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159 results for “soil organic matter”
Supplementary material 5 from: Tóth Z, Hornung E, Báldi A (2018) Effects of set-aside management on certain elements of soil biota and early stage organic matter decomposition in a High Nature Value Area, Hungary. Nature Conservation 29: 1-26. https://doi.org/10.3897/natureconservation.29.24856
Map file :
Supplementary material 2 from: Tóth Z, Hornung E, Báldi A (2018) Effects of set-aside management on certain elements of soil biota and early stage organic matter decomposition in a High Nature Value Area, Hungary. Nature Conservation 29: 1-26. https://doi.org/10.3897/natureconservation.29.24856
Table S2 :
Supplementary material 4 from: Tóth Z, Hornung E, Báldi A (2018) Effects of set-aside management on certain elements of soil biota and early stage organic matter decomposition in a High Nature Value Area, Hungary. Nature Conservation 29: 1-26. https://doi.org/10.3897/natureconservation.29.24856
Table S4 :
Supplementary material 1 from: Tóth Z, Hornung E, Báldi A (2018) Effects of set-aside management on certain elements of soil biota and early stage organic matter decomposition in a High Nature Value Area, Hungary. Nature Conservation 29: 1-26. https://doi.org/10.3897/natureconservation.29.24856
Table S1 :
Synergy between early soil formation and organic matter build-up: a study case in a 20-year Technosol chronosequence
<p>Supporting dataset for paper.</p> <p> </p>
Carbon burial in soils of the Great Marsh, DE: Evaluating accumulation rates and organic matter composition
<p>This data was collected to address the research questions listed in Rachel Owrutsky's master's thesis (2022) titled <em>Carbon burial in soils of the Great Marsh, DE: evaluating accumulation rates and organic matter composition. </em></p>
Influence of grain size, organic carbon and organic matter residue content on the sorption of per-and polyfluoroalkyl substances in aqueous film forming foam contaminated soils-Implications for remediation using soil washing
<p>Supporting information from Influence of grain size, organic carbon and organic matter residue content on the sorption of per-and polyfluoroalkyl substances in aqueous film forming foam contaminated soils-Implications for remediation using soil washing</p>
Soil microbial community in 47 Chinese forest sites: biogeographic patterns and links with soil dissolved organic matter
<p>Physical and chemical properties of soil samples in this Manuscript.</p>
Data from: Warming alters surface soil organic matter composition despite unchanged carbon stock in a Tibetan permafrost ecosystem
Open the record for dataset details and reuse information.
Thermodynamics of soil organic matter decomposition in semi-natural oak (Quercus) woodland in southwest Ireland
Open the record for dataset details and reuse information.
Mechanisms driving the soil organic matter decomposition response to nutrient enrichment: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).
NACP Soil Organic Matter of Burned Boreal Black Spruce Forests, Alaska, 2009-2011
This data set provides organic soil layer characteristics, estimated carbon content, and soil depth measurements made at four black spruce stands in interior Alaska that had burned twice in the last 37-52 years (intermediate-interval fire events). The most recent fires occurred in 2004, 2005, and 2010. Measurements of soil depth and distance from the adventitious roots to the soil, and total organic matter are also included for unburned black spruce sites adjacent to the burned sites dominated by live, intermediate-aged (~37-52 years) black spruce trees.
ABoVE: Burn Severity of Soil Organic Matter, Northwest Territories, Canada, 2014-2015
This dataset provides maps at 30-m resolution of landscape surface burn severity (surface litter and soil organic layers) from the 2014-2015 fires in the Northwest Territories and Northern Alberta, Canada. The maps were derived from Landsat 8 Operational Land Imager/Thermal Infrared Sensor (OLI/TIRS) imagery and two separate multiple linear regression models trained with field data; one for the Plains and a second for the Shield ecoregion. Field observations were used to estimate area burned in each of five severity classes (unburned, singed, light, moderate, severely burned) in six stratified randomly selected plots of 10 x 10-m in size across a 1-ha site. Using this five class scale a burn severity index (BSI) for each 1-ha site was calculated using multiple weighted and averaged field parameters. Pre- and post-fire phenologically paired Landsat 8 images were used to model the five discrete severity classes using midpoints as breaks.
Dataset: Effect of soil organic matter content and nutrient loading on productivity of Spartina patens (v.0.10)
<p class="MsoNormal">River sediment diversions in the Mississippi River Delta have been planned as a keystone strategy for wetland restoration in coastal Louisiana. The introduction of mineral sediment and dissolved nutrients present in Mississippi River water could drastically alter the abiotic environment of the surrounding wetlands, and the effects on wetland vegetation are unclear. In this study, 50 sods were transplanted from a <em>Spartina patens-</em>dominated brackish marsh into a greenhouse and grown in either mineral or organic soil in combination with one of five levels of nutrient enrichment. The primary component of the mineral soil was silt collected from the bank of the Mississippi River, while that of the organic soil was peat collected from the aforementioned <em>S. patens</em> marsh. Nutrient treatments were based on a range of Mississippi River diversion discharge rates of nitrate, phosphate, sulfate, potassium, and iron as well as a control with no nutrient addition. After one summer, we found that total porewater conductivity increased with nutrient loading under both soil types. Under higher nutrient treatments the concentrations of porewater sulfide were elevated to phytotoxic levels, but this effect was only observed in the organic soil treatment. Nitrate and ammonium porewater concentrations were affected by both nutrient loading and soil type; however, nitrate was higher in the mineral soil while ammonium was higher in the organic soil. Porewater phosphorous and potassium concentrations were elevated in organic soil conditions and higher nutrient loading, while porewater iron was higher under mineral soil and lower nutrient loading. Aboveground standing crop, belowground biomass accumulation (i.e., ingrowth), and soil shear strength were also sampled at the end of the growing season with the goal of examining their relationships with nutrient and sediment enrichment and porewater chemistry.</p>
Dataset for: Calcium promotes persistent soil organic matter by altering microbial transformation of plant litter
<p>Dataset and code for the publication:</p> <p>Shabtai, I.A., Wilhelm, R.C., Schweizer, S.A. <em>et al.</em> Calcium promotes persistent soil organic matter by altering microbial transformation of plant litter. <em>Nat Commun</em> <strong>14</strong>, 6609 (2023). https://doi.org/10.1038/s41467-023-42291-6<br><br></p>
Dataset: Effect of soil organic matter content and nutrient loading on productivity of Spartina patens (v.0.10)
Open the record for dataset details and reuse information.
Effect of land use and soil organic matter quality on the structure and function of microbial communities in pastoral soils: implications for disease suppression
GEO Series GSE112489. Archaea; uncultured soil bacterium; Bacteria; Eukaryota. 50 samples. Type: Other.
The soil organic matter decomposition mechanisms in ectomycorrhizal fungi are tuned for liberating soil organic nitrogen
GEO Series GSE110485. Paxillus involutus; Laccaria bicolor. 24 samples. Type: Expression profiling by high throughput sequencing.
Organic matter content (om) soil maps of the Upper Colorado River Basin
<p>The data here were originally posted to facilitate timely and transparent peer review. The final public data release with formal metadata is now available from at the following location:</p> <p>Nauman, T.W., and Duniway, M.C., 2020, Predictive soil property maps with prediction uncertainty at 30 meter resolution for the Colorado River Basin above Lake Mead: U.S. Geological Survey data release,<a href="http://https//doi.org/10.5066/P9SK0DO2"> https://doi.org/10.5066/P9SK0DO2</a>.</p> <p>Associated publication:</p> <p>Nauman, T. W., and Duniway, M. C., 2020, A hybrid approach for predictive soil property mapping using conventional soil survey data: Soil Science Society of America Journal, v. 84, no. 4, p. 1170-1194. <a href="https://doi.org/10.1002/saj2.20080">https://doi.org/10.1002/saj2.20080</a>.</p> <p>UPDATE: WE FOUND A RENDERING ERROR IN MANY AREAS OF THE 5 CM MAP. WE HAVE RECREATED THE MAP AND INCLUDED IN THIS VERSION OF THE REPOSITORY.</p> <p>Repository includes maps of organic matter content (% wt) as defined by United States soil survey program. </p> <p>These data are preliminary or provisional and are subject to revision. They are being provided to meet the need for timely best science. The data have not received final approval by the U.S. Geological Survey (USGS) and are provided on the condition that neither the USGS nor the U.S. Government shall be held liable for any damages resulting from the authorized or unauthorized use of the data.</p> <p>This data should be used in combination with a soil depth or depth to restriction layer map (both layers that will be released soon as part of this project) to eliminate areas mapped at deeper depths than the soil actually goes. This is a limitation of this data which will hopefully be updated in future updates. </p> <p>The creation and interpretation of this data is documented in the following article. Please note this article has not been reviewed yet and this citation will be updated as the peer review process proceeds.</p> <p>Nauman, T. W., Duniway, M. C., In Preparation. Predictive reconstruction of soil survey property maps for field scale adaptive land management. Soil Science Society of America Journal.</p> <p>File Name Details:</p> <p>ACCURACY!! Please see manuscript and Github repository (https://github.com/naumi421/SoilReconProps) for full details on accuracy. We do provide cross validation (CV) accuracy plots in this repository for both the overall sample (_CV_plots.tif). These plots compare CV predictions with observed values relative to a 1:1 line. Values plotted near the 1:1 line are more accurate. Note that values are plotted in hex-bin density scatter plots because of the large number of observations (most are >3000). Predictions are also evaluated with the U.S. soil survey laboratory database soil organic carbon (SOC) data. The SOC measurements were coverted to OM matter values using the common 1.724 conversion factor. The converted OM values are compared to predicted OM values using an accuracy plot (OM_SOC_plots.tif).</p> <p>Elements are separated by underscore (_) in the following sequence:</p> <p>property_r_depth_cm_geometry_model_additional_elements.extension</p> <p>Example: om_r_0_cm_2D_QRF_bt.tif</p> <p>Indicates soil organic matter content (om) at 0 cm depth using a 2D model (separate model for each depth) employing a quantile regression forest. This file is the raster prediction map for this model. There may be additional GIS files associated with this file (e.g. pyramids) that have the same file name, but different extensions. The _bt indicates that the map has been back transformed from ln or sqrt transformation used in modeling.</p> <p>The following elements may also exist on the end of filenames indicating other spatial files that characterize a given model's uncertainty (see below).</p> <p>_95PI_h: Indicates the layer is the upper 95% prediction interval value.</p> <p>_95PI_l: Indicates the layer is the lower 95% prediction interval value.</p> <p>_95PI_relwidth: Indicates the layer is the 95% relative prediction interval (RPI). The RPI is a standardization of the prediction interval that indicates that model is constraining uncertainty relative to the original sample. RPI values less than one represent uncertainty is being improved by the model relative to the original sample, and values less than 0.5 indicate low uncertainty in predictions. See paper listed above and also Nauman and Duniway (In revision) for more details on RPI.</p> <p>References</p> <p> Nauman, T. W., and Duniway, M. C., In Revision, Relative prediction intervals reveal larger uncertainty in 3D approaches to predictive digital soil mapping of soil properties with legacy data: Geoderma</p>
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International Brain Laboratory public data
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OpenNeuro
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