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245 results for “soil datasets”
Dataset for "Insect frass from upcycling vegetable by-products with cereals: effects on the soil properties, plant development and soil invertebrate fitness"
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From soil to sediment: Bedform migration shapes microbial communities from eroding bank soil during terrestrial-aquatic regime shift [dataset]
<p>This dataset contains raw data of metabolism measurements, microbial abundance, and nutrients that were assessed for the research paper entitled "From soil to sediment: Bedform migration shapes microbial communities from eroding bank soil during terrestrial-aquatic regime shift," which has been submitted to the Journal of Geophysics: Biogeosciences on October 19, 2024. Please note that raw sequencing data were already submitted to the NCBI library and are accessible via https://www.ncbi.nlm.nih.gov./sra/PRJNA1154565.</p> <p>The excel sheet (.xlsx) contains all relevant parameters that were used to detect the influence of environmental parameters on the microbial community structure, e.g. bacterial, fungal and algal abundance, nutrient concentrations, and final NCP and CR rates. The .zip archive contains all raw metabolism measurements during our experimental duration.</p>
Dataset for: Root exudates simultaneously form and disrupt soil organo-mineral associations
<p>Dataset for the publication:</p> <p>Shabtai, I.A., Hafner, B.D., Schweizer, S.A. <em>et al.</em> Root exudates simultaneously form and disrupt soil organo-mineral associations. <em>Commun Earth Environ</em> <strong>5</strong>, 699 (2024). https://doi.org/10.1038/s43247-024-01879-6</p>
Dataset for The Chosen Few — Variations in Common and Rare Soil Bacteria across Biomes
<p>Rarefied relative abundance data of soil bacterial 16S rDNA amplicon sequence variants (ASVs) merged from three studies [1-3] as previously reported [4].<br>The ASV abundance table provided here is based on the previously published data (https://doi.org/10.5281/zenodo.3366252) and was compiled to analyze patterns of bacterial rarity across terrestrial biomes [5].</p><p>This repository consists of the following files:<br>- meta-samples.csv<br> Information on sample locations and additional variables (for units see Supplementary Information of reference [4], p.8)<br>- meta-ASV.csv<br> Sequences and their taxonomic assignment with confidence for highest taxonomic level (see reference [4]).<br>- abundance-table.csv<br> Table with relative abundance of rarefied counts (columns sum to one). The soil sample ids and ASV sequences are used as column and row indices, respectively.</p><p>Dataset citation should refer to [4] and method reference to [5].</p><p>References<br>[1] Bahram, Mohammad, Falk Hildebrand, Sofia K. Forslund, Jennifer L. Anderson, Nadejda A. Soudzilovskaia, Peter M. Bodegom, Johan Bengtsson-Palme, et al. 2018. "Structure and Function of the Global Topsoil Microbiome." Nature 560 (7717): 233–37. https://doi.org/10.1038/s41586-018-0386-6.<br>[2] Thompson, Luke R., Aaron R. Jex, Alexandra H. Campbell, Alexandra M. Linz, Allison Berry, Allison E. Williams, Alyssa Cochran, et al. 2017. "A Communal Catalogue Reveals Earth's Multiscale Microbial Diversity." Nature 551 (7681): 457–63. https://doi.org/10.1038/nature24621.<br>[3] Zhou, Jizhong, Ye Deng, Lina Shen, Chongqing Wen, Qingyun Yan, Daliang Ning, Yujia Qin, et al. 2016. "Temperature Mediates Continental-Scale Diversity of Microbes in Forest Soils." Nature Communications 7 (July): 1–10. https://doi.org/10.1038/ncomms12083.<br>[4] Bickel, Samuel, Xi Chen, Andreas Papritz, and Dani Or. 2019. "A Hierarchy of Environmental Covariates Control the Global Biogeography of Soil Bacterial Richness." Scientific Reports 9 (1): 1–10. https://doi.org/10.1038/s41598-019-48571-w.<br>[5] Bickel, Samuel, and Dani Or. 2021. "The Chosen Few — Variations in Common and Rare Soil Bacteria across Biomes." The ISME Journal, May. https://doi.org/10.1038/s41396-021-00981-3.</p><p> </p>
FTICR-MS Dataset for 'Playing with FiRE: A genome resolved view of the soil microbiome responses to high severity forest wildfire'
<p>This dataset is the raw data for FTICR-MS used in Nelson et al.: 'Playing with FiRE: A genome resolved view of the soil microbiome responses to high severity forest wildfire'. The files correspond to the raw spectral files for each sample and can be opened with Bruker data analysis software. The numbers correspond to sample number (See Supplementary Data 1 in publication for sample metadata) and the r1 and r2 identifiers indicate if there were replicates of that sample.</p>
Soil micronutrients & grassland productivity (NutNet dataset)
<p>The dataset and the R code used in the study: 'Soil properties as key predictors of global grassland production: have we overlooked micronutrients?' The dataset contains information about biomass productivity, climate, soil properties, nutrients and management of 72 non-fertilized NutNet grassland sites. </p>
Dataset for effects of shear zone thickness in root-reinforced soils: Fallow P X-ray CT scans and digital volume correlation data
<p>Dataset for effects of shear zone thickness in root-reinforced soils: Fallow P X-ray CT scans and digital volume correlation data</p>
Dataset for effects of shear zone thickness in root-reinforced soils: Gorse A X-ray CT scans and digital volume correlation data
<p>Dataset for effects of shear zone thickness in root-reinforced soils: Gorse A X-ray CT scans and digital volume correlation data</p>
Dataset for effects of shear zone thickness in root-reinforced soils: Willow C X-ray CT scans and digital volume correlation data
<p>Dataset for effects of shear zone thickness in root-reinforced soils: Willow C X-ray CT scans and digital volume correlation data</p>
Dataset for effects of shear zone thickness in root-reinforced soils
<p>Dataset for paper titled: <strong><em>Modelling of stress transfer in root reinforced soils informed by 4D X-ray computed tomography and digital volume correlation data</em></strong></p> <ul> <li><strong>Rood Area Ratios.zip</strong> - Root area ratio data for figure 6 and figure 7, and table 5.</li> <li><strong>All_load_data_with_reducing_area.xlsx</strong> - Shear Stress vs shear displacement plot for figure 4.</li> <li><strong>Local_shear_Zone_Thickness_vs_x_displacement.xlsx</strong> - Change in shear zone thickness for figure 13.</li> <li><strong>Depth_vs_vx_plots_local_regions.xlsx</strong> - Depth <em>vs</em> <em>x</em>-displacement line profiles for figure 11.</li> <li><strong>Estimate of change in length.xlsx</strong> - Comparison between changes in root length derived from equations and measured directly from the root path geometry for figure 14.</li> <li><strong>Artificial_root.xlsx</strong> - Shear stress-displacement curves for specimens containing an artificial root, and a fallow specimen for figure 17.</li> </ul> <p> </p>
Dataset for effects of shear zone thickness in root-reinforced soils: Gorse G X-ray CT scans and digital volume correlation data
<p>Dataset for effects of shear zone thickness in root-reinforced soils: Gorse G X-ray CT scans and digital volume correlation data</p>
Dataset for effects of shear zone thickness in root-reinforced soils: Fallow D X-ray CT scans and digital volume correlation data
<p>Dataset for effects of shear zone thickness in root-reinforced soils: Fallow D X-ray CT scans and digital volume correlation data</p>
Dataset for: Variations in the reproductive cycle of Bornean montane tree species along elevational gradients on ultrabasic and non-ultrabasic soils
<p><span>Although lowland tree species in the ever-wet regions of Southeast Asia are characterised by the supra-annual cycle of reproduction, the reproductive phenology of montane tree species remains poorly understood. In this study, we investigated the reproductive phenology of montane tree species using litter samples that were collected every two weeks from six rainforest sites, consisting of three elevations (1700, 2700, and 3100 m), on Mount Kinabalu, Borneo. At each elevation, one site was on infertile ultrabasic soil and one was on relatively fertile non-ultrabasic soil. We used a composite sample from 10 or 20 litter traps per site and sorted it by species. Therefore, the obtained data captured reproductive phenology in the population of each species rather than in an individual tree. Ten-year time series of flower and fruit litterfall were obtained for 30 and 39 tree species, respectively. Fourier analysis was used to identify the dominant cycle of each time series. The most abundant cycle across species was supra-annual, followed by sub-annual, and annual cycles. Many species at higher elevations showed supra-annual cycles of flower litterfall, whereas species in the 1700 m sites often showed annual or sub-annual cycles regardless of soil type. No systematic differences were found among sites for fruit litterfall. Mechanisms underlying these elevational patterns in the reproductive cycle remain unclear but may include more </span>severe El Niño droughts, <span>lower primary productivity, lower soil fertility, and the absence of some sub-annually or annually reproducing families at higher elevations.</span></p>
Dataset for Salinity Gradient Solar Pond under different Climatic Conditions and Soil Conditions
<p>Salinity Gradient Solar Pond as a two-dimensional model with an internal heat source. The differential equations in this model are solved using the finite difference technique in MATLAB software.</p> <p>The attached dataset includes the soil conditions, the climate of the particular site, the thickness of the solar pond layers, the depth of the water table.</p>
Dataset for "Co-alignment of Laboratory and In-Situ Reflectance Spectra of Chang'e-5 Lunar Soil"
<p>This dataset provides the reflectance data measured in the laboratory for the <45-μm, 45-355-μm fractions, and bulk soil sample, respectively.</p>
Datasets for numerical Monte Carlo simulations of Diclofenac bio-degradation in a soil-water system
<p>This record contains files and main instructions to repeat the numerical simulations of Diclofenac bio-degradation is a soil-water system. The text file Readme.docx contains a description of the overall content of this record, which is organized in two separate folders.</p>
Datasets for "Reconstructing Global High Quality 3–day Surface Soil Moisture from ESA CCI and SMAP product from 2015 to 2021 using Conditional Variational Auto-Encoder"
<p>These are supporting datasets for the paper titled, "<strong>Reconstructing Global High Quality 3–day Surface Soil Moisture from ESA CCI and SMAP product during 2015–2021 using Conditional Variational Auto-Encoder</strong>"</p>
Dataset for "Responses of Soil Greenhouse Gas Fluxes to Land Management in Forests and Grasslands : A Global Meta-analysis"
<p>This dataset archives the original data for the study "Responses of Soil Greenhouse Gases Fluxes to Land Management in Forests and Grasslands: A Global Meta-analysis".</p>
Datasets for crop, soil properties and soil greenhouse gas emissions from an intercropping experiment with broccoli and fava bean
<p>Datasets with all properties measured during three crop cycles of an experiment developed to assess the efficiency of intercropping between broccoli and fava bean to enhance crop productivity, soil health and carbon sequestration and storage and reduce soil greenhouse gas emissions and the use of external inputs. </p> <p>We compared a broccoli monocrop (<em>Brassica oleracea var. italica</em> Plenck), a fava bean monocrop (<em>Vicia faba</em> L.) and different broccoli-fava bean intercropping systems in three winter crop cycles: 2018/2019, 2019/2020 and 2020/2021. The intercropping systems were: i) mixed intercropping (alternation within the same row of broccoli and fava bean plants), row intercropping 1:1 (combination of alternate rows of broccoli - fava bean) and row intercropping 2:1 (combination of two rows of the broccoli crop and one row of fava bean).</p>
Dataset of manuscript "Divergent responses of soil bacterial and fungal communities to climate warming in an alpine tundra ecosystem"
<p>Our study conducts a translocation experiment in the alpine tundra of the Changbai Mountains to explore how climate warming will affect soil bacterial and fungal communities in the alpine tundra and what are the underlying ecological mechanisms for their potential community changes. Soil samples (n = 24) were respectively collected during the early growing season (June 5, EGS), peak growing season (July 30, PGS), and late growing season (September 20, LGS) of 2021. The uploaded data contains the soil properties and OTU abundance measurements for these soil samples, as well as air and soil temperature from June 1, 2020 to September 15, 2021. </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)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
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.