Variability Of Soil Properties Research Articles

Field-scale spatial correlation between soil and Vis-NIR spectra in the Cerrado biome of Central Brazil

Visible and near-infrared (Vis-NIR) spectroscopy is a tool to determine soil spatial variability and has been used to map soils and their properties. Considering that physical, chemical, mineralogical, and morphological soil properties can affect the intensity and the depth of the spectral reflectance band in the Vis-NIR region, the objectives of this work were to: (i) evaluate the potential of the reflectance inflection difference (RID) to discriminate soils; and (ii) verify potential spatial correlations of the RID with soil properties, compared with the full spectra, in order to build thematic maps at a field scale. In a farm of 375 ha, 78 soil samples from the 0.87–0.92-m depth were collected in a regular grid of 200 m, with a focus on the soil diagnostic horizon (Bw horizon). The sampled soils were a Latossolo Vermelho-Amarelo ácrico (Haplic Ferralsol) and a Latossolo Vermelho distrófico (Rhodic Ferralsol). Twenty-two physical, chemical, mineralogical, and morphological soil properties were determined, and the Vis-NIR spectra between 400 and 2500 nm were measured. Considering the presence of an inflection band and its relationship with soil properties, the spectral bands used to calculate the RID were between (base 1/base 2): 400–510, 730–930, 1290–1450, 1800–1950, 2000–2218, and 2218–2290 nm. The RID failed to map the spatial variability of soil properties, with a Kappa index of 39%; therefore, it is not a good parameter for building thematic maps of soil parameters. In addition, the complete spectrum (mainly in 400–510, 730–930, 1290–1450, 1800–1950, 2000–2218, and 2218–2290 nm) was better spatially correlated with soil properties than the decomposition of the spectrum by the RID. Soil classification and level of discretization as affected by spectral variability were also discussed here. Three soil groups were discriminated mainly by the Ki and Kr indexes and clay content. Moreover, the variability of the spectra was conditioned by the spatial variability of the mentioned variables. The clay content for soils with a discrepant particle size (group 1 compared with groups 2 and 3) and the Ki and Kr indexes for soils with a homogeneous particle size (between groups 2 and 3), associated with the full Vis-NIR spectral analysis, allowed building thematic maps with a good precision, without the need of mathematical models; this was possible by the modification of the reflectance intensity and the size of the concavity of the spectral band.

Nickel oral bioavailability in contaminated soils using a mouse urinary excretion bioassay: Variation with bioaccessibility

To assess the health risk of nickel (Ni) in contaminated soils, studies rarely evaluated Ni bioavailability in the gastrointestinal (GI) tract, limiting the accurate regulation of contaminated sites. Here, for 15 soil samples contaminated by Ni-electroplating, Ni oral relative bioavailability (RBA, relative to NiSO4) was measured using a mouse urinary excretion bioassay. Nickel-RBA varied from 7.89% to 33.8% at an average of 19.1 ± 18.6%. The variation was not explained well by variation in soil properties including Ni speciation and co-contamination of other metals, which showed weak correlation with Ni-BRA (R2 < 0.36). In comparison, the Ni-RBA variation was explained well by the variation of soil-Ni solubility in simulated human gastric or gastrointestinal fluids, i.e., Ni bioaccessibility. Determined using the gastric (GP) and intestinal phases (IP) of solubility bioaccessibility research consortium (SBRC), physiologically based extraction test methods (PBET), and unified BARGE method (UBM), Ni bioaccessibility explained 54–71% variation of the Ni-RBA, suggesting that Ni oral bioavailability was predominantly controlled by Ni solubility in the GI tract. The results highlight the suitability of using simple, fast, and cost-effective bioaccessbility assays to predict site-specific Ni oral bioavailability.

Developing a Harvest Plan by Considering the Effects of Skidding Techniques on Forest Soil Using a Hybrid TOPSIS-Entropy Method

Abstract The aim of this study was to evaluate skidding techniques, which result in minimal damage to the soil, depending on the slope and stand type. Thus, three skidding techniques with tractor for harvesting (suspended skidding [SS], using a skidding cone [SC], and cable-pulling [CP]) were used in six different study sites and the variations in soil properties were examined at three different slopes (0%–20%, 20%–33%, &amp;gt;33%), 2 different stand types (A, B), and 2 different soil depths (0–5 cm, 5–10 cm). Soil bulk density, soil organic matter, soil compaction, organic carbon (C), and total nitrogen (N) were determined. The Entropy and TOPSIS methods were used among the multiple-criteria decision-making methods for six different coniferous stands. With the combination of the Entropy and TOPSIS methods, we found that slope was an important factor in determining the preferred skidding technique. Suspended skidding was seen as the preferred method of skidding technique in the 0–20% slope group. For the 20%–33% slope group, the usability of the three methods varied depending on stand type and soil depth, whereas the technique using a skidding cone was found to be the preferred skidding technique in the &amp;gt; 33% slope group.

Assessing the Spatial Variability of Soil Properties to Delineate Nutrient Management Zones in Smallholder Maize-Based System of Nigeria

Spatially explicit information on soil variability is relevant for agronomic decisions; however, such information is limited in the northern Guinea savanna (NGS) agroecological zone of Nigeria. This study was conducted to delineate soil nutrient management zones (MZs), based on spatial variability of soils in the smallholder maize-based farming system within the NGS. Two hundred and eighty-nine soil samples were analyzed for some physical and chemical properties. Principal component analysis (PCA) was used to aggregate the soil properties into four principal components, which accounted for about 60% of the variation in the data, and spatial variability was assessed with a semivariogram. The ordinary kriging technique was used to predict soil properties at unsampled locations, while weighted overlay analysis was conducted to delineate nutrient management zones. Results showed that total nitrogen (0.06%), available phosphorus (5.6 mg kg−1), organic carbon (0.66%), and effective cation exchange capacity (5.6 cmol(+) kg−1) are below optimal requirement for maize production. Four MZs were identifiable in the region with the highest fertility (MZ3 and MZ4) associated with the northern area but covering a relatively small part (9.1%). The differences observed in soil properties among the MZs suggest that each zone requires different agronomic management, especially in relation to fertilizer application.

Distribution Characteristics of Soil Particles and Their Relationships With Soil Organic Carbon Components in the Alluvial/Sedimentary Zone in the Lower Reaches of the Yellow River

Land use and sediment alluviation/deposition are the main factors influencing the vertical distributions of particles with different sizes and soil organic carbon (SOC) forms. Based on field investigation, experimental analysis, data analysis, soil particle characteristics, and the relationships with SOC compositions are studied in the typical alluviation/deposition area of Kaifeng–Zhoukou. In the soil profile, the particulate matter is mainly 10–50 μm and 50–250 μm in size with an average content of approximately 65%, the content difference within the same size particle range is small. There is a large content range of &amp;lt;1,000 μm particles, which is the main factor affecting the change in soil properties. The fractal dimension (D) of soil particles ranges from 2.21 to 2.78. The value of D of each layer in farmland is higher than that of each layer in woodland, and it has been observed that DNF(farmland in the nonflooded area) &amp;gt; DF(farmland in the flooded area) and DNW(woodland in the nonflooded area) &amp;gt; DW(farmland in the nonflooded area). The contents of particles smaller than 50 μm have a positive effect on D, and the particles exceeding 50 μm have a negative effect. The contents of 10–50 μm, &amp;lt;2 μm, 2–5 μm, and 5–10 μm particles and their dynamic variances are the root causes of the D differences in the farmland/woodland soil in the FA (the flooded area) and NFA (the nonflooded area). SOC components combine to a greater extent with silt and clay that are &amp;lt;10 μm in size in the NF, and the stability is relatively high. The contents of the 10–50 μm and &amp;lt;10 μm particles are the main reasons for the differences in the soil active and nonactive organic carbon (AOC and NOC, respectively) contents in the FA and the NFA. The difference in D can reflect the change in SOC and its components and can be used as an index to characterize the variance in soil properties and quality. This study revealed the influences of the different particle sizes in the SOC components, which will expand and enrich the current area of study and further provide a basis to increase SOC and improve soil quality.

Delineation of nutrient management zones for precise fertilizer management in wheat crop using geo‐statistical techniques

AbstractUnderstanding the variability in crop yield in relation to the spatial variations in soil properties can help to more efficiently apply agricultural inputs on a site‐specific basis. This study was designed to characterize and quantify the spatial variation in soil properties and wheat yield and to delineate prescription maps for site‐specific fertilization. A wheat field was selected at the research farm of the University of Agriculture, Faisalabad, Pakistan, and a grid pattern (30 m * 30 m) was established at the experimental sites to collect soil and crop yield samples at two sampling depths (0–15 &amp; 15–30 cm). The soil samples were analysed for soil nitrogen (N), phosphorus (P), potassium (K), pH, electrical conductivity (EC), soil organic matter (SOM) and saturation (S) at both sampling depths. The locations of the sampling points and field boundary were marked with a GPS receiver. Results of classical, geo‐statistical and interpolated maps revealed significant spatial variability in soil properties and crop yield, demanding for site‐specific nutrient management. The cluster analysis was performed to group the soil and yield data into five productivity zones termed as ‘very low’, ‘low’, ‘medium’, ‘high’ and ‘very high’ without prior knowledge of productivity potential with the internal homogeneity and external heterogeneity at a similarity level of greater than 70%. Results of correlation matrix suggested significant relationships among the crop yield and the soil properties. Results of means comparison in different productivity zones indicated that the crop yield and soil properties were significantly different in developed management zones except ‘low’ and ‘very low’ zones. Significant variation of soil nutrients in very low‐to‐very high productivity zones at both sampling depths suggested that the soil nutrients in combination with soil pH and organic matter can be used to develop prescription maps for site‐specific fertilization. Furthermore, the results of this study emphasize the need to predict soil and crop variables using sensors, in future studies, to delineate prescription maps, as soil sampling and analysis is expansive and time consuming. Site‐specific fertilization based on soil and crop needs can improve economic and environmental efficiency.

Soil Bunds Effect on Soil Properties under Different Topographies of Southwest Ethiopia

Soil erosion is a major environmental problem affecting development endeavors. Physical soil and water conservation (SWC) measures such as soil bunds are implemented to mitigate soil erosion. However, information on the effects of soil bunds on soil fertility is limited. This study aimed to evaluate soil quality in fields with soil bunds and with no soil bunds in steep, middle and lower sloping cultivated lands as well as spatial variation of soil properties in between bunds in southwest Ethiopia. About 7-15 years old bunds and nearby cultivated fields lacking bunds were assessed. From 0 cm-20 cm soil depth, 36 soil samples were collected. Soil texture, soil organic carbon (SOC), total nitrogen (Ntot) and exchangeable potassium (Kexch) were analyzed. Soil bunds showed significantly (p&lt;0.0.5) greater clay but less sand than adjacent no-bund fields. In steep, middle, and lower slopes, concentrations of SOC and Kexch were greater in fields with soil bunds than without. Lower slope fields showed greater clay, SOC and nutrients than steep slopes. In between soil bunds, soil was more fertile at bunds than below the bunds. In Fanta watershed, soil bunds are a vital conservation measure to retain soil fertility in cultivated mountainous areas.

Fragility analysis of a pipeline under slope failure-induced displacements occurring parallel to its axis

Providing urbanized centers with hydrocarbon supplies from remote production centers, transmission pipelines run for thousands of kilometers, inevitably traversing mountainous and rugged terrain, where slope failure is the dominant source of risk. Strategies to manage these risks heavily depend on the quantification of uncertainty. To this end, this paper presents a fragility analysis framework to quantify the effect of uncertainties, that makes use of a Random Forests algorithm as a surrogate model to thoroughly explore the uncertain parameter space. The Random Forests algorithm is trained and tested against a small, yet statistically significant sample of Sliding Slope-Pipeline Interaction (SSPI) cases that are meticulously analyzed using a rigorous 3D continuum-based numerical methodology. The fragility analysis framework is applied to a 36 in. pipeline descending a slope, with possible soil movement occurring parallel to its axis. Uncertainty stems from the variability in soil properties (friction angle, cohesion and density), in pipe steel material properties (yield strength), in the magnitude of operational loads (pressure and temperature) and in the pipeline placement depth around their expected values, as well as from the lack of knowledge of the geological conditions (the depth of the eroded surficial layer) that ultimately control the shape of the failure surface. Τhe significance of each uncertain variable on the response of the pipeline is investigated, concluding that the depth and shape of the failure surface (correlated with the depth of the surficial layer) is be the most influential parameter, governing the pipeline performance and ultimately the safety thresholds.

Variations in peat soil properties at the west coast of Sumatra Island

Peat in coastal areas has different characteristics compared to peat in inland areas because coastal peat usually has high DHL, pyrite, marine sandy substratum, and maturity which is generally classified as hemic to sapric. These variants in soil characteristics drive peculiarity in its management. For this reason, a more detailed information about the characteristics is needed to allow sustainable management and utilization. A total of 78 peat soil samples from 20 peat soil profiles taken over west coast of Sumatra was studied and analyzed for their physical and chemical properties. Field observations were made using a peat auger to determine thickness and maturity, substratum, presence of pyrite, and others. Results showed that peat thickness varied from shallow (50-100 cm), medium (100-200 cm), to very deep (>700 cm); peat situated closer to the coast generally has shallow peat depth. Peat soil in coastal areas contained a mineral soil substrate with a sand content of >70%. It was found that soil had a hemic maturity level and a very acidic to acidic pH value (pH 2.5-5.4). The P2O5 content extracted by 25% HCl varied from low to moderate, while K2O content of 25% HCl extraction was very low. Cations K, Na, and Ca were very low to very high, while Mg spanned from very low to high. Based on its thickness, 25% of peatland were not suitable (Nrc) for general agriculture uses because of >300 cm thickness. Therefore, it is necessary to improve soil fertility and water management in several places.

Quantifying the relationships of soil properties and crop growth with yield in a NPK fertilizer application maize field

Spatial variability of soil properties, crop performance, fertilization management, and tillage methods play an important role in yield prediction and improvement. However, the farm nutrient management in most regions of the world is still based on conventional and uniform management strategies, without take into consideration the spatial variability of the above factors. Therefore, the objectives of this study were to delineate potential management zones (MZs), with the considering of spatial variability of soil properties, crop performance, fertilization management, tillage methods, and investigate their relationships with yield, and their contributions to yield in each management zone. A 1.60 ha maize field with fertilizer and tillage management, in Lishu County, Jilin Province, China, was selected as the study area and soil samples with soil organic matter, total nitrogen and soil pH measured values, crop samples with crop height, leaf nitrogen content, above ground biomass at V6, silking, and maturity growth stages, and yield measured values were collected in 2019 and 2020. Firstly, the rectangular MZs were defined to divide the study area into relatively homogeneous areas based on the spatial variability of soil properties, crop performance, and yield of 2019 and 2020. Secondly, the correlations of soil properties and crop performance with yield were obtained across MZs and growth stages in 2019 and 2020. Lastly, the yield prediction models were established based on the above four types of factors by using random forest (RF) model and the contributions of main factors were obtained quantitatively across different MZs and years. The results showed that (1) the small maize field was divided into three rectangular MZs and most of the soil and crop attributes presented homogeneous characteristics in each zone; (2) correlations of soil properties and crop performance with yield varied across different MZs and growth stages, and even different years; (3) RF model obtained good performance across MZs and years, with R2 = 0.86 and RMSE = 0.77 kg/ha in 2019 and R2 = 0.89 and RMSE = 1.04 kg/ha in 2020 both for the whole field. The contribution of main factors for yield varied across both MZs and years, while some characteristics of the main factors’ contributions remain unchanged. This study would open the opportunity to farmers and agricultural experts for site-specific nutrient management in the maize field.

Digital soil mapping of PAU-Regional Research Station, Kapurthala, Punjab, India

Digital soil mapping is an invention that uses modern technologies to express geographical soil information. Across the country, there has been a transition of digital soil mapping from the research phase to the operational phase, but no comprehensive research has been conducted at the Regional Research Station in Kapurthala. Instead of dealing with the whole field as a single unit, dealing with small units per spatial soil properties is the first step towards sustainable agriculture. However, all soil's spatial variations could not be corrected with one blanket recommendation. Considering this in mind, the current investigation carried out the research station with 84.4 ha of agricultural land comprising eight blocks, with an objective of delineating the spatial variation in soil properties viz. soil organic carbon (%), electrical conductivity, pH, available Phosphorus, potash, zinc, iron, manganese, and copper (mg kg−1), respectively on to the soil maps prepared using geo-statistics. Finally, digital soil mapping (DSM) was prepared for dealing with such spatial soil variation after preparing the base maps using GPS-60 (GARMIN). For this purpose, 40 representative spatial soil samples were collected from all the blocks. DSM delineated that most spots are low in SOC at the farm while available P, K, and Cu are sufficiently available. Further, the micronutrients DTPA-Zn, Fe, and Mn, were reported with spatial deficiencies in different blocks. Therefore, these recommendations help in the more sustainable and judicious use of the fertilizers on one side while also helping in controlling micronutrient deficiencies before their symptoms appear. Henceforth, DSM must be prepared and is a prerequisite to achieving sustainability in any soil–plant interphase despite any agro-climatic zone and soil textural class to improve soil health and practice sustainable agriculture at the farm.

Spatial variability of soil properties determined by the interpolation methods in the agricultural lands

Spatial variability of soil properties determined by the interpolation methods in the agricultural lands

Detecting spatial variability of soil compaction using soil apparent electrical conductivity and maize traits

AbstractSoil compaction is one of the main limiting factors for sustainable agriculture. Efficient methods for detecting the distribution of soil compaction at a field scale are urgently needed in precision agriculture. We evaluated the possibility to detect soil compaction from measurements of apparent electrical conductivity (ECa) by using electromagnetic induction (EMI) and maize traits at a ~1 ha field parcel. The soil was Luvisol, and soil compaction‐related properties, such as bulk density (BD), penetration resistance (PR), soil texture, soil salinity, soil moisture and maize traits, were measured at ten locations across the field based on ECa variability. In this site‐specific study, no good correlation between soil compaction properties (i.e. BD and PR) and ECa was found but soil clay content was positively related to ECa in the sublayer (P = 0.08). The variation in the unmanned aerial vehicle (UAV)‐derived maize canopy height was significantly negatively correlated with soil compaction and a negative relationship between dry above‐ground biomass and BD and PR existed at 25–50 cm layer. In addition, ECa and UAV‐derived maize canopy height was negatively correlated (Spearman's rank correlation coefficients of −0.67 in the 0–25 cm layer) under the rather dry conditions prevailing during this study. Overall, as could be expected, detecting soil compaction with ECa was challenging under heterogeneous terrains, while maize traits had a better correlation with spatial variability of soil compaction. Owing to its sensitivity to the integral variation of multiple soil properties, ECa was a good indicator of maize canopy height.

Multi-objective optimization design of pile-anchor structures for slopes based on reliability theory considering the spatial variability of soil properties

Pile-anchor structures (PAS) are emerging as a promising tool for slope stabilization and landslide mitigation. However, the optimized design of PAS is an essential yet challenging issue. In particular, there is an irreconcilable contradiction between the safety and cost-efficiency in PAS design, and a coordinated balance between these two factors is critical for safe and practical applications. Previous optimization design studies rarely considered the uncertainty of PAS-reinforced slope systems while the spatial variability of soil properties has a significant impact on the optimization design. This study, therefore, proposes a framework for the multi-objective optimization design of PAS in slopes based on reliability theory and in consideration of the spatial variability of soil properties. The study is automated by coupling a multi-objective optimization design using Pareto optimality theory and PAS-reinforced slope simulations using Monte Carlo simulations to consider the spatial variability of soil properties. An illustrative example of the PAS design for a two-layer slope is provided to demonstrate the proposed framework. The results suggest that the optimal PAS design achieved meets the minimum failure probability and has the lowest total cost. This study aims to motivate the subsequent development of optimization design for slope engineering.

Full probability design of soil slopes considering both stratigraphic uncertainty and spatial variability of soil properties

Full probability design of soil slopes considering both stratigraphic uncertainty and spatial variability of soil properties

Computation of pull-out resistance of pressure-grouted soil nails in sand using cavity expansion and contraction solutions

ABSTRACT Pressure-grouted soil nailing has been extensively used as a soil stabilization technique in transportation infrastructure projects, wherein resistance against pull-out failure is offered by shear resistance mobilized along the nail–soil interface. However, the different stages of soil nail installation significantly alter the soil properties and residual normal stress at the grout-soil interface and thereby the maximum pull-out shear stress. This article presents a computational procedure to predict the maximum pull-out shear stress of pressure-grouted soil nails in sand, incorporating the variation in soil properties and stresses throughout the installation processes and loading. The procedure is formulated within the framework of cavity expansion-contraction solutions as the entire installation and testing phases resemble either expansion or contraction of a cylindrical cavity. The proposed approach was validated using grouting and pull-out test data of soil nails in sand. The influence of various parameters on pull-out shear stress has also been examined.

Multi-Sensor Approach Combined with Pedological Investigations to Understand Site-Specific Variability of Soil Properties and Potentially Toxic Elements (PTEs) Content of an Industrial Contaminated Area

A combination of indirect soil investigation by proximal soil sensors (PSS), based on geophysical (ARP, EMI), physical (Cone Index –CI– by ultrasound penetrometry) and spectrometric (γ-rays) techniques, as well as pedological surveys, was applied in the field to assess the spatial variability of soil pollution and physical degradation in an automobile-battery recycling plant in southern Italy. Five homogeneous zones (HZs) were identified by the PSS and characterized by soil profiles. CI measurements and field analysis showed clear features of physical (i.e., soil compaction, massive structure) degradation. XRF in situ (on profiles) analysis using portable equipment (pXRF) showed Pb, Cd and As concentrations exceeding the contamination thresholds provided by the Italian regulation for industrial land use up to 20 or 100 cm of depth. Hence, a validation procedure, based on pXRF field survey, was applied to the PSS approach used for the HZs identification. High consistency was found between the HZs and the PTEs in the most contaminated areas. Significant negative Pearson correlation coefficients were found between γ-rays dose rate and Pb, Cu, Zn, As and Ni; positive ones were found between γ-rays and autochthonous lithogenic elements (V, Ti, Mn, K, Sr, Nb, Zr, Rb, Th), confirming that higher radionuclide activity correlated with lower pollution levels.

Modelling the effect of catena position and hydrology on soil chemical weathering

Abstract. The sensitivity of chemical weathering to climatic and erosional forcing is well established at regional scales. However, soil formation is known to vary strongly along catenas where topography, hydrology, and vegetation cause differences in soil properties and, possibly, chemical weathering. This study applies the SoilGen model to evaluate the link between the topographic position and hydrology with the chemical weathering of soil profiles on a north–south catena in southern Spain. We simulated soil formation in seven selected locations over a 20 000-year period and compared it against field measurements. There was good agreement between simulated and measured chemical depletion fraction (CDF; R2=0.47). An important variation in CDF values along the catena was observed that is better explained by the hydrological variables than by the position along the catena alone or by the slope gradient. A positive trend between CDF data and soil moisture and infiltration and a negative trend with water residence time was found. This implies that these hydrological variables are good predictors of the variability in soil properties. The model sensitivity was evaluated with a large precipitation gradient (200–1200 mm yr−1). The model results show an increase in the chemical weathering of the profiles up to a mean annual precipitation value of 800 mm yr−1, after which it drops again. A marked depth gradient was obtained for CDF up to 800 mm yr−1, and a uniform depth distribution was obtained with precipitation above this threshold. This threshold reflects a change in behaviour, where the higher soil moisture and infiltration lead to shorter water transit times and decreased weathering. Interestingly, this corroborates similar findings on the relation of other soil properties to precipitation and should be explored in further research.

Pedotransfer functions for cation exchange capacity estimation in highly weathered soils of the tropical highlands of NW Cameroon

Cation exchange capacity (CEC) is a very important soil property widely used in the assessment of soil quality. Unfortunately, its determination in the laboratory can be very tedious, especially when samples are many, necessitating high costs and time. To curb these challenges, pedotransfer functions (PTFs) can be used as indirect and reliable tools for CEC estimation using easy-to-measure soil properties such as pH, soil organic carbon (OC), and texture. Soil survey data from 98 soil profiles in the North West region of Cameroon, belonging to eleven Reference Soil Groups (RSGs) classified as Acrisols, Andosols, Cambisols, Ferralsols, Fluvisols, Histosols, Regosols, Nitisols, Alisols, Luvisols, and Chernozems were used to develop pedotransfer functions for estimating CEC in these soils. Pedotransfer functions were developed using linear and non-linear regressions, while their reliability was evaluated using the error ratio (ER), the geometric mean error ratio (GMER), and root mean square error (RMSE). Predicted and measured CECs were equally compared using non-parametric tests to assess the deviations observed. To enhance the quality of the PTFs, stratifications of the data were done at various levels; (i) pooled data for all soil samples, (ii) within each RSG and (iii) within pedogenic soil horizons. Results indicate that PTFs obtained within the various reference soil groups were better than those obtained from pooled data due to the reduced variability of soil properties. Best results were obtained when soils were stratified according to pedogenic soil horizons. The best PTFs were observed in the most highly weathered soils, the Ferralsols, probably associated with their existence in the near steady state with greater stability and equilibrium among various soil properties. In most of the cases, OC proved to be the dominant soil property contributing to CEC. Results of this study will enable estimation of CEC from available soil survey data in the study area and similar environments, as well as the need to consider stratifications in terms of soil types and pedogenic soil horizons as reported in the literature to improve the reliability of PTFs.

Shift in tree species changes the belowground biota of boreal forests.

Summary The replacement of native birch with Norway spruce has been initiated in Norway to increase long‐term carbon storage in forests. However, there is limited knowledge on the impacts that aboveground changes will have on the belowground microbiota.We examined which effects a tree species shift from birch to spruce stands has on belowground microbial communities, soil fungal biomass and relationships with vegetation biomass and soil organic carbon (SOC).Replacement of birch with spruce negatively influenced soil bacterial and fungal richness and strongly altered microbial community composition in the forest floor layer, most strikingly for fungi. Tree species‐mediated variation in soil properties was a major factor explaining variation in bacterial communities. For fungi, both soil chemistry and understorey vegetation were important community structuring factors, particularly for ectomycorrhizal fungi. The relative abundance of ectomycorrhizal fungi and the ectomycorrhizal : saprotrophic fungal ratio were higher in spruce compared to birch stands, particularly in the deeper mineral soil layers, and vice versa for saprotrophs.The positive relationship between ergosterol (fungal biomass) and SOC stock in the forest floor layer suggests higher carbon sequestration potential in spruce forest soil, alternatively, that the larger carbon stock leads to an increase in soil fungal biomass.