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388 results for “organic matter”
Organic matter loading modifies the microbial community responsible for nitrogen loss in estuarine sediments
GEO Series GSE65430. synthetic construct; aquatic metagenome. 4 samples. Type: Other.
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>
GNPS - Non-targeted 2D LC-MS/MS analysis of NEHLA Dissolved Organic Matter (2/2)
Open the record for dataset details and reuse information.
GNPS - Non-targeted 2D LC-MS/MS analysis of NEHLA Dissolved Organic Matter (1/2)
Open the record for dataset details and reuse information.
Dataset - A multiparametrical analysis of spatiotemporal dissolved organic matter variation in three catchments of Lake Nam Co, Tibetan Plateau
<p>The multiparametrical dataset employed in the upcoming reserach contribution of spatiotemporal dissolved organic matter variation in three catchments of Lake Nam Co, Tibetan Plateau</p> <p> </p> <p>Disclaimer: 04.01.2022, associated full text in preparation by authors</p>
Bacteria rather than fungi mediate the chemodiversity of dissolved organic matter in a mudflat intertidal zone
<p>Sediment samples were collected from a mudflat intertidal zone (120.75 °E, 36.46 °N) located in Qingdao, China. A nested sector sampling scheme was designed to investigate the DOM chemodiversity and its associations with biotic and abiotic factors. Specifically, the circular center of the sector (quarter circle) was located on the mudflat between the highest and lowest tide levels, and the radii of the nested sectors were 5m, 10m, 20m, 50m, 100m and 200m. A total of 13 sediment samples were collected after the tide had retreated when the sediment was exposed to the air. For each sample, five surface sediment cores (~15 cm depth) were collected, homogenized and immediately placed in ice boxes before transporting to the laboratory. The chemical composition of DOM was determined by SPE-ESI for 13 samples.</p>
Data associated with: Shifts in controls and abundance of particulate and mineral-associated organic matter fractions among subfield yield stability zones.
<p>These are the soil organic matter fraction and environmental covariate data associated with the manuscript, " Shifts in controls and abundance of particulate and mineral-associated organic matter fractions among subfield yield stability zones." Please note that these data are currently for review only; our agreement with farmers currently limits the public availability of these data for any purposes other than review by assigned peer-reviewers. Following review, data will be shared following a reasonable request.</p>
Dataset - Dissolved organic matter sources and processing in the endorheic Lake Nam Co catchment (Tibet) as assessed by ultra-high resolution Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS)
<p> </p> <p>Disclaimer 2022-01-04: Associated full text in preparation</p>
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International Brain Laboratory public data
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OpenNeuro
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