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opencc-by-4.0Sep 2024View details →

Spatiotemporal prediction of soil organic carbon density (SOCD) for pan-Europe (2000-2022) in 3D+T

<h2>Sub-dataset: SOCD mean, 2016–2020</h2> <h2>Disclaimer</h2> This is the first release of pan-EU predictions of soil health indicators (the Soil Health Data Cube). Use for testing purposes only. A publication describing methods used has been submitted to PeerJ and is in review. Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or European Commision. Neither the European Union nor the granting authority can be held responsible for them. The data is provided "as is". AI4SoilHealth project consortium and its suppliers and licensors hereby disclaim all warranties of any kind, express or implied, including, without limitation, the warranties of merchantability, fitness for a particular purpose and non-infringement. Neither AI4SoilHealth project Consortium nor its suppliers and licensors, makes any warranty that the Website will be error free or that access thereto will be continuous or uninterrupted. You understand that you download from, or otherwise obtain content or services through, the Website at your own discretion and risk. <h2>Description</h2> This dataset covers pan-European areas, including Ukraine, the UK, and Turkey. This data cube could be used for applications such as soil property mapping and comprehensive soil health assessment across Europe. The dataset spans four depth ranges and multiple time periods, providing information for studies on soil organic carbon stock and dynamics. This dataset is part of the Spatiotemporal prediction of soil organic carbon density for Europe (2000-2022) in 3D+T dataset. Check the related identifiers section below to access other parts of the dataset. This data set includes: <ul> <li>Soil Organic Carbon Density (SOCD) (2000-2022, 4-year intervals): This data includes mean, p975, and p025 SOCD maps for four depth ranges (0-20cm, 20-50cm, 50-100cm, and 100-200cm) in kg/m3 (scaled 10x). </li> <li>Organic carbon content based on dry combustion weight percentage (WPCT) (2000-2022, 4-year intervals): This data includes mean, p975, and p025 WPCT maps for four depth ranges (0-20cm, 20-50cm, 50-100cm, and 100-200cm) in percentage (scaled 10x). </li> </ul> <h3>Related identifiers</h3> <ul> <li>SOCD mean: <a href="https://doi.org/10.5281/zenodo.13754343">2000-2004</a> <a href="https://doi.org/10.5281/zenodo.13771721">2004-2008</a> <a href="https://doi.org/10.5281/zenodo.13771841">2008-2012</a> <a href="https://doi.org/10.5281/zenodo.13771911">2012-2016</a> <a href="https://doi.org/10.5281/zenodo.13771967">2016-2020</a> <a href="https://doi.org/10.5281/zenodo.13772054">2020-2022</a> </li> <li>SOCD p025: <a href="https://doi.org/10.5281/zenodo.13779539">2000-2004</a> <a href="https://doi.org/10.5281/zenodo.13774064">2004-2008</a> <a href="https://doi.org/10.5281/zenodo.13774089">2008-2012</a> <a href="https://doi.org/10.5281/zenodo.13774114">2012-2016</a> <a href="https://doi.org/10.5281/zenodo.13774167">2016-2020</a> <a href="https://doi.org/10.5281/zenodo.13774196">2020-2022</a> </li> <li>SOCD p975: <a href="https://doi.org/10.5281/zenodo.13778472">2000-2004</a> <a href="https://doi.org/10.5281/zenodo.13773396">2004-2008</a> <a href="https://doi.org/10.5281/zenodo.13773765">2008-2012</a> <a href="https://doi.org/10.5281/zenodo.13773828">2012-2016</a> <a href="https://doi.org/10.5281/zenodo.13773953">2016-2020</a> <a href="https://doi.org/10.5281/zenodo.13774003">2020-2022</a> </li> </ul> <h3>Data Details</h3> <ul> <li>Time period: 2000–2022, in 4-year intervals (last period covers 2020–2022).</li> <li>Type of data: Spatiotemporal soil organic carbon data cube, with depth ranges and weighted percentage data for soil carbon assessments.</li> <li>How the data was collected or derived: The data was derived using machine learning models.</li> <li>Statistical methods used: Quantile Random Forest</li> <li>Limitations or exclusions in the data: The dataset does not include data for Svalbard. </li> <li>Coordinate reference system: EPSG:3035</li> <li>Bounding box (Xmin, Ymin, Xmax, Ymax): (900,000, 899,000, 7,401,000, 5,501,000)</li> <li>Spatial resolution: 30m</li> <li>Image size: 216,700P x 153,400L</li> <li>File format: Cloud Optimized Geotiff (COG) format.</li> </ul> <h3>Support</h3> If you discover a bug, artifact, or inconsistency, or if you have a question please raise a GitHub issue: GitLab Issues (tbc) <h3>Name convention</h3> To ensure consistency and ease of use across and within the projects, we follow the standard Ai4SoilHealth and Open-Earth-Monitor file-naming convention. The convention works with 10 fields that describe important properties of the data. In this way users can search files, prepare data analysis etc, without needing to open files. The fields are: <ol> <li>generic variable name: oc = organic carbon</li> <li>variable procedure combination: iso.10694.1995.mg.cm3 = ISO method 10694:1995, with values in mg/cm3 for SOCD | iso.10694.1995.wpct = ISO method 10694:1995, with values in weighted percentage of organic carbon content.</li> <li>Position in the probability distribution/variable type: m = mean | p975 = percentile 97.5 | p025 = percentile 2.5</li> <li>Spatial support: 30m</li> <li>Depth reference: b0cm..20cm = depth range from 0 to 20cm</li> <li>Time reference begin time: 20000101 = 2000-01-01</li> <li>Time reference end time: 20041231 = 2004-12-31</li> <li>Bounding box: eu = pan-Europe</li> <li>EPSG code: epsg.3035</li> <li>Version code: v20240804 = version from 2024-08-04</li> </ol>

opencc-by-4.0Jun 2024View details →

Suppression of Methanogenesis by Microbial Reduction of Iron-Organic Carbon Associations in Fully Thawed Permafrost Soil

This data set contains data associated with the manuscript "Suppression of Methanogenesis by Microbial Reduction of Iron-Organic Carbon Associations in Fully Thawed Permafrost Soil". Currently under review.

opencc-zeroNov 2021View details →

Climatic controls on soil carbon accumulation and loss in a dryland ecosystem

Arid and semiarid ecosystems drive year-to-year variability in the strength of the terrestrial carbon (C) sink, yet there is uncertainty about how soil C gains and losses contribute to this variation. To address this knowledge gap, we embedded C-depleted soil mesocosms, containing litter or biocrust C inputs, within an in situ dryland ecosystem warming experiment. Over the course of one year, changes in microbial biomass and total soil organic C pools were monitored alongside hourly measurements of soil CO2 flux. We also developed a biogeochemical model to explore the mechanisms that gave rise to observed soil C dynamics. Field data and model simulations demonstrated that water exerted much stronger control on soil biogeochemistry than temperature, with precipitation events triggering large CO2 pulses and transport of litter- and biocrust-derived C into the soil profile. We expected leaching of organic matter would result in steady accumulation of C within the mineral soil over time. Instead, the size of the total organic C pool fluctuated throughout the year, largely in response to microbial growth: increases in the size of microbial biomass were negatively correlated with the quantity of C residing in the top 2 cm, where most biogeochemical changes were observed. Our data and models suggest that microbial responses to precipitation events trigger rapid metabolism of dissolved organic C inputs, which strongly limit accumulation of autotroph-derived C belowground. Accordingly, changes in the magnitude and/or frequency of precipitation events in this dryland ecosystem could have profound impacts on the strength of the soil C sink.

opencc-zeroNov 2021View details →

The effect of plant invasion on soil microbial carbon-use efficiency in semiarid grasslands of the Rocky Mountain West

1. Grassland ecosystems invaded by exotic plant species often exhibit substantially higher aboveground productivity and soil nitrogen (N) than the native communities they replace. These shifts are likely associated with altered microbial carbon (C) and N cycling, but we know surprisingly little about how these processes change with plant invasion. 2. Targeting four invasive plant species common in the Rocky Mountain West, we collected soils from invaded and adjacent uninvaded grassland field plots, as well as from an experimental garden. We used a laboratory incubation of soils with 13C- and 15N-labelled substrates to examine how microbial C respiration, C assimilation, and N cycling differed among plant communities. To assess how these rates corresponded with plant productivity and microbial communities, we measured aboveground plant biomass and characterized bacterial and fungal communities using Illumina sequencing. 3. In the paired observational plots, soil microbial communities associated with invaders generally had higher respiration rates and lower growth rates than those associated with the native plant communities, leading to a lower microbial carbon-use efficiency (CUE). Overall, soil substrate with a lower C:N was related to decreased CUE, and lower CUE was related to increased gross and net N mineralization. In turn, faster gross N mineralization was related to greater aboveground biomass. These patterns coincided with significant differences in fungal communities, whereas bacterial communities varied by site. Invasive plants also altered microbial communities in the experimental plots, but this was not associated with shifts in microbial CUE, which was low overall. 4. Synthesis. Our results provide evidence that invasive plants alter bacterial and fungal communities. These shifts were not associated with changes in microbial CUE and, thus, the often-assumed link between compositional and functional shifts was not apparent in this study. However, lower CUE was associated with elevated rates of N cycling and productivity, which, in low-productivity systems, could help explain the increased growth and success of exotic plant invaders.

opencc-by-4.0Jan 2022View details →

Raw data for "Plot-scale variability of organic carbon in temperate agricultural soils - Implications for soil monitoring"

This dataset is the raw data that belongs to a peer-reviewed study on the small-distance variability of soil organic carbon in agricultural soils in Germany. It consists of three different files. The first file gives the coordinates of the 16 soil cores that were taken at each of the 16 sites (eight cropland and eight grassland sites). The second file gives the soil properties measured at each individual core (n=16 per site) and the third file the soil properties measured at each indivdual soil profile (n=6 per site).

opencc-zeroFeb 2022View details →

Soil carbon composition and persistence under various management practices on Mollisols

This dataset contains information of the manuscript entitled "Persistent soil carbon enhanced in Mollisols by well-managed grasslands but not annual grain or dairy forage cropping systems". Grasslands-derived Mollisols cover a large area globally and are usually under intensive agricultural production, which has liberated large amounts of carbon (C) into the atmosphere. Whether improved management practices such as no-till, diversified crop rotations, legumes and/or manure additions, or re-establishing perennial grasslands and integrating livestock can restore soil C on Mollisols is unclear. In this study, we utilized the Wisconsin Integrated Cropping Systems Trial (WICST), a long-term trial comparing conventional and alternative agricultural systems in the North Central USA, and studied soil C composition and persistence, and their relationships with soil microbial attributes after 29 years of different agricultural management. The soil C composition data include particulate organic matter (POM)-C, which is believed to be primarily plant-derived and unprocessed or partially processed by microbes, and mineral-associated organic matter (MAOM)-C, which is believed to be mostly microbial-derived and simple structured. These soil C fractions were obtained by physical fractionation (53 µm). Diffuse reflectance infrared fourier transform spectroscopy (DRIFTS) was used to study the composition of MAOM (Aliphatic C vs. Aromatic C). Soil microbial attributes studied include soil microbial biomass C (by chloroform fumigation method), microbial C-use efficiency (CUE) (by 13C-tracing method), and microbial necromass (amino sugars biomarkers, including glucosamine, muramic acids, galactosamine, and mannosamine). Activities of oxidative enzymes were studied to assess the potential of soil organic matter oxidation under these different management regimes. These data suggested that on the Mollisols, only perennial pastures that were managed by rotational grazing could enhance soil (0-30 cm) carbon stock and persistence compared to the conventional continuous corn system that had annual tillage. No-till did not increase soil C stock or persistence, while including legumes/manure in crop rotations could enhance microbial C cycling, but could not enhance the stock of persistent MAOM-C.

opencc-by-4.0May 2022View details →

Dataset for 'Massive warming-induced carbon loss from subalpine grassland soils in an altitudinal transplantation experiment' Volk et al. 2022

These files contain the essential data used to produce the above paper

opencc-zeroDec 2013View details →

Data from: Do microorganism stoichiometric alterations affect carbon sequestration in paddy soil subjected to phosphorus input?

Ecological stoichiometry provides a powerful tool for integrating microbial biomass stoichiometry with ecosystem processes, opening far-reaching possibilities for linking microbial dynamics to soil carbon (C) metabolism in response to agricultural nutrient management. Despite its importance to crop yield, the role of phosphorus (P) with respect to ecological stoichiometry and soil C sequestration in paddy fields remains poorly understood, which limits our ability to predict nutrient-related soil C cycling. Here, we collected soil samples from a paddy field experiment after 7 years of superphosphate application along a gradient of 0, 30, 60, 90 (P-0 through P-90, respectively) kg P ha-1 y-1 in order to evaluate the role of exogenous P on soil C sequestration through regulating microbial stoichiometry. P fertilization increased soil total organic C and labile organic C by 1-14% and 4-96%, respectively, while rice yield is a function of the activities of soil β-1, 4-glucosidase (BG), acid phosphatase (AP) and the level of available soil P through a stepwise linear regression model. P input induced C limitation as reflected by decreases in the ratios of C:P in soil and microbial biomass. An ecoenzymatic ratio indicating microbial investment in C versus P acquisition, i.e., ln(BG):ln(AP), changed the ecological function of microbial C acquisition and was stoichiometrically related to P input. This mechanism drove a shift in soil resource availability by increasing bacterial community richness and diversity, and stimulated soil C sequestration in the paddy field by enhancing C degradation-related bacteria for the breakdown of plant-derived carbon sources. Therefore, the decline in the C:P stoichiometric ratio of soil microorganism biomass under P input was beneficial for soil C sequestration, which offered a "win-win" relationship for the maximum balance point between C sequestration and P availability for rice production in the face of climate change.

opencc-by-4.0Jul 2022View details →

Crop Diversification Effects on Soil Aggregation and Aggregate-Associated Carbon and Nitrogen in Short-Term Rainfed Olive Groves under SemiaridMediterranean Conditions

Soil particle aggregation and their associated carbon (C) and nitrogen (N) content can provide valuable diagnostic indicators of changes in soil properties in response to the implementation of different agricultural management practices. In this sense, there is limited knowledge regarding the impact of intercropping on soil organic carbon (SOC) and total nitrogen (TN) pools in aggregates. This study aimed to evaluate the short-term effect (4 years) of three crop diversifications in rainfed olive orchards on soil aggregation, SOC and TN concentration and SOC stocks (SOC-S) under semi-arid Mediterranean conditions. Olive orchards were diversified with Crocus sativus (D-S), Vicia sativa and Avena sativa in rotation (D-O) and Lavandula x intermedia (D-L) and compared with monocropping system (CT). Soil samples were collected at two depths (0–10 and 10–30 cm) and analysed for soil aggregate mass, SOC and TN content in aggregate-size fractions obtained by the wet-sieving method. Changes caused by crop diversifications on SOC-S were also determined. Overall, after 4 years, a reduction in aggregation values was observed. However, D-S increased the macroaggregates (>250 m) percentage, Mean Weigh Diameter values, and Geometric Mean Value in the 0–10 cm. Across treatments, aggregate-associated C in 0–10 cm was higher in the D-S treatment, while in the 10–30 cm soil layer, the greatest values were found in CT. Regarding the SOC-S, after 4 years, significant losses were recorded under CT management in 0–10 cm (􀀀1.21 Mg ha􀀀1) and 10–30 cm (􀀀0.84 Mg ha􀀀1), while D-O and D-L showed similar values to those obtained at the beginning of the study. The highest increases in SOC-S were found in D-S, with an increase of 5.88% in the 0–10 cm and 14.47% in the 10–30 cm. Our results showed the high potential of the diversified cropping system to increase soil stability and SOC sequestration.

opencc-zeroJul 2022View details →

Local temperature increases reduce soil microbial residues and carbon stocks

Warming is known to reduce soil carbon (C) stocks by promoting microbial respiration, which is associated with the decomposition of microbial residue C (MRC). However, the relative contribution of MRC to soil organic C (SOC) across temperature gradients is poorly understood. Here, we investigated the contribution of MRC to SOC along two independent elevation gradients of our model system (i.e., the Tibetan Plateau and Shennongjia Mountain in China). Our results showed that local temperature increases were negatively correlated with MRC and SOC. Further analyses revealed that rising temperature reduced SOC via decreasing MRC, which helps to explain future reductions in SOC under climate warming. Our findings demonstrate that climate warming has the potential to reduce C sequestration by increasing the decomposition of MRC, exacerbating the positive feedback between rising temperature and CO2 efflux. Our study also considered the influence of multiple environmental factors such as soil pH and moisture, which were more important in controlling SOC than microbial traits such as microbial life-style strategies and metabolic efficiency. Together, our work suggests an important mechanism underlying long-term soil C sequestration, which has important implications for the microbial-mediated C process in the face of global climate change.

opencc-zeroAug 2022View details →

Observation‐based global soil heterotrophic respiration indicates underestimated turnover and sequestration of soil carbon by terrestrial ecosystem models

Soil heterotrophic respiration (Rh) refers to the flux of CO2 released from soil to atmosphere as a result of organic matter decomposition by soil microbes and fauna. As one of the major fluxes in the global carbon cycle, the estimation of global Rh still exists large uncertainties, which further limited our current understanding of the carbon accumulation in soils. Here, we applied a Random Forest algorithm to create a global dataset of soil Rh, by linking 761 field observations with both abiotic and biotic predictors. We estimated that the global Rh was 48.8 ± 0.9 Pg C yr-1 for 1982–2018, which was 16% less than the ensemble mean (58.6 ± 9.9 Pg C yr-1) of 16 terrestrial ecosystem models. By integrating our observational Rh with independent soil carbon stock datasets, we obtained a global mean soil carbon turnover time of 38.3 ± 11 yr. Using observation-based turnover times as a constraint, we found that terrestrial ecosystem models simulated faster carbon turnovers, leading to a 30% (74 Pg C) underestimation of terrestrial ecosystem carbon accumulation for the past century, which was especially pronounced at high latitudes. This underestimation is equivalent to 45% of the total carbon emissions (164 Pg C) caused by global land use change at the same time. Our analyses highlight the need to constrain ecosystem models using observation-based and locally adapted Rh values to obtain reliable predictions of the carbon sink capacity of terrestrial ecosystems.

opencc-zeroSep 2022View details →

Soil carbon is mostly grass-derived in tropical savannas, even under woody encroachment

Tropical savannas have been increasingly targeted for carbon (C) sequestration from afforestation, assuming large gains in soil organic C (SOC) with increasing tree cover. Because savanna SOC is also derived from grasses, this assumption may not reflect real changes in SOC under afforestation, but grass contributions to SOC and changes in SOC with increasing tree cover remain poorly synthesized. Here, we combine a case study from Kruger National Park, South Africa, with data synthesized from tropical savannas globally to show that grass-derived C constitutes more than half of total SOC to a soil depth of 1-meter, even in soils directly under trees. The largest SOC concentrations were associated with the largest grass contributions (> 70% of total SOC). Regionally and across the tropics, SOC concentration was not explained by tree cover. Both SOC gain and loss were observed following increasing tree cover, and on average SOC storage within 1-meter profile only increased by a negligible and non-significant 6% (SE = 4%, n = 44). These results underscore the substantial contribution of grasses to SOC and the considerable uncertainty in SOC responses to increasing tree cover, challenging the widespread assumption that afforestation universally and substantially enhances SOC storage across tropical savannas.

opencc-by-4.0May 2024View details →

Temperature Controls the Relation between Soil Organic Carbon and Microbial Carbon Use Efficiency

This is the dataset for the manuscript entitled "Temperature controls the relation between soil organic carbon and microbial carbon use efficiency".

opencc-by-4.0May 2024View details →

Data associated with "The importance of terrain and climate for predicting soil organic carbon is highly variable across local to continental scales"

The zipped folder contains the processed soil datasets including covariates, soil depths, and SOC concentrations for training the deep learning models described in the paper "The importance of terrain and climate for predicting soil organic carbon is highly variable across local to continental scales".  "soil_profile/" contains a table including the geolocations of all the soil profiles in this study. "patch_data/" and "point_data/" contain the covariates to feed the models with patch input and point input respectively. "depth/" contains the upper and lower depths of the soil samples. "y/" contains the target variable - SOC concentration of the soil samples. The data files with suffix "_1" is a small subset of their counterparts without "_1" (10 % in sample size) used for model hyperparameters tuning.

opencc-zeroJun 2024View details →

Data from: Impacts of organic matter amendments on urban soil carbon and soil quality: A meta-analysis

Organic matter amendment application is an important avenue of beneficial waste diversion and is used to improve soil quality in agricultural and urban settings. In urban regions, amendments are used to support local food production, maintain vegetation for landscaping and recreational use, and reclaim disturbed soils. Urban regions generate large quantities of wasted organic resources for potential application aiding in creating a circular nutrient economy. There is a growing interest in understanding the effects of amendments such as compost, biosolids, and biochar on soil properties in agricultural settings. Gaps remain, however, in assessing their effects in urban land uses. We conducted a literature review to assess the effects of compost, biochar, and biosolids on soil carbon and soil quality of urban soils managed for gardening, landscaping, recreation, and reclamation. Application of organic matter amendments led to an average increase of 3.6 units of soil organic matter% (SOM%). Compost and biochar improved SOM% the most, by 3.1 and 6.5 units of SOM%, respectively. Biosolids resulted in the smallest increase in SOM% but had greater nutrient benefits than other amendments. Parameters related to chemical and physical soil quality improved with the application of amendments. Gaps in the literature remain, such as assessing urban gardens, soil to depths greater than 30 cm, and the persistence of SOM in amended soils. This meta-analysis proposes that organic matter amendments are a powerful means to improve soil quality in urban regions, provide vital cobenefits to surrounding communities, and increase soil carbon storage.

Soil organic carbon formation efficiency from straw/stover and manure input and its drivers: Estimates from long-term data in global croplands

The supporting data for raw data, geographic location of the experimental sites, grid-level maps showing the predicted NCE (%) of global cropland

Soil organic carbon formation efficiency from straw/stover and manure input and its drivers: Estimates from long-term data in global croplands

In-situ observations collected from publications,  grid-level maps showing the predicted NCE (%) of global cropland and data-driven model codes

Soil organic carbon formation efficiency from straw/stover and manure input and its drivers: Estimates from long-term data in global croplands

In-situ observations collected from publications,  grid-level maps showing the predicted NCE (%) of global cropland and data-driven model codes

Dataset for "Towards an ecosystem capacity to stabilise organic carbon in soils"

This dataset includes the data that was used in the Global Change Biology publication "Towards an ecosystem capacity to stabilise organic carbon in soils" by Poeplau et al.. It contains two xlsx files, with dataset_full.xlsx including all sites with soil properties that were used in the first part of the manuscript. It is a combined dataset from several open source datasets with a total of 1396 individual sites. The file modelled_converged.xlsx includes the RothC model results of a total of 587 sites, for which modelling was possible and a convergence of measured and modelled data was reached. Both files include two sheets, one with a short explanation of the variable names and one data sheet.