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

卓越研究中心在科学和技术博士后研究奖学金（CREST-PRF）的CREST计划内的轨道支持开始CREST中心研究人员具有显着的潜力，并为他们提供培训和研究经验，将拓宽视野，促进跨学科的互动，并建立他们在科学界的领导地位。 该CREST-PRF项目与新墨西哥州大学CREST水与环境中心（CWE）的研究重点保持一致。本研究的目的是测量干旱区河流系统初级生产力和生态系统呼吸的时空变异程度。干旱地区的河流在河流边缘具有典型的初级生产区（即，浴缸环），为消费生物体提供了大量的食物来源。然而，这些系统的代谢可能被低估时，适用于整个系统代谢的常见方法。 将空间变化纳入代谢模型将为量化总初级生产力（GPP）和生态系统呼吸（ER）以及理解代谢驱动因素的方法提供新的见解。以下目标集中在一个9公里的研究达到中格兰德河，新墨西哥州：目标1是确定总初级生产力和生态系统呼吸的空间和时间的变化;目标2是比较方法来量化代谢;和目标3是探索不断变化的流量对生物生产力区的影响。所获得的知识可转移到其他河流系统，并可作为一种工具，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量。旱地河流，包括干旱地区的河流，是代谢领域研究很少的系统;然而，是气候条件变化方面最脆弱的系统。在干旱地区的河流网络中了解到的代谢率的时空信息可以被整合到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的估计值代表整个河段。然而，河流代谢是不均匀的，在干旱地区的河流空间变化。本研究项目中分析的空间和时间复杂性水平将推进在多尺度上控制碳过程的基础知识。该项目整合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，这项研究将有助于对干旱区河流生产力及其在区域碳收支中的作用的基本认识。此外，这个研究地点是密切相关的工程河流系统正在减少和改变的径流和随后的水质退化和营养物污染下游。该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的知识价值和更广泛的影响审查标准进行评估来支持。

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.