括旱地河流在内的旱地河流是新陈代谢领域中研究较少的系统；然而，在气候条件变化方面，它们是最脆弱的系统。关于旱地河流网络代谢率的时空信息可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估计数。全系统新陈代谢的常用方法假定GPP和ER的估计值代表整个河段。然而，干旱区河流的河流代谢并不是均匀的，而且在空间上是不同的。本研究项目分析的空间和时间复杂性水平将促进在多个尺度上控制碳过程的基础知识的发展。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。从整体上看，这项研究将有助于基本了解干旱区河流的生产力及其在区域碳预算中的作用。此外，这一研究地点与工程河流系统密切相关，这些河流系统正在经历河流流量的减少和改变，以及随后的水质退化和下游营养物质污染。建模方法和结果将适用于大型河流系统。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 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.