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Forest headwater streams serve as critical interfaces between terrestrial forests and downstream aquatic ecosystems, playing essential roles in the storage and movement of carbon (C) and nutrients. However, despite their importance, our understanding of the dynamics of plant litter calcium (Ca) and magnesium (Mg) stocks within these streams remains limited. In this study, we conducted a quantitative analysis of the spatiotemporal dynamics of plant litter Ca and Mg concentrations and stocks in a subtropical forest headwater stream from March 2021 to February 2022. We found that: (1) the average concentrations of litter Ca and Mg were 9.9 and 0.7 mg/g, respectively, with mean stocks of 8 792.3 and 620.8 mg/m², respectively; (2) significant variations in litter Ca and Mg concentrations were observed among non-woody debris (13.1 and 0.9 mg/g), fine woody debris (9.0 and 0.5 mg/g), and coarse woody debris (6.1 and 0.4 mg/g), though plant litter type did not significantly affect the stocks of Ca and Mg; and (3) the stocks of Ca and Mg were positively correlated with factors such as rainfall amount, rainfall frequency, water temperature, flow velocity, water depth, electrical conductivity, and discharge, while negatively correlated with stream water alkalinity and dissolved oxygen levels. These findings highlight the critical role of plant litter in headwater streams as a component of forest nutrient stocks and provide empirical support for incorporating headwater streams into the assessment of nutrient stocks and fluxes in forest ecosystems.

Calcareous soils, typically characterized by low fertility, low organic matter and nitrogen content, and often deficient in phosphorus, zinc, and iron, as well as having low microbial activity, require the development of sustainable soil conditioners to improve fertility. To address these shortcomings and promote sustainable agriculture, biochar, especially with acidic character, may offer a promising solution. This study investigates the effects of modified biochar by H₂SO₄ and ZnSO₄ on soil properties and wheat yield under field conditions. For this purpose, biochar (B), acidified biochar (AB), Zn enriched biochar (BZn), and acidified-Zn enriched biochar (ABZn) were applied to the field at two different doses (0.5 and 1.0%) together with the control treatment (Ck) without biochar application. AB_1.0% was determined as the most effective treatment in decreasing soil pH (0.15 units), while B1.0% was determined as the most effective treatment in increasing organic carbon and cation exchange capacity, 13% and 32%, respectively. The effect of the treatments varied for specific nutrients. The highest antioxidant enzyme activities were found in acidified biochars where the lowest yields were obtained. Compared to the Ck, the highest catalase (CAT) (32%) was determined in ABZn_1.0%, ascorbate peroxidase (APX) (56%) and glutathione peroxidase (GPX) (36%) were determined in ABZn_0.5%, and superoxide dismutase (SOD) (28%) was determined in AB_0.5%. The highest proline (PRO), with the least decrease in yield, was found in the AB_1.0% application, which is 205% more than Ck. B and BZn treatments all increased the grain yield, and the highest increase was 20% in B_1.0% when compared to the Ck.

Field measurement of wind erosion is still a great challenge for researchers. In this study, field performance of a newly designed sediment trap BEST (Basaran and Erpul Sediment Trap) was evaluated for the first time and compared with the commonly used Modified Wilson and Cook (MWAC) traps. Experiments were carried out at the Karapinar Research Station of Konya Soil and Water Resources Institute over the 50 × 50 m tilled sandy loam plot. Three wind erosion events occurred during the experiments. A small amount of sediment was trapped by the MWAC traps only at 0.20 m in all three events, and there were not sufficient sediment measurements at the catch heights to obtain vertical mass flux profiles. On the other hand, BEST was able to catch sufficient amount of sediment at each trap height to calculate soil losses from the experimental fields. Besides, an analysis for particle size characteristics by electron microscopy imagery indicated that almost all of the sediment particles trapped by BEST at any height above 0.60 m were smaller than 100 mm. Hereby, during three erosive wind events a better performance of BEST than of MWAC at comparable catch heights was verified.

Mine water is one of the factors threatening the environment. The aim of the review article is to discuss and critically evaluate individual strategies for the remediation of neutral mine water. A critical evaluation is an essential tool to determine an appropriate remediation strategy. A wetland system is the preferred method of metal removal. However, the disadvantage is that it takes up more space compared to other methods and has a lower metal removal efficiency compared to active metal removal methods. When creating a suitable strategy, it is also necessary to assess the conditions of the mining site, which partially or completely prevent the use of the selected remediation strategy. The benefit of this review article is the processing of suitable combinations of treatment methods for the removal of potentially hazardous elements and their subsequent recovery. Future research in the field needs to focus on the analysis of the negative aspects of the environment that may disrupt or support the implementation of the selected method of remediation.

Soil organic carbon (SOC) is an important soil characteristic as well as a way how to mitigate climate change. Information on its content and spatial distribution is thus crucial. Digital soil mapping (DSM) is a suitable way to evaluate spatial distribution of soil properties thanks to its ability to obtain accurate information about soil. This research aims to apply machine learning algorithms using various environmental covariates to generate digital SOC maps for mineral topsoils in the Liberec and Domažlice districts, located in the Czech Republic. The soil class, land cover, and geology maps as well as terrain covariates extracted from the digital elevation model and remote sensing data were used as covariates in modelling. The spatial distribution of SOC was predicted based on its relationships with covariates using random forest (RF), cubist, and quantile random forest (QRF) models. Results of the RF model showed that land cover (vegetation) and elevation were the most important environmental variables in the SOC prediction in both districts. The RF had better efficiency and accuracy than the cubist and QRF to predict SOC in both districts. The greatest R² value (0.63) was observed in the Domažlice district using the RF model. However, cubist and QRF showed appropriate performance in both districts, too.

Soil salinity is a growing problem for agricultural production in irrigated areas of arid and semi-arid regions. The extent of salinity levels has not been fully studied in the Kesem irrigation scheme in Ethiopia's Afar region. The objective of the study was to identify the main issues related to soil salinity and their variations, and to assess the influence of environmental variables on soil salinity using multivariate analysis (MVA). The dominant cations in the soil were found to be soluble Na⁺, Ca²⁺ and K+ while SO₄^2-and Cl^- were the dominant anions. These ions are responsible for the salinity in the scheme. Groundwater table surveys showed that cultivated fields experienced greater fluctuations in groundwater levels compared to abandoned land due to frequent irrigation. The first two principal components (PCA) explained approximately 60% and 63% of the total variation in salinity for the top and bottom layers, respectively. The difference between the top and bottom layers suggests a management influence. According to redundancy analysis (RDA), the groundwater depth and length of irrigation years were identified as the major environmental factors contributing to 99% and 52% of the variability in salinity, respectively. These findings highlight the importance of considering the rising groundwater levels in future land management decisions.

Water erosion poses a significant threat to more than 50% of agricultural land in the Czech Republic. Maize (Zea mays L.) is particularly susceptible to soil erosion, with the bare soil space between maize rows exposed to erosive agents. Intercropping has emerged as a potential solution to mitigate soil erosion risks in maize cultivation. A series of soil erosion field experiments were conducted from 2022 to 2023 using natural rainfall to investigate the influence of selected intercrop mixtures during the growing season on sediment yields and surface runoff volume. The results revealed a gradual decrease in surface runoff volume and sediment yields over the growing season. Significantly reduced surface runoff volume and soil loss were observed in two tested intercropped plots S2 – rye (Secale cereale) and incarnate clover (Trifolium incarnatum); S3 – ryegrass only (Lolium)), compared to a control plot managed conventionally with maize (S1). Surface runoff volume and soil loss from S2 and S3 reached 2.57–43.5% and 1.26–11.65% of the control plot, respectively. These findings highlight the soil conservation effect of intercrop technologies (S2 and S3) in mitigating soil erosion in maize cultivation. The importance of vegetation cover in reducing soil erosion intensified over time. Intercropping holds promise as a sustainable agricultural management strategy for sloping maize fields.

Preferential water flow in soil significantly affects runoff, water infiltration, storage, groundwater environment, and soil stability. Plant roots positively affect preferential flow development. This study explored the relationship between the root system of Paulownia fortunei (Seem.) Hemsl. and preferential flow using dyeing tracer test and image analysis techniques. A typical red soil hilly region on the outskirts of Guilin City (Guangxi, China) was selected as the study area. A Bright Blue solution was used to visualize the pathways followed by the infiltrated water in simulated rainfall experiments, and Image Analyzer of Plants was used to analyze the root length, surface area, and volume. The results revealed significant differences in the root surface area density of coarse roots (RSAD-CR) and length index of preferential flow (LI) among soil profiles at various distances from the tree trunk. The root volume density of coarse (RVD-CR) and total roots (RVD-TR), the root length density of coarse roots (RLD-CR), and RSAD-CR were significantly correlated with the characteristics of dyeing morphology. Conversely, the root length density and root surface area density of fine (RLD-FR and RSAD-FR, respectively) and total roots (RLD-TR and RSAD-TR, respectively), and the root volume density of fine roots (RVD-FR) were not significantly correlated with the characteristic parameters of dyeing morphology. The root systems of P. fortunei were critical for enhancing soil water infiltration and developing preferential flow in red soil hilly regions. Coarse roots had a greater impact on the development of preferential flow than fine roots, and root volume had a greater influence on preferential flow development than root length and root surface area. This study contributes to a better understanding of the hydrological cycle at the plant-soil interface in red soil hilly regions.

Most studies of agroforestry system biodiversity focus on assessing visible, aboveground biodiversity, largely ignoring soil biodiversity. To fill this gap, a preliminary assessment of soil biodiversity in an agroforestry system was undertaken based on changes in soil enzyme activity. The study was conducted in the village of Maziarnia, Lubelskie Voivodeship, Poland, Europe. Arable fields with spring wheat, mid-field trees and perennial mixed forest were selected for the study. Soil material for physicochemical analyses (pH_H2O, pH_KCl, sorption properties, total carbon and total nitrogen) and biochemical analyses (activity of acid phosphatase, alkaline phosphatase, urease and dehydrogenases) was collected in the spring and autumn of 2022. The present study showed that the biochemical properties of the soils of the selected study sites varied depending on the type of ecosystem determining habitat conditions. Each ecosystem that makes up the agroforestry system studied is characterised by a distinctive microbiome composition and its own level of enzymatic activity. The obtained results support the thesis that agroforestry systems significantly increase the functional diversity and overall biodiversity of agricultural landscapes. However, a full, objective characterisation of the processes taking place in agroforestry systems requires long-term monitoring.

This work presents the advantages and risks of selected soil quality criteria using data from the monitoring of agricultural soils in the Czech Republic. Soil samples were taken from 71 sites covering various soil types. Basic soil parameters and mid-infrared spectra were measured. Indicators describing the quality of soil organic matter (SOM), and soil were calculated. The results show that soil types differ significantly in the qualitative indicators of soil organic matter. More acidic soils with lower clay content contain lower proportions of aromatic and higher proportions of aliphatic organic compounds than neutral soils with higher clay particles content. These soils differ little in total carbon content and C/N ratio but considerably in C/clay ratio. Cambisols are the least degraded soils in the Czech Republic in terms of C/clay ratio, which is controversial in many respects. The results indicate that more aliphatic organic matter is important for the SOM content in the upper part of the agricultural soil, and more aromatic organic matter is mainly bound to the clay fraction. The results raise questions about the suitability of uniform C/clay target values proposed in European legislation as a criterion for assessing soil degradation due to carbon loss.

Life Cycle Assessment (LCA) is normally used independently of the physical and temporal location of the product, process or service under analysis. This makes LCA results more easily comparable and globally accepted. At the same time, it has drawbacks though, e.g. land use will have the same impact regardless of location. However, the use of certain terrains in high erosion risk areas as compared to others in low erosion risk areas will have a different impact on the ecosystem. The availability of airborne Light Detection and Ranging (LiDAR) data (ALS) allows a quick and accurate morphogeometric analysis of any terrain. For this reason, this article offers a methodology, based on Revised Universal Soil Loss Equation (RUSLE) method and airborne LiDAR data, for the straightforward detection of zones with high vulnerability to erosion problems. Based on these local erosion risk data, a method is developed to assess the environmental impact of land use, based on its location. In this way, the LCA methodology is incorporated to gather local data, dependent on the specific location of the activity under analysis. The methodology developed has been applied, as a case study, to a specific municipality in the high mountains of the Autonomous Community of La Rioja (Spain).

This study aimed to examine the changes in selected soil properties at Lítov spoil heap (Sokolov, Czech Republic) and compare the current situation with the situation described twenty years ago. A total of 110 soil samples were taken at Lítov at the same sites as in 1998. The analyses of basic soil characteristics involved: exchangeable soil pH (pH_KCl), organic carbon content (C_ox), quality of humic substances (A_400/A₆₀₀), exchangeable acidity (E_a), and two types of aluminium contents in the soil. Changes in all soil characteristics between 1998 and 2018 were statistically evaluated, compared, and visualized using Geographical Information Systems (GIS). We have observed an increase of pH_KCl, C_ox and a slight improvement in humus quality compared to the results from 1998. The temporal changes of soil characteristics were evident in the whole area, and the influence of reclamation methods was also pronounced. Soil development close to the regional common natural conditions was found in the area where agricultural reclamation measures (i.e., covering with topsoil) were carried out. Furthermore, afforestation – mainly by deciduous trees – supported the improvement of soil characteristics favourable for plant growth. High pyrite content and marshland were identified as the main causes that led to vegetation cover mortality.

The paper proposes a new soil evaluation system using the principle of the Saaty method. The Saaty method has been modified and named Soil Assessment System (SAS). Significance weights are assigned to individual soil characteristics (indicators). This provides a more detailed differentiation of the significance of the indicator on soil quality and a more accurate assessment, especially in marginal cases where the assessment by the methods used so far has not been fully conclusive. In addition to physico-chemical properties, other criteria are taken into account to assess not only productional but also non-productional functions. The possibility of using indicators referring to a broader context (e.g., soil sealing value) is also important, thus enabling a comprehensive assessment of the quality of the land. This results in points for individual sampling locations. Soils are categorized according to the number of points and results are shown on maps.

Advancements in technology have recently enabled to assess soil aggregate stability (SAS) using digital devices. To address the need for a faster and more efficient method of measuring SAS, we have developed a simple yet effective approach using a specialized device. The innovative method named SlakeLight involves measuring the changes in light transmittance as aggregates undergo slaking. The device consists of the measuring chamber, which is placed on a LED light source with a surface-homogeneous distribution of luminosity. During the disintegration process of aggregates immersed in water, reduction in the light emitted to the photodiodes is proportional to SAS. The functionality of the device was tested using topsoil samples from two field fertilization trials. The recorded SAS_trans values were compared with the wet sieving method (WSA) and SLAKE test. The new method showed a strong correlation with both reference methods (r = 0.89 for WSA, r = –0.86 for SLAKE). The device was able to detect a statistically significant differences in SAS between the grassland and the cropland at both sites. Although differences in SAS_trans were not significant between different fertilization treatments unlike WSA, the simplicity and speed of the measurement increase the potential of the method for practical implementation in agriculture, surpassing the limitations of traditional and labor-intensive laboratory techniques.

Land use changes together with riverbed regulations to avoid the annual floods affect the ecosystem of floodplain forests. Later subsequent revitalization measures, transboundary controlled river management, wetland restoration, and integrated planning were realized to reduce the negative effect of groundwater dropping and other environmental problems. This study aimed to follow the dynamic of groundwater level, soil properties and forest vitality as affected by climate change. The continuous dataset (2019–2022) of soil physical and hydrophysical parameters and tree radial growth parameters were obtained. Groundwater level was evaluated by z-score and the means, and standard deviation values were considered. The monthly assessment of soil and climatic conditions showed that the uneven distribution of rainfall and the increase in temperatures have significantly affected the soil hydrological regime and forest growth. Continual monitoring is necessary to prepare projection models, which can help better understand both the soil and tree growth parameters in the changing environment.

Soil erosion resistance is influenced by intrinsic soil properties and multiple external factors. This study investigated the effect of tea planting age on soil resistance to flowing water erosion (reflected by rill erodibility (K_r) and critical shear stress (τ_c)) in Three Gorges Reservoir Area. One slope farmland (as the control) and five tea plantations cultivated for 3 to 34 years were selected for sampling sites. The results indicated that bulk density (BD), soil cohesion (Coh), water stable aggregate (WSA), mean weight diameter (MWD), soil organic carbon (SOC), litter density (LD), and root mass density (RMD) increased generally with tea planting age. Compared to the control, K_r of tea plantations reduced by 71.1%–85.3%. The temporal variation in soil erosion resistance was controlled greatly by the variations in most near-surface characteristics. K_r decreased with WSA, Coh, LD, RMD, and SOC following a power function (P < 0.01); τ_c increased with MWD, LD, RMD, and SOC as an exponential function, with BD a power function, and Coh a logarithmic function (P < 0.01). In this study, K_r could be simulated well by WSA and LD with a power function, and τ_c could be simulated well by MWD and RMD with an exponential function.

Agricultural production is one of the main sources of anthropogenic greenhouse gas (GHG) emissions, contributing 50% and 60% of CH₄ and N₂O emissions, respectively. This study evaluated the rice yield and components, the CH₄ and N₂O emissions and the global warming potential between the triple rice (R-R-R) and sesame-rice rotation (S-R-R) systems in Can Tho city, Vietnam. The experiments were conducted in 3 cropping seasons: Spring-Summer 2016, Summer-Autumn 2016, and Winter-Spring 2016-2017. The results showed that there was no significant difference in yield components and grain yield between triple rice and rotation systems. The application of sesame rotation in rice-based could reduce the CH₄ and N₂O emission by 30.5% and 18.7%, respectively. Global warming potential in the S-R-R rotation was 9860 kg CO_2e/ha, significantly lower than the R-R-R rotation (12410 kg CO_2e/ha) by 20.6%. These results show that the S-R-R rotation has the potential to mitigate GHG emissions, especially CH₄, which contributes to a large amount of emissions in rice cultivation.

Grassland as a part of farmland is important for agrobiodiversity, soil protection and agricultural production (grazing, hay production). In the Czech Republic, grassland area increases with increasing altitude. In this study we evaluated the period 1966–2021 and the change in grassland area in different locations in South Bohemia region: fertile lowlands (Písek, České Budějovice, Tábor districts) and marginal uplands (Český Krumlov, Prachatice districts). Data on land use including the share of grassland were obtained from the Czech Cadastral and Surveying Office and Czech Statistical Office. In the upland districts, there is the largest share of grassland areas in the whole region. The prevalence of grasslands is probably due to the geographic and climatic conditions, which are challenging here. Our research shows the results of changes in grassland areas between 1967 and 2021, with regard to the assessed districts. The difference in the percent area of grassland in 2021 compared to 1967 is –0.04 to –1.77 for lowlands, and +1.45 to +5.99 for uplands. Despite this, uplands farmers practice relatively extensive farming methods and extensive grazing due to low ruminant numbers. Although farmers maintain relevant carbon sinks, it is unlikely to increase the carbon stocks per hectare of extensive grasslands on an annual basis, which would be a barrier to participation in a carbon farming system.

The development and provision of soil spectral library (SSL) could facilitate the application of near infrared (NIR) spectroscopy for economical, accurate, and efficient determination of soil organic matter (SOM). In this work, the performances of partial least squares regression (PLSR) and convolutional neural network (CNN) combined with the datasets of Zhejiang provincial SSL (ZSSL) and the feature subset (FS) were compared for the prediction of SOM at the target field. The FS dataset was chosen from ZSSL based on similarity to the spectral characteristics of the target samples. The results showed that compared with modelling using ZSSL, modelling using FS can greatly improve the prediction accuracy of the PLSR model, but the impact on the performance of the CNN model was limited. The method of mean squared Euclidean distance (MSD) was an effective way for determining the optimal spiking sample size for the PLSR model only using the spectral data of the spiking subset and the prediction set. The PLSR model combined with the FS dataset and the spiking subset determined by MSD achieved the optimal prediction results among all developed models, which is an accurate and easy-to-implement solution for the SOM determination based on ZSSL.

The determination of the saturated hydraulic conductivity Ks on a field scale presents a challenge in which several variables have to be considered. As there is no benchmark or reference method for the Ks determination, the suitability of each available method has to be evaluated. This study is aimed at the functional evaluation of three publicly available types of pedotransfer functions (PTFs) with different levels of utilised predictors. In total, ten PTF models were applied to the 56 data sets including the measured Ks value and the required predictors (% sand, silt and clay particles, dry bulk density, and organic matter/organic carbon content). A single agricultural field with a relatively homogenous particle size distribution was selected for the study to evaluate the ability of the PTF to reflect the variability of Ks. The correlation coefficient, coefficient of determination, mean error, and root mean square error were determined to evaluate the Ks prediction quality. The results showed a high variability in Ks within the field; the measured Ks values ranged between 10 and 1261 cm/day. Although the tested PTF models are based on a robust background of soil databases, they could not provide estimates with satisfactory accuracy unless local soil data were incorporated into the PTF development.

A precise measurement of evapotranspiration (ET) and soil water storage (SWS) is necessary for crop management and understanding hydrological processes in agricultural catchments. In this study, we extracted the vegetative indices (VIs, including normalised difference vegetation index (NDVI), soil-adjusted vegetation index (SAVI), and enhanced vegetation index (EVI)) from satellite images of the Nučice catchment. We found a consistent seasonal pattern of VIs across the catchment with higher values and variation ranges during spring and summer and lower values and variation ranges during autumn and winter. Spatial variation of VIs also followed a seasonal trend, decreasing during crop growth and increasing after crop harvesting. Seasonal correlations were observed between monthly average ET and SWS with VIs throughout one crop season, which can be expressed mathematically as exponential functions. We propose that VIs can be used as a surrogate measure for ET and SWS in catchments with poor monitoring capabilities. Further studies are required to investigate the spatial distribution of ET and SWS throughout the watershed and their relationship with VIs. Furthermore, our research emphasises the importance of subsurface recharge in the water balance of the investigated fields. It suggests that subsurface flow may be influenced by potential gradients of the water table, driving its seasonal behaviour in response to bedrock morphology.

Open-cast coal mining presents a big global issue because of the large areas the mines occupy, which get entirely changed. Their ecosystems lose most of their functions, and a huge amount of fertile soil gets utterly destroyed. Reclamation is a process of returning the functions of the soil after the excavation is finished, most commonly achieved by establishing vegetation, which can sometimes be very difficult. This happens due to the physical, chemical and biological changes that occur on these sites, which are described in this paper. Also, some directions for mitigating these problems are given. Once the vegetation is successfully introduced, natural cycles that were compromised by the mining are established once again, and the process of soil formation begins. Some trends and problems related to pedogenesis research on reclaimed mine sites are presented and discussed, along with presumptions of how the process of soil formation evolves on afforested clayey Technosols of central Europe. The potential future research which would confirm these presumptions is discussed, with the emphasis on the need of research performed on older reclamation sites, as well as sites with similar ecological conditions and different tree species cover.

The establishment of the reference ambient background concentrations (ABCs) and quality reference values (QRVs) for trace metal (TM) concentrations in soils are required for the environmental assessment and any implementation of a protective action. This information is lacking for soils of the eastern Mitidja plain, which is an important agricultural production area in Algeria. Data for the aqua regia extractable Cd, Cr, Cu, Fe, Ni, Pb and Zn concentrations from 180 composite topsoil samples taken across the Mitidja plain in a stratified random pattern were statistically analysed. Descriptive statistical methods and linear regression equations were applied to determine the upper limit of the ABCs for the TMs. After removal of outliers, the derived QRVs were: Cd 0.24, Cr 62.1, Cu 99.3, Fe 45 590, Ni 47.7, Pb 33 and Zn 115 mg/kg. Iron is a macro element in the soils, but is included as its concentration can be used to normalise the concentrations of the other elements. The derived QRVs are similar or less than those reported for other regions of the world, apart from Cu, where a wide range (36 to 206 mg/kg) is reported. These reference values can be used to identify areas that may require follow-up surveys or to identify priority sites for decision making.

This study investigates the effects of repeated applications of the non-ionic soil surfactant H2Flo (ICL-SF Inc., Israel) on the soil water content, hydraulic conductivity, nutrient distribution, and organic carbon fractions (OCFs) in non-hydrophobic loamy sand soils under subsurface drip irrigation. Our results indicate that H2Flo treatment reduces both saturated and unsaturated hydraulic conductivity while promoting the uniform irrigation distribution, consistent with previous findings on surfactants’ effects on sandy soils. An increase in soil pH levels, organic carbon content, and extractable magnesium, calcium, and potassium was observed in treated soils, with elevated levels of potassium permanganate oxidizable organic carbon (POXC) implying accelerated decomposition rates. Notably, a positive linear relationship was found between POXC and the increased NO₃^–-N content of treated soils, suggesting induced conditions of nitrification. However, the carbon fractions water-soluble organic carbon (C_ws) and hot water-soluble organic carbon (C_hws) remained quantitatively unchanged, even though they exhibited a positive linear relationship with the soil’s hydraulic conductivity. The study highlights the crucial role of monitoring changes in OCFs and nutrient dynamics after surfactant application to optimize soil organic matter utilization and chemical fertilizer management.

Plantain is the most important crop for the Peruvian Amazonian population, developed in recent alluvial soils rich in nutrients, but fragile and susceptible to degradation. Therefore, the impact of permanent cultivation was evaluated, through modelling, on indicators of recent alluvial soil quality and production in plantations of Musa paradisiaca L. var. Harton, in the Aguaytia River valley, Peru. The treatments were areas with permanent plantain plantations of 2 (T0), 15 (T1), 4 (T2), and 5 (T3) years of management, evaluating soil physicochemical indicators and plantain production indicators. The results show significant differences for all yield and soil indicators evaluated, except for bulk density (Bd), clay fraction, soil organic matter (OM) and N. The modelling determined a significant positive impact on Bd and a significant negative impact on pH, P, pseudostem diameter and height, commercial fingers and bunch weight. In conclusion, the modelling shows trends of quality and yield reduction in 15 years of permanent management of plantain Var. Harton, and compromises the sustainability of the agroecosystem in the medium term.

Machine learning can handle an ever-increasing amount of data with the ability to learn models from the data. It has been widely used in a variety of disciplines and is gaining increasingly more attention nowadays. As it is challenging to map soil and hydrological information that are characterised with high spatial and temporal variability, applications of machine learning in soil science and hydrology (AMLSH) have become popularised. To better understand the current state of AMLSH research, a scientific and quantitative approach was performed to statistically analyse publication information from 1973 to 2021 archived in the Scopus database using scientometric analysis tools, including VOSviewer, CiteSpace, and the open-source R package “bibliometrix”. The results show a significant increase in the number of publications on AMLSH since 2006. The major contributions were identified based on country origins (China, the USA, and India), institutions (Hohai University, Islamic Azad University, and Wuhan University), and journals (Journal of Hydrology, Remote Sensing, and Geoderma). The keywords analysis of the AMLSH research demonstrates four research hotspots: neural network, artificial intelligence, machine learning, and soil. The most frequently utilised machine learning (ML) methods are neural networks, decision trees, random forests and other methods for image processing and predictive analysis. McBratney et al. 2003 is the most highly cited article. Our research sheds light on the research process on AMLSH and concludes with future research perspectives.

This study focuses on the effect of agricultural soil management on soil organic matter (SOM) composition. The addition of manure and crop residues was tested under different pedoclimatic conditions. The quality of SOM was assessed using diffuse reflectance infrared spectroscopy. The following parameters were calculated from the spectra:   sum of aliphatic bands (ΣAL), aromatic bands at wave numbers 1 620 and 1 520 cm^–1 (AR₁₆₂₀ and AR₁₅₂₀), potential wettability (PWI), organic matter quality (OMQ), and decomposability (DI) indexes. The addition of manure or crop residues may not cause fundamental changes in the qualitative composition of SOM. Rather, pedoclimatic conditions determine which components are fixed in the soil on a long-term scale. A dominant effect of soil type was found in the distribution of all spectral parameters studied using main effect ANOVA. The main differences between the soil types concern the aromatic, oxygen and nitrogen groups contained in the SOM. Chernozems are soils with higher OMQ and DI, whereas Cambisols are soils with low OMQ and DI and the highest PWI. The stabilisation of SOM in soils can thus be based on the biochemical persistence of organic molecules, their specific affinity for minerals and the formation of aggregates that protect enclosed SOM.

Soil organic carbon (SOC) and clay, as indicators of soil fertility, are mainly used to determine the ability of soil to retain water and store the nutrients that are necessary for plant growth. However, the distribution of SOC and clay is influenced by topography and land-use. In the present study, the relationships between SOC, clay, altitude, and slope in the topsoil of two different districts in the Czech Republic including the Liberec (71 samples) and Domažlice (67 samples) districts were investigated. To analyse the relationships between slope and SOC, linear regression was used. Results showed that SOC content increased when slope, clay, or altitude increased; however, there were no significant correlations between SOC and clay in both districts. Clay increased with decreasing slope, but clay and altitude were not correlated well in both areas. Then, study areas were divided into three land-use types including arable land, forest, and complex system of agriculture, parcels, and forests. Consequently, the correlations between SOC and slope and clay and slope were generally improved, indicating the importance of land-use on SOC and clay content. Additionally, using multiple regression with several topographic factors can provide a better prediction of SOC and clay content in each land-use for both districts, indicating the complex effects of topography on SOC and clay.

The aim of this study was to evaluate the response pattern of diazotrophic microbes, denitrifiers and nitrifiers to different types of land use management, such as soybean monoculture (M) during 5 and 24 years (M5 and M24) and soybean-maize rotation (R) during 4 and 15 years (R4 and R15) in two subsequent years at the time point of flowering. Soil samples from a site recently introduced into agriculture (RUA) and a pristine soil under native vegetation (NV) were used as controls. Abundances of different functional groups of microbes were assessed using the direct quantification of marker genes by quantitative real-time PCR using extracted DNA from rhizosphere samples. In addition, soil chemical and physical properties were analysed and correlated with the abundance data from the functional microbial groups under investigation. Overall, the results indicate that the abundance of nifH genes was higher under R treatments compared to M treatments. The abundance of ammonium monooxygenase genes amoA (AOA) was generally higher under rotation systems and decreased under M24. RUA evidenced a negative effect on the establishment and development of AOA communities. The influence of land use on nirS abundance was inconsistent. However, R treatments showed a high abundance of nirK genes compared to M treatments. In both growing seasons, the abundance of nosZ genes was higher under NV compared with the other treatments. Furthermore, M24 treatment was related to strongly changed chemical and physical soil properties compared with the other sites. As expected, soil samples from RUA showed the strong dynamics of measured parameters indicating the high sensitivity of soils under transition to environmental parameters. Our results also indicated that the long-term crop rotation modified the abundance of the investigated microbial groups compared to the monoculture and increased soil chemical and physical quality. Therefore, our results provide evidence for a stimulatory effect of the long-term crop rotation on the abundance of microbes involved in N transformation.

In this study, a typical site that had been contaminated by the chemical industry in the past was selected for investigation. To reveal the pollution status, 18 organochlorine pesticides (OCPs) and seven polychlorinated biphenyls (PCBs) in the surface soil and sediment samples were analysed by gas chromatography-mass spectrometry (GC-MS). The levels of the persistent organochlorine residues in the sediment ranged from 44.59-143.29 ng/g, whereas they were 13.94-97.91 ng/g in the soil. A principal component analysis identified that PCBs and dichlorodiphenyltrichloroethanes (DDTs) were the primary sources of the organochlorine residues in the study area. The p,p'-DDT/(p,p'-DDE + p,p'-DDD) values were all below 1, which indicated that the historical inputs of the technical DDT and dicofol were the major sources of DDTs rather than recent inputs. The composition diversity of the hexachlorocyclohexane (HCH) isomers showed that the main sources in the soil were the past use of pesticides, whereas the sediment sources might be due to the historical use of technical HCHs and recent lindane inputs. The ecological risk assessment showed that γ-HCH could pose the highest risks for benthic organisms, followed by DDTs and heptachlor epoxide. These compounds are known to bio-accumulate in fatty tissues. Therefore, routine monitoring of the persistent organochlorine residues in the area is needed and the health risks to local residents should be assessed.