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133 results for “Soil sampling”

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edi40/100

Soil nitrogen and carbon from organic and mineral soil of 32 mature black spruce sites across interior Alaska (Sampled 2001)

Soil nitrogen and carbon was collected at 33 sites as part of a bigger study looking at the structure and function of black spruce stands in interior Alaska. These variables can be compared to any of the environmental site descriptions, GPS coordinates, soil characteristics, physical site characteristics, stand and structural characteristics, active layer, collected in the summers of 2000, 2001 for these sites

openOpenDec 2007View details →
edi40/100

Spatial patterns of understory vegetation and soil in an Alaskan upland boreal forest fire chronosequence. Three sites located in Delta Junction Alaska. Soil sampled during summer 2007

In this study we used geostatistics to characterize the spatial heterogeneity of soil carbon and nitrogen pools, microbial respiration, microbial biomass, nitrogen mineralization, soil moisture, soil pH, depth of organic horizon and forest floor covers and understory vegetation abundances in three sites (1999, 1987 and 1920 wildfires) of a boreal forest chronosequence of Interior Alaska (near Delta Junction). Soil sampling and vegetation measurements occured during summer 2007.

openOpenApr 2010View details →
edi40/100

Eight Mile Lake Research Watershed, Thaw Gradient: Geochemistry of soil pore waters sampled in May 2018 (0 - 20 cm depth) and August 2019 (0-120 cm depth) at Gradient site, 2018-2019

In this larger study, we are asking the question: Is old carbon that comprises the bulk of the soil organic matter pool released in response to thawing of permafrost? We are answering this question by using a combination of field and laboratory experiments to measure radiocarbon isotope ratios in soil organic matter, soil respiration, and dissolved organic carbon, in tundra ecosystems. The objective of these proposed measurements is to develop a mechanistic understanding of the SOM sources contributing to C losses following permafrost thawing. We are making these measurements at an established tundra field site near Healy, Alaska in the foothills of the Alaska Range. Field measurements center on a natural experiment where permafrost has been observed to warm and thaw over the past several decades. This area represents a gradient of sites each with a different degree of change due to permafrost thawing. As such, this area is unique for addressing questions at the time and spatial scales relevant for change in arctic ecosystems. Analysing the geochemistry of soil pore waters at Gradient site complements the overarching aim of this study. The dissolved organic carbon and mineral elements are determined in soil pore waters from sites of minimum, moderate and extensive permafrost degradation during the spring thaw (0-20 cm depth) in May 2018 and during late summer (0-120 cm depth) in August 2019. Soil pore waters were collected from sites approximately 15 m uphill of the highly monitored Gradient sites. The geochemical data was used to assess the mineral element-organic carbon associations in soil pore waters between contrasting sites of permafrost degradation.

openOpenJun 2021View details →
zenodo36/100

Hearth Soil Sample, 150,000-40,000 BCE

Upper Mousterian (ca. 150,000-40,000 BCE) Flint, bone, and soil Europe; France; St. Leon 5.5 x 3 in. MH 2016.16.664 View this object on the Database: http://museums.fivecolleges.edu/detail.php?museum=all&t=objects&type=all&f=&s=mh+2016+16+664&record=0 Photographs and photogrammetry by Laura Shea (Digital Collections Coordinator and Museum Photographer), Mount Holyoke College Art Museum; Copyright info: Contact the Mount Holyoke College Art Museum South Hadley, Massachusetts, USA 01075 413-538-2245 http://www.mtholyoke.edu/artmuseum/ The Mount Holyoke College Art Museum is dedicated to teaching and learning; therefore, we value your feedback and welcome any scholarly observations. Please feel free to contact us if you would like to learn more about the objects you see here or to request 3D models of other objects in our collections. Description: Specimen of hearth site - to show how the material lies when dug. Contains tools and/or flakes, ash, charcoal, bone - from Saint Leon dig in France. Source: Objaverse 1.0 / Sketchfab

opencc-byDec 2019View details →
dryad36/100

Highly-replicated soil, topography and vegetation sampling across an old-growth tropical rain forest landscape

<p class="MsoNormal">Here we present data from highly-replicated sampling of soil, topography, and vegetation across an old-growth tropical rainforest landscape at the La Selva Biological Station, Costa Rica.  Samples were taken at 100 x 50 m spacing using an existing surveyed grid system.  The 573-ha sample area spanned a variety of soil, topographic and vegetation conditions, including flat terraces on old alluvial soil, ridge tops and steep slopes on residual soil, riparian habitats and fresh-water swamps.  At each of 1170 grid points we established a circular 0.01 ha quadrat (radius = 5.64 m).  We sampled soil at 30-50 cm depth with a soil augur and collected a sample for subsequent analysis.  We measured slope angle with a clinometer and slope direction with a compass.  We measured stem diameter to <u>+</u>1 mm with a synthetic fabric diameter tape for all stems <u>&gt;</u>10 cm diameter (N= 5236) at 1.3 m from the ground or to ~ 6 m height if there were basal irregularities.  We classified stems to life form (tree, palm, liana), and identified all trees and palms to species or morphospecies (N=266; lianas were not identified to species).  We collected vouchers from all trees that we could not positively identify in the field (N=920).</p> <p class="MsoNormal">As a whole the data set presents an integrated view of soil, topography and vegetation across a mesoscale old-growth tropical rain forest landscape.  The data have been used to refine a reserve-wide soils map for La Selva, and for a variety of papers analyzing the interactions of soil, topography and species distributions at landscape scales (see the 10 papers listed in the Related Works section below).</p> <p class="MsoNormal">There are no restrictions at all on the use of these data, and we think they will be useful for teaching and analysis projects as well as further original research applications.  The data also provide a detailed benchmark of the status of old-growth vegetation in 1993-95 for one of the most intensively studied tropical rain forest landscapes in the world.  Because the data are accurately georeferenced and detailed metadata on all methods are provided, this study could be repeated at any time to assess the trajectory of vegetation changes at La Selva, particularly in relation to local disturbances and changing regional and global climates.   </p>

opencc-zeroJun 2022View details →
zenodo36/100

Fig. 2 in Scale Insect (Hemiptera, Coccomorpha) Survey Of Soil Samples From Southern Asia With Description Of Two New Species Of Rhizoecidae

Fig. 2. Ripersiella danyii Kaydan et Konczné Benedicty sp. n. adult female, holotype

opencc-by-4.0Jul 2017View details →
zenodo36/100

Fig. 1 in Scale Insect (Hemiptera, Coccomorpha) Survey Of Soil Samples From Southern Asia With Description Of Two New Species Of Rhizoecidae

Fig. 1. Rhizoecus muranyii Kaydan sp. n. adult female, holotype

opencc-by-4.0Jul 2017View details →
zenodo36/100

Raw data of diversity, abundance and soil samples

<p>Raw data of diversity, abundance and soil samples of the paper:&nbsp;Secondary Succession under invasive species (<em>Pteridium aquilinum</em>) conditions in a seasonal dry tropical forest in southeastern Mexico</p>

opencc-by-4.0Apr 2019View details →
zenodo36/100

Measured properties in soil samples and marine sediment collected in Galion Bay (Martinique, France) in order to trace erosion sources in insular tropical catchments

<p>This dataset was compiled in order to select the optimal suite of tracers and identify and quantify the main sources of sediment deposited in Galion Bay and associated chlordecone transfers since the 1960s. It includes measured properties for potential sources collected across the Galion catchment (Martinique, France) and along a sediment core sampled in Galion Bay (GAL17-04, N°IGSN TOAE0000000573). Associated with this dataset, metadata are integrated for sources and targets registered using International Geological Sample Numbers (IGSN).</p>

opencc-by-4.0Nov 2023View details →
zenodo36/100

Delta-15N values for leaf and soil samples from a mesocosm experiment looking at dung beetle presence and the movement of dung-derived nitrogen (DDN)

<b>Description: </b><p>We deployed 18 mesocosms into each of the ecosystem types (logged forest and oil palm) in mid-May 2016, to give the soil one month to recover from the disturbance. We constructed mesocosms from black plastic containers, 40 cm diameter and 25 cm high after removing the base. We dug mesocosms 20 cm into the ground leaving 5cm above the surface. We arranged them in a 6 x 3 grid with a minimum of 3 m between each mesocosm to minimise interaction between the soil nutrient cycling in each mesocosm. As proximity of the seedlings to mature trees may increase competition for nitrogen and other nutrients we recorded the distance of each mesocosm to the nearest mature tree (any species with diameter at breast height &gt; 30 cm) for inclusion in our analyses. <br>We randomly selected 12 of the mesocosms, to receive 15N-labelled dung patties weighing 300 ± SD 2.27 g in logged forest and 410 ± SD 2.04 g in oil palm. We populated six randomly selected mesocoms from within those 12 treated with dung with a standardised dung beetle communities (Fig. 1, Table S2). The remaining six mesocosms were left as soil only controls. We covered each mesocosm with a fine nylon mesh secured with a rubber belt to prevent beetles leaving or colonising the mesocosms, and to standardise any microclimatic effects between treatments. However, after 48 hours we opened the dung beetle treatments for a 24 hours period to allow the beetles to emigrate rather than forcing them to artificially stay in the same pat (cf. Roslin 2000; Slade et al. 2017), and then re-covered the mesocosms with netting.<br>We sampled soil seven times from logged forest over the course of the experiment. Any remaining surface dung was removed prior to soil sampling, and replaced thereafter, in order to reduce the possibility of contamination. If a soil core was unsuccessful (most likely due to beetle channels) a second core was taken directly beside. On each sample day, a core of 10cm depth was taken and split into vertical horizons 0- 2cm, 2-5 cm and 5-10cm. <br>We sampled leaves eight times over the eight-month duration of the experiment, with high frequency during the first month, aimed to capture the initial assimilation of DDN into the plants. We collected one leaf from the Dipterocarpaceae or palm seedlings for each sample event. For dipterocarp seedlings we alternated collection of the terminal leaf from top and bottom (leaving the topmost, newest leaf) between consecutive sample days, and for palm seedlings we sampled the two penultimate leaflets from alternating sides of the mid-stem, from the youngest fully formed frond. As assimilated 15N did not plateau in logged forest during the 8-month timeframe of the experiment, we took a sample after 21 months in order to determine whether all DDN had been turned over in the plant biomass after this time.<br>The leaf and soil samples were dried at 60°C for a minimum of 48 hours. We then ground samples to a fine powder using a ball mill (Retsch UK Ltd., Hope, UK). We weighed ground samples into 6 x 4 mm ultraclean tin capsules (Elemental Microanalysis Ltd., Okehampton, UK) using an ultra-microbalance with readability 1 μg (Mettler-Toledo, Greifensee, Switzerland) to provide sufficient elemental carbon and nitrogen for analysis by continuous flow isotope ratio mass spectrometry (SERCON, Crewe, UK). <br>Isotope ratios are expressed in per mil (‰) relative to international reference standards (Rstandard), which are Atmospheric Nitrogen and Vienna PeeDee Belemnite (VPDB) for nitrogen and carbon, respectively. The delta value describes the isotopic composition of each sample, which signifies a measurement of difference relative to laboratory standards. The calculation of δ values is given by: <br>δHX = [(RSAMPLE /RSTANDARD −1)]*1000</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/11"><b>Using stable isotopes to link biogeochemical processes to biodiversity of conservation concern</b></a></p><p><b>Funding: </b>These data were collected as part of research funded by: </p><ul><li>NERC (Research grant, NE/K016148/1)</li></ul><p>This dataset is released under the CC-BY 4.0 licence, requiring that you cite the dataset in any outputs, but has the additional condition that you acknowledge the contribution of these funders in any outputs.</p><p></p><p><b>Permits: </b>These data were collected under permit from the following authorities:</p><ul><li>Sabah Biodiversity Centre (SABC) (Research licence JKM/MBS.1000-2/2 (374) )</li><li>Sabah Biodiversity Centre (SABC) (Research licence JKM/MBS.1000-2/2 JLD.4 (41))</li><li>Sabah Biodiversity Centre (SABC) (Research licence JKM.1000-2/2 JLD.5 (153))</li></ul><p></p><p><b>XML metadata: </b>GEMINI compliant metadata for this dataset is available <a href="https://www.safeproject.net/datasets/xml_metadata?id=5113431">here</a></p><p><b>Files: </b>This consists of 1 file: 3_Kemp_15N_mesocosms_data.xlsx</p><p><b>3_Kemp_15N_mesocosms_data.xlsx</b></p><p>This file contains dataset metadata and 3 data tables:</p><ol><li><p><b>OP leaf</b> (described in worksheet OP_leaf)</p><p>Description: Details the δ15N of leaves sampled in oil palm from palm seedlings across eight sample days up to day 233. </p><p>Number of fields: 13</p><p>Number of data rows: 144</p><p>Fields: </p><ul><li><b>Name</b>: Code for date (ddmm), mesocosms ID and depth (00 = surface; 02 = 2 cm belowground; 05 = 5 cm belowground, and 10 = 10 cm belowground) (Field type: id)</li><li><b>Day</b>: Experimental day as the number of days since day zero (defined by the planting of the seedlings, either dipterocarps or palms) (Field type: id)</li><li><b>Day2</b>: Experimental day as a factor (Field type: id)</li><li><b>Mesocosm</b>: Unique identifier for each of the 18 mesocosms (Field type: id)</li><li><b>Treatment</b>: Treatment assignment (Field type: categorical)</li><li><b>DistMature</b>: Distance from the nearest mature tree (any species with diameter at breast height &gt; 30 cm). (Field type: numeric)</li><li><b>Weight</b>: Sample weight (Field type: numeric)</li><li><b>Beam.Area.N</b>: Measure of the nitrogen peak i.e. calculated as the area under the nitrogen curve by Calisto software. This value is directly related to N_weight. (Field type: numeric)</li><li><b>ugN</b>: Measure of the elemental nitrogen content of the sample (Field type: numeric)</li><li><b>d15N</b>: the delta value of the sample, which describes the ration of 15N: 14N isotopes (Field type: numeric)</li><li><b>Beam.Area.C</b>: Measure of the carbon peak i.e. calculated as the area under the carbon curve by Calisto software. This value is directly related to C_weight (Field type: numeric)</li><li><b>ugC</b>: Measure of the elemental carbon content of the sample (Field type: numeric)</li><li><b>d13C</b>: the delta value of the sample, which describes the ration of 13C: 12C isotopes (Field type: numeric)</li></ul></li><li><p><b>LFE leaf</b> (described in worksheet LFE_leaf)</p><p>Description: Details the δ15N of leaves sampled in logged forest, taken from dipterocarp seedlings across nine sample days, up to day 625.</p><p>Number of fields: 13</p><p>Number of data rows: 147</p><p>Fields: </p><ul><li><b>Name</b>: Code for date (ddmm), mesocosms ID and depth (00 = surface; 02 = 2 cm belowground; 05 = 5 cm belowground, and 10 = 10 cm belowground) (Field type: id)</li><li><b>Day</b>: Experimental day as the number of days since day zero (defined by the planting of the seedlings, either dipterocarps or palms) (Field type: id)</li><li><b>Day2</b>: Experimental day as a factor (Field type: id)</li><li><b>Mesocosm</b>: Unique identifier for each of the 18 mesocosms (Field type: id)</li><li><b>Treatment</b>: Treatment assignment (Field type: categorical)</li><li><b>DistMature</b>: Distance from the nearest mature tree (any species with diameter at breast height &gt; 30 cm). (Field type: numeric)</li><li><b>Weight</b>: Sample weight (Field type: numeric)</li><li><b>Beam.Area.N</b>: Measure of the nitrogen peak i.e. calculated as the area under the nitrogen curve by Calisto software. This value is directly related to N_weight. (Field type: numeric)</li><li><b>ugN</b>: Measure of the elemental nitrogen content of the sample (Field type: numeric)</li><li><b>d15N</b>: the delta value of the sample, which describes the ration of 15N: 14N isotopes (Field type: numeric)</li><li><b>Beam.Area.C</b>: Measure of the carbon peak i.e. calculated as the area under the carbon curve by Calisto software. This value is directly related to C_weight (Field type: numeric)</li><li><b>ugC</b>: Measure of the elemental carbon content of the sample (Field type: numeric)</li><li><b>d13C</b>: the delta value of the sample, which describes the ration of 13C: 12C isotopes (Field type: numeric)</li></ul></li><li><p><b>LFE soil</b> (described in worksheet LFE_soil)</p><p>Description: Details the δ15N of soil sampled in logged forest across seven sample days up to day 64</p><p>Number of fields: 14</p><p>Number of data rows: 375</p><p>Fields: </p><ul><li><b>Name</b>: Code for date (ddmm), mesocosms ID and depth (00 = surface; 02 = 2 cm belowground; 05 = 5 cm belowground, and 10 = 10 cm belowground) (Field type: id)</li><li><b>Day</b>: Experimental day as the number of days since day zero (defined by the planting of the seedlings, either dipterocarps or palms) (Field type: id)</li><li><b>day2</b>: Experimental day as a factor (Field type: id)</li><li><b>Mesocosm</b>: Unique identifier for each of the 18 mesocosms (Field type: id)</li><li><b>Treatment</b>: Treatment assignment (Field type: categorical)</li><li><b>DistMature</b>: Distance from the nearest mature tree (any species with diameter at breast height &gt; 30 cm). (Field type: numeric)</li><li><b>Depth</b>: The depth which the soil sample was taken from, i.e. 0002 is the horizon between the ground surface and 2 cm belowground (Field type: numeric)</li><li><b>Weight</b>: Sample weight (Field type: numeric)</li><li><b>Beam.Area.N</b>: Measure of the nitrogen peak i.e. calculated as the area under the nitrogen curve by Calisto software. This value is directly related to N_weight. (Field type: numeric)</li><li><b>ugN</b>: Measure of the elemental nitrogen content of the sample (Field type: numeric)</li><li><b>d15N</b>: the delta value of the sample, which describes the ration of 15N: 14N isotopes (Field type: numeric)</li><li><b>Beam.Area.C</b>: Measure of the carbon peak i.e. calculated as the area under the carbon curve by Calisto software. This value is directly related to C_weight (Field type: numeric)</li><li><b>ugC</b>: Measure of the elemental carbon content of the sample (Field type: numeric)</li><li><b>d13C</b>: the delta value of the sample, which describes the ration of 13C: 12C isotopes (Field type: numeric)</li></ul></li></ol><p><b>Date range: </b>2016-05-01 to 2017-02-01</p><p><b>Latitudinal extent: </b>4.5000 to 5.0700</p><p><b>Longitudinal extent: </b>116.7500 to 117.8200</p>

opencc-by-4.0Dec 2020View details →
zenodo36/100

Sample microscopic images of soil microorganism

<p>The images within this repository contains raw, unprocessed, microscopic images of soil fungi belonging to the following genera: Fusarium, Trichoderma, Verticillium, and Chromista of the Phytophthora genus that filenames contain name of the genus followed by underscore and number of an image for a given genera. Each image is labeled based on the specific microorganism genus it represents. The subimages&nbsp;images contains retrieved subimages, where each subimage corresponds to a single object that contains fragments of a microorganism. The subimages are generated from the original images and follow a specific naming convention. The image name indicates the microorganism genus, followed by information about the input image it was generated from, and finally the number of the retrieved subimage from that input image.</p> <p>These subimages are utilized for training purposes using the Transfer Learning method with the CNN model called ResNet50.</p> <p>This repository is provided as a Supplementary Material to the article &quot;Automated Identification of Soil Fungi and Chromista&nbsp;through Convolutional Neural Networks&quot; submitted to the&nbsp;<a href="https://www.sciencedirect.com/journal/engineering-applications-of-artificial-intelligence">Engineering Applications of Artificial Intelligence</a>&nbsp;journal.</p>

opencc-by-4.0May 2023View details →
zenodo36/100

Animating soils: analysed samples

<p>In the dissertation Animating soils:&nbsp;geoarchaeological approaches to past human-environment relationships in the Arctic, five sites in northern Scandinavia was analysed with geoarchaeological methods. This dataset contain sample information and results. Sample coordinates from&nbsp;Brodtkorbneset, Steintj&oslash;rna and Hobergstr&auml;sk have been measured with a totalstation in custom coordinate systems. The analytical parameters include soil organic matter, inorganic and total phosphate analysis, magnetic susceptiblity before and after ignition.&nbsp;</p>

opencc-by-4.0Jun 2023View details →
dryad36/100

Data for: Soil organic carbon contents of collected soil samples from China's black soil region

<p><span>The long-term use of cropland and cropland reclamation from natural ecosystems led to soil degradation. This study investigated the effect of the long-term use of cropland and cropland reclamation from natural ecosystems on soil organic carbon (SOC) content and density over the past 35 years. Altogether, 2140 topsoil samples (0</span>–<span>20 cm) were collected across Northeast China. Landsat images were acquired from 1985 to 2020 through Google Earth Engine, and the reflectance of each soil sample was extracted from the Landsat image that its time was consistent with sampling. The hybrid model that included two individual SOC prediction models for two clustering regions was built for accurate estimation after k-means clustering. The probability hybrid model, a combination between the hybrid model and classification probabilities of pixels, was introduced to enhance the accuracy of SOC mapping. Cropland reclamation results were extracted from the land cover time series dataset at a 5-year interval. Our study indicated that: (1) Long-term use of cropland led to a 3.07 g kg<sup>-1</sup> and 6.71 Mg C ha<sup>-1</sup> decrease in SOC content and density, respectively, and the decrease of SOC stock was 0.32 Pg over the past 35 years; (2) Nearly 64% of cropland had a negative change in terms of SOC content from 1985 to 2020; (3) Cropland reclamation track changed from high to low SOC content, and almost no cropland was reclaimed on the 'Black soils' after 2005; (4) Cropland reclamation from wetlands resulted in the highest decrease, and reclamation period of years 31</span>–<span>35 decreased when SOC density and SOC stock were 16.05 Mg C ha<sup>-1</sup> and 0.005 Pg, respectively, while reclamation period of years 26</span>–<span>30 from forest witnessed SOC density and stock decreases of 8.33 Mg C ha<sup>-1</sup> and 0.01 Pg, respectively. Our research results provide a reference for SOC change in the black soil region of Northeast China and can attract more attention to the area of the protection of 'Black soils' and natural ecosystems.</span></p>

opencc-zeroJun 2023View details →
dryad36/100

Data for: Soil organic carbon contents of collected soil samples from China's black soil region

Open the record for dataset details and reuse information.

publicJun 2023View details →
dryad36/100

Data from: The importance of accounting method and sampling depth to estimate changes in soil carbon stocks

Open the record for dataset details and reuse information.

publicAug 2024View details →
dryad36/100

Data from: The deep-soil sampling in Chile revealed a new elateroid beetle lineage, Badmaateridae fam. nov. (Coleoptera)

Open the record for dataset details and reuse information.

publicNov 2025View details →
dryad36/100

Highly-replicated soil, topography and vegetation sampling across an old-growth tropical rain forest landscape

Open the record for dataset details and reuse information.

publicAug 2022View details →
edi36/100

GIS Shapefile - Soil, Sampling locations, Baltimore City

Soil_Samples_BACI Available only by request on a case by case basis. Contact rthe author, David Nowak, at dnowak@fs.fed.us Tags Biophysical Resources, Land, Social Institutions, Health, BES, Soil, Lead, Sample, UFORE Summary Samples were taken to relate soil data to vegetation data obtained for the Urban Forestry Effects Model (UFORE). Description The data is soil concentrations and characteristics of the following: land use, bulk density, sand, silt, clay, pH, organic matter, nitrogen, Al, P, S, Ti, Cr, Mn, Fe, Co, Ni, Cu Zn, Mo, Pb, Cd, Na, Mg, K, Ca, and V. Soils were sampled in 125 plots located within the City of Baltimore in the summer of 2000. The plots were randomly stratified by Anderson Land Cover Classification System Level II, which included commercial, industrial, institutional, transportation right-of-ways, high and medium density residential (there were no low density residential areas identified within the city boundaries), golf course, park, urban open, forest, and wetland land-use types. The number of plots situated in each land-use type was weighted to their proportion of spatial area within the City. The resultant number of plots sampled for soil by land-use type was: commercial (n = 2); industrial (n = 3); institutional (n = 10); transportation right-of-ways (n = 7); high density residential (n = 19); medium density residential (n = 33); golf course (n = 3); riparian (n=2); park (n = 10); urban open (n = 10); and forest (n = 26) land-use types, respectively. The distribution of plots represents the proportion of area covered by impervious surfaces. Credits Rich Pouyat, USDA Forest Service Use limitations Not for profit use only Extent West -76.711030 East -76.530612 North 39.371355 South 39.200686 Scale Range There is no scale range for this item. The data is soil concentrations and characteristics of the following: land use, bulk density, sand, silt, clay, pH, organic matter, nitrogen, Al, P, S, Ti, Cr, Mn, Fe, Co, Ni, Cu Zn, Mo, Pb, Cd, Na, Mg

openCustomDec 2009View details →
dryad32/100

Data from: Taxonomic survey of Agaricomycetes (Fungi: Basidiomycota) in Ontario tallgrass prairies determined by fruiting body and soil rDNA sampling

The fungal composition of North America's grasslands is poorly known, but an important area of study due to grassland conservation concerns and their close relation to agricultural lands. This study is a survey of Agaricomcyetes from fifteen diverse tallgrass prairies across southwestern Ontario, determined through fruiting body surveys (above-ground) and next-generation sequencing of soil ribosomal DNA (below-ground), and makes comparisons between the results of these two techniques. The most species rich taxa were the Clavariaceae, Hygrophoraceae, and Entolomataceae, each detected by both techniques, with the addition of the Sebacinaceae and Polyporaceae sensu lato below-ground, and Hymenogastraceae (Hebeloma spp.) and Mycenaceae above-ground. Many of the most abundant species belonged to these species-rich taxa and were highly abundant by either technique. The above-ground surveys found at least 73 species and the below-ground technique 238 operatonal taxonomic units. Although many fine-scale taxa (species and approximate families) were unique to one technique or the other (only eight genetic species were shared between both), the below-ground technique uncovered a greater breadth of higher taxa (mostly equivalent to orders), including ones undetected by the above-ground technique. A review of grassland fungi surveys around the world shows many similarities and the potential for grassland fungal conservation in North America. Given current technological advancements and grassland conservation concerns, it is prudent to further study North America's grassland fungi.

opencc-zeroSep 2019View details →
zenodo32/100

Isotopic analysis: How our community analyzes soil and plant water samples for their isotopic composition

<p>As part of a project to develop a common methodological framework for water sampling, extraction, and isotopic analysis to study vegetation water use, we conducted an informal survey of current practices.&nbsp; A simple questionnaire via Google form was sent out to all members of the WATer isotopeS in the critical zONE (WATSON) European Cooperation in Science and Technology (COST) Action (#19120, 2020-2024) between July and September 2021. In this repository, we've included a brief write-up of this survey and the survey data.&nbsp;</p>

opencc-by-4.0Nov 2023View details →

ScienceDex guides

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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

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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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record