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2,078 results for “soil data”
Data from: Allocation and functional traits of trees and saplings of Bornean tree species growing under contrasting soil nutrient availabilities
<p>The files hold the data of allocation and traits of adult trees ((i) the relationship between tree height and diameter at breast height, (ii) nutrient concentration in green leaves, senescent leaves, wood, and (iii) wood density) and saplings ((i) biomass allocation to leaves, stem, coarse roots, and fine roots, (ii) nutrient concentration in levees, senescent leaves, stem, and roots, and (iii) leaf mass per area) in Bornean tropical tree species growing under contrasting soil nutrient availabilities.</p> <p>Study site includes the Tawau Hills Park (4°27′N, 117°56′E, ca. 300 m asl), the Deramakot Forest Reserve (5°22′N, 117°25′E, ca. 250 m asl), and Nabawan (5°05′N, 116°29′E, ca. 500 m asl), Sabah, Malaysia. Vegetation of Tawau and Deramakot is a mixed dipterocarp forest, whereas that of Nabawan is a tropical heath forest. These sites considerably differ in soil characteristics. The forests in the Tawau Hills Park lie on the andesitic volcanic ash derived from the past eruptions ca. 27000 years ago by Mt. Magdalena, Mt. Lucia, and Mt. Maria. On the other hand, soils in the Deramakot Forest Reserve are derived from tertiary sedimentary rocks. Soils of Nabawan are classified as white sand podosol.</p>
Data from: More diverse rhizobial communities can lead to higher symbiotic nitrogen fixation rates, even in nitrogen-rich soils
<p>Symbiotic nitrogen fixation (SNF) by legumes and their rhizobial partners is one of the most important sources of bioavailable nitrogen to terrestrial ecosystems. While most work on the regulation of SNF has focused on abiotic drivers such as light, water, and soil nutrients, the diversity of rhizobia with which an individual legume partners may play an important but under-recognized role in regulating nitrogen inputs from SNF. By experimentally manipulating the diversity of rhizobia available to legumes, we demonstrate that rhizobial diversity can increase average SNF rates by more than 90%, and that high rhizobial diversity can induce increased SNF even under conditions of high soil N fertilization. However, the effects of rhizobial diversity, the conditions under which diversity effects were strongest, and the likely mechanisms driving these diversity effects differed between the two legume species we assessed. These results provide evidence that biodiversity-ecosystem function relationships can occur at scales of an individual plant, and that the effects of rhizobial diversity may be as important as long-established abiotic factors, such as nitrogen availability, in driving terrestrial nitrogen inputs via SNF.</p>
Congo Basin forest soil CO2, CH4 and N2O flux data.
<p><span>Tropical forests play an important role in the greenhouse gas exchange between biosphere and atmosphere. Despite holding the second largest tropical forest globally, the Congo basin is generally understudied and ground based greenhouse gas flux data are lacking. In this study, high frequency measurements spanning of sixteen months from automated and manual soil chambers are combined, to characterize spatio-temporal variability in soil greenhouse gas fluxes from a lowland tropical forest in Yangambi, in the Congo Basin. </span></p>
Fiber-optic seismic sensing of vadose zone soil moisture dynamics data sets
<p>CC_daily.h5: Daily cross-correlation functions for common-offset DAS channels.</p> <p>RCC_dv_v_full.csv: Summary of all the measured dv/v from the ballistic surface waves in daily cross-correlation functions.</p>
Data from: Canopy cover and soil moisture influence forest understory plant responses to experimental summer drought
<p>Extreme droughts are globally increasing in frequency and severity. Most research on drought in forests focuses on the response of trees, while less is known about the impacts of drought on forest understory species and how these effects are moderated by the local environment.</p> <p>We assessed the impacts of a 45-day experimental summer drought on the performance of six boreal forest understory plants, using a transplant experiment with rainout shelters replicated across 25 sites. We recorded growth, vitality and reproduction immediately, two months, and one year after the simulated drought, and examined how differences in ambient soil moisture and canopy cover among sites influenced the effects of drought on the performance of each species.</p> <p>Drought negatively affected the growth and/or vitality of all species, but the effects were stronger and more persistent in the bryophytes than in the vascular plants. The two species associated with older forests, the moss <em>Hylocomiastrum umbratum</em> and the orchid <em>Goodyera repens</em>, suffered larger effects than the more generalist species included in the experiment. The drought reduced reproductive output in the moss <em>Hylocomium splendens </em>in the next growing season, but increased reproduction in the graminoid <em>Luzula pilosa</em>. Higher ambient soil moisture reduced some negative effects of drought on vascular plants. Both denser canopy cover and higher soil moisture alleviated drought effects on bryophytes, likely through alleviating cellular damage.</p> <p>Our experiment shows that boreal understory species can be adversely affected by drought and that effects might be stronger for bryophytes and species associated with older forests. Our results indicate that the effects of drought can vary over small spatial scales and that forest landscapes can be actively managed to alleviate drought effects on boreal forest biodiversity. For example, by managing the tree canopy and protecting hydrological networks.</p>
Data from: Spatial variation of soil CO2, CH4 and N2O fluxes across topographical positions in tropical forests of the Guiana Shield in Ecosystems
<p>Data from: Spatial variation of soil CO2, CH4 and N2O fluxes across topographical positions in tropical forests of the Guiana Shield in Ecosystems</p>
Forest soil temperature data
<b>Description: </b><p>Microclimate datalogger recordings of belowground temperature</p><p><b>Project: </b>This dataset was collected as part of the following SAFE research project: <a href="https://www.safeproject.net/projects/project_view/111"><b>Microclimate stratification in modified forests</b></a></p><p><b>XML metadata: </b>GEMINI compliant metadata for this dataset is available <a href="https://www.safeproject.net/datasets/xml_metadata?id=89">here</a></p><p><b>Data worksheets: </b>There are 1 data worksheets in this dataset:</p><ol><li><p><b>Forest soil temperature data</b> (Worksheet Data)</p><p>Dimensions: 411690 rows by 6 columns</p><p>Description: Microclimate datalogger recordings of belowground temperature</p><p>Fields: </p><ul><li><b>Plot</b>: Location of record (Field type: Location)</li><li><b>time</b>: Date and time of record (Field type: Datetime)</li><li><b>Temp</b>: Air temperature 1 m above ground (Field type: Numeric)</li><li><b>LoggerType</b>: Make of datalogger that was used (Lascar or iButton) (Field type: ID)</li><li><b>LoggerID</b>: Unique reference number for the datalogger (Field type: ID)</li></ul><br></li></ol><p><b>Date range: </b>2011-04-20 to 2012-07-10</p><p><b>Latitudinal extent: </b>4.6353 to 4.7714</p><p><b>Longitudinal extent: </b>116.9477 to 117.7028</p>
Soil moisture maps of Ukraine based on SMAP satellite data, vegetation season 2018
<p>A set of soil moisture maps of Ukraine based on SMAP satellite data</p> <p>Product: SMAP Enhanced L3 Radiometer Global Daily 9 km EASE-Grid Soil Moisture V001</p> <p>Vegetation season 2018</p> <p> </p>
Geophysical data from: "A review of geophysical methods for soil structure characterization"
<p>The geophysical data presented herein was collected in the Soil Structure Observatory (see, Keller et. al. 2017) and were used to create Figures 4b, 5a, 5b, 9a and 9b for the manuscript entitled: "A review of geophysical methods for soil structure characterization" submitted to reviews of geophysics. The data set includes:<br> <br> GPR data collected from South to North in the bare soil of block C before and after compaction<br> GPR_800Mhz_BSbeforecompaction.DZW<br> GPR_800Mhz_BSbeforecompaction.DZT<br> GPR_800Mhz_BSaftercompaction.DZW<br> GPR_800Mhz_BSaftercompaction.DZT<br> <br> ERT data collected from South to North in the bare soil of block B before and after compaction<br> ERT_B2_14-03beforecompaction.bin<br> ERT_B2_14-04aftercompaction.bin<br> <br> Time-lapse ERT data collected in block A in September of 2017:<br> timelapseERT2017.zip<br> The date and time in the files names indicate the time in which the resistivimeter started collecting data plus two hours.<br> e.g. for 2017-09-11-18-01-41.bin, the first data point was collected at 14:01 on the 11th of September of 2017.<br> The first 464 data points correspond to bare soil collected from North to South<br> The following 464 data points correspond to grassy soil from South to North<br> <br> Meteorological data from 2017<br> meteodata_Reckenholz2017.xls<br> <br> Time domain reflectometry data from September of 2017 for block A (10, 20, 40 and 70cm depth). Two land covers (bare soil and grassy soil) and two compaction treatments (full compacted and non compacted) are included.<br> TDR_A1_Sept2017.xlsx</p> <p> </p> <p>Keller, T., Colombi, T., Ruiz, S., Manalili, M. P., Rek, J., Stadelmann, V., ... & Schymanski, S. (2017). Long-Term Soil Structure Observatory for Monitoring Post-Compaction Evolution of Soil Structure. <em>Vadose Zone Journal</em>, <em>16</em>(4).</p>
On-farm study reveals positive relationship between gas transport capacity and organic carbon content in arable soil (Data set)
<p>Data used for "On-farm study reveals positive relationship between gas transport capacity and organic carbon content in arable soil" by Colombi T, Walder F, Büchi L, Sommer M, Liu K, Six J, van der Heijden M, Charles R and Keller T. (2019). SOIL. 5, 91-105, https://doi.org/10.5194/soil-5-91-2019.</p> <p>.txt file "MetaInformation_On-farm study reveals positive relationship between gas transport capacity and organic carbon content in arable soil" contains all necessary meta-information </p>
Raw data of diversity, abundance and soil samples
<p>Raw data of diversity, abundance and soil samples of the paper: Secondary Succession under invasive species (<em>Pteridium aquilinum</em>) conditions in a seasonal dry tropical forest in southeastern Mexico</p>
Input data for soil erosion practical
<p>This dataset is to be used for the soil erosion practical published at: https://github.com/wieka29/Soil-erosion-practical</p> <p> </p>
Data for: Soil domestication by rice cultivation results in plant-soil feedback through shifts in soil microbiota
<p>This repository contains the data for the manuscript entitled "Soil domestication by rice cultivation results in plant-soil feedback through shifts in soil microbiota." Analysis scripts can be found at <a href="https://github.com/bulksoil/SoilDomestication">https://github.com/bulksoil/SoilDomestication</a></p>
Data for Cloud resolving WRF simulations of precipitation and soil moisture over the central Tibetan Plateau: an assessment of various physics options
<p>This dataset accompanies the submitted paper in the Earth and Space Science:Cloud resolving WRF simulations of precipitation and soil moisture over the central Tibetan Plateau: an assessment of various physics options.</p>
The data for the article entitled "Soil carbon release responses to long-term versus short-term climatic warming in an arid ecosystem"
<p>The data for the article entitled "Soil carbon release responses to long-term versus short-term climatic warming in an arid ecosystem" Yu et al. </p>
Earth Microbiome Project and Global Soil Mycobiome Data Subsets
<p>These are subsets of the publicly available Earth Microbiome Project (<a href="https://earthmicrobiome.org/">https://earthmicrobiome.org/</a>, <a href="../records/890000">https://zenodo.org/records/890000</a>) [1] and Global Soil Mycobiome project datasets (<a href="https://doi.org/10.15156/BIO/2263453"><span>https://doi.org/10.15156/BIO/2263453</span></a>) [2,3], provided for benchmarking and testing purposes. These are re-released with attribution under a CC-BY-4.0 license, following the license of the original source creators. If you use this resource, please cite the original references as given below:</p> <p>1. Thompson, L. R., <em>et al.</em> (2017). A communal catalogue reveals Earth’s multiscale microbial diversity. <em>Nature</em>, 551:457-463. <a href="http://doi.org/10.1038/nature24621" target="_blank" rel="noopener noreferrer">doi:10.1038/nature24621</a>.</p> <p>2. Tedersoo, L., <em>et al.</em> The Global Soil Mycobiome consortium dataset for boosting fungal diversity research. <em>Fungal Diversity</em> <strong>111</strong>, 573–588 (2021). https://doi.org/10.1007/s13225-021-00493-7</p> <p>3. Tedersoo, L. (2021): The Global Soil Mycobiome consortium dataset for boosting fungal diversity research v2. University of Tartu. 10.15156/BIO/2263453</p>
Metal(loid)s in urban soil from historical municipal solid waste landfill: Geochemistry, source apportionment, bioaccessibility testing and human health risks - Supplementary data
<p>This is a supplementary dataset to the paper:</p> <p>Hiller E., Faragó T., Kolesár M., Filová L., Mihaljevič M., Jurovič L., Demko R., Mchlica A., Štefánek J., Vítková M. (2024): Metal(loid)s in urban soil from historical municipal solid waste landfill: Geochemistry, source apportionment, bioaccessibility and human health risks. <em>Chemosphere</em> <strong>362</strong>, 142677. DOI: 10.1016/j.chemosphere.2024.142677</p> <p>This research was supported by the Johannes Amos Comenius Programme (OP JAC), project No. CZ.02.01.01/00/22_008/0004605, Natural and anthropogenic georisks. The dataset is published under the Creative Commons Attribution 4.0 International License (CC-BY-4.0). This license allows others to distribute, remix, adapt, and build upon the dataset for any purpose, even commercially, as long as they give appropriate credit to the original creator(s).</p>
Wetland sediment soil organic carbon sequestration data to support radiometric technique comparisons
<p>This workbook shows the ID, the geographical location, the year of sampling, and sediment core information in samples collected from undisturbed wetlands situated across four provinces of Canada (Alberta, Saskatchewan, Manitoba, and Ontario) from 2016 to 2019.</p>
Data for: Synergistic mechanisms of plant phosphorus (P) resorption and microbial P-limitation affecting soil P during grassland vegetation succession
<p>Data for: <strong>Synergistic mechanisms of plant phosphorus (P) resorption and microbial P-limitation affecting soil P during grassland vegetation succession</strong></p>
Data-driven Soil Moisture Sensing with mmWave Radar In Environment 1
<p>This is a millimeter-wave radar soil moisture dataset, which includes soil samples with 20 different moisture levels, ranging from 6.20% to 43.82% with approximately 2% intervals. In the bin file names, the first number after "data" represents the soil moisture level, labeled as 1 to 20, with moisture levels of 6.20%, 8.30%, 10.80%, 12.60%, 14.44%, 16.14%, 18.96%, 19.70%, 23.34%, 25.24%, 26.24%, 28.90%, 31.10%, 32.46%, 33.80%, 36.44%, 38.20%, 40.56%, 42.68%, and 43.82%, respectively.In the bin file names, the second number after "data" represents the height of the radar development board above the soil surface, measured in centimeters, specifically 16 cm, 20 cm, and 24 cm. The data was collected using the IWR1843 radar board, with 1 transmitting antenna and 4 receiving antennas. Each bin file contains 128 radar frames, with each frame consisting of 32 chirps, and each chirp containing 384 sampling points.</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)
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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.