Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
264
datasets available to search
ShareScore release 0.7.1
Dataset results
264 results for “soil organic carbon”
Data from: Decipher soil organic carbon dynamics and driving forces across China using machine learning
<p><span><span>The dynamics of soil organic carbon (SOC) play a critical role in modulating global warming. However, the long-term spatiotemporal changes of SOC at large scale and the impacts of driving forces remain unclear. In this study, we investigated the dynamics of SOC in different soil layers across China through the 1980s to 2010s using a machine learning approach and quantified the impacts of the key factors based on factorial simulation experiments. Our results showed that the latest (2000-2014) SOC stock in the first meter soil (SOC<sub>100</sub>) was 80.68 ± 3.49 Pg C, of which 42.6% was stored in the top 20 cm, sequestrating carbon with a rate of 30.80 </span><span>± 12.37</span><span> g C m<sup>-2</sup> yr<sup>-1</sup> since the 1980s. Our experiments focusing on the recent two periods (2000s and 2010s) revealed that climate change exerted the largest relative contributions to SOC dynamics in both layers and warming or drying can result in SOC loss. However, the influence of climate change weakened with soil depth, while the opposite for vegetation growth. </span><span>Relationships between SOC and forest canopy height further confirmed this strengthened impact of vegetation with soil depth, and highlighted the carbon sink function of deep soil in mature forest. Moreover, our estimates suggested that SOC dynamics in 71% of topsoil were controlled by climate change and its coupled influence with environmental variation (CE). Meanwhile CE and the combined influence of climate change and vegetation growth dominated the SOC dynamics in 82.05% of the first meter soil. </span><span>Additionally, the national cropland topsoil organic carbon increased with a rate of 23.6 </span><span>± 7.6 </span><span>g C m<sup>-2</sup> yr<sup>-1</sup> since the 1980s, and the widely applied nitrogenous fertilizer was a key stimulus. </span><span>Overall, our study extended the knowledge about the dynamics of SOC and deepened our understanding about the impacts of the primary factors.</span></span></p>
Data from: Loamy sand soil approaches organic carbon saturation after 37 years of conservation tillage
<p>This is digital research data corresponding to a published manuscript, Loamy sand soil approaches organic carbon saturation after 37 years of conservation tillage. Conservation tillage is reported to increase soil organic carbon (SOC) and total nitrogen (TN) contents, but long-term (>30 yr) field results quantifying the responses in Coastal Plain Ultisols are sparse. The distribution, accumulation, and topsoil storage of SOC and TN after 37 yr of crop production using conventional (CvT) or conservation tillage (CnT) on a Norfolk loamy sand (fine-loamy, kaolinitic, thermic, Typic Kandiudults) were quantified. Soil samples were collected annually from the 0−5-, 5−10-, and 10−15-cm depth increments beneath corn (Zea mays L.), soybean [Glycine max (L.) Merr.], and cotton (Gossypium hirsutum L.) crops.</p>
Large dataset of soil organic carbon and topographic derivatives
<p><strong>Abstract</strong>: The dataset compiles 840 georeferenced SOC measurements over a 26-ha agricultural field located in southern Ontario, Canada with a sampling density of ~32 points per ha. As SOC is influenced by site topography (i.e., slope and landscape position), each point of the database was associated with a wide range of topographic derivatives. The columns include sample ID, SOC measurement, latitude, Longitude, NDVI values, as well as a set of 54 topographic derivatives (i.e., primary and secondary - see metadat.pdf attached file) with a spatial resolution of a 5 m. </p>
More soil organic carbon is sequestered through the mycelium-pathway than through the root-pathway under nitrogen enrichment in an alpine forest
<p><span>Plant roots and associated mycorrhizae exert a large influence on soil carbon (C) cycling. Yet, little was known whether and how roots and </span><span>ectomycorrhizal</span><span> extraradical mycelia differentially contribute to soil organic C (SOC) accumulation in alpine forests under increasing nitrogen (N) deposition. Using ingrowth cores, the relative contributions of the root-pathway (RP) (i.e., roots and rhizosphere processes) and mycelium-pathway (MP) (i.e., extraradical mycelia and hyphosphere processes) to SOC accumulation were distinguished and quantified in an ectomycorrhizal-dominated forest receiving chronic N addition (25 kg N ha<sup>-1</sup> yr<sup>-1</sup>). Under the non-N addition, the RP facilitated SOC accumulation, while the MP reduced SOC accumulation. Nitrogen addition enhanced the positive effect of RP on SOC accumulation from +18.02 mg C g<sup>-1</sup> to +20.55 mg C g<sup>-1</sup> but counteracted the negative effect of MP on SOC accumulation from -5.62 mg C g<sup>-1</sup> to -0.57 mg C g<sup>-1</sup>, as compared to the non-N addition. Compared to the non-N addition, the N-induced SOC accumulation was 1.62~2.21 mg C g<sup>-1</sup> and 3.23~4.74 mg C g<sup>-1</sup>, in the RP and the MP, respectively. The greater contribution of MP to SOC accumulation was mainly attributed to the higher microbial C pump (MCP) efficacy (the proportion of</span><span> increased microbial residual C to the increased SOC under N addition) in the MP (72.5%) relative to the RP (57%). The higher MCP efficacy in the MP was mainly associated with the higher fungal metabolic activity (i.e., the greater fungal biomass and N-acetyl glucosidase activity) and greater binding efficiency of fungal residual C to mineral surfaces than those of RP. Collectively, our findings highlight the indispensable role of mycelia and hyphosphere processes in the formation and accumulation of stable SOC in the context of increasing N deposition.</span></p>
Contribution of wheat and maize to soil organic carbon in a wheat-maize cropping system: a field and laboratory study
<p><span>Retention of crop biomass is widely recommended to improve soil organic carbon (SOC). However, the magnitude of contribution of aboveground residues and belowground roots from C3 and C4 crops to SOC is unclear. </span></p> <p><span>Data from a 10-year field experiment and a 60-day laboratory incubation were synthesized to identify the respective contribution of C3 (e.g., wheat) and C4 (e.g., maize) residues and roots to SOC, as well as its underlying mechanisms under no-till (NT) using <sup>13</sup>C labelling trace in wheat-maize rotations. </span></p> <p><span>The field experiment showed that residue retention significantly increased SOC accumulation, and SOC derived from wheat was 126.0% higher than that from maize. Conversion to NT promoted SOC derived from wheat and thus accumulated 17.6% higher SOC stock compared with plow tillage (PT) under residue returning at 0-20 cm soil depth (P<0.05). The data from laboratory incubation revealed the mechanisms that lower priming effects at 0-10 cm depth decreased total mineralization by 91.8% after inputs of wheat residues and roots compared with that of maize residues and roots, especially under NT compared with PT. Priming effects were negatively correlated with enzyme activities associated with the C recycle, SOC, and total nitrogen (TN) contents (P<0.01). NT increased enzyme activities, SOC, and TN contents and thus reduced priming effects and improved residual C. </span></p> <p><em><span>Synthesis and applications.</span></em><span> These results suggested that wheat may contribute more to SOC accumulation than maize, and carbon increment efficiency in farmland could be enhanced by considering the crucial roles of C3 crops in SOC accumulation. NT practice sustains the benefits of C3 crops to SOC sequestration</span> <span>in the upper soil depths.</span></p>
Effects of land clearing for agriculture on soil organic carbon stocks in drylands: A meta-analysis
<p><span>To improve our understanding of clearing natural ecosystems for cropland on soil organic carbon stocks in drylands, we searched for related peer-reviewed research papers published from 1980 to 2022 on the Web of Science (<a href="https://www.webofscience.com">https://www.webofscience.com</a>) and the Scopus Database (<a href="https://www.scopus.com">https://www.scopus.com</a>) (accessed on 30th April 2022). Then, we screened papers for </span><span>integrity, relevance, and scientific merit under the following criteria: (1) We made sure all studies were independent and based on field-measured data; (2) Each study had to report paired SOC stocks of cropland and adjacent natural ecosystems with the same or a similar suite of environmental factors; (3) Studies need to explicitly present results on SOC stocks or concentrations for certain depths and areas; (4) Studies have specified the types of natural ecosystems that were converted to cropland, which are used as criteria for defining CNEC types. Finally, we winnowed results to a total of 159 scientific journal articles, comprising 242 sites with 1379 paired soil layer observations from 601 paired soil profiles.</span></p>
Global soil organic carbon in tidal marshes version 1
<p><strong>[Please note: The current version is incorrect as the prediction values are maxed out to 256 due to a data formatting error when preparing the tiles for the Zenodo upload. We apologize for the inconvenience, and are in the process of preparing a new upload of the data.]</strong></p> <p>This dataset is the first version of the predictions, expected model error, and area of applicability of the global soil organic carbon in tidal marshes at a 30 m resolution. All methods are provided in detail in the accompanying <em>Nature Communications</em> paper, <a href="https://doi.org/10.1038/s41467-024-54572-9">Maxwell et al. (2024)</a> Soil carbon in the world's tidal marshes.</p> <p>Tidal marsh extent map</p> <ul> <li><a href="https://doi.org/10.1101/2023.05.26.542433">Worthington et al. (2023)</a> The distribution of global tidal marshes from earth observation data. <em>bioRxiv</em>. </li> </ul> <p>Training data</p> <ul> <li><a href="https://doi.org/10.1038/s41597-023-02633-x">Maxwell et al. (2023)</a> Global dataset of soil organic carbon in tidal marshes. <em>Scientific Data</em>.</li> <li><a href="https://doi.org/10.1111/gcb.17098">Holmquist et al. (2024)</a> The Coastal Carbon Library and Atlas: Open source soil data and tools supporting blue carbon research and policy. <em>Global Change Biology</em>. </li> <li>Citations for the training data from the above-mentioned syntheses are available <a href="https://github.com/Tania-Maxwell/global-marshC-map/blob/main/reports/02_data_process/data/map_training_data.bib">here</a>.</li> </ul> <p>Model </p> <ul> <li>Code available on <a href="https://github.com/Tania-Maxwell/global-marshC-map/tree/main">Github</a>.</li> <li>3D soil modelling approach: <a href="https://soilmapper.org/">Hengl & MacMillan (2019)</a>. Predictive Soil Mapping with R.</li> <li>Random forest model: <a href="https://doi.org/10.18637/jss.v028.i05">Kuhn (2008)</a>. Building Predictive Models in R Using the caret Package. <em>J. Stat. Softw</em>. </li> <li>k-NNDM spatial cross validation: <a href="https://hannameyer.github.io/CAST/">Meyer, Milà & Ludwig (2022)</a>. CAST: ‘caret’ Applications for Spatial-Temporal Models. </li> <li>Area of applicability: <a href="https://doi.org/10.1038/s41467-022-29838-9">Meyer & Pebesma (2022)</a>. Machine learning-based global maps of ecological variables and the challenge of assessing them. <em>Nature Communications</em>.</li> </ul> <h2>Description of files</h2> <ul> <li>GRID.zip: shapefile with the location of each tile in the zipped folders below </li> <li>Final_predicted_SOC_both_layers.png: final predicted tidal marsh soil organic carbon (SOC) for a) the 0-30 cm soil layer and b) the 30-100 cm soil layer (aggregated per 2° cell). </li> </ul> <p><strong>Area of applicability </strong></p> <ul> <li>aoa0.zip: the area of applicability (AOA) mask for the 0-30 cm layer. Pixels with an AOA value of 0 or 0.5 are considered outside the AOA; with an AOA value of 1 are considered inside the AOA.</li> <li>aoa30.zip: the area of applicability (AOA) mask for the 30-100 cm layer. Pixels with an AOA value of 0 or 0.5 are considered outside the AOA; with an AOA value of 1 are considered inside the AOA.</li> </ul> <p><strong>Final predictions and expected error </strong></p> <ul> <li>pred0_aoa.zip: predicted soil organic carbon for the 0-30 cm layer (Mg C ha-1), masked by the area of applicability.</li> <li>pred30_aoa.zip: predicted soil organic carbon for the 30-100 cm layer (Mg C ha-1), masked by the area of applicability.</li> <li>err0_aoa.zip: expected model error for the 0-30 cm layer (Mg C ha-1), masked by the area of applicability. </li> <li>err30_aoa.zip: expected model error for the 30-100 cm layer (Mg C ha-1), masked by the area of applicability. </li> </ul> <p><strong>Initial predictions and expected error</strong></p> <ul> <li>pred0.zip: predicted soil organic carbon for the 0-30 cm layer (Mg C ha-1).</li> <li>pred30.zip: predicted soil organic carbon for the 30-100 cm layer (Mg C ha-1).</li> <li>err0.zip: expected model error for the 0-30 cm layer for all tidal marsh extent pixels (Mg C ha-1).</li> <li>err30.zip: expected model error for the 30-100 cm layer for all tidal marsh extent pixels (Mg C ha-1).</li> </ul>
Contrasting Responses of Particulate and Mineral-Associated Organic Carbon to Afforestation Potentially Obscure Soil Carbon Accumulation [Dataset]
<p><span>This is the data repository for the manuscript “Contrasting Responses of Particulate and Mineral-Associated Organic Carbon to Afforestation Potentially Obscure Soil Carbon Accumulation” submitted to <em>Global Biogeochemical Cycles</em>.</span></p>
Data from: Warming reduces priming effect of soil organic carbon decomposition along a subtropical elevation gradient
<p>The priming effects (PEs) of soil organic carbon (SOC) is a crucial process affecting the C balance of terrestrial ecosystems. However, there is uncertainty about how PEs will respond to climate warming. Here, we sampled soils along a subtropical elevation gradient in China and conducted a 126-day lab-incubation experiment with and without additions of <sup>13</sup>C-labeled high-bioavailability glucose or low-bioavailability lignin. Based on the mean annual temperature (MAT) of each elevation (9.3–16.4°C), a temperature increase of 4°C was used to explore how PEs mediate the decomposition of SOC in response to warming. Our results showed that the magnitude of glucose-induced PEs (PE<sub>glu</sub>) was higher than lignin-induced PEs (PE<sub>lig</sub>), with both PEs linearly increasing with MAT. Across the MAT (<em>i.e</em>., elevation) gradient, warming had consistent negative effects on PE<sub>glu</sub>, whereas rising MAT exacerbated the negative effects of warming on PE<sub>lig</sub>. Moreover, the temperature sensitivity of SOC decomposition decreased after adding glucose and lignin across the MAT gradient, suggesting that fresh C inputs may prime microbial breakdown of labile SOC under warming. Taken together, warming alleviated the SOC loss due to PEs through varying mechanisms depending on substrate bioavailability, since warming mediated the PE<sub>glu</sub> by increasing available nitrogen and weakening microbial nitrogen-mining but inhibited the PE<sub>lig</sub> by switching from microbial nitrogen-mining to microbial co-metabolization. Our findings highlight the role of warming in regulating the PEs and suggest that incorporating the suppression effect of warming on PEs can contribute to the accurate prediction of soil C dynamics in a warming world.</p>
Supporting material for von Fromm et al (2024) Moisture and soil depth govern relationships between soil organic carbon and oxalate-extractable metals at the global scale
<p>This file contains the supporting material for von Fromm et al (2024) Moisture and soil depth govern relationships between soil organic carbon and oxalate-extractable metals at the global scale (<em>submitted</em>). </p> <p>For more details see the corresponding manuscript (once it is published) and the github repository (https://github.com/SophievF/Global_Mox_analysis/tree/main). </p>
How do fine root traits of fast-growing trees promote soil organic carbon stabilization?
<p>Soil represents a larger reservoir of soil organic carbon (SOC) than terrestrial vegetation, offering a great potential for reducing the widespread adverse consequences of climate change. In forests and tree plantations, fine roots significantly impact SOC stabilization through their functional traits. However, it is not obvious which fine root traits between those related to chemistry (easily decomposable or recalcitrant), to architecture or morphology are the most conducive to SOC stabilization in phylogenetically related fast-growing trees. We assessed the effects of root functional traits on SOC storage and stabilization by studying <span>five hybrid poplar clones </span><span>(<em>Populus </em>spp.)</span><span> </span><span>with different root traits in plantations located in New Liskeard, ON, Canada</span>. We collected <span>soil cores at depths of 0-20, 20-40 and 40-60 cm, and determined bulk soil organic carbon, </span><span>particulate organic carbon (> 53 μm, POC) and mineral-associated organic carbon (< 53 μm, MAOC) fractions and fine root (< 2 mm diameter) traits.</span><span> We found that r</span>oot length density (RLD) was the best predictor of increased SOC stocks and MAOC among all root traits. Soil organic C stocks and MAOC were also positively correlated with root traits indicative of low chemical recalcitrance (i.e. high N and soluble compounds concentrations and low lignin/N). Such easily decomposed root matter could be readily consumed by soil microorganisms and promote adsorption of microbial by-products onto mineral surfaces. Thus, root traits that increase the soil volume explored by fine roots and are associated with easily decomposed organic compounds play a key role in SOC accumulation and persistence.</p>
On-farm study reveals positive relationship between gas transport capacity and organic carbon content in arable soil (Data set)
<p>Data used for "On-farm study reveals positive relationship between gas transport capacity and organic carbon content in arable soil" by Colombi T, Walder F, Büchi L, Sommer M, Liu K, Six J, van der Heijden M, Charles R and Keller T. (2019). SOIL. 5, 91-105, https://doi.org/10.5194/soil-5-91-2019.</p> <p>.txt file "MetaInformation_On-farm study reveals positive relationship between gas transport capacity and organic carbon content in arable soil" contains all necessary meta-information </p>
Three-dimensional soil organic carbon density by logarithmic function and coefficient scaling in Yangtze River Delta, China
<h3>Three-dimensional soil organic carbon density (SOCD) dataset with 90-m resolution generated by Lin, S., Zhu, Q., Yin, B., Yang, G., Liao, K., Lai, X., Guo, C., 2025. Generating three-dimensional soil organic carbon density dataset by soil depth function and correction methods in Yangtze River Delta, China. Environmental Modelling & Software, <a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.envsoft.2025.106582" target="_blank" rel="noreferrer noopener"><span><span>https://doi.org/10.1016/j.envsoft.2025.106582.</span></span></a></h3> <h3>Here, based on the best performance, the three-dimensional SOCD generated by LF corrected with coefficient scaling method were provided. The accurate SOCD maps with the spatial resolution of 90-m at any specific depth interval can be generated by our method. This dataset includes:</h3> <ul> <li>Spatial distribution map of parameter 1 (p1) of LF (LF_p1.tif)</li> <li>Spatial distribution map of parameter 2 (p2) of LF (LF_p2.tif)</li> <li>The calculation code and fitted functions of scaling coefficient a, k of LF (fitted_fx_scalingcoff.m)</li> <li>Readme.docx</li> </ul> <p>Note: the unit of SOCD is kg m-2; the spatial distribution maps provided by this dataset does not mask any water bodies.</p> <p><strong>How to use our dataset? Please refer to our article and Readme.docx for more details.</strong></p> <p> </p> <p> </p>
Wetland sediment soil organic carbon sequestration data to support radiometric technique comparisons
<p>This workbook shows the ID, the geographical location, the year of sampling, and sediment core information in samples collected from undisturbed wetlands situated across four provinces of Canada (Alberta, Saskatchewan, Manitoba, and Ontario) from 2016 to 2019.</p>
Mapping Soil Organic Carbon in the World's Largest Arid Mangrove Forest (Indus Delta, Pakistan): A Multi-Sensor Remote Sensing and Machine Learning Approach
<p>Mangrove forests play a crucial role in carbon sequestration, especially in arid regions where their ability to store carbon in soil is vital for mitigating climate change. The Indus Delta in Pakistan, the world’s largest arid mangrove forest system, lacks spatially explicit data on Soil Organic Carbon (SOC) despite its importance for conservation and carbon budgeting. This study aims to establish a baseline SOC map 2020 at 10 m spatial resolution using Sentinel-1 (Synthetic Aperture Radar) and Sentinel-2 (MultiSpectral Instrument) satellite imagery, integrated with in-situ soil sampling. SOC predictions were made using a Classification and Regression Tree (CART) machine learning model within the Google Earth Engine platform, leveraging 40 predictor variables, including spectral bands and derived indices. A total of 53 topsoil (0-10 cm) samples were collected in February 2020 across the Indus Delta, and SOC was analyzed using the Walkley-Black method. The results showed an average SOC value of 65.88 Mg C ha⁻¹ with substantial spatial variability, ranging from 15.06 Mg C ha⁻¹ to 138.03 Mg C ha⁻¹ with a total of 0.91 Pg C. The CART model demonstrated high accuracy, with an R² of 0.95 and an RMSE of 9.18 Mg C ha⁻¹. However, the region faces challenges such as seawater intrusion and salinity, which threaten its ability to sequester carbon. With the first high-resolution SOC map for the Indus Delta, this study provides valuable insights for ecosystem management, conservation planning, and carbon budgeting. These findings of this study have the potential to significantly influence initiatives like REDD+ and Blue Carbon projects, which aim to enhance carbon sequestration while addressing the ecological challenges facing Pakistan’s mangroves</p>
Climate warming and soil drying lead to a reduction of riverine dissolved organic carbon in China
<p>The raw datasets for spatio-temporal analysis of riverine dissolved organic carbon in China</p>
Global warming may turn ice-free areas of Maritime and Peninsular Antarctica into potential soil organic carbon sinks
<h2>Dear researchers and interested parties,</h2> <p>We are excited to announce the publication of our recent research on Zenodo, presenting <strong>high-resolution</strong> (8 m) spatial models of <strong>soil organic carbon (SOC) stocks in ice-free areas of Maritime and Peninsular Antarctica</strong>. This research evaluates the potential impacts of climate change on SOC stocks under three Shared Socioeconomic Pathways (SSPs), providing a comprehensive understanding of the role these regions may play as carbon sinks in the face of intensified global warming.</p> <h2>Available resources:</h2> <h3>SOC stock predictions:</h3> <p>We provide detailed maps of SOC estimates and uncertainties for different soil depths across various IPCC Shared Socioeconomic Pathways, including mean values (Mg ha⁻¹) and coefficients of variation (%). All maps are available in "tif" format, using the South Pole Stereographic projection system (<a href="https://epsg.io/102021" target="_blank" rel="noopener">ESRI:102021</a>).</p> <p>Open-Source Code and Data: The entire analytical workflow, developed in R, <strong>is accessible through our <a href="https://github.com/moquedace/soc_stock_antarctica" target="_blank" rel="noopener">GitHub repository</a></strong>, ensuring reproducibility and transparency. Additional methodological details are provided in our publication:</p> <p>Mello, D., Francelino, M. R., Moquedace, C. M., Baldi, C. G. O., Silva, L., Siqueira, R. G., Veloso, G. V., Fernandes-Filho, E. I., Thomazini, A., Demattê, J., Ferreira, T., Gomes, L. C., Senra, E., Schaefer, C. E. G. R. Global warming may turn ice-free areas of Maritime and Peninsular Antarctica into potential soil organic carbon sinks. <em>Commun Earth Environ</em>, v. 6, n. 1, p. 143, 2025. DOI: <a href="https://doi.org/10.1038/s43247-024-01937-z" target="_blank" rel="noopener">10.1038/s43247-024-01937-z</a></p> <h2>Availability objectives:</h2> <h3>Advancing scientific collaboration:</h3> <p>We invite scientists, researchers, and organizations to explore our findings to support additional studies on soil carbon dynamics and climate change.</p> <h3>Supporting environmental understanding:</h3> <p>By providing open access to these models, we aim to contribute to global knowledge on Antarctic soil carbon dynamics and assist in formulating sustainable climate mitigation strategies.</p> <h3>Fostering innovation:</h3> <p>Sharing this data aims to stimulate advances in spatial modeling and SOC prediction methodologies, especially in high-latitude environments.</p> <h2>We appreciate your interest and collaboration. We look forward to advancing knowledge and promoting sustainable solutions to essential environmental challenges together.</h2>
Soil dissolved organic carbon in terrestrial ecosystems: global budget, spatial distribution and controls
<p><strong>Aims: </strong>Soil dissolved organic carbon (DOC) is a primary form of labile carbon in terrestrial ecosystems and therefore plays a vital role in soil carbon cycling. This study aims to quantify the budgets of soil DOC at biome- and global levels and to examine the variations in soil DOC and their environmental controls. Location: Global Time period: 1981 - 2019 Method: We compiled a global dataset and analyzed the concentration and distribution of DOC across 10 biomes.</p> <p><strong>Results: </strong>Large variations in DOC are found among biomes across space and the soil DOC concentration declines exponentially along soil depths. Tundra has the highest soil DOC concentration in 0 - 30 cm soils (453.75 (95% confidence interval: 324.95 – 633.5) mg·kg-1); whereas tropical and temperate forests have relatively lower DOC concentrations, ranging from 30.20 (24.78 - 36.80) mg·kg-1 to 54.54 (49.77 – 59.77) mg·kg-1. DOC generally accounts for < 1% of total organic carbon in soils, and DOC in 0 - 30 cm contributes more than half of total DOC in 0 - 100 cm soil profile. Furthermore, variations in DOC are primarily controlled by soil texture, moisture, and total organic carbon.</p> <p><strong>Main conclusion: </strong>A global synthesis is combined with an empirical model to extrapolate the DOC concentration along soil profiles across the globe, and global budgets of DOC are estimated as 7.20 Pg C in top 0 - 30 cm and 12.97 Pg C in 0 - 100 cm, respectively, with a considerable variation among biomes. The strong soil texture control but weak TOC control on DOC variations suggest that the investigation of physical protection of soil organic carbon might need to expand to consider the labile C in soils. The global maps of DOC concentration serve as a benchmark for validating land surface models in estimating carbon storage in soils.</p>
Cryoturbation leads to iron-organic carbon associations along a permafrost soil chronosequence in northern Alaska
<p>In permafrost soils, substantial amounts of organic carbon (OC) are potentially protected from microbial degradation and transformation into greenhouse gases by association with reactive iron (Fe) minerals. As permafrost environments respond to climate change, increased drainage of thaw lakes in permafrost regions is predicted. Soils will subsequently develop on these drained thaw lakes, but the role of Fe-OC associations in future OC stabilization during this predicted soil development is unknown. To fill this knowledge gap, we have examined Fe-OC associations in organic, cryoturbated and mineral horizons along a 5500-year chronosequence of drained thaw lake basins in Utqiaġvik, Alaska. By applying chemical extractions, we found that ~17 % of the total OC content in cryoturbated horizons is associated with reactive Fe minerals, compared to ~10 % in organic or mineral horizons. As soil development advances, the total stocks of Fe-associated OC more than double within the first 50 years after thaw lake drainage, because of increased storage of Fe-associated OC in cryoturbated horizons (from 8 to 75 % of the total Fe-associated OC stock). Spatially-resolved nanoscale secondary ion mass spectrometry showed that OC is primarily associated with Fe(III) (oxyhydr)oxides which were identified by <sup>57</sup>Fe Mössbauer spectroscopy as ferrihydrite. High OC:Fe mass ratios (>0.22) indicate that Fe-OC associations are formed via co-precipitation, chelation and aggregation. These results demonstrate that, given the proposed enhanced drainage of thaw lakes under climate change, OC is increasingly incorporated and stabilized by the association with reactive Fe minerals as a result of soil formation and increased cryoturbation.</p>
Large-scale drivers of relationships between soil microbial properties and organic carbon across Europe
<p>The aim of this study was to quantify direct and indirect relationships between soil microbial community properties (potential basal respiration, microbial biomass) and abiotic factors (soil, climate) in three major land-cover types.</p> <p>Location: Europe</p> <p>Time period: 2018</p> <p>Major taxa studied: Microbial community (fungi and bacteria)</p> <p>We collected 881 soil samples from across Europe in the framework of the Land Use/Land Cover Area Frame Survey (LUCAS). We measured potential soil basal respiration at 20ºC and microbial biomass (substrate-induced respiration) using an O2-microcompensation apparatus. Climate and soil data were obtained from previous LUCAS surveys and online databases. Structural equation modeling (SEM) was used to quantify relationships between variables, and equations extracted from SEMs were used to create predictive maps. Fatty acid methyl esters were measured in a subset of samples to distinguish fungal from bacterial biomass. Soil microbial properties in croplands were more heavily affected by climate variables than those in forests. Potential soil basal respiration and microbial biomass were correlated in forests but decoupled in grasslands and croplands, where microbial biomass depended on soil carbon. Forests had a higher ratio of fungi to bacteria than grasslands or croplands. Soil microbial communities in grasslands and croplands are likely carbon-limited in comparison with those in forests, and forests have a higher dominance of fungi indicating differences in microbial community composition. Notably, the often already-degraded soils of croplands could be more vulnerable to climate change than more natural soils. The provided maps show potentially vulnerable areas that should be explicitly accounted for in coming management plans to protect soil carbon and slow the increasing vulnerability of European soils to climate change.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.