Soil Particle Size Distribution Research Articles

Laser Diffraction Particle Size Distribution of North American Turfgrass Horse Racing Surfaces

Highlights Laser diffraction analysis of soil particle size distribution is uniquely suited for active turf racetracks. Eight standard sampling locations are shown to be sufficient for characterizing a racing surface. Differences between the three archetypes of turfgrass racing surfaces were significant using laser diffraction. There is a need for consensus on the proper handling of organic content in samples. Abstract. Significant research has focused on North American dirt and synthetic Thoroughbred racing surfaces. Turfgrass racing surfaces have received less consideration. Basic information, including climate and turfgrass species, can be documented relatively easily. However, a key characteristic, the particle size distribution of the growing medium, is not readily available for turf tracks. Particle size distribution and the deviation from nominal values are important to infiltration rate, shear strength, and turf health, as well as being critical for the selection of top-dressing and divot repair sand. The primary difficulty with obtaining the particle size distribution is the relatively large quantity of material required for traditional sedimentation test methods. Sampling an active racing surface could present a risk to the horses and riders. Laser diffraction testing methods present an opportunity to use much smaller samples. The use of smaller samples introduces new questions about the ability of a small sample to represent a large area, such as a racetrack. Tests were carried out with high resolution sampling at one racetrack. By sampling a large number of locations, 96 locations on a single racetrack, the variability of the track could be evaluated, and an eight-sample protocol was developed. Using the eight-location protocol, 22 additional turf racetracks throughout North America were sampled. A total of 23 turf racetracks were tested, representing all three of the designs used for North American turf racetracks. By looking at the three different track designs: engineered profile, engineered profile with fiber, and native soil, appropriate testing parameters and measurements were identified. While the primary objective was to understand turf racetracks, this unique data set also provided a method to investigate the applicability of laser diffraction for the analysis of soil samples. Mineralogy and organic content had previously been identified as important in the measurement of particle size distribution using laser diffraction. Mineralogy and organic content were determined for samples from each surface using X-ray diffraction (XRD) and loss on ignition. The PSD of the three types of turfgrass horse racing surfaces showed significant differences between native soil (N), engineered surfaces without synthetic fibers (EWOF), and engineered surfaces with synthetic fibers (EWF). These basic design descriptions were also found to be sufficient for making reasonable estimates of the settings used in the machine configuration and sample preparation. A single refractive index was used for the entire range of samples in this group; however, the sample quantity tested was different for the three different types of track designs. Keywords: Horse, Laser diffraction, Racing, Soil, Thoroughbred, Turf, Turfgrass.

Comparison of saturated hydraulic conductivity estimated by surface NMR and empirical equations

This study used eight empirical equations such as Kozeny-Carman (K-C), Terzaghi, Hazen, Slitcher, Kruger, Sauerbrei, NAVFACDM7, and Zamarin to estimate saturated hydraulic conductivity from soil particle size distribution and surface NMR porosity. The estimated empirical hydraulic conductivities were compared with the saturated surface nuclear magnetic resonance (surface NMR) hydraulic conductivity. It was found that most of the empirical equations showed poor correlation with the surface NMR hydraulic conductivity except Kozeny-Carman (KC), Hazen, and Zamarin equations. The value of the coefficient (β) of each equation is modified in such a way as to obtain a linear equation with the unit slope to improve the performance and accuracy of empirical equations. The modified Kozeny-Carman equation showed the maximum correlation R2=0.904, Pearson's r=0.951, and RMSE =6.36 in comparison with other empirical equations. The NAVFACDM7 and the Terzaghi equations showed the highest underestimated hydraulic conductivity data (64%) and overestimated hydraulic conductivity data (38%); however, the Zamarin equation showed the highest overlapped hydraulic conductivity data (44%), respectively, with the 1:1 line.

Fractal Features of Soil Particles as an Indicator of Land Degradation under Different Types of Land Use at the Watershed Scale in Southern Iran

Soil particle-size distribution (PSD) is an important soil feature that is associated with soil erosion, soil fertility, and soil physical and chemical properties. However, very few studies have been carried out to investigate soil degradation using the fractal dimension (D) of the PSD of soils from different land-use types in the calcareous soil of Iran. For this study, 120 soil samples (0–20 cm) were collected from different land-use types in the Fars Province, and various basic soil properties such as soil organic matter (SOM), soil texture fractions, calcium carbonate (CaCO3), pH, and cation-exchange capacity (CEC) were measured. The PSD of the soil samples was determined using the international classification system for soil size fraction, and the D of the PSD was calculated for all soils. The results of this study show that D is significantly correlated with clay content (r = 0.93) followed by sand content (r = −0.54) and CEC (r = 0.51). The mean D values of the forest areas (D = 2.931), with a SOM content of 2.1%, are significantly higher than those of the agricultural land (D = 2.905 and SOM = 1.6%) and pastures (D = 2.910 and SOM = 1.6%), indicating that fine soil particles, particularly clay, have been preserved in forest soils but lost in agricultural and pasture soils. We conclude that agricultural land has experienced significantly higher levels of soil erosion than forest areas.

Comparison of soil particle density determined by a gas pycnometer using helium, nitrogen, and air

AbstractSoil particle density (ρs) is often assumed as 2.65 g cm−3 (density of quartz). The objectives of this study were to compare the use of different gases for determining ρs in a gas pycnometer and relate measured ρs to soil particle size distributions. The ρs of 36 natural soil samples representing 12 USDA textural classes, fine glass beads, crushed granite rock, kaolinite, and bentonite were measured by a commercial gas pycnometer using He, N2, and dry air. The ρs of 30 of the soil samples, glass beads, and crushed rock were also determined with a water pycnometer. The ρs of 36 soil samples determined by He and 30 samples determined by water had narrow ranges with averages of 2.65 and 2.59 g cm−3, respectively. The ρs determined by air and N2 had much wider ranges with averages of 2.93 and 2.97 g cm−3, respectively. There was a near 1:1 relationship between ρs of all samples determined by air and N2 with a highly significant (p < .001) correlation coefficient (r = .99). The average ratio of ρs determined by He and water was 1.03, but the correlation coefficient for their relationship was only .416. Although the relationship between ρs determined by He and either air or N2 was relatively strong (r < .61), the regression coefficient was <.17. There was a strong relationship between soil clay content and ρs determined by N2 or air but a weaker, yet statistically significant (p < .05) relationship when using He.

CHEMICAL STABILIZATION OF GULLIES OF NANKA AND OKO IN ANAMBRA STATE, SOUTH-EASTERN NIGERIA

This study investigated the use 2 mL solution each of AlCl3, CaCl2, Ca(OH)2, MgCl2 and CaCO3 chemicals in stabilizing 10 g and 15 g each of two the gullies in Nanka and Oko towns; and tested with a pocket penetrometer to find out the unconfined compressive strength (UCS). The soil particle size distribution (PSD) were determined also, before treating with the chemical solution. The result from PSD showed that the soil samples had high level of sand in both of them, and low clay content. Also, the stabilizing effects of the chemicals show that AlCl3, CaCl2 and MgCl2 had the highest stabilizing strength on both samples, while CaCO3, Ca(OH)2 showed a low strength. Keyword: Gullies, Erosion, Soil, Stabilization, Penetrometer, Chemical

Evaluating the distribution of soil particle size on glass samples by a new generation of optical microscopy for solar PV applications.

In this work, an image analysis technique combining a new generation optical microscope (Leica DM6 M) and Cleanliness Expert image acquisition and processing software is proposed for the study of dirt particles on PV modules in three different regions: Souss-Massa region, Drâa-Tafilalet region, and Rabat-Salé-Kénitra region. This method offers the possibility of providing an appropriate assessment of the particle size distribution. The analyzed glass samples were installed in these three different regions, on wooden holders tiled 15°, 30°, and 45° and for a period ranging from 64 to 75days. The studies carried out to evaluate the soiling phenomenon based on image processing are very limited and do not take into account the total scanning of the analyzed surface. They are generally limited to a single (one) or a few images taken at different locations of the sample and are then extrapolated over the entire surface. This observation raises the question of the representativeness of the results obtained with respect to the result on the entire surface of the sample. In this context, we thought of carrying out this experimental study, which aims to answer this question and evaluate the particle size of the dirt samples on the PV modules. The results obtained in this study have shown that three images will be enough to represent the whole area of the sample. In addition, the dominant particle diameters by number are in the range of 1-5µm.

Physical and chemical properties of the soils in selected communal property associations of South Africa.

Communal Property Associations (CPAs) rangeland users need more knowledge on the state of their respective grazing lands and also the interaction of soil properties with grazing management implemented. This study aimed to investigate the effect grazing has on the physical and chemical properties of four different soil types found in selected CPAs of the Bela-Bela municipality, they are as follows: Mawela (Hutton-clay loam: HCL), Bela-Bela (Hutton-clay: HC), Moretele (Hutton-loamy sand: HLS) and Ramorula (Ecca sand-clay loam: ESCL).The macro and micro minerals, pH, nitrate-nitrogen, ammonium-nitrogen, organic carbon, soil particle size distribution, acidity and resistance were all measured. All data were subjected to two-way factorial analysis of variance (SAS, 2010). The topsoil was sampled at a depth of 300 mm at an interval of 100 m (100 and 200 m) from the same transect used for woody species data collection resulting in a total of 18 samples per CPA. In each CPA, three camps were selected. In each camp, three transects 200 m apart at the length of 200 m were set. In each transect, soils were drawn at 0, 100 and 200 m making a total of nine soil samples per each camp. The highest (P<0.05) pH (7.14) recorded on the sub-soil was in HLS. Nitrate nitrogen (2.4 mg/kg) concentration on the topsoil was high (P<0.05) in HC soil type. Soil organic carbon for both topsoil (0.66%) and subsoil (0.41%) was significantly lower (P<0.05) in HLS soil type and ESCL soil type respectively. Phosphorus concentration was significantly high (P<0.05) in ESCL soil type for both topsoil (12.86 mg/kg) and sub-soil (1.59 mg/kg). Iron concentration was high in both topsoil (11.8 mg/kg) and sub-soil (7.3 mg/kg) in ESCL soil type. Sub-soil manganese concentration was found to be higher (P<0.05) in ESCL soil type (7.58 mg/kg). Soil resistance (2880 Ω ) measured in topsoil was high (P<0.05) in HCL soil type compared to other soil types. Moreover, for the sub-soil the highest (P<0.05) resistance (least salts) (3640 Ω) was recorded in ESCL soil type. For most of the soil types, the mineral concentration was higher in topsoil than in sub-soil, this trend explains that the uptake of these minerals by plants took place due to the inconsistencies of grazing management employed in these selected CPA farms. It is of colossal significance to properly manage rangelands, to allow a fair-to-good herbaceous layer in the presence of minerals in the soils and farmer should prioritize having enclosures and keeping N-fixing tree species in the rangelands to achieve the above mentioned conditions.

Effects of Ecological Restoration on the Distribution of Soil Particles and Organic Carbon in Alpine Regions

This study discusses the impact of two different ecological restoration approaches on the distribution of soil particle size and organic carbon, expecting to provide references for research on the effects of ecological restoration on the soil carbon pool in alpine regions. By replacing the method of time sampling with spatial sampling, grasslands enclosed only in the growing season and woodlands enclosed all year round were respectively selected as the research objects. Through centrifugation, the soil samples were classified by grain size into sand (50–2000 μm), silt (2–50 μm), and clay (&lt;2 μm) to analyze the distribution of organic carbon in soil particles of different sizes. The major findings were as follows. First, sand accounted for the largest proportion of all the soil components in the grasslands and woodlands that had been restored for different years, followed by silt and clay. Second, most of the organic carbon in the grasslands and woodlands was from sand and silt. As the restoration years increased, the proportion of organic carbon in clay grew in fluctuation. In short, both ecological restoration approaches have improved the soil structure and raised the content of soil organic carbon (SOC). Specifically, the restoration scheme of the woodlands exerted a more significant influence on the soil components and the distribution of organic carbon than that of the grasslands.

Spatial prediction of soil particle size distribution in arid agricultural lands in central Iran

Spatial prediction of soil particle size distribution in arid agricultural lands in central Iran

Use of multifractal parameters to determine soil particle size distribution and erodibility of a physical soil crust in the Loess Plateau, China

Understanding the knowledge of multifractal analysis on particle size distribution (PSD) of soil physical crusts is indispensable for progressing soil surface erosion mode. In this study, hoeing tillage (20 cm long × 15 cm wide × 5 cm deep) were conducted to simulate classic tillage mode in Yangling, China to obtain physical crusts under artificial rainfall (60 mm h−1 intensity with three durations (5, 15, and 30 min)). We defined crusts formed in ridges as structural crust (Cst), formed by infiltration of runoff in hoes as sediment-containing depositional crust (Cscd), and formed by the extraction of runoff as sediment-free depositional crust (Csfd). Soil stratification methods were used to explore physical crust particle sorting. Results represented that the sand content of Cst, Cscd, and Csfd decreased, whereas clay and silt contents increased after rainfall compared to undisturbed soil. There was no significant difference between Cscd and Csfd under short rainfall duration. Three crust types became gradually concentrated in areas with higher density with increasing rainfall duration according to six common parameters in the generalised dimension spectrum (D0, D1, D2, D1/D0, Dv(D-10–D0), and Ds(D0–D10)). Multifractal singularity spectrum (α0, Av, Fv) showed that PSD was most symmetrical in Csfd, followed by Cscd and Cst. Erodibility index KEPIC was largest for Cst, followed by Csfd then Cscd. The relationship between KEPIC and multifractal parameters were significant. Spatial difference caused by tillage activities and rainfall events determine the heterogeneous formation mode, particle size distribution and erodibility of physical crust.

Enhancing Properties of Unfired Clay Bricks Using Palm Fronds and Palm Seeds

The building industry has been thriving all around the world. With global advancement, particularly in technology, real estate development is evolving with the ongoing adoption of new tactics. The current study investigates the performance of palm fronds and palm seeds in enhancing the properties of unfired clay bricks as construction materials. The methodologies used to attain the study's objectives were; determining particle size distribution and Atterberg limits of clay soil, efflorescence, compressive strength, water absorption, and fire resistance of bricks, which were used to give the most appropriate percent of palm fronds and palm seeds for robust bricks. The study required experimental research of the materials used and samples made. Using particle size distribution and Atterberg limits, the soil was classified as clayey soil and low to medium plasticity soil. Batching by weight was achieved using a weighing scale and substitution technique to obtain the proportions of contents in samples. Sample 5, which contained 80% clay, and 20% palm fronds, and sample 6, which contained 65% clay, 25% palm seeds, and 10% palm fronds, passed all the tests. Samples 5 and 6, under efflorescence check, confirmed slight responses where 10% of the brick was covered with a skinny deposit of salts. Under compressive strength, samples 5 and 6 recorded 4.23 N/mm2 and 3.85 N/mm2, respectively, which were more significant than the required minimum compressive strength of fired bricks. For water absorption, they attained a moisture content of 18.1% and 16.1%, respectively, which was in the range of 16–20% under second-class bricks. All bricks passed the fire resistance test, which confirmed that they had a reasonable safety factor. In conclusion, mixes of samples 5 and 6 are recommended to produce robust bricks.

Experimentally and spectroscopically evidenced mechanistic study of butyl peroxyacid oxidative degradation of benzo[a]pyrene in soil.

Benzo[a]pyrene (BaP) is a major indicator of soil contamination and categorized as a highly persistent, carcinogenic, and mutagenic polycyclic aromatic hydrocarbon. An advanced peroxyacid oxidation process was developed to reduce soil pollution caused by BaP originating from creosote spills from railroad sleepers. The pH, organic matter, particle size distribution of soil, and concentrations of BaP and heavy metals (Cd, Cu, Zn, Pb, and As) in the BaP-contaminated soils were estimated. A batch experiment was conducted to determine the effects of organic acid type, soil particle size, stirring speed, and reaction time on the peroxyacid oxidation of BaP in the soil samples. Additionally, the effect of the organic acid concentration on the peroxyacid degradation of BaP was investigated using an oxidizing agent in spiked soil with and without hydrogen peroxide. The results of the oxidation process indicated that BaP and heavy metal residuals were below acceptable Korean standards. A significant difference in the oxidative degradation of BaP was observed between the spiked and natural soil samples. The formation of a peroxyacid intermediate was primarily responsible for the enhanced BaP oxidation. Further, butyric acid could be reused thrice without losing the efficacy (<90%). The systematic peroxyacid oxidative degradation mechanism of BaP was also discussed. A qualitative analysis of the by-products of the BaP reaction was conducted, and their corresponding toxicities were determined for possible field applications. The findings conclude that the developed peroxyacid oxidation method has potential applications in the treatment of BaP-contaminated soils.

Variations of leachate CO2 and N2O concentrations on typical cultivated and natural hillslopes in southeastern hilly area of China

Greenhouse gases dissolved in the soil water and transported through subsurface flow were poorly understood in comparison to their emissions at the soil-atmosphere interface. In this study, leachate CO2 and N2O concentrations were monitored on a tea garden (TG) hillslope (cultivated) and a bamboo forest (BF) hillslope (naturally vegetated) from September 2019 to February 2022 in the south-eastern hilly area of China. Leachate CO2 and N2O concentrations ranged from 1.07 to 9.83 mg C L−1 and from 0.32 to 11.74 μg N L−1, respectively, on the TG hillslope, while they ranged from 0.64 to 25.95 mg C L−1 and from 0.23 to 5.68 μg N L−1, respectively, on the BF hillslope. On both hillslopes, leachate CO2 concentrations were the greatest in summer, while they were the lowest in winter. On the TG hillslope, the highest and the lowest leachate N2O concentrations were observed in spring and summer, respectively, while on the BF hillslope, they were observed in autumn and winter, respectively. On both hillslopes, soil temperature, precipitation during the previous 15 days, and matrix potential were positively related to the leachate CO2 concentrations but not related to the leachate N2O concentrations. Soil water content was positively related to both leachate CO2 and N2O concentrations, while such relationships with groundwater table depth were negative. Leachate total inorganic nitrogen and soil total inorganic nitrogen concentrations were positively related to the leachate N2O concentration on the TG hillslope, while such relationships were not observed on the BF hillslope. Spatial variations of leachate CO2 and N2O concentrations were mainly influenced by land covers, terrain attributes (slope, elevation), soil particle size distribution, bulk density and soil organic matter content. The findings of this study supplemented the knowledge of soil water dissolved CO2 and N2O in the cultivated and naturally vegetated land covers. Further researches are needed to quantify the CO2 and N2O losses through subsurface flow and their contributions to the total soil CO2 and N2O losses.

Effects of Different Vegetation Restoration Types on the Fractal Characteristics of Soil Particles in Earthy-Rocky Mountain Area of Northern China

The fractal characteristics of soil particle-size distribution (PSD) constitute an important soil physical property, and fractal models of soil PSD are increasingly used to describe the effects of vegetation on the improvement of soil-related properties. Based on the fractal theory, this paper selected four typical vegetation restoration types (Quercus acutissima, QAC; Robinia pseudoacacia, RPL; Pinus densiflora, PDS; QAC × PDS) in the Taiyi mountainous area as the research object, and the single-fractal dimension (D) and multi-fractal parameters of PSD and its correlation with soil-associated properties were studied. The results show that (1) QAC × PDS reduced the heterogeneity of soil sand distribution, which also increased the range and concentration of soil PSD in the dense area. Soil clay and silt contents showed QAC × PDS &gt; RPL &gt; QAC &gt; PDS. QAC × PDS significantly increased clay and silt content in 0–20 cm soil. (2) D varies among different vegetation restoration types, which was QAC × PDS &gt; RPL &gt; QAC &gt; PDS, and the D of 0–20 cm soil was greater than that of 20–40 cm. For the multi-fractal parameters of PSD, the capacity dimension (D0), information dimension (D1), correlation dimension (D2) and D1/D0 in 0–20 cm soil of different vegetation restoration types showed significant differences. (3) D and multi-fractal parameters were significantly positively correlated with clay and silt contents, which were significantly negatively correlated with sand contents. (4) QAC × PDS had the smallest soil bulk density and largest porosity. Fractal dimension was negatively correlated with soil bulk density and positively correlated with soil total porosity and capillary porosity. These results indicate that the soil fractal dimension can well characterize the vegetation improvement on soil structure and properties in the earthy-rocky mountain areas of northern China.

Releasing Atmospheric Martian Dust in Sand Grain Impacts

Emission of dust up to a few microns in size by impacts of sand grains during saltation is thought to be one source of dust within the Martian atmosphere. To study this dust fraction, we carried out laboratory impact experiments. Small numbers of particles of about 200 μm in diameter impacted a simulated Martian soil (bimodal Mars Global Simulant). Impacts occurred at angles of ∼18° in vacuum with an impact speed of ∼1 m s−1. Ejected dust was captured on adjacent microscope slides and the emitted particle size distribution (PSD) was found to be related to the soil PSD. We find that the ejection of clay-sized dust gets increasingly harder the smaller these grains are. However, in spite of strong cohesive forces, individual impacts emit dust of 1 μm and less, i.e., dust in the size range that can be suspended in the Martian atmosphere. More generally, the probability of ejecting dust of a given size can be characterized by a power law in the size range between 0.5 and 5 μm (diameter).

Distribution characteristics of microplastics in the soil of mangrove restoration wetland and the effects of microplastics on soil characteristics.

The dense vegetation in the wetland could effectively retain microplastic particles, and the distribution of microplastics varied significantly under different planting densities. In addition, microplastics in the soil environment can affect soil properties to a certain extent, which in turn can affect soil functions and biodiversity. In this study, we investigated the distribution of soil microplastics in a mangrove restoration wetland under different planting densities and their effects on wetland soil properties. The results indicated that the average abundance of soil microplastics was 2177.5 n/500 g, of which 70.9% exhibited a diameter ranging from 0.038-0.05 mm, while the remaining soil microplastics accounted for less than 20% of all microplastics, indicating that smaller-diameter microplastics were more likely to accumulate in wetland soil. The microplastic abundance could be ranked based on the planting density as follows: 0.5 × 0.5 m > 1.0 × 0.5 m > 1.0 × 1.0 m > control area. Raman spectroscopy revealed that the predominant microplastic categories in this region included polyethylene terephthalate (PET, 52%), polyethylene (PE, 24%) and polypropylene (PP, 15%). Scanning electron microscopy (SEM) images revealed fractures and tears on the surface of microplastics. EDS energy spectra indicated a large amount of metal elements on the surface of microplastics. Due to the adsorptive features of PET, this substance could influence the soil particle size distribution and thus the soil structure. All physicochemical factors, except for the soil pH, were significantly affected by PET. In addition, the CV analysis results indicated that soils in vegetated areas are more susceptible to PET than are soils in bare ground areas, leading to greater variation in their properties.

Base cation evidence for enhanced water infiltration in Ancestral Pueblo gravel mulch fields, Northern New Mexico, USA

AbstractIn the Northern Rio Grande region of New Mexico, USA, Ancestral Pueblo villages experienced rapid demographic and economic growth in the late 14th and 15th centuries A.D. Recent research has proposed that this growth was underwritten by cotton production for exchange. Gravel mulch was an important component of cotton agriculture, but its function and soil legacies are not well understood. Since water management was likely a critical feature of gravel mulch, this study examines soil variables affected by changes to water supply. Gravel mulch analyzed in this study was found to have a substantial impact on the surface soil particle size distribution, but other aspects of soil quality were unaffected. The depth profiles of base cation ratios in mulched and unmodified locations suggest that gravel mulch continues to enhance water infiltration. Based on the timing of cotton development and inferred infiltration depths associated with gravel mulch soils, gravel mulch technology is well suited to the monsoonal precipitation regime of the region and the phenology of cotton.

Soil particle size prediction using Vis-NIR and pXRF spectra in a semiarid agricultural ecosystem in Central Anatolia of Türkiye

The recent technologies employed for rapid, cost-effective, and non-destructive prediction of soil particle size distribution (clay, sand, and silt) are becoming increasingly interesting among soil scientists. Our aims were to explore the effect of surface, profile wall, and surface + profile wall on prediction accuracy using individual and combined both soil spectra (Vis-NIR and pXRF) with machine learning algorithms for sand, silt, and clay. In total, 191 soil samples were collected from the soil surface (0–30 cm) and profile wall (1 m × 1 m) from cultivated fields in Eskisehir, Central Anatolia of Türkiye. The pXRF (0–45 keV) and Vis-NIR (350–2500 nm) spectroradiometers were used to obtain soil spectra from sieved soil samples. The prediction accuracy of each soil particle size was evaluated by 54 models to explore the predictive performance. The five machine learning algorithms (elastic net, lasso, random forest, ridge, and support vector machine-linear) were applied with calibration (70% soil samples) and validation (30% soil samples) data set for each soil particle size.Results showed the dominant clay mineral in the A and C horizons is chlorite. Moderate and high prediction accuracy for sand (R2 = 0.56–0.84) and clay (R2 = 0.61–0.80), whereas only moderate prediction accuracy for silt (R2 = 0.47–0.55) using both soil spectra in the surface, profile wall, and surface + profile wall. The highest prediction accuracy for each soil particle size was achieved in the soil profile wall using Vis-NIR spectra with elastic net, which outperformed other samplings such as individual pXRF, combined both soil spectra, and other machine learning algorithms. In addition, the prediction accuracy of clay was more affected by sampling strategies compared to sand and silt. We concluded that individual Vis-NIR spectroradiometer can be utilized to achieve the highest prediction accuracy for sand, silt, and clay ratio in semiarid ecosystems for soil surveys and land use studies.

Multifractal Features of Particle-Size Distribution and Their Relationships With Soil Erosion Resistance Under Different Vegetation Types in Debris Flow Basin

Understanding the influence of vegetation types on soil particle-size distribution (PSD) is essential to evaluate the effects of sediment control by vegetation restoration. In this work, we studied the effects of different vegetation types, including bare land, meadow, shrub and forest on soil PSD in Jiangjiagou gully, Yunnan province, China. A total of 60 soil samples were collected and analyzed for soil particle size distribution using the laser diffraction method. Fractal theory was used to calculate multifractal parameters. The volume fraction of silt particles in shrub and forest is significantly higher than that in bare land, meadow, whereas the total volume fraction of sand particles in bare land and meadow exceed that in shrub and forest. The soil particle size distribution along soil layers has no significant difference in each vegetation type. The volumetric fractal dimension is significantly higher in forest and shrub than in bare land and grassland, but there is no significant difference between forest and shrub. In addition, soil erosion resistance exhibits significant differences of forest &amp;gt; shrub &amp;gt; grassland &amp;gt; bare land. Multifractal parameters are highest in bare land except for multifractal spectrum values (f (αmax) and f (αmin)) and the maximum value of singularity index (αmin). All generalized dimensions spectra curves of the PSD are sigmoidal, whereas the singular spectrum function shows an asymmetric upward convex curve. Furthermore, soil erosion resistance has significant relationships with multifractal parameters. Our results suggest that multifractal parameters of the soil PSD can predict its anti-ability to erosion. This study also provides an important insight for the evaluation of soil structure improvement and the effects of erosion control by vegetation restoration in dry-hot valley areas.

C:N ratios of bulk soils and particle-size fractions: Global trends and major drivers

C:N ratios are the most ancillary and available proxy for soil organic matter (SOM) chemical composition and quality in the literature, but there is surprising little information on how it is affected by environmental factors. To address this knowledge gap, we searched the global literature and gathered information from 74 studies conducted between 1980 and 2019, covering 29 countries and a wide range of variation environmental settings. We compiled data on soil organic carbon (SOC), total N (TN) and C:N ratios in bulk soil and, for the first time, within soil particle-size fractions – sand, silt, and clay. Correlation and random forest statistical analyses showed that SOC and TN contents were mostly controlled by macroscale, climatic drivers, namely temperature and precipitation, whereas soil C:N ratios were more responsive to microscale drivers, e.g. soil particle-size distribution. Specifically, C:N ratios in bulk soil were most strongly correlated with sand contents (r = 0.52; p < 0.001), consistent with the high C:N of sand-sized SOM (median 16.7). Otherwise, clay-sized SOM showed much less variation in C:N ratios (5.0–17.6, median 9.6), regardless of sampling depth and land use. Clay C:N ratios were only consistently lower under arid climate types. Silt-sized SOM showed intermediate C:N ratios (median 13.1) relative to sand and clay-sized fractions. Hence, our results suggest a preferential immobilization of N-enriched SOM onto clay-sized particles coupled to a segregation of N-depleted SOM in sand-sized fractions. Although bulk soil C:N increased with sand contents, the accumulation of N-depleted SOM within sand-sized fractions increased with clay content. Overall, by identifying the complementarity of macro- and microscale factors underpinning soil C and N pools and their C:N ratios, our results contribute to reduce the inherent complexity to model SOM cycling across global to local scales.