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47 results for “Soil mechanics”
Soil Organic Matter Mechanisms of Stabilization (SOMMOS) - enhanced soil characterization data from 40 National Ecological Observatory Network (NEON) sites
Soil organic matter (SOM) is a critical linkage among many ecosystem services that sustain our society and life on Earth. It is the primary energy source for microbes and the principal storehouse of water necessary for plant growth. SOM also stores nutrients for plants and sorbs pollutants that otherwise could contaminate food and water supplies. Soils also help regulate climate by storing carbon that would otherwise be released to the atmosphere and contribute to climate change. The SOMMOS project investigated processes in the soil that protect SOM from being decomposed by microbes, processes that increase its sensitivity to environmental changes, and how changes in climate and land management influence the amount and stability of SOM. The project, which was a collaboration between scientists from the National Ecological Observatory Network (NEON), University of Colorado, University of Michigan, Oregon State University, Virginia Polytechnic Institute and State University, and the USDA-Forest Service, took advantage of soil samples collected across NEON, a major NSF investment in environmental monitoring that covers the entire United States. This continental-scale soil sample set was analyzed for a wide array of physical and chemical properties, well beyond those typically measured on such a large-scale sample set, including radiocarbon, extractable metals, organic matter chemistry by pyrolysis-GCMS, liquid extract fluorescence spectroscopy, and more. In addition to this dataset, archived samples are available from the project for sharing with interested researchers.
Mechanisms influencing physically sequestered soil carbon in temperate restored grasslands in South Africa and North America
This dataset contains a measurement of physically protected carbon (microaggregate-within-macroaggregate C) and potential drivers of physically protected C accumulation during grassland restoration. The data were collected from three independent grassland restorations from agriculture in North America and South Africa. Northeast Kansas, USA data were collected in May 2013. Northeast Free State, RSA data were collected in September–November 2005. Southeast Nebraska, USA data were collected in October 2008–May 2008. Aggregate fractionations were performed by hierarchical wet sieving (Six et al 2000). Carbon and N quantification were done by flash combustion-gas chromatography. Microbial biomass C quantification was performed with chloroform fumigation-incubation (chloroform fumigation-extraction in the case of northeast Kansas). Phospholipid fatty acid biomass analysis was conducted using the methods of Bligh and Dyer (1959).
Data from: Mechanical soil disturbance in a pine savanna has multi-year effects on plant species composition
<p>Data used in the manuscript Mechanical soil disturbance in a pine savanna has multi-year effects on plant species composition accepted for publication in Ecosphere. Data included are species lists for all plots and years, percent cover of species in each plot in 2021, and life-history characteristics (life span, dispersal mechanism, seed bank persistence) of all species. See manuscript for site description and data collection methodology. </p>
Text-fig. 1. A. Location of the sites of Capo di Fiume, Palena and Pollenzo near Alba. B. Capo di Fiume stratigraphic section. Facies of coastal-transitional marine associations – a. Freshwater marsh and tidal creeks interval, b. Swamp interval, c1–c4. Facies of eustarine bay associations, d1–d6. Facies of open shelf marine associations. Symbols: "black star" – fossiliferous horizon with plant material studied here, 1. mottled grey to dark-brown marls and clayey marls, 2. fissile dark-grey marls and shaly marls, 3. limestones, 4. marly limestones and limey marls, 5. bio-lithoclastic calcarenites, 6. lime conglomerate, 7. massive muddy deposit produced by mass-flow mechanism, 8. diatomitic marls, 9. "terra rossa" soil (modified after Carnevale et al. 2011). in Feather Palm Foliage From The Messinian Of Italy (Capo Di Fiume, Palena And Pollenzo Near Alba) Within The Framework Of Northern Mediterranean Late Miocene Flora
Text-fig. 1. A. Location of the sites of Capo di Fiume, Palena and Pollenzo near Alba. B. Capo di Fiume stratigraphic section. Facies of coastal-transitional marine associations – a. Freshwater marsh and tidal creeks interval, b. Swamp interval, c1–c4. Facies of eustarine bay associations, d1–d6. Facies of open shelf marine associations. Symbols: "black star" – fossiliferous horizon with plant material studied here, 1. mottled grey to dark-brown marls and clayey marls, 2. fissile dark-grey marls and shaly marls, 3. limestones, 4. marly limestones and limey marls, 5. bio-lithoclastic calcarenites, 6. lime conglomerate, 7. massive muddy deposit produced by mass-flow mechanism, 8. diatomitic marls, 9. "terra rossa" soil (modified after Carnevale et al. 2011).
Various seasonal pattern and mechanisms of soil nitrogen transformation along elevations in the Hengduan Mountains
<p><span>Soil nitrogen (N) transformation, a key microbial process in global N cycling, is thought to alter soil N availability and subsequently regulate ecosystem functioning. In particular, the gross rates of N transformation can provide a deeper understanding of internal N dynamics and mechanisms, but questions of whether gross N transformation processes and their underlying drivers change with seasons and elevations remain large uncertain.</span></p> <p><span>Based on field collection along an elevational gradient and laboratory incubation experiments, we investigated the seasonal processes of soil N mineralization and nitrification with 15N isotope dilution technique, and also explored the potential mechanisms involved in the Hengduan Mountains.</span></p> <p><span>Unimodal soil gross/net mineralization rates were higher in the wet season (61.32 mg kg<sup>-1</sup> d<sup>-1</sup>; 1.01 mg kg<sup>-1</sup> d<sup>-1</sup>; respectively) than in the dry season (10.88 mg kg<sup>-1</sup> d<sup>-1</sup>; 0.55 mg kg<sup>-1</sup> d<sup>-1</sup>; respectively) (P < 0.001), with a peak at medium elevation. Soil gross/net nitrification rates were lower in the wet season (1.43 mg kg<sup>-1</sup> d<sup>-1</sup>; -0.017 mg kg<sup>-1</sup> d<sup>-1</sup>) than in the dry season (2.49 mg kg<sup>-1</sup> d<sup>-1</sup>; 0.004 mg kg<sup>-1</sup> d<sup>-1</sup>; respectively) (P < 0.001), which increased with increasing elevation. The results detected the dominant drivers of the gross transformation rates, specifically microbial attributes occupied crucial roles in controlling the gross mineralization/nitrification</span> <span>in the wet season, and soil physicochemical properties were dominant controllers on the gross mineralization/nitrification</span> <span>during the dry season.</span></p> <p><span>This study revealed the divergent patterns and drivers of N transformation, suggesting that seasonal N cycling should no longer be overlooked if we are to predict N biogeochemical cycles in response to environmental change accurately.</span></p>
Various seasonal pattern and mechanisms of soil nitrogen transformation along elevations in the Hengduan Mountains
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Data for: Mechanisms of root-reinforcement in soils: an experimental methodology using four-dimensional X-ray computed tomography and digital volume correlation
<p>Collection of data files used in the paper titled: Mechanisms of root-reinforcement in soils: an experimental methodology using four-dimensional X-ray computed tomography and digital volume correlation.</p> <p>Additional dataset which covers the noise study CT scans and digital volume correlation noise studies can be found in DOI: <a href="http://www.doi.org/10.5281/zenodo.3352268">10.5281/zenodo.3361832</a></p> <p><strong>Data contains the following:</strong></p> <ul> <li>X-ray CT data for the interrupted direct shear tests of a soil sample containing a Willow plant. The first file is the specimen scanned unloaded, followed by seven incremental shear load steps to 20 mm shear displacement. Files are 8-bit unsigned and 1800x1800x1600px. Voxel resolution is 0.04642 mm. <ol> <li><strong>20180430_HUTCH_1839_DJB_willow_C_8-bit_1800x1800x1600.raw</strong></li> <li><strong>20180430_HUTCH_1839_DJB_willow_C_Load_A_8-bit_1800x1800x1600.raw</strong></li> <li><strong>20180430_HUTCH_1839_DJB_willow_C_Load_B_8-bit_1800x1800x1600.raw</strong></li> <li><strong>20180430_HUTCH_1839_DJB_willow_C_Load_C_8-bit_1800x1800x1600.raw</strong></li> <li><strong>20180430_HUTCH_1839_DJB_willow_C_Load_D_8-bit_1800x1800x1600.raw</strong></li> <li><strong>20180430_HUTCH_1839_DJB_willow_C_Load_E_8-bit_1800x1800x1600.raw</strong></li> <li><strong>20180430_HUTCH_1839_DJB_willow_C_Load_F_8-bit_1800x1800x1600.raw</strong></li> <li><strong>20180430_HUTCH_1839_DJB_willow_C_Load_G_8-bit_1800x1800x1600.raw</strong></li> </ol> </li> <li>Direct shear vs. displacement data is presented in an Excel spreadsheet: <ul> <li><strong>All_load_data_with_reducing_area.xlsx</strong></li> </ul> </li> <li>Normal and shear strain DVC data which has been averaged and plotted against specimen depth is presented in an Excel spreadsheet: <ul> <li><strong>Average_slice_vs_depth_data_all_samples_all_loads3.xlsx</strong></li> </ul> </li> <li>CT scan metadata giving information to the scan settings, voxel resolution, etc. is contained in a .zip file which consists of .xtekct and .XML files generated from the Nikon CT scanner. <ul> <li><strong>CT_Scan_Metadata.zip</strong></li> </ul> </li> <li>Drawings and Solidworks CAD files of the direct shear test rig are contained within the .zip file. There are a number of parts to the assembly. The file SSSB1003-5.SLDASM contains the complete assembly of the direct shear rig and will help identify the part names. The folder CAD_Drawings contains pdf documents of the part drawings. <ul> <li><strong>Direct_Shear_Drawings_Solidworks_Files.zip</strong></li> </ul> </li> <li>Tabulated DVC data taken at 32x32x32px subset size is contained inside a .zip file. These consist of tab separated .dat files from unloaded (data_1.dat) through incremental load steps Load A, Load B... Load G, (data_2.dat, data_3.dat... data_8.dat). The structure of the .dat file contains columns of data with each column number corresponding to the following: (1) x, (2) y (3) z, (4) vx, (5) vy, (6) vz, (7) exx, (8) eyy, (9) ezz, (10) exy, (11) exz, (12) eyz, (13) volumetric strain, (14) is valid. Columns 1-3 are subset positions in mm, 4-6 are displacements in mm, 7-9 are normal strains, 10-12 are shear strains, 13 is volumetric strain and 14 is a binary value indicating if the subset is valid. <ul> <li><strong>DVC_Load_Data_Willow_C.zip</strong></li> </ul> </li> <li>Tabulated DVC data applied to the load step CT data at 32, 48, 64, 96, 128 pixels is presented in the .zip files containing .dat tab separated files. The structure of the .dat files is described in the previous bullet point. These files were used to construct the noise study applied to incrementally loaded CT data by sampling regions away from the shear zone where the strain signals are close to zero. <ul> <li><strong>DVC_Noise_Study_Data_Load_Steps_Willow_C.zip</strong></li> </ul> </li> <li>Processed noise study data which compares the effects of DVC subset size is presented in the .xlsx file. This file contains both the controlled noise experiment data (stationary, magnification and rigid body motion) and noise study data applied to incrementally loaded data using sampled regions away from the shear zone where the strain signals are close to zero. <ul> <li><strong>Willow_C_Processed_Noise_study2.xlsx</strong></li> </ul> </li> <li>Tabulated data which compares the local x displacement vs depth profile from DVC and direct measurement of root position is contained in the following Excel spreadsheet file: <ul> <li><strong>X_Displacement_Root_and_DVC_Comparison_Willow C.xlsx</strong></li> </ul> </li> </ul>
Effects of Grass Cover on the Overland Soil Erosion Mechanism under Simulated Rainfall
<p><span>Grass cover has a complex influence on overland soil erosion. This study quantified the impact of grass cover on overland soil erosion using a dimensionless water flow path index. It systematically analyzed the response mechanism among overland soil erosion, slope gradient, rainfall intensity, and hydrodynamic parameters, aiming to identify the optimal hydrodynamic parameters capable of characterizing overland soil erosion. A predictive model for soil erosion was constructed based on general dimensionless water flow intensity parameters, comprehensively evaluating the mechanism of soil erosion on grass-covered overland under simulated rainfall conditions. The results indicate that the model constructed using dimensionless parameters exhibits strong adaptability and can be effectively validated in other experiments.</span></p>
Elevational shifts in foliar-soil δ15N in the Hengduan Mountains and different potential mechanisms
<p><span>The natural abundance of stable nitrogen isotopes (δ<sup>15</sup>N) provides insights into the N dynamics of </span><span>terrestrial ecosystems, the determination of which is considered</span><span> an effective approach for gaining a better understanding ecosystem N cycling</span><span>. </span><span>However, there is currently little information available regarding the patterns and mechanisms underlying the variation in foliar-soil δ<sup>15</sup>N among mountain ecosystems. </span><span>In this study, we examined the determinants of foliar-soil δ<sup>15</sup>N in association with N transportation rates along an elevational gradient in the </span><span>Hengduan </span><span>Mountains.</span><span> Despite the relatively high levels of available N produced from high N fixation and mineralization, we detected the lowest levels of foliar δ<sup>15</sup>N at 3500 m a.s.l., reflecting the stronger vegetation N limitation at medium high elevations. The enhanced vegetation N limitation was driven by the combined effects of higher microbial immobilization and inherent plant dynamic (the shifts of δ<sup>15</sup>N in vegetation preference, including </span><span>vegetation community</span><span>) </span><span>with changing </span><span>climate along the elevational gradient.</span><span> </span><span>Unexpectedly</span><span>, we established that soil δ<sup>15</sup>N was characterized by an undulating rise and uncoupled correlation with foliar δ<sup>15</sup>N with increasing elevation, thereby indicating that litter input might not be a prominent driver of soil δ<sup>15</sup>N. Conversely, soil nitrification and denitrification were found to make a more pronounced contribution to the pattern of soil δ<sup>15</sup>N along the elevational gradient. Collectively, our results serve to highlight the importance of microbial immobilization in soil N dynamics and provide novel insights that will contribute to enhancing our understanding of N cycling</span><span> </span><span>as indicated by foliar-soil δ<sup>15</sup>N along elevational gradients.</span></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>
Progressive failure analysis of slip zone soils with strain-softening behavior and implications for landslide triggering mechanisms
<p>All figure for paper entitled “Progressive failure analysis of slip zone soils with strain-softening behavior and implications for landslide triggering mechanisms”</p>
Reduce revenue vs. increase expenditure: Fires and plant invasion drive soil carbon loss with different mechanisms in a Mediterranean shrubland
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Elevational shifts in foliar-soil δ15N in the Hengduan Mountains and different potential mechanisms
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Soil nitrate and ammonium: Mechanisms of Grasshopper-Plant Interactions
This experiment is designed to examine the mechanisms of competition among grasshoppers, effects of grasshoppers on plant competition, and the effects of plant species and biomass on the ability of grasshoppers to coexist. The plots were set up within the E026 fenced exclosure. The plots are 60cm x 60cm. They are enclosed by a cage which is 1.2m high. The 240 plots were seeded with monocultures and pairwise combinations of two grasses, Schizachyrium scoparium, Poa pratensis, and a legume Lespedeza capitata. To each plant monoculture and species combination, two grasshopper species were added at high density according to four treatments: each grasshopper species by itself (2 treatments), both species together, and no grasshoppers (empty cage). Introduced grasshoppers were allowed to decline to an "equilibrium" density, as determined by counting all grasshoppers in cages every 5 days. After grasshoppers reached "equilibrium", vegetation was sampled by clipping a 50cm x 5cm strip. Soil samples were taken 5 times during the summer to determine the effect of grasshoppers on available soil nitrogen. For a list of treatments, see the treatment layouts in file trmte71.
Noise study data for: Mechanisms of root-reinforcement in soils: an experimental methodology using four-dimensional X-ray computed tomography and digital volume correlation
<p>This dataset contains noise study data used in the paper: Mechanisms of root-reinforcement in soils: an experimental methodology using four-dimensional X-ray computed tomography and digital volume correlation. These include raw CT scans and processed digital volume correlation data.</p> <p>This dataset is part of another dataset which covers other aspects of the paper DOI: <a href="http://www.doi.org/10.5281/zenodo.3352268">10.5281/zenodo.3352268</a></p> <p>The structure of the dataset is as follows:</p> <ul> <li>Noise study CT raw volumes are contained in a zip file. There are four raw files corresponding to the four noise study steps. These files are 8-bit unsigned, dimensions are 1800 x 1800 x 1400 pixels. A txt file giving more details to the data is included. <ul> <li><strong>CT_Raw_data_Noise_Scans.zip</strong></li> </ul> </li> <li>Metadata files generated for each scan given details of scan parameters are found in the zip file: <ul> <li><strong>CT_Scan_Metadata.zip</strong></li> </ul> </li> <li>Tabulated digital volume data for the noise study scans are contained in the zip file. Tabulated data for each subset size is included in subfolders. A .txt file explains the structure of the tab separated .dat files, i.e. what each column of data represents, and what CT scan each of the four .dat files relate to. <ul> <li><strong>DVC_Noise_Study_Data.zip</strong></li> </ul> </li> </ul> <p> </p> <p> </p>
Island biogeography of soil bacteria and fungi: similar patterns, but different mechanisms
<p>Microbes, similar to plants and animals, exhibit biogeographic patterns. However, in contrast with the considerable knowledge on the island biogeography of higher organisms, we know little about the distribution of microorganisms within and among islands. Here, we explored insular soil bacterial and fungal biogeography and underlying mechanisms, using soil microbiota from a group of land-bridge islands as a model system. Similar to island species-area relationships observed for many macroorganisms, both island-scale bacterial and fungal diversity increased with island area; neither diversity, however, was affected by island isolation. By contrast, bacterial and fungal communities exhibited strikingly different assembly patterns within islands. The loss of bacterial diversity on smaller islands was driven primarily by the systematic decline of diversity within samples, whereas the loss of fungal diversity on smaller islands was driven primarily by the homogenization of community composition among samples. Lower soil moisture limited within-sample bacterial diversity, whereas smaller spatial distances among samples restricted among-sample fungal diversity, on smaller islands. These results indicate that among-island differences in habitat quality generate the bacterial island species-area relationship, whereas within-island dispersal limitation generates the fungal island species-area relationship. Together, our study suggests that different mechanisms underlie similar island biogeography patterns of soil bacteria and fungi.</p>
Data from: Beyond plant-soil feedbacks: mechanisms driving plant community shifts due to land-use legacies in post-agricultural forests
Although biotic legacies of past agricultural practices are widespread and increasing in contemporary ecosystems, our understanding of the mechanisms driving such legacies is still poor. Forest understories on former agricultural land show low frequencies and abundance of typical woodland species when compared with ancient forests. These community shifts have been ascribed to the effects of dispersal limitation. A rarely considered mechanism is that post-dispersal processes driven by plant-associated communities determine the poor performance and recruitment of woodland indicators. Given the strong alterations in soil conditions due to former agricultural practices, we hypothesized that (abiotic) plant–soil feedbacks could be a major factor in community shifts. We addressed this hypothesis by comparing plant-associated communities in the soil and above the ground in ancient and post-agricultural alluvial forests; then, we experimentally tested whether the changes in biotic and abiotic soil properties could affect above-ground herbivore abundance and pressure and plant performance. Ancient and post-agricultural communities clearly differed in composition at different levels of the food web. Besides the plant community, we also observed the differences in the microbial and nematode community with increased abundance of root-feeding nematodes in post-agricultural soils. The composition of the above-ground invertebrate community did not differ in ancient and post-agricultural forest parcels; however, plants growing in post-agricultural sites showed higher abundance of invertebrate herbivores and suffered more herbivory. Nutrient analyses of soil and plants showed that increased levels of phosphorus (and to a lesser extent, nitrogen) made plants more nutritious for insect herbivores. Laboratory experiments further pointed to this mechanism as an explanation of the poorer performance of woodland indicators in post-agricultural woodlands. Our results point to biotic and abiotic plant–soil feedbacks coupled with herbivory as a new mechanism to explain the legacy effects in temperate forests. The modification of the below-ground community and soil abiotic characteristics by previous agricultural activity affects not only the plant growth but also the plant nutrient content in the compared understorey species, making them more susceptible to above-ground herbivory. Our results provide one of the first examples of integrating plant–soil feedback and above- and below-ground interactions to explain land-use legacies.
Data from: Unraveling the mechanisms underlying pulse dynamics of soil respiration in tropical dry forests
Tropical dry forests are already undergoing changes in the quantity and timing of rainfall, but there is great uncertainty over how these shifts will affect belowground carbon (C) cycling. While it has long been known that dry soils quickly release carbon dioxide (CO2) upon rewetting, the mechanisms underlying the so-called 'Birch effect' are still debated. Here, we quantified soil respiration pulses and their biotic predictors in response to simulated precipitation events in a regenerating tropical dry forest in Costa Rica. We also simulated the observed rewetting CO2 pulses with two soil carbon models: a conventional model assuming first-order decay rates of soil organic matter, and an enzyme- catalyzed model with Michaelis–Menten kinetics. We found that rewetting of dry soils produced an immediate and dramatic pulse of CO2, accompanied by rapid immobilization of nitrogen into the microbial biomass. However, the magnitude of the rewetting CO2 pulse was highly variable at fine spatial scales, and was well correlated with the size of the dissolved organic C pool prior to rewetting. Both the enzyme-catalyzed and conventional models were able to reproduce the Birch effect when respiration was coupled directly to microbial C uptake, although models differed in their ability to yield realistic estimates of SOC and microbial biomass pool sizes and dynamics. Our results suggest that changes in the timing and intensity of rainfall events in tropical dry forests will exert strong influence on ecosystem C balance by affecting the dynamics of microbial biomass growth.
R code of the mechanism controlling soil bacterial α and β diversity under N addition
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Data from: A novel mechanism for grazing lawn formation: large herbivore-induced modification of the plant-soil water balance
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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.
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