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Data and scripts associated with “Point-scale organic-matter decomposition in streambeds is weakly associated with reach-scale respiration”

This data package is associated with “Point-scale organic-matter decomposition in streambeds is weakly associated with reach-scale respiration” published in EGU Biogeosciences (Stegen et al., 2026; https://doi.org/10.5194/bg-23-3981-2026). It contains cotton strip decomposition rates (Kcd and Kdd) collected across the Yakima River Basin (YRB), Washington, USA. These data were collected to support a broader study examining the drivers of spatial variability in sediment respiration rates in the Yakima River Basin. Associated data used in analysis, metadata, and field protocols can be accessed at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1923689, https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1969566, and https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1987520. This data package is associated with the repository found at https://github.com/river-corridors-sfa/rcsfa-ST-2B-SSS-cotton-strip. A preliminary version of this data package was published in December 2025 at the time of manuscript submission. It was updated in June 2026, at the time of manuscript acceptance, to include additional metadata (this readme, data dictionary, and file level metadata). The data did not change. 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. This data package consists of (1) readme; (2) data dictionary (dd); (3) file level metadata (flmd); and (4) four folders: (1) R-scripts; (2) figures; (3) outputs from the scripts; and (4) published data. The published data folder contains a readme directing the user to download data in order to run the R-scripts. All files are .csv, .pdf, .R, .Rmd, and .txt. We acknowledge the Yakama Nation as owners and caretakers of the lands where we collected 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↗

Spatial Study 2022: Surface Water Samples, Cotton Strip Degradation, and Hydrologic Sensor Data across the Yakima River Basin, Washington, USA (v3)

This dataset supports a broader study examining the drivers of spatial variability in sediment respiration rates in the Yakima River Basin. The dataset provides data and photos generated from sample collection during the same one-week period at 48 sites within multiple rivers throughout the Yakima River Basin in Washington, USA. The contents include surface water geochemistry data; river substrate grain size photos; stream depth data; manual chamber open channel respiration data; and field metadata (including qualitative information on instream and river corridor characteristics). Grain size photos can be used to improve estimates of channel substrate D50 data. The dataset also includes tensile strength and photos from cotton strip field degradation experiments; five-week sensor time series temperature, dissolved oxygen, pressure, pH, specific conductance, chlorophyll A, and turbidity data; plots of the sensor data; and R scripts used to generate the plots. Samples collected during this study were labeled as “Second Spatial Study” or “SSS.” A subset of data from the SSS samples were published in the contiguous United States (CONUS)-Scale Model-Sample (CM) study data package available at https://data.ess-dive.lbl.gov/view/doi:10.15485/1923689 that presents data from across the CONUS. SSS data published in the CM data package were not included in this data package. They include dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC), total nitrogen (TN), grain size, aerobic sediment respiration, dissolved oxygen (DO), and temperature. Parent IDs and Site IDs are consistent between the SSS and CM data packages, and they can be mapped directly so data across packages can be used together. Additionally, sensor data from a similar 2021 spatial study can be found at https://data.ess-dive.lbl.gov/view/doi:10.15485/1892052 and 2021 sample data can be found at https://data.ess-dive.lbl.gov/view/doi:10.15485/1898914. The 2021 spatial study had some sites in common with this 2022 spatial study. This dataset is comprised of three photo folders and one main data folder with six subfolders. The photo folders contain photographs and videos of cotton strip retrieval and sediment quadrats. The main data folder consists of (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) total suspended solids (TSS) data and cotton strip tensile strength data and averages; (5) field protocol; (6) readme; (7) methods codes; (8) international generic sample number (IGSN) mapping file; (9) sensor installation methods summary; (10) stream depth and averages; and (11) Ultrameter data and averages. The Sonar subfolder consists of Sonar time-series depth data and a processing script. The BarotrollAtm, DepthHOBO, MantaRiver, miniDOT, and miniDOTManualChamber subfolders contain time-series data, plots, and summary files. All files are .csv, .pdf, .txt, .R, .Rmd, .jpg, .jpeg, .AVI, .mp4, or .mov. The data package was originally published in April 2023. It was updated in August 2023 (v2; modified files) and September 2024 (v3; modified files). See the change history section in the readme for details. We acknowledge the Yakama Nation as owners and caretakers of the lands where we collected 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↗

Anaerobic respiration pathways and response to increased substrate availability of Arctic wetland soils

The availability of labile carbon (C) compounds in Arctic wetland soils is expected to increase due to thawing permafrost and increased fermentation as a result of decomposition of organic matter with warming. How microbial communities respond to this change will affect the balance of CO 2 and CH 4 emitted during anaerobic organic matter decomposition, and ultimately the net radiative forcing of greenhouse gas emissions from these soils. While soil water content limits aerobic respiration, the factors controlling methanogenesis and anaerobic respiration are poorly defined in suboxic Arctic soils. In this study, we conducted incubation experiments on two tundra soils from field sites on the Seward Peninsula, Alaska, with contrasting pH and geochemistry to determine the pathways of anaerobic microbial respiration and changes with increasing substrate availability upon warming. In incubation of soils from the circumneutral Teller site, the ratio of CO 2 to CH 4 dropped from 10 to <2 after 60 days, indicating rapid depletion of alternative terminal electron acceptors (TEAs). Addition of acetate stimulated production of CO 2 and CH 4 in a nearly 1:1 ratio, consistent with methanogenesis, and the composition of the microbial community shifted to favor clades capable of utilizing the added acetate such as the Fe(III)-reducing Geobacter and the methanogenic archaea Methanosarcina. In contrast, both CO 2 and CH 4 production declined with acetate addition during incubation of soils from the more acidic Council site, and fermentative microorganisms increased in abundance despite the high availability of fermentation products. These results demonstrate that the degree to which increasing substrate availability stimulates greenhouse gas production in tundra wetlands will vary widely depending on soil pH and geochemistry.

54 ENVIRONMENTAL SCIENCES↗

Exploring the determinants of organic matter bioavailability through substrate-explicit thermodynamic modeling

Microbial decomposition of organic matter (OM) in river corridors is a major driver of nutrient and energy cycles in natural ecosystems. Recent advances in omics technologies enabled high-throughput generation of molecular data that could be used to inform biogeochemical models. With ultrahigh-resolution OM data becoming more readily available, in particular, the substrate-explicit thermodynamic modeling (SXTM) has emerged as a promising approach due to its ability to predict OM degradation and respiration rates from chemical formulae of compounds. This model implicitly assumes that all detected organic compounds are bioavailable, and that aerobic respiration is driven solely by thermodynamics. Despite promising demonstrations in previous studies, these assumptions may not be universally valid because OM degradation is a complex process governed by multiple factors. To identify key drivers of OM respiration, we performed a comprehensive analysis of diverse river systems using Fourier-transform ion cyclotron resonance mass spectrometry OM data and associated respiration measurements collected by the Worldwide Hydrobiogeochemistry Observation Network for Dynamic River Systems (WHONDRS) consortium. In support of our argument, we found that the incorporation of all compounds detected in the samples into the SXTM resulted in a poor correlation between the predicted and measured respiration rates. The data-model consistency was significantly improved by the selective use of a small subset (i.e., only about 5%) of organic compounds identified using an optimization method. Through a subsequent comparative analysis of the subset of compounds (which we presume as bioavailable) against the full set of compounds, we identified three major traits that potentially determine OM bioavailability, including: (1) thermodynamic favorability of aerobic respiration, (2) the number of C atoms contained in compounds, and (2) carbon/nitrogen (C/N) ratio. We found that all three factors serve as “filters” in that the compounds with undesirable properties in any of these traits are strictly excluded from the bioavailable fraction. This work highlights the importance of accounting for the complex interplay among multiple key traits to increase the predictive power of biogeochemical and ecosystem models.

59 BASIC BIOLOGICAL SCIENCES↗

Generalizing Microbial Parameters in Soil Biogeochemical Models: Insights From a Multi‐Site Incubation Experiment

Abstract Incorporating microbial processes into soil biogeochemical models has received growing interest. However, determining the parameters that govern microbially driven biogeochemical processes typically requires case‐specific model calibration in various soil and ecosystem types. Here each case refers to an independent and individual experimental unit subjected to repeated measurements. Using the Microbial‐ENzyme Decomposition model, this study aimed to test whether a common set of microbially‐relevant parameters (i.e., generalized parameters) could be obtained across multiple cases based on a two‐year incubation experiment in which soil samples of four distinct soil series (i.e., Coland, Kesswick, Westmoreland, and Etowah) collected from forest and grassland were subjected to cellulose or no cellulose amendment. Results showed that a common set of parameters controlling microbial growth and maintenance as well as extracellular enzyme production and turnover could be generalized at the soil series level but not land cover type. This indicates that microbial model developments need to prioritize soil series type over plant functional types when implemented across various sites. This study also suggests that, in addition to heterotrophic respiration and microbial biomass data, extracellular enzyme data sets are needed to achieve reliable microbial‐relevant parameters for large‐scale soil model projections.

58 GEOSCIENCES↗

WHONDRS River Corridor Sediment and Water Geochemistry and In Situ Sensor Data from 7 Perennial and 7 Intermittent Streams across San Antonio, Texas (v3)

This dataset supports a broader study examining the effects of intermittency on sediment respiration. The dataset provides sediment and surface water geochemistry and in situ sensor data from 7 perennial and 7 intermittent streams in San Antonio, Texas. Each stream/site was visited both in summer during base flow (July-September 2023) and winter during peak flow (January-February 2024). Related data were collected and will be published separately in collaboration with A. Veach. The data package was originally published in April 2025. It was updated in June 2025 (v2; modified and new files) and September 2025 (v3; modified files). See the change history section in the readme for more details. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. This dataset is comprised of two folders of field photos and videos, one folder of raw Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) data and one main data folder containing (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) readme; (5) international generic sample number (IGSN) mapping file; (6) field protocol; (7) a subfolder with sample data; and (8) a subfolder with sensor data. The sample data subfolder contains (1) surface water and sediment dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC) data and averages; (2) surface water and sediment total nitrogen data and averages; (3) sediment grain size data; (4) sediment iron (II) data and averages; (5) wet sediment mass, dry sediment mass, water mass, and wet sediment volume in incubation and sediment ICR vials; (7) sediment incubation respiration rate data and averages; (8) normalized respiration rate data and averages; (9) methods codes; (10) sediment percent carbon and nitrogen; (11) sediment X-ray diffraction (XRD) data; (12) gravimetric moisture and averages; (13) a subfolder with sediment incubation respiration data, scripts, and plots; (14) surface water and sediment FTICR methods; and (15) a subfolder of 9.4 Tesla (9.4T) FTICR-MS data. This folder contains five subfolders, one containing the sediment .xml data files, one containing the water .xml files, one containing the sediment CoreMS output files, one containing the water CoreMS output files, and the other containing instructions and scripts for processing the files in CoreMS (https://github.com/EMSL-Computing/CoreMS). The sensor data subfolder contains (1) a subfolder with miniDOT dissolved oxygen and temperature data and plots; (2) miniDOT dissolved oxygen and temperature summary data; and (3) miniDOT installation methods. All files are .csv, .pdf, .R, .xml, .d, .html, .Rmd, .py, .cal, .json, .jpg, .jpeg, .png, .mov, or .mp4. CORRECTION: The data processing methods for FTICR described in “v3_WHONDRS_AV1_Methods_Codes.csv” mistakenly indicate that users should process the data in Formultitude. The corrected description should read: “Both unprocessed and processed data are provided to allow users flexibility in data processing. Instructions and scripts for processing the data using CoreMS are included.” CORRECTION: Carbon and nitrogen content are reported as percentages. The current column headers "01395_C_percent_per_mg" and "01397_N_percent_per_mg" are incorrect. These should read "01395_C_percent" and "01397_N_percent" and will be corrected in the next version of this data package.

54 ENVIRONMENTAL SCIENCES↗

Respirable particulate monitoring with remote sensors. (Public health ecology: Air pollution)

The feasibility of monitoring atmospheric aerosols in the respirable range from air or space platforms was studied. Secondary reflectance targets were located in the industrial area and near Galveston Bay. Multichannel remote sensor data were utilized to calculate the aerosol extinction coefficient and thus determine the aerosol size distribution. Houston Texas air sampling network high volume data were utilized to generate computer isopleth maps of suspended particulates and to establish the mass loading of the atmosphere. In addition, a five channel nephelometer and a multistage particulate air sampler were used to collect data. The extinction coefficient determined from remote sensor data proved more representative of wide areal phenomena than that calculated from on site measurements. It was also demonstrated that a significant reduction in the standard deviation of the extinction coefficient could be achieved by reducing the bandwidths used in remote sensor.

Severs, R. K.↗

Cardiopulmonary Inflammatory Response to Meteorite Dust Exposures - Implications for Human Health on Earth and Beyond

This year marks the 50th anniversary of Apollo 11, the first time humans set foot on the Moon. The Apollo missions not only help answer questions related to our solar system, they also highlight many hazards associated with human space travel. One major concern is the effect of extraterrestrial dust on astronaut health. In an effort to expand upon previous work indicating lunar dust is respirable and reactive, the authors initiated an extensive study evaluating the role of a particulate’s innate geochemical features (e.g., bulk chemistry, internal composition, morphology, size, and reactivity) in generating adverse toxicological responses in vitro and in vivo. To allow for a broader planetary and geochemical assessment, seven samples were evaluated: six meteorites from either the Moon, Mars, or Asteroid 4 Vesta and a terrestrial basalt analogue. Even with the relatively small geochemical differences (all samples basaltic in nature), significant difference in cardiopulmonary inflammatory markers developed in both single exposure and multiple exposure studies. More specifically: 1) the single exposure studies reveal relationships between toxicity and a meteorite sample’s origin, its pre-ejected state (weathered versus un-weathered), and geochemical features (e.g. bulk iron content) and 2) multiple exposure studies reveal a correlation with particle derived reactive oxygen species (ROS) formation and neutrophil infiltration. Extended human exploration will further increase the probability of inadvertent and repeated exposures to extraterrestrial dusts. This comprehensive dataset allows for not only the toxicological evaluation of extraterrestrial materials but also clarifies important correlations between geochemistry and health. The utilization of an array of extraterrestrial samples from Moon, Mars, and asteroid 4Vesta will enable the development of a geochemical based toxicological hazard model that can be used for: 1) mission planning, 2) rapid risk assessment in cases of unexpected exposures, and 3) evaluation of the efficacy of various in situ techniques in gauging surface dust toxicity. Furthermore, by better understanding the importance of geochemical features on exposure related health outcomes in space, it is possible to better understand of the deleterious nature of dust exposure on Earth.

Harrington, A. D.↗

Biome-scale temperature sensitivity of ecosystem respiration revealed by atmospheric CO2 observations

Abstract The temperature sensitivity of ecosystem respiration regulates how the terrestrial carbon sink responds to a warming climate but has been difficult to constrain observationally beyond the plot scale. Here we use observations of atmospheric CO 2 concentrations from a network of towers together with carbon flux estimates from state-of-the-art terrestrial biosphere models to characterize the temperature sensitivity of ecosystem respiration, as represented by the Arrhenius activation energy, over various North American biomes. We infer activation energies of 0.43 eV for North America and 0.38 eV to 0.53 eV for major biomes therein, which are substantially below those reported for plot-scale studies (approximately 0.65 eV). This discrepancy suggests that sparse plot-scale observations do not capture the spatial-scale dependence and biome specificity of the temperature sensitivity. We further show that adjusting the apparent temperature sensitivity in model estimates markedly improves their ability to represent observed atmospheric CO 2 variability. This study provides observationally constrained estimates of the temperature sensitivity of ecosystem respiration directly at the biome scale and reveals that temperature sensitivities at this scale are lower than those based on earlier plot-scale studies. These findings call for additional work to assess the resilience of large-scale carbon sinks to warming.

54 ENVIRONMENTAL SCIENCES↗

Interactions among soil texture, pore structure, and labile carbon influence soil carbon gains

Perennial vegetation with high plant diversity, e.g., restored prairie, is known for stimulation of soil carbon (C) gains, due in part to enhanced formation of pore structure beneficial for long-term C storage. However, the prevalence of this phenomenon across soils of different types remains poorly understood. The aim of the study was to assess the associations between pore structure, soil C, and their differences in monoculture switchgrass and polyculture restored prairie vegetation across a wide range of soils dominating the Upper Midwest of the USA. Six experimental sites were sampled, representing three soil types with texture ranging from sandy to silt loams. The two vegetation systems studied at each site were (i) monoculture switchgrass (Panicum virgatum L.), and (ii) polyculture restored prairie, also containing switchgrass as one of its species. X-ray computed micro-tomography (µCT) was employed to analyze soil pore structure. Structural equation modeling and multiple path analyses were used to assess direct and indirect effects of soil texture and pore characteristics on microbial biomass C (MBC), particulate organic matter (POM), dissolved organic C (DOC), short-term respiration (CO 2 ), and, ultimately, soil organic C (SOC). Across studied sites, prairie increased fractions of medium (50–150 µm Ø) pores by 11–45 %, SOC by 3–69 %, and MBC by 18–59 % (except for one site). The greater were the prairie-induced increases in the medium pore volumes, the greater were the prairie-induced SOC gains. Greater C losses via CO 2 and DOC contributed to slower C accumulation in the prairie soil. We surmise that the interactive feedback loop relating medium pores and soil C acts across a wide range of soil textures and is an important mechanism through which perennial vegetation with high plant diversity, such as restored prairie, promotes rapid SOC gains.

54 ENVIRONMENTAL SCIENCES↗

Data and Scripts Associated with the Manuscript “Water Column Respiration in the Yakima River Basin is Explained by Temperature, Nutrients and Suspended Solids”

This data package is associated with the publication “Water Column Respiration in the Yakima River Basin is Explained by Temperature, Nutrients and Suspended Solids” published in EGU Biogeochemistry (Laan et al. 2025). In this research, water column respiration (ERwc) data, surface water chemistry data, organic matter (OM) chemistry data, and publicly available geospatial data were used in analysis to evaluate the variability in ERwc at 47 sites across the Yakima River basin in Washington, USA. In addition to this 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 includes the data inputs, and outputs, and R scripts to reproduce all the analyses performed in the manuscript and create manuscript figures. The data package is comprised of three main folders (Code, Data, and Figures). The Code folder is comprised of four scripts and three analysis-specific subfolders that contain the R scripts to perform the analyses described in the publication and create publication figures. The Data folder is comprised of two “.csv” files and four subfolders that contain data input and output files. The Published_Data folder contains a readme that directs the user to download the appropriate files and add to this folder when using scripts. The Figures folder includes figures from the manuscript in “.pdf” and “.png” formats and a folder with intermediate figure files. This data package is associated with a GitHub repository which can be found at https://github.com/river-corridors-sfa/rcsfa-RC2-SPS-ERwc. 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↗

Temporal Study 2021-2022: Sensor-Based Time Series of Surface Water Temperature, Specific Conductance, Total Dissolved Solids, Turbidity, pH, and Dissolved Oxygen from across Multiple Watersheds in the Yakima River Basin in Washington, USA (v2)

This dataset supports a broader study examining the drivers of temporal variability in sediment respiration rates in the Yakima River Basin. The dataset provides periodic (weekly or biweekly) in situ hydrological and water chemistry sensor data, handheld sensor water chemistry data, general environmental context photos, and field metadata collected at six sites within multiple rivers in the Yakima River Basin in Washington, USA. In addition to the sensor data, there are plots of continuous in situ sensor data and R scripts used to generate the plots. Related sample-based water chemistry data are published separately at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1898912.The data package was originally published in September 2022. It was updated in June 2025 (v2; modified files). See the change history section in the readme for more details. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. This dataset is comprised of one main data folder containing two sensor-specific subfolders, and one photographs folder. The main data folder includes file-level metadata (flmd), data dictionary (dd), installation methods, field metadata, handheld sensor data, field data collection protocols, international generic sample number (IGSN) mapping file, and a readme file. Each sensor subfolder (BarotrollAtm and MantaRiverData) contains a subfolder containing sensor timeseries data and plots. The BarotrollAtm Data subfolder contains In Situ Rugged BaroTROLL sensor pressure and air temperature data. The MantaRiverData subfolder contains Eureka Manta+ 35B multisonde temperature, specific conductance, and turbidity. The FieldPhotos folder contains environmental context photographs and videos. All files are .csv, .pdf, .R, .jpg, .jpeg, .heic, .mov, or .mp4.

54 ENVIRONMENTAL SCIENCES↗

Sleep and Respiration in Microgravity

Sleep is often reported to be of poor quality in microgravity, and studies on the ground have shown a strong relationship between sleep-disordered breathing and sleep disruption. During the 16-day Neurolab mission, we studied the influence of possible changes in respiratory function on sleep by performing comprehensive sleep recordings on the payload crew on four nights during the mission. In addition, we measured the changes in the ventilatory response to low oxygen and high carbon dioxide in the same subjects during the day, hypothesizing that changes in ventilatory control might affect respiration during sleep. Microgravity caused a large reduction in the ventilatory response to reduced oxygen. This is likely the result of an increase in blood pressure at the peripheral chemoreceptors in the neck that occurs when the normally present hydrostatic pressure gradient between the heart and upper body is abolished. This reduction was similar to that seen when the subjects were placed acutely in the supine position in one-G. In sharp contrast to low oxygen, the ventilatory response to elevated carbon dioxide was unaltered by microgravity or the supine position. Because of the similarities of the findings in microgravity and the supine position, it is unlikely that changes in ventilatory control alter respiration during sleep in microgravity. During sleep on the ground, there were a small number of apneas (cessation of breathing) and hypopneas (reduced breathing) in these normal subjects. During sleep in microgravity, there was a reduction in the number of apneas and hypopneas per hour compared to preflight. Obstructive apneas virtually disappeared in microgravity, suggesting that the removal of gravity prevents the collapse of upper airways during sleep. Arousals from sleep were reduced in microgravity compared to preflight, and virtually all of this reduction was as a result of a reduction in the number of arousals from apneas and hypopneas. We conclude that any sleep disruption in microgravity is not the result of respiratory factors.

West, John B.↗

Temporal Study 2022-2024: Sensor-Based Time Series of Surface Water Temperature, Specific Conductance, Total Dissolved Solids, Turbidity, Chlorophyll A, and Dissolved Oxygen from across Multiple Watersheds in the Yakima River Basin in Washington, USA

This dataset supports a broader study examining the drivers of temporal variability in sediment respiration rates in the Yakima River Basin. The dataset provides periodic (bi-weekly or monthly) in situ hydrological and water chemistry sensor data, handheld sensor water chemistry data, general environmental context photos, and field metadata collected at six sites across the Yakima River Basin in Washington, USA. Sample and sensor data from previous years (2021-2022) can be found at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1898912 and https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1892054, respectively. Related sample data from 2022-2024 are available at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/2562910. 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 This dataset contains a folder of environmental context photographs and videos and (1) file-level metadata; (2) data dictionary; (3) readme; (4) field metadata; (5) field protocols; (6) international generic sample number (IGSN) mapping file; (7) handheld sensor data; and (8) two sensor subfolders. Each sensor subfolder (BarotrollAtm and MantaRiverData) contains a subfolder containing sensor time series data and plots. The BarotrollAtm Data subfolder contains In Situ Rugged BaroTROLL sensor pressure and air temperature data. The MantaRiverData subfolder contains Eureka Manta+ 35B multisonde temperature, specific conductance, and chlorophyll A. All files are .csv, .pdf, .jpg, .jpeg, .mp4, .png, or .mov.

54 ENVIRONMENTAL SCIENCES↗

Tundra Underlain By Thawing Permafrost Persistently Emits Carbon to the Atmosphere Over 15 Years of Measurements

Warming of the Arctic can stimulate microbial decomposition and release of permafrost soil carbon (C) as greenhouse gases, and thus has the potential to influence climate change. At the same time, plant growth can be stimulated and offset C release. This study presents a 15-year time series comprising chamber and eddy covariance measurements of net ecosystem C exchange in a tundra ecosystem in Alaska where permafrost has been degrading due to regional warming. The site was a carbon dioxide source to the atmosphere with a cumulative total loss of 781.6 g C m -2 over the study period. Both gross primary productivity (GPP) and ecosystem respiration (R eco ) were already likely higher than historical levels such that increases in R eco losses overwhelmed GPP gains in most years. This shift to a net C source to the atmosphere likely started in the early 1990s when permafrost was observed to warm and thaw at the site. Shifts in the plant community occur more slowly and are likely to constrain future GPP increases as compared to more rapid shifts in the microbial community that contribute to increased Reco. Observed rates suggest that cumulative net soil C loss of 4.18–10.00 kg C m -2 —8%–20% of the current active layer soil C pool—could occur from 2020 to the end of the century. This amount of permafrost C loss to the atmosphere represents a significant accelerating feedback to climate change if it were to occur at a similar magnitude across the permafrost region.

54 ENVIRONMENTAL SCIENCES↗

Temporal Study 2021-2022: Sample-Based Surface Water Chemistry and Organic Matter Characterization across Watersheds in the Yakima River Basin, Washington, USA (v3)

This dataset supports a broader study examining the drivers of temporal variability in sediment respiration rates in the Yakima River Basin. The dataset provides geochemistry and organic matter characterization data generated from samples collected at weekly or bi-weekly intervals at six sites across the Yakima River Basin in Washington, USA. Related sensor data will be published separately and can be used to link sediment respiration rates to biogeochemical processing rates. The data package was originally published in November 2022. It was updated in November 2023 (v2; modified files) and April 2025 (new and modified files). See the change history section in readme for more details. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. This dataset is comprised of one main data folder containing (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) dissolved inorganic carbon (DIC), dissolved organic carbon (DOC; reported as non-purgeable organic carbon; NPOC), total nitrogen (TN), total suspended solids (TSS), and ions; (5) averaged values from water chemistry data; (6) surface water sampling protocol; (7) sensor protocol; (8) readme; (9) methods codes; (10) international generic sample number (IGSN) mapping file; and (11) folder of high resolution characterization of organic via 12 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory). This folder contains two subfolders, one containing the .xml data files and the other containing instructions for using Formularity (https://omics.pnl.gov/software/formularity) and an R script to process the data based on the user's specific needs. All files are .csv, .pdf, .R, .ref, or .xml. We acknowledge the Yakama Nation as owners and caretakers of the lands where we collected our 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↗