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61 results for “soil physics”
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>
Dataset associated with "Assessment of the effects of the 2021 Caldor megafire on soil physical properties, eastern Sierra Nevadas, USA"
<p>This dataset includes both raw and processed data associated with the publication entitled "Assessment of the effects of the 2021 Caldor megafire on soil physical properties, eastern Sierra Nevadas, USA", published in MDPI Fire (doi: <a href="https://doi.org/10.3390/fire6020066">10.3390/fire6020066</a>). Raw files include exported .xlsx files from Meter Group HYPROP analyses, .csv files from 10 replicate measurements of saturated hydraulic conductivity for each analyzed sample using the Meter Group KSAT device, and raw .dat files from measurement of bulk thermal properties. A single additional file also documents the laboratory results from particle size and loss on ignition analyses. Processed data includes curve fitting parameters associated with fitting the soil water retention curves (SWRC) and thermal conductivity functions (TCFs) for each sample, as described in Sion et al. (2023). Additional requests associated with data from Sion et al. (2023) should be directed to the lead author.</p>
Soil physical, biological, chemical, and carbon data and cover crop biomass data from Sac Valley almond orchard comparing multiple cover crop compositions with resident vegetation for effects on soil health and nematodes
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Land use drives the distribution of free, physically protected, and chemically protected soil organic carbon storage at a global scale
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Dataset for a physics informed deep learning method with adaptively weighted loss for modeling soil water flows
<p>The data for the 11 scenarios generated by Hydrus-1D is located in data.zip</p> <p>The code for the physics-informed neural networks with adaptively weighted loss used to simulate water flow in loam soils is located at PINN_adaptively_weighted_loss_loam.zip</p>
Soil physical-chemical alterations by Patawatermes turricola mounds in northwestern Amazonian grasslands.
<p>The dataset describes soil physicochemical properties at different locations within the pasture transect at the Macagual Amazon Research Center in northwestern Colombian Amazonia. The data include samples collected from mounds constructed by the termite species <em>Patawatermes turricola</em> and from unmodified soils (topsoil) located 5 m from the mounds. The variables measured cover a wide range of soil characteristics, such as cation content (Ca, Mg, K, Na), organic carbon (SOC), available phosphorus (Pav), total porosity, bulk density, and aggregate stability, among others. These measurements allow us to evaluate the impact of termite mound construction activities on soil fertility and soil structure, comparing conditions between amended and unamended soils in a context of rotational grazing in pastures with scattered trees.</p>
Modeling water flow and solute transport in unsaturated soils using physics-informed neural networks trained with geoelectrical data
<p>Numerical codes and results for the article: Modeling water flow and solute transport in unsaturated soils using physics-informed neural networks trained with geoelectrical data</p>
Data from: Effects of soil physical properties on dung beetle assemblages in pasture landscapes of the Brazilian Cerrado
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Dataset for: Physics-informed neural networks with monotonicity constraints for Richardson-Richards equation: Estimation of constitutive relationships and soil water flux density from volumetric water content measurements by Toshiyuki Bandai and Teamrat A. Ghezzehei
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Ecological resilience of physical plant–soil feedback to chronic deer herbivory: slow, partial but functional recovery
<p>Ecological resilience to ungulate overbrowsing is an important issue in forest ecosystem. After chronic herbivory, the recovery rate of understory vegetation and its related functions can be slow even with decreasing grazing intensity; thus, detecting elasticity during alternative successional trajectories is fundamental to understanding state perturbations. In this context, we focused on physical plant–soil feedback (functional interactions between plant growths and soil physical conditions), and evaluated elasticity and recovery processes according to deer density. The effects of 40-year chronic herbivory by sika deer (average density 14.7 individuals km<sup>-2</sup>) on the recovery of understory plant communities and associated improvements in soil physical properties in headwater catchments were assessed. Using 8 years of catchment-wide exclusion (fenced) and reduction (only culled; average 4.3 individuals km<sup>-2</sup>) treatments, plot sampling was conducted in 2010 (before treatment) and 2018 (after treatment). The recovery of vegetation and soil physical properties were evaluated, and functional plant–soil relationships and spatial variability were assessed to detect recovery processes during alternative successional trajectory. Woody species increased only under the exclusion treatment and the average soil bulk density was lower than that under reduction treatments. Soil bulk density was negatively correlated with root biomass in the fenced catchment, and root biomass was positively associated with woody species richness. Reduced soil bulk density (~0.5 g cm<sup>-3</sup>) was observed with greater root biomass and woody species richness on upper hillslopes in the deer-excluded catchment where plant coverage was minimal. Successional failure under the reduction treatment suggested slow recovery with a depressed threshold according to deer density, indicating a clockwise hysteretic response to deer density. Unlike plant coverage during the earlier period of overbrowsing, woody species root development led the recovery of functional physical plant–soil feedback; however, this was probably limited by the higher soil erosion rate in riparian areas and an underdeveloped herb layer. Our results highlight an alternative recovery trajectory of physical plant–soil feedback driven by an alternative plant element (woody roots) to degradation trajectory with decreasing plant cover. However, riparian erosion and herb layer would still suppress recovery. Therefore, recovery might be slower at landscape scale.</p>
Figure 3 in Changes in galling insect community on Caryocar brasiliense trees mediated by soil chemical and physical attributes
Figure 3. Principal components regressions among: (A) abundance of parasitoids (A.P.) with abundance of galling insects (A.G.I.); (B) species richness of parasitoids (S.R.P.) with pH in water, species richness of galling insects (S.R.G.I.), and sand (dag kg-1) (Sa.); (C) diversity of parasitoids (D.P.) with diversity of galling insects (D.G.I.), silt (dag kg-1) (Si.), and clay (dag kg-1) (Cl.); (D) Sycophila sp. adults (Syc.) with Eurytoma sp. galling insect adults (Eur.) and Ablerus magistretti adults (Ama.); and (E) Ama. with Eur., phosphorus-Mehlich 1 (mg dm-3) contents (P.C.), Si., Syc., aluminum (cmol dm-3) contents (A.C.), and pH on Caryocar brasiliense trees in three years. The c symbols represent the averages and the bars the standard errors. n = 111.
Vercelli soil physical properties 2005
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Ecological resilience of physical plant–soil feedback to chronic deer herbivory: slow, partial but functional recovery
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Soil Matric Potential, Dielectric, and Physical Properties, Arctic Alaska, 2018
This dataset provides lab-measured soil properties, including soil water matric potential, soil dielectric properties, soil electrical conductivity, corresponding soil moisture. The dataset also includes the basic soil physical properties such as soil organic matter, bulk density, porosity, fiber content, root biomass, and mineral texture. Soil samples were collected from August 21 to August 27, 2018, from the surface to permafrost table in soil pits at nine sites along the Dalton Highway in northern and central regions of Alaska. Permittivity and soil electrical conductivity measurements were conducted using METER TEROS 12 probes. Soil moisture measurements were made with a TEROS 21 probe. The measurements were conducted in the lab over the span of three years. The purpose of soil collection and lab measurements was to develop an integrated framework that relates the hydrological properties to dielectric properties of permafrost active layer soil in support of the NASA Arctic and Boreal Vulnerability Experiment (ABoVE) Airborne Campaign.
Soil physical-hydric attributes under no-tillage crop in the savannah of the Southwest region of the Piaui State, Brazil
<p>The soils of the savannah region, Piaui State, Brazil, are favorable to agriculture; however, intensive use combined with inadequate management has caused soil degradation in the region. For this reason, studies focused on the use of alternative production systems as a no-till system (SPD), have become essential. Thus, the objective was to evaluate the changes in the physical-hydric attributes and organic matter in Oxisols under different times of no-tillage crop under straw in savannah areas of the Southwest region of the Piaui State, Brazil. Field data collection was carried out on commercial farms in the municipalities of Baixa Grande do Ribeiro (07° 48'10" S, 45° 00'60" W and altitude of 600 m), Uruçuí (08º14'07" S, 44º38'09" W and altitude of 550 m) and Bom Jesus (09º10'35" S, 44º50'36" W and altitude of 600 m), Piaui State, Brazil. The areas had different times of no-tillage crop under straw: SPD2 - 2 years, SPD3 - 3 years, SPD6 - 6 years, SPD10 - 10 years, SPD12 - 12 years, SPD15 - 15 years and SPD18 - 18 years old, as well as areas of native forest (control), in which the physical-water attributes were evaluated (distribution of granulometric fractions, soil density, total porosity, macro and microporosity, available water and field capacity), organic matter and the humid fraction. The database is organized as follows: identification of sampling sites, characterization of no-tillage systems under straw, soil physical-hydric attributes by layers and figures with the location of the farms and points sampling.</p>
SOIL STRUCTURE AND CHANGES IN THEIR PHYSICAL PROPERTIES UNDER THE INFLUENCE OF EROSION PROCESSES
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Soil physical-hydric attributes under no-tillage crop in the savannah of the Southwest region of the Piaui State, Brazil
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Data and code used in the article "A deep learning method for predicting soil moisture in unsaturated areas based on physical constraints"
<p>Data and code used in the article "A deep learning method for predicting soil moisture in unsaturated areas based on physical constraints", specifically included are water content data from 55 in situ observations for the years 2018-2020 (observation frequency of 5min or 10min), and example code for implementing LSTM and PIDL using python (mainly the tensorflow library).These data can help the reader to better understand and replicate our research. All the data and code has been uploaded. </p><p>The paper has been published in <i>Water Resources Research</i>, and the citation is: </p><p>Wang, Y., Wang, W., Ma, Z., Zhao, M., Li, W., Hou, X., et al. (2023). A deep learning approach based on physical constraints for predicting soil moisture in unsaturated zones. <i>Water Resources Research</i>,<i>59</i>, e2023WR035194. https://doi.org/10.1029/2023WR035194</p>
TRACE-Soils, LTEs soil physical data
<p>This dataset contains the measured soil physical parameters (weight at sampling, at -30, -60 and -100 hPa matric potential and after oven-drying, Darcian and apparent air permeability, and relative gas diffusivity) measured on 100-cm3 cylindrical samples from 0-10 and 10-20 cm depth from seven European long-term tillage experiments. </p>
SELECTED PHYSICAL AND CHEMICAL PROPERTIES OF SOIL UNDER DIFFERENT AGRICULTURAL LAND-USE TYPES IN ILE-IFE, NIGERIA
<p>The study examined changes in soil properties under different agricultural land-use types. This is with the view to extending knowledge on the nature of soil properties under long-term land-use practices. Six land-use types were considered; paddock, continuously cropped, secondary forest, teak, oil palm and cacao plantations. Soil strength and saturated hydraulic conductivity were determined at two soil depths (0-15 and 15-30 cm) in-situ. Soil samples were collected to determine particle size distribution, bulk density, aggregate stability, pH, organic carbon, cation exchange capacity, total nitrogen and available phosphorus.</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.