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519 results for “organic soil”
Soil organic matter responses to nutrient enrichment in the Nutrient Network:Nutrient Network. A cross-site investigation of bottom-up control over herbaceous plant community dynamics and ecosystem function.
This experiment is one implementation of a globally distributed experiment, known as the Nutrient Network. At Cedar Creek, as in over 70 other sites in grasslands around the world, the experiment aims to describe impacts of increased nutrients (nitrogen, phosphorus, potassium, sulfur and other metals) and decreased herbivory (removal of mammals by fencing). Two overarching questions are being explored with these manipulations: 1. To what extent are plant production and diversity co-limited by multiple nutrients in herbaceous-dominated communities? 2. Under what conditions do grazers or fertilization control plant biomass, diversity, and composition? By utilizing identical protocols at diverse grassland sites around the world, NutNet aims to uncover both the generalities in ecosystem functioning, and the contingencies or differences which can obscure those common mechanisms. In addition to the standard NutNet protocol, e247 includes an additional low Nitrogen gradient (1 gram Nitrogen per meter squared per year and 5 grams Nitrogen per meter squared per year in addition to the standard 10 grams Nitrogen per meter squared per year).
Soil organic matter, total nitrogen and pH:Microbial composition and function across an old-field chronosequence
As mediators of biogeochemical cycles, understanding the ecological forces structuring soil microbial communities is of ecosystem-level significance. Due to gradual shifts in plant species composition and litter addition through time, succession can be used as a model to understand how plant communities shape microbial community composition and function in soil. Numerous studies have investigated microbial biomass and diversity along successional gradients, yet few have quantified changes in microbial communities. Using the established successional dynamics experiment at Cedar Creek, principal investigators Lauren C. Cline and Donald R. Zak investigated the influence of plant community composition in structuring microbial community composition and function. Specifically, their research addressed the following questions: 1. Do shifts in saprotrophic microbial communities correlate to changes in plant community composition through successional time? 2. What is the relative influence of soil properties and plant community characteristics in determining microbial community dynamics? Cline and Zak sampled soils from 8 established abandoned agricultural fields (e054), as well as three adjacent forests representing potential late-successional ecosystems, to investigate microbial dynamics using three complementary approaches: targeted sequencing of fungal and bacterial communities, quantitative PCR, and shotgun metagenomics. Further, the characterization of soil properties across the chronosequence will enable us to disentangle the impact of abiotic factors in structuring microbial communities.
Soil Organic Carbon balance
<p>Provisional demonstration of SOC balance in eucalyptus and sugarcane systems in Brazil</p>
Thermodynamics of soil organic matter decomposition in semi-natural oak (Quercus) woodland in southwest Ireland
<p>The evolution of soil terrestrial ecosystems is a subject with difficulties to define their maturity and evolutionary state. In the last century, thermodynamics was one of the options considered by ecologists for that goal. Difficulties in quantifying the thermodynamic parameters needed by the evolutionary theories caused that this subject has been practically locked since the end of the last century. Application of thermodynamics needs reactions and one of the main reactions in soil ecosystems are those involved in the decomposition of the soil organic matter. This paper aims to provide an initial step to study those reactions from a thermodynamic perspective. With that goal in mind, thermal analysis and isothermal calorespirometric measurements were made on soil samples collected at three depths in semi-natural oak woodlands at three different sites in southwest Ireland. It is assumed that the organic matter evolves from a less to a higher mature state as soil depth increases. The maturity state could be chemically defined by the redox state. The proposed methods yield the enthalpy change, Gibbs energy change, and entropy change for the microbial catabolism and combustion reactions of the soil organic matter. The degree of reduction was calculated by the enthalpy changes. Results show the soil organic matter becomes more reduced from the soil organic surface to mineral soils. The top layer is characterized by high carbon content, organic materials with low energy content per Cmole, and fast biodegradation rates. Mineral soils are characterized by low carbon content, organic materials with high energy content per Cmole, and slow biodegradation rates. Values obtained for the entropy change were sensitive to these differences among the different soil layers. These results contribute to unlock the thermodynamics of the soil reactions and to develop the bioenergetics of soil ecosystems.</p>
Quantitative efficacy assessments of organic fertilizers in Chinese tea gardens: responses of soil fertility and tea yield and quality
<p>This file includes all supporting information of the paper “Quantitative efficacy assessments of organic fertilizers in Chinese tea gardens: responses of soil fertility and tea yield and quality”. Details are given as follows:</p> <p><strong>Figure A1</strong> Distribution of organic fertilization study sites in China included in this meta-analysis.</p> <p><strong>Table A1</strong> Effects of mineral fertilizers on soil nutrients and tea production and tea biochemical constituents, based on the current OFs database.</p> <p><strong>Table A2</strong> All datasets of this meta-analysis are listed.</p> <p><strong>Panel A1</strong> Data source literature included in this meta-analysis.</p>
Supplemental information for McClelland et al. (2020). Management of cover crops in temperate climates influences soil organic carbon stocks – A meta-analysis
<p>All supplemental information for McClelland et al. (2020). Management of cover crops in temperate climates influences soil organic carbon stocks – A meta-analysis. </p>
Dataset for: Short-term temperature history affects mineralization of fresh litter and extant soil organic matter, irrespective of agricultural management
<p>Dataset for the article:</p> <p>Mason-Jones, K., Vrehen, P, Koper, K., Wang, J., van der Putten, W.H., Veen, G.F. 2020. Short-term temperature history affects mineralization of fresh litter and extant soil organic matter, irrespective of agricultural management. Soil Biology and Biochemistry, 150, 107985.</p> <p>Article DOI: 10.1016/j.soilbio.2020.107985</p>
Data from: Spatial-temporal variability and related factors of soil organic carbon in Henan province
Spatial variability and influence factors are important to evaluate soil organic carbon(SOC) and the carbon pool in large areas. In the present study, sampling was conducted from May to November 2011 in Henan province, a typical agricultural region of central China, to study the effects of soil properties and anthropogenic factors on SOC variability in cropland. Physicochemical properties of soil samples were analyzed, which were collected at 280 sites from the surface layer (at a depth of 0–20 cm), and related data about the sampling sites were also collected from the Second State Soil Survey of China (SSSSC), conducted in 1981. The main results were as follows: 1) Increasing trends in soil organic carbon density (SOCD) and soil organic carbon pool (SOCP) were obvious from 1981 to 2011, and we conclude that cropland presents great carbon sequestration potential for the future. Carbon pool ability varied with soil properties: the order of fixed carbon amount in different soil types was found to be Inceptisols > Luvisols > Semi-hydromorphic soil > Anthrosols, and the average SOCP increased significantly from 1981 to 2011. 2) Soil bulk density, pH and returning straw are the key influence factors for SOCD in the past 30 years. 3) Although random factors (returning straw) only explain 29.1% of SOCD variability, the factor should be paid more attention, because application of returning strawwas the most dominant anthropogenic factors, which can be used to improve cropland productivity and carbon sink capacity within a short period if they are properly managed in the future.
Data from: Direct and indirect effects of nitrogen enrichment on soil organisms and carbon and nitrogen mineralization in a semi‐arid grassland
1. Semi-arid grasslands on the Mongolian Plateau are expected to experience high inputs of anthropogenic reactive nitrogen in this century. It remains unclear, however, how soil organisms and nutrient cycling are directly affected by N enrichment (i.e., without mediation by plant input to soil) vs. indirectly affected via changes in plant-related inputs to soils resulting from N enrichment. 2. To test the direct and indirect effects of N enrichment on soil organisms (bacteria, fungi, and nematodes) and their associated C and N mineralization, in 2010 we designated two subplots (with plants and without plants) in every plot of a six-level N-enrichment experiment established in 1999 in a semi-arid grassland. 3. In 2014, 4 years after subplots with and without plant were established, N enrichment had substantially altered the soil bacterial, fungal, and nematode community structures due to declines in biomass or abundance whether plants had been removed or not. N enrichment also reduced the diversity of these groups (except for fungi) and the soil C mineralization rate and induced a hump-shaped response of soil N mineralization. As expected, plant removal decreased the biomass or abundance of soil organisms and C and N mineralization rates due to declines in soil substrates or food resources. 4. Analyses of plant removal-induced changes (ratios of without- to with-plant subplots) showed that microorganisms and C and N mineralization rates were not enhanced as N enrichment increased but that nematodes were enhanced as N enrichment increased, indicating that the effects of plant removal on soil organisms and mineralization depended on trophic level and nutrient status.5. Surprisingly, there was no statistical interaction between N enrichment and plant removal for most variables, indicating that plant-related inputs did not qualitatively change the effects of N enrichment on soil organisms or mineralization. Structural equation modeling confirmed that changes in soil communities and mineralization rates were more affected by the direct effects of N enrichment (via soil acidification and increased N availability) than by plant-related indirect effects. Our results provide insight into how future changes in N-deposition and vegetation may modify below-ground communities and processes in grassland ecosystems.
Data from: Variability in potential to exploit different soil organic phosphorus compounds among tropical montane tree species
We hypothesized that tropical plant species with different mycorrhizal associations reduce competition for soil phosphorus (P) by specializing to exploit different soil organic P compounds. We assayed the activity of root/mycorrhizal phosphatase enzymes of four tree species with contrasting root symbiotic relationships–arbuscular mycorrhizal (angiosperm and conifer), ectomycorrhizal and non-mycorrhizal–collected from one of three soil sites within a montane tropical forest. We also measured growth and foliar P of these seedlings in an experiment with P provided exclusively as inorganic orthophosphate, a simple phosphomonoester (glucose phosphate), a phosphodiester (RNA), phytate (the sodium salt of myo-inositol hexakisphosphate), or a no-P control. The ectomycorrhizal tree species expressed twice the phosphomonoesterase activity as the arbuscular mycorrhizal tree species, but had similar phosphodiesterase activity. The non-mycorrhizal Proteaceae tree had markedly greater activity of both enzymes than the mycorrhizal tree species, with root clusters expressing greater phosphomonoesterase activity than fine roots. Both the mycorrhizal and non-mycorrhizal tree species contained significantly greater foliar P than in no-P controls when limited to inorganic phosphate, glucose phosphate, and RNA. The ectomycorrhizal species did not perform better than the arbuscular mycorrhizal tree species when limited to organic P in any form. In contrast, the non-mycorrhizal Proteaceae tree was the only species capable of exploiting phytate, with nearly three times the leaf area and more than twice the foliar P of the no-P control. Our results suggest that arbuscular and ectomycorrhizal tree species exploit similar forms of P, despite differences in phosphomonoesterase activity. In contrast, the mycorrhizal tree species and non-mycorrhizal Proteaceae appear to differ in their ability to exploit phytate. We conclude that resource partitioning of soil P plays a coarse but potentially ecologically important role in fostering the coexistence of tree species in tropical montane forests.
Dataset of manuscript "A stoichiometric approach to estimate sources of mineral-associated soil organic matter"
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Long time-series (2020-2100) high-resolution (1km) multi-scenario and multi-depth soil organic carbon dataset in China
<p>unit: kg C m-2 (soil oganic carbon density)</p><p>0100: denote 0-100 cm</p><p>020: denote 0-20 cm</p><p>Example 2020: 2020-2024 (five years mean soc)</p>
Supplemental Data for "Soil organic carbon change can reduce the climate benefits of biofuel produced from forest residues"
<p>The files contain the code and supplementary data for the article.</p>
Fluxes and concentrations of dissolved organic carbon in soils
<p>Dissolved organic carbon (DOC) in soil solution plays roles in soil C storage and biogeochemical cycles. Factors regulating fluxes and concentrations of DOC still remain unclear. To identify the factors regulating fluxes and concentrations of DOC in the soil profiles, we compiled the data of site information [Country, Region or state, Coordinates, Vegetation, Mean annual air temperature (ºC), Climate type, Vegetation type, Mycorrhiza type, Soil (USDA, Soil Taxonomy)], soil properties [Litter pH (H<sub>2</sub>O), Soil pH (H<sub>2</sub>O), Soil C/N ratio, Clay (%), Al<sub>o</sub>+1/2Fe<sub>o</sub> (g kg<sup>-1</sup>), O horizon C stock (Mg C ha<sup>-1</sup>), Mineral soil C stock (Mg C ha<sup>-1</sup>)], fluxes and concentrations of DOC [Throughfall DOC flux (kg C ha<sup>-1</sup> yr<sup>-1</sup>), DOC flux at the bottom of the O horizon (kg C ha<sup>-1</sup> yr<sup>-1</sup>), DOC flux at the bottom of the B horizon (kg C ha<sup>-1</sup> yr<sup>-1</sup>), DOC concentration at the bottom of the O horizon (mg C L<sup>-1</sup>), DOC concentration at the bottom of the B horizon (mg C L<sup>-1</sup>), DOC/Dissolved organic N (DON) (O horizon), DOC/DON (B horizon), Precipitation (mm yr<sup>-1</sup>), Water flux at the bottom of the O horizon (mm y<sup>r-1</sup>), Water flux at the bottom of B horizon (mm yr<sup>-1</sup>)], plant litter properties [Litterfall C input (Mg C ha<sup>-1</sup> yr<sup>-1</sup>), C/N ratio in litter, Lignin content in litter (%), Lignin/N ratio in litter, Root litter C input (Mg C ha<sup>-1</sup> yr<sup>-1</sup>)], and DOC retention in mineral soil (%), DOC flux relative to C input (%), Contribution of DOC to C input in mineral soil (%), and Turnover time of mineral soil C (yr)].</p>
Patterns and drivers of soil organic carbon fractions and persistence in coastal wetlands in China
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Dataset for Prolonged storage of bound organic carbon in wetland but not upland soils: A 13C and 14C perspective
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Spatiotemporal prediction of soil organic carbon density (SOCD) for pan-Europe (2000-2022) in 3D+T
<h2><strong>Sub-dataset: SOCD mean, 2000-2004</strong></h2> <h2>Disclaimer</h2> <p>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.</p> <h2>Description</h2> <p>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.</p> <p>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.</p> <p>This data set includes:</p> <ul> <li><strong>Soil Organic Carbon Density (SOCD) (2000-2022, 4-year intervals):</strong><br>This data includes mean, p975, and p025 SOCD maps for four depth ranges (0-20cm, 20-50cm, 50-100cm, and 100-200cm) in kg/m<sup>3</sup> (scaled 10x).</li> <li><strong>Organic carbon content based on dry combustion weight percentage (WPCT) (2000-2022, 4-year intervals):</strong><br>This data includes mean, p975, and p025 WPCT maps for four depth ranges (0-20cm, 20-50cm, 50-100cm, and 100-200cm) in percentage.</li> </ul> <h3>Related identifiers</h3> <ul> <li><strong>SOCD mean:</strong><br><a href="https://zenodo.org/records/13754343">2000-2004</a> <a href="https://zenodo.org/records/13771721">2004-2008</a> <a href="https://zenodo.org/records/13771841">2008-2012</a> <a href="https://zenodo.org/records/13771911">2012-2016</a> <a href="https://zenodo.org/records/13771967">2016-2020</a> <a href="https://zenodo.org/records/13772054">2020-2022</a></li> <li><strong>SOCD p025:</strong><br><a href="https://zenodo.org/records/13779539">2000-2004</a> <a href="https://zenodo.org/records/13774064">2004-2008</a> <a href="https://zenodo.org/records/13774089">2008-2012</a> <a href="https://zenodo.org/records/13774114">2012-2016</a> <a href="https://zenodo.org/records/13774167">2016-2020</a> <a href="https://zenodo.org/records/13774196">2020-2022</a></li> <li><strong>SOCD p975:</strong><br><a href="https://zenodo.org/records/13778472">2000-2004</a> <a href="https://zenodo.org/records/13773396">2004-2008</a> <a href="https://zenodo.org/records/13773765">2008-2012</a> <a href="https://zenodo.org/records/13773828">2012-2016</a> <a href="https://zenodo.org/records/13773953">2016-2020</a> <a href="https://zenodo.org/records/13774003">2020-2022</a></li> </ul> <h3>Data Details</h3> <ul> <li><strong>Time period:</strong> 2000–2022, in 4-year intervals (last period covers 2020–2022).</li> <li><strong>Type of data:</strong> Spatiotemporal soil organic carbon data cube, with depth ranges and weighted percentage data for soil carbon assessments.</li> <li><strong>How the data was collected or derived:</strong> The data was derived using machine learning models.</li> <li><strong>Statistical methods used:</strong> Quantile Random Forest</li> <li><strong>Limitations or exclusions in the data:</strong> The dataset does not include data for Svalbard.</li> <li><strong>Coordinate reference system:</strong> EPSG:3035</li> <li><strong>Bounding box (Xmin, Ymin, Xmax, Ymax):</strong> (900,000, 899,000, 7,401,000, 5,501,000)</li> <li><strong>Spatial resolution:</strong> 30m</li> <li><strong>Image size:</strong> 216,700P x 153,400L</li> <li><strong>File format:</strong> Cloud Optimized Geotiff (COG) format.</li> </ul> <h3>Support</h3> <p>If you discover a bug, artifact, or inconsistency, or if you have a question please raise a GitHub issue: GitLab Issues (tbc)</p> <h3>Name convention</h3> <p>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:</p> <ol> <li><strong>generic variable name:</strong> oc = organic carbon</li> <li><strong>variable procedure combination:</strong> iso.10694.1995.mg.cm3 = ISO method 10694:1995, with values in mg/cm<sup>3</sup> for SOCD | iso.10694.1995.wpct = ISO method 10694:1995, with values in weighted percentage of organic carbon content.</li> <li><strong>Position in the probability distribution/variable type:</strong> m = mean | p975 = percentile 97.5 | p025 = percentile 2.5</li> <li><strong>Spatial support:</strong> 30m</li> <li><strong>Depth reference:</strong> b0cm..20cm = depth range from 0 to 20cm</li> <li><strong>Time reference begin time:</strong> 20000101 = 2000-01-01</li> <li><strong>Time reference end time:</strong> 20041231 = 2004-12-31</li> <li><strong>Bounding box:</strong> eu = pan-Europe</li> <li><strong>EPSG code:</strong> epsg.3035</li> <li><strong>Version code:</strong> v20240804 = version from 2024-08-04</li> </ol>
Appendix dataset for "Distribution, storage, and factors influencing particulate and mineral-associated organic matter in paddy soils"
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Herbivore grazing mitigates the negative effects of nitrogen deposition on soil organic carbon in low-diversity grassland
<p>1. Changes in soil carbon (C) sequestration in grassland ecosystems have important impacts on the global C cycle. As such, it is important that researchers better understand the underlying mechanisms affecting soil C. Increasing evidence has shown that atmospheric nitrogen (N) deposition can cause dramatic changes in grassland soil C. It remains unclear whether herbivore grazing, a primary means to manage and utilize grassland resources, can regulate the effects of N deposition on soil C, and whether these effects are dependent on plant community diversity.</p> <p>2. Here, we examined the joint effects of herbivore grazing and N-addition on soil organic C (SOC) stocks in two types of communities with low and high plant diversity, respectively.</p> <p>3. Our results showed that the effects of N-addition and its combination with herbivore grazing on grassland SOC were inconsistent in the two types of communities. In the low-diversity community, N-addition greatly decreased SOC stocks, while grazing significantly increased it. Additionally, the grazing-induced increase in soil C stocks in presence of N-addition was so great that it completely counteracted the significant decline in SOC induced by N-addition. However, in the high-diversity community, we observed no effects of N-addition on SOC and grazing increased SOC only in the absence of N-addition and had no significant effect in presence of N-addition.</p> <p>4. Synthesis and applications. Our study suggests that increased N deposition can trigger a remarkable reduction in soil C sequestration in grasslands with low plant diversity, but that herbivore grazing can offset this decline, which may help to mitigate greenhouse gas emissions caused by atmospheric N deposition. As a result, we suggest that moderate herbivore grazing should be considered as an effective grassland management measure for maintaining and improving grassland soil C sequestration as the increasing global change such as elevated atmospheric carbon dioxide, N deposition, and biodiversity losses threat.</p>
The main driver of soil organic carbon differs greatly between topsoil and subsoil in a grazing steppe
<p>1. Soil organic carbon (SOC) dynamics is regulated by a complex interplay of factors such as climate and potential anthropogenic activities. Livestocks play a key role in regulating the C cycle in grasslands. However, the interrelationship between SOC and these drivers remains unclear at different soil layers, and their potential relationships network have rarely been quantitatively assessed.</p> <p>2. Here, we completed a six-year manipulation experiment of grazing exclusion (no grazing: NG) and increasing grazing intensity (light grazing: LG, medium grazing: MG, heavy grazing: HG). We measurements of light fraction organic carbon (LFOC) and heavy fraction organic carbon (HFOC) in 12 plots along grazing intensity in three soil layers (topsoil: 0-10 cm, mid-soil: 10-30 cm, subsoil: 30-50 cm) to assess their underlying controls.</p> <p>3. Grazing significantly reduced SOC of the soil profile, but with significant depth and time dependencies. (1) SOC and SOC stability of the topsoil is primarily regulated by grazing duration (years). Specifically, grazing duration and grazing intensity increased the SOC lability of topsoil due to an increase in LFOC. (2) Grazing intensity was the major factor affecting the mid-soil SOC dynamics, among which MG had significantly lower SOC than did NG. (3) Subsoil organic carbon dynamics were mainly regulated by climatic factors. The increase in mean annual temperature (MAT) may have promoted the turnover of LFOC to HFOC in the subsoil.</p> <p>4. Synthesis and applications. When evaluating the impacts of grazing on soil organic fraction, we need to consider the differences in sampling depth and the duration of grazing years. Our results highlight that the key factors influencing SOC dynamics differ among soil layers. Climatic and grazing factors have different roles in determining SOC in each soil layer.</p>
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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)
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DANDI Archive for NWB datasets
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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.