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.
709
datasets available to search
ShareScore release 0.7.1
Dataset results
709 results for “soil carbon”
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>
Soil carbon maintained by perennial grasslands but lost in field crop systems over 30 years in a temperate Mollisol according to longitudinal, compaction-corrected, full-soil profile analysis
<p>To mitigate climate change, some seek to store carbon from the atmosphere in agricultural soils. However, our understanding of how agriculture affects soil organic carbon (SOC) is muddied by studies 1) lacking longitudinal data, 2) ignoring bulk density changes, or 3) sampling only surface soils. To better understand SOC trends, here we measured changes over 30 years in density-corrected, full-soil-depth (90 cm) SOC stocks under 6 cropping systems and a restored prairie in a Mollisol of southern Wisconsin, USA. Cash-grain systems and alfalfa-based systems lost SOC. Prairie and rotationally-grazed pasture maintained SOC. Average SOC losses for cash-grain and alfalfa-based systems were -0.82 (±0.12) and -0.64 (±0.17) Mg C ha<sup>-1</sup> yr<sup>-1</sup>, respectively. Sensitivity analysis showed that incomplete methodologies overestimated SOC improvements. Our findings using more comprehensive methods demonstrate the inadequacy of row-crop systems and the need for well-managed grasslands to protect SOC in productive agricultural soils of the Upper Midwest USA.</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>
Daily cycles in soil carbon flux
<p><strong>Description: </strong></p> <p>Measurements of 24 hour cycles in soil CO2 flux taken from soil collars in the Belian Carbon plot at Maliau. Measurements were taken from 12 subplots over four days at 5-hourly intervals, ensuring good coverage of the complete 24 hour cycle. Air and soil temperatures, soil moisture content and CO2 flux were taken from each plot at each visit. 9 subplots only have a single total soil respiration collar, but 3 subplots also have soil flux partitioning treatments to separate contributions to total respiration from soil organic matter, mycorrhizae and roots.<br> <br> This data was collected by the 2019 cohort of the Tropical Forest Ecology MRes at Imperial College London.</p> <p><strong>Project: </strong>This dataset was collected as part of the following SAFE research project: <a href="https://www.safeproject.net/projects/project_view/152"><strong>MRes Tropical Forest Ecology Field Course</strong></a></p> <p><strong>XML metadata: </strong>GEMINI compliant metadata for this dataset is available <a href="https://www.safeproject.net/datasets/xml_metadata?id=3247592">here</a></p> <p><strong>Files: </strong>This dataset consists of 2 files: Carbon_corrected_slopes.xlsx, raw_egm.zip</p> <p><strong>Carbon_corrected_slopes.xlsx</strong></p> <p>This file contains dataset metadata and 2 data tables:</p> <ol> <li> <p><strong>24 hour observations of CO2 flux patterns</strong> (described in worksheet Carbon_flux_data)</p> <p>Description: Estimated CO2 flux values, soil moisture and air and soil temperatures from Carbon subplots</p> <p>Number of fields: 14</p> <p>Number of data rows: 296</p> <p>Fields:</p> <ul> <li><strong>record_no</strong>: EGM 'Plot' value - record number on EGM machine for this collar (Field type: ID)</li> <li><strong>plot</strong>: Carbon subplot number (Field type: Location)</li> <li><strong>date</strong>: Calendar date that measurements taken (Field type: Date)</li> <li><strong>time</strong>: Time that measurements taken (Field type: Time)</li> <li><strong>soil_wmc</strong>: Soil water moisture content (Field type: Numeric)</li> <li><strong>soil_temp</strong>: Soil temperature (Field type: Numeric)</li> <li><strong>air_temp</strong>: Air temperature (Field type: Numeric)</li> <li><strong>treatment</strong>: Exclusion treatments for partitioning soil respiration components (Field type: Categorical)</li> <li><strong>field_flux</strong>: CO2 flux reported in the field by EGM (Field type: Numeric)</li> <li><strong>Source</strong>: EGM dat file of source data used for corrected fluxes where available (Field type: File)</li> <li><strong>corrected_flux</strong>: Corrected flux measurements using by eye exclusion of raw flux data (Field type: Numeric)</li> <li><strong>n_points</strong>: Number of points in EGM record (Field type: Numeric)</li> <li><strong>n_used</strong>: Number of points used for corrected slope estimation (Field type: Numeric)</li> <li><strong>flux</strong>: Final flux values, using corrected values where available (Field type: Numeric)</li> </ul> </li> <li> <p><strong>EGM raw data</strong> (described in worksheet EGM_raw_data)</p> <p>Description: Duplicates key information from raw EGM files and indicates points excluded in calculation of corrected flux values</p> <p>Number of fields: 7</p> <p>Number of data rows: 7114</p> <p>Fields:</p> <ul> <li><strong>Plot</strong>: EGM recorder 'plot' code, actually just the record sequence number. (Field type: ID)</li> <li><strong>RecNo</strong>: EGM record number - time points of gas measurement at a single plot (Field type: ID)</li> <li><strong>Datetime</strong>: Time of gas concentration measurement (Field type: Datetime)</li> <li><strong>CO2.Ref</strong>: Measured CO2 (Field type: Numeric)</li> <li><strong>Input.E</strong>: EGM internal variable used in slope estimation (Field type: Numeric)</li> <li><strong>Source</strong>: Original EGM dat file containing the flux data (Field type: File)</li> <li><strong>ignore</strong>: Indicates where points from raw data excluded from corrected slope calculations (Field type: Categorical)</li> </ul> </li> </ol> <p><strong>raw_egm.zip</strong></p> <p>Description: Zipfile of raw EGM dat files</p> <p><strong>Date range: </strong>2019-02-18 to 2019-02-21</p> <p><strong>Latitudinal extent: </strong>4.7467 to 4.7480</p> <p><strong>Longitudinal extent: </strong>116.9693 to 116.9704</p>
The data for the article entitled "Soil carbon release responses to long-term versus short-term climatic warming in an arid ecosystem"
<p>The data for the article entitled "Soil carbon release responses to long-term versus short-term climatic warming in an arid ecosystem" Yu et al. </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>
Data from: Desiccation and rehydration of mosses greatly increases resource fluxes that alter soil carbon and nitrogen cycling
1. Mosses often have positive effects on soil carbon and nitrogen cycling, but we know little about how environmentally determined cycles of desiccation and rehydration in mosses influence these processes. 2. In this context, we compared carbon and nitrogen in throughfall after precipitation passed through eight moss species that were either hydrated continuously or desiccated and rehydrated. Also, the throughfall of four moss species was added to soil and used to determine the net effect of carbon and nitrogen added in moss throughfall on soil CO2 and N2O efflux. 3. Depending on the species, desiccated-rehydrated (rehydrated) mosses lost 2-31 times more carbon in throughfall than mosses that were continuously hydrated (hydrated). Hydrated mosses lost little to no detectable nitrogen; whereas most rehydrated mosses lost some nitrogen in throughfall. Throughfall from both hydrated and rehydrated mosses generated higher CO2 and N2O efflux than water treated soils, but rehydrated moss throughfall promoted larger N2O efflux than hydrated moss throughfall. Throughfall from hydrated mosses caused net negative changes in soil carbon and had very little effect on soil nitrogen, whereas throughfall from rehydrated mosses generated positive changes in soil carbon and nitrogen. 4. Synthesis. Our results indicate that resources lost from desiccated mosses during rehydration influence soil carbon and nitrogen transformations and may be important drivers of carbon and nitrogen cycling and storage in ecosystems.
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>
Shrub influence on soil carbon and nitrogen in a semi-arid grassland is mediated by precipitation and largely insensitive to livestock grazing
<p>Dryland (arid and semi-arid) ecosystems globally provide more than half of livestock production and store roughly one-third of soil organic carbon (SOC). Biogeochemical pools are changing due toshrub encroachment, livestock grazing, and climate change. We assessed how vegetation microsite, grazing, and precipitation interacted to affect SOC and total nitrogen (TN) at a site with long-term grazing manipulations and well-described patterns of shrub encroachment across elevation and mean annual precipitation (MAP) gradients. We analyzed SOC and TN in the context of vegetation cover at ungrazed locations within livestock exclosures, high-inten- sity grazing locations near water sources, and moderate-intensity grazing locations away from water. SOC was enhanced by MAP (p<0.0001), but grazing intensity had little effect regardless of MAP (p = 0.12). Shrubs enhanced SOC (300–1279 g C m2) and TN (27–122 g N m2), except at high MAP where the contribution or stabilization of shrub inputs relative to grassland inputs was likely diminished. Cover of perennial herbaceous plants and litter were significant predictors of SOC (r2 = 0.63 and 0.34, respectively) and TN (r2 = 0.64 and 0.30, respectively). Our results suggest that continued shrub encroachment in drylands can increase SOC storage when grass production remains high, although this response may saturate with higher MAP. In contrast, grazing – at least at the intensities of our sites – has a lesser effect. These effects underscore the need to understand how future climate and grazing may interact to influence dryland biogeochemical cycling.</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>
Deforestation for agriculture increases microbial carbon use efficiency in subarctic soils
<p>This repository contains all necessary raw data as well as the R code used to conduct statistical analysis and create figures of the publication</p><p> </p><p><strong>Deforestation for agriculture increases microbial carbon use efficiency in subarctic soils</strong></p><p>Julia Schroeder1, Tino Peplau1, Frank Pennekamp2, Edward Gregorich3, Christoph C. Tebbe4, Christopher Poeplau1</p><p>1 Thünen Institute of Climate-Smart Agriculture, Bundesallee 68, 38116 Braunschweig, Germany</p><p>2 Department of Evolutionary Biology and Environmental Studies, University of Zurich, Winterthurerstrasse 190, 8057 Zürich, Switzerland</p><p>3 Research and Development Centre, Central Experimental Farm, Agriculture and Agri-Food Canada, 960 Carling Ave, Ottawa, Ontario K1A 0C6, Canada</p><p>4 Thünen Institute of Biodiversity, Bundesallee 65, 38116 Braunschweig, Germany</p><p>DOI: https://doi.org/10.1007/s00374-022-01669-2 </p><p>This study investigated how and through which pathways deforestation and conversion to agricultural land (i.e. grassland, cropland) alters the microbial carbon use efficiency (CUE) in subarctic soils to allow the development of mitigation strategies to alleviate C losses. We assessed CUE using 18O-labelled water in a paired-plot approach on soils collected from 19 farms across the subarctic region of Yukon, Canada, comprising 14 pairs of forest-to-grassland conversion and 15 pairs of forest-to-cropland conversion. Microbial CUE significantly increased following conversion to grassland and cropland. Land-use conversion resulted in a lower estimated abundance of fungi, while the archaeal abundance increased, as assessed by qPCR. Interestingly, structural equation modelling revealed that increases in CUE were mediated by a rise in soil pH and a decrease in soil C:N ratio rather than by shifts in microbial community composition, i.e. the ratio of fungi, bacteria and archaea. Our findings indicate a direct control of abiotic factors on microbial CUE via improved nutrient availability and facilitated conditions for microbial growth.</p><p>The R code was developed under R v3.6.3 and adapted to work under version R v.4.1.2.</p><p>The repository includes the following files:</p><ul><li>general_soil_parameters_per_site.csv - general soil data assessed on pooled reference forest plot (n=19)</li><li>general_soil_parameters_per_plot.csv - general soil data assessed on pooled replicated field samples (n=48)</li><li>sample_data.csv - data measured for each laboratory sample (n=147)</li></ul><p> </p><ul><li>Land-use change effects on 18O-CUE.Rproj - Rproject (load project to work on provided scripts and data)</li><li>load_data_script.R - loads required data</li><li>Multivariate_normality_script.R - tests for multivariate normaility in dataset</li><li>PCA_script.R - calculates PC1 and 2 of clay mineralogy data to reduce dimensions</li><li>map_Yukon_script.R - create Figure 1</li><li>plot_density_script.R - create Figure 2</li><li>linear_mixed-effects_models_script.R - calculates response ratios</li><li>plot_boxplots_script.R - plot boxplots per land use including compact letter display indicating significant differences, create Figure 3 + 4</li><li>correlogram_script.R - correlation analysis to identify drivers of CUE, create Figure 6</li><li>plot_correlations_script.R - plot drivers of CUE, create Figure 5 + 7</li><li>SEM_script.R - development of structural equation model, create Figure 8</li></ul>
Abiotic and biotic drivers of tree trait effects on soil microbial biomass and soil carbon concentration
<p>Forests are critical ecosystems to understand the global carbon budget, due to their carbon sequestration potential in both above- and belowground compartments, especially in species-rich forests. Soil carbon sequestration is strongly linked to soil microbial communities, and this link is mediated by the tree community, likely due to modifications of micro-environmental conditions (i.e., biotic conditions, soil properties, and microclimate). We studied soil carbon concentration and the soil microbial biomass of 180 local neighborhoods along a gradient of tree species richness ranging from 1 to 16 tree species per plot in a Chinese subtropical forest experiment (BEF-China). Tree productivity and different tree functional traits were measured at the neighborhood level. We tested the effects of tree productivity, functional trait identity and dissimilarity on soil carbon concentrations, and their mediation by the soil microbial biomass and micro-environmental conditions. Our analyses showed a strong positive correlation between soil microbial biomass and soil carbon concentrations. Besides, soil carbon concentration increased with tree productivity and tree root diameter while it decreased with litterfall C:N content. Moreover, tree productivity and tree functional traits (e.g. root fungal association and litterfall C:N ratio) modulated micro-environmental conditions with substantial consequences for soil microbial biomass. We also showed that soil history and topography should be considered in future experiments and tree plantations, as soil carbon concentrations were higher where historical (i.e., at the beginning of the experiment) carbon concentrations were high, themselves being strongly affected by the topography. Altogether, these results imply that the quantification of the different soil carbon pools is critical for understanding microbial community–soil carbon stock relationships and their dependence on tree diversity and micro-environmental conditions.</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.