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DOE OSTI2024

A functional microbiome catalogue crowdsourced from North American rivers

Predicting elemental cycles and maintaining water quality under increasing anthropogenic influence requires knowledge of the spatial drivers of river microbiomes. However, understanding of the core microbial processes governing river biogeochemistry is hindered by a lack of genome-resolved functional insights and sampling across multiple rivers. Here we used a community science effort to accelerate the sampling, sequencing and genome-resolved analyses of river microbiomes to create the Genome Resolved Open Watersheds database (GROWdb). GROWdb profiles the identity, distribution, function and expression of microbial genomes across river surface waters covering 90% of United States watersheds. Specifically, GROWdb encompasses microbial lineages from 27 phyla, including novel members from 10 families and 128 genera, and defines the core river microbiome at the genome level. GROWdb analyses coupled to extensive geospatial information reveals local and regional drivers of microbial community structuring, while also presenting foundational hypotheses about ecosystem function. Building on the previously conceived River Continuum Concept, we layer on microbial functional trait expression, which suggests that the structure and function of river microbiomes is predictable. We make GROWdb available through various collaborative cyberinfrastructures, so that it can be widely accessed across disciplines for watershed predictive modelling and microbiome-based management practices.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

Hydropower Infrastructure - LAkes, Reservoirs, and RIvers (HILARRI), v4

HILARRI is a database of links between major datasets of operational hydropower dams and powerplants, and inland water bodies. These connections are critical for conducting large-scale analysis of hydropower infrastructure and their associated natural and engineered water systems. Features include: – Dams from the National Inventory of Dams (2025) and the Global Reservoir and Dam Database (GRanD v1.3) – Hydropower plants from the Existing Hydropower Assets dataset (EHA 2025) – Power plants that are listed in the 2025 U.S. Hydropower Development Pipeline Data or were listed in previous versions of the dataset These hydropower infrastructure features are linked to several major datasets that provide hydrologic and hydraulic information relevant for analysis of hydropower systems that includes the integral water resources. That information comes from: – Products from the National Hydrography Dataset (NHD) – NHDPlusV2 Medium Resolution river network flowlines, – NHD waterbodies (limited to lakes and reservoirs), – NHD Watershed Boundary Dataset (HUC12-level for the Conterminous United States (CONUS)) – NHD High Resolution waterbodies – HydroLAKES water bodies (lakes and reservoirs) – LAGOS-US lakes and reservoirs – EPA National Lakes Assessment (2007, 2012, 2017, and 2022) – The Reservoir Sedimentation Database (RESSED) – EPA SuRGE sampling locations Unique identifiers are used to facilitate joining to the original full datasets. For example, characteristics of NHD flowlines such as estimated average flow rate can be joined from the NHDPlusV2 dataset to a dam or power plant listed in HILARRI based on the ID field, “COMID”, that is common to both datasets. HILARRI only includes basic information about identifiers, location, and data quality or usage notes. It does not contain the attributes or time series data associated with these sites. The HILARRI dataset incorporates information from several datasets to facilitate more effective and accurate analysis of hydropower infrastructure and their associated waterbodies. For example, dams were checked against the most recent American Rivers Dam Removal Database to identify and flag facilities that may no longer exist. Additionally, dams that are listed multiple times in the NID are identified and flagged to avoid double-counting when analyzing and summarizing information. Other quality flags include certainty of operational hydropower (i.e., if one or more datasets indicates hydropower at a particular location), whether an associated water body is accurate or composed of multiple polygons, or whether there is a known issue with reported characteristics in one of the underlying datasets. These additional data flags are designed to increase confidence in data usage for individual to large-scale analyses.

Hansen, Carly [ORNL] (ORCID:0000000193280838)↗

DOE OSTI2026

Data, model inputs, and analysis scripts associated with a manuscript on stream intermittency controls across spatial scales in Pacific Northwest watersheds

NOTE: The manuscript associated with this data package is currently in review. The data may be revised based on reviewer feedback. Upon manuscript acceptance, this data package will be updated with the final dataset and additional metadata. This data package is associated with the manuscript "Hydroclimatic Memory and Watershed Template Shape Stream Intermittency: Multi-scale Attribution Using Process-based Simulation and Explainable ML" by Niroula et al. (2026), submitted to Water Resources Research (WRR). The study investigates the dominant controls on stream intermittency across local, reach, and watershed scales using a coupled process-based simulation and explainable machine-learning framework. Long-term daily simulations from the Advanced Terrestrial Simulator (ATS) were used to generate wetness states and ponded-depth responses over river-corridor cells. These ATS outputs were then aggregated across scales and used to train XGBoost (eXtreme Gradient Boosting) models. SHAP (SHapley Additive exPlanations) was applied to quantify the relative importance of hydroclimatic forcings, watershed template attributes, and antecedent-memory effects in shaping intermittency behavior. The analysis is carried out for three contrasting Pacific Northwest watersheds: Oak Creek (OCW), American River Watershed (ARW), and H.J. Andrews (HJA). Across these testbeds, the package contains ATS-ready watershed inputs, ATS run configuration and selected output files, model-evaluation data products, intermittency-analysis datasets, machine-learning target-feature tables, SHAP outputs, and notebooks used to organize, analyze, and visualize results. At a high level, the package documents a workflow in which ATS provides the physically based simulation backbone and explainable machine learning is used as a post-processing attribution tool. The contents are intended to support interpretation of the manuscript figures and results, provide context for how intermittency metrics were generated at multiple scales, and preserve the key artifacts needed to understand and reuse the analysis workflow. The package contains a high-level directory summary file (`summary.txt`) and four main content folders (1) `evaluation_plots` contains evaluation figures and supporting evaluation datasets; (2) `intermittency_plots` contains intermittency-focused analysis notebook and prepared datasets; (3) `ml-training-and-shap_values_plots` contains ML training inputs, SHAP outputs, and figure-generation notebooks; and (4) `watershed_mesh_and_ats_input` contains ATS model setup materials, forcing inputs, geometry, and selected run files. More specifically, the `evaluation_plots` folder contains the notebook used for ATS evaluation plotting and site-specific evaluation datasets. These include evapotranspiration and water-balance products for three watersheds, as well as an Oak Creek field-measurement discharge file. The `intermittency_plots` folder contains the notebook used for intermittency analysis and the prepared datasets used to analyze intermittent and non-intermittent wetness behavior across the study watersheds. The `ml-training-and-shap_values_plots` folder contains notebooks and outputs for the machine-learning and explainability workflow. This includes the main XGBoost and SHAP notebook(s), a beeswarm plotting notebook, target-feature tables for machine-learning training, SHAP summary tables, and per-sample SHAP value archives. The `watershed_mesh_and_ats_input` folder contains ATS-related watershed inputs and supporting materials. This includes mesh and shape products, ATS-readable LAI and meteorological forcing inputs, selected ATS spinup and transient-run files, and a watershed workflow example notebook. Subdirectories are organized by watershed where applicable.All files are .cpg (codepage files), .csv (comma-separated values), .dbf (database files), .exo (Exodus mesh format), .h5 (HDF5 format), .ipynb (Jupyter notebooks), .pkl (Python pickle), .prj (projection files), .sh (shell scripts), .shp (shapefile geometry), .shx (shapefile index), .txt (text files), or .xml (markup data).

Advanced Terrestrial Simulator↗

DOE OSTI2026

Data and scripts associated with a manuscript analyzing ELM-FATES parameter sensitivity under pre-fire and postfire scenarios using machine learning

Aboveground biomass↗

NASA NTRS1973

Evaluation of ERTS data for certain hydrological uses

The author has identified the following significant results. Melting ice has been detected in Lake Erie by comparison of visible and near infrared differential reflectance. This melting condition is confirmed by meteorological ground truth data and concurrent NOAA-2 thermal infrared data. Using near-synchronous ERTS-1 data, it was possible to determine the approximate ground resolution of NOAA-2 very high resolution radiometer by comparing the smallest identifiable ice crack in the imagery and measuring the same crack on the ERTS-1 image. It was determined that photointerpretation and analysis of a single Lake Erie image can, under certain conditions, provide meaningful data on ice dynamics. ERTS-1 imagery is effective for icepack monitoring of the Great Lakes, but the sampling interval of 18 days imposes a severe limitation. Maps of the snow cover in the American River basin for 16 March 1973 have been prepared using all four bands.

Wiesnet, D. R.↗

NASA NTRS1973

Evaluation of ERTS data for certain hydrological uses

The author has identified the following significant results. A snow-extent map of the American River basin was prepared for 27 May 1973 from MSS band 4 imagery. The basin was 14% snow covered. NOAA-2 visible band imagery was used to determine date of disappearance of snow in the basin: 15 July 1973. A snowmelt curve comparing ERTS-1 and NOAA-2 snow-extent maps is provided. ERTS-1 data were superior in quality and outstanding in cartographic fidelity and were found to be an excellent control or calibration for the distorted and coarse (1 km) imagery from NOAA-2's VHRR which, however, is available on a daily basis.

Wiesnet, D. R.↗

NASA NTRS1974

Snow-extent mapping and lake ice studies using ERTS-1 MSS together with NOAA-2 VHRR

Five snow extent maps of the 5,601 sq km American River Basin were prepared using a Zoom Transfer Scope from ERTS-1 MSS band 4 imagery. The maps were generally completed within one hour. A snowmelt curve based on ERTS-1 imagery was used as a calibration standard or comparison for maps prepared from NOAA-2 VHRR imagery in the same manner. Cost comparisons with U-2 derived imagery indicate that ERTS-1 snow mapping of the basins is six times faster. Conservative estimates of comparable aircraft snow survey flights yields a cost figure 200 times that of the ERTS-1 snow map. Snow mapping attempts in the Lake Ontario Basin demonstrated that ERTS-1 is not well suited to large basins. Optimum size of basins for ERTS studies is believed to range from about 250 sq km to 30,000 sq km. The value of the ERTS-1 MSS for Great Lake ice evaluation was proved during the past winter on Lake Erie. Not only were ice features and types of ice identified, but melting ice was detected through the combined use of band 5 and band 7. Ice movement (direction and speed) was mapped by examining imagery from two successive days.

Wiesnet, D. R.↗

DOE OSTI2026

Data and script associated with “Shifts in Rain-Snow Partitioning Drive Faster Water Transit Times in the US Pacific Northwest”

This data package contains the data and code to use and run the Water Tracer enabled version of the Weather Research and Forecasting Hydrologic model (WT-WRF-Hydro) with the Sequential Precipitation Input Tagging (SPIT) framework. It is associated with the publication “Shifts in Rain-Snow Partitioning Drive Faster Water Transit Times in the US Pacific Northwest” published in Scientific Reports (Butler et al., 2026; https://doi.org/10.1038/s41598-026-46539-1). We use the Continental U.S. (CONUSII; Rasmussen et al., 2021) dataset to force the model with an historical climate (2006–2013) and a future climate (2086–2093) with a representative carbon pathway (RCP) 8.5 scenario. We use the model to calculate water transit times in five headwater catchments within the U.S. Pacific Northwest. We also show key hydrologic and environmental variables that affect water transit times and changes in the future. Finally, we use observed data to validate the model such as stream water isotopes, snowpack characteristics, and stream discharge. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. In addition to a readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions. The data package consists of 11 folders: (1) "Figures" contains the exported figures used in the manuscript; (2) "Model_Isotope_Date" contains the WT-WRF-Hydro isotope date used in model validation; (3) “Model_Outputs_Future” contains the WT-WRF-Hydro future climate outputs; (4) “Model_Outputs_Historical” contains the WT-WRF-Hydro historical climate outputs; (5) “Model_Outputs_Weights_Areas” contains the WT-WRF-Hydro weights per catchment used to calculate water transit times and isotopes in stream water; (6) “MODIS_data_scripts” contains data used to validate snow conditions in the study area; (7) “Observed_Flow_Data” contains the observed streamflow data used in model validation; (8) “Observed_Isotope_Data” contains the observed stream water isotope data used in model validation; (9) “Scripts” contains the Python scripts used to general results and the figures; (10) “Statistic_Outputs” contains the water transit time statistical outputs reported in this manuscript; (11) “Validation_SNOTEL” contains the SNOTEL data used in model validation. The files in this data package have the following file extensions: .tif, .txt, .csv, .pdf, .py, .jpg, and .png.

American River↗

DOE OSTI2025

Metagenome-assembled genomes from topsoils along a hillslope water gradient across early snowmelt to late summer in East River, CO

Drought is changing the American Mountain West at unprecedented rates with unknown consequences to soil microbiome composition and function. As a part of LBNL Watershed Science Focus Area (SFA), we investigated shifts in microbial community and transcriptional activity on a subalpine conifer-meadow transition zone throughout the summer of 2023 as soil dried down. This work took place in Crested Butte, CO on Snodgrass mountain, using a proxy for drought conditions.Here we present metagenome assembled genomes (MAGs) for the bacterial and archaeal community at 0-10cm from three sites along a hillslope water gradient across five timepoints from early snowmelt to late summer. 42 metagenomes were sequenced at Joint Genome Institute (JGI) and can be found under the JGI GOLD (Genomes Online Database) sequencing project Gs0166660. Metagenomes were assembled through an inhouse pipeline (see methods), binned using four autobinners (concoct, maxbin2, metabat2, and vamb) and consolidated using dastool. The consolidated bins from all metagenomes were pooled, filtered by completeness (>70%) and contamination (<10%), and dereplicated at 95% ANI using drep. This dataset (1) a zip file of 157 MAGs (as fasta files, Gs0166660_bins_tar.gz), (2) sample metadata file with sample IGSNs (International Generic Sample Numbers) (samples.csv), (3) bounding box coordinates for the sampled locations (Gs0166660.kml), (4) metagenome assembly and coassembly metadata file listing IMG/M (Integrated Microbial Genomes/Metagenomes) metagenome accessions linking samples to metagenomes (EastRiver_Drought_ESSDive_Metadata.csv), (5) location metadata file (locations.csv), (6) file-level metadata file (flmd.csv) and (7) data dictionary (dd.csv) file.This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1982

A satellite magnetic model of northeastern South American aulacogens

Magnetic modeling of the Amazon River and Takatu Aulacogens in northeastern South America illustrate the utility of satellite magnetic data in characterizing the properties and structure of the lithosphere. Specifically, reduction of preliminary Magsat scalar magnetic anomaly data to an equivalent condition of vertical polarization shows a general correlation between magnetic anomaly minima and the Amazon River and Takatu Aulacogens. Surface gravity data demonstrate a correlative positive anomaly. Spherical earth modeling of the magnetic data indicates a less magnetic crust associated with the aulacogens which is compatible with previous studies over the Mississippi River Aulacogen and Rio Grande Rift in North America.

Longacre, M. B.↗

DOE OSTI2024

Deep Learning for Fish Identification from Sonar Data (CRADA 481 Final Report)

In eastern regions of the United States, the American eel is a species of management and regulatory concern because of significant population declines, despite the species’ previous abundance in all tributaries of rivers flowing into the Atlantic Ocean. The American eel is also a candidate for listing under the U.S. Endangered Species Act. While hydropower construction and operation are only one of several factors contributing to this population decline, such a listing could impose additional regulatory challenges for a large number of hydropower projects. In this CRADA project, we improved technologies for identifying migrating eels with the goal of reducing the cost and time required for future American eel hydropower impact assessment and mitigation studies, while maintaining accuracy. We built on results from a previous FOA project (FOA# DE-FOA-0001662), led by the Electric Power Research Institute (EPRI), which developed a highly accurate, deep-learning method for identifying migrating eels from imaging sonar data. The current study aimed to further optimize this deep-learning model, originally designed for image classification, and to develop an object detection software capable of identifying fish from sonar videos in real time, enabling the detection of events like fish migrations and specific species, such as the American eel, at hydropower dams. The data conversion algorithms were packaged as software with a graphical user interface, and the software is evaluated by external collaborators. We focused on the American eel in this project and explored the transferability of the developed deep learning models to the sea lamprey, given the similar body shape and swimming behavior between the two species.

13 HYDRO ENERGY↗

DOE OSTI2024

The Iowa Tribe of Kansas and Nebraska: Advancing Clean, Resilient, and Sovereign Energy (Summary Report of Communities LEAP Activities)

The Iowa Tribe of Kansas and Nebraska (ITKN) is a federally recognized Native American Tribe located along the Missouri River on the border of northeast Kansas and southeastern Nebraska. There are over 800 residents (Tribal citizens and non-Tribal) who live on the reservation, as well as more than 500 people who visit or work on the reservation on a daily basis. The ITKN faces many energy challenges, including rising service costs and dozens of power outages annually that impact resident well-being and business activities on Tribal lands. Power service issues are made more challenging by the remoteness of the reservation, which is 20 miles from the nearest town. Despite this, the ITKN has a long history of cultural and economic resilience: Local self-reliance, environmental stewardship, respecting the carrying capacity of the land, and strengthening the community are Tribal communities' traditional strengths. Long-term energy goals for the ITKN are centered around achieving energy sovereignty. Priority actions include: (1) Establishing a Tribal Utility Authority (TUA) to promote social welfare and community development.; (2) Deploying renewable community microgrids with ground-mount solar arrays and sustainable energy storage systems to advance energy sovereignty, resilience, and reliability. To advance these goals, the ITKN partnered with the U.S. Department of Energy's (DOE's) Communities LEAP (Local Energy Action Program) pilot. From August 2022 to March 2024, the ITKN community coalition collaborated with technical assistance providers at DOE's National Renewable Energy Laboratory (NREL) and Sandia National Laboratories to evaluate TUA planning needs and microgrid deployment scenarios. This final report details the Communities LEAP technical assistance process, models and analysis performed, and results.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

The Iowa Tribe of Kansas and Nebraska: Advancing Clean, Resilient, and Sovereign Energy

The Iowa Tribe of Kansas and Nebraska (ITKN) is a federally recognized Native American Tribe located along the Missouri River on the border of northeast Kansas and southeastern Nebraska. There are over 800 residents (Tribal citizens and non-Tribal) who live on the reservation, as well as more than 500 people who visit or work on the reservation on a daily basis. The ITKN faces many energy challenges, including rising service costs and dozens of power outages annually that impact resident well-being and business activities on Tribal lands. Power service issues are made more challenging by the remoteness of the reservation, which is 20 miles from the nearest town. Despite this, the ITKN has a long history of cultural and economic resilience: Local self-reliance, environmental stewardship, respecting the carrying capacity of the land, and strengthening the community are Tribal communities' traditional strengths. Long-term energy goals for the ITKN are centered around achieving energy sovereignty. Priority actions include: (1) Establishing a Tribal Utility Authority (TUA) to promote social welfare and community development.; (2) Deploying renewable community microgrids with ground-mount solar arrays and sustainable energy storage systems to advance energy sovereignty, resilience, and reliability. To advance these goals, the ITKN partnered with the U.S. Department of Energy's (DOE's) Communities LEAP (Local Energy Action Program) pilot. From August 2022 to March 2024, the ITKN community coalition collaborated with technical assistance providers at DOE's National Renewable Energy Laboratory (NREL) and Sandia National Laboratories to evaluate TUA planning needs and microgrid deployment scenarios. This fact sheet provides an overview of the results and outcomes from the Communities LEAP technical assistance process.

Communities Leap↗

NASA NTRS1979

An Environmental Innovation: The Sewer Mouse

In the effort to clean up America's waters, there is a little-known complicating factor: because they leak, sewer systems in many American cities are causing rather than preventing pollution of rivers and lakes. Fixing the leaks is difficult because their locations are unknown. Maintenance crews can't tear up a whole city looking for cracks in the pipes; they must first determine which areas are most likely suspects. An aerospace spinoff is providing help in that regard. The problem starts with heavy rains. Rainwater naturally flows into the sewers from streets, but sewage systems are designed to accommodate it. However, they are not designed to handle the additional flow of "groundwater", rain absorbed by the earth which seeps into the sewers through leaks in pipes and sewer walls. After a storm, groundwater seepage can increase the waterflow to deluge proportions, with the result that sewage treatment plants are incapable of processing the swollen flow. When that happens the sluices must be opened, dumping raw sewage into rivers and lakes.

Source record↗

DOE OSTI2025

Physical properties, internal structure, and the three‐dimensional petrography of CI chondrites

physical properties and the nature of their breccation, we investigated nine samples of the Ivuna and Orgueil CI chondrites ranging in size from 1 mm to 4 cm in approximate diameter. The combined mass of unique material investigated in this work is 113 g. For our investigations, we use ideal gas pycnometry, 3-D laser scanning, x-ray computed microtomography (μCT), and accompanying digital data extraction techniques. We found that the bulk density of the samples ranged from 1.61 to 2.10 g cm −3 . Larger samples tend to have a lower bulk density. Grain density (ranging from 2.44 to 2.55 g cm −3 ) is significantly less variable than the bulk density in our samples and the quantity of porosity (ranging from 14.6% to 33.8%) is the dominant factor in determining the bulk density of CI chondrite material. Our μCT results show that the visible porosity across all sizes of our CI chondrite samples is in the form of cracks, but these cracks can account for less than two-thirds of the porosity in the CI chondrites. Other porosity is not visible, even at μCT resolutions of 2.7 μm voxel edge −1 and we conclude that it is sub-micron in nature. It is not clear if the cracks seen in our samples are indigenous to the chondrites or are a result of terrestrial processes. We also find that the CI chondrites are excellent examples of the fractal-like nature of brecciation, where clasts can be observed at all scales we imaged. The breccias are composed of sub-equant-shaped and sub-rounded-textured clasts like melt-free impact breccias on other solar system bodies. From our μCT volume and digital data extraction, we determine that the Ivuna CI chondrite breccia is organized: the mostly sub-equant clasts within our ~2 cm chunk of Ivuna have a mean diameter of 1.33 mm and their aligned longest axes define a lineation structure. We speculate that the lineation was imparted after fragmentation of the clasts by slight shear on the parent asteroid which could be the result of seismic-related granular flow or mild non-axial impact-related compaction. These data will help to place returned asteroidal material from asteroids 162173 Ryugu and 101955 Bennu and the CI chondrites into a mutual geological context.

CI chondrite↗

DOE OSTI2025

Uptake and elimination of 137Cs in aquatic biota inhabiting a contaminated effluent canal

Radiocesium (137Cs) is among the most prevalent and concerning radionuclide released from anthropogenic activities due to its relatively slow decay time and high bioavailability. Numerous studies have reported activity concentrations of 137Cs in exposed biota, but few have assessed detailed toxicokinetics. The objective of our study was to quantify and compare the uptake and elimination of 137Cs in aquatic taxa from multiple classes with different ecological roles inhabiting a canal contaminated from nuclear production activities on the Savannah River Site in South Carolina, USA. We tracked accumulation and elimination of 137Cs in four understudied aquatic species: one aquatic macrophyte [American white water lily (Nymphae odorata), two benthic associated omnivorous species (American bullfrog (Lithobates catesbeianus) and red swamp crayfish (Procambarus clarkii), and one pelagic carnivorous fish (Eastern mosquitofish (Gambusia holbrooki)]. We monitored accumulation of 137Cs from initial exposure until equilibrium for biota restricted within the canal and subsequently tracked elimination of 137Cs over time by moving organisms from the canal to a nearby reference pond. Results indicated bullfrog tadpoles reached 95 % equilibrium in approximately 9 days, the fastest among the species evaluated. After bullfrog tadpoles, the next fastest time to equilibrium was achieved by red swamp crayfish (51 days) followed by mosquitofish (86 days). At equilibrium, bullfrog tadpoles were found to have similar 137Cs activity concentrations to mosquitofish (3.16 and 3.57 Bq/g, respectively), and both were significantly higher than red swamp crayfish (1.77 Bq/g). For elimination, we found biological half-lives to range between 8 and 43 days with bullfrog tadpoles eliminating 137Cs the fastest followed by water lilies, mosquitofish, and red swamp crayfish. Overall, we found the uptake and elimination of 137Cs to vary widely among our studied species, but benthic organisms are not at an increased risk to accumulate 137Cs compared to organisms in less frequent contact with the sediment.

Benthic organism Bioaccumulation Bioindicator Elim↗

DOE OSTI2026

AmeriFlux FLUXNET-1F US-xLE NEON Lenoir Landing (LENO)

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-xLE NEON Lenoir Landing (LENO). This is the FLUXNET version of the carbon flux data for the site US-xLE NEON Lenoir Landing (LENO) produced by applying the standard ONEFlux (1F) software. Site Description - This terrestrial field site is located in a hardwood bottomland with seasonal flooding each spring located in southwest Alabama. The meteorological/flux tower and tower sampling plots are located at Lenoir Landing and the distributed plots are located approximately 5 km south of the tower at Choctaw National Wildlife Refuge. The ecosystem at LENO is dominated by closed-canopy pine-oak mixed forest with a developed understory, and also includes a small fraction of meadows, wetlands, and smaller water bodies. Dominant plant species include American sweetgum (Liquidambar styraciflua), American hornbeam (Carpinus caroliniana), and loblolly pine (Pinus taeda). Choctaw National Wildlife Refuge also provides a protected wintering area for waterfowl and wood duck brood habitat. This site is colocated with the Lower Tombigbee river aquatic site.

Network), NEON (National Ecological Observatory [N↗

DOE OSTI2025

Probing Electronic Coherence between Core-Level Vacancies at Different Atomic Sites

The detailed understanding of electronic coherence in quantum systems requires measurements on the attosecond timescale. Attosecond x-ray pulses enable the study of electronic coherence in core-excited molecular systems. Here we report on the coherent motion of electrons in the 1,1-difluoroethylene ion following ionization of the K shell of the two nonequivalent carbon sites with a subfemtosecond x-ray pulse. Using the angular streaking technique to track the Auger-Meitner decay, we observe temporal modulations of the emission, indicating the electronic coherence of the core-excited ionic states, and extract a 6.5 ± 0.8 fs average lifetime of the core-level vacancies. A quantum-mechanical model is employed to interpret the measurement, and we find the observed temporal modulations are independent of charge density oscillations. This work opens a new regime of coherent electronic motion, beyond charge migration, where electronic coherence manifests in the nonlocal quantum correlation between atomic sites while charge density oscillation is absent. Our results broaden the landscape of electronic coherence in molecular systems. Published by the American Physical Society 2025

Wang, Jun (ORCID:000000031962895X)↗