Find research datasets worth reusing

openCC0Aug 2022View details →

Nevada Desert FACE Facility Soil Organic Carbon Data

This data set is the result of soils analysis from the Nevada Desert Free-Air CO2 Enrichment Facility (NDFF) experiment in the Mojave Desert and reports soil organic carbon (%C) and delta 13C stable isotope values. These soils were collected at the end of the NDFF experiment in 2007 and stored at Cornell University until analysis in 2018. Soils were harvested from 6 cover types (5 perennial vegetation covers and unvegetated interspace soils) from 0-100 cm in the soil profile in 20 cm increments. Soils were pretreated for inorganic carbon removal using an acid fumigation technique with HCl. Bulk density from NDFF plots is provided (kg soil* ha ^ -1) so that SOC stocks may be calculated. These data provide the basis for a publication challenging the prevailing idea that arid ecosystems will increase soil organic carbon stocks under long term elevated CO2.

openCC (other)Dec 2022View details →

Organic and inorganic carbon concentration and stable isotope composition in poorly drained agricultural soils in Iowa, USA

We measured soil organic carbon (SOC) and inorganic carbon (carbonate) in samples collected along topographic gradients in agricultural fields in Iowa, USA, in 2018. We also measured stable isotopes of SOC, soil nitrogen, and carbon in respired CO2 to provide additional context for organic matter dynamics. Additional physical, chemical, and hydrologic variables were measured on these samples and in the field sites to understand mechanisms underlying patterns in soil organic and inorganic carbon.

openCC (other)Jun 2023View details →

Effects of drying temperature on potential carbon mineralization and water-extractable organic carbon in Iowa cropland and riparian buffer soils

Measuring carbon dioxide (CO2) produced after re-wetting a previously dried soil is an increasingly popular soil health assay, but there is disagreement on the optimal soil drying temperature. We tested whether soil drying temperature impacts water-extractable organic carbon (WEOC) and soil CO2 emissions (potential carbon mineralization) following rewetting of dried soil. Samples were collected at four sites in north-central Iowa, US, and each site had soils planted to corn/soybean or perennial vegetation. The dataset includes measurements of WEOC prior to the incubation experiment, and measurements of CO2 flux and its stable carbon isotope ratio over the course of a 28-day incubation. The manuscript describing these data is under review in Geoderma.

openCC (other)Jan 2020View details →

Photo-oxidation and photomineralization apparent quantum yield dataset for dissolved organic carbon leached from permafrost soils collected from the North Slope of Alaska, July 2018.

Dissolved organic carbon (DOC) was leached from permafrost soils near the Toolik Field Station in the Alaskan Arctic and then characterized for its photochemical properties. Oxygen (O2) consumed from photo-oxidation of permafrost DOC was measured as a function of sunlight wavelength, defined as the apparent quantum yield spectrum of photo-oxidation (O2 consumed per mol photon absorbed by DOC). Carbon dioxide (CO2) produced from photomineralization of permafrost DOC was measured as a function of sunlight wavelength, defined as the apparent quantum yield spectrum of photomineralization (CO2 produced per mol photon absorbed by DOC).

opencc-zeroDec 2018View details →

Data from: Soil organic carbon stability in forests: distinct effects of tree species identity and traits

Rising atmospheric CO2 concentrations have increased interest in the potential for forest ecosystems and soils to act as carbon (C) sinks. While soil organic C contents often vary with tree species identity, little is known about if, and how, tree species influence the stability of C in soil. Using a 40‐year‐old common garden experiment with replicated plots of eleven temperate tree species, we investigated relationships between soil organic matter (SOM) stability in mineral soils and 17 ecological factors (including tree tissue chemistry, magnitude of organic matter inputs and their turnover, microbial community descriptors, and soil physico‐chemical properties). We measured five SOM stability indices, including heterotrophic respiration, C in aggregate‐occluded particulate organic matter (POM) and mineral‐associated SOM, and bulk SOM δ15N and ∆14C. The stability of SOM varied substantially among tree species and this variability was independent of the amount of organic C in soils. Thus, when considering forest soils as C sinks, the stability of C stocks must be considered in addition to their size. Further, our results suggest tree species regulate soil C stability via the composition of their tissues, especially roots. Stability of SOM appeared to be greater (as indicated by higher δ15N and reduced respiration) beneath species with higher concentrations of nitrogen and lower amounts of acid‐insoluble compounds in their roots, while SOM stability appeared to be lower (as indicated by higher respiration and lower proportions of C in aggregate‐occluded POM) beneath species with higher tissue calcium contents. The proportion of C in mineral‐associated SOM and bulk soil ∆14C, though, were negligibly dependent on tree species traits, likely reflecting an insensitivity of some SOM pools to decadal‐scale shifts in ecological factors. Strategies aiming to increase soil C stocks may thus focus on particulate C pools, which can more easily be manipulated and are most sensitive to climate change.

opencc-by-4.0Nov 2023View details →

Quantification of soil organic carbon: the challenge of biochar-induced spatial heterogeneity

R-script and output from model on spatially discrete biochar application and its influence on representative SOC sampling. An additional document to explain the data curation is also available ("Comment on Data curation").

opencc-zeroDec 2023View details →

Soil organic carbon loss decreases biodiversity but stimulates multitrophic interactions that promote belowground metabolism

Soil organic carbon (SOC) plays an essential role in mediating community structure and metabolic activities of belowground biota. Unraveling the evolution of belowground communities and their feedback mechanisms on SOC dynamics helps embed the ecology of soil microbiome into carbon cycling, which serves to improve biodiversity conservation and carbon management strategy under global change. Here, croplands with a SOC gradient were used to understand how belowground metabolisms and SOC decomposition were linked to the diversity, composition, and co-occurrence networks of belowground communities encompassing archaea, bacteria, fungi, protists, and invertebrates. As SOC decreased, the diversity of prokaryotes and eukaryotes also decreased, but their network complexity showed contrasting patterns: prokaryotes increased due to intensified niche overlap, while that of eukaryotes decreased possibly because of greater dispersal limitation owing to the breakdown of macro aggregates. Despite the decrease in biodiversity and SOC stocks, the belowground metabolic capacity was enhanced as indicated by increased enzyme activity and decreased enzymatic stoichiometric imbalance. This could, in turn, expedite carbon loss through respiration, particularly in the slow-cycling pool. The enhanced belowground metabolic capacity was dominantly driven by greater multitrophic network complexity and particularly negative (competitive and predator-prey) associations, which fostered the stability of the belowground metacommunity. Interestingly, soil abiotic conditions including pH, aeration, and nutrient stocks, exhibited a less significant role. Overall, this study reveals a greater need for soil C resources across multitrophic levels to maintain metabolic functionality as declining SOC results in biodiversity loss. Our researchers highlight the importance of integrating belowground biological processes into models of SOC turnover, to improve agroecosystem functioning and carbon management in the face of intensifying anthropogenic land-use and climate change.

opencc-by-4.0Nov 2024View details →

scmcclelland/joint-mediation-study: Data, Analysis, and Figure Scripts for "Soil organic carbon sequestration jointly-mediated by plants and microbes after compost application"

This repository contains data, analysis, and figure scripts to create findings from the manuscript "Soil organic carbon sequestration jointly-mediated by plants and microbes after compost application" currently under minor revisions. This release includes updated code, primarily improvements to figures, and a new script for a supplementary map figure.

opencc-zeroJun 2024View details →

Total data for global pattern of organic carbon pools in forest soil

Understanding the mechanisms of soil organic carbon (SOC) sequestration in forests is vital to ecosystem carbon budgeting, and helps gain insight in the functioning and sustainable management of world forests. An explicit knowledge of the mechanisms driving global SOC sequestration in forests is still lacking because of the complex interplays between climate, soil and forest type in influencing SOC pool size and stability. Based on a synthesis of 1179 observations from 292 studies across global forests, we quantified the relative importance of climate, soil property and forest type on total SOC content and the specific contents of physical (particulate vs. mineral-associated SOC) and chemical (labile vs. recalcitrant SOC) pools in upper 10 cm mineral soils, as well as SOC stock in the O horizons. The variability in the total SOC content of the mineral soils was better explained by climate (47~60%) and soil factors (26%~50%) than by NPP (10~20%). The total SOC content and contents of particulate (POC) and recalcitrant SOC (ROC) of the mineral soils all decreased with increasing mean annual temperature because SOC decomposition overrides the C replenishment under warmer climate. The content of mineral-associated organic carbon (MAOC) was influenced by temperature, which directly affected microbial activity. Additionally, the presence of clay and iron oxides physically protected SOC by forming MAOC. The SOC stock in the O horizons was larger in the temperate zone and Mediterranean regions than in the boreal and sub/tropical zones. Mixed forests had 64% larger SOC pools than either broadleaf or coniferous forests, because of i) higher productivity, and ii) litter input from different tree species resulting in diversification of molecular composition of SOC and microbial community. While climate, soil and forest type jointly determine the formation and stability of SOC, climate predominantly controls the global patterns of SOC pools in forest ecosystems.

opencc-by-4.0Dec 2018View details →

Database Manuscript Temperature and moisture are minor drivers of regional-scale soil organic carbon dynamics - Gonzalez Dominguez et al

The database contained the data used in the manuscript Temperature and moisture are minor drivers of regional-scale soil organic carbon dynamics, by Gonzalez Dominguez et al.

opencc-by-4.0Nov 2024View details →

Long-term biochar and soil organic carbon stability– Evidence from field experiments in Germany-ROW DATA

Row data for researcher paper Long-term biochar and soil organic carbon stability– Evidence from field  experiments in Germany

opencc-by-4.0Apr 2023View details →

Soil organic carbon models need independent time-series validation for reliable prediction

Supplementary Data 1 to the paper: Soil organic carbon models need independent time-series validation for reliable prediction By: Le Noë, J., Manzoni, S., Abramoff, R.Z., Bölscher, T., Bruni, E., Cardinael, R., Ciais, P., Chenu, C., Clivot, H., Derrien, D., Ferchaud, F., Garnier, P., Goll, D., Lashermes, G., Martin, M.P., Rasse, D., Rees, F., Sainte-Marie, J., Salmon, E., Schiedung, M., Schimel, J., Wieder, W.R., Abiven, S., Barré, P., Cécillon, L., Guenet, B.

opencc-by-4.0Jan 2023View details →

Upscaling soil organic carbon measurements at the continental scale using multivariate clustering analysis and machine learning

Data Description: To improve SOC estimation in the United States, we upscaled site-based SOC measurements to the continental scale using multivariate geographic clustering (MGC) approach coupled with machine learning models. First, we used the MGC approach to segment the United States at 30 arc second resolution based on principal component information from environmental covariates (gNATSGO soil properties, WorldClim bioclimatic variables, MODIS biological variables, and physiographic variables) to 20 SOC regions. We then trained separate random forest model ensembles for each of the SOC regions identified using environmental covariates and soil profile measurements from the International Soil Carbon Network (ISCN) and an Alaska soil profile data. We estimated United States SOC for 0-30 cm and 0-100 cm depths were 52.6 + 3.2 and 108.3 + 8.2 Pg C, respectively. Files in collection (32): Collection contains 22 soil properties geospatial rasters, 4 soil SOC geospatial rasters, 2 ISCN site SOC observations csv files, and 4 R scripts gNATSGO TIF files: ├── available_water_storage_30arc_30cm_us.tif                   [30 cm depth soil available water storage] ├── available_water_storage_30arc_100cm_us.tif                 [100 cm depth soil available water storage] ├── caco3_30arc_30cm_us.tif                                                 [30 cm depth soil CaCO3 content] ├── caco3_30arc_100cm_us.tif                                               [100 cm depth soil CaCO3 content] ├── cec_30arc_30cm_us.tif                                                     [30 cm depth soil cation exchange capacity] ├── cec_30arc_100cm_us.tif                                                   [100 cm depth soil cation exchange capacity] ├── clay_30arc_30cm_us.tif                                                     [30 cm depth soil clay content] ├── clay_30arc_100cm_us.tif                                                   [100 cm depth soil clay content] ├── depthWT_30arc_us.tif                                                        [depth to water table] ├── kfactor_30arc_30cm_us.tif                                                 [30 cm depth soil erosion factor] ├── kfactor_30arc_100cm_us.tif                                               [100 cm depth soil erosion factor] ├── ph_30arc_100cm_us.tif                                                      [100 cm depth soil pH] ├── ph_30arc_100cm_us.tif                                                      [30 cm depth soil pH] ├── pondingFre_30arc_us.tif                                                     [ponding frequency] ├── sand_30arc_30cm_us.tif                                                    [30 cm depth soil sand content] ├── sand_30arc_100cm_us.tif                                                  [100 cm depth soil sand content] ├── silt_30arc_30cm_us.tif                                                        [30 cm depth soil silt content] ├── silt_30arc_100cm_us.tif                                                      [100 cm depth soil silt content] ├── water_content_30arc_30cm_us.tif                                      [30 cm depth soil water content] └── water_content_30arc_100cm_us.tif                                   [100 cm depth soil water content] SOC TIF files: ├──30cm SOC mean.tif                             [30 cm depth soil SOC] ├──100cm SOC mean.tif                           [100 cm depth soil SOC] ├──30cm SOC CV.tif                                 [30 cm depth soil SOC coefficient of variation] └──100cm SOC CV.tif                              [100 cm depth soil SOC coefficient of variation] site observations csv files: ISCN_rmNRCS_addNCSS_30cm.csv       30cm ISCN sites SOC replaced NRCS sites with NCSS centroid removed data ISCN_rmNRCS_addNCSS_100cm.csv       100cm ISCN sites SOC replaced NRCS sites with NCSS centroid removed data Data format: Geospatial files are provided in Geotiff format in Lat/Lon WGS84 EPSG: 4326 projection at 30 arc second resolution. Geospatial projection:  <pre><code>GEOGCS["GCS_WGS_1984", DATUM["D_WGS_1984", SPHEROID["WGS_1984",6378137,298.257223563]], PRIMEM["Greenwich",0], UNIT["Degree",0.017453292519943295]] (base) [jbk@theseus ltar_regionalization]$ g.proj -w GEOGCS["wgs84", DATUM["WGS_1984", SPHEROID["WGS_1984",6378137,298.257223563]], PRIMEM["Greenwich",0], UNIT["degree",0.0174532925199433]] </code></pre>

opencc-by-4.0Sep 2023View details →

Potassium fertilization effects on cereal yield and soil organic carbon in agricultural ecosystems at the global scale

This dataset includes the raw data of a global meta-analysis study on the responses of cereal yield and soil organic carbon to potassium fertilization in agricultural ecosystems.