Find research datasets worth reusing

openCC (other)Mar 2025View details →

Soil respiration rates, biogeochemical pools, and mineral-associated organic matter from high organic matter and high mineral content coastal wetland soils in Apalachicola, Florida, 2022

This data set was used to observe how the application of dredged sediment would impact soil respirations rates, biogeochemical pools, mineral associated organic matter of coastal wetland soils from Apalachicola, Florida. To achieve this, a combination of intact core and bottle incubations were used, comparing a high organic matter coastal wetland soil to a high mineral content wetland soil which were collected in June, 2022. All laboratory analysis was conducted at the University of Central Florida in Orlando, Florida.

openCC (other)Aug 2025View details →

Soil organic carbon and nutrient dynamics in response to anaerobic digestate application to farm fields, Eastern Iowa, 2011-2023

This dataset documents a long-term, field-scale study of anaerobic digestate application on commercial croplands in eastern Iowa, USA. It includes detailed records of digestate composition, application rates, and timing, as well as soil test results collected over a 12-year period (2011–2023) from 14 agricultural fields. The dataset supports analysis of soil organic carbon (SOC), nutrient dynamics, and isotopic composition in response to digestate inputs. It contains 421 georeferenced soil samples, digestate nutrient profiles, field management histories, and spatial boundaries. The data were collected as part of a collaborative effort between researchers at Iowa State University and Sievers Family Farms to evaluate the agronomic and environmental implications of integrating anaerobic digestion into row crop and livestock systems.

openCC (other)Sep 2021View details →

NEON distributed initial soil characterization dataset (DP1.10047.001) modified for statistical analysis of organic carbon and extractable metals in Hall and Thompson (2021)

We compiled National Ecological Observatory Network (NEON) datasets related to the initial distributed soil sampling effort and subsetted them (removed samples with missing values for certain variables, and several samples with extreme values) for use in statistical analyses to describe relationships between soil organic carbon (SOC) and metals measured in several soil chemical extractions. The NEON provisional data products we used were DP1.10047.001 and DP1.10008.001, which were subsequently combined by NEON as a single data product DP1.10047.001, “Soil physical and chemical properties, distributed initial characterization”. These datasets were used for the analyses reported in a manuscript by Hall and Thompson (2021) in the Soil Science Society of America Journal.

openCC0Sep 2021View details →

Model estimates of runoff, dissolved organic carbon, soil temperature and moisture for Elson Lagoon watershed, Alaska, 1981-2020

This dataset contains model estimates of dissolved organic carbon (DOC) yield (mg C/m^2) and runoff (mm), for surface and subsurface flows, soil temperature (degree C), and soil moisture (% of soil volume) for grid cells spanning the Elson Lagoon watershed in northwest Alaska. Daily air temperature, precipitation, and wind speed data from Utqiagvik airport were used for meteorological forcings for the daily simulation by the Permafrost Water Balance Model (PWBM) from 1981 to 2020. The DOC and runoff data files are organized by grid cell and month. The soil temperature and soil moisture files are organized by grid cell and day of year (DOY), and contain values for the first eight model soil layers, with centers of the layers at 1, 3, 8, 13, 23, 33, 45, 55 cm depth. The estimates are most useful for analyses of the dynamics of the watershed’s surface and subsurface runoff and DOC yield. Leachate DOC concentrations can be obtained using the gridded runoff and yield values. A manuscript describing the data and associated analysis has been accepted for publication in Environmental Research Letters (Rawlins et al., 2021).

openOpenNov 2024View details →

Overwintering Fires from 2009-2010 Burns near Fairbanks, Alaska: Residual Soil Organic Layer Depth, Burn Depth and Thaw Depth Collected 2023

This dataset contains data from adjacent overwintering and single-season burn sites. For the overwintering fires, we targeted locations that had burned in the summers of 2009, smouldered through the winter months, and reignited in 2010. Adjacent to these overwintering sites, we identified single-season burn sites from within portions of the 2009 fires that were unaffected by overwintering. A total of seven overwintering fire sites and four single-season fire sites were sampled. Within each site, three plots were established. Data inlcudes within plot measurments of post-fire seedling composition and density, residual SOL, burn depth estimated by black spruce adventitious roots, thaw depth, and pre-fire tree species composition and estimates of combustion. This is one of three packages from this project; this one contains the soils data.

openCC (other)Mar 2024View details →

Mass and Chemistry of Organic Horizons and Surface Mineral Soils on Watershed 6 at the Hubbard Brook Experimental Forest, 1976 - present

The forest floor of Watershed 6 was first sampled in 1969-70. These data include forest floor thickness, soil mass, organic matter content, and major-element composition for samples collected since 1976. Watershed 6 has been resampled at intervals varying from one to ten years. Sampling at five to ten year intervals is expected to continue. These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station.

openCC (other)Mar 2022View details →

Mass and Chemistry of Organic Horizons and Surface Mineral Soils on Watershed 1 at the Hubbard Brook Experimental Forest 1996-present

This data set includes chemistry of O-horizons ("forest floor") and the 0-10 cm mineral soil layer in Watershed 1 at Hubbard Book. Calcium in the form of wollastonite (CaSiO3) was added to Watershed 1 in October 1999. The application rate was 1028 kg Ca per ha, and the application was relatively uniform across the watershed. Pre-treatment forest floor surveys were completed in 1996 and 1998. The first post-treatment forest floor survey was completed in 2000. This data set includes mass and thickness data for the sampled layers. Chemical data include concentrations and pools of organic matter, C, N, Ca, Mg, K, P, Mn, Fe, Al, Cu, Pb, and Zn. Soil pH and exchangeable Al, Ca, Mg, K, and H are also included. Sampling is intended to continue at 4 or 5 year intervals. These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station.

openCC (other)Dec 2021View details →

Soil organic matter content sampled in and around harvester ant nests in three habitats at the Jornada Basin LTER site, 1987

This dataset contains soil organic matter content measurements from harvester ant nests and reference soils in three nesting habitats at the Jornada Basin LTER site in 1987. The purpose of this investigation was to answer three general questions: 1. How does the modification of soil properties and the ratios of resources (e.g., water-N) by ants alter species assemblages of winter annual plants at the edge of the ant nests? 2. How does the "spring cleaning", clipping, predation or herbivory by ants affect success of the winter annual plants at the edge of ant nests? 3. Are there significant differences in the floristic assemblage and belowground standing crop (root biomass) between the edge of ant nest and the surrounding unaffected soils? Five ant nests and paired (non-nest) reference soils were sampled in three study locations. This dataset contains percent (%) organic matter content measured by mass-loss on combustion in a muffle furnace. This study was completed in 1987.

openCustomOct 2023View details →

Erosion Rates, Soil Core Descriptions and Organic Matter on the Virginia Coast

These data include stratigraphic, organic matter, and organic carbon analyses of sediment cores, as well as values used to calculate the time-averaged carbon erosion rate for the central 10 islands of the Virginia Barrier Island chain.

openCustomAug 2022View details →

Crab Burrows, Soil Nutrients, and Spartina alterniflora : organic content in Brownsville, VA 1992

The effect of Crab Burrows on Soil Nutrients and Spartina alterniflora by Winli Lin This study investigated the effects of fiddler crab (Uca pugnax) burrows on soil nutrients and the marsh grass Spartina alterniflora. Tall-form Spartina alterniflora (1-2m tall) typically dominates the marsh area that is flooded daily by tides. The short-form S. alterniflora(<0.5m tall) generally occupies the higher tidal heights (Bertness 1985). These short-form S. alterniflora are charterized by reduced soil drainage (Mendelssohn and Senecs 1980; Howes et al. 1981; Mendelssohn et al. 1981) and increased soil sulfide levels (King et al. 1982). From comparing control areas devoid of burrrows to those with burrows added, an increase in above-ground Spartina alterniflora production has been observed along with an increase of soil drainage rates and redox potential levels (Bertness 1985). Others have looked at how nutrient availability (Mendelssohn 1979) and sulfide accumulation (King et al. 1982; Howarth and Giblin 1983) may be the primary limiting factors controlling the production and success of S. alterniflora. While soil water movement has been shown to influence the soil parameters, (i.e., sulfide concentration and redox potential) that directly affect cordgrass production (King et al. 1982; Koch et al. 1990), little has been studied on how biotic modifications, such as crab burrows, mediate these physical factors. The Uca pugnax, are burrowing deposit-feeders that excavate and maintain semi-permanent burrows in the marsh surface. They have been found to not only oxygenate marsh soils (Howes et al 1981) and modify sediment meiofaunal abundance, they could also provide a suitable environment for continued burrowing and, as a byproduct, increase the marsh grass production and maintain the tall-form S. alterniflora. Uca pugnax, the mud fiddler crab, is the dominant form of crab seen in Brownsville, VA. Their burrows are primarily restricted to areas of tall-form S. alterniflora, due

opencc-by-4.0Jan 2020View details →

Data on ground ice, organic carbon and soluble cations in tundra permafrost and active-layer soils near Lac de Gras in the Slave Geological Province, N.W.T., Canada

Data and computer code for producing figures for the manuscript: Subedi, R., Kokelj, S. V., and Gruber, S.: Ground ice, organic carbon and soluble cations  in tundra permafrost soils and sediments near a Laurentide ice divide in the Slave  Geological Province, N.W.T., Canada. The Cryosphere, accepted for publication in October 2020.  Discussion paper and final version: https://doi.org/10.5194/tc-2020-33   ==========================================================================================    CONTENT OF DIRECTORIES ========================================================================================== -– data [input data to produce plots]    |–– BoreholesMeta.csv    |–– brackets_photos_ice.csv    |–– brackets_photos_thawed.csv    |–– Lac_de_Gras_permafrost_20200612.csv    |–– NordicanaD        |–– ds_000582159 [authoritative copy at doi: 10.5885/45558XD-EBDE74B80CE146C6]        |–– Cored_Drill_TCR.csv        |–– Cored_Drill_TCR.csv_ReadMe.txt            |–– ds_000582163 [authoritative copy at doi: 10.5885/45558XD-EBDE74B80CE146C6]        |–– Cored_Drill_Logs.csv_ReadMe.txt        |–– Cored_Drill_Logs.csv –– plot [R scripts write plots into this subdirectory] –– src [R scripts to generate plots]    |–– Combined_Plots.R              [produces Figures 3–6]    |–– Eskers.R                      [helper function called by Combined_Plots.R]    |–– Organics.R                    [helper function called by Combined_Plots.R]    |–– plot_boreholes_DD_single.R    [produces Figures S3]    |–– plot_boreholes_DD.R           [produces raw Figure S2 for further graphic processing]    |–– Till.R                        [helper function called by Combined_Plots.R]    |–– Valley.R                      [helper function called by Combined_Plots.R] ==========================================================================================    RUNNING SCRIPTS ========================================================================================== Adjust the variable 'path' in these scrips, then run:      Combined_Plots.R     plot_boreholes_DD_single.R     plot_boreholes_DD.R  Tested with R version 3.6.3 (2020-02-29) -- "Holding the Windsock"   ==========================================================================================    REFRERENCE ========================================================================================== Please note that the data contained in data/NordicanaD is published as Gruber et al. (2018) and only included here for convenience. The full reference for the authoritative copy is:         Gruber, S., Brown, N., Stewart-Jones, E., Karunaratne, K., Riddick, J., Peart, C.,  Subedi, R., Kokelj, S. 2018. Drill logs, visible ice content and core photos from 2015  surficial drilling in the Canadian Shield tundra near Lac de Gras, Northwest Territories,  Canada, v. 1.0 (2015-2015). Nordicana D38, doi: 10.5885/45558XD-EBDE74B80CE146C6.   http://www.cen.ulaval.ca/nordicanad/dpage.aspx?doi=45558XD-EBDE74B80CE146C6

opencc-zeroJan 2022View details →

Organic soil surveys across Flanders

This dataset contains geospatial data of organic soils in wetlands and valleys across the Flemish region (Belgium). It is a compilation of several surveys, mainly commissioned by Agentschap voor Natuur en Bos (ANB), Vlaamse Milieumaatschappij (VMM) and Natuurpunt to map the presence of shallow organic soil layers for conservation purposes. Organic layer depth was mapped by pushing a (pvc) rod into the organic ground until it hits a resistance or mineral layer, then recording the depth and the geographical position with a handheld gps. This method allows a quick and cost-effective survey of large shallow carbon stocks. At several locations additional auger boring sample data and electrical conductivity-probe sample data was included in the dataset. Since the majority of the samples were not analysed on carbon content, soils were defined as "organic soils". Dataset maintained by the Research Institute for Nature and Forest/INBOFor any inquiries, please contact <a href="mailto:Tom.dedobbelaer@inbo.be">Tom.dedobbelaer@inbo.be</a> or <a href="mailto:Cecile.herr@inbo.be">Cecile.herr@inbo.be</a>. The .csv will be updated as required to correct issues or to add data from additional surveys. Please check for updated versions periodically.Data description<ul><li>location: inventory location name</li><li>year: year of survey</li><li>Sample_ID: Point-ID given during survey, not unique</li><li>Unique_ID: Unique point-ID created for this dataset</li><li>EPSG_31370_X: X-coordinaat in EPSG 31370 (Lambert72), rounded to the closest meter</li><li>EPSG_31370_Y: Y-coordinaat in EPSG 31370 (Lambert72), rounded to the closest meter</li><li>stratigraphy: stratigraphy of the organic layer (near surface, substrate)</li><li>organic_layer_notation: indicates if depth is a value or within a range</li><li>organic_layer_depth: depth of the organic layer, measured from surface level (in cm)</li><li>sign: certain surveys mention a sign indicating if the actual depth is equal to or bigger then the given depth (e.g. when the measuring rod is too short or damaged during a survey)</li><li>method: method used to define organic layer depth</li><li>source: indicates the source of the data, it can be original field data or derived data from a map.</li><li>comment_soil: field comment given during survey (in Dutch)</li><li>contractor: contractor of the survey</li><li>awarding authority: commissioner of the survey</li></ul>

opencc-by-4.0Feb 2024View details →

Dataset to: Organic carbon stocks, quality and prediction in permafrost-affected forest soils in North Canada (CATENA) - Version 2 (Corrected)

Version update: Coordinates were not correct in previsous version and have been corrected now in version 2   Dataset to the manuscript: Schiedung et al. (2022, Catena) Organic carbon stocks, quality and prediction in permafrost-affected forest soils in North Canada ( <a href="https://doi.org/10.1016/j.catena.2022.106194">https://doi.org/10.1016/j.catena.2022.106194</a> ) Data files, variables and parameter are described in Var_names_dd_all.csv for all data on each sample and Var_names_dd_composites.csv for all data on composited samples per site and depth. DRIFT data and corresponding explenation are in Schiedung_CATENA_DRIFT_v1.1.zip.

opencc-by-4.0Nov 2021View details →

Dataset to manuscript: Soil organic carbon stocks and quality in small-scale tropical, sub-humid and semi-arid watersheds under shrubland and dry deciduous forest in southwestern India

Raw data to the manuscript entitled "Soil organic carbon stocks and quality in small-scale tropical, sub-humid and semi-arid watersheds under shrubland and dry deciduous forest in southwestern India" by Severin-Luca Bellè, Jean Riotte, Muddu Sekhar, Laurent Ruiz, Marcus Schiedung and Samuel Abiven. Data files include all raw data of soil cores (20211111_Raw_data.zip), data measured on composited samples (20211111_Composite_data.zip) and DRIFT spectra (20211111_DRIFT_data.zip). Files ending with var_names are the README files.

opencc-by-4.0Dec 2021View details →

Data to support the publication "Soil Water Retention as Affected by Management Induced Changes of Soil Organic Carbon: Analysis of Long-Term Experiments in Europe", https://doi.org/10.3390/land10121362

Soil organic carbon content and water content at the different pressure points, as measured by Ioanna Panagea for  the publication "Soil Water Retention as Affected by Management Induced Changes of Soil Organic Carbon: Analysis of Long-Term Experiments in Europe",  https://doi.org/10.3390/land10121362 from the the long term experiments  belonging in some of the SoilCare project partners.

opencc-by-sa-4.0May 2022View details →

Soil organic carbon content [g/kg] for continental Europe at 30 m spatial resolution for period 2000-2020: Open Soil Data Cube for Europe

Predictions are based on the 3D Ensemble Machine Learning framework, as implemented in the R environment for statistical computing (Hengl & MacMillan, 2019; Hengl, et al., 2021). For each pixel we provide prediction errors as 1 standard deviation in either log or the original variable scale. The short description of currently available soil properties: log organic carbon [g/kg] to back-transform use exp(x/10)-1; Soil properties were predicted at fixed depths:     Surface soil = s0..0cm,     Subsoil 1 = s30..30cm,     Subsoil 2 = s60..60cm,     Subsoil 3 = s100..100cm. To produce estimates for depth intervals e.g. 0–30 cm, 0–100 cm best use the trapezoidal rule formula. Periods: 2000 (2000–2003), 2004 (2004–2007), 2008 (2008–2011), 2012 (2012–2015), 2016 (2016–2019), 2020; To back-transform the log.oc maps use formula: exp(x/10)-1. These are examples of back-transformed values:     log.oc = 15 → 0.3% SOC;     log.oc = 20 → 0.6% SOC;     log.oc = 25 → 1.1% SOC;     log.oc = 30 → 1.9% SOC;     log.oc = 35 → 3.2% SOC;     log.oc = 40 → 5.3% SOC;     log.oc = 50 → 14.8% SOC;

Soil Organic Carbon Content estimations over the Lithuanian pilot area (2022)

In the context of the EU-funded project DIONE (No. 870378), Soil Organic Carbon Content (SOC) estimations have been released as outputs of novel machine learning algorithms which combined the point measurements (i.e. soil properties detected by the Soil Scanning Systems) with temporal EO multispectral imagery and other ancillary variables, enabling end-users, and for the DIONE case, the national paying agency of Lithuania (National Paying Agency - NPA) to mine meaningful information about overall soil health and the effects applied agricultural practices. The dataset is delivered in a single-banded GeoTIFF file (DIONE_SOC_estimations_LT_2022.tif- EPSG:4326) containing the SOC content (SOC %) labelled as Band 1.

Soil Organic Carbon Content estimations over the Cypriot pilot area (2022)

In the context of the EU-funded project DIONE (No. 870378), Soil Organic Carbon Content (SOC) estimations have been released as outputs of novel machine learning algorithms which combined the point measurements (i.e. soil properties detected by the Soil Scanning Systems) with temporal EO multispectral imagery and other ancillary variables, enabling end-users, and for the DIONE case, the national paying agency of Cyprus (Cyprus Agricultural Payments Organisation - CAPO) to mine meaningful information about overall soil health and the effects applied agricultural practices. The dataset is delivered in a single-banded GeoTIFF file (DIONE_SOC_estimations_CY_2022.tif- EPSG:4326) containing the SOC content (SOC %) labelled as Band 1.

Soil Organic Carbon Content estimations over the Cypriot pilot area (2021)

In the context of the EU-funded project DIONE (No. 870378), Soil Organic Carbon Content (SOC) estimations have been released as outputs of novel machine learning algorithms which combined the point measurements (i.e. soil properties detected by the Soil Scanning Systems) with temporal EO multispectral imagery and other ancillary variables, enabling end-users, and for the DIONE case, the national paying agency of Cyprus (Cyprus Agricultural Payments Organisation - CAPO) to mine meaningful information about overall soil health and the effects applied agricultural practices at a parcel level. The dataset is delivered in a shapefile format (DIONE_SOC_estimations_CY_2021.shp - EPSG: 4326) containing the SOC content (SOC %) labeled as SOC.

Soil Organic Carbon Content estimations over the Lithuanian pilot area (2021)

In the context of the EU-funded project DIONE (No. 870378), Soil Organic Carbon Content (SOC) estimations have been released as outputs of novel machine learning algorithms which combined the point measurements (i.e. soil properties detected by the Soil Scanning Systems) with temporal EO multispectral imagery and other ancillary variables, enabling end-users, and for the DIONE case, the national paying agency of Lithuania (National Paying Agency - NPA) to mine meaningful information about overall soil health and the effects applied agricultural practices at a parcel level. The dataset is delivered in a shapefile format (DIONE_SOC_estimations_LT_2021.shp - EPSG:3346) containing the SOC content (SOC %) labeled as SOC.