Variability Of Soil Properties Research Articles

Mechanisms of enhancing MgO for stabilization/solidification of Pb-contaminated red clay through CO2 sequestration

Pb-contaminated soil poses significant environmental and health risks as well as soil stability issues. Research on sandy soils highlights CO2-enhanced reactive MgO as a promising solution for improving the solidification of Pb-contaminated soils. However, carbonation effects can differ markedly between soil types owing to varying soil properties. In this study, we evaluated the effects of CO2-enhanced reactive MgO on the engineering and environmental characteristics of Pb-contaminated red clay and explored its mechanism of carbonation solidification. The results showed that CO2-enhanced reactive MgO increased the strength of Pb-contaminated red clay to over 3 MPa within 1 h, which was approximately 25 times the strength of untreated soil (0.2 MPa) and significantly higher than that of reactive MgO-treated, uncarbonated soil (0.8 MPa). The pH of the carbonated soil (9–10) facilitated Pb2+ immobilization, and the increase over the initial parameter elevated the electrical conductivity value. Moreover, CO2-enhanced reactive MgO reduced the Pb2+ leaching concentration to below 0.1 mg/L, even at high Pb concentrations (10,000 mg/kg). Pb2+ transformed into lead carbonates during the carbonation process, with the hydrated magnesium carbonates forming a dense internal structure. This solidification mechanism included chemical precipitation, physical adsorption, and encapsulation. Notably, the carbonation time should be controlled within 1 h to prevent soil expansion. Together, these findings support the potential of CO2-enhanced reactive MgO for efficient and low-carbon application in the solidification of Pb-contaminated red clay.

ТРАНСФОРМАЦИЯ ПЛОДОРОДИЯ ПОЧВ ЗАЛЕЖЕЙ ЛЕСОСТЕПНОЙ ЗОНЫ ПРИ РАЗЛИЧНОМ НАПРАВЛЕНИИ ИХ ИСПОЛЬЗОВАНИЯ

The purpose of research is to provide a comprehensive comparative assessment of the fertility of gray fallow soils in the forest-steppe zone of the Krasnoyarsk Region, overgrown with forest, used for hayma-king and re-developed into arable land. The studies were conducted in 2007–2020 in the Krasnoyarsk and Achinsk-Bogotol forest-steppe on gray soils of fallow lands no longer used for agricultural purposes. Stu-dies were carried out to assess the indicators of the potential and effective fertility of gray soils of fallow lands of the Krasnoyarsk and Achinsk-Bogotol forest-steppe with their various post-agrogenic use. It has been established that forests regenerated on fallow lands do not lead to degradation of soil fertility, especially in terms of the content of humus and agronomically valuable aggregates. The emerging forest litter and tree litter accelerate the accumulation of organic matter, a source of humus. There is weak spatial va¬riation in most indicators of effective and potential fertility in soils under regenerating forest compared to pure fallow lands. With the re-involvement of fallow land into arable land, nitrification somewhat increases, spatial variation in soil properties decreases, and the content of humus and absorbed bases decreases. The structural composition of the soils of all study objects is characterized as excellent (ACF 88–77 %) with an insignificant value of the coefficient of variation of fractions (4–7 %). When reclaiming fallow lands into arable land, the proportion of the blocky fraction is significantly reduced. The spatial variability of the structural composition of soils in fallow lands and hayfields is higher than on arable land, which is asso¬ciated with the “clumpiness” of the ground cover and root system of plants on uncultivated soils. In terms of fertility, post-agrogenic gray soils used for haymaking occupy an intermediate position between clean fallow lands and those overgrown with forest. The productivity of the phytomass of fallow lands, arable land and hayfields in the Krasnoyarsk and Achinsk-Bogotol forest-steppe is more closely correlated with the indicators of the potential fertility of post-agrogenic gray soils. In most cases, the values of the correlation coefficients are closer between phytomass reserves and indicators of effective fertility in the Achinsk-Bogotol forest-steppe, which is associated with more favorable hydrothermal conditions in this research area and optimal water-physical properties.

Compilation of Consolidation Properties Data of Champlain Sea Clay from Ottawa Region

AbstractEstimation of consolidation settlements in fine-grained soils due to various civil infrastructure loads is traditionally based on results derived from consolidation tests performed on undisturbed soil samples, combined with the data of other soil properties. In many geotechnical engineering applications, consolidation settlements are also estimated using empirical consolidation parameters derived from basic soil properties. This approach relies on correlations from the literature to bypass the time-consuming and expensive sampling techniques, laboratory testing, and other associated expenses. However, these correlations may not provide reasonable consolidation settlement estimations as these correlations are typically developed without considering the influence of stress history, geology, salinity of pore water, gradation, soil fabric, and chemical properties of the soils. This is especially true for Champlain Sea clay deposits from Eastern Ontario region of Canada that are typically with heterogeneous site conditions and exhibit spatial variability of soil properties. In this paper, data from the published literature and industrial and government reports on sensitive Champlain Sea clays were gathered for the Ottawa region. The data collection and clean-up methodology towards enhancing the reliability of the gathered data is comprehensively discussed. The summarized data from this study can be used with a greater degree of confidence towards developing reliable correlations in the estimation of consolidation settlements in geotechnical engineering practice.

Influence of geological uncertainty and soil spatial variability on tunnel deformation and their importance evaluation

In geotechnical engineering, geological uncertainty and the inherent spatial variability of soil properties are two primary sources of uncertainty, significantly impacting embedded geo-structures. While the influence of the soil spatial variability and geological uncertainty has been separately investigated, the coupling effect of these two types of uncertainties on tunnel is still limited. Meanwhile, little effort has been devoted to quantifying the degree of importance of these two types of uncertainties. This study quantitatively evaluates the effects of geological uncertainty and soil spatial variability on tunnels, and first assess the importance of these two uncertainties based on a novel approach. Improved coupled Markov chain model was utilized to simulate the geological uncertainty based on sparse and limited boreholes. The coefficient of variation (COV) was adopted to characterize the different levels of soil spatial variability in this study. The results illuminated the role of geological uncertainty and spatial variability in tunnel probabilistic analysis by comparing different boreholes schemes and COV. In addition, the geological uncertainty index (GUI) was presented to quantitatively estimate the degree of uncertainty in the simulated strata. A novel approach for evaluating the significance of geological uncertainty and soil spatial variability on tunnel was proposed. Based on the Kendall correlation coefficient, the classification was also given, divided into high, strong, moderate, weak and no correlation. The geological uncertainty should be considered in high and strong correlation groups. Both two types of uncertainties should be simultaneously taken into account in moderate and weak correlation divisions.

Effects of soil spatial variability on the behaviour of the embankment supported with a combined retaining structure

In this study, the effects of soil spatial variability on the behaviour of the embankment supported with a combined retaining structure (CRS) were investigated. The numerical model of the CRS embankment was established and validated with the field data. An application programming interface (API) was developed to deal with the data exchanging issue between the numerical model and the spatial variability characterization model. Based on the verified numerical model and the API, the probabilistic analysis with 500 Monte Carlo simulations was automatically computed. Three influencing factors of the retained soil (the mean of the friction angle, the variation of the friction angle and the vertical correlation length of the random field) are analysed by parametric analysis. The results show that the vertical correlation length of the random field is most important in the earth pressure calculation process, while the mean of the friction angle is the factor with least impact. On the whole, the spatial variability of soil properties has minimal impact on the distribution and magnitude of earth pressure behind the retaining structure.

Internal Piping Erosion Evaluation of Embankment Dam Considering the Spatial Variability of Soil Properties

Internal Piping Erosion Evaluation of Embankment Dam Considering the Spatial Variability of Soil Properties

Spatial-temporal variability in nitrogen use efficiency: Insights from a long-term experiment and crop simulation modeling to support site specific nitrogen management

Within-field soil heterogeneity can lead to large variation in nitrogen use efficiency (NUE). Crop simulation models provide a multi-faceted approach to management considering both soil and plant interactions. However, research using crop models for investigating within field variation in NUE is limited, in part because of challenges quantifying spatially variable soil model parameters. Here soil apparent electrical conductivity (ECa) and measured soil properties were used to map spatial variations in soil characteristics across a Long-Term Experiment in Norfolk, England. The relationship between plot ECa across the 3 ha experiment and agronomic data across three different nitrogen rates (0, 110, and 220 kg N ha-1) over five wheat years (2010–2020) was quantified. The Sirius crop model was parameterized for two soils representing the extremes of ECa. Sirius was validated using recorded plot data. Site-specific optimal nitrogen and associated leaching risks were simulated across 29 years of weather data. Variation in soil properties had significant impact on measured NUE. At 220 kg N ha-1 mean observed yields across 5 years ranged from 9.0 to 10.7 t ha-1 and grain protein from 11.6% to 11% on the low EC and high EC plots, respectively. On average fertiliser grain N recovery was 19.7 kg N ha-1 lower on the low ECa plots. Sirius simulated the variation in yield, grain protein and grain N recovery to a good level of accuracy with RRMSE of 19.5%, 15.4% and 19.5%, respectively. Simulated optimal nitrogen on the low EC soils was on average 12 kg N ha-1 lower, with >1 in 4 years with optimal nitrogen <200 kg N ha-1. Our work demonstrated that using a combination of proximal soil EC scans and targeted soil sampling we can optimize the data requirements for model parameterisation to support site-specific N management.

Effect of 2-D spatial variability of soil properties on cofferdam stability considering degradation of soft soil foundation

Effect of 2-D spatial variability of soil properties on cofferdam stability considering degradation of soft soil foundation

Assessment of Soil Spatial Variability in Agricultural Ecosystems Using Multivariate Analysis, Soil Quality Index (SQI), and Geostatistical Approach: A Case Study of the Mnasra Region, Gharb Plain, Morocco

Accurate assessment of soil quality is crucial for sustainable agriculture and soil conservation. Thus, this study aimed to assess soil quality in the agricultural ecosystem of the Mnasra region within the Gharb Plain of Morocco, employing a comprehensive approach integrating multivariate analysis and geostatistical techniques. Thirty soil samples were collected from the surface layers across thirty selected sites. The results showed significant variations in soil properties across the study area, influenced by factors such as soil texture, parent material, and agricultural practices. Pearson correlation and principal component analysis (PCA) were employed to analyze the relationships among soil properties and compute the Soil Quality Index (SQI). The SQI revealed values ranging from 0.48 to 0.74, with 46.66% of sampled soils classified as “Good” and 53.33% as “Fair”. Geostatistical analysis, particularly ordinary kriging (OK) interpolation and semivariogram modeling, highlighted the spatial variability of soil properties, aiding in mapping soil quality across the landscape. The integrated approach demonstrates the importance of combining field assessments, statistical analyses, and geospatial techniques for comprehensive soil quality evaluation and informed land management decisions. These findings offer valuable insights for decision-makers in monitoring and managing agricultural land to promote sustainable development in the Gharb region of Morocco.

Carbon sequestration potential and its main drivers in soils under alfalfa (Medicago sativa L.)

As a perennial forage crop, alfalfa (Medicago sativa L.) has been extensively utilized for the vegetation restoration of degraded soil and provides feedstock for forage. Its high usage can be attributed to its high yield potential and the increasing soil organic carbon (SOC) sequestration of alfalfa cultivation. However, the impact of land conversion to alfalfa on SOC content and its underlying drivers remain unclear. We performed a meta-analysis at the global scale to explore the quantified effects of alfalfa cultivation on SOC content and identify its controlling factors. We employed 1699 pairwise data points from 90 publications based on cropland/abandoned land conversion to alfalfa. Globally, cropland (cropland-alfalfa) and abandoned land (abandoned land-alfalfa) conversion to alfalfa enhanced SOC content by 12.1 % and 13.7 %, respectively. Alfalfa exhibited greater SOC content benefits in the surface soils (0–20 cm) with a lower level of initial SOC (<16 g kg−1), regardless of the land conversion type. Cropland-alfalfa was observed to increase SOC content with fertilization, irrigation, and conventional tillage in the long term (>5 years). Furthermore, abandoned land-alfalfa enhanced SOC content in the absence of alfalfa biomass removal and for longer cultivation durations (>5 years). Boosted regression tree analyses indicated variations in soil properties (75 % for cropland-alfalfa and 65 % for abandoned land-alfalfa) as the primary factors driving changes in SOC content. The dominant drivers were determined as the soil layer (51.6 %), cultivation duration (13.1 %), and initial SOC (12.9 %) for cropland-alfalfa, and initial SOC (43.7 %), soil layer (24.6 %) and cultivation duration (17.1 %) for abandoned land-alfalfa. Land conversion to alfalfa has great potential for SOC sequestration, particularly in low-fertility soils. Therefore, alfalfa cultivation is highly recommended for degraded lands due to its SOC sequestration benefits in vegetation restoration.

Mitigative translocation of Singleton Mint Bush (Prostanthera cineolifera) on the NSW North Coast: Effects of soil texture, horticultural practice and bushfire on the translocation outcome

SummaryTranslocation of the threatened species Singelton Mint Bush (Prostanthera cineolifera R.T.Baker &amp; H.G.Sm.) was carried out for a highway project on the New South Wales North Coast to mitigate development impact on this species. The translocation aimed to augment an existing population with propagated plants to compensate for cleared plants and conduct field research to better understand the effects of soil properties, horticultural practices and a wildfire on translocation results. A novel soil seedbank and fire method applied ex‐situ was used to propagate plants for introduction. After an initial attempt at site‐wide introduction resulted in widespread mortality of seedlings from a wilt disease, three plot‐based experiments were carried out to examine how disease incidence was related to spatial variation in soil properties and horticultural practices. The experiments showed that relatively subtle changes in the clay and sand content of soil strongly affected susceptibility of Singelton Mint Bush seedlings to wilt disease; 12 month old seedlings performed much better than 6 month old seedlings; plants propagated from seed performed better than cuttings, and most of the recipient site represented unsuitable habitat for Singelton Mint Bush. Sufficient Singelton Mint Bush seedlings were established after 3 years, but after a bushfire, the translocated cohort recruited poorly from seed, so that after 6 years, &lt;10% of the total Singelton Mint Bush population in the recipient site was of translocated origin and &gt;90% of in‐situ (pre‐translocation) origin. Lessons learnt from the translocation project were that: (i) microhabitat is as important as macrohabitat in selecting a translocation recipient site; (ii) short‐term survival may not be a reliable indicator of a self‐sustaining population; (iii) translocation incorporating designed experiments can greatly improve understanding of how certain factors influence species performance and (iv) horticultural practices can be as important as ecology in determining the translocation outcome.

Cedrelinga catenaeformis (Tornillo) in natural and agroforestry systems: Dendrometry, soil and macrofauna

Agroforestry and protected areas are alternatives to mitigate the adverse impacts generated by human activities in the tropical forests of the Peruvian Amazon. The aim of this study was to determine the influence of natural and agroforestry systems of Cedrilinga catenaeformis (Tornillo) on soil properties. The physical, chemical, and soil macrofauna properties, as well as dendrometric variables of Tornillo aged 140 and 180 years in natural systems and 7, 17 and 37 years in agroforestry systems, were examined. Results revealed variability in soil properties depending on their origin; however, no marked differences were observed due to tree age or natural versus agroforestry condition. Regarding soil macrofauna, greater diversity was noted in the older agroforestry system, while dendrometric variables exhibited a sigmoidal behavior, except for wood volume, which showed a linear increase. Agroforestry systems of Tornillo associated with Centrosema macrocarpum (Centrosema) maintain soil properties similarly compared to natural systems; however, the soil of the oldest agroforestry system showed higher activity of earthworms Rhinodrilus lavellei, Rhinodrilus pashanasii, Diptera orders, and Julidae, compared to soils of more recent agroforestry systems and natural systems. It was estimated that dendrometric variables of Tornillo show stagnation in the increase of total height at 150 years, commercial height at 165 years, and DBH at 70 years. Meanwhile, total height and DBH showed very strong and strong positive correlations (p < 0.05) with soil N content and CEC in agroforestry systems with 17 and 37 years. Estimating dendrometric variables and understanding the nutritional requirements in the growth and development of Tornillo will contribute to its more effective management in natural and agroforestry ecosystems in the Amazon region.

Nutrient contents and microbial communities as mediators of the effects of land-use in ecosystem functioning in alpine ecosystems from Central Mexico

Abstract Purpose The interplay between microbial taxonomy, functional diversity, and land-use changes across diverse ecosystems must be better understood. This study explores, through a statistical modeling approach, the intricate relationships between microbial communities, soil properties (nutrient contents and physicochemical parameters), and land-use changes, using stable isotopes ratio (δ13C/δ15N) as ecosystem function indicator. Methods Using Structural Equation Modeling (SEM) this study aims to investigate how soil microbial communities, soil properties and ecosystem function are interconnected in three ecosystems undergoing land-use change in Nevado de Toluca, Mexico. Results Multivariate analyses of microbial communities and soil parameters for the different land-uses reveal significant variation in both microbial composition and soil properties (i.e. nutrient contents) mainly explained by the land-use history of the studied ecosystems. Through the SEM approach, it was possible to disentangle the relative contribution of land-use change, microbial community composition and nutrient contents to the ecosystem function defined as the δ13C/δ15N ratio. Conclusions Microbial communities are the main drivers of soil ecosystem functioning. However, through SEM approach it is possible to formally test direct and indirect relationships impacting microbial communities and the resulting functional consequences, contributing to a mechanistic understanding of the ecological implications of land-use change, aiding in sustainable land-use decision-making.

Impact of Randomized Soil Properties and Rock Motion Intensities on Ground Motion

Seismic site response is inevitably influenced by natural variability of soil properties and anticipated earthquake intensity. This study presents the influence of variability in shear wave velocity (Vs) and amplitude of input rock motion on seismic site response analysis. Monte Carlo simulations were employed to randomize the Vs profile for different scenarios. A series of 1-D equivalent linear (EQL) seismic site response analyses were conducted by combining the randomized Vs profile with different levels of rock motion intensities. The results of the analyses are presented in terms of surface spectral acceleration, amplification factors (AFs), and peak ground acceleration (PGA). The mean and standard deviation of these parameters are thoroughly discussed for a wide range of randomized Vs profile, number of Vs randomizations, and intensities of input rock motions. The results demonstrate that both the median PGA and its standard deviations across different number of Vs profile realization exhibit a slight variation. As few as twenty Vs profile realizations are sufficient to compute reliable response parameters. Both rock motion intensity and standard deviation of Vs variability cause significant variation in computed surface parameters. However, the variability in the number of records used to conduct site response has no significant impact on ground response if the records closely match the target spectrum. Incorporating the multiple sources of variabilities can reduce uncertainty when conducting ground response simulations.

Prediction of the undrained base heave and post uplift in braced excavation of a typical subway station in thick soft clay

Construction of a typical subway station usually involves a narrow long excavation with a width of approximately 20 m. An undrained base heave is a common problem in deep excavation areas with soft clay, which may induce considerable post uplift and damage the safety of the retaining system. Post uplift involves complex interactions between soil, pile post foundation, and supported struts, and an accurate prediction of post uplift is challenging. This paper aimed to establish a practical method for predicting the base heave and post uplift in the construction of typical subway stations in areas with thick soft clay. Series soil–water coupled finite element method (FEM) analysis was conducted to investigate the characteristics of the base heave with different soil properties and wall stiffnesses. The results showed that the calculated base heave can be fitted by a normalized function, regardless of large variations in soil properties and wall design parameters. The normalized function was then applied to a soil–post–strut interaction analysis model to predict the post uplift at different excavation depths. The application of the proposed method to a real subway station project showed that the predicted results were in good agreement with the field observations.

Relationship of selected properties of Cambisols to altitude and forest ecosystems of four vegetation grades

Currently, little is known about the spatial variability of significant soil properties and their relationships to forest ecosystems of different vegetation grades. This work evaluates the variability of the properties of the upper layer of Cambisol taxa and their relationship to altitude and forest ecosystems of 2nd to 5th forest vegetation grades selected in the Western Carpathians using PCA and regression analysis. The content of clay, total carbon and total nitrogen, humus, energy, and ash in the soils varied between 5.43 and 11.53 %, 21–65 mg g−1, 1.9–4.7 mg g−1, 36–112 mg g−1, 438.4–5845.7 J g−1 and 852.9–946.3 mg g−1, and C/N, pHH2O, and pHKCl values ranged between 11.2 and 16.7, 4.0–5.8 and 3.1–4.6. PCA showed that EAC in the 3rd oak-beech vegetation grade had significantly higher pH values and significantly lower energy content, ESC in the 4th beech vegetation grade had a significantly higher ash content and a significantly lower energy content, and DC in the 5th fir-beech vegetation grade had a significantly higher content of Ct, Nt, and humus. Linear regression revealed a strong negative correlation between the energy content and soil reaction (R2 for pHH2O = 0.48; R2 for pHKCl = 0.38) for all Cambisol taxa. Ct content and ash show a strong negative correlation (R2 = 0.78). The positive relationship between altitude and FVGs was found only for the soil Ct (R2 = 0.87), Nt (R2 = 0.81), and humus content (R2 = 0.87). A strong negative linear relationship between altitude and FVGs showed the ash content (R2 = 0.77). In turn, the oscillatory, polynomial course had a relationship between the clay content (R2 = 0.65) and energy (R2 = 0.75) to altitude and FVGs. Recognizing significant soil variables and better understanding their impact on the development of forest ecosystems is a prerequisite for distinguishing areas with the highest risk of their damage under conditions of various anthropogenic interventions and climate change. Therefore, this topic continues to require increased research efforts. For this reason, a better understanding of the relationships between soil properties and ecologically differentiated communities of forest ecosystems will allow us to identify areas with the highest risk of ecological changes that could lead to the degradation of European forests in the future.

Predicting wetland soil properties using machine learning, geophysics, and soil measurement data

PurposeMachine learning models can improve the prediction of spatial variation of wetland soil properties, such as soil moisture content (SMC) and soil organic matter (SOM). Their performance, however, relies on the quantity of data used to train the model, limiting their use with insufficient data. In this study, we assessed the use of synthetic data constrained by limited field data for training an eXtreme Gradient Boosting (XGBoost) algorithm used to predict the distribution of soil properties based on geophysical measurements constrained by soil samples.Materials and methodsA spatial distribution of soil apparent electrical conductivity (ECa) and laboratory measurements of SOM and SMC from twenty-two core samples were acquired at the St. Michael restored wetland near Defiance, Ohio. The correlations between ECa, SOM, and SMC were explored for predicting the spatial distribution of SOM and SMC. We used a Beta Variational AutoEncoder (β-VAE) approach to synthetically generate over 70,000 training data from the original twenty-two data from soil cores. The training data samples were taken from the latent space. The XGBoost algorithm was then trained on the β-VAE generated data and used to predict the spatial distribution of SOM and SMC at the site. We also validated the accuracy of the XGBoost predictions using an original holdout model validation technique.Results and discussionsThe generated synthetic data using the β-VAE include both soil attributes and ECa, which are larger and more diverse than the original training set with an absolute mean reconstructed error for SMC and SOM ranging from 0.018 to 0.022 and 0.026 to 0.041, respectively. This indicates that the β-VAE successfully generated a realistic synthetic dataset and overcame the technical barrier of using limited datasets. In addition, using generated data to expand the original training data helps the XGBoost model make more accurate predictions compared to training on the original data. The XGBoost prediction performance yielded average Lin’s concordance correlation coefficient (LCCC) values of 0.82 and 0.85 for SOM and SMC and a ratio of performance to deviation (RPD) values of 1.92 and 2.22 respectively, indicating a good performance.ConclusionsThis study validated the use of β-VAE to successfully generate synthetic wetland soil datasets with attributes of the original field data that can be effectively used to train the machine learning XGBoost model. The proposed framework offers an efficient solution for mapping the spatial variability of soil property in data-scarce wetland soil environments.

Vegetation communities and soil properties along the restoration process of the Jinqianghe mine site in the Qilian Mountains, China.

The study explores the impact of mine grassland restoration on plant communities and soil properties in alpine grasslands, a subject of significant interest due to the observed relationship between grassland changes, plant communities, and soil properties. While prior research has mainly focused on the consequences of grassland degradation on plant diversity and soil characteristics, the specific effects of varying restoration degrees in alpine mining grasslands at the regional scale remain poorly understood. To address this knowledge gap, we established 15 sampling plots (0.5m×0.5m) across five different restoration degrees within alpine mining grasslands in the Qilian Mountains, China. Our objective was to assess the variations in plant diversity and soil properties along these restoration gradients. We conducted comprehensive analyses, encompassing soil properties [soil water content (SWC), available nitrogen (AN), total phosphorus (TP), nitrate nitrogen (NO3-N), ammonium nitrogen (NH4-N), total nitrogen (TN), available phosphorus (AP), soil organic carbon (SOC), nitrate nitrogen, soil pH, and electrical conductivity (EC)], plant characteristics (height, density, frequency, coverage, and aboveground biomass), and plant diversity indices (Simpson, Shannon-Wiener, Margalef, Dominance, and Evenness indexes). Our findings included the identification and collection of 18 plant species from 11 families and 16 genera across the five restoration degrees: Very Low Restoration Degree (VLRD), Low Restoration Degree (LRD), Moderate Restoration Degree (MRD), High Restoration Degree (HRD), and Natural Grassland (NGL). Notably, species like Carex duriuscula, Cyperus rotundus, and Polygonum viviparum showed signs of recovery. Principal component analysis and Pearson correlation analysis revealed that soil pH, SWC, SOC, NO3-N, and AN were the primary environmental factors influencing plant communities. Specifically, soil pH and EC decreased as restoration levels increased, while SWC, AN, TP, NH4-N, TN, AP, SOC, and NO3-N exhibited a gradual increase with greater restoration efforts. Furthermore, the HRD plant community demonstrated similarities to the NGL, indicating the most effective natural recovery. In conclusion, our study provides valuable insights into the responses of plant community characteristics, plant diversity, and soil properties across varying restoration degrees to environmental factors. It also elucidates the characteristics of plant communities along recovery gradients in alpine grasslands.

A Study of the Multivariate Spatial Variability of Soil Properties, and their Association with Vine Vigor Growing on a Clayish Soil

A Study of the Multivariate Spatial Variability of Soil Properties, and their Association with Vine Vigor Growing on a Clayish Soil

Assessment of Selected Physical and Chemical Soil Properties and Organic Carbon Stock, Under Different Land-Uses in Melka Gura Subwatershed of North Shewa Zone, Oromia, Ethiopia

A study conducted in Melka Gura Subwatershed to assess soil properties across three types of land uses plantation forest, grazing land, and cultivated land from 2022 to 2023 found that all land uses had loam soil, except for the plantation forest, which had sandy loam. The mean soil BD in the study area ranged from 1.06 to 1.39 g/cm3. Conversely, plantation forest soil and grazing land had the highest mean AWC (194.8 mm/m) at 0–20 cm depth. The highest mean values of sand, silt, TP, pH, AP, exchangeable basic cations, CEC, SOC, TN, and SOC stock (68.62-ton ha-1) were registered in the soil of plantation forest land. The highest mean values of BD (1.39 g/cm3), clay content (19%), Ex. A, and Ex. Al were recorded in the soil of cultivated land. The average values of clay, BD, FC, PWP, pH, PBS, and exchangeable bases all indicated an increasing trend from the surface toward the subsurface. The highest mean value of SOCS (68.62 tons’ ha-1) was discovered in plantation forest land and the lowest in cultivated land. The differences in soil management practices could be the major reasons for variations in soil properties across land-use types. Further studies are needed on the effects of land-use change on fertility-related soil properties in relation to integrated soil and water conservation practices to reduce further land degradation.