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245 results for “soil datasets”
Dataset for Estimating soil hydraulic properties from oven-dry to full saturation using inverse modeling and shortwave infrared imaging
<p>In this repository, we provide all the datasets that are needed to reproduce the analysis conducted in the paper entitled "Estimating soil hydraulic properties from oven-dry to full saturation using inverse modeling and shortwave infrared imaging."</p> <p><br> codes: This folder contains Python codes to run the forward and inverse modeling. Install the following packages.<br> notebook, fenics, numpy, pandas, matplotlib, scipy, numdifftools, and lmfit for inverse modeling (needs to be run on Linux).<br> data: This directory contains data used in the inverse modeling.<br> gif: This directory contains GIF movies of the upward infiltration experiments.</p> <p>readme.xlsx: This file explains which data are used for each figure in the paper.</p>
Dataset and code for "Evident decrease in future European soil moisture in the Kiel Climate Model grand ensemble"
<p>Here, you only have the processed data. Most calculations have been made with CDO (version 2.0.6 or 1.9.9). The history of commands made can be seen in the file with a simple ncdump -h file. If you need to see more data, please contact the corresponding author.</p>
Spatial patterns and effects of invasive plants on soil microbial activity and diversity along river corridors - dataset
<p>environmental data, plant community data, CLPP profiles, microbial activity data</p>
Soil grid dataset of agricultural sites in the Czech Republic
<p>The current dataset includes 320 topsoil samples (0–20 cm depth) collected from four agricultural sites in the Czech Republic. The samples were gathered from Přestavlky, Klučov, Nová Ves nad Popelkou, and Udrnice (80 samples from each site) in June 2021. It contains sample coordinates and some soil parameters including SOC and texture, prepared and stored in MS Excel (.xlsx) format. The data were used in STEROPES WP1 (basic local model development), WP3 (effect of texture), and WP4 (effect of vegetation and plant residues). </p>
SensRes dataset for downscaling soil maps
<p>This dataset contains soil information and sensor data from agricultural fields in Denmark, Lithuania, Northern Ireland, the Netherlands, and Turkey to downscale coarse-resolution maps to high resolution in the SensRes project (EJP SOIL).</p> <p> It includes 1455 soil samples with data on soil organic carbon and soil texture fractions (clay, silt, and sand). For each sampling site, the dataset also contains rasters of Sentinel-2 bare soil images, aerial images (RGB), and maps from Electromagnetic Induction and Gamma sensors. The soil data is provided in .txt file format, while the sensor data is available in .tif format. There are also shapefiles from each field in .shp format. </p> <p>The SensRes project developed a framework for downscaling soil maps, which was published as an R package (<a href="https://github.com/anbm-dk/soilscaler/tree/main">https://github.com/anbm-dk/soilscaler/tree/main</a>), and this dataset contains the required local inputs to apply the downscaling process. Part of the soil information present in this dataset has also been used in the STEROPES EJP SOIL project. </p>
Dataset of the assessment of the sensitivity of soil communities under climate change
<p>Dataset of the assessment of the sensitivity of soil communities under climate change. Includes measures of microbial biomass and enzymatic activities </p>
Dataset on laboratory soil greenhouse gas fluxes and soil microbial parameters as affected by soil management strategies in SOMMIT long term experiments
<p>We present a database containing over 50 soil-microbial parameters from eight long-term European experiments where specific soil management strategies are compared. Intact topsoil cores (7 cm diameter, 7 cm height) were collected from LTE participating in the tasks WP3.2 and WP3.3. from the SOMMIT experiment, and incubated under standard conditions in the laboratory. The soil management strategies considered at the eight LTEs ("ACBB Estrées-Mons, France", "Rutzendorf_17, Austria", , "Foggia, Italy", "ULBF-Ljubljana, Slovenia", "Toholampi, Finland", "Senés, Spain", "La Poveda, Spain" and "Grabow 1, Poland") included crop residue management, addition of different types of compost and sludge and biochar addition. All LTEs are referenced according to the LTE Index from https://doi.org/10.5281/zenodo.7598122 . The soil cores were subjected to i) a pre-equilibration phase of five days ("pre.inc"), followed by ii) a drying phase ("DR") of ten days and finally a iii) rewetting (five days, "RW"). A subset of the cores were kept under iv) constantly moist conditions for comparison purposes ("moist"). By the end of the "pre.inc" phase, soil microbial biomass, soil microbial community (phospholipidic fatty acids), enzymatic activities and soil nutrient data were collected. After the "pre.inc" phase, soil fluxes of N2O and CO2 were monitored with an automated system at subdaily temporal resolution. In addition, soil nutrients and microbial biomass data were estimated during at the end of the "DR", "RW" and "moist" phases. This dataset contributes to a better understanding of the linkages between soil conditions, soil microbes and soil greenhouse gas fluxes as affected by different soil management strategies across European agro-ecosystems. This product is part of the EJP SOIL internal project SOMMIT, and serves as deliverable WP3.4</p>
Datasets used to support the work presented in: Beringer, C.J., K.W. Goyne, R.N. Lerch, E.B. Webb, and D. Mengel. 2020: Clothianidin decomposition in Missouri wetland soils. J. Environ. Qual. JEQ-2020-05-0167-TR
<p>Neonicotinoid pesticides can persist in soils for extended time periods; however, they also have a high potential to contaminate ground and surface waters. Studies have reported negative effects associated with neonicotinoids and non-target taxa, including aquatic invertebrates, pollinating insect species, and insectivorous birds. This study evaluated factors associated with clothianidin (1-[(2-chloro-1,3-thiazol-5-yl) methyl]-3-methyl-2-nitroguanidine, CTN) degradation and sorption in Missouri wetland soils to assess the potential for wetland soils to mitigate potential environmental risks associated with neonicotinoids. Solid-to-solution partition coefficients (<i>K</i><sub>d</sub>) for CTN sorption to eight wetland soils were determined via single-point sorption experiments, and sorption isotherm experiments were conducted using the two most contrasting soils. Clothianidin degradation was determined under oxic and anoxic conditions over 60 d. Degradation data were fit to zero- and first-order kinetic decay models to determine CTN half-life, i.t<sub>0.5</sub>). Sorption results indicated CTN sorption to wetland soil was relatively weak (average <i>K<sub>d </sub></i>= 3.58 L kg<sup>-1</sup>); thus, CTN has the potential to be mobile and bioavailable within wetland soils. However, incubation results showed anoxic conditions significantly increased CTN degradation rates in wetland soils (anoxic average <i>t<sub>0.5</sub> </i>=27.2 d; oxic average<i> t<sub>0.5</sub></i> = 149.1 d). A significant negative correlation was observed between anoxic half-life values and soil organic carbon content (r<sup>2</sup>=0.782; <i>p</i>=0.046). Greater CTN degradation rates in wetland soils under anoxic conditions suggest that managing wetlands to facilitate anoxic conditions could mitigate CTN presence in the environment and reduce exposure to non-target organisms.</p>
Dataset for: Relative contribution of high and low elevation soil microbes and nematodes to ecosystem functioning
<ol> <li><span>Ecosystem productivity is largely dependent on soil nutrient cycling which, in turn, is driven by decomposition rates governed by locally-adapted belowground microbial and invertebrate communities. How climate change will impact soil biota and the correlated ecosystem functioning, however, remains largely an open question.</span></li> <li><span>To address this challenge, we first characterized the functional identity of soil microbial and nematode communities originated from the foothills or in the sub-alpine soils of the Alps, and then, using a full-factorial reciprocal transplant common garden experiment at two elevations, we asked whether soil biota from low elevation were more prone in generating nutrient cycling than high elevation soil biota. Specifically, we separately transplanted soil microbial and nematode to community from low and high elevation in their home or opposite elevation in pots added with a common plant community. </span></li> <li><span>We found evidence for ecotypic and functional differentiation of the microbial and nematode communities growing in. We also observed a decrease in microbial diversity and activity at high elevation, and additionally, through nematodes' functional characterization, we found increased fungal-dominated energy channels at high elevation. </span></li> <li><span>Moreover, while we found little effect of soil biodiversity change based on elevation of origin on plant productivity, soils inoculated with microbes originating from low elevation respired more than those originating at high elevation. This observation correlates well with the observed faster carbon degradation rates by the low-elevation microbial communities. </span></li> <li><span>Climate change can reshuffle soil invertebrate communities depending on organism-specific variation in range expansion, ultimately affecting soil fertility and vegetation productivity.</span></li> </ol>
Dataset of the paper: A first-year melon/cowpea intercropping system improves soil nutrients and changes the soil microbial community
<p>Dataset and raw data</p>
Effects of soil conditioning, root and shoot litter addition interact to determine the intensity of plant-soil feedback (dataset)
<p>Plant-soil feedback (PSF) is recognized as an important mechanism shaping plant communities and determining plant abundance and coexistence. Under natural conditions, plants affect the outcome of plant-soil interactions simultaneously by conditioning the soil by living roots and by litter inputs into the soil. However, most experimental studies only focus on one of the pathways, which limits our understanding of PSF in the field. </p> <p>Here, we simultaneously explored the effect of soil conditioning by living roots and of root and shoot litter addition on the performance of seven <em>Impatiens</em> species grown in a two-phase garden experiment. </p> <p>Soil conditioning negatively affected plant performance and the effect was at least partly explained by nutrient depletion. Root litter addition affected plant performance negatively and the results suggest that biotic effects such as pathogen transmission via the root litter played a role. The effects of root litter addition were more pronounced in control soil which, contrary to the conditioned soil, supposedly did not accumulate pathogens during the conditioning phase. Shoot litter addition increased soil nutrient levels, but had no impact on plant performance. However, presence of shoot litter aggravated the negative effects of root litter, probably due to increased amounts of nutrients available for soil biota and thus their faster growth and intensified effect on the plants. </p> <p><span></span></p> <p>Overall, our study suggests that root and shoot litter have contrasting roles in plant-soil interactions and understanding their separate and interactive effects together with effects of soil conditioning is crucial for assessing the complexity of PSF.</p>
UAS dataset for soil moisture mapping
<p>This dataset is obtained from a UAS survey on 13-14 June 2019 on the field site MFC2 located in Monteforte Cilento (SA, Italy), within the Harmonious COST action CA16219 - Harmonization of UAS techniques for agricultural and natural ecosystems monitoring-, activities framework. The general aim was soil moisture mapping using the thermal inertia method and vegetation-temperature triangle model method. A multispectral camera (tetracam) and a thermal one (FLIR tau2) were used. The NDVI was calculated from the red and near-infrared reflectance from the multispectral imagery, and the land surface temperature was generated from the thermal imagery</p>
Dataset for 'Massive warming-induced carbon loss from subalpine grassland soils in an altitudinal transplantation experiment' Volk et al. 2022
<p>These files contain the essential data used to produce the above paper</p>
Soil Moisture from SMAP, Sentinel 1 and in-situ observations dataset
<p>Each folder contains the dataset for the entire CONUS over the corresponding time period.</p> <p>For folder contains two classes of GeoTIFF images, namely the NW_Day_XXX_9km_Signals.tif and NW_Day_XXX_1km_Signals.tif, corresponding to data at 9 and 1 km spatial resolution respectively (XXX encodes the specific date e.g. 20180601)</p> <p>Each *9km_Signals.tif image contains 7 bands that correspond to the following variables:</p> <ol> <li> <p>SMAP Tb, Horizontal polarization</p> </li> <li> <p>SMAP Tb, Vertical polarization</p> </li> <li> <p>Soil Moisture (estimation)</p> </li> <li> <p>Clay</p> </li> <li> <p>Bulk Density</p> </li> <li> <p>Latitude</p> </li> <li> <p>Longitude</p> </li> </ol> <p> </p> <p>Each *1km_Signals.tif image contains 12 bands that correspond to the following variables:</p> <ol> <li> <p>Sentinel 1 σ0, Vertical polarization</p> </li> <li> <p>Sentinel 1 σ0, Horizontal polarization</p> </li> <li> <p>SMAP TB, vertical polarization;</p> </li> <li> <p>In-Situ Soil Moisture value</p> </li> <li> <p>Soil Moisture (estimated) at 1km;</p> </li> <li> <p>Vegetation Water Content</p> </li> <li> <p>Surface Temperature</p> </li> <li> <p>Precipitation</p> </li> <li> <p>Land cover map</p> </li> <li> <p>In-Situ location name</p> </li> <li> <p>Latitude</p> </li> <li> <p>Longitude</p> </li> </ol> <p> </p>
Dataset of punctual observations along soil moisture gradients in France
<p><span>The interface between wetlands and uplands is characterized by grad</span><span>ients</span><span> in hydrological, soil and biological components. </span><span>Consequently</span><span>, the exact spatial distribution of this transitional area </span><span>is not well </span><span>known because it often occurs as a fuzzy moisture gradient. However, ecological assessment and conservation require mapping and characterizing this interface to better understand and model biotic and abiotic interactions between wetlands and uplands. To this end, </span><span>in 2021 and 2022, </span><span>we observed soil properties and vegetation types along </span><span>soil </span><span>moisture gradients throughout the Atlantic, Continental, Mediterranean and Alpine biogeographic regions of France. The dataset contains </span><span>2 236</span> <span>georeferenced plots (accuracy ± 5 m) distributed along 1 088 transects placed along the slope at 377 sites</span><span>.</span><span> Each plot in the database is characterized by </span><span>21</span><span> fields that describe the vegetation habitat type based on the European Nature Information System (EUNIS) and soil properties (</span><span>i.e. </span><span>depth of appearance and thickness of </span><span>redoximorphic features </span><span>in the soil profile, moisture). These data are useful for researchers and engineers in a variety of disciplines </span><span>(e.g. E</span><span>arth and life sciences) to calibrate and validate </span><span>models to predict </span><span>the spatial distribution of habitats or</span><span> to analyze</span><span> flow</span><span>s</span><span>.</span></p>
Soil and Rock dataset Santa Cruz Galapagos
<p>General data about study sites as well as texture, geochemistry of soil and rock samples are presented in this database.</p>
Dataset for "Towards an ecosystem capacity to stabilise organic carbon in soils"
<p>This dataset includes the data that was used in the Global Change Biology publication "Towards an ecosystem capacity to stabilise organic carbon in soils" by Poeplau et al.. It contains two xlsx files, with dataset_full.xlsx including all sites with soil properties that were used in the first part of the manuscript. It is a combined dataset from several open source datasets with a total of 1396 individual sites. The file modelled_converged.xlsx includes the RothC model results of a total of 587 sites, for which modelling was possible and a convergence of measured and modelled data was reached. Both files include two sheets, one with a short explanation of the variable names and one data sheet. </p>
Supplemental Dataset for Article: Non-invasive measurements on production, release, and vertical distribution of biogenic gas content in large peat soil columns
<p>Supplemental dataset for a journal article in preparation for publication:</p> <p><strong>Structure controls gas migration: Non-invasive measurements on production, release, and vertical distribution of biogenic gas content in large peat soil columns</strong></p> <p>William Wright<sup>1*</sup> and Xavier Comas<sup>1</sup></p> <p><sup>1</sup>Department of Geosciences, Florida Atlantic University, Davie, Florida, 33314, USA</p> <p>*Corresponding author (wwrigh19@gmail.com)</p>
Sensitivity of the landslide model LAPSUS_LS to vegetation and soil parameters - DATASET
<p>The dataset include the data used to run the model and perform the sensitivity of the LAPSUS_LS model to the effect of vegetation described in the paper: 'Sensitivity of the landslide model LAPSUS_LS to vegetation and soil parameters' http://dx.doi.org/10.1016/j.ecoleng.2017.08.010</p>
Dataset underying the publication titled: Warming-induced contrasts in snow depth drive the future trajectory of soil carbon loss across the Arctic-Boreal region
<p>LPJ-GUESS model outputs underlying the figures published in the article "Warming-induced contrasts in snow depth drive the future trajectory of soil carbon loss across the Arctic-Boreal region".</p> <p> </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.
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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.