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237 results for “Soil properties”
Figure 1 in Dynamics of arbuscular mycorrhizal fungi in relation to root colonization, spore density, and soil properties among different spreading stages of the exotic plant threeflower beggarweed (Desmodium triflorum) in a ZoysiO tenuifoliO lawn
Figure 1. Dynamics of the soil physiochemical properties (average ± SE, n = 5) within different Desmodium triflorum coverage levels and seasons. "Season" and "Coverage" indicate ANOVA results of each indicator among seasons and D. triflorum coverage levels, respectively. Level 1, level 2, level 3, level 4, and level 5 indicate the coverage levels of D. triflorum in the Zoysia tenuifolia lawn, respectively, in this and all following figures.
FIGURE 3. Quantitative burrow properties. A in Linking burrow morphology to the behaviors of predatory soil arthropods: Applications to continental ichnofossils
FIGURE 3. Quantitative burrow properties. A) Measurements were taken for number of surface openings (SO), burrow slope (S), maximum depth (D), total length (L), tunnel, shaft, and chamber width (w), height (h), and circumference (c), and branching angles (BA). B) Complexity includes the number of segments (s), chambers (h), and surface openings (e) within a single burrow system. C) Tortuosity of a single burrow segment is found by dividing the total length (u) by the straight-line distance (v) from end to end. Modified from Hembree (2019).
Figure 2 in The influence of distance from crushed stone mining on surface-active arthropods and soil chemical properties
Figure 2. Principal coordinates analyses (PCO) of the composition of soil chemical properties across sampling points from A, Blue Rock and B, Ikwezi mining sites. Grey triangles = 5 m, circles = 30 m, squares = 50 m, and open triangles = 70 m from the mining activities.
Figure 1 in The influence of distance from crushed stone mining on surface-active arthropods and soil chemical properties
Figure 1. Study sites showing sampling points (5 m, 30 m, 50 m and 70 m) from the mining activities at Blue Rock and Ikwezi mining sites.
Figure 3 in The influence of distance from crushed stone mining on surface-active arthropods and soil chemical properties
Figure 3. Effect of distance from the mining sites on the mean values of zinc. A, Blue Rock and B, Ikwezi mining site.
Enzymes, PLFA, NLFA and soil properties measured in Juniperus thurifera forest expansion gradient
<table> <tbody> <tr> <td>Columns<span> </span></td> <td>Description</td> <td>Unit</td> <td>Comments</td> </tr> <tr> <td>Site</td> <td>Huertahernando, Ribarredonda, Maranchón</td> <td> </td> <td>3 levels</td> </tr> <tr> <td>Stage</td> <td>Stage of forest expansion gradient (Mature forest, transition zone and expanding front)</td> <td> </td> <td>3 levels</td> </tr> <tr> <td>Microhabitat</td> <td>Under canopy/Open areas</td> <td> </td> <td>2 levels</td> </tr> <tr> <td>Sample code</td> <td>Sample code corresponding to sampling point</td> <td> </td> <td> </td> </tr> <tr> <td>Plot</td> <td>18 plots</td> <td> </td> <td> </td> </tr> <tr> <td>From F to AG<span> </span></td> <td>PLFAs peaks</td> <td>nmol g-1 soil</td> <td> </td> </tr> <tr> <td>Column AF</td> <td>NLFA peak</td> <td>nmol g-1 soil</td> <td> </td> </tr> <tr> <td>OM<span> </span></td> <td>organic matter</td> <td>%</td> <td> </td> </tr> <tr> <td>pH</td> <td>pH</td> <td> </td> <td> </td> </tr> <tr> <td>From AK to AQ</td> <td>Enzimes</td> <td>pmol mg-1 min-1</td> <td> </td> </tr> </tbody> </table>
Incubation data, CO2 and CH4 flux data and soil properties of thaw slump soils on Kurungnakh, Lena Delta in July 2016 and July 2019
<p>CO2 and CH4 rates from incubations and potential fluxes: This dataset contains rates of CO2 and CH4 production and the potential CO2 and CH4 emission rates calculated from these incubation fluxes</p> <p>in situ CO2 and CH4 chamber fluxes: This dataset contains CO2 and CH4 fluxes measured with closed chambers from different sites on Kurungnakh in July 2016 and July 2019</p> <p>simulated soil temperature and modelled CO2 fluxes: This dataset contains daily mean soil temperature data simulated with JSBACH for 2016 and the annual CO2 fluxes simulated with a Q10 model and the Introductory Carbon Balance Model (ICBM)</p> <p>thaw depth, TOC in active layer, soil temperature 2016: This dataset contains the thaw depth, TOC pools in the active layer and the soil temperature during the measurement period in July 2016</p> <p>thaw depth, TOC in active layer, soil temperature 2019: This dataset contains the thaw depth, TOC pools in the active layer and the soil temperature during the measurement period in July 2019</p> <p> </p> <p> </p> <p> </p> <p> </p>
Phosphorus fractions and related properties in soils under Pinus sylvestris L. plantations in Spain
<p>This database presents information about the P fractions in soils determined following the method developed by Hedley et al. (1982) and modified by Tiessen and Moir (1993) and other soil chemical properties of soils under <em>Pinus sylvestris </em>L. plantations in Spain.</p> <p>Abbreviations of variables names and units are described below:</p> <p>pH: soil pH; EOC: easily oxidizable C (%); EA: exchangeable acidity (cmol<sub>(+)</sub>·kg<sup>-1</sup>); Ca: exchangeable Ca (cmol<sub>(+)</sub>·kg<sup>-1</sup>); Sat: base saturation of the exchangeable complex (%); Al<sub>A</sub>, Fe<sub>A</sub>: amorphous Al and Fe (mg kg<sup>-1</sup>); Al<sub>E</sub>: exchangeable Al (cmol<sub>(+)</sub>·kg<sup>-1</sup>); Al<sub>M</sub>, Fe<sub>M</sub>: organically bound Al and Fe (mg kg<sup>-1</sup>); SI: forest site index (m); Cmic: microbial biomass C (mg kg<sup>-1</sup>); Pmic: microbial biomass P (mg kg<sup>-1</sup>); Cmin: mineralizable C (mg·kg<sup>-1</sup>·week<sup>-1</sup>) ; AcPhos: acid phosphatase activity (µg·g<sup>-1</sup>·h<sup>-1</sup>); PAEM: available P (mg kg<sup>-1</sup>); PiNaHCO3, PoNaHCO3: inorganic and organic highly labile P (mg kg<sup>-1</sup>); PoNaOH; PiNaOH: inorganic and organic moderately labile P (mg kg<sup>-1</sup>); PHCl1M: primary P (mg kg<sup>-1</sup>); PHClconc: stable P (mg kg<sup>-1</sup>); PHClO4: residual P (mg kg<sup>-1</sup>); PTotal: addition of all previous P fractions analysed (mg kg<sup>-1</sup>).</p>
A laboratory study of the photometric properties of Mars Global Soil Simulant MGS-1 and its variants
<p>Figures 2 and 5-16 of "A laboratory study of the photometric properties of Mars Global Soil Simulant MGS-1 and its variants" submitted to Planetary & Space Science.</p>
Database on soil properties of the CS1 Study case
<p>Soil properties dataset of the CS1 Study Case corresponding to the article "The combination of crop diversification and no tillage enhances key 1 soil quality parameters related to soil functioning without compromising crop yields in a low-input rainfed almond orchard under semiarid Mediterranean conditions" by Almagro et al.</p>
Spatio-temporal change of selected soil physico-chemical properties in grevillea-banana agroforestry systems
<p>This is a data base containin raw data (soil and litter data) as well as the R scripts used for their analyses</p>
Effects of powdered cactus pear pruning amendment on the physical and hydraulic properties of two contrasting Mediterranean soils
<p>Full database.</p> <p>A production and consumption paradigm known as "circular economy" (CE) emphasizes sharing, renting, reusing, repairing, refurbishing, and, in particular, recycling materials as much as feasible. Traditional agriculture relied totally on the CE, progressively the search for maximization of yields has produced more and more by-products. Their recovery and reuse are possible with approaches that refer to the CE, for example, with the use of pruning biomasses. The cultivation of the cactus pear annually produces large quantities of pruning residues, which have been shown to be useful for the recovery and reuse of nutrients. This study investigates the hydraulic properties of benchmark soils in which this by-product is incorporated. Here we show that the amendment with powdered cactus pear pruning waste (PCPPW) positively affects soil water retention. However, observable benefits require very high amendment proportions, more than 20% by volume. These quantities make use in the open field unrealistic but offer perspectives in the horticultural and floricultural sectors. These results reveal agreement in direct comparison to what was thought to be the case previously, i.e., a decrease in soil bulk density, an increase in plant available water capacity and an increase in soil swelling. A few per cent application of PCPPW improves the drainable water capacity only in the case of not very clayey soils, where their use becomes useless. The principles of the CE are important, but they must not be pursued a priori. For example, in the use of soil amendments, the behavior in the different soils conditions the suitability of their use.</p>
Soil chemistry dataset from the work "Modelling and prediction of major soil chemical properties with Random Forest: machine learning as tool to understand soil-environment relationships in Antarctica"
<p>Bases sum, H+Al (potential acidity), pH, phosphorous, remaining P (P-rem), sodium and total organic carbon distribution in Antarctic soils modeled and predicted through Machine Learning approaches, legacy soil data and environmental covariates. The quantile and prediction interval data represent the spatial uncertainty of the predictions.</p> <p>As soon as the work "Modelling and prediction of major soil chemical properties with Random Forest: machine learning as tool to understand soil-environment relationships in Antarctica" is published, the paper will be cited here. </p> <p>The .zip file contains the following folders:</p> <p>1) soil_chemistry_antarctica: data containing the soil chemical attributes distribution</p> <p>2) soil_chemistry_prediction_interval: uncertainty from the prediction interval 90% (Q95% - Q5%) of the soil attributes prediction</p> <p>4) soil_texture_quantile05: quantile 5% of the soil attributes prediction</p> <p>5) soil_texture_quantile95: quantile 95% of the soil attributes prediction</p>
Fine-scale variation in soil properties promotes local taxonomic diversity of hybridizing oak species (Quercus spp.)
Open the record for dataset details and reuse information.
Data from: The PDI model system for parameterizing soil hydraulic properties
Open the record for dataset details and reuse information.
Spatial soil properties distribution in “Hoya del río Suárez” region in Colombia.
There is a spatial soil properties distribution surface in raster format. This is the result of a study about digital soil mapping. Implementing geoestatistics (regression kriging RK) and machine learning algorithms (random forest RF, support vector machines SVM, and ensemble models), the study found the best performance for 5 soil properties (clay fraction, bulk density, total porosity, pH, and cation exchange capacity). The study was located in a region named “Hoya del río Suárez”, which is the main sugarcane-producing region in Colombia, and its land area is around 47000 hectares. Those raster surfaces were carried out in 2021, and the database used for doing this study was compiled between 2015 and 2016.
Microbial biomass and soil properties data, global scale,1970s-2010s
The data for Microbial Data System. We will collect data for soil and microbial characteristics in terrestrial ecosystems and update regularly. The date of publications used spans from the late 1970s to 2012. The data were aggregated into 11 major biome types. These data points were collected exclusively for surface soils, primarily 0–15 cm depth with some 0–30 cm. We obtained 3259 data points with geographical information.
Peat cores were collected along the Dalton Highway for the analysis of soil properties, 13C and percent of modern age, North Slope, Alaska 1989.
Peat cores were collected along the Dalton Highway in 1989 and analysed for percent moisture, percent organic carbon, bulk densitey, del C-13, and radiocarbon content at varying depth intevals throughout the core. Samples were collected to the mineral zone and kept in cold storage until analysis. Samples were collected from 12 sites.
Nitrogen cycling, soil properties and infiltration rates along a topographic gradient in lawns in Baltimore County, Maryland
The aim of this research was to examine how topography and homeowner fertilizer practices affected soil and hydrologic properties of residential lawns to determine if there are locations within lawns that have the potential to act as hotspots of nitrogen transport during rain events. This data set contains measurements of saturated infiltration rates, sorptivity, soil moisture, soil organic matter, pH, soil nitrate, soil ammonium, denitrification potentials and limiting factors, and nitrogen mineralization rates from fertilized and unfertilized residential and institutional lawns. Study lawns were located at homes of people who agreed to volunteer their lawn for the study from a door knocking campaign. Four sampling houses were located in an exurban neighborhood in Baisman Run. Five sampling houses were located in a suburban neighborhood in Dead Run. Two sampling locations on institutional lawns were located at University of Maryland Baltimore County. At the exurban study houses and institutional lawns sites,we identified one hillslope to conduct sampling on. At the Dead Run houses we identified one hillslope on the front yard and one in the backyard as there were distinct locations that were not present in the exurban neighborhood. In total we sampled on 16 hillslopes. At each hillslope, we identified the top, toe and swale locations. At each hillslope location, we selected three sampling locations along a transect (maximum 10 meters in length; total of 144 sampling locations). At each sampling location we ran a Cornell Sprinkle Infiltrometer to measure sorptivity and saturated infiltration rates. Volumetric water content was measured before and after infiltrometer runs with a Field Scout TDR 300 with 7.5 cm rods. In addition, at each sampling location we took two soil cores to 10 cm depth, and combined and homogenized the two cores for that sampling location for a total of 144 soil samples. Soil cores were stored on ice in the field, and then stored at 4°C in the
Eight Mile Lake Research Watershed, Thaw Gradient Extended sites: Physical properties of soil (temperature, moisture and thaw depth).
This data set contains meausrements of soil properties (soil moisture, soil temperature, thaw depth) of sites surrounding an eddy covariance tower. The purpose was to see how physical changes in the lanscape effect carbon fluxes measurede by the EC tower.
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Allen Brain Atlas
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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.