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60 results for “Organic content”
Organic matter and sand content for backbarrier marsh cores from Metompkin island, VA 2012
Cores collected: Summer of 2012 Organic matter and sand content for backbarrier marsh cores from Metompkin island. Cores were taken from 6 different locations in the backbarrier on the south end of Metompkin island, with varying along- and cross-shore distances. The core sites are labelled MA-MF (eg: Metompkin core A, Metompkin core B, etc.), and each has an associated set of latitude and longitude coordinates showing the location where the core was taken. Included is the data for the percent organic matter, measured at 5cm intervals in the core, via loss-on-ignition experiments. Also included is the data for the percent sand, measured at 10cm intervals in the core, using a LS 13 320 particle analyzer.
Raw data for the manuscript: Influence of soil organic matter content on the toxicity of pesticides to soil invertebrates: A review
<p>Files containing Survival (LC50) and reproduction (EC50) data for soil invertebrates exposed to organic chemicals in different soils. The first file contains an overview of all the toxicity data used in the study. The second and third files contain the data used for the "direct comparisons" method, and the fourth and fifth files contain the data (and calculated ratios) used for the "indirect comparisons".</p>
The first comprehensive revision of all the species attributed to Melomys led J. I. Menzies in 1996 to resurrect the genus Paramelomys and to redefine its morphologicallimits and species content. Menzies created P. gressitti as a new species belonging to a group displaying morphological similarities and including also P. lorentzii and P. moncktoni. Monotypic Distribution. E New Guinea. Descriptive notes. Head-body 135-162 mm, hindfoot 30-34 mm; no specific data are available for body weight. Gressitt's Mosaic-tailed Rat is a medium-sized Paramelomys with a soft, thick and woolly pelage, a long narrow foot, and a tail with three hairs per scale. It exhibits a medium-sepia dorsal pelage and a gray-buff ventral one. Tail is slightly shorter (99%) than head-body length. The skull has a narrow zygomatic plate. Habitat. Moist tropical mountain forest between 2300 m and 2400 m. Food and Feeding. No information. Breeding. No information. Activity patterns. Gressitt's Mosaic-tailed Rat is terrestrial. Movements, Home range and Social organization. No information. Status and Conservation. Classified as Endangered on The IUCN Red List owing to its small geographic range (less than 3500 km?*) and the destruction ofits habitat by mining and logging activities. The major threat to Gressitt's Mosaic-tailed Rat is ongoing habitat degradation caused by nearby human populations; habitat on Mount Kandy has been destroyed by gold-miners and wood-cutters. Bibliography. Menzies (1996). in Muridae
The first comprehensive revision of all the species attributed to Melomys led J. I. Menzies in 1996 to resurrect the genus Paramelomys and to redefine its morphologicallimits and species content. Menzies created P. gressitti as a new species belonging to a group displaying morphological similarities and including also P. lorentzii and P. moncktoni. Monotypic Distribution. E New Guinea. Descriptive notes. Head-body 135-162 mm, hindfoot 30-34 mm; no specific data are available for body weight. Gressitt's Mosaic-tailed Rat is a medium-sized Paramelomys with a soft, thick and woolly pelage, a long narrow foot, and a tail with three hairs per scale. It exhibits a medium-sepia dorsal pelage and a gray-buff ventral one. Tail is slightly shorter (99%) than head-body length. The skull has a narrow zygomatic plate. Habitat. Moist tropical mountain forest between 2300 m and 2400 m. Food and Feeding. No information. Breeding. No information. Activity patterns. Gressitt's Mosaic-tailed Rat is terrestrial. Movements, Home range and Social organization. No information. Status and Conservation. Classified as Endangered on The IUCN Red List owing to its small geographic range (less than 3500 km?*) and the destruction ofits habitat by mining and logging activities. The major threat to Gressitt's Mosaic-tailed Rat is ongoing habitat degradation caused by nearby human populations; habitat on Mount Kandy has been destroyed by gold-miners and wood-cutters. Bibliography. Menzies (1996).
Predicted organic carbon content on the Norwegian continental margin
<p>Output data relating to R workflow for predicting organic carbon content on the Norwegian continental margin (https://github.com/diesing-ngu/TOC). The following files are included:</p> <p><strong>OC0-10cm_median_2024-02-16.tif</strong> - Georeferenced Tiff-file of the predicted organic carbon content in the upper 10 cm of the sediment column</p> <p><strong>OC0-10cm_PI90_2024-02-16.tif</strong> - Georeferenced Tiff-file of the 90% prediction interval. Can be used as a measure of uncertainty.</p> <p><strong>OC0-10cm_AOA_2024-02-16.tif </strong>- Georeferenced Tiff-file of the area of applicability of the model <a href="https://doi.org/10.1111/2041-210X.13650">(Meyer & Pebesma, 2021)</a></p> <p><strong>OC0-10cm_AOA_2024-02-16.shp</strong> - Same as above but as polygon shapefile</p>
Input data for predicted organic carbon content on the Norwegian continental margin
<p>Input data relating to R workflow for predicting organic carbon content on the Norwegian continental margin (https://github.com/diesing-ngu/TOC). The following files are included:</p><p><strong>mosaic_2023-04-21.csv</strong> - Data on organic carbon content in surface sediments from the <a href="https://doi.org/10.5194/essd-15-4105-2023">MOSAIC v2.0</a> database</p><p><strong>predictors_ngb.tif </strong>- Multi-band georeferenced TIFF-file of predictor variables</p><p><strong>predictors_description</strong>.txt - Information on variables stored in predictor_ngb.tif including units, statistics, time period and sources.</p><p><strong>GrainSizeReg_folk8_classes_2023-06-28.tif</strong> - Georeferenced TIFF-file of predicted substrate classes. Used to update the area of interest (exclude areas mapped as Rock and boulders).</p><p><strong>mud_2023-06-30.tif </strong>- Georeferenced TIFF-file of predicted mud content. Used as an additional predctor.</p>
Excess 210Pb, 137C, total organic carbon content, HBI biomarkers (IPSO25, HBI III) and biogenic silica of marine deposits from sediment core 2018_R2_2F from Sheldon Cove, Antarctic Peninsula
<p><strong>Description</strong>: Sediment core 2018_R2_2F was collected from Sheldon Cove, Antarctic Peninsula (67.55°S 68.27°W) from a water depth of 177 m, in December 2018 as part of expedition JR18003 by the British Antarctic Survey aboard RV James Clark Ross (Sands et al. 2019). Total core length was 25 cm. The dataset presented here consists of: gamma spectrometry measurements of excess 210Pb (calculated as a difference between the total 210Pb and the average of 214Pb and 214Bi) and 137Cs; total organic carbon (TOC) content; biogenic silica (BSi) content; and HBI biomarker (IPSO25, HBI III) concentrations. The excess 210Pb and 137Cs were measured at the Institute of Geology at Adam Mickiewicz University in Poznań, Poland, using a gamma detector Canberra BE3830, cooled with cryostat Cryo-Pulse®5 plus. The detector is placed in 10 cm thick lead shield walls and is equipped with a remote detector chamber option (RDC-6 inches) for low energy background reduction. The detector was commercially characterized by ISOCS (In-Situ Object Calibration Software) and LabSOCS (Laboratory Sourceless Object Calibration Software). Efficiencies for measured geometries were determined using LabSOCS code applying all corrections for sample geometry, matrix, and container type, and were verified with IAEA standards measurements. The results (spectra) were analyzed in Canberra GENIE-2000 v. 3.3 gamma spectrometry software and are presented with 2-sigma uncertainty ranges (Szczuciński, submitted). TOC concentrations (given in %) were measured at the Faculty of Earth Sciences, University of Silesia, Poland, using an Eltra CS-500 IRanalyzer with a Total Inorganic Carbon module according to the procedure described in Racka et al. (2010). TOC was calculated as the difference between TC (total carbon) and TIC (total inorganic carbon). Each TOC sample was analysed in duplicate. Analytical precision and accuracy were better than ±2% for TC and ±3% for TIC. HBI biomarker preparation and analysis followed slightly modified (Pieńkowski et al. 2021) standard protocols (Belt 2012). HBI concentrations are given per weight of sediment (ng/g sed), and organic carbon content (μg/g OC) (Belt et al. 2012). Biogenic (opaline) silica (BSi) analysis on dried, homogenised samples followed Heiri et al. (2001) and Bechtel et al. (2007). Each BSi and TOC sample was analysed in duplicate; values are given in %. BSi and TOC standard deviation calculations are based on data from the replication.</p> <p><strong>References</strong> <br><br>* Bechtel, A., Woszczyk, M., Reischenbacher, D., Sachsenhoffer, R., Gratzer, R., Püttmann, W. Spychalski, W., 2007: Biomarkers and geochemical indicators of Holocene environmental changes in Lake Sarbsko (Poland). Org. Geoch. 38, 1112–1131. <br>* Belt, S.T., Brown, T.A., Navarro Rodriguez, A., Cabedo Sanz, P., Tonkin, A., Ingle, R. 2012. A reproducible method for the extraction, identification and quantification of the Arctic sea ice proxy IP25 from marine sediments. Anal. Methods 4, 705-713. <br>* Heiri, O., Lotter, A. F., Lemcke, G., 2001. Loss on ignition as a method for estimating organic and carbonate content in sediments: reproducibility and comparability of results. J. Paleolimnol. 25, 101-110. <br>* Pieńkowski, A.J., Husum, K., Belt, S.T., Ninnemann, U., Köseoğlu, D., Divine, D.V., Smik, L., Knies, J., Hogan, K., Noormets, R. 2021. Seasonal sea ice persisted through the Holocene Thermal Maximum at 80°N. Commun. Earth Environ. 2, 124. <br>* Racka, M., Marynowski, L., Filipiak, P., Sobstel, M., Pisarzowska, A., Bond, D.P.G., 2010: Anoxic Annulata events in the Late Famennian of the Holy Cross Mountains (Southern Poland): geochemical and palaeontological record. Palaeogeography, Palaeoclimatology, Palaeoecology 297(3-4), 549-575. <br>* Sands, C.J., Annett, A., Apeland, B., Barnes, D.K.A, Bascur, M., Bruning, P., Costa, M., Dadd, G., De Lecea, A., Ensor, N., Featherstone, A., Flint, G., Goodger, D., Guzzi, A., Howard, F., Hunter, D., Jenkins, S., Kender, S., Lincoln, B., Munoz-Ramirez C., Pienkowski, A., Retallick, K., Roman-Gonzalez, A., Scourse, J., Sheen, K., Whitaker, T., Williams, J., Zhao, L., Zwerschke, N., 2019: JR18003 Cruise Report. British Antarctic Survey, 132 pp. <br>* Szczuciński, W. (submitted): Applications of gamma-emitting isotopes (210Pb and 137Cs) for assessment of sedimentary processes – insights from studies of lake, deltaic and continental shelf deposits. <br><br><strong>Projects</strong> <br><br>* CHARME: CHanging AntaRctic Marine Environments, <strong>Web</strong>: <a title="Follow link" href="https://charme.amu.edu.pl/" target="_blank" rel="nofollow noopener">https://charme.amu.edu.pl/</a>, <strong>Award</strong>: Norwegian Financial Mechanism 2014-2021, UMO-2020/37/K/ST10/04127 <br><br><strong>File descriptions</strong>: Excel file with all data, as well as core details (coordinates and water depth).</p> <p><strong>Comment</strong>: This dataset is related to the following article which has been accepted for publication:</p> <p>Pieńkowski, Anna J.; Szczuciński, Witold; Breszka, Agnieszka; Chyleński, Maciej; Juras, Anna; Romel, Paulina; Rozwalak, Piotr; Trzebny, Artur; Dabert, Mirosława; Belt, Simon; Jagodziński, Robert; Smik, Lukas; Włodarski, Wojciech. Sedimentary ancient DNA and HBI biomarkers as sea-ice indicators: a complementary approach in Antarctic fjord environments. Limnology Oceanography Letters. doi: 10.1002/lol2.10395</p>
Aerosol Particle Hygroscopicity and Aerosol Water Content is Driven by Nitrate and Organics in the Particle Phase in Houston, TX.
<p>Related datasets and codes utilized in preparing the manuscript by the same name, submitted to JGR Atmosphere in June 2024. </p>
Data for: Cover crop functional types differentially alter the content and composition of soil organic carbon in particulate and mineral-associated fractions
<p>Cover crops (CCs) can increase soil organic carbon (SOC) sequestration by providing additional OC residues, recruiting beneficial soil microbiota, and improving soil aggregation and structure. The various CC species that belong to distinct plant functional types (PFTs) may differentially impact SOC formation and stabilization. Biogeochemical theory suggests that selection of PFTs with distinct litter quality (C:N ratio) should influence the pathways and magnitude of SOC sequestration. Yet, we lack knowledge on the effect of CCs from different PFTs on the quantity and composition of physiochemical pools of SOC. We sampled soils under monocultures of three CC PFTs (legume [crimson clover]; grass [triticale]; and brassica [canola]) and a mixture of these three species, from a long-term CC experiment in Pennsylvania, USA. We measured C content in bulk soil and C content and composition in contrasting physical fractions: particulate organic matter, POM; and mineral-associated organic matter, MAOM. The bulk SOC content was higher in all CC treatments compared to the fallow. Compared to the legume, monocultures of grass and brassica with lower litter quality (wider C:N) had higher proportion of plant-derived C in POM, indicating selective preservation of complex structural plant compounds. In contrast, soils under legumes had greater accumulation of microbial-derived C in MAOM. Our results for the first time, revealed that the mixture contributed to a higher concentration of plant-derived compounds in POM relative to the legume, and a greater accumulation of microbial-derived C in MAOM compared to monocultures of grass and brassica. Mixtures with all three PFTs can thus increase the short- and long-term SOC persistence balancing the contrasting effects on the chemistries in POM and MAOM imposed by monoculture CC PFTs. Thus, despite different cumulative C inputs in CC treatments from different PFTs, the total SOC stocks did not vary between CC PFTs, rather PFTs impacted whether C accumulated in POM or MAOM fractions. This highlights that CCs of different PFTs may shift the dominant SOC formation pathways (POM vs. MAOM), subsequently impacting short- and long-term SOC stabilization and stocks. Our work provides a strong applied field test of biogeochemical theory linking litter quality to pathways of C accrual in soil.</p>
Data for: Cover crop functional types differentially alter the content and composition of soil organic carbon in particulate and mineral-associated fractions
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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>
Data from: High nighttime humidity and dissolved organic carbon content support rapid decomposition of standing litter in a semi-arid landscape
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In-depth organic mass cytometry reveals differential contents of 3-hydroxybutanoic acid at the single-cell level
GEO Series GSE262591. Homo sapiens. 1 samples. Type: Expression profiling by high throughput sequencing.
Web-based content organization and the transformation of traditional classification systems
<p> Traditional hierarchical classification systems were designed to optimize the management, findability and use of physical collections of objects. But as more and more collections of objects are being accessed and used on the Web, these predominant classification models have been modified by facetted taxonomies with semantic relationships. The diverse uses of information require specialized classification strategies that reach beyond simple use cases. The ubiquity of web search engines and hypertext is also leading to new interest in labelling and describing named entities. This paper discusses these developments and provides examples for their utility in a variety of organizations, profit and non-profit.</p>
Organic carbon content and estimated organic carbon stocks for Northern Irish Marine Sediments
<p>Northern Ireland is a constituent region of the United Kingdom, consisting of 14,330 square kilometers of land in the north east of the island of Ireland. Northern Ireland's devolved administration has repsonsibility for 6000 square kilometers of shelf seas, encompassing the north western portion of the Irish Sea, the North Channel and part of the Malin Sea. There is growing interest in the capacity of marine sediments to sequester and store carbon, as a potential natural feedback against climate change. Between 2021 and 2024, the Northern Ireland Department of Agriculture, the Environment and Rural Affairs provided funding to AFBI NI to support the initial quantification and mapping of sediment carbon content in Northern Ireland's Marine Sediments. Here we present a consolidated dataset of sediment organic carbon content and estimates of areal seabed carbon stocks (for the upper 10cm of sediment) across the Northern Irish portion of the UK's territorial seas. The dataset includes sediment carbon data from recent oceanographic surveys, alongside historical datasets from AFBI's internal data archive. The data are supported by metadata including location (Latitude and Longitude), bathymetric depth, seabed type (percentage mud, sand and gravel), year of collection, sampling metier and information on the data source.</p>
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>
FEATURES OF THE ORGANIZATION OF FOREIGN LANGUAGE TEACHING IN THE MODERNIZATION OF EDUCATIONAL CONTENT
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Content, Bioavailability and Health Effects of Trace Elements and Bioactive Components in Organic Agricultural Systems
ClinicalTrials.gov study NCT00738166. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Dataset: Effect of soil organic matter content and nutrient loading on productivity of Spartina patens (v.0.10)
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Transcriptional responsen of phosphorus (re-)absorbing organs to diets varying in phosphorus content in pigs (low-intake; medium intake; high-intake)
GEO Series GSE94448. Sus scrofa. 57 samples. Type: Expression profiling by array.
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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