Variability Of Soil Chemical Properties Research Articles

Intraspecific variability in plant and soil chemical properties in a common garden plantation of the energy crop Populus.

Optimizing crops for synergistic soil carbon (C) sequestration can enhance CO2 removal in food and bioenergy production systems. Yet, in bioenergy systems, we lack an understanding of how intraspecies variation in plant traits correlates with variation in soil biogeochemistry. This knowledge gap is exacerbated by both the heterogeneity and difficulty of measuring belowground traits. Here, we provide initial observations of C and nutrients in soil and root and stem tissues from a common garden field site of diverse, natural variant, Populus trichocarpa genotypes-established for aboveground biomass-to-biofuels research. Our goal was to explore the value of such field sites for evaluating genotype-specific effects on soil C, which ultimately informs the potential for optimizing bioenergy systems for both aboveground productivity and belowground C storage. To do this, we investigated variation in chemical traits at the scale of individual trees and genotypes and we explored correlations among stem, root, and soil samples. We observed substantial variation in soil chemical properties at the scale of individual trees and specific genotypes. While correlations among elements were observed both within and among sample types (soil, stem, root), above-belowground correlations were generally poor. We did not observe genotype-specific patterns in soil C in the top 10 cm, but we did observe genotype associations with soil acid-base chemistry (soil pH and base cations) and bulk density. Finally, a specific phenotype of interest (high vs low lignin) was unrelated to soil biogeochemistry. Our pilot study supports the usefulness of decade-old, genetically-variable, Populus bioenergy field test plots for understanding plant genotype effects on soil properties. Finally, this study contributes to the advancement of sampling methods and baseline data for Populus systems in the Pacific Northwest, USA. Further species- and region-specific efforts will enhance C predictability across scales in bioenergy systems and, ultimately, accelerate the identification of genotypes that optimize yield and carbon storage.

Variability of soil chemical properties and rice productivity in salt-affected soil in the north coastal rice field of Central Java, Indonesia

A coastal rice field is generally characterized by salt-affected soil and low soil quality for rice cultivation. Identifying soil chemical properties in these areas is necessary to determine soil management options for rice production. Therefore, soil samples were collected from 33 sampling points in the Wedung Sub-district of Demak Regency in the late dry season of 2021 to evaluate the variation among soil chemical characteristics in a coastline rice field. Soil samples were obtained beneath the topsoil (0-20 cm soil depth) and observed for electrical conductivity, exchangeable potassium, sodium, calcium, magnesium, and cation exchange capacity. Soils in the research field were categorized as slightly salty (0.75-2 dS m-1) to lightly salty (2.0-4.0 dS m-1) with very high sodium (>2 cmol(+) kg-1). Exchangeable potassium was dominated by moderate (0.3-0.7 cmol(+) kg-1) and low categories (0.2-0.3 cmol(+) kg-1). Based on soil calcium-to-magnesium ratios, around 6% of all samples were classified as calcium-deficient. The range of soil cation exchange capacity was 22-30 cmol(+) kg-1 and classified as high soil cation exchange capacity. Rice productivity in the salt-affected soil was around 4 t ha-1. Strategies for soil and controlling plants, such as soil amelioration and salt-tolerant rice cultivars, should be pursued to support plant growth and enhance rice productivity in the salt-affected soil, particularly in the coastal area.

Exploring Spatial Variability and Yield-Determining Factors in Cotton Production: A Multivariate Analysis

ABSTRACT The yield of cotton crops is severely affected by the soil’s chemical characteristics. This research probes the influence of soil properties on cotton yield, with a focus on assessing within-field spatial variability for advanced site-specific management in cotton production. Geostatistical analysis and semivariograms were conducted to examine the spatial variability of soil chemical properties. While multivariate analysis was employed to identify key yield-determining factors. Principal Component Analysis (PCA) was employed to explore leading soil indicators, as opposed to using a pre-defined set of indicators, and to analyze the spatial variability of soil properties. The soil characteristics encompassed saturation, soil pH, electrical conductivity (EC), organic matter (OM), phosphorous (P), potassium (K), calcium carbonate (CC), and micronutrients such as zinc (Zn), copper (Cu), iron (Fe), manganese (Mn), and boron (B). For this study, one thousand soil samples were meticulously collected from the Multan district, facilitated by Global Positioning System (GPS) devices. The PCA revealed that the first four PCs accounted for 57% of the total variation. The first PC, Cu, B, Mn, OM, and Fe emerged as the most influential variables, while the second PC exhibited a high correlation with CC, pH, and saturation. The third PC highlighted the dominant role of K and P in its construction, whereas the fourth PC was primarily shaped by Zn. The Principal Component Regression (PCR) analysis further revealed that EC, K, P, and Zn had positive impacts on cotton yield, while pH, Cu, Fe, Mn, and B had negative impacts.

Seasonal variations in soil characteristics control microbial respiration and carbon use under tree plantations in the middle gangetic region

Seasonal variations directly impact the biochemical and microbial properties of the soil, influence carbon and nutrient cycling within the soil system. Soils under tree plantation (TP) are rich in organic matter and microbial population, making them more susceptible to seasonal variation. We studied the effect of seasonal variations in soil chemical properties (pH, electrical conductivity (EC), total organic carbon (TOC), total nitrogen (TN), C/N ratio etc) and microclimate (moisture and temperature) on microbial respiration (SR), biomass, and carbon (C) utilization efficiency under 13 years old Kadamb (Anthocephalus cadamba Miq.), Simaraubha (Simarouba glauca DC), and Litchi (Litchi chinensis Sonn.) based TPs in middle Gangetic region. In contrast to higher SR and metabolic quotient (qCO2) in winter, the microbial biomass carbon (MBC) and microbial biomass nitrogen (MBN) in fall > summer > spring > winter, irrespective of TPs. The positive relationship between qCO2 and C/N ratios strongly supports the dependence of microbes on soil carbon for respiration. qCO2 had a significantly positive relationship with soil moisture (MC) and Electrical conductivity (EC), but a significantly negative relationship with temperature and pH. Higher MBN/TN and MBC/TOC ratios fall under simaraubha, and litchi-based TPs indicated more nitrogen (N) and carbon accumulation into microbial biomass. The seasonal variation of MBC/MBN ratios signifies the changes in microbial communities and fungi dominate over bacteria during winter, as bacteria have a lower C/N ratio than fungi. Stepwise regression analysis suggested that soil properties and micro-climate regulated microbial biomass and SR differ with TPs. Thus, the study indicates that microbial activities and biomass production can significantly influence by soil properties and seasonal variations under TPs.

Chemical and micronutrients assessment in Himalayan Foothill highway soil surface

This study examines the chemical properties and micronutrient concentrations of roadside soil in the ecologically sensitive Himalayan foothills of Uttarakhand, India. The primary objective is to assess soil contamination levels and their implications for urban ecosystem services. Soil samples from 13 locations were systematically collected, processed, and analyzed using atomic absorption spectrophotometry. Results indicated average concentrations of Zn, Cu, Fe, Mn, and Ni at 9.94, 3.28, 24.32, 17.35, and 0.28 mg/kg, respectively. Significant variations in soil chemical properties and micronutrient levels (p < 0.05) were observed across different sites, excluding phosphate levels. These findings underscore the critical need for targeted environmental management strategies to mitigate soil contamination and preserve vital ecosystem services in urbanized regions. The data provided can guide administrators in developing policies that promote sustainable development and environmental resilience.

Spatial Variability of Soil Chemical Properties of an Undulating Site within a University Farm at Okha, near Benin City in Nigeria

Spatial Variability of Soil Chemical Properties of an Undulating Site within a University Farm at Okha, near Benin City in Nigeria

Using GIS and Geostatistics to Monitoring Spatial Variability in Soil Chemical Properties Impacted by Cultivation Practices

Using GIS and Geostatistics to Monitoring Spatial Variability in Soil Chemical Properties Impacted by Cultivation Practices

Directional Differences in Thematic Maps of Soil Chemical Attributes with Geometric Anisotropy

In the study of the spatial variability of soil chemical attributes, the process is considered anisotropic when the spatial dependence structure differs in relation to the direction. Anisotropy is a characteristic that influences the accuracy of the thematic maps that represent the spatial variability of the phenomenon. Therefore, the linear anisotropic Gaussian spatial model is important for spatial data that present anisotropy, and incorporating this as an intrinsic characteristic of the process that describes the spatial dependence structure improves the accuracy of the spatial estimation of the values of a georeferenced variable in unsampled locations. This work aimed at quantifying the directional differences existing in the thematic map of georeferenced variables when incorporating or not incorporating anisotropy into the spatial dependence structure through directional spatial autocorrelation. For simulated data and soil chemical properties (carbon, calcium and potassium), the Moran directional index was calculated, considering the predicted values at unsampled locations, and taking into account estimated isotropic and anisotropic geostatistical models. The directional spatial autocorrelation was effective in evidencing the directional difference between thematic maps elaborated with estimated isotropic and anisotropic geostatistical models. This measure evidenced the existence of an elliptical format of the subregions presented by thematic maps in the direction of anisotropy that indicated a greater spatial continuity for greater distances between pairs of points.

Variations in soil chemical properties and growth traits of tissue culture banana under bio-slurry soil amendments in Uganda

Variations in soil chemical properties and growth traits of tissue culture banana under bio-slurry soil amendments in Uganda

Arbuscular mycorrhizal characterization associated with Uncaria guianensis and Uncaria tomentosa in Amazonian soils

There are some plant species with cultural and economic importance in the Amazon, such as Uncaria guianensis and U. tomentosa, both commonly named “cat's claw”. Since these species grow in soils with low levels of organic matter and nutrients, both depend on arbuscular mycorrhizae to grow. The information about arbuscular mycorrhizal fungi communities for U. tomentosa is limited and there is no current research on U. guianensis. Therefore, this research provides additional information on the arbuscular mycorrhizal fungi communities associated with Uncaria species in Amazonian soils. Both the percentage of root colonization and the influence of the edaphic composition in the two species were determined. Also, the richness and diversity of arbuscular mycorrhizal fungi were assessed using the spore isolation method and also, through the molecular analysis of virtual taxa. In addition, the difference between the soils was analyzed. Although U. guianensis grows in both Oxisols and Alluvial Entisols and U. tomentosa is restricted to Oxisols, sporulation of AM and root colonization does not respond significantly to variations in soil chemical properties. Additionally, 72 virtual taxa were identified for Uncaria species (53 U. tomentosa and 19 U. guianensis) and the relative abundance of arbuscular mycorrhizal fungi was higher in roots of Uncaria species than in soils. The arbuscular mycorrhizal fungi community that colonizes the roots of Uncaria species indicates that these species behave as wild species; therefore, the ex-situ propagation of the species in agricultural systems could be less successful than forest enrichment.

A large-scale assessment on spatial variability of potato yield and soil chemical properties in northern China

Understanding the spatial variability of potato yield and soil chemical properties is critical for designing management strategies and ensuring potato sustainable production. However, there has been no detailed investigation on a large-scale variation in yields and soil nutrients in potato production areas of China. In this study, 938 soil samples and potato production information were collected from the main potato-producing areas in northern China. The results showed that potato yields and selected soil properties varied considerably, with coefficients of variation ranging between 12.2% and 110.8%. Potato yield, pH, soil organic matter (SOM), total nitrogen (TN), available potassium (AK), and electrical conductivity (EC) showed strong spatial correlations, while mineral nitrogen (MN) and available phosphorus (AP) had moderate spatial correlations based on semi-variograms analysis. The spatial distribution of yields indicated that 83.3% of potato yields ranged from 20 to 60 t ha−1. The SOM, TN, AP, and AK showed similar spatial distribution trends with high concentrations in the northeast, while pH showed the opposite trend. EC was found to be highly variable with high values in the west. The high soil pH and low SOM were the most important constraints limiting potato productivity, and the high MN implied excessive nitrogen fertilizer application. The soil quality index (SQI) was calculated using selected soil properties, and a significant correlation between SQI and potato yield was observed. The spatial distribution of SQI showed that 42.2% of the study area was of low soil quality (SQI less than 0.6). A relatively low SQI indicated that there was great potential for increasing potato productivity in northern China. After dividing soil samples into rainfed and irrigated, the effect of soil nutrients on potato yield was found to become weaker at irrigated sites, where there was no correlation between SQI and yield, suggesting that the role of soil moisture overshadowed the role of nutrients. The spatial variability of soil chemical properties provided essential information for developing rational nutrient management strategies and regional planning to achieve sustainable potato production in China.

13 Cycles of Consecutive Tomato Monoculture Cropping Alter Soil Chemical Properties and Soil Fungal Community in Solar Greenhouse

Consecutive tomato monoculture cropping (CTM) obstacles severely restrict the development of facility tomato industry in China. However, the effect of CTM on the soil fungal community in greenhouses is still unclear. Here, we aim to identify the variation of soil chemical properties and soil fungal community associated with CTM for 1, 3, 5, 9 and 13 cycles. The results indicated that CTM led to a significant increase in soil total phosphorus (TP) and soil electrical conductivity (EC) value. CTM, though, significantly increased soil fungal community diversity, yet also led to the imbalance of soil fungal community compositions. Specifically, a beneficial soil fungus, Chaetomiaceae, decreased significantly at CTM13, while several soil pathogenic fungi, including Fusarium and Cladosporium, increased significantly at CTM13. A redundancy analysis (RDA) indicated that soil EC value, pH and TP had a greater impact on soil fungal community structure. Structural-equation-model (SEM) analysis indicated that, when compared with CTM3–CTM9, the decline of tomato fruit fresh weight per plant (TFFW) at CTM13 might be related to the significant increase in soil EC value, soil Fusarium and Cladosporium. Thus, appropriately decreasing soil EC and soil pathogenic fungi and enhancing soil beneficial fungi under a CTM system is crucially important for sustainable tomato production in greenhouses.

Comparison of rehabilitation treatments on mechanically reconstructed soils following strip coal mining activities: effects on soil properties

A rainfed rehabilitation trial on mechanically reconstructed soil, following strip coal mining, was laid out in the Mpumalanga Province of South Africa. It was used to evaluate seven rehabilitation treatments with four different depths of topsoil on coal spoil over three experimental seasons. A strip plot design was used to apply the treatments. The test crop was a grass mixture comprising of annual and perennial species. Trial measurements included soil physical, chemical and microbiological measurements, as well as growth and composition of the grass stand. Monthly rainfall was very variable with annual totals below the long-term values. Statistical significance was proved for most measurements. Relatively high soil bulk densities, stratified with depth, were measured, indicating undesirable soil compaction. Infiltration rates increased while soil strength decreased dramatically with increased topsoil thickness. A reciprocal interaction of profile water content and biomass yield was observed with water content decreasing as biomass yield increased. A large variation in soil chemical properties was observed as a function of the treatments. This study highlights the fact that the monitoring of soil and plant properties should be a prerequisite in any rehabilitation study. Similar trials on different soils and in different rainfall regions should be considered to expand our knowledge of the impacts of different soil treatments in a range of ecosystems.

Assessment of Chemical Properties of Soils Derived from Basement Complex Rocks of the Jos Plateau

Information on the chemical characteristics of soils is required in the sustainable the management of soil fertility and productivity. The objective of this study was to determine chemical characteristics of basement complex derived soils of the Jos Plateau. Soil study followed the approach in the Soil Survey manual and began by identification of three geologic units: granite gneiss, biotite granite and migmatite. Furthermore, eighteen soil profile pits were dug in each geologic units and eighty-four samples were taken from genetic horizons. Standard laboratory procedures were used to analyze soil samples for pH, organic matter, nitrogen and phosphorus. Results showed that organic matter contents in the soils were generally low and seemed to influence the distribution of nitrogen in the soils. Consequently, contents of total nitrogen were low. Mean contents of pH in the A horizon were 5.15, 4.64 and 5.58 respectively for soils derived from granite gneiss, biotite granite and migmatite. Low pH levels are linked to the basic cations draining out of the profile and the acidic character of the basement complex rocks from which the soils were formed. Soil reaction in most cases indicated that soils had a net negative charge. Available P contents in the magmatic soils was significantly higher than those of other geologic units. Effects of granite gneiss, biotite granite and migmatite parent materials on variation in soil chemical properties were more noticeable for soil reaction and available P contents.

Long-term changes in soil chemical properties with cropland-to-orchard conversion on the Loess Plateau, China: Regulatory factors and relations with apple yield

CONTEXTFarmland-to-apple orchard conversion prevails on the Loess Plateau in China and in other developing countries, but simultaneously, apple orchards have been severely overfertilized in the past two decades. OBJECTIVEWe quantified the changes in soil chemical properties between the 1980s and 2010s, and identified environmental factors that controlled spatial variability of soil properties and relations with apple yields. In addition, early warnings were provided by forecasting the changes in soil properties to 2100 under various fertilization scenarios. METHODSGeostatistics was performed using soil data obtained from the 1980s and 2010s to evaluate spatial-temporal variations in soil chemical properties. Drivers of the variation were identified by boosted regression tree analysis. Variance partitioning analysis and regression analysis were conducted to quantify the threshold values and then identify the potential factors limiting apple yield. Scenario analysis was conducted to forecast soil degradation, and thus, help to determine optimum fertilization. RESULTS AND CONCLUSIONSSoil properties, except pH, varied considerably in the 1980s and 2010s, with coefficients of variation between 22.55% and 60.62%. Compared with the 1980s, pH decreased in the 2010s, whereas concentrations of soil organic matter (SOM), total nitrogen (TN), available N (AN), available phosphorus (AP), and available potassium (AK) increased. Fertilization was the dominant factor affecting soil properties (except AP), followed by climate, terrain, and soil physical factors. Apple yield was significantly related to all properties, and critical thresholds were identified for pH, SOM, AN, AP, and AK to obtain maximum apple yield. In most apple orchards, pH, SOM, AP, and AK were much lower than corresponding thresholds, whereas AN exceeded the threshold. VPA identified soil as the most important factor explaining variation in apple yield, followed by anthropogenic, climatic, and topographic factors. Compared with an optimal fertilization scenario, continuing with conventional fertilization was predicted to lead to severe soil acidification and excessive accumulation of AN, AP, and AK in 2100. Thus, overfertilization must be controlled to improve apple orchard soil fertility and productivity. To summarize, soil chemical properties in apple orchards on the Loess Plateau changed substantially following long-term overfertilization, and soil acidification and low levels of SOM, AP, and AK were key variables limiting apple production. SIGNIFICANCEThe results provide new insights into spatial variability of soil properties and relations of soil properties to apple yields at a regional scale, and thus, contribute to optimizing orchard management in China and other countries with similar dilemmas in apple production systems.

Covariates in sample planning optimization for digital soil fertility mapping in agricultural areas

The study aimed to evaluate whether the use of covariates in sample optimization helps characterize the spatial variability of soil chemical properties. To this end, data from two agricultural areas located in southeastern Brazil were used. The covariates were used at two stages: sample planning optimization and building predictive methods. The covariates were divided into five categories: relief, vegetation, soil, management, and spatial coordinates. We compared two criteria in sample planning optimization: one aims to ensure spatial distribution by minimizing the mean squared shortest distance (MSSD); the other integrated four criteria through a multipurpose function (SPAN), aiming to represent the distribution and correlation between the covariates, the minimization of the mean squared shortest distance and the distribution of pairs of points for each lag size of the semivariogram. We evaluated three predictive methods (Robust Ordinary Kriging (ROK), Random Forest (RF), and Random Forest-Robust Kriging (RF-RK)) and a null model (mean-based) to predict four soil properties (Cation exchange capacity (CEC), Base saturation (V), Potassium (K) and Phosphorus (P)). We observed that not all areas would benefit from the inclusion of covariates in the sample planning. When our previous knowledge of variability is limited or unknown, we need to evaluate the management in the areas. When the cropping system is more complex and diversified, spatial coverage sampling is more feasible, using the covariates only on the prediction models.

Variation in soil chemical properties in relation to vegetation characteristics in a serpentine area of Hokkaido, Japan

Serpentine soils typically have chemical characteristics that can create adverse conditions for plant growth (e.g., low plant nutrients, low Ca/Mg ratio, and high heavy metal concentrations). Many studies have reported the unique characteristics of soils and plant communities (including endemic plants) in serpentine areas, especially on outcrop landscapes. However, little is known about variation in soil conditions within the geographical range of serpentine areas, such as from outcrops to adjacent grasslands and forests. The objective of this study was to assess the variation in soil chemistry among vegetation types in a serpentine soil area. We measured the chemical properties of soils for four vegetation types: outcrop, grassland, forest-edge, and mid-forest, in a serpentine area of Hokkaido, Japan. The results showed wide variation in the chemical properties of soil among vegetation types. In particular, outcrop and grassland sites showed extremely low Ca/Mg ratios and had higher Ni concentrations than those for the two forest sites. In addition, these differences in soil chemistry were strongly related to soil carbon content. These results suggest that forest litter alters the soil chemistry in serpentine areas, via soil development associated with organic matter accumulation, to conditions that are more conducive to a broader range of plants.

Influence of spatial variability of soil chemical attributes on the nutritional status and growth of the rubber tree

The productive potential of the rubber tree (Hevea brasiliensis) is dependent on its genetic composition, in addition to edaphoclimatic factors and management practices. However, as soil properties are not homogenous, knowing the spatial variability of soil attributes would be important to increase productivity and reduce production costs. In this context, the objective of this study was to determine the spatial variability of chemical attributes of the soil and its influence on the nutritional status and growth of rubber tree clones. Clones FX 3864, FDR 5788, CDC 312, and RRIM 600 were planted at Jaturnaíba Farm, in the municipality of Silva Jardim, Rio de Janeiro State, Brazil. The sampling sites were distributed at a spacing of 20 × 20 m on the northern and southern sides of the relief. The chemical attributes of the soil (pH, Ca2+, Mg2+, K+, P, Al3+, H+Al, sum of bases, cation exchange capacity, and base saturation) were evaluated at a depth of 0–20 cm in the different clone plantations. Additionally, the N, P, K, Ca, and Mg content as well as trunk circumference and total plant height, were also evaluated. Geostatistics was used to determine the spatial variability of the soil and clone attributes, while Ordinary Kriging was used to draw variability maps of the variables. A difference in the distribution of the variables, which was dependent on the slope of the relief, was detected through the maps. The southern side presented better conditions as some degradation was observed on the northern side. Certain soil characteristics influenced the distribution of the attributes of the planted clones; for example, the low concentration of Ca2+ in the soil caused Ca deficiency in the FX clone on the southern slope, indicating that liming did not supply enough nutrients for this clone. Our results showed that the variability in soil attributes influenced the nutritional status and growth of the rubber tree clones, indicating that variability maps can guide the planting and management of the rubber tree, providing more efficient management.

The Effect of Tree-Uprooting on the Soil Spatial Complexity in an Old-Growth Temperate Forest, Central Europe

The formation of spatial pedocomplexity in forested landscapes is an issue that has not yet been comprehensively resolved. This study analysed the effects of tree disturbances on the spatial variability of soil chemical properties in order to explain the spatial pedocomplexity in one of the oldest forest reserves in Europe. A total of 1545 sites over an area of 74 ha were assessed in terms of soil taxonomy, morphology, and profiles. We quantified the spatial autocorrelation of soil chemical properties and analysed the effects of soil disturbance regimes on soil chemical properties in both the surface and subsurface layers using geostatistics and redundancy analysis, respectively. A paired difference test revealed that the factors involved in the soil formation of the two layers are different. The neoformation of the surface layer proceeds rapidly after soil disturbance and, therefore, some formerly disturbed surface layers become mature above immature subsurface layers. The effect of tree disturbances on soil chemical properties was significant for totally decomposed treethrows. Treethrow density partially explained the variation in soil chemical properties in both layers, but even more so in the subsurface layer. This study further elucidates the impact of treethrows on soils and shows that they are an important driver of soil spatial pedocomplexity.

Spatial Variability of Selected Soil Properties in Long-Term Drained and Restored Peatlands

Drained peatlands have been rewetted for restoration in Europe and North America for about 25 years. However, information on spatial variability of soil chemical and biochemical properties in long-term drained and restored peatlands is insufficient to design appropriate research methods and soil sampling protocols for monitoring biogeochemical processes. The study aimed to examine the influence of long-term drainage and rewetting of peatlands on smallscale spatial variability of the soil chemical properties and enzyme activities. We collected 400 soil samples from the 0–15 cm and 15–30 cm soil depths of a drained and a corresponding rewetted peatland. The number of grid cells was 100 for each of the drained and the rewetted peatland, and the size of each grid cell was 3 m × 3 m. We analyzed 17 soil parameters from the surfaces and 14 from the subsurface of both sites. The variability (range, SD, and CV) of all the soil properties was higher in the drained peatland than in the restored peatlands except for the soil pH. The geostatistical analysis revealed only the soil pH, acid phosphatase, β-glucosidase, and arylsulfatase activities disclosed the strong spatial dependency at the ≤5 m semivariance range in the drained peatland. However, more than 80% of the soil properties showed a strong spatial dependence within the 4–20 m semivariance ranges in the restored peatland. The strong spatial dependencies of all the soil properties in the long-term restored peatland conclusively call for the spatial soil sampling and geostatistical data analysis methods to capture substantial spatial variability that has important implications in degraded peatland restoration.