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At least 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Nitrogen availability and summer drought, but not N:P imbalance, drive carbon use efficiency of a Mediterranean tree-grass ecosystem

All ecosystems contain both sources and sinks for atmospheric carbon (C). A change in their balance of net and gross ecosystem carbon uptake, ecosystem-scale carbon use efficiency (CUE ECO ), is a change in their ability to buffer climate change. However, anthropogenic nitrogen (N) deposition is increasing N availability, potentially shifting terrestrial ecosystem stoichiometry towards phosphorus (P) limitation. Depending on how gross primary production (GPP, plants alone) and ecosystem respiration (R ECO , plants and heterotrophs) are limited by N, P or associated changes in other biogeochemical cycles, CUE ECO may change. Seasonally, CUE ECO also varies as the multiple processes that control GPP and respiration and their limitations shift in time. We worked in a Mediterranean tree-grass ecosystem (locally called ‘dehesa’) characterized by mild, wet winters and summer droughts. We examined CUE ECO from eddy covariance fluxes over 6 years under control, +N and + NP fertilized treatments on three timescales: annual, seasonal (determined by vegetation phenological phases) and 14-day aggregations. Finer aggregation allowed consideration of responses to specific patterns in vegetation activity and meteorological conditions. We predicted that CUE ECO should be increased by wetter conditions, and successively by N and NP fertilization. Milder and wetter years with proportionally longer growing seasons increased CUE ECO , as did N fertilization, regardless of whether P was added. Using a generalized additive model, whole ecosystem phenological status and water deficit indicators, which both varied with treatment, were the main determinants of 14-day differences in CUE ECO . The direction of water effects depended on the timescale considered and occurred alongside treatment-dependent water depletion. Overall, future regional trends of longer dry summers may push these systems towards lower CUE ECO .

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2021

Liana optical traits increase tropical forest albedo and reduce ecosystem productivity

Lianas are a key growth form in tropical forests. Their lack of self-supporting tissues and their vertical position on top of the canopy make them strong competitors of resources. A few pioneer studies have shown that liana optical traits differ on average from those of colocated trees. Those trait discrepancies were hypothesized to be responsible for the competitive advantage of lianas over trees. Yet, in the absence of reliable modelling tools, it is impossible to unravel their impact on the forest energy balance, light competition, and on the liana success in Neotropical forests. To bridge this gap, we performed a meta-analysis of the literature to gather all published liana leaf optical spectra, as well as all canopy spectra measured over different levels of liana infestation. We then used a Bayesian data assimilation framework applied to two radiative transfer models (RTMs) covering the leaf and canopy scales to derive tropical tree and liana trait distributions, which finally informed a full dynamic vegetation model. According to the RTMs inversion, lianas grew thinner, more horizontal leaves with lower pigment concentrations. Those traits made the lianas very efficient at light interception and significantly modified the forest energy balance and its carbon cycle. While forest albedo increased by 14% in the shortwave, light availability was reduced in the understorey (−30% of the PAR radiation) and soil temperature decreased by 0.5°C. Those liana-specific traits were also responsible for a significant reduction of tree (−19%) and ecosystem (−7%) gross primary productivity (GPP) while lianas benefited from them (their GPP increased by +27%). This study provides a novel mechanistic explanation to the increase in liana abundance, new evidence of the impact of lianas on forest functioning, and paves the way for the evaluation of the large-scale impacts of lianas on forest biogeochemical cycles.

Félicien Meunier↗
DOE OSTI2025

Advancing the Understanding of Snow Accumulation, Melting, and Associated Thermal Insulation Using Spatially Dense Snow Depth and Temperature Time Series

Snow thermal insulation is a critical factor influencing ground thermal dynamics and associated biogeochemical processes. We analyzed the spatiotemporal variability of snow accumulation, melting, and thermal insulation dynamics using spatially dense, collocated snow depth and ground interface temperature time series over two consecutive years. We demonstrated that considering late‐winter snow depth alone was insufficient to fully capture the complexity in snow and insulation dynamics. The influence of vegetation and topography on snow depth distribution varied over the season, across sites and years. We found that deep snow with a long melting period had a substantial impact on thawing n‐factors. To better predict snow insulation effects, we proposed a new weighted snow depth metric that integrates mean daily snow depth and air temperature throughout the cold season. Our results provide insights for developing space‐time remote sensing products and evaluating the representation of snow and permafrost processes in Earth system models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Using Ensemble Data Assimilation to Estimate Transient Hydrologic Exchange Flow Under Highly Dynamic Flow Conditions

Abstract Quantifying dynamic hydrologic exchange flows (HEFs) within river corridors that experience high‐frequency flow variations caused by dam regulations is important for understanding the biogeochemical processes at the river water and groundwater interfaces. Heat has been widely used as a tracer to infer steady‐state flow velocities through analytical solutions of heat transport defined by the diurnal temperature signals. Under sub‐daily dynamic flow conditions, however, such analytical solutions are not applicable due to the violation of their fundamental assumptions. In this study, we developed a data assimilation‐based approach to estimate the sub‐daily flux under highly dynamic flow conditions using multi‐depth temperature observations at a 5‐min resolution. If the hydraulic gradient is measured, Darcy's law was used to calculate the flux with permeability estimated from temperature responses below the riverbed. Otherwise, flux was estimated directly by assimilating multi‐depth temperature data at 1‐ or 2‐hr time intervals assuming one‐dimensional flow and heat transport governing equation. By comparing estimated fluxes with model‐generated synthetic truth, we demonstrated that both schemes have robust performance in estimating fluxes under highly dynamic flow conditions. This data assimilation‐based flux estimation method was able to capture the vertical sub‐daily fluxes using multi‐depth high‐resolution temperature data alone, even in the presence of multi‐dimensional flow. This approach has been successfully applied to real field temperature data collected at the Hanford site, which experiences highly dynamic HEFs. Our study shows the promise of adopting distributed 1‐D temperature monitoring to capture spatial and temporal exchange dynamics in river corridors at a watershed scale or beyond.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Linkages Between Mineral Element Composition of Soils and Sediments With Hyporheic Zone Dissolved Organic Matter Chemistry Across the Contiguous United States

The hyporheic zone is a hotspot for biogeochemical cycling where interactions with mineral metals preserve the release and biodegradation of organic matter (OM). A small fraction of OM can still be exchanged between localized sediments and the overlying water column, and recent evidence suggests there exists a longitudinal structuring in sediment dissolved OM (DOM) chemistry across the continental United States (CONUS). In this study, we tested a hypothesis that water extractable sediment DOM chemistry could be explained by sediment metal contents and integrative watershed scale features at the CONUS scale. Crowdsourced samples were characterized for high resolution mass spectrometry and coupled with sediment metals determined via x-ray fluorescence as well as with land cover and soil elemental information obtained from national databases. Our results highlight weak relationships between DOM chemistry and elemental composition at the CONUS scale indicating limited transferability of organo-metal linkages into multi-scale hydrobiogeochemical models.

58 GEOSCIENCES↗
NASA NTRS2013

An Overview of Regional Experiments on Biomass Burning Aerosols and Related Pollutants in Southeast Asia: From BASE-ASIA and the Dongsha Experiment to 7-SEAS

By modulating the Earth-atmosphere energy, hydrological and biogeochemical cycles, and affecting regional-to-global weather and climate, biomass burning is recognized as one of the major factors affecting the global carbon cycle. However, few comprehensive and wide-ranging experiments have been conducted to characterize biomass-burning pollutants in Southeast Asia (SEA) or assess their regional impact on meteorology, the hydrological cycle, the radiative budget, or climate change. Recently, BASEASIA (Biomass-burning Aerosols in South-East Asia: Smoke Impact Assessment) and the 7-SEAS (7- South-East Asian Studies) Dongsha Experiment were conducted during the spring seasons of 2006 and 2010 in northern SEA, respectively, to characterize the chemical, physical, and radiative properties of biomass-burning emissions near the source regions, and assess their effects. This paper provides an overview of results from these two campaigns and related studies collected in this special issue, entitled Observation, modeling and impact studies of biomass burning and pollution in the SE Asian Environment. This volume includes 28 papers, which provide a synopsis of the experiments, regional weatherclimate, chemical characterization of biomass-burning aerosols and related pollutants in source and sink regions, the spatial distribution of air toxics (atmospheric mercury and dioxins) in source and remote areas, a characterization of aerosol physical, optical, and radiative properties, as well as modeling and impact studies. These studies, taken together, provide the first relatively complete dataset of aerosol chemistry and physical observations conducted in the sourcesink region in the northern SEA, with particular emphasis on the marine boundary layer and lower free troposphere (LFT). The data, analysis and modeling included in these papers advance our present knowledge of source characterization of biomass-burning pollutants near the source regions as well as the physical and chemical processes along transport pathways. In addition, we raise key questions to be addressed by a coming deployment during springtime 2013 in northern SEA, named 7-SEASBASELInE (Biomass-burning Aerosols Stratocumulus Environment: Lifecycles and Interactions Experiment). This campaign will include a synergistic approach for further exploring many key atmospheric processes (e.g., complex aerosol-cloud interactions) and impacts of biomass burning on the surface-atmosphere energy budgets during the lifecycles of biomass burning emissions.

aerosol/biomass burning↗
DOE OSTI2023

Light Energy Transduction in Green Sulfur Bacteria

Green sulfur bacteria (GSB) are exquisitely adapted for growth at extraordinarily low light intensities. They are important primary producers of biomass in many anoxic environments, and they contribute significantly to the biogeochemical cycling of carbon, nitrogen, and sulfur on Earth. Green bacteria more generally share the property of using chlorosomes for light-harvesting, and these unusual organelles have many unique features. These include the presence of a monolayer lipid-protein envelope, self-assembling bacteriochlorophylls (BChl) in which pigment-pigment interactions predominate, and the presence of redox components ([2Fe-2S] ferredoxins and quinones) that play a role in regulating excitation energy transfer to the type-1 homodimeric reaction centers. The reaction centers of GSB are related to Photosystem I of cyanobacteria and higher plants but also exhibit several unique structural and functional features. The long-term objectives of this research program are to understand the structure, functions, and biogenesis of the chlorosomes, reaction centers, and electron transport chains that carry out the photochemical transduction of light energy into chemical energy in the model green sulfur bacterium, Chlorobaculum (formerly Chlorobium) tepidum. Over a period of 26 years, we characterized chlorosomes in detail. We identified the proteins in the chlorosome envelopes of diverse organisms, identified the nearest neighbors of those proteins, and characterized the chlorosomes of mutant strains lacking one to five of these proteins. After the genome sequence of Cba. tepidum became available, we identified all genes encoding enzymes for BChl a , BChl c/d/e/ƒ , and Chl a biosynthesis Cba. tepidum . We additionally identified all genes encoding enzymes for carotenoid biosynthesis. By constructing a bchQRU mutant strain that produces [Et, Me]-BChl d , together with collaborators who are specialists in solid-state NMR and cryo-electron microscopy, we solved the structure of the BChls in chlorosomes. Using similar methods and chlorosomes containing [Et, Me]-BChl c , we then showed that alternative structures were possible using the same syn-anti BChl dimer. The structures were refined by introducing spectroscopic data from single-chlorosome measurements. Over the course of this project, we sequenced the genomes of approximately twenty GSB strains, which provided important information for comparative analyses. Through analyses of metagenomic data from Mushroom and Octopus Springs in Yellowstone National Park, we identified a novel chlorophototroph belonging to the phylum Acidobacteriota. We successfully isolated an axenic culture of this organism. We characterized the photosynthetic apparatus of this bacterium, named Chloracidobacterium thermophilum, in significant detail, in particular its type-1, homodimeric reaction centers. Surprisingly, these reaction centers contain three types of Chls, BChl a , Chl a , and Zn-BChl a' . We showed that a dimer of Zn-BChl a' is the primary donor and Chl a the primary acceptor of electrons in this reaction center by using advanced spectroscopic techniques. We isolated eight additional strains of Chloracidobacterium spp. from Mushroom Spring and Rupite hot springs in Bulgaria. Comparative genomes showed that these represent three species, Cab. thermophilum , Cab. aggregatum , and Cab. validum . By applying comparative genomics, genetic, biochemical biophysical and physiological approaches to study green bacteria, we produced a wealth of new information about the remarkable light-harvesting and energy transduction capabilities of these poorly characterized microorganisms.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Machine learning model inputs, outputs, and scripts associated with “Artificial intelligence-guided iterations between observations and modeling significantly improve environmental predictions”

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 “Artificial intelligence-guided iterations between observations and modeling significantly improve environmental predictions” (Malhotra et al., in prep). This effort was designed following ICON (integrated, coordinated, open, and networked) principles to facilitate a model-experiment (ModEx) iteration approach, leveraging crowdsourced sampling across the contiguous United States (CONUS). New machine learning models were created every month to guide sampling locations. Data from the resulting samples were used to test and rebuild the machine learning models for the next round of sampling guidance. Associated sediment and water geochemistry and in situ sensor data can be found at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1923689, https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1729719, and https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1603775. This data package is associated with two GitHub repositories found at https://github.com/parallelworks/dynamic-learning-rivers and https://github.com/WHONDRS-Hub/ICON-ModEx_Open_Manuscript. In addition to this readme, this data package also includes two file-level metadata (FLMD) files that describes each file and two data dictionaries (DD) that describe all column/row headers and variable definitions. This data package consists of two main folders (1) dynamic-learning-rivers and (2) ICON-ModEx_Open_Manuscript which contain snapshots of the associated GitHub repositories. The input data, output data, and machine learning models used to guide sampling locations are within dynamic-learning-rivers. The folder is organized into five top-level directories: (1) “input_data” holds the training data for the ML models; (2) “ml_models” holds machine learning (ML) models trained on the data in “input_data”; (3) “examples” contains files for direct experimentation with the machine learning model, including scripts for setting up “hindcast” run; (4) “scripts” contains data preprocessing and postprocessing scripts and intermediate results specific to this data set that bookend the ML workflow; and (5) “output_data” holds the overall results of the ML model on that branch. Each trained ML model resides on its own branch in the repository; this means that inputs and outputs can be different branch-to-branch. There is also one hidden directory “.github/workflows”. This hidden directory contains information for how to run the ML workflow as an end-to-end automated GitHub Action but it is not needed for reusing the ML models archived here. Please see the top-level README.md in the GitHub repository for more details on the automation. The scripts and data used to create figures in the manuscript are within ICON-ModEx_Open_Manuscript. The folder is organized into four folders which contain the scripts, data, and pdf for each figure. Within the “fig-model-score-evolution” folder, there is a folder called “intermediate_branch_data” which contains some intermediate files pulled from dynamic-learning-rivers and reorganized to easily integrate into the workflows. NOTE: THIS FOLDER INCLUDES THE FILES AT THE POINT OF PAPER SUBMISSION. IT WILL BE UPDATED ONCE THE PAPER IS ACCEPTED WITH ANY REVISIONS AND WILL INCLUDE A DD/FLMD AT THAT POINT. We thank the United States Forest Service, Washington Department of Fish and Wildlife, Washington Department of Natural Resources, Cowiche Canyon Conservatory, Washington State Parks and Recreation Commission (Scientific Research Permit #210901), and the Confederated Tribes and Bands of the Yakama Nation for access to field locations where the samples labeled “SSS” were collected. We also thank the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate sample collection and optimization of data usage according to their values and worldview. WHONDRS consortium members were asked to provide any acknowledgments for the collection of samples labeled “CM” and the following is a list of acknowledgments that were submitted with their corresponding Site IDs: (MART) Research activities were conducted in part on the Wind River Experimental Forest within the Gifford Pinchot National Forest; (MP- 100379) Philadelphia is part of Lenapehoking, the ancestral homelands of the Lenape peoples; (MP-102398) Land surveyed is the ancestral homelands of the Nookhose'iinenno (Arapaho), Tsis tsis'tas (Cheyenne), and Nuuchu (Ute); (MP-100749 and MP- 100747) Georgia Coastal Ecosystem LTER, OCE-1832178; (SP-70 and SP-72) Eastern Shoshone, Shoshone-Bannock; (MP- 102944) Funded by Oregon Watershed Enhancement Board. On the traditional lands of the Confederated Tribes of the Siletz, Confederated Tribes of the Grand Rhonde, and the Clatsop-Nehalem Confederated Tribe; (MP- 100607) Holiday Creek is located on the traditional territory of the Monacan Indian Nation; (SP-45) Lafayette Blue Springs State Park; (MP-102420) NSF DEB-2016749; (MP-100019) New Hampshire Agriculture Experiment Station; (SP-35) Rayonier (land owner; https://www.rayonier.com/); (MP- 101276) US Department of Energy, Office of Science, Biological and Environmental Research, Subsurface Biogeochemical Research, Watershed Dynamics and Evolution SFA at ORNL; (MP- 103224) Watershed Dynamics and Evolution SFA at ORNL; (MP- 101584) Traditional lands of the Oceti Sakowin (Dakota, Lakota, Nakoda) and Anishinaabe Peoples.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2019

Deriving High-Resolution Reservoir Bathymetry from ICESat-2 Prototype Photon-Counting Lidar and Landsat Imagery

Knowledge of reservoir bathymetry is essential for many studies on terrestrial hydrological and biogeochemical processes. However, there are currently no cost-effective approaches to derive reservoir bathymetry at the global scale. This study explores the potential of generating high-resolution global bathymetry using elevation data collected by the 532-nm Advanced Topographic Laser Altimeter System (ATLAS) onboard the Ice, Cloud, and Land Elevation Satellite (ICESat-2). The novel algorithm was developed and tested using the ICESat-2 airborne prototype, the Multiple Altimeter Beam Experimental Lidar (MABEL), with Landsat-based water classifications (from 1982 to 2017). MABEL photon elevations were paired with Landsat water occurrence percentiles to establish the elevation-area (E-A) relationship, which in turn was applied to the percentile image to obtain partial bathymetry over the historic dynamic range of reservoir area. The bathymetry for the central area was projected to achieve the full bathymetry. The bathymetry image was then embedded onto the digital elevation model (DEM). Results were validated over Lake Mead against survey data. Results over four transects show coefficient of determination (R²) values from 0.82 to 0.99 and root-mean-square error (RMSE) values from 1.18 to 2.36 m. In addition, the E-A and elevation-storage (E-S) curves have RMSEs of 1.56 m and 0.08 km³, respectively. Over the entire dynamic reservoir area, the derived bathymetry agrees very well with independent survey data, except for within the highest and lowest percentile bands. With abundant overpassing tracks and high spatial resolution, the newly launched ICESat-2 should enable the derivation of bathymetry over an unprecedented number of reservoirs.

Yao Li↗
NASA NTRS2012

Diagnostic modeling of dimethylsulfide production in coastal water west of the Antarctic Peninsula

The rate of gross biological dimethylsulfide (DMS) production at two coastal sites west of the Antarctic Peninsula, off Anvers Island, near Palmer Station, was estimated using a diagnostic approach that combined field measurements from 1 January 2006 through 1 March 2006 and a one-dimensional physical model of ocean mixing. The average DMS production rate in the upper water column (0-60 m) was estimated to be 3.1 +/- 0.6 nM/d at station B (closer to shore) and 2.7 +/- 0.6 nM/d1 at station E (further from shore). The estimated DMS replacement time was on the order of 1 d at both stations. DMS production was greater in the mixed layer than it was below the mixed layer. The average DMS production normalized to chlorophyll was 0.5 +/- nM/d)/(mg cubic m) at station B and 0.7 +/- 0.2 (nM/d)/(mg/cubic m3) at station E. When the diagnosed production rates were normalized to the observed concentrations of total dimethylsulfoniopropionate (DMSPt, the biogenic precursor of DMS), we found a remarkable similarity between our estimates at stations B and E (0.06 +/- 0.02 and 0.04 +/- 0.01 (nM DMS / d1)/(nM DMSP), respectively) and the results obtained in a previous study from a contrasting biogeochemical environment in the North Atlantic subtropical gyre (0.047 =/- 0.006 and 0.087 +/- 0.014 (nM DMS d1)/(nM DMSP) in a cyclonic and anticyclonic eddy, respectively).We propose that gross biological DMS production normalized to DMSPt might be relatively independent of the biogeochemical environment, and place our average estimate at 0.06 +/- 0.01 (nM DMS / d)/(nM DMSPt). The significance of this finding is that it can provide a means to use DMSPt measurements to extrapolate gross biological DMS production, which is extremely difficult to measure experimentally under realistic in situ conditions.

Dimethylsulfide↗
DOE OSTI2020

Influence of manganese abundances on iron and arsenic solubility in rice paddy soils

Arsenic (As) mobilization in rice paddy soils under fluctuating redox conditions is influenced by the biogeochemical cycling of redox sensitive elements such as iron (Fe) and manganese (Mn). Arsenic mobility in paddy soils is highly variable, and the influence of Mn abundances and Mn/Fe ratios on As mobility in these soils have received little attention. In this contribution, we developed a complementary set of field and laboratory experiments designed to evaluate the impact of Mn on interconnected Fe and As solubilization in rice paddy soils experiencing wetting-drying cycles through controlled irrigation. Porewater monitoring and synchrotron-based imaging and spectroscopy of thin sections prepared from an Arkansas paddy soil confirmed that As release was primarily governed by reductive dissolution of Fe (oxy)hydroxide phases. Experiments with laboratory soil microcosms amended with the synthetic nanocrystalline Mn oxide, δ-MnO 2 , showed that higher initial Mn/Fe inhibited Fe and As mobilization into porewater relative to unamended soil by up to 95% and 45%, respectively. Geochemical modeling suggests that pH increases driven by microbial MnO 2 reduction, in conjunction with microbial Fe- and sulfate-reduction in carbonate-rich porewater, enhanced the precipitation of siderite (FeCO 3(s) ), mackinawite (FeS (s) ), and potentially a Mn(II) arsenate phase. These secondary mineral phases likely played a greater role in controlling As solubilization than the role of Mn as a redox buffer regulating the redox conditions in the flooded soils. Field and laboratory experiments showed that alternate wetting and drying approaches with a single dry-down can be effective at reducing dissolved As concentrations in porewater through the oxidation of Fe. Differences in soil Mn/Fe ratios had no clear impact on the effectiveness of dry-downs as a strategy to reduce As mobilization.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Artificial intelligence models, photos, and data associated with the manuscript “Quantifying Streambed Grain Size, Uncertainty, and Hydrobiogeochemical Parameters Using Machine Learning Model YOLO” (v2)

This data package is associated with the manuscript “Quantifying Streambed Grain Size, Uncertainty, and Hydrobiogeochemical Parameters Using Machine Learning Model YOLO” published in Water Resources Research (Chen et al., 2024). This data package includes the training, validation, testing, and prediction data used by the artificial intelligence (AI) model for automated grain size and hydro-biogeochemistry quantification using streambed photos. The grain size data are extracted for each photo using You Look Only Once (YOLO), a pre-trained object detection model. This data package was originally published in October 2023. It was updated August 2025 (v2; new and modified files). File and folder names were not revised to indicate changes. See the change history section in the readme for more details. Please see flmd.csv for a list of all files contained in this data package and descriptions for each. Please see dd.csv for a data dictionary that defines the column headers of .csv files in the data package. This dataset is comprised of one data folder containing (1) file-level metadata; (2) data dictionary; (3) readme; and (4) six subfolders. Subfolders 1 to 4 include the training, validation, testing, and prediction data. Subfolder 5_Summary includes the summary results of different combinations of training, validation, testing, and prediction data. Subfolder 6_SupplementalData includes additional data downloaded from public sources (Kaufman et al., 2023a; Kaufman et al., 2023b; Garefalakis et al., 2023; Mair et al., 2024; https://github.com/river-corridors-sfa/Geospatial_variables). In total, the data package includes 110 folders and 44,283 files. These files include 9,047 .jpg photos, 1 .png photo, 3 .tif photos; 26,639 photo labels and individual grain sizes and probability from AI (.txt); 8,447 grain size distribution data (.dat); and 126 CSV files for results summary, and 14 required metadata files (.xlsx). The summary CSV files contain 68 columns and approximately 2,200 rows that represent photo names, site locations, recording time, GPS coordinates, grains sizes (D10, D50, D60, and D84), number of grains, and additional hydro-biogeochemical data such as water depth, flow velocity, Manning’s coefficient, friction factor, hydraulic conductivity, permeability, streambed interstitial velocity magnitude, mass transfer rate, and nitrate uptake velocity. The photos were obtained from 75 sites in the Yakima River Basin and the Columbia River shorelines, and other associated data from samples and sensors obtained when the photos were taken are publicly available (Fulton et al. 2022; Grieger et al. 2023). All files are .csv, .txt, .dat, .jpg, or .pdf. We acknowledge the Yakama Nation as owners and caretakers of the lands where we collected some of these data. We thank the Confederated Tribes and Bands of the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate sample collection and optimization of data usage according to their values and worldview.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2001

An Integrated Use of Experimental, Modeling and Remote Sensing Techniques to Investigate Carbon and Phosphorus Dynamics in the Humid Tropics

Moist tropical forests comprise one of the world's largest and most diverse biomes, and exchange more carbon, water, and energy with the atmosphere than any other ecosystem. In recent decades, tropical forests have also become one of the globe's most threatened biomes, subjected to exceptionally high rates of deforestation and land degradation. Thus, the importance of and threats to tropical forests are undeniable, yet our understanding of basic ecosystem processes in both intact and disturbed portions of the moist tropics remains poorer than for almost any other major biome. Our approach in this project was to take a multi-scale, multi-tool approach to address two different problems. First, we wanted to test if land-use driven changes in the cycles of probable limiting nutrients in forest systems were a key driver in the frequently observed pattern of declining pasture productivity and carbon stocks. Given the enormous complexity of land use change in the tropics, in which one finds a myriad of different land use types and intensities overlain on varying climates and soil types, we also wanted to see if new remote sensing techniques would allow some novel links between parameters which could be sensed remotely, and key biogeochemical variables which cannot. Second, we addressed to general questions about the role of tropical forests in the global carbon cycle. First, we used a new approach for quantifying and minimizing non-biological artifacts in the NOAA/NASA AVHRR Pathfinder time series of surface reflectance data so that we could address potential links between Amazonian forest dynamics and ENSO cycles. Second, we showed that the disequilibrium in C-13 exchanged between land and atmosphere following tropical deforestation probably has a significant impact on the use of 13-CO2 data to predict regional fluxes in the global carbon cycle.

Townsend, Alan R.↗
DOE OSTI2022

Detecting Hot Spots of Methane Flux Using Footprint‐Weighted Flux Maps

Abstract In this study, we propose a new technique for mapping the spatial heterogeneity in gas exchange around flux towers using flux footprint modeling and focusing on detecting hot spots of methane (CH 4 ) flux. In the first part of the study, we used a CH 4 release experiment to evaluate three common flux footprint models: the Hsieh model (Hsieh et al., 2000), the Kljun model (Kljun et al., 2015), and the K & M model (Kormann and Meixner, 2001), finding that the K & M model was the most accurate under these conditions. In the second part of the study, we introduce the Footprint‐Weighted Flux Map, a new technique to map spatial heterogeneity in fluxes. Using artificial CH 4 release experiments, natural tracer approaches and flux chambers we mapped the spatial flux heterogeneity, and detected and validated a hot spot of CH 4 flux in a oligohaline restored marsh. Through chamber measurements during the months of April and May, we found that fluxes at the hot spot were on average as high as 6589 ± 7889 nmol m −2 s −1 whereas background flux from the open water were on average 15.2 ± 7.5 nmol m −2 s −1 . This study provides a novel tool to evaluate the spatial heterogeneity of fluxes around eddy‐covariance towers and creates important insights for the interpretation of hot spots of CH 4 flux, paving the way for future studies aiming to understand subsurface biogeochemical processes and the microbiological conditions that lead to the occurrence of hot spots and hot moments of CH 4 flux.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Hydrobiogeochemical Controls on the Delivery of Dissolved Organic Matter to Boreal Headwater Streams

Understanding controls on the delivery of dissolved organic matter (DOM) from terrestrial to aquatic systems is key for constraining carbon balances and fluxes in boreal headwater catchments. The largest export of DOM generally occurs during intense periods of water delivery to the landscape (e.g., rain events); however, the timing and magnitude of DOM is complicated by geomorphological, hydrometeorological, and biogeochemical variability. To better assess mechanisms controlling the delivery of DOM to boreal streams, DOM was investigated in two morphologically distinct catchments of an experimental forest watershed in western Newfoundland, one dominated by low relief wetlands and the other by steep hillslopes. The DOM was compared during two fall storms of similar magnitude but contrasting moisture conditions during the autumn transition. Variable concentrations and optical character highlighted antecedent conditions are important for the delivery of DOM to boreal streams. Concentration-discharge relationships with stream hydrograph separation analysis suggest preferential flowpaths through shallow mineral horizons as a key pathway for delivery of DOM in the hillslope dominated catchment compared to rapid input from near-stream wetlands in the low relief catchment. Loss of DOM via preferential pathways suggests an additional mechanism for surface soil carbon loss not directly informed by lateral flow and soil hydrology, which has important implications for our conceptualization and modeling of carbon fluxes in boreal systems. These results suggest watershed scale responses of DOM in boreal headwater catchments are complex, and better linkages between catchment scale hydrology and landscape hydrobiogeochemistry are required to constrain terrestrial to aquatic carbon fluxes in boreal landscapes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Data sets for Unraveling Iron Oxides as Abiotic Catalysts of Organic Phosphorus Recycling in Soil and Sediment Matrices

In biogeochemical phosphorus cycling, iron oxide minerals are acknowledged as strong adsorbents of inorganic and organic phosphorus species. The dephosphorylation of organic phosphorus is attributed only to biological processes, but iron oxides could also catalyze this hydrolytic cleavage. Limited evidence of this abiotic catalysis has relied on monitoring inorganic phosphate in solution, thereby ignoring iron oxides as both catalysts and adsorbents. Here we apply high-resolution mass spectrometry and X-ray absorption spectroscopy to characterize dissolved and particulate phosphorus species, respectively. In soil and sediment samples reacted with ribonucleotides, we uncover the abiotic production of particulate inorganic phosphate associated specifically with iron oxides. Experiments with various organic phosphorus compounds revealed up to 12-fold greater catalytic and adsorption reactivities with iron oxides than with the silicate and aluminosilicate minerals identified in the environmental samples. Remarkably, we obtained dephosphorylation rates by the iron oxides that are within reported enzymatic rates in soils. However, phosphorus cycle models do not yet include a quantitative account of the abiotic evolution of inorganic phosphate from organic phosphorus trapped on iron oxides in environmental matrices. Our findings imply a missing abiotic axiom for organic phosphorus mineralization in the phosphorus cycle.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Reviews and syntheses: Opportunities for robust use of peak intensities from high-resolution mass spectrometry in organic matter studies

Abstract. Earth's biogeochemical cycles are intimately tied to the biotic and abiotic processing of organic matter (OM). Spatial and temporal variations in OM chemistry are often studied using direct infusion, high-resolution Fourier transform mass spectrometry (FTMS). An increasingly common approach is to use ecological metrics (e.g., within-sample diversity) to summarize high-dimensional FTMS data, notably Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS). However, problems can arise when FTMS peak-intensity data are used in a way that is analogous to abundances in ecological analyses (e.g., species abundance distributions). Using peak-intensity data in this way requires the assumption that intensities act as direct proxies for concentrations. Here, we show that comparisons of the same peak across samples (within-peak) may carry information regarding variations in relative concentration, but comparing different peaks (between-peak) within or between samples does not. We further developed a simulation model to study the quantitative implications of using peak intensities to compute ecological metrics (e.g., intensity-weighted mean properties and diversity) that rely on information about both within-peak and between-peak shifts in relative abundance. We found that, despite analytical limitations in linking concentration to intensity, ecological metrics often perform well in terms of providing robust qualitative inferences and sometimes quantitatively accurate estimates of diversity and mean molecular characteristics. We conclude with recommendations for the robust use of peak intensities for natural organic matter studies. A primary recommendation is the use and extension of the simulation model to provide objective guidance on the degree to which conceptual and quantitative inferences can be made for a given analysis of a given dataset. Broad use of this approach can help ensure rigorous scientific outcomes from the use of FTMS peak intensities in environmental applications.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Calibration, measurement, and characterization of soil moisture dynamics in a central Amazonian tropical forest

Soil moisture plays a key role in hydrological, biogeochemical, and energy budgets of terrestrial ecosystems. Accurate soil moisture measurements in remote ecosystems such as the Amazon are difficult and limited because of logistical constraints. Time domain reflectometry (TDR) sensors are widely used to monitor soil moisture and require calibration to convert the TDR's dielectric permittivity measurement (K a ) to volumetric water content (θ v ). In this study, our objectives were to develop a field-based calibration of TDR sensors in an old-growth upland forest in the central Amazon, to evaluate the performance of the calibration, and then to apply the calibration to determine the dynamics of soil moisture content within a 14.2 -m-deep vertical soil profile. Depth-specific TDR calibration using local soils in a controlled laboratory setting yielded a novel K a –θ v third-degree polynomial calibration. The sensors were later installed to their specific calibration depth in a 14.2-m pit. The widely used K a –θ v relationship (Topp model) underestimated the site-specific θ v by 22–42%, indicating significant error in the model when applied to these well-structured, clay-rich tropical forest soils. The calibrated wet- and dry-season θ v data showed a variety of depth and temporal variations highlighting the importance of soil textural differentiation, root uptake depths, as well as event to seasonal precipitation effects. Data such as these are greatly needed for improving our understanding of ecohydrological processes within tropical forests and for improving models of these systems in the face of changing environmental conditions.

54 ENVIRONMENTAL SCIENCES↗