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At least 397 records · Page 22

Evaluating Cloud Computing in the Proposed NASA DESDynI Ground Data System

The proposed NASA Deformation, Ecosystem Structure and Dynamics of Ice (DESDynI) mission would be a first-of-breed endeavor that would fundamentally change the paradigm by which Earth Science data systems at NASA are built. DESDynI is evaluating a distributed architecture where expert science nodes around the country all engage in some form of mission processing and data archiving. This is compared to the traditional NASA Earth Science missions where the science processing is typically centralized. What's more, DESDynI is poised to profoundly increase the amount of data collection and processing well into the 5 terabyte/day and tens of thousands of job range, both of which comprise a tremendous challenge to DESDynI's proposed distributed data system architecture. In this paper, we report on a set of architectural trade studies and benchmarks meant to inform the DESDynI mission and the broader community of the impacts of these unprecedented requirements. In particular, we evaluate the benefits of cloud computing and its integration with our existing NASA ground data system software called Apache Object Oriented Data Technology (OODT). The preliminary conclusions of our study suggest that the use of the cloud and OODT together synergistically form an effective, efficient and extensible combination that could meet the challenges of NASA science missions requiring DESDynI-like data collection and processing volumes at reduced costs.

Benchmark↗

AmeriFlux FLUXNET-1F US-CMW Charleston Mesquite Woodland

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-CMW Charleston Mesquite Woodland. This is the FLUXNET version of the carbon flux data for the site US-CMW Charleston Mesquite Woodland produced by applying the standard ONEFlux (1F) software. Site Description - Site is a riparian mesquite woodland located along an old alluvial terrace along the banks of the San Pedro River in southeastern Arizona. Site climate is semiarid with monsoonal (Jul-Sep) rainfall. The mesquite trees access groundwater from an alluvial aquifer recharged elsewhere. Site water balance is not closed and ET greatly exceeds precipitation. The understory grasses and forbs are rainfall dependent. This groundwater-dependent ecosystem is far more ebulliant and productive than the upland vegetation around it (shrublands and grasslands).

Scott, Russell [USDA-ARS]↗

Reekeekee- and roodoodooviruses, two different Microviridae clades constituted by the smallest DNA phages

Small circular single-stranded DNA viruses of the Microviridae family are both prevalent and diverse in all ecosystems. They usually harbor a genome between 4.3 and 6.3 kb, with a microvirus recently isolated from a marine Alphaproteobacteria being the smallest known genome of a DNA phage (4.248 kb). A subfamily, Amoyvirinae, has been proposed to classify this virus and other related small Alphaproteobacteria-infecting phages. Here, we report the discovery, in meta-omics data sets from various aquatic ecosystems, of sixteen complete microvirus genomes significantly smaller (2.991–3.692 kb) than known ones. Phylogenetic analysis reveals that these sixteen genomes represent two related, yet distinct and diverse, novel groups of microviruses—amoyviruses being their closest known relatives. We propose that these small microviruses are members of two tentatively named subfamilies Reekeekeevirinae and Roodoodoovirinae. As known microvirus genomes encode many overlapping and overprinted genes that are not identified by gene prediction software, we developed a new methodology to identify all genes based on protein conservation, amino acid composition, and selection pressure estimations. Surprisingly, only four to five genes could be identified per genome, with the number of overprinted genes lower than that in phiX174. These small genomes thus tend to have both a lower number of genes and a shorter length for each gene, leaving no place for variable gene regions that could harbor overprinted genes. Even more surprisingly, these two Microviridae groups had specific and different gene content, and major differences in their conserved protein sequences, highlighting that these two related groups of small genome microviruses use very different strategies to fulfill their lifecycle with such a small number of genes. The discovery of these genomes and the detailed prediction and annotation of their genome content expand our understanding of ssDNA phages in nature and are further evidence that these viruses have explored a wide range of possibilities during their long evolution.

59 BASIC BIOLOGICAL SCIENCES↗

Three-dimensional modeling of hyphal fusion, branching, and nutrient transport in filamentous fungi

Fungi exhibit behaviors distinct from other microbes. Filamentous fungi grow by extending complex networks of branched filaments collectively referred to as the mycelium. These networks can expand over large distances and traverse low-nutrient areas by translocating nutrients through the filament network. This spatial characteristic makes filamentous fungi crucial for soil ecosystems, supporting stable microbial communities and promoting plant growth. However, simulating these behaviors is complex. The elongated nature of fungal compartments results in different mechanical interactions compared to the commonly modeled spherical bacteria. These detailed hyphal mechanics require specialized consideration and are often excluded from conventional fungal simulation packages. Additionally, the extensive fungal networks in nature demand computationally intensive simulations, necessitating high-performance algorithms. Therefore, realistic fungi simulations require specialized software. Here, we introduce a fungal modeling expansion to the high-performance biological modelling and interface exchange (bmx) software suite. bmx leverages adaptive mesh refinement in AMReX for chemical diffusion and incorporates a full mechanical model for bacterial cells, accelerated by GPUs. By extending bmx to model filamentous particles, we demonstrate the formation of complex filament networks through interactions like hyphal branching and fusion (anastomosis). We show that the networks produced match real-world fungal structures through various metrics. This work supports computational studies of fungal growth dynamics and can be adapted to investigate the growth of other filamentous structures in biology or materials science. The expanded-BMX package is open-sourced and is available online.

Cell mechanics↗

Development of the IES Plug-and-Play Framework

This report discusses the status of the flexible plug-and-play framework development currently ongoing that aims to integrate Modelica/Dymola with the Risk Analysis and Virtual ENvironment (RAVEN) software in terms of both Functional Mock-Up Interface (FMI)/Functional Mock-Up Unit (FMU) construction and repository structures that aim to ease the sharing and simulation of complex dynamic models. This report aims to provide an overview of all the performed activities resolving around the deployment of methods, software infrastructures, guidelines and workflow for the construction and usage of models, encapsulated using the FMI/FMU protocols and standards. In particular, the report is organized in three main macro-subjects, which are connected to each other: - FMI/FMU adaptors for modelica models - HYBRID repository new structure and open-source deployment - RAVEN FMI/FMU exporting capabilities and Artificial Intelligence (AI)-based analysis acceleration. The first part of the report discusses the FMI/FMU adaptors that have been created within the HYBRID repository to allow users to quickly export models, such as FMUs. Several examples are shown that highlight the step-by-step process of converting an existing Modelica model into an FMU for use within the Dymola platform. Simulation results demonstrate that, while minor differences may occur, the overall control, trends, and solution integrity are maintained between standard Modelica simulation and FMU simulation results. However, it is worth noting that, for small systems, the FMU results have a slower simulation time than the Modelica only simulation. Using this process, a company can provide models that contain proprietary information to entities without disclosing any of the information about the model that could be considered business sensitive. Such an ability would allow institutions to bypass the necessity of “whitewashing” data. In the second part of the report, the new structure of the HYBRID repository is discussed with a major focus on the series of updates that has been completed. These updates include the addition of Modelica system-level regression tests and software quality assurance documentation that ensure that modifications to the Modelica models do not alter system-level model results. The third and final part of the report aims to report the work that has been performed for the deployment of methods and workflows for the construction of RAVEN AI-based models compliant with the FMI/FMU standard. Such development represents the key for the deployment of the concept of “Flexible ecosystem” since it allows for the replacement of high-fidelity modelica models (or any other FMI/FMU compliant model) with RAVEN generated AI surrogate models. Overall, extensive work has been completed on developing FMUs and FMIs from existing models, understanding the requirements and limitations of FMUs, and open-sourcing the HYBRID repository with an integrated regression system.

42 ENGINEERING↗

Development of the IES Plug-and-Play Framework

This report discusses the status of the flexible plug-and-play framework development currently ongoing that aims to integrate Modelica/Dymola with the Risk Analysis and Virtual ENvironment (RAVEN) software in terms of both Functional Mock-Up Interface (FMI)/Functional Mock-Up Unit (FMU) construction and repository structures that aim to ease the sharing and simulation of complex dynamic models. This report aims to provide an overview of all the performed activities resolving around the deployment of methods, software infrastructures, guidelines and workflow for the construction and usage of models, encapsulated using the FMI/FMU protocols and standards. In particular, the report is organized in three main macro-subjects, which are connected to each other: - FMI/FMU adaptors for modelica models - HYBRID repository new structure and open-source deployment - RAVEN FMI/FMU exporting capabilities and Artificial Intelligence (AI)-based analysis acceleration. The first part of the report discusses the FMI/FMU adaptors that have been created within the HYBRID repository to allow users to quickly export models, such as FMUs. Several examples are shown that highlight the step-by-step process of converting an existing Modelica model into an FMU for use within the Dymola platform. Simulation results demonstrate that, while minor differences may occur, the overall control, trends, and solution integrity are maintained between standard Modelica simulation and FMU simulation results. However, it is worth noting that, for small systems, the FMU results have a slower simulation time than the Modelica only simulation. Using this process, a company can provide models that contain proprietary information to entities without disclosing any of the information about the model that could be considered business sensitive. Such an ability would allow institutions to bypass the necessity of “whitewashing” data. In the second part of the report, the new structure of the HYBRID repository is discussed with a major focus on the series of updates that has been completed. These updates include the addition of Modelica system-level regression tests and software quality assurance documentation that ensure that modifications to the Modelica models do not alter system-level model results. The third and final part of the report aims to report the work that has been performed for the deployment of methods and workflows for the construction of RAVEN AI-based models compliant with the FMI/FMU standard. Such development represents the key for the deployment of the concept of “Flexible ecosystem” since it allows for the replacement of high-fidelity modelica models (or any other FMI/FMU compliant model) with RAVEN generated AI surrogate models. Overall, extensive work has been completed on developing FMUs and FMIs from existing models, understanding the requirements and limitations of FMUs, and open-sourcing the HYBRID repository with an integrated regression system.

14 SOLAR ENERGY↗

The Importance of Freeze/Thaw Cycles on Lateral Transport in Ice-Wedge Polygons: Modeling Archive

This Modeling Archive is in support of an NGEE Arctic publication "The importance of freeze/thaw cycles on lateral transport in ice-wedge polygons". The dataset includes xml input/configuration files. These files are compatible with the ATS version 1.0 and higher. The mesh folder contains mesh files used for high-centered polygon (hcp) and low-centered polygon (lcp). The mesh files represent the transect of the polygonal tundra (Fig 1). Here we used two types of mesh with impermeable layer and without. The mesh with an impermeable layer corresponds to the synthetic permafrost (no freezeup case). The freeze up case uses mesh without impermeable layer to simulated frozen ground start at the same depth where the impermeable layer is for the no freezeup case. The meteorological data used drive the model saved in the "inputs" folder. The processed tracer flow rates are saved in the "tracer-flow-ratesCfolder. To plot figures 1 and 2, we used VisIt software. To plot all the flow rates, we used ipython notebook script. All required inputs are saved in "freezeup" and "no freezeup" folders. Each folder includes the corresponding "lcp" and "hcp" folders. The "freezeup" folder has also flat-centered polygon (fcp) case, low porosity "lpor", and low permeability "lper" cases. Included are *.xml, *.exo, *.h5, *pdf, *.ipynb, *.sh, *.py, and *.out files. NGEE Arctic Project Summary: The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

AmeriFlux FLUXNET-1F US-xKZ NEON Konza Prairie Biological Station (KONZ)

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-xKZ NEON Konza Prairie Biological Station (KONZ). This is the FLUXNET version of the carbon flux data for the site US-xKZ NEON Konza Prairie Biological Station (KONZ) produced by applying the standard ONEFlux (1F) software. Site Description - Konza Prairie Biological Station (KPBS) was established to provide a "natural laboratory" to conduct ecological research and is located on a 3,487 hectare native tallgrass prairie preserve. KPBS is a field research station dedicated to conservation, education and long-term ecological research. Over 1,580 scientific papers have been published by scientists conducting studies at KPBS. The study of ecological patterns and processes in native tallgrass prairie ecosystems is the primary subject of research.

Network), NEON (National Ecological Observatory↗

AmeriFlux FLUXNET-1F US-LS2 San Pedro River Lewis Springs Savanna

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-LS2 San Pedro River Lewis Springs Savanna. This is the FLUXNET version of the carbon flux data for the site US-LS2 San Pedro River Lewis Springs Savanna produced by applying the standard ONEFlux (1F) software. Site Description - A riparian savanna located on an old alluvial terrace about 0.5 km from the banks of the entrenched San Pedro River in southeastern Arizona USA. Site climate is semiarid with monsoonal (Jul-Sep) rainfall. The trees access groundwater (depth of ~7 m)from an alluvial aquifer recharged elsewhere. Therefore, site water balance is not closed and ET greatly exceeds precipitation. The perennial bunchgrasses use primarily rainfall. This groundwater-using ecosystem is far more ebulliant and productive than the upland vegetation around it (shrublands and grasslands) outside of the San Pedro River corridor.

Scott, Russell↗

Dataset for Cruz-O'Byrne et al (2026): "Divergent biogeochemical responses in upland coastal forest soils to repeated flooding and shifts in water chemistry"

Hydrologic disturbances from accelerated sea-level rise and the increasing frequency and intensity of storms and tidal flooding are altering biogeochemical processes in upland coastal forests, transforming these ecosystems into wetlands. However, the initial effects of flooding on belowground biogeochemistry and the mechanisms driving greenhouse gas dynamics and soil organic matter stability during the early stages of this transition remain poorly understood. This dataset presents the results of a mesocosm experiment conducted in a controlled, highly instrumented laboratory environment, in which freshwater and brackish water pulses were applied to intact soil monoliths from a temperate upland coastal forest to examine how floodwater chemistry influences soil biogeochemistry and organo-mineral interactions. All data files are plain-text CSV (comma-separated value), and no special software is required to read them. Details about the content of each file are available in the document “Dataset_readme”. The dataset consists of the following data: • rcruzobyrne_moisture: Soil volumetric water content (VWC) • rcruzobyrne_GHG: Headspace greenhouse gas (GHG) concentration and fluxes • rcruzobyrne_methane_isotopes: Headspace methane isotope signature • rcruzobyrne_porewater: Porewater chemistry • rcruzobyrne_CDOM: Porewater colored dissolved organic matter (CDOM) • rcruzobyrne_FTIR: Soil Fourier-transform infrared (FTIR) spectroscopy Details of the experimental setup, data collection, and data analysis are provided in the manuscript by Cruz-O’Byrne et al (2026) Divergent biogeochemical responses in upland coastal forest soils to repeated flooding and shifts in water chemistry. Biogeochemistry. https://doi.org/10.1007/s10533-026-01340-0

EARTH SCIENCE > ATMOSPHERE > GREENHOUSE GAS↗

Tropical Tree Species Identity and Diameter at Breast Height in a Throughfall-Reduction Drying Experiment in Four Lowland Panamanian Forests

Objectives: Climatic drying is predicted for many tropical forests, yet effects on soil properties across moisture and soil gradients within tropical forests remain poorly characterized, hampering predictions of forest-climate feedbacks. We hypothesized that drying would suppress soil CO2 fluxes (i.e., respiration) in already-drier tropical forests by further reductions in soil moisture, but increases CO2 fluxes in wetter tropical forests by alleviating anaerobiosis and soil saturation. We measured soil CO2 fluxes, soil moisture, soil temperature, and forest floor biomass during wet-dry cycles (2015 – 2022) in four Panamanian forests that vary in rainfall and soil fertility. We also surveyed all tree species and identified to species in 2018 and 2019.Results: We found that soil moisture peaked in the wet season and declined in the dry season. Measured soil CO2 fluxes declined in the dry season and peaked in the early wet season ahead of peak soil moisture, resulting in a lower soil moisture optimum for respiration than previously modeled. Chronic throughfall exclusion also suppressed soil moisture across the four forests to 20cm depths, and also initially suppressed soil CO2 fluxes across forests. There was sustained suppression of soil CO2 fluxes after four years in the wettest forest only (-28 ± 4% during the dry season), but elevated soil CO2 fluxes in a fertile forest after four years (+75 ± 28% during the late wet season). The unexpected negative drying effect in the wettest, most infertile forest could have resulted from reduced vertical flushing of nutrients into soils, as the drying effect increased with time. Including hydro-nutrient interactions in ecosystem models could improve predictions of tropical forest-climate feedbacks (results presented in Cusack et al. 2023). Datasets included: Datasets included here include .csv and .xls files for tree species identity and diameter at breast height (dbh) in the study plots. There is also a .kml file that includes coordinates for all 32 plots included in the study of four forests (n = 4 throughfall reduction and n = 4 control plots per site). No special software is needed to open these files.

54 ENVIRONMENTAL SCIENCES↗

Carbon dioxide, water vapor and methane soil efflux (soil respiration) in a Pinus palustris root exclusion in Georgetown, SC

This dataset contains processed data from a combination of survey flux chambers and long-term automated flux chambers. Soil flux measurements were conducted from June 2023 through December 2025 in a mature longleaf pine forest in Georgetown, SC. Soil respiration measurements were conducted approximately biweekly for two and a half years, before and after a root exclusion that took place on May 5, 2024. Processed, QAQC’d data for the treatment (root exclusion) and control (roots intact) before and after the root exclusion can be found in the file: 1_DATA_ESS_DOE_HR_RS_HB2_QAQC_Survey_Data_20260223.csv. Two multiday deployments were also conducted prior to the root exclusion using long-term automated chambers to continuously monitor greenhouse gas soil efflux. Processed, QAQC’d data for both long-term deployments can be found in the file: 2_DATA_ESS_DOE_HR_RS_HB2_QAQC_Longterm_Data_20260209.csv. Raw and working data files (.json, .81x, & .82z format) from LI-COR equipment are included for reference and can be accessed using SoilFluxPro software. CSV metadata files describe the raw data and modifications made using SoilFluxPro v5 and Matlab R2024b, as well as formatting and units for processed CSVs. Matlab code is included for reading in the processed CSVs, with sample figures comparing treatment and control. This research was performed as part of the project: “Improving models of stand and watershed carbon and water fluxes with more accurate representations of soil-plant-water dynamics in southern pine ecosystems”, which examines in part the effects hydraulic redistribution on soil efflux of carbon dioxide, water vapor and methane, as well as soil moisture and temperature in a southern pine ecosystem with sandy soils and high water table.

CARBON DIOXIDE FLUX↗

THE NEW ONLINE METADATA EDITOR FOR GENERATING STRUCTURED METADATA

Nobody is better suited to “describe” data than the scientist who created it. This “description” about a data is called Metadata. In general terms, Metadata represents the who, what, when, where, why and how of the dataset [1]. eXtensible Markup Language (XML) is the preferred output format for metadata, as it makes it portable and, more importantly, suitable for system discoverability. The newly developed ORNL Metadata Editor (OME) is a Web-based tool that allows users to create and maintain XML files containing key information, or metadata, about the research. Metadata include information about the specific projects, parameters, time periods, and locations associated with the data. Such information helps put the research findings in context. In addition, the metadata produced using OME will allow other researchers to find these data via Metadata clearinghouses like Mercury [2][4]. OME is part of ORNL’s Mercury software fleet [2][3]. It was jointly developed to support projects funded by the United States Geological Survey (USGS), U.S. Department of Energy (DOE), National Aeronautics and Space Administration (NASA) and National Oceanic and Atmospheric Administration (NOAA). OME’s architecture provides a customizable interface to support project-specific requirements. Using this new architecture, the ORNL team developed OME instances for USGS’s Core Science Analytics, Synthesis, and Libraries (CSAS&L), DOE’s Next Generation Ecosystem Experiments (NGEE) and Atmospheric Radiation Measurement (ARM) Program, and the international Surface Ocean Carbon Dioxide ATlas (SOCAT).Researchers simply use the ORNL Metadata Editor to enter relevant metadata into a Web-based form. From the information on the form, the Metadata Editor can create an XML file on the server that the editor is installed or to the user’s personal computer. Researchers can also use the ORNL Metadata Editor to modify existing XML metadata files.As an example, an NGEE Arctic scientist use OME to register their datasets to the NGEE data archive and allows the NGEE archive to publish these datasets via a data search portal (http://ngee.ornl.gov/data). These highly descriptive metadata created using OME allows the Archive to enable advanced data search options using keyword, geo-spatial, temporal and ontology filters. Similarly, ARM OME allows scientists or principal investigators (PIs) to submit their data products to the ARM data archive.How would OME help Big Data Centers like the Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC)?The ORNL DAAC is one of NASA’s Earth Observing System Data and Information System (EOSDIS) data centers managed by the Earth Science Data and Information System (ESDIS) Project. The ORNL DAAC archives data produced by NASA's Terrestrial Ecology Program. The DAAC provides data and information relevant to biogeochemical dynamics, ecological data, and environmental processes, critical for understanding the dynamics relating to the biological, geological, and chemical components of the Earth's environment. Typically data produced, archived and analyzed is at a scale of multiple petabytes, which makes the discoverability of the data very challenging. Without proper metadata associated with the data, it is difficult to find the data you are looking for and equally difficult to use and understand the data.OME will allow data centers like the NGEE and ORNL DAAC to produce meaningful, high quality, standards-based, descriptive information about their data products in-turn helping with the data discoverability and interoperability. Useful Links:USGS OME: http://mercury.ornl.gov/OME/NGEE OME: http://ngee-arctic.ornl.gov/ngeemetadata/ARM OME: http://archive2.ornl.gov/armome/Contact: Ranjeet Devarakonda (devarakondar@ornl.gov)References:[1] Federal Geographic Data Committee. Content standard for digital geospatial metadata. Federal Geographic Data Committee, 1998.[2] Devarakonda, Ranjeet, et al. "Mercury: reusable metadata management, data discovery and access system." Earth Science Informatics 3.1-2 (2010): 87-94.[3] Wilson, B. E., Palanisamy, G., Devarakonda, R., Rhyne, B. T., Lindsley, C., & Green, J. (2010). Mercury Toolset for Spatiotemporal Metadata.[4] Pouchard, L. C., Branstetter, M. L., Cook, R. B., Devarakonda, R., Green, J., Palanisamy, G., ... & Noy, N. F. (2013). A Linked Science investigation: enhancing climate change data discovery with semantic technologies. Earth science informatics, 6(3), 175-185.

FGDC CSDGM↗

The 1984 NASA/ASEE summer faculty fellowship program

The assessment of forest productivity and associated nitrogen flux in a number of conifer ecosystems is described. As a base line study of acid precipitation in the Sierra Nevada, involved is the extraction and integration of a number of data planes describing the terrain, soils, lithology, vegetation cover and structure, and microclimate of the region. The development of automated techniques to extract topographic networks (stream canyons and ridge lines) for use as a landscrape skeleton to organize and integrate data sets into an efficient geographical information system is examined. The software is written in both FORTRAN and C, and is portable to a number of different computer environments with minimal modification.

Source record↗

AmeriFlux FLUXNET-1F US-LS1 San Pedro River Lewis Springs Sacaton Grassland

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-LS1 San Pedro River Lewis Springs Sacaton Grassland. This is the FLUXNET version of the carbon flux data for the site US-LS1 San Pedro River Lewis Springs Sacaton Grassland produced by applying the standard ONEFlux (1F) software. Site Description - This is a riparian grassland located along an old alluvial terrace along the banks of the entrenched San Pedro River in southeastern Arizona. Site climate is semiarid with monsoonal (Jul-Sep) rainfall. The grasses access groundwater (depth of 2-4 m)from an alluvial aquifer recharged elsewhere. Site water balance is not closed and ET greatly exceeds precipitation. The perennial bunchgrasses use both rainfall, groundwater and occasional flood water. This groundwater-using ecosystem is far more ebulliant and productive than the upland vegetation around it (shrublands and grasslands) outside of the San Pedro River corridor.

Scott, Russell [USDA-ARS]↗

A comprehensive data acquisition and management system for an ecosystem-scale peatland warming and elevated CO 2 experiment

Ecosystem-scale manipulation experiments represent large science investments that require well-designed data acquisition and management systems to provide reliable, accurate information to project participants and third party users. The SPRUCE project (Spruce and Peatland Responses Under Climatic and Environmental Change, http://mnspruce.ornl.gov ) is such an experiment funded by the Department of Energy's (DOE), Office of Science, Terrestrial Ecosystem Science (TES) Program. The SPRUCE experimental mission is to assess ecosystem-level biological responses of vulnerable, high carbon terrestrial ecosystems to a range of climate warming manipulations and an elevated CO 2 atmosphere. SPRUCE provides a platform for testing mechanisms controlling the vulnerability of organisms, biogeochemical processes, and ecosystems to climatic change (e.g., thresholds for organism decline or mortality, limitations to regeneration, biogeochemical limitations to productivity, and the cycling and release of CO 2 and CH 4 to the atmosphere). The SPRUCE experiment will generate a wide range of continuous and discrete measurements. In order to successfully manage SPRUCE data collection, achieve SPRUCE science objectives, and support broader climate change research, the research staff has designed a flexible data system using proven network technologies and software components. The primary SPRUCE data system components are the following; 1. data acquisition and control system – set of hardware and software to retrieve biological and engineering data from sensors, collect sensor status information, and distribute feedback to control components; 2. data collection system – set of hardware and software to deliver data to a central depository for storage and further processing; and 3. data management plan – set of plans, policies, and practices to control consistency, protect data integrity, and deliver data. This publication presents our approach to meeting the challenges of designing and constructing an efficient data system for managing high volume sources of in situ observations in a remote, harsh environmental location. Finally, the approach covers data flow starting from the sensors and ending at the archival/distribution points, discusses types of hardware and software used, examines design considerations that were used to choose them, and describes the data management practices chosen to control and enhance the value of the data.

54 ENVIRONMENTAL SCIENCES↗

AmeriFlux FLUXNET-1F CA-NS1 UCI-1850 burn site

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site CA-NS1 UCI-1850 burn site. This is the FLUXNET version of the carbon flux data for the site CA-NS1 UCI-1850 burn site produced by applying the standard ONEFlux (1F) software. Site Description - The UCI-1850 site is located in a continental boreal forest, dominated by black spruce trees, within the BOREAS northern study area in central Manitoba, Canada. The site is a member of a chronological series of sites that are representative secondary succession growth stages after large stand replacement fires. Black spruce trees undergo a slow growth process enabling the accurate determination of the chronosequence of stand age disturbance. Additionally, boreal forests make up approximately 25% of forest ecosystems on earth. With both of these in mind, the UCI sites provide an excellent location to study the CO2 exchange between the atmosphere and boreal forest ecosystems as a function of sequential wildfires.

Goulden, Mike↗

AmeriFlux FLUXNET-1F CA-NS2 UCI-1930 burn site

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site CA-NS2 UCI-1930 burn site. This is the FLUXNET version of the carbon flux data for the site CA-NS2 UCI-1930 burn site produced by applying the standard ONEFlux (1F) software. Site Description - The UCI-1930 site is located in a continental boreal forest, dominated by black spruce trees, within the BOREAS northern study area in central Manitoba, Canada. The site is a member of a chronological series of sites that are representative secondary succession growth stages after large stand replacement fires. Black spruce trees undergo a slow growth process enabling the accurate determination of the chronosequence of stand age disturbance. Additionally, boreal forests make up approximately 25% of forest ecosystems on earth. With both of these in mind, the UCI sites provide an excellent location to study the CO2 exchange between the atmosphere and boreal forest ecosystems as a function of sequential wildfires.

Goulden, Mike↗