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Results for “EARTH SCIENCE > AGRICULTURE > SOILS > SOIL RESPIRATION”

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Remote Sensing and GIS data at 1km-grid over Chesapeake Bay used in “He et al. 2024, Effects of spatial variability in vegetation phenology, climate, landcover, biodiversity, topography, and soil property on soil respiration across a coastal ecosystem”

The package contains the data layers used in “He et al. 2024, Effects of spatial variability in vegetation phenology, climate, landcover, biodiversity, topography, and soil property on soil respiration across a coastal ecosystem”. The study aims to use multi-source remote sensing and GIS datasets to investigate the spatial heterogeneity and identify spatial zones with similar environmental characteristics and understand the primary driving factors affecting soil respiration within sub-ecosystems of the coastal ecosystem. We employed unsupervised hierarchical clustering analysis to identify spatial regions with distinct environmental characteristics, then determined the main driving factors using Random Forest regression and SHapley Additive exPlanations (SHAP). Spatial data layers include soil respiration, kernel Normalized Difference Vegetation Index (kNDVI) computed from Harmonized Landsat 8 and Sentinel-2 time series, climate variables from the Daymet dataset, land cover, biodiversity, topographical metrics, soil property, and tidal elevation.

54 ENVIRONMENTAL SCIENCES↗

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

This dataset contains processed data from a combination of survey flux chambers and long-term automated flux chambers. Biweekly soil flux measurements were conducted from June 2023 through December 2025 at a longleaf pine restoration site in Georgetown, SC. Processed, QAQC’d data can be found in the file: 1_DATA_ESS_DOE_HR_RS_HB3_QAQC_Survey_Data_20260223.csv. Raw and working data files (.json, & .81x format) from LI-COR equipment are included for reference and can be accessed using SoilFluxPro software. CSV metadata files describe the raw data and modifications made using SoilFluxPro v5 and Matlab R2024b, as well as formatting and units for processed CSVs. Matlab code is included for reading in the processed CSVs. This research was performed as part of the project: “Improving models of stand and watershed carbon and water fluxes with more accurate representations of soil-plant-water dynamics in southern pine ecosystems”, which examines in part the effects hydraulic redistribution on soil efflux of carbon dioxide, water vapor and methane, as well as soil moisture and temperature in a southern pine ecosystem with sandy soils and high water table.

CARBON DIOXIDE FLUX↗

Patch-level CO2 and CH4 fluxes and porewater concentrations in experimental wetlands, 2 PPT saltwater intrusion simulations, Aug-Oct 2022: Louisiana

This dataset contains carbon dioxide (CO2) and methane (CH4) flux measurements from patches of wetland vegetation dominated by Typha domingensis and Panicum hemitomon, which were conducted to assess flux responses to acute saltwater intrusion. The measurements occurred before, during, and after simulated acute saltwater intrusion events of low concentrations of ~ 2 PPT. The measurements comprise gas fluxes from the wetland surface (i.e., soil-water column and vegetation) and fluxes from the soil-water column exclusively. These two sets of fluxes are separated into two files and are complemented with four more files containing porewater concentrations of CO2 and CH4 collected at 0-5 cm, 10-15 cm, and 20-25 cm depth increments, spectral indices measurements, biomass, and sediment elevation table measurements. The files can be opened with regular text editors or spreadsheet programs.

54 ENVIRONMENTAL SCIENCES↗

Patch-level CO2 and CH4 fluxes and porewater concentrations in experimental wetlands, 5 and 10 PPT saltwater intrusion simulations, Louisiana 2023-2024

This dataset containes carbon dioxide (CO2) and methane (CH4) flux measurements collected from wetland vegetation patches dominated by Typha domingensis and Panicum hemitomon to assess greenhouse gas flux responses to experimental saltwater intrusion (SWI) pulses. Measurements were conducted before, during, and after simulated SWI events at target salinities of approximately 5 parts per thousand (ppt) with durations of 6, 10, and 17 days and 10 ppt with a duration of 48 days, alongside a control wetland (with no salinity added, flood manipulation only). These data were generated to evaluate how the magnitude and duration of SWI alter wetland carbon exchange and related biogeochemical and plant responses. This data package includes flux measurements from the wetland surface (i.e, soil/water surface and enclosed vegetation) and from the soil/water surface only; porewater and surface water concentrations of CO2 and CH4; salinity, pH, electrical conductivity collected in porewater (at 5, 10, and 20 cm soil depths) and in surface water; soil redox potential; leaf spectral indices, leaf vapor pressure deficit, stomatal conductance; water level, salinity, and photosynthetically active radiation; and aboveground biomass.

EARTH SCIENCE > AGRICULTURE > SOILS > SOIL RESPIRA↗

Radiocarbon of soil CO2 efflux and soils with experimental soil warming and drying in lowland tropical forests in Panama

In 2019, we measured the Δ14C and δ13C of soil respired carbon dioxide (CO2) in Panamanian forests that are subject to either in situ experimental soil warming (4C above ambient temperature to 1.2 m depth) or in situ experimental drying (50% throughfall exclusion). The warming site and one drying site are both within the Barro Colorado Nature Monument in nearby and similar forests on similar soils, enabling direct comparison of warming and drying effects on soil CO2 efflux. A second drying experiment is on the northern side of the Panama Isthmus on infertile soils where mean annual precipitation is greater, representative of a broad geographic area of the tropics. Given the seasonality of these forests, we performed measurements at stages of the seasonal cycle for which we expected the largest variation in CO2 efflux between control and experimental plots based on previous studies – the wet season (October-December) and dry season (March/April) or dry-to-wet season transition (May). This dataset includes Δ14C and δ13C of in situ soil surface CO2 flux as well as CO2 flux rates, volumetric soil moisture, soil temperature, and calculated partitioning of the fraction of total soil respiration from heterotrophs vs roots at the time of isotope sampling in AllSites_SoilResp_14C_data.xlsx. This dataset also includes Δ14C and δ13C of bulk soil, density fractions, and CO2 respired during laboratory incubations in AllSites_bulk_soil14C.xlsx. Datafiles are also available in csv format.

54 ENVIRONMENTAL SCIENCES↗

Evaluating the Persistence of Soil Carbon After a 30-Year Nitrogen Fertilization Experiment at the Fernow Experimental Forest, WV

We sampled soils in a previously nitrogen (N)-fertilized watershed (Watershed 3), which received 35 kg N per hectare annually for 30 years, and a reference watershed (Watershed 7), 4 years after the end of a 30-year N fertilization experiment at the Fernow Experimental Forest in West Virginia. As N deposition has reduced soil pH and plant carbon (C) investments into the rhizosphere, we compared the extent to which removing these potential limitations to microbial decomposition by increasing soil pH, adding artificial root exudates, or elevating soil temperature would increase microbial decomposition (and soil C losses) in soils that have and have not received excess N inputs. As such, we incubated soils with and without the addition of artificial root exudates and dolomitic lime (2 amendment treatments and 1 untreated control), at three different temperatures (15, 20, and 25 C) to simulate warming. We measured soil respiration, enzyme activity (acid phosphatase, N -acetyl-β-glucosaminidase, beta-glucosidase, phenol oxidase, and peroxidase), and microbial biomass carbon in a 15-week microcosm experiment. All of the datasheets include the metadata for all of the treatment combinations from this incubation experiment (ID, incubation temperature, treatment, watershed).The "Soil_Chemistry_Data.csv" data includes (1) the ratio of dry soil weight (g) by wet (or fresh) soil weight (g) after 72 hours at 65 C, (2) the wet (or fresh) weight of the soil samples used to determine soil pH, and (3) soil pH, which was measured in CaCl2. Detailed methods for the measurements of soil pH are described in the datasheet itself.The "Respiration_Data.csv" data includes (1) respiration day for the measurement, and (2) cumulative CO2 respiration (mmol) measured in the microcosms on specific days.The "Microbial_Biomass_Data.csv" data includes (1) mmol microbial biomass carbon per g (dry weight) of soil in each microcosm.The "Enzyme_Data.csv" data includes (1) all extracellular soil enzyme activity (N-acetyl-glucosaminidase (NAG), acid phosphatase (AP), β-glucosidase (BG), phenol oxidase and peroxidase) that we measured in our microcosms.

54 ENVIRONMENTAL SCIENCES↗

Zero Resistance Ammetry (ZRA) Measurements of Sediment Electrochemical Gradients, Old Woman Creek, Ohio, USA, June–November 2022

This dataset contains raw and processed zero resistance ammetry (ZRA) measurements collected from wetland sediments at Old Woman Creek, a freshwater estuary on Lake Erie, Ohio, USA, between June and November 2022. Measurements were obtained using a vertically deployed electrode array positioned at multiple depths within the sediment profile to capture electrochemical gradients associated with microbial activity and sediment geochemistry. The raw dataset consists of parsed instrument log files containing timestamps, electrode pair identifiers, and measured electrical potential (mV). The processed dataset includes standardized and quality-controlled values with instrument saturation limits removed and timestamps converted to ISO 8601 format. Electrode line identifiers were mapped to physical depths, enabling interpretation of depth-resolved electrochemical gradients. Instrument saturation values (−2048, −2047, 2047, and 2048 mV) were identified as measurement limits and excluded from quantitative analyses. All data parsing, processing, and quality control steps are documented in an accompanying R Markdown script, ensuring full reproducibility from raw instrument logs to final datasets.

EARTH SCIENCE > AGRICULTURE > SOILS > ELECTRICAL C↗

Data for Regier et al. (2025), "Short-term experimental flooding impacts soil biogeochemistry but not aboveground vegetation in a coastal forest"

Rising sea levels and intensifying storms increase flooding pressure on coastal forests, but the mechanisms that drive coastal forest mortality remain unclear. This study used an ecosystem-scale manipulation (TEMPEST, Terrestrial Ecosystem Manipulation to Probe the Effects of Storm Treatments) to simulate hurricane-level flooding of a coastal forest and explore the individual and interactive impacts of inundation and salinity. This dataset comprises the results reported by Regier et al. (2025) in their paper "Short-term experimental flooding impacts soil biogeochemistry but not aboveground vegetation in a coastal forest." It consists of measurements of:- Belowground conductance- Soil dissolved oxygen and redox- Soil and tree greenhouse gas fluxes- Leaf photosynthesis, stomatal conductance, and intercellular carbon dioxide- Sap flux- Soil volumetric water content and electrical conductivityAll files are plain-text CSV (comma separated value) and no special software is required to read them.

54 ENVIRONMENTAL SCIENCES↗

Plant Characteristics, Porewater, Gas Flux, and Soil Biogeochemistry at Council Road Site Mile Marker 71, Seward Peninsula, Alaska, 2023

Data collected at Council, AK (64°51’35.0”N 163°41’59.1”W) during a summer campaign in 2023. Water data consists of soil porewater collected by centrifuging soil cores and also by field collection with porewater samplers (rhizons). Gas data consists of CO2, CH4 and N2O surface soil fluxes measured with a portable FTIR analyzer. Plant and root data consists of biomass, root length, diameter and mass. Soil data consists of total C and N. Air, water and soil samples span two main locations: a thermokarst wetland and an upland tussock. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).This dataset was generated to broadly address the following research question: how will climate change (i.e., thawing permafrost, landscape change) alter the ecosystem flux (sink versus source) of important greenhouse gases such as CO2, CH4 and N2O?Description of the contents of this data package: This dataset contains 5 different individual .csv files containing plant, soil, water and gas data. No software is needed to utilize them. PFTCover: Plant functional type ground cover in 1x1 meter plots. SoilCores: Solidphase and porewater phase soil biogeochemical variablesPlantData: Above and belowground plant traits. GasFlux: Surface plant-soil gas measurementsFieldPorewater: Field collected porewater biogeochemical variables

54 ENVIRONMENTAL SCIENCES↗

Data for Myers-Pigg et al. (2026), "Short-term coastal forest responses to a hurricane-scale freshwater and saltwater flooding experiment"

Coastal upland forests are exposed to intensifying precipitation regimes and sea level rise, increasing tree mortality and transforming these coastal forests into wetland ecosystems. Despite these well-known risks, the differing degrees to which hydrological, biogeochemical, and biological components of upland forests respond to novel salinity exposure is relatively unknown. The Terrestrial Ecosystem Manipulation to Probe the Effects of Storm Treatments (TEMPEST) experiment decouples two distinct disturbances associated with hydrological extremes: (1) flooding from heavy precipitation and (2) exposure to saline conditions from storm surge. This dataset includes data reported in Myers-Pigg et al. (2025), which analyzed data from the first TEMPEST flooding treatment in 2022. This includes: - Colored dissolved organic matter in porewaters - Soil temperature and oxygen - Groundwater temperature and chemistry - Dissolved organic carbon concentrations in porewaters - Soil-to-atmosphere CH4 and CO2 fluxes - Soil temperature, water content, and electrical conductivity - Root-influenced CH4 and CO2 flux - Tree sap flow velocity - The R analytical code and documentation about the computational environmental in which it was run (the "sessionInfo.txt" file) All data files are plain-text comma separated value (CSV) and no special software is required to read them.

54 ENVIRONMENTAL SCIENCES↗

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

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

CARBON DIOXIDE FLUX↗

Data for Zheng et al. (2025), "AquaMEND: Reconciling multiple impacts of salinization on soil carbon biogeochemistry"

Soil salinization, exacerbated by climate change, poses a global threat to coastal ecosystems and soil function. Salinity affects soil carbon cycling by directly impacting microbial activity and indirectly altering soil physicochemical properties, but current models inadequately represent these complexities. This dataset contains the observational and modeling data from Zheng et al. (2025), which described a process-based modeling framework that couples soil solution chemistry with microbial carbon cycling reactions to study the impacts of soil salinization. This conceptual model is implemented numerically into the open-source geochemical program PHREEQC 3.0 (Parkhurst and Appelo, 2013). This dataset consists of: - Figure2_AquaMEND_salinity_buffer: Contains model simulation outputs to assess the impact of three different cation exchange and surface complexation processes on salinity buffering (Fig. 2 from Zheng et al. 2025). - Figure3_Salinity_function: Contains salinity function fitting for literature data (Fig. 3 from Zheng et al. 2025). - Figure4_AquaMEND_microbial_mechanisms: Contains model simulation outputs for testing various microbial process-based hypotheses related to soil salinization, including microbial mortality, carbon use efficiency (CUE), extracellular enzyme activity, and other microbial mechanisms (Fig. 4 from Zheng et al. 2025). - Figure5_AquaMEND_Redox: Contains on model simulation outputs to evaluate shifts among key redox processes, such as aerobic respiration, sulfate reduction, and methanogenesis (Fig.5 from Zheng et al. 2025). - Figure6_AquaMEND_sorption: Contains on model simulation outputs for investigating the effects of salinity on dissolved organic matter (DOM) sorption and desorption processes (Fig. 6 from Zheng et al. 2025). - Figure7_AquaMEND_process_couple: Contains on model simulation outputs for exploring coupled biotic-abiotic processes and their interactions (Fig. 7 from Zheng et al. 2025). - data: Includes datasets used to develop salinity response functions and evaluate salinity buffering capacity. Datasets for MEND model calibration. - database: Contains the `.dat` file required by PHREEQC for model execution. - README.md: A Markdown plain text file describing the computational tools and directories. Files are a mixture of plain text CSV (comma-separated value) and plain text *.dat files written by the model; no special software is required to read them.

EARTH SCIENCE > AGRICULTURE > SOILS > SOIL SALINIT↗

Data from: Lowland Tropical Forests Remain a Methane Sink Under Warming and Long-Term Hurricane Disturbance Recovery

The repository folder contains spreadsheets and script for soil greenhouse gas (GHG) fluxes, soil moisture, soil temperature, air temperature, and precipitation measurements collected from the Tropical Responses to Altered Climate Experiment (TRACE) at the Sabana Research Field Station, El Yunque National Forest (USDA Forest Service; 18°19′28.74″ N, 65°43′50.09″ W) — an open-air field warming experiment located in a lowland tropical forest in Puerto Rico within the Luquillo Experimental Forest (LEF) — six to seven years after Hurricanes Irma and Maria (2017). All spreadsheets for soil and air microclimate data, as well as soil greenhouse gas data, are included as csv files. Air temperature data are also included as Excel spreadsheets (.xlsx). The script is built in R Studio, which is the only software required to run data analysis. This dataset is associated with the manuscript “Larocca Conte G ; Zuvela L ; Cruz-Pérez R ; Barreto-Vélez T ; Becerra-Santillan N ; Campbell S ; Chu H ; Dam T ; Grullón-Penkova I ; Kleit M ; Ortiz-Iglesias D ; Rubio-Lebrón L ; Cavaleri M ; Reed S ; Sihi D ; Wood T ; O'Connell C., 2026. Lowland Tropical Forests Remain a Methane Sink Under Warming and Long-Term Hurricane Disturbance Recovery. Agricultural and Forest Meteorology. In review". The dataset was used to test the effect of warming on soil CH4 dynamics following long-term legacy effects of hurricane disturbance. The dataset includes: - An overall README file in word and pdf format describing methodology and spreadsheets’ structure. - Continuous measurements of soil temperature and moisture from January 2023 to July 2024 measured with Campbell CS655 probes (“TRACE_soil_temperature_and_moisture_2023_cleaned(in).csv” and “TRACE_soil_temperature_and_moisture_2024_cleaned. csv”). - Air temperature data measured with a HOBO MX23O1A data logger (“Hobo air temperature 2023 Sep 2024” and “Hobo air temperature 2023 Sep 2024” – “CSV FILES folders”). - Precipitation data from a nearby weather tower downloaded from González et al. (2025; “sabana_2020-2025.csv”). - Soil CH4 and CO2 effluxes measured intermittently in two summer campaigns (June – August 2023 and June – July 2024) with a LI-COR 8200-01S Portable Smart Chamber coupled with a LI-COR LI-7810 CH4/ CO2/H2O Trace Gas Analyzer (“23_24COMBO2.0.csv”). - R markdown script for data analysis (“Trace new_PLOTS.Rmd”).

54 ENVIRONMENTAL SCIENCES↗