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Data for: Patel et al. Carbon flux estimates are sensitive to data source: A comparison of field and lab temperature sensitivity data

This dataset contains data and code used for the paper "Carbon flux estimates are sensitive to data source: A comparison of field and lab temperature sensitivity data" [DOI COMING SOON]A large literature exists on mechanisms driving soil production of the greenhouse gases CO2 and CH4. Measurements of these gases’ fluxes are often performed using closed-chamber incubations in the laboratory or in situ, i.e., in the field. Although it is common knowledge that measurements obtained through field studies vs. laboratory incubations can diverge because of the vastly different conditions of these environments, few studies have systematically examined these patterns. It is crucial to understand the magnitude and reasons for any differences, as these data are used to parametrize and benchmark ecosystem- to global-scale models, which are then susceptible to the biases of the source data. Here, we specifically examine how greenhouse gas measurements may be influenced by whether the measurement/incubation was conducted in the field vs. laboratory, focusing on CO2 and CH4 measurements. We use Q10 of greenhouse gas flux (temperature sensitivity) for our analyses, because of the ubiquity of this metric in biological and Earth system sciences and its importance to many modeling frameworks. We predicted that laboratory measurements would be less variable, but also less representative of true field conditions. However, there was greater variability in the Q10 values calculated from lab-based measurements of CO2 fluxes, because lab experiments explore extremes rarely seen in situ, and reflect the physical and chemical disturbances occurring during sampling, transport, and incubation. Overall, respiration Q10 values were significantly greater in laboratory incubations (mean = 4.19) than field measurements (mean = 3.05), with strong influences of incubation temperature and climate region/biome. However, this was in part because field measurements typically represent total respiration (Rs), whereas lab incubations typically represent heterotrophic respiration (Rh), making direct comparisons difficult to interpret. Focusing only on Rh-derived Q10, these values showed almost identical distributions across laboratory (n = 1110) and field (n = 581) experiments, providing strong support for using the former as an experimental proxy for the latter, although we caution that geographic biases in the extant data make this conclusion tentative. Due to a smaller sample size of CH4 Q10 data, we were unable to perform a comparable robust analysis, but we expect similar interactions with soil temperature, moisture, and environmental/climatic variables. Our results here suggest the need for more concerted efforts to document and standardize these data, including sample and site metadata. This dataset contains a compressed (.zip) archive of the data and R scripts used for this manuscript. The dataset includes files in .csv format, which can be accessed and processed using MS Excel or R. This archive can also be accessed on GitHub at https://github.com/kaizadp/field_lab_q10 (DOI: 10.5281/zenodo.7106554).

54 ENVIRONMENTAL SCIENCES↗

Soil and soil fraction radiocarbon, C and N from the Enriched Background Isotope Study, Oak Ridge National Laboratory, Tennessee, USA

A large accidental 14CO2 release at the Oak Ridge Reservation in Tennessee, USA provided a strong label pulse into adjacent, well-studied oak forests, resulting in highly elevated Δ14C values in leaf litter (~1000‰) and roots (~260–450‰). A four-year manipulative study was conducted to provide insight into mechanisms underlying soil Organic matter dynamics, specifically to determine the relative contribution of litter versus roots to the bulk mineral soil C pool, as well as to free light, occluded light and heavy fractions. The heavy fraction was further split into fractions with densities of 1.7–2.4 g cm-3 and >2.4 g cm-3 to test the homogeneity of the mineral-associated fraction of C. Substantial concentrations of label were detected in all soil fractions within a year of the 14CO2 release, indicating rapid incorporation of newly fixed photosynthates in all fractions of soil organic C, regardless of differences in stability inferred by previous work. This rapid incorporation of label occurred only in treatments where roots were labeled, indicating that roots are the major source of inputs to mineral soil C stocks at these sites. Separation of the heavy fraction into subfractions of intermediate (1.7–2.4 g cm -3) and high (>2.4 g cm-3) density indicated that both subfractions incorporated label at similar rates, despite significant differences in degree of microbial processing.

54 ENVIRONMENTAL SCIENCES↗

Transport and Retention of Particulate Organic Matter in Sand: Lab Experiments and Modelling

Flow-through reactor (FTR) experiments were conducted at three different downward vertical flow rates to study the transport and retention of particulate organic matter (Chlorella powder) in riverbed sediments. This data package includes data files (.csv) regarding effluent collected from the FTRs during the experiments (time, duration, volume of each sample collection; concentration of nonreactive bromide tracer; concentration of suspended Chlorella determined by absorbance measurements) and sediment (sand) slices collected from the FTRs after the experiments (mass of Chlorella retained in 1 cm depth intervals determined by loss-on-ignition method). More detailed descriptions of data are provided in the data dictionary, and detailed methods are available in the associated MSc thesis listed in ‘Related References.’ The data dictionary and file level meta data (FLMD) are included in the data package as both .csv and .xlsx files. This data package also includes timelapse videos (.mp4) of the experiments, and modelling scripts associated with the experiments. The modelling scripts are included as MATLAB ‘live scripts’ (.mlx, which can be run using MATLAB), and are also included as .pdf and .html files with output plots included (which can be viewed without a MATLAB license and installation). The data files and modelling scripts are organized into a .zip folder for each of the three FTR experiments (three flow rates).

54 ENVIRONMENTAL SCIENCES↗

Soil organic matter, tree communities, and fungal communities across mycorrhizal gradients in the Eastern United States

We collected these data to investigate how mycorrhizal associations are related to soil C and N across four sites in the eastern U.S. broadleaf forest biome, which capture broad variability in climate and tree species. Our sites represented each of the four ecoregions in the eastern United States temperate forest—warm continental (New Hampshire), hot continental (Wisconsin), Prairie (Illinios), and subtropical (Georgia). This breadth naturally provided tree species diversity and allowed us to also investigate how soil C and N are related to canopy tree and EcM fungal community composition. Specifically, we analyzed the effects of mycorrhizal association, canopy tree family, and EcM fungal taxa on the proportion of C and N associated with soil minerals (MAOM) and bulk soil C:N. These are plot level data from forests in New Hampshire, Georgia, Wisconsin, and Illinois. The plots are 10 m in radius and vary across gradients of ectomycorrhizal tree basal area. Within each plot, data include the basal area of all trees >2 cm in diameter identified to species, the abundance of different fungal taxa based on ITS sequences, and the %C, %N, C:N of bulk soil and of soil density fractions (free light, occluded light, and particulate) as well as the proportion of soil C and N within each fraction. The soil data (both organic matter and fungal communities) are from the top 10 cm of the mineral soil. This also includes a meta-analysis of leaf litter k and C:N values for the tree species present in the forests.The "Tree_BA_ALL.csv" files include the basal area of all trees >2 cm in diameter at breast height within our 10 cm radii plots. The "Soil_Data_Final.csv" file contains the soil carbon and nitrogen in bulk and density fractions (concentrations as well as proportion for free light fraction (fLF), occluded light fraction (oLF), and heavy or dense fraction (HF), oxalate extractable iron and aluminum concentrations, as well as the geographic coordinates of each plot's location. The "FungiNonRelative.csv" file contains the abundances of fungal taxa identified via ITS sequencing for each plot (with the exception of 4 plots from GA where there was not enough quality DNA to extract).The "R_ReadyK.csv" and "R_Ready_CN.csv" files contain leaf litter decomposition constant (k) and C:N values from the literature for the tree species found at our sites.

54 ENVIRONMENTAL SCIENCES↗

Mycorrhiza better predict soil fungal community composition and function than aboveground traits in temperate forest ecosystems

We sampled soil in the organic and mineral horizons beneath two AM-associated (Fraxinus americana, Thuja occidentalis) and two ECM-associated tree species (Betula alleghaniensis, and Tsuga canadensis), with an evergreen and deciduous species in each mycorrhizal group. To characterize fungal communities and organic matter decomposition beneath each tree species, we sequenced the ITS1 region of fungal DNA and measured the potential activity of carbon and nitrogen-targeting extracellular enzymes. Each tree species harbored distinct fungal communities, supporting the need to consider both mycorrhizal type and leaf habit. However, between tree characteristics, mycorrhizal type better predicted fungal communities. Across fungal guilds, saprotrophic fungi were the most important group in shaping fungal community differences in soils beneath all tree species. The effect of leaf habit on carbon and nitrogen-targeting hydrolytic enzymes depended on tree mycorrhizal association in the organic horizon, while oxidative enzyme activities were higher beneath EcM-associated trees across both soil horizons and leaf habits. These data include extracellular hydrolytic and oxidative enzyme activities, ITS sequencing fungal community data, soil carbon to nitrogen, and soil pH. Site level data include climate (mean annual temperature, precipitation), elevation, and soil series and order information.

54 ENVIRONMENTAL SCIENCES↗

Ectomycorrhizal effects on decomposition are highly dependent on fungal traits, climate, and litter properties: A model-based assessment. Dataset.

To simulate the effects of mycorrhizal fungi on soil organic matter cycling, we incorporated mycorrhizal processes into the Carbon, Organisms, Rhizosphere, and Protection in the Soil Environment (CORPSE) model to develop a new soil model Myco-CORPSE. The new model was calibrated and evaluated against soil measurements taken at temperate forests in New Hampshire (NH) and Georgia (GA). A series of scenario analysis were also conducted to explore the conditions under which ectomycorrhizal (ECM) N acquisition processes can induce different soil C accumulation in ECM systems compared to arbuscular (AM) systems.In this data package, we included:-The Python codes of the standard Myco-CORPSE model we developed: "Standard Myco_CORPSE python codes.zip". The main program is the "gradient_sim.py" which calculates the bulk soil microbes and CN content along a user defined gradient of clay, soil temperature, soil moisture and mycorrhizal dominance, and relies on two subprograms "CORPSE_deriv.py" and "CORPSE_integrate.py". "CORPSE_deriv.py" calculated the changes in all simulated soil stock within every time step and "CORPSE_integrate.py" integrate the changes in all simulated soil stock within simulated time period. The program "Plot.py" is used to plot the major outputs produced by the main program "gradient_sim.py".-The modified Python codes of Myco-CORPSE models with site-level environmental inputs (in NH and GA) used to conduct simulations in NH and GA sites: "NH_GA model simulations.zip". -The Python codes used to evaluate the Myco-CORPSE simulation outputs in NH and GA sites against site-level measurements: "Plot NH_GA simulation against measurements.zip". It includes both the evaluation Python code, the model outputs on NH and GA sites, and the measured soil properties in both sites.-The modified Python codes of Myco-CORPSE models "Scenario analysis_model simulations.zip" that is used to conduct scenario analysis of how different litter properties, mycorrhizal fungal traits, climate, and seasonal variation in temperature and vegetation phenology impact the mycorrhizal effects on soil CN properties. The sub file folder "Scenario analysis_litter traits" contains the codes for scenario analysis of different litter properties; The sub file folder "Scenario analysis_ECM types" contains the codes for scenario analysis of different ECM fungal traits; The sub file folder "Scenario analysis_climate&seasonality" contains the codes for scenario analysis of different climate and seasonalities;-"Scenario analysis_model results and plotting codes.zip" contains all the output files from the the scenario analysis of Myco-CORPSE model as described above and the plotting codes used to the generate the heatmaps and scatterplots shown in the manuscript "Ectomycorrhizal effects on decomposition are highly dependent on fungal traits, climate, and litter properties: A model-based assessment"The majority of the model outputs did not have specific geographic information or temporal coverage because the analysis we conducted are mainly hypothetical model simulations. We only provided geographic description, coordinates and temporal coverage for those soil measurements which we used for model evaluations (included in the "Plot NH_GA simulation against measurements.zip").

54 ENVIRONMENTAL SCIENCES↗

Carbon dioxide (CO2) flux, amplicon sequencing and liquid chromatography–mass spectrometry (LC-MS) data for pyrogenic organic matter (PYOM) amended soil incubations in lab, Madison, WI, 2021-22

This dataset comprises soil-pyrogenic organic matter (PyOM) incubation experiments conducted in a laboratory setting. The focus was on measuring carbon dioxide (CO2) flux emitted in the headspace of incubation jars over a one-month period. The aim was to estimate carbon mineralization from two different carbon fractions in PyOM, as well as carbon mineralization from soil organic carbon (SOC). Bacterial and fungal community profiles were tracked at various time points during the incubation to observe changes in the overall community and specific responders to PyOM. LC-MS analysis of soil samples was also performed to monitor changes in the soil's chemical composition.The provided dataset includes processed CO2 flux measurements obtained from the Picarro-multiplexer measurement setup for each sample incubation jar. This data is available in the "CO2Flux.csv" file. Additionally, the dataset includes CO2 flux data partitioned to estimate mean carbon mineralization from the two PyOM carbon fractions, bulk PyOM, and SOC. The cumulative carbon mineralization data is provided in "cml_respired.csv," while the rate of carbon mineralization data is in "rate_respired.csv." The file "cml_respired_lastcyc.csv" contains cumulative carbon mineralization data for the PyOM carbon fractions, bulk PyOM, and SOC throughout the entire incubation period.For the LC-MS analysis, the raw data can be found in the "20220721_NZ_PeakHeights_FinalAnalysis.csv" file, while sample metadata is provided in "20220721_NZpilot_Metadata.csv". Processed LC-MS data is available in the file "20220721_NZ_FINAL_msdat_sub3.csv". Lastly, the dataset includes the relative abundance data for bacterial genera that exhibited a significant positive response to the addition of PyOM produced at 350 degrees Celsius, which can be found in "resp_genera_350.csv".

54 ENVIRONMENTAL SCIENCES↗

Classification of River Catchments in the Contiguous United States: Code, Dataset, Similarity Patterns, and Resulting Classes

This dataset serves as supplementary information for the paper by Ciulla F. and Varadharajan C. A Network Approach for Multiscale Catchment Classification using Traits (see reference 1). It contains environmental and physical catchment traits, such as temperatures, precipitation, land use and human interference, from 9067 sites across the contiguous United States (CONUS). The purpose of this dataset is to provide information for a better trait-based categorization of river catchments in the CONUS using networks as an analytical tool. The traits variables match the ones present in the GAGES-II dataset and the preprocessing steps are described in the Methods section (processed_dataset.csv). Additionally we include the topologies (nodes, edges and clusters, also referred as classes) of the catchment network and traits network generated by said dataset (csv and json files). A series of tables support the information carried by the network providing more detailed descriptions of cluster components (SI1.pdf). A summary of all the plots of clusters of catchments with at least 50 nodes is provided (SI2.pdf). The characteristic traits for each cluster of catchments is presented as z-score (traits_categories_zscores_per_catchment_class.csv). The link to the hydrological behavior of clusters of catchments is displayed by boxplots, each describing a particular river discharge index (SI3.pdf). Both csv and json files can be read by common text editors but the data contained into them can be better handled using programming languages like python and database oriented libraries like pandas. Pdf files can be read by any pdf reader software.[02-23-2024] Update: The code and datasets necessary to reproduce the results of the study are available as a zipped repository (code_datasets_catchments_similarity.zip).

54 ENVIRONMENTAL SCIENCES↗

Building heights and urban canopy parameters for urban modeling

GLObal Building heights for Urban Studies (UT-GLOBUS) is a random forest model based framework that provides a level-of-detail-1 (LoD-1) building height dataset. The primary objective of UT-GLOBUS is not to precisely predict the height and footprint of individual buildings, but rather to offer a functional framework for generating building level information using open-source datasets for modeling applications. Specifically, UT-GLOBUS is tailored to meet the requirements of deriving urban canopy parameters (UCPs) for the multi-layer model within the Weather Research and Forecasting (WRF) model and building heights for the SOLWEIG and SUEWS model. Building-level data is accessible in vector file format (GeoPackage: .gpkg), which can be converted into raster file format (geoTIFF). The vector files employ the Universal Transverse Mercator (UTM) projection. The vector files are compatible with GIS platforms like QGIS and ArcGIS, and can be imported for analysis using programming languages such as Python. We are also providing UCPs required by the multi-layer urban model in the urban WRF in binary file format. Additionally, we provide the urban fractions calculated using ESA world cover dataset (https://esa-worldcover.org/en) for WRF model in binary file format. These binary files can be directly incorporated into the WRF pre-processing system (WPS).

54 ENVIRONMENTAL SCIENCES↗

Duke Forest FACE (FACTS-I): Plant and Soil Response Data

This dataset describing the responses of plant and soil pools and fluxes to elevated atmospheric CO2 concentration and increased nitrogen supply was collected from Duke Forest Free Air CO2 Enrichment (FACE) – Forest-Atmosphere Carbon Transfer and Storage (FACTS-I) experiment from 1996 to 2012. The dataset includes data files for allometry (diameter at breast height, tree height, and height to live crown base), leaf area index, biomass (stem, branch, foliage, and root biomass, tree density, and basal area), net primary productivity (stem, branch, foliage, reproductive, and coarse root NPP), sap flux density, soil CO2 efflux, and stem temperature. Data files were formatted as .csv (Microsoft Excel or other spreadsheet programs can be used to read the format) and file descriptions, including variable name, unit, and data range, can be found in ‘FileDescription_[data_name].txt’ files. The Duke FACE experiment was in a loblolly pine (Pinus taeda L.) plantation established in 1983. Naturally regenerated broadleaved species including sweetgum (Liquidambar styraciflua L.) and tulip poplar (Liriodendron tulipifera L.), mostly in the overstory, and winged elm (Ulmus alata Michx.) and red maple (Acer rubrum L.) were common in the understory. The FACE experiment commenced with two plots (plots 7-8) in 1994 (Oren et al. 2001), with six additional plots (plots 1-6) coming online on 27 August 1996. CO2 enrichment was terminated on 31 October 2010 and post-enrichment data collection continued through 2012. Complete fertilization was applied annually to half of plots 7-8 from 1998 to 2004. The nutrient addition experiment expanded to half of plots 1-6 with a common protocol of N-fertilization in 2005 and continued until 2012. The levels of treatment in this dataset were expressed as ambient CO2 (AMB) or elevated CO2 (ELE) for CO2 treatment and control soil (CONT) or fertilized soil (FERT) for N treatment, respectively.

54 ENVIRONMENTAL SCIENCES↗

Data associated with Quaternary Research manuscript Latest Pleistocene glacial chronology and paleoclimate reconstruction for the East River watershed, Colorado, USA

The data here are associated with Quaternary Research manuscript Latest Pleistocene glacial chronology and paleoclimate reconstruction for the East River watershed, Colorado, USA and include data associated with cosmogenic exposure and depth profile dating as well as glacier-climate numerical modeling. Reconstructing Pleistocene glaciation timing and extent is vital for understanding paleoclimate. While late Pleistocene glaciation has been studied extensively in western North American mountain ranges, the glacial history of the western Elk Range in Colorado remains understudied, particularly in the East River watershed, a site of intense scientific focus. Here we use cosmogenic nuclide exposure and depth–profile dating methods to determine the timing of glaciation in the East River watershed. We use glacier modeling to reconstruct paleoglacier extents and quantify past climate conditions. Our findings indicate that the East River glacier retreated from its maximum position approximately 17–18 ka, moving to recessional positions between 13–15 ka, before experiencing more substantial retreat to high-elevation cirques around 12.9 ka. Glacier modeling suggests that the maximum ice extents at 17–18 ka could have been sustained by temperature depressions of approximately −6.5°C compared to modern conditions, assuming consistent precipitation. Additionally, the ice position at 13–15 ka could have been supported by temperature depressions of around −4.0°C. These results offer insights into the deglaciation timeline in the East River watershed and broader western Elk Range as well as paleoclimate conditions during the late Pleistocene, which may aid future research on critical zone evolution in the East River watershed.The data files include: 1. Table 1 In situ-produced 10Be sample data (.pdf, .csv, .xlsx)2. Table 2 In situ-produced 10Be exposure age results (.pdf, .csv, .xlsx)3. S1_A CRONUS calculator input assuming no erosion (.csv)4. S1_B CRONUS calculator input assuming erosion (.csv)5. S1_C CRONUS calculator results and comparison (.csv)6. S2_A In situ-produced 10Be sample data for depth profile (.csv)7. S2_B In situ-produced 10Be depth profile model input (.csv)8. S2_C In situ-produced 10Be depth profile model results (.csv)9. S3 Monthly cloudiness, rH, and windspeed data used in glacier climate model (.csv)10. S4 Glacier climate model results (.csv)

54 ENVIRONMENTAL SCIENCES↗

Snow Camera Photos at the Teller 27 Field Site from 2022-2023, Seward Peninsula, Alaska

Snow distribution in the Arctic is highly variable and driven by high winds and microtopography, which result in deep snow drifts and shallow scoured areas. To better understand snow drifting and scouring, 4 Reconyx HyperFire 2 game cameras were installed at the Teller 27 Watershed Field Site on the Seward Peninsula, Alaska from September 2022 to September 2023. Game cameras were installed at 4 locations across the watershed to capture pictures of snow in drift and scour areas. Three-meter tall, red PVC poles were used as snow-stakes to measure snow depth from these pictures. One photo was taken at each camera once per hour during daylight. Distances between cameras and snow stakes were measured so that snow depth can later be calculated from the pictures. This dataset contains four folders of *.jpg files from each camera and one *.kml file of camera locations.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 15-year research effort (2012-2027) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy’s Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy’s Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

Model output from simulations of manganese-carbon interactions in temperate forest soil profiles

This archive contains model output, code, and scripts for simulations of coupled manganese-carbon cycling in temperate forest soil profiles. These model results were generated as part of a study investigating how manganese availability influences soil organic carbon stocks and demonstrating a new model framework for coupling carbon and manganese cycling. The simulations were in support of a manuscript: "Modeling interactive effects of manganese bioavailability, nitrogen deposition, and warming on soil carbon storage." The study addresses the research questions: How does Mn bioavailability, as driven by subsurface mineral properties, pH, and redox status, affect temperate forest soil organic carbon and litter carbon stocks?How is the relationship between Mn bioavailability and carbon cycling affected by changes in temperature and nitrogen deposition?"Model simulations were conducted in a reactive transport modeling framework using PFLOTRAN coupled to python. Multiple model simulations testing different Mn-bearing mineral solubilities, hydrological patterns, nitrogen deposition rates, and temperatures are included. Soil properties, including total and exchangeable Mn concentrations, are based on values reported for the Susquehanna Shale Hills Critical Zone Observatory (SSHCZO), a temperate forested watershed in central Pennsylvania, U.S.A where Mn cycling through vegetation has been documented.File formats include netCDF (.nc), python script (.py), shell script (.sh), plain text PFLOTRAN input file (.in), and plain text PFLOTRAN database file (.dat), and gzipped tar archive (tar.gz).

54 ENVIRONMENTAL SCIENCES↗

Comparing the Recovery of Arbuscular and Ectomycorrhizal Stands from Long-Term Nitrogen Fertilization at the Fernow Experimental Forest, WV (2021 and 2022)

This data was generated to answer the research question: After the end of a 30-year nitrogen (N) fertilization experiment in an Eastern temperate forest, to what extent do plant microbial interactions and carbon cycling in arbuscular mycorrhizal (AM) and ectomycorrhizal (ECM) dominated stands follow different recovery trajectories?The soil and the roots used in this dataset were sampled from two watersheds (N-fertilized watershed 3 and Reference watershed 7) with 6 AM and 6 ECM dominated stands each, over the course of three months (June, July, August) in 2021 and 2022. The "All_Roots.csv" data includes fine root biomass (in g) scaled to sampled soil (m2) (Scaled_Rt_Bm_gm2), and AM and ECM root colonization (%) in two soil fractions: the organic horizon (O) and the mineral horizon (B). The "All_Enzymes.csv" data includes extracellular soil enzyme activity (N-acetyl-glucosaminidase (NAG), acid phosphatase (AP), β-glucosidase (BG), phenol oxidase and peroxidase), and the ratios of BG to AP (BG:AP) and BG to NAG (BG:NAG) in three soil fractions: the organic horizon (O), the bulk soil (B), and the rhizosphere (R).The "All_Nmin" data includes inorganic N (NO3- and NH4+) pools (unit: μg of N per g of dry soil) measured pre- (I_Nitrate_ugNgsoil and I_Ammonia_ugNgsoil) and post-incubation (F_Nitrate_ugNgsoil and F_Ammonia_ugNgsoil), as well as calculated nitrification (Nitrification_day) and nitrogen mineralization (Mineralization_day) rates per day, in three soil fractions: the organic horizon (O), the bulk soil (B), and the rhizosphere (R).

54 ENVIRONMENTAL SCIENCES↗

NEON AOP Survey of Upper East River CO Watersheds: Waveform LiDAR Binary Data

The waveform Light Detection and Ranging (LiDAR) data in this package were generated through a National Ecological Observatory Network Airborne Observation Platform (NEON AOP) acquisition over watersheds of interest surrounding Crested Butte, Colorado. The remote sensing imagery acquired by the NEON AOP supports an interdisciplinary project on hydrology, biogeochemistry, and ecosystem functioning in a snow-dominated headwater environment. These waveform LiDAR data enable spatially continuous estimation of vegetation structure parameters to facilitate analyses of the major environmental drivers of structural and compositional variability. The package contains 97 compressed file archives in 7-zip (.7z) format, each corresponding to one acquisition flightpath. Within each .7z archive is a set of constituent files describing properties of the LiDAR waveforms, such as return intensity, geolocation, outgoing pulse and other behavior of the sensor and signals. Once downloaded, the files must first be unzipped using the widely distributed command-line software utility 7z, using the command '7z x \[filename\].7z \[target_directory\]'. All files within the .7z archives can be opened in IDL, MatLab, or the open-source R statistical computing environment. Further details about the data package are in the attached user guide (neon_aop_crbu_waveformlidar_userguide.pdf). This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

2018 NEON and 2025 CHESS Campaigns↗

The importance of accounting for landscape position when investigating grasslands: A multidisciplinary characterisation of a Californian coastal grassland

Data from the characterisation of the Point Reyes Field Site, published in AGU Earth's Future under the title: The importance of accounting for landscape position when investigating grasslands: A multidisciplinary characterisation of a Californian coastal grassland. This paper explored the effect of landscape position on the response of a Californian grassland to seasonal changes. All files are csv files. The EMI data contains 8 csv files with a metadata csv explaining the columns. The dataset also includes soil variables including total concentrations calculated from fused samples, then dissolved and measured on ICP-AES for whole-rock elements and ICP-MS for trace elements. Mineral composition was attained using X-ray diffraction at BL 11-3 at SSRL . Data was then run through the High Score database to characterise different mineral phases. total It also includes a table with bulk soil characteristics such as soil pH, cation exchange capacity, and soil textural data. Data from Teros 12 Meter soil moisture, electrical conductivity and temperature sensors are presented in SMS Csv file. While the WL bottom and top files contain data from Piezometers measuring the ground water table. We have included a csv file that contains soil CO2 efflux data from Feb 2021-Oct 2021 in the Point Reyes Grassland Experiment We have included the spatially orientated (easting northing) remotely sensed datasets that were used in the K-means clustering analysis conducted on our site with electrical conductivity, normalised difference vegetation index, elevation, slope, solar radiation, topographic position and wetness index, and a clustering score. Finally there is a list of all the identified grassland species at the site.For more information on flux data, please contact the corresponding author.

54 ENVIRONMENTAL SCIENCES↗

Soil carbon, nitrogen, and ice content data (2014-2018) at Happy Valley and Sagwon Hills in Northern Alaska, United States

This dataset contains three data files from soil data collected by sampling soil cores and pits across a toposequence on two hillslopes in permafrost affected soils in Northern Alaska, USA. Soil cores and profiles were excavated to 3m or until auger refusal. Samples were collected by genetic soil horizons for laboratory analysis and organized into complete soil profiles ordered depth. Soil carbon, nitrogen, and ice stocks (stocks_by_core.csv) were calculated from the core dataset . Data for mean values by depth increments (20,50,100,150,200 cm) of total soc, total nitrogen, bulk density, and ice content were determined and made available in this dataset (soc-tn-bd-ice-slab_tables.csv). Stocks by site are included in a separate file (stocks_by_site.csv). Each of these three files also has an associated data dictionary file (stocks_by_core_dd.csv, soc-tn-bd-ice-slab_tables_dd.csv, stocks_by_site_dd.csv). Finally, an FLMD file is also included (FLMD_Happy_Valley_Sagwon.csv).

54 ENVIRONMENTAL SCIENCES↗

Root biomass and traits across four lowland Panamanian forests from 0 - 1.2 m soil depths

Fine roots are key to ecosystem-scale nutrient, carbon (C), and water cycling, yet our understanding of fine root traits variation within and among tropical forests, one of Earth’s most C-rich ecosystems, is limited. We characterized root biomass, morphology, nutrient content, and arbuscular mycorrhizal fungal (AMF) colonization in 10 cm increments to 1.2 m depth across four distinct lowland Panamanian forests. The datasets provided include a .xlsx file for fine root characteristics across 10 cm increment depths to 1.2 m collected from late 2017 to 2018 across four different forests. Root characteristics include live fine root biomass, dead fine root biomass, coarse root biomass, specific root length, root diameter, root tissue density, specific root area, arbuscular mycorrhizal fungi colonization, root chemistry (e.g., organic chemistry), root %N, root %C, root C/N ratio, and root radiocarbon content. This .xlsx file contain four tabs with 1) Dataset; 2) Metadata with information about each column in the dataset; 3) The sampling methods summarized; 4) Sites information. We also provided csv files for each of these tabs. Additionally, a .kml file is provided with coordinates for all 32 plots included in the study across four forests (n = 8 plots per site/forest). This dataset serves as baseline data before a throughfall exclusion experiment, Panama Rainforest Changes with Experimental Drying (PARCHED), was implemented. No special software is needed to open these files.

54 ENVIRONMENTAL SCIENCES↗