Variability Of Soil Properties Research Articles

PVD-Aided Consolidation with Spatial Variations in Soil Properties and Initial Excess Pore Pressure

PVD-Aided Consolidation with Spatial Variations in Soil Properties and Initial Excess Pore Pressure

Effect of Spatial Variability of Soil Properties on Bearing Capacity of Strip Footing under Fuzzy Uncertainty

AbstractThe present study investigates the effect of spatial variability of soil parameters on the probability of failure of strip footings against bearing pressure resting on a homogeneous and two...

Assessing the Suffusion Susceptibility of the Homogeneous Earth Dam Body Considering Spatial Variability of Soil Properties

The suffusion susceptibility of the soil samples is evaluated through an erosion resistance index. The erosion resistance index is estimated from several soil parameters thanks to existing statistical analyses. In actual exploitation, the soil properties with the input parameters are related to the grain distribution of the soil. Vary greatly from the original design value due to the influence of many factors. One of the factors is the inherent variability. Inherent soil variability is modeled as a random field. The usual problems used to assess the suffusion susceptibility maybe not give accurate results or fully evaluate the actual working ability of the ground in each case. That is one of the reasons why dams are still eroded when they are put into use. The paper aims to assess the suffusion susceptibility of the earth dam body using a two-dimensional (2D) Stochastics random field, modeling the initial problem, considering the variability spatial of soil properties, using the assumption of a Normal random field of soil characteristics parameters. The research goals predict the two-dimensional spatial variability of erosion resistance index of the dam body, probability of suffusion susceptibility, and the variability spatial of density and internal friction angle. An illustration of a numerical simulation of a homogeneous earth dam body is presented in this paper. The scientific novelty of the paper shows the predicted results of the two-dimensional spatial variability of erosion resistance index with a contour map and probability of suffusion susceptibility of the homogeneous earth dam body. Furthermore, the two-dimensional spatial variability maps of density and internal friction angle are also shown.

Effect of environmental factors on soil properties under different land use types in a typical basin of the North China Plain

Soil physicochemical properties can not only reflect ecosystem integrity, land quality and biogeochemical processes, but also are impacted by diverse land use types formed by intensive human activities. Exploring the comprehensive function of land use types and environmental factors on soil properties are of great significance for the relative land management, nutrition cycling and agricultural sustainable development. And little previous studies considered the inherent relations between soil properties under the dual effects of the above two, especially in an area with high land use intensity. This study tried to achieve the comprehensive research of human activities and environmental factors on soil properties through the study of the functions on soil properties from the environment factors under different land use types in the Beijing-Tianjin-Hebei region, which is a typical area with the most intense human activities in China. In this study, soil samples were collected in an area typified by intensive human activities in the Baiyangdian Watershed in the Beijing-Tianjin-Hebei region. The relationships between soil properties and environmental factors as well as the relationships between soil properties and land use intensity were explored by principal component analysis and geographically weighted regression (GWR) respectively. Additionally, impacts on soil properties from environmental factors were explored by structural equation modeling (SEM). GWR results suggested that pH was positively related to land use intensity (LUI); comparatively, all other soil properties were negatively related to LUI. SEM results showed that precipitation, temperature, and elevation all had direct and indirect influences on soil properties. Moreover, soil organic carbon was not only directly affected by environmental factors, but also indirectly through total phosphorus content in residential areas and plain farmland, pH in mountainous farmland areas, and bulk density in residential areas and mountainous farmland. Our work focus on the combined function of environmental factors and land uses on soil properties under various land use types with different human activities intensities. Our main conclusion from the above findings was that precipitation and temperature are both important factors that impact soil properties. High temperature and improper agricultural activities also reduced soil carbon accumulation. These findings underscore that scientific fertilizer addition during farming and soil quality management such as planning a proper reclamation range should be advocated in areas with intensive human activities. Taken together, our research will allow for a better understanding of the variations in soil properties and other influential factors in the context of human activities.

Geo-spatial Assessment of Soil Quality Index of Alirajpur District of Madhya Pradesh, India

Information regarding spatial variability and distribution of soil properties is critical for stakeholders attempting to increase nutrients use efficiency and crop productivity. The soils of Alirajpur district having the bulk density, pH, EC, OC and CaCO3 varied from4.70 to 8.40, 0.03 to 0.90 dSm-1, 0.47 to 12.92 g kg-1 and 5.0 to 115.0 g kg-1 soil, respectively. Available N, P, K and S content in soils of Alirajpur district ranged from 76.0 to 382.0 kg ha-1, 1.34 to 62.13 kg ha-1, 53.52 to 529.85 kg ha-1 and 0.55 to 33.90 mg kg-1 soil, respectively. Zn, Cu, Fe, Mn and B contents in soil varied from 0.03 to 1.98, 0.06 to 3.74, 1.07 to 36.0, 1.34 to 43.0 and 0.03 to 4.76 mg kg-1 soil, respectively. The categories of the soil fertility status were made with respect to N, P, K and S as medium, high, medium and low (M-H-M-L). The 64.71%, 93.01% and 25.37% soil samples were observed to be low in S, Zn and Fe, respectively. The results revealed that none of the samples were tested low in Cu and Mn and these are not a major problem in Alirajpur district. Correlation analyses among the above highly weighted variables were done to remove the redundant variables, accordingly OC and N, Fe and Mn, CaCO3 and Zn were highly correlated, and finally OC, Fe and Zn were retained owing to their high factor loading. The sensitive indicators (Minimum dataset) under the soils of Alirajpur District in descending order of importance as revealed by factor analysis were as follows: OC > Fe > Zn > B > EC > K > MBC.
 The sensitive indicators under the soils of Alirajpur district in descending order of importance as revealed by factor analysis were as follows: OC > Fe > Zn > B > EC > K > MBC. This suggests that these indicators may be used in future for characterizing the state of soil conditions of district. Soil quality index rating ranged from 0.22 to 0.31 under the different blocks and 0.22 for district as whole with l parameter soil quality index 0.31 for Alirajpur district.

Mapping of soil organic carbon using machine learning models: Combination of optical and radar remote sensing data

AbstractSoil organic C (SOC) plays an important role in soil quality. Thus, it is of great significance to know the spatial distribution characteristics of SOC. Environmental variables, such as natural predictors, remote sensing (RS) variables, and digital soil mapping approaches have been widely used in SOC prediction. However, it is still challenging to determine which methods and variables are effective to map SOC in farmland. In this study, we compare the performance of three machine learning models, including random forest, Cubist, and the support vector machine model for the prediction of SOC contents using RS variables, topographic variables, climate variables, soil property variables, and spatial position variables as environmental covariates. The recursive feature elimination (RFE) technique was used to select optimal variables. Of the 130 sampling sites of the cultivated layer that were collected in Shanggao county, 70% of the data were used for training and 30% for validation. Prediction accuracy and uncertainty was quantified using the bootstrap approach with 100 iterations. The performance of the model was verified by the mean absolute error, RMSE, R2, and Lin's concordance correlation coefficient (CCC); the SD was used as a measure of prediction uncertainty. Results showed that the Cubist model combined with the RFE method (Cubist_RFE) had a mean R2, RMSE, and SD of .84, 2.39 g kg–1, and 0.73 g kg–1, respectively, which showed the highest prediction accuracy and the lowest uncertainty. The soil property variables (soil alkaline hydrolysis N and pH) and RS variables (soil adjusted vegetation index, enhanced vegetation index, and band7 of Sentinel‐2) were the controlling factors of SOC prediction. Thus, the results indicate the potential of the Cubist model in SOC prediction, and the combination of the optical and radar RS data is a viable way for predicting SOC.

Variation in soil properties and its influence on the dynamic change of soil erosion resistance to overland flow in the water-level fluctuation zone of the Three Gorges Reservoir, China

The water level fluctuations, rainstorms, and plants could lead to the variation in soil properties in the water-level fluctuation zone (WLFZ) and thus may influence the soil erosion resistance (soil erodibility, Kr, and critical shear stress, τc). However, variation in soil properties and its influence on the dynamic change of soil erosion resistance to overland flow in the WLFZ of the Three Gorges Reservoir (TGR) still unclear and need to be further quantified. Therefore, soil samples from different elevations were collected along a slope profile at different times in the WLFZ of the TGR, then the soil properties and plant biomass were measured and the soil detachment capacity (Dc) were estimated by conducting a scouring experiment. Then the Kr and τc were obtained according to the linear relationship between Dc and shear stress. The results indicated that most measured soil properties suffered low variability but organic matter content showed the moderate variability. Kr varied from 0.10 to 0.17 s m−1 and τc varied in the range of 1.56–2.24 Pa for all sampling points, and both showed spatial and temporal variations. Kr decreased with increasing elevation until reaching a minimum value and then increased spatially, while it showed a decreasing trend or a decreasing trend followed by an increasing trend over time for different elevation segments temporally. τc increased with increasing elevation spatially and increased or showed an increase followed by a decrease over time for different elevation segments temporally. Kr was significantly influenced by clay, silt, and sand content, mean weight diameter and soil organic matter content, while τc was only affected by clay content. These research results highlight the dynamic change of soil erosion resistance and are helpful for understanding the spatial and temporal variations in soil erosion resistance in the WLFZ of the TGR area.

Mapping soil nutrients via different covariates combinations: theory and an example from Morocco

BackgroundMapping of soil nutrients using different covariates was carried out in northern Morocco. This study was undertaken in response to the region's urgent requirement for an updated soil map. It aimed to test various covariates combinations for predicting the variability in soil properties using ordinary kriging and kriging with external drift.MethodsA total of 1819 soil samples were collected at a depth of 0–40 cm using the 1-km grid sampling method. Samples were screened for their pH, soil organic matter (SOM), potassium (K2O), and phosphorus (P2O5) using standard laboratory protocols. Terrain attributes (T) computed using a 30-m resolution digital elevation model, bioclimatic data (C), and vegetation indices (V) were used as covariates in the study. Each targeted soil property was modeled using covariates separately and then combined (e.g., pH ~ T, pH ~ C, pH ~ V, and pH ~ T + C + V). k = tenfold cross-validation was applied to examine the performance of each employed model. The statistical parameter RMSE was used to determine the accuracy of different models.ResultsThe pH of the area is slightly above the neutral level with a corresponding 7.82% of SOM, 290.34 ppm of K2O, and 100.86 ppm of P2O5. This was used for all the selected targeted soil properties. As a result, the studied soil properties showed a linear relationship with the selected covariates. pH, SOM, and K2O presented a moderate spatial autocorrelation, while P2O5 revealed a strong autocorrelation. The cross-validation result revealed that soil pH (RMSE = 0.281) and SOM (RMSE = 9.505%) were best predicted by climatic variables. P2O5 (RMSE = 106.511 ppm) produced the best maps with climate, while K2O (RMSE = 209.764 ppm) yielded the best map with terrain attributes.ConclusionsThe findings suggest that a combination of too many environmental covariates might not provide the actual variability of a targeted soil property. This demonstrates that specific covariates with close relationships with certain soil properties might perform better than the compilation of different environmental covariates, introducing errors due to randomness. In brief, the approach of the present study is new and can be inspiring to decision-makers in the region and other world areas as well.

Variability of Potential Soil Nitrogen Cycling Rates in Stormwater Bioretention Facilities

Low-impact development (LID) is a common management practice used to infiltrate and filter stormwater through vegetated soil systems. The pollutant reduction potential of these systems is often characterized by a single pollutant removal rate; however, the biophysical properties of soils that regulate the removal of pollutants can be highly variable depending on environmental conditions. The goal of this study was to characterize the variability of soil properties and nitrogen (N) cycling rates in bioretention facilities (BRFs). Soil properties and potential N cycling processes were measured in nine curbside bioretention facilities (BRFs) in Portland, OR during summer and winter seasons, and a subset of six sites was sampled seasonally for two consecutive years to further assess temporal variability in soil N cycling. Potential N cycling rates varied markedly across sites, seasons, and years, and higher variability in N cycling rates was observed among sites with high infiltration rates. The observed seasonal and annual changes in soil parameters suggest that nutrient removal processes in BRFs may be highly variable across sites in an urban landscape. This variability has important implications for predicting the impacts of LID on water quality through time, particularly when estimated removal rates are used as a metric to assess compliance with water quality standards that are implemented to protect downstream ecosystems.

Assessment of Soil Redistribution Following Land Rehabilitation with an Apple Orchard in Hilly Regions of Central Iran

This study was executed to explore soil redistribution and soil quality changes induced by land degradation and then rehabilitation by orchard plantation in different slope positions in a semi-arid region in central Iran. A total of 72 surface soil samples (0–30 cm) were collected from three land uses (natural rangelands, dryland farming, and apple orchards) in four slope positions (shoulder, backslope, footslope, and toeslope). The soil physicochemical properties and magnetic parameters were measured, and soil redistribution was determined in the selected soil samples using the 137Cs technique. The results showed that rangeland degradation and, subsequently, rainfed cultivation, led to a significant decline in the soil quality indicators, such as soil organic matter (SOM), total nitrogen (TN), available potassium (Kava), and available phosphorous (Pava), thus incurring further soil loss, as determined by the 137Cs technique. Conversely, the conversion and rehabilitation of drylands to apple orchards cultivated on the contour terraces improved soil quality significantly and decreased soil loss (p < 0.05) and soil quality grade (p < 0.01). Additionally, the findings indicated that slope positions relative to land use change had a reasonable impact on the variability of soil properties and soil loss and deposition. The results of 137Cs analysis showed that the drylands had the highest soil loss (185.3 t ha−1 yr−1) and maximum sedimentation (182. 5 t ha−1 yr−1) in the shoulder and footslope positions, respectively. The random forest model applied between 137Cs inventory and soil properties indicated that calcium carbonate equivalent (CCE), TN, Pava, Kava, and bulk density (ρb) could explain 75% of the total variability in 137Cs inventory with high R2 (0.94) and low RMSE (111.29). Magnetic measurements have shown great potential as a cost-effective and fast method for assessing soil redistribution in hilly regions, as confirmed by the findings of the 137Cs analysis, which agreed well with the magnetic susceptibility at low frequency (χlf). Overall, the results confirmed that restoring abandoned dryland by orchard cultivation may improve soil quality and diminish soil loss in the semi-arid region of Iran. However, further research is required to assess other aspects of the ecosystem affected by this restoration.

Modeling Soil Organic Carbon Changes under Alternative Climatic Scenarios and Soil Properties Using DNDC Model at a Semi-Arid Mediterranean Environment

Soil organic carbon (SOC) is one of the central issues in dealing with soil fertility as well as environmental and food safety. Due to the lack of relevant data sources and methodologies, analyzing SOC dynamics has been a challenge in Morocco. During the last two decades, process-based models have been adopted as alternative and powerful tools for modeling SOC dynamics; whereas, information and knowledge on the most sensitive model inputs under different climate, and soil conditions are still very limited. For this purpose, a sensitivity analysis was conducted in the present work, using the DeNitrification-DeComposition (DNDC) model based on the data collected at a semi-arid region (Merchouch station, Morocco). The objective is to identify the most influential factors affecting the DNDC-modeled SOC dynamics in a semi-arid region across different climatic and soil conditions. The results of sensitivity analysis highlighted air temperature as the main determinant of SOC. A decrease in air temperature of 4 °C results in an almost 161 kg C ha−1 yr−1 increase in C sequestration rate. Initial SOC was also confirmed to be one of the most sensitive parameters for SOC. There was a 96 kg C ha−1 yr−1 increase in C sequestration rate under low initial SOC (0.005 kg C ha−1). In the DNDC, air temperature in climatic factors and initial SOC in variable soil properties had the largest impacts on SOC accumulation in Merchouch station. We can conclude that the sensitivity analysis conducted in this study within the DNDC can contribute to provide a scientific evidence of uncertainties of the selected inputs variables who can lead to uncertainties on the SOC in the study site. The information in this paper can be helpful for scientists and policy makers, who are dealing with regions of similar environmental conditions as Merchouch Station, by identifying alternative scenarios of soil carbon sequestration.

Spatial Variability of Soil Properties and Its Effect on Maize Yields within Field—A Case Study in Hungary

To better understand the potential of soils, understanding how soil properties vary over time and in-field is essential to optimize the cultivation and site-specific technologies in crop production. This article aimed at determining the within-field mapping of soil chemical and physical properties, vegetation index, and yield of maize in 2002, 2006, 2010, 2013, and 2017, respectively. The objectives of this five-year field study were: (i) to assess the spatial and temporal variability of attributes related to the maize yield; and (ii) to analyse the temporal stability of management zones. The experiment was carried out in a 15.3 ha research field in Hungary. The soil measurements included sand, silt, clay content (%), pH, phosphorous (P2O5), potassium (K2O), and zinc (Zn) in the topsoil (30 cm). The apparent soil electrical conductivity was measured in two layers (0–30 cm and 30–90 cm, mS/m) in 2010, in 2013, and in 2017. The soil properties and maize yields were evaluated in 62 management zones, covering the whole research area. The properties were characterized as the spatial-temporal variability of these parameters and crop yields. Classic statistics and geostatistics were used to analyze the results. The maize yields were significantly positively correlated (r = 0.62–0.73) with the apparent electrical conductivity (Veris_N3, Veris_N4) in 2013 and 2017, and with clay content (r = 0.56–0.81) in 2002, 2013, and 2017.

Soil Water Content Shapes Microbial Community Along Gradients of Wetland Degradation on the Tibetan Plateau.

Soil microbes are important components in element cycling and nutrient supply for the development of alpine ecosystems. However, the development of microbial community compositions and networks in the context of alpine wetland degradation is unclear. We applied high-throughput 16S rRNA gene amplicon sequencing to track changes in microbial communities along degradation gradients from typical alpine wetland (W), to wet meadow (WM), to typical meadow (M), to grassland (G), and to desert (D) in the Zoige alpine wetland region on the Tibetan Plateau. Soil water content (SWC) decreased as wetland degradation progressed (79.4 and 9.3% in W and D soils, respectively). Total organic carbon (TOC), total nitrogen (TN), and total phosphorus (TP) increased in the soils of WM, and then decreased with alpine wetlands degradation from WM to the soils of M, G, and D, respectively. Wetland degradation did not affect microbial community richness and diversity from W soils to WM, M, and G soils, but did affect richness and diversity in D soils. Microbial community structure was strongly affected by wetland degradation, mainly due to changes in SWC, TOC, TN, and TP. SWC was the primary soil physicochemical property influencing microbial community compositions and networks. In wetland degradation areas, Actinobacteriota, Acidobacteriota, Cholorflexi, and Proteovacteria closely interacted in the microbial network. Compared to soils of W, WM, and M, Actinobacteriota played an important role in the microbial co-occurrence network of the G and D soils. This research contributes to our understanding of how microbial community composition and networks change with varied soil properties during degradation of different alpine wetlands.

Distribution and influencing factors of soil organic carbon in a typical karst catchment undergoing natural restoration

Understanding the distribution patterns and controlling factors of soil organic carbon (SOC) in karst areas is important for soil carbon management. However, due to the wide variety of human activities and karst habitats, the factors influencing SOC in karst areas vary. A typical catchment undergoing natural restoration in the karst region of South China was investigated to determine the distribution and variation of soil properties and SOC stocks (SOCSs) under three types of terrain: a hillslope, a depression and a sinkhole. The factors influencing SOC under the different terrain types were determined by redundancy analysis and multiple linear regression modelling. The results indicated that terrain and hydrological conditions affect the distribution of SOC on the hillslope. The spatial heterogeneity of SOC and dissolved organic carbon (DOC) on the hillslope was high. Terrain type and land use differences significantly affected the SOC and DOC concentrations at the catchment scale. SOC loss was more serious in the depression due to agricultural activities, and SOC accumulation was more obvious on the hillslope due to its relatively long natural restoration period. The average SOCSs of the hillslope were 16.5% and 54.6% larger than those of the depression and sinkhole, respectively, and the average dissolved organic carbon stocks (DOCSs) were 70.6% and 179.7% larger, respectively. In addition, the impacts of environmental factors on SOC and DOC varied among the different terrain types. Soil texture and topography were the main factors controlling the distribution of SOC and DOC on the hillslope and in the whole catchment, and soil texture was the main factor controlling SOC at the catchment scale. In addition, soil loss through sinkholes may be an important carbon sink in karst areas. The results of this study are of great significance for evaluating soil carbon storage and vegetation restoration strategies in karst areas.

Effect of grazing exclusion on soil bacterial community links with variations in soil properties but not in vegetation characteristics

Effect of grazing exclusion on soil bacterial community links with variations in soil properties but not in vegetation characteristics

Variability of soil properties in Sikhe village under Lower Subansiri district, Arunachal Pradesh

The study was conducted under three land uses, viz., terrace, jhum and forest to assess the variability of soil properties in Sikhe village under Lower Subansiri district, Arunachal Pradesh. The soil pH was strong to moderate acidic in reaction (pH 4.6 to 6.1). Organic carbon ranged from 10.7 to 46.0 g kg-1 which was found to be highest in forest ecosystem among the land uses. Cation exchange capacity (CEC) ranged between 7.9 and 22.8 cmol (p+) kg -1 and had significant positive correlation with organic carbon (r=0.68**). Bulk density varied from 1.10 to 1.56 Mg m-3, and showed significant negative correlation with organic carbon(r= -0.61*). Bulk density of forest was recorded to be the lowest. Water holding capacity (WHC) varied from 37.0 to 64.2 %, and was found higher under forest land use. WHC had significant positive correlation with organic carbon (r=0.55*) and significant negative one with sand (r=-0.62*). Hydraulic conductivity varied from 0.21 to 1.86 cm hr-1, and was found lowest under terrace land uses. Water stable aggregates (WSA > 0.25) ranged from 83.0 to 96.8 %. Mean weight diameter of the soil varied from 0.52 to 0.88 mm. The textural classes of various soils under different land use systems were loam, sandy loam and silt loam. The dispersion ratio varied from 30.2 to 47.9, which was very high in all the land uses. It had significant positive correlation with sand (r=0.76**) and significant negative correlation with organic carbon (r= -0.74**) and clay (r=-0.56**). Erosion index ranged from 48.1 to 89.9, and the highest was observed under terrace land use and lowest under forest land use. Erosion index had significant positive correlation with sand (r=0.72**) and dispersion ratio (r=0.74**) and significant negative one with organic carbon (r=-0.69**) and clay (r=-0.68**). The dispersion ratio and erosion index of all the land uses were very high indicating that the soils are highly erodible.

Variability of soil properties in Sikhe village under Lower Subansiri district, Arunachal Pradesh

The study was conducted under three land uses, viz., terrace, jhum and forest to assess the variability of soil properties in Sikhe village under Lower Subansiri district, Arunachal Pradesh. The soil pH was strong to moderate acidic in reaction (pH 4.6 to 6.1). Organic carbon ranged from 10.7 to 46.0 g kg-1 which was found to be highest in forest ecosystem among the land uses. Cation exchange capacity (CEC) ranged between 7.9 and 22.8 cmol (p+) kg -1 and had significant positive correlation with organic carbon (r=0.68**). Bulk density varied from 1.10 to 1.56 Mg m-3, and showed significant negative correlation with organic carbon(r= -0.61*). Bulk density of forest was recorded to be the lowest. Water holding capacity (WHC) varied from 37.0 to 64.2 %, and was found higher under forest land use. WHC had significant positive correlation with organic carbon (r=0.55*) and significant negative one with sand (r=-0.62*). Hydraulic conductivity varied from 0.21 to 1.86 cm hr-1, and was found lowest under terrace land uses. Water stable aggregates (WSA > 0.25) ranged from 83.0 to 96.8 %. Mean weight diameter of the soil varied from 0.52 to 0.88 mm. The textural classes of various soils under different land use systems were loam, sandy loam and silt loam. The dispersion ratio varied from 30.2 to 47.9, which was very high in all the land uses. It had significant positive correlation with sand (r=0.76**) and significant negative correlation with organic carbon (r= -0.74**) and clay (r=-0.56**). Erosion index ranged from 48.1 to 89.9, and the highest was observed under terrace land use and lowest under forest land use. Erosion index had significant positive correlation with sand (r=0.72**) and dispersion ratio (r=0.74**) and significant negative one with organic carbon (r=-0.69**) and clay (r=-0.68**). The dispersion ratio and erosion index of all the land uses were very high indicating that the soils are highly erodible.

Geophysical and contamination assessment of soil spatial variability for sustainable precision agriculture in Omu-Aran farm, Northcentral Nigeria

The spatial and temporal variability of soil properties (fluid composition, structure, and water content) and hydrogeological properties employed for sustainable precision agriculture can be obtained from geoelectrical resistivity methods. For sustainable precision agricultural practices, site-specific information is paramount, especially during the planting season. An integrated one-dimensional (1D) and two-dimensional (2D) electrical resistivity survey have been adopted to characterize the subsoil parameters and delineate the aquifer unit of large farm areas, especially in precision agricultural practices. Also, contamination assessment reveals the soil quality status of farmlands. This study aims to determine the site-specific soil parameters of a commercial farm in Omu-Aran, Northcentral, Nigeria. The subsoil features from the geoelectrical resistivity surveys indicate 3 to 4 distinctive lithology to a depth of 43.4 m into the subsurface of the farm. The ID (Vertical Electrical Sounding) and 2D resistivity inversion models results have revealed the heterogeneity nature of the topsoil, also known as the stone zone comprising of reworked clayey soil and sandy gravelly soil, the weathered/saprolite zone (gravelly sandy/sandy soil), the fractured basement and the fresh basement rock. Contamination factor (Cf), pollution load index (PLI) and Nemerow integrated pollution index (NIPI) were used to assess the contamination index on the farmland. Toxic elements such as arsenic, cadmium, chromium, cobalt, lead, manganese, nickel, and zinc have low to moderate contamination in the farm. The depth of investigation (≤3m) covers the upper root zone of significant crops grown in the area. The findings can assess soil contamination, delineate basement features, subsoil variability, soil profiling, and determine the subsoil hydrological properties.

The Effects of Shrub Removal on Soil Microbial Communities in Primary Forest, Secondary Forest and Plantation Forest on Changbai Mountain.

Shrub removal is a common management method in forest ecosystems, but comparatively little is known regarding the effects of shrub removal on soil microbial communities among primary forest, secondary forest, and plantation forests in temperate forests, which limits our accurate assessment of sustainable management of understory vegetation removal. Given this, we used a long-term operation experiment across a contrasting mixed broadleaved-Pinus koraiensis forest, Betula platyphylla forest, and Larix gmelinii plantation forest to explore the variations of soil properties and microbial community after 5years of shrub removal on Changbai Mountain, as well as the contribution of the soil properties and understory plant diversity to the soil microbial community. The results demonstrated that shrub removal could significantly alter soil SWC and TN, TP, and AP contents of the L. gmelinii, as well as N/P of B. platyphylla. Moreover, shrub removal also clearly improved soil bacterial Pielou_e index and Simpson index of mixed broadleaved-P. koraiensis and soil bacterial Simpson index of L. gmelinii, and decreased soil fungal Pielou_eindex and Shannon index of L. gmelinii and soil bacterial Pielou_e index and soil fungal Shannon index of B. platyphylla. Identically, shrub removal notably altered the soil bacterial community composition. Soil characteristics and understory plant diversity accounted for 48.02% and 26.88%, and 45.88% and 27.57% of the variance in the bacterial and fungal community composition, respectively. This study aimed to provide an important scientific basis for the restoration and sustainable management of temperate forests in the Changbai Mountain region.

Effect of Different Land-Use Types on Soil Properties in Cheha District, South-Central Ethiopia

Land-use changes under poor management practices are among the major causes of decline in soil fertility and agricultural productivity in south-central Ethiopia. Therefore, the study of soil properties variations across land-use types will have implications for planning proper soil management strategies. This study assessed the effects of land-use types on soil physicochemical properties in the Cheha district, south-central Ethiopia. Seven land-use types, eucalyptus plantation, cultivated, grazing, shrub, enset (Ensete ventricosum), khat (Chata edulis), and natural forest, were considered in describing soil fertility. A total of 21 soil samples (0–20 cm depth) were collected randomly from three representative soil sampling plots across each land-use type and examined for their analysis of soil physicochemical properties. Results showed that land-use changes induced significant (p < 0.05) differences in the soil OC, total N, CEC, pH, aluminum saturation, and Fe among land-use types were observed. Soils under eucalyptus plantation were considerably low in the sand (23.44%), silt (24.00%), and available water content (111.13 mm/m), whereas high in clay (52.56%) content and bulk density (1.39 g cm−3) as compared to enset land-use type. Compared to natural forest, soils under enset land-use type were high in soil OC (2.41%), total N (0.23%), and CEC (37.61 cmol (+) kg−1) followed by khat land-use. Correlation analysis also showed a highly significant positive relationship between soil OC and CEC but negative with bulk density, soil pH, and aluminum saturation. Total N in eucalyptus plantation, cultivated, khat, and enset lands were depleted by 56.0%, 40.0%, 36.0%, and 8.0%, respectively. Relative to forest land, lower exchangeable Ca, Mg, and Na contents were recorded in soils of cultivated land use. The extractable Fe, Mn, and Zn contents of soils were generally high and are not limiting for crop production. The intensive exploitation of land resources and improper soil management systems in the area could be the major factors for variations in soil properties across land-use types. Therefore, there is a need to develop integrated soil management practices that could help to restore soil nutrients and thereby minimize the continuing soil degradation for sustainable agricultural productivity.