Related Soil Properties Research Articles

Variation in Soil Aggregate Stability Due to Land Use Changes from Alpine Grassland in a High-Altitude Watershed

Land use change affects soil aggregate composition and stability, which impacts soil structure and health. To reveal how land use change impacted soil aggregates of alpine grassland in a high-altitude watershed, soil samples from 161 sites including alpine grassland, cropland and abandoned land were selected to measure and analyze the distribution of aggregate fractions (macro-aggregates, micro-aggregates, silt+clay), soil aggregate stability (mean weight diameter, geometric mean diameter, fractal dimension, etc.) and related soil properties (soil organic carbon content, soil particle composition, etc.) in the Huangshui River watershed of the Qinghai–Tibet Plateau. The results showed: (1) As alpine grasslands were converted to croplands and croplands to abandoned lands, the proportion of macro-aggregates and the aggregate stability index showed a trend of first decreasing and then increasing (p < 0.05), indicating that tillage and abandonment have significant influences on soil aggregate structure. (2) Compared with temperate grassland, alpine grassland had richer soil organic carbon, and a higher ratio of macro-aggregates and aggregate stability. (3) Soil organic carbon and sand content had distinct influences on the fractions and stability of aggregates during land use change. These results suggested that cultivation can substantially reduce the soil aggregate stability in alpine grassland, whereas abandonment can effectively improve soil aggregate structure.

Assessment of Variability among Humus Forms and Soil Properties in Relation to Tree Species and Forest Operations in the Kheyrud Forest, Nowshahr

Tree species and litter play a key role in the functioning of forest ecosystems as influential factors affecting soil ecological processes and the distribution of humus forms. This study investigates the morphology of humus under the litter of different trees on compacted skid trails at different time intervals after skidding operations (6, 10, and 20 years) in the Kheyrud forest, Nowshahr. Each skid trail was identified with three replications in pure beech, beech-hornbeam and mixed beech stands and a total of 81 profiles with dimensions of 30 × 30 cm, drilled and classified using the European Humus Group Proposal (EHGP). According to the results, the mull of the most dominant humus was under the mixed beech litter, while in the pure beech litter the amphi humus was the most abundant form of humus. Three types of humus mull, moder, and amphi were observed in the skid trail under the beech-hornbeam litter. Oligomull was the most abundant form of humus mull in the skid trail under mixed beech litter, while in the trails under pure beech Eumacroamphi, Eumesoamphi, and Hemimoder were the most common forms of humus amphi and moder. Also, the thickness of the organic layer (Organic litter, Organic fragmentation, and Organic humus) was higher in all skid trails under the pure beech litter as compared to other treatments, while from younger trails (6 years) to older trails (20 years), the thickness of the organic-mineral horizon (Ah) increased under the beech mixed litter. We can conclude that different litter types were the main factor to control the presence of different forms of humus after forest operations.

Correlation between soil erodibility and light penetrometer blows: A case study in Sungai Langat, Malaysia

The soil erodibility (K) factor is one of the key parameters used for predicting and estimating soil erosion in models such as Universal Soil Loss Equation (USLE) and Modified Universal Soil Loss Equation (RUSLE). It is the inherent resistance of soil to survive erosion and reflects the susceptibility of soil to the erosion process. Long-term studies for direct measurement of K factor are time-consuming and expensive, so efforts were made by the researchers to develop simple indices to relate soil properties with K factor for instant and economical estimation of erodibility. Mackintosh Probe is a portable and lightweight dynamic penetrometer that provides a relatively fast, economical, and easy assessment of subsoil. In this study, soil samples were collected from the Sungai Langat site, and a series of laboratory tests, including sieve analysis, hydrometer analysis, and organic matter content, were performed. K factor was determined by employing Wischmeier and Tew equations. The mean values of the K factor for the Sungai Langat site were found to be 0.005 and 0.0045 for Tew and Wischmeier equations, respectively. Multiple regression analysis was performed to analyze the relations between Mackintosh Probe and K factor, which the coefficient of multiple correlation values of 0.345 and 0.352 for the Tew and Wischmeier equation, respectively. Although the analysis represented a weak relation between Mackintosh Probe values and K factor, however, it provides a basis for the research perspective to simplify the estimation of soil erodibility with a minimalistic experimental setup.

Meta-Analysis of Soil Property Relationships and Construction Platform Design

This paper introduces the concept of using an existing low-volume road design method to design the lower granular layers within a mechanistic-empirical design to ensure an adequate construction platform. The DCP-DN design method was chosen because it has advantages over other cover-based empirical methods in this context, including utilizing a full-depth measurement and requiring a balanced layer profile. To implement the DCP-DN method and use field Dynamic Cone Penetrometer (DCP) data in the mechanistic-empirical design, a relationship to convert between stiffness and DCP penetration index was required. A new set of internally consistent relationships between various soil strength and stiffness parameters was thus developed, using a meta-analysis of 126 models published since the 1960s. These were used to develop a new nomograph for estimating the properties of various soils.

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

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

Crop residue return improved soil nitrogen availability by increasing amino acid and mineralization under appropriate N fertilization

AbstractSoil organic nitrogen (SON) and its mineralization are among the most critical factors that affect soil N availability. However, it is unclear how crop residue return and chemical N fertilization affect soil N availability by altering SON and its mineralization. Therefore, we studied the SON pools, SON mineralization, and related soil properties and enzymes activities in the lower reaches of the Yangtze River Valley in China with stand ages of 7‐year N (0, 75, 150, and 300 kg N ha−1) fertilization and 4‐year barley‐cotton residue return. Regardless of residue retention or removal, the contents of total SON and its fractions (ammonium N, amino acid N, amino sugar N, and unidentified N) increased consistently with the increasing of N input, while SON mineralization, microbial biomass N content, urease and protease activities showed a curvilinear response that was highest at N rate of 150 kg N ha−1. Crop residue returning significantly increased SON content under 75 and 150 kg N ha−1, mostly due to the increase of amino acids N. Other variables, such as SON mineralization, microorganism, and enzymes, were also enhanced by residue returning, and the largest increases were observed at 150 kg N ha−1. In addition, our result also show that excessive N input (300 kg N ha−1) would reduce soil N availability by mainly suppressing microbial N processes. We concluded that crop residue combined with appropriate N has a great potential to improve soil N availability by mainly improving amino acid N content and SON mineralization.

EFFECTS OF SELECTED SOIL AND WATER CONSERVATION STRUCTURES ON SOIL PHYSIOCHEMICAL PROPERTIES, LEMO WOREDA, SOUTHERN ETHIOPIA

Soil erosion is now almost universally recognized as a serious threat to man's well-being, if not his very existence. As a result, we assessed the soil physicochemical properties of two possible levels of level bund and fanya juu. The experiment assessed from seven locations with three replications was used to collect soil samples from each soil conservation structure. Five composite soil samples were collected from each soil structure based on slope (0-30cm). Soil physicochemical properties such as erosion index, dispersion ratio, and erodibility proportionality ratio were investigated. The effect of different soil structure levels revealed that soil properties differed significantly (P≤0.05) for all parameters studied. The control plots had significantly higher (P≤0.05) dispersion ratio, erosion indexes, and erodibility proportionality than the soils treated by the level bund and level Fanya juu structures. On the control plot, this result showed lower clay content and higher sand content. The level of soil bund and fanya juu had a significant (P≤0.05) effect on selected soil parameters. As a result, all related soil properties show a positive relative change when the level of soil bund and fanya juu is compared to the control plot. Aside from this result, the dynamic natures of the sciences compel us to conduct additional research based on the agro-ecological zones of the study area.

Terrain Variables Based Spatial Mapping of Soil Properties in a Watershed of Himalayan Landscape Using Random Forest Model

Soil information, including their spatial variability is vital for devising various soil and land management policies and strategies as well as assessing the environmental impact of different land use changes. Among the various soil forming factors, terrain plays a vital role in determining the spatial distribution of soil properties especially in hilly terrains due to its impact on soil processes as well as the redistribution of soil materials. The study was carried out for assessing the applicability and efficiency of various terrain parameters for prediction as well as spatial mapping of different soil properties using Random Forest (RF) modeling approach, in a mid-Himalayan watershed located in Tehri Garhwal district, Uttarakhand. Field data collection was done by collecting soil samples from 0-15cm depth (surface layer) at 68 different locations in the study area, following a transect survey method. Collected samples were pre-processed and analyzed in the laboratory for estimating various soil properties such as sand, silt and clay contents as well as soil nutrients such as Soil Organic Carbon (SOC) and nitrogen (N). Fifteen terrain parameters derived by digital terrain analysis of CartoDEM of 10m spatial resolution were used as predictor variables during RF modeling. Pearson correlation analysis revealed poor linear relationship of soil properties with various terrain parameters. Variable importance ranking revealed that compound topographic index, elevation, heat load index, integrated moisture index and mean curvature are the most important variables, explaining maximum variability in different properties. The performance of RF models for predicting various soil properties were evaluated based on the coefficient of determination (R2), Root Mean Square Error (RMSE) as well as Lin’s Concordance Correlation Coefficient (CCC). The models were found to perform well with R2 and CCC values of 0.47 and 0.50 for sand, 0.52 and 0.55 for silt, 0.44 and 0.57 for clay, 0.41 and 0.36 for organic carbon and 0.55 and 0.34 for nitrogen, respectively. The validated models were further employed for generating the spatial distribution maps of various soil properties. Such attempts combining various environmental variables with machine learning based models may aid us in mapping the spatial distribution of various soil properties in the hilly mountainous terrains with considerable accuracies.

Relationship of Selected Soil Properties with the Micronutrients in Salt-Affected Soils

The present study aimed to assess the relationship of soil properties in salt-affected soils. The soil samples were collected from 14 districts of Pakistan. Soil salinity and sodicity are the common features of the arid and semiarid regions. The effects of the salt’s interactions with soil micronutrients have not been well studied. Therefore, saline and non-saline soil samples were collected from different locations. The microelements (Fe, Cu, Mn, and Zn) were fractionated into water-soluble, exchangeable, carbonate, Fe + Mn oxide, organic, and residual fractions. Univariate and multivariate analysis (PCA) was carried out to determine the linear relationship between soil properties and micronutrients fractions. Results showed that the magnitude of micronutrients appeared to be affected by the salinity in soils. In saline soil, the Fe fractions differed in the order of residual > organic bound > Fe + Mn bound > carbonate bound > exchangeable > water soluble. Iron fractions varied in the non-saline soils as residual > Fe + Mn bound > organic bound > exchangeable > carbonate bound > water soluble. Copper concentration was higher in the residual and carbonate forms, and the amount was lower in the exchangeable and water-soluble forms under both saline and non-saline conditions. The water-soluble Mn fraction was lower, and the residual Mn fraction was proportionately higher than other forms of Mn in soils. Zinc was found mostly in the residual fraction in both saline and non-saline soils. The mobility factor of micronutrients in non-saline soil was greater than in saline soil. PCA revealed that organic matter (OM) and pH directly affected the fractionation of Cu, Mn, Zn, and Fe in soil. Thus, it could be inferred that salts can bring changes to the composition of micronutrients depending on the nature of the soil and the magnitude of salts.

Intensive forest harvest increases N2O emission from soil: A meta-analysis

A comprehensive evaluation of the impact of forest harvest on soil N2O flux at the global scale is currently unavailable. In this study, by using a global meta-analysis of 64 observations from 29 peer-reviewed publications over the last 30 years, we elucidated how forest harvest impacted soil N2O flux and related soil properties. Intensive forest harvest significantly increased soil N2O flux with a mean effect size of 0.85 and the increase was associated with elevated soil temperature, increased concentration of NO3−-N and decreased soil pH. The effect on soil N2O flux lasted for around six years, and soil N2O emission depended on existing forest types in the late stage (the recovery period >6 years) after harvest. Forest harvest clearly increased soil N2O flux, with effect size ranging 0.73–2.12, in broadleaf forests but did not significantly affect it in coniferous and mixed broadleaf-conifer forests. In addition, the time required for the complete recovery from harvest in terms of N2O flux was difficult to define because of the scarcity of long-term experiments. Overall, this study provides the first formal global-scale assessment on how forest harvest intensity, forest types and the time since harvest affect soil N2O flux. The findings of this study help to narrow the knowledge gap regarding the effect of forest harvest on soil N2O flux, and to facilitate decision making to decrease soil N2O emission post forest harvest.

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.

Pedological assessments along an arid and semi-arid transect using soil spectral behavior analysis

Reflectance spectroscopy as an efficient proximal sensing method, can be employed in soil genesis, monitoring, and management studies. However, limited data about the performance of this technique in different pedoenvironmental conditions is available. This study was conducted to investigate the capability of VIS-NIR-SWIR in detection of soil variations along a transect, monitoring the vertical changes of soil properties in relation to soil-forming factors and processes, and determination of the relationship between soil variables and their effects on the spectral features. Nine representative pedons were selected on different geomorphic positions including alluvial fan, piedmont plain, flood plain, and lowland. Soil samples were collected from different diagnostic horizons and analyzed for routine physico-chemical properties, iron forms, clay mineralogy, and VIS-NIR-SWIR spectroscopy. The results of the spectral interpretations revealed that the differences between soil horizons, clay mineralogy and the variations in key soil properties can be detected regarding the reflectance intensity, shape and absorption features. Smectite, chlorite, illite, kaolinite, and palygorskite were identified in the studied soils based on X-ray diffraction (XRD) analyses and their detection ranges were presented using spectral library and the second-derivative spectrum analyses. OC, CEC, clay, Fed and ᵡlf were negatively correlated with the reflectance wavelengths, while CCE, EC, sand, silt, and the evolution index (Feo/Fed) showed positive correlations. The most important factors affecting spectral behavior of the studied soils were found as particle size distribution, clay minerals, iron oxides, organic carbon, gypsum, CaCO3, soluble salts, and soil drainage conditions. Moreover, quantitative estimation of soil properties using partial least squares regression (PLSR) model showed VIS-NIR-SWIR to be accurate for estimation of CEC (RPD > 2), and reliable for OC, clay, Fed and ᵡlf (1.4 < RPD < 2). Overall, the results highlighted the significant role of VIS-NIR-SWIR on pedological assessments through soil characterization and differentiation of the horizons.

Variation in Carbon Sequestration and Soil Properties in Relation to Stand Age in Maple and Alder Plantations

ABSTRACT Increased CO2 levels caused by human activities (e.g., fossil fuel consumption and deforestation) has become a major concern for climate change and caused environmental problems. Afforestation/reforestation can help mitigate CO2 emission in the atmosphere by sequestering atmospheric carbon (C) in tree biomass. Herein, the above- and below-ground C sequestration of two pioneer tree species, including Acer velutinum Bioss and Alnus glutinosa L plantation stands of 25 (A25) and 35 (A35) years old were studied. The mean annual growth of diameter at breast height (cm/year) was significantly higher in A35 than A25, while the mean growth of height (m/year) was significantly higher in A25. The total and mean annual growth of the tree biomass and C storage (root and trunk) was significantly higher in A35. The amount of soil C sequestration in A35 was also significantly higher than in A25. The above-ground C sequestration and the annual average of C sequestration of the trees were positively correlated with soil moisture, pH, nitrogen, and phosphorus. Our study illustrates the benefits of considering stand age in the growth and developmental patterns of forest ecosystems in estimating terrestrial C stocks.

Land use driven change in soil organic carbon affects soil microbial community assembly in the riparian of Three Gorges Reservoir Region

After decades of anti-seasonal water fluctuation in the Three Gorges Reservoir (TGR), a distinctive riparian zone had been formed and played critical roles on soil biogeochemistry cycling, substance exchange and soil microbial functions. However, the effect of land use on terrestrial ecological processes and soil microbial community assembly in riparian zone was still imprecise. This study focused on the relationship of soil properties and microbial communities in paddy and dryland soils of a typical riparian zone in the TGR. The results indicated a higher level of accumulation of total organic carbon (TOC) in paddy soil (14.88–20.29 g kg−1) than that in dryland soil (7.59–16.20 g kg−1). The riparian soil was slightly polluted by cadmium and phthalate acid esters with an average concentration of 0.19 mg kg−1 and 6.45 mg kg−1, which may be from agricultural sources, posing a potential health risk. Based on 16S rRNA sequencing analysis, there was a higher microbial diversity in paddy soils than dryland soils, and Acidobacteriaceae and Anaerolineaceae represented the dominant taxa in dryland and paddy soils, respectively. Furthermore, the results of redundancy analysis and structural equation modeling showed that land use driven change in soil organic carbon affected the fate of soil pollutants, and constructed soil microbial communities in the riparian zone of TGR. Null model revealed that homogeneous selection explained about 76.36% and 53.33% microbial community assembly, followed by dispersal limitation (14.54% and 37.50%) in dryland and paddy soil. In consequence, a strong effect of environmental filtering was observed on arable soil microbial community structure with different land use in the riparian zone of TGR, and TOC was the key regulator.

Statistical and machine learning methods for crop yield prediction in the context of precision agriculture

It is of critical importance to understand the relationships between crop yield, soil properties and topographic characteristics for agricultural management. This study’s objective was to compare techniques to quantify the relationship between soil and topographic characteristics for predicting crop yield using high-resolution data and analytical techniques. The study was conducted on a multiple field dataset located in Southwestern Ontario, Canada, where few studies have assessed the impact of applications for precision agriculture and machine learning (ML) to the soil property-yield relationship in this region. The dataset included 145,500 observations of corn and soybean yield, topographic and soil nutrient characteristics. The attributes considered for this study included pH, soil organic matter (OM) content, cation exchange capacity (CEC), soil test phosphorus, zinc (Zn), potassium (K), elevation and topographic wetness index. Multiple linear regression (MLR), artificial neural networks, decision trees and random forests were compared to identify methods able to relate soil properties and crop yields on a subfield scale (2 m). Random forests were the most successful at predicting yield with an R2 value of 0.85 for corn and 0.94 for soybeans. MLR was the least successful with an R2 of 0.40 for corn and 0.45 for soybeans. Cross-validation experiments showed that random forest models in most cases could predict low- and high-yield areas from fields excluded from training datasets, but this was not possible in all cases. Techniques tested the models and identified significant soil and topographic attributes when predicting yield, though the identification was subject to some uncertainty. These results suggest that ML techniques might be used to predict high yield areas of fields without existing yield maps, if those fields have similar relationships of soil properties to yield.

Assessment of the spatial distribution of cereal yields on sandy soil related to the application of soil-improving cropping systems (SICS)

Sandy soils occur in different regions throughout the world. In spite of poor quality, they are being used in crop production. The use of sandy soils for crop production requires soil-improving cropping systems (SICS). The aim of this study was to determine the spatial relationships of soil properties including intrinsic texture and relatively stable organic carbon, pH(KCl), cation exchange capacity, and cereal yield (grain and straw yields and plant height) in response to random application of SICS using geostatistics and maps. A 4-year field experiment included the following crop rotation: oat, wheat, wheat and oat and SICS: the control (C) and SICS: liming (L), leguminous catch crops for green manure (LU), farmyard manure (M), and farmyard manure+liming+leguminous catch crops together (M + L + LU). The use of the soil properties as auxiliary variables in the cross-semivariograms improved the prediction of the spatial distribution of the cereal yield, compared to the semi-variograms. The cokriging maps showed positional similarity between the cereal yield, the application of some SICS, and soil textural fractions. The application of M and M + L + LU providing the greatest amounts of organic matter and nitrogen was an effective measure in increasing cereal yields in sub-areas with low contents of sand, compared with the C, L, and LU variants. This increase in the yield was most pronounced in the last study year with an adequate rainfall amount and distribution during the growing season. The similar spatial effects of the SICS M and M + L + LU suggest that the application of M can be in part replaced by incorporation of atmospheric nitrogen-fixing legume catch crops and liming with maintenance of the same productivity and nitrogen supply. The spatial interrelations of the yield response, soil texture, and SICS type will help in selection of the most effective SICS in terms of cereal productivity, depending on local soil conditions.

Microbiological Properties in Cropping Systems and Their Relationship with Water Erosion in the Brazilian Cerrado

Many researchers have reported relationships of physical and chemical properties with water erosion; however, little is known about microbiological properties in this context. Thus, the aim of this study was to evaluate soil properties in relation to erosion in areas with different cropping system practices under no-tillage in the Brazilian Cerrado. The experiment has been carried out since 2014 in a Typic Haplustox under soybean (S) and maize (M) monoculture, maize/soybean annual rotation (MS), maize/brachiaria/soybean/brachiaria rotation (MBSB), two of those treatments with high input of fertilizer (MBSB-HI and MS-HI), and bare soil (BS). Soil losses were quantified in erosion plots. The design was completely randomized. The greater vegetation cover crop, provided by intercropping/succession with brachiaria, increased microbial biomass carbon. The lack of vegetation cover affected the basal soil respiration and metabolic quotient. Basal soil respiration proved to be inversely related to soil and water losses. Vegetation cover was a key factor regulating water erosion. Penetration resistance and aggregate stability correlated with soil and water losses. Thus, not only physical and chemical, but also biological properties are deeply affected by erosion, aiding in early monitoring of water erosion. Soil quality improvement in ecologically supported management contributes to mitigating erosion.

Relationships between vegetation of Macedonian pine (Pinus peuce Griseb.) and different types of soils on which it develops

Abstract This paper deals with relationships between vegetation of Macedonian pine (Pinus peuce) and soils developed on different parent materials on the territory of North Macedonia. We analysed the floristic composition at localities on limestone, on scree of dolomite marble and on scree of silicate. On limestone and scree of dolomite marble, rendzinas on hard limestone and dolomite have developed, and on silicate parent material brown forest soils. The vegetation was sampled according to the Braun-Blanquet approach. DCA and indicator values were used for ecological interpretation of the vegetation patterns. The mechanical and chemical properties of soil and textural classes were also processed. An evident increased presence of carbonates in the soil of scree of dolomite marble on Nidže Mountain was observed, unlike that on Shar Mountain which has formed on typical limestone. Although it is a forest community dominated by the same species, differences between the massifs, the precipitation regime, geology, differences in soil properties in relation to the appearance of carbonates and pH values, and other factors, result in differences in their floristic composition and are the reason for the distinction between the two groups. On silicate on Nidže Mountain, Macedonian pine forests have also developed on brown forest soils, with a different floristic composition to that of the other group on carbonate (dolomite and limestone).

Comparison of Physico-chemical Properties of Soils under Different Forest Types in Dry Tropical Forest Ecosystem in Achanakmar-Amarkantak Biosphere Reserve, India

The present study was conducted to assess the variations in physico-chemical properties of soils under four forest types viz. Mixed Forest, Mixed Sal Forest, Mixed Teak Forest, and Teak Mixed Forests in a typical dry tropical ecosystem of Achanakmar-Amarkantak Biosphere Reserve (AABR), Central India. Soil samples were collected from four types of forest and analyzed for the soil samples were taken at three soil depths, i.e. at 0-20 cm, 20-40cm and 40-60 cm and analysed for pH, EC, Organic C, soil moisture, bulk density, nitrogen (N), phosphorous (P) and potassium (K). The pH of soil was lower (5.43) under Mixed Forest and higher (6.13) in Teak Mixed Forest, while EC in soil was lower (0.04 dS m-1) in Mixed Sal Forest and higher (0.32 dS m-1) under Teak Mixed Forest. Organic C varied from 11.5 Mg ha-1 to 17.8 Mg ha-1 at 0-20 cm soil depth which was highest in soil under Mixed Sal Forest and lowest in Teak Mixed Forest. The Organic C and EC values were decreased with an increase in soil depth, while the bulk density showed reverse trend. Soil nutrients in different depths varied between 160.2 -196.9 kg ha-1, 10.4-17.7 kg ha-1 and 266.4-439.1 kg ha-1 for N, P and K, respectively. The nutrient quantities in soil were higher in Mixed Sal Forest and lower under Teak Mixed Forest, which decreased with soil depth. The paper discusses the possible variations in soil properties in relation to structure and composition of forest type and suggests appropriate management practices for the sustainable development of forest soils in dry tropical ecosystem.

ГЕОХІМІЧНА ТРАНСФОРМАЦІЯ ОБ’ЄКТІВ ДОВКІЛЛЯ В МЕЖАХ ПОЛІГОНІВ ЗАХОРОНЕННЯ ТВЕРДИХ ПОБУТОВИХ ВІДХОДІВ (НА ПРИКЛАДІ МІСТА КИЄВА)

The presented research is devoted to the study of geochemical transformation of environmental key objects (soils, surface and groundwater) within the solid waste landfills. The object of the study is the one of the largest landfills for solid waste disposal in Ukraine – Kyiv landfill №5. The main factual material, which is the basis of the article, was obtained by the authors during a comprehensive field ecological and geochemical research in 2018-2020. The aim of the work was to determine the geochemical (in particular physical and chemical) features of soil sediments within the landfill, which made it possible to assess the protective properties of soils in relation to the impact of technogenic metals. The condition of surface waters (ponds within the landfill territory) and groundwater (wells in Pidhirtsi village) was also studied; the comparison of the main indicators of chemical composition with the maximum allowable concentrations determined by normative documents was performed. It was found that in the studied soils there is a high concentration of heavy metals associated with the fraction of easily exchangeable ions, as well as an increased content of water-soluble forms. The main migration forms of macro- and microelements in soil solutions have been established. It was found that free hydrated cations and metal-organic complexes are characteristic of heavy metals. For groundwater used for potable water consumption by the population of Pidhirtsi village, exceeding of maximum allowable concentrations were recorded for certain indicators, in particular for nitrates, as well as deviations from the established norms for Ba, SO4, Fe, Mn, Co, Ni, Mo, and Pb. The pond waters, located directly within the landfill territory, are characterized by significant deviations from the norm in terms of Fe, Mn, Ni, Ti, V, Cu and Zn. As a result of the study, it was found that within the landfill there are favorable conditions for the formation of mobile forms of toxic elements and their migration to surface and groundwater