Soil-structure interaction (SSI) could affect the seismic response of structures. Since liquid storage tanks are vital structures and must continue their operation under severe earthquakes, their seismic behavior should be studied. Accordingly, the seismic response of liquid storage tanks founded on half space soil is scrutinized under different earthquake ground motions. To better comparison, the six considered ground motions are classified based on their pulse like characteristics, into two groups, named far and near fault ground motions. To model the liquid storage tanks, the simplified mass-spring model is used and the liquid is modeled as two lumped masses known as sloshing and impulsive, and the interaction of fluid and structure is considered using two coupled springs and dashpots. The SSI effect, also, is considered using a coupled spring and dashpot. Besides, four types of soils are used to consider wide variety of soil properties. To this end, after deriving the equations of motion, the MATLAB programming is employed to obtain the time history responses. Results show that although the SSI effect leads to decrease the impulsive displacement, overturning moment and normalized base shear, the sloshing (or convective) displacement is not affected by such effects due to its long period.

Satellite-derived high-resolution soil moisture and precipitation data have become widely adopted in natural hazard and climate change research. Landslide susceptibility mapping, which often relies on static predisposing factors, faces challenges in accounting for temporal changes, limiting its efficacy in accurately identifying potential locations for landslide occurrences. A key challenge is the lack of sufficient ground-based monitoring networks for soil moisture and precipitation, especially in remote areas with limited access to rain gauge data. This study addresses these limitations by integrating static landslide conditioning factors—such as topography, geology, and landscape features—with high-resolution dynamic satellite data, including soil moisture and precipitation. Using machine learning techniques, particularly the Random Forest (RF) algorithm, the approach enables the generation of dynamic landslide susceptibility maps that incorporate both spatial and temporal variations. The work validates the method by analyzing two major landslide events and their relationship to hydrological factors, occurred during two rainfall events in 2019 in Italy. The results successfully identified high-probability landslide areas by accounting for multiple hydrogeological factors and capturing the unique patterns of rainfall and soil moisture distribution and intensity. The findings emphasize the need for further research to refine the use of high-resolution satellite precipitation and soil moisture data, particularly in identifying the optimal temporal and spatial resolutions for landslide susceptibility mapping.

Although corn is the most important and nitrogen (N)-fertilized crop, there is a lack of long-term data on the effects of organic and inorganic N fertilizer on N balance and losses for corn systems under different tillage systems. From 2012 to 2023 we assessed the effects of N sources on grain yields from cultivated continuous corn receiving irrigation at a site with minimal erosion in Fort Collins, Colorado, USA, and compared these effects to no-till (NT) and strip till (ST) systems receiving inorganic N. An N balance accounting for N and carbon (C) sequestration found a system nitrogen use efficiency (NUE_Sys) for organic N fertilizer (manure) with tillage of 86.3%, which was higher than the NUE_Sys of 60.2% with inorganic N fertilizer (enhanced efficiency fertilizer, EEF). Conventional tillage with manure use is a good management practice that contributed to higher grain yields (2 of 11 yr.), C sequestration (P<0.05), soil organic N content (P<0.05), and soil phosphorus (P) content than inorganic N fertilizer with tillage (P<0.05). Tilled systems, whether receiving organic or inorganic N fertilizer, had higher yields and grain N content than NT and ST systems receiving inorganic N fertilizer (P<0.05). The grain production of the cultivated system receiving organic N fertilizer did not decrease with time, while the yields of the cultivated system receiving inorganic N fertilizer decreased with time (P<0.05), suggesting that cultivated systems receiving organic N fertilizer may be more sustainable and better able to adapt to a changing climate. Additionally, a combination of manure (30% of N input) with EEF (70% of N input) contributed to a synergistic effect that increased agronomic productivity (harvested grain yields).

Phosphorus (P) is an essential element in food production, but it is often largely unavailable for plants as it persists in soils in immobilized forms. Farmers have been using P fertilizers extensively to overcome this unavailability, leading to the exhaustion of non-renewable deposits of phosphorite, rising fertilizers prices and causing several environmental impacts such as eutrophication. Its large-scale utilization is also inefficient since most of the added P becomes quickly unavailable for the plants. Therefore, farming solutions that improve P uptake, P use efficiency of plants and P mobilization in soils are highly important. In this narrative review, we summarized and explored the link between the Silicon (Si) and P cycles in soils. Silicon is quasi-essential for plants, and it has been established that its presence in soil and uptake by plants has several benefits, especially in toxic and nutrient-deficient conditions. Here, we established that Si in soils can affect crop production in P-deficient conditions through: 1) the pH effect – Si improves organic matter decomposition and decreases Al3+ availability; the Si uptake effect – the deposited Si in the plant improves its photosynthetic performance, improves the root ability to uptake P, improves organic matter decomposition and increases P/Mn ration in plant, improving P use; and 3) the Si soil effect – Si stimulates phosphorite rocks weathering and competes with P for the binding places at the surface of Ak and Fe hydroxides, releasing P into soil solution. This positive effect of Si on P mobilization in soils and consequent use by crops should be further disseminated to farmers and other relevant stakeholders.

In this paper, we present the application of a special soil resistivity model, the Exponentially Graded Multilayered Soil model, to the interpretation of Borehole Resistivity Logging surveys. The model, which was recently introduced by the authors, offers an alternative to the interpretation provided by constant resistivity layer models. The model is applied to synthetic soil surveys as well as to a real survey that is not satisfactorily interpreted using conventional models.

In the recent years, with the advent of Artificial Intelligence (AI) traditional methods have seen a significant transformation in the agriculture sector, especially in soil management. Soil management involves practices that maintains and improves the physical, chemical as well as the biological properties of the soil. Soil health management is essential for both the environmental conservation and sustainable agriculture production, ensuring the soil productivity and functional aspects associated with the ecosystem. Soil health management is one of the most important aspects of agriculture and food production, hence preserving and enhancing the soil health is an essential factor for supporting agriculture. Integration of Artificial Intelligence (AI) technologies with soil health management offers the potential to enhance agricultural sustainability, productivity, adapt to the climatic changes and resource constraints. The study of AI tools that can help improve soil health management by providing more accurate and efficient monitoring, analysis and decision-making capabilities. This paper studies the potential AI technologies including machine learning, robotics, and remote sensing in enhancing soil health, raising crop yields, and lowering environmental concerns by examining previous research and case studies.

The present study aims at investigating the potential impact of agricultural policies on GHG emissions from agriculture across the European Union. The study begins with a brief analysis of the context of implementation of the 2014-2022 Common Agricultural Policy (CAP), within which many interventions were designed to improve sustainability and increase competitiveness. It follows a description of the structural changes the European agriculture is witnessing, that are both influenced and contribute influencing policies. The method of Qualitative Comparative Analysis (QCA) is used to investigate possible causalities and to cluster observations based on similar combinations of conditions (i.e., drivers) and outcomes (i.e., positive or negative variations in GHG emissions from agriculture between the end and the begin of the CAP programming period). The results reveal that the increase in GHG emissions from agriculture over the study period is mainly attributable to the low share of agricultural land under management contracts targeting climate change mitigation and carbon sequestration through the CAP. CAP payments coupled with the production is found to contribute to further increasing GHG emission from agriculture in some eastern and northern EU countries. Livestock concentration, income support payments and the high price of agricultural land drive the increase in GHG emissions for other central and eastern EU countries. The paper concludes addressing existing shortcomings due to conflicting interventions in the current CAP Strategic Plans.

Swamp soil presents significant challenges for infrastructure development due to its soft and deformable nature, which compromises the stability of structures. Traditional wood pillars, while cost-effective and locally available, suffer from degradation caused by moisture and biological organisms. This study investigates various methods to strengthen wood pillars, focusing on the combination of wood and concrete pillars to enhance durability and load-bearing capacity in swamp soil environments. Laboratory experiments and field tests demonstrate that encasing wood pillars in concrete or using composite materials significantly improves their mechanical strength and resistance to deformation. The results highlight the potential of these techniques to provide sustainable and economical solutions for construction in swamp areas, ensuring greater stability and longevity of the infrastructure.

The microbial communities are closely related to the overall health and quality of soil, but studies on microbial ecology in apple-pear orchard soils are limited. In the current study, 28 soil samples were collected from three apple-pear orchards in northeastern China, and the composition and structure of fungal and bacterial communities were investigated by high-throughput sequencing. Molecular ecological network showed that the keystone taxa of bacterial communities were Actinobacteria, Proteobacteria, Gemmatimonadetes, Acidobacteria, Nitrospirae, and Chloroflexi, and the keystone taxa of fungal communities was Ascomycota. Mantel tests showed that soil texture and pH were important factors shaping soil bacterial and fungal communities, and soil water soluble organic carbon (WSOC) and nitrate nitrogen (NO3--N) were also closely related to soil bacterial communities. Canonical correspondence analysis (CCA) and variation partition analysis (VPA) analysis revealed that geographic distance, soil texture, pH, and other soil properties could explain 10.55%, 13.5%, and 19.03% of the overall variation of bacterial communities, and they explained 11.61%, 13.03%, and 20.26% of the overall variation of fungal communities, respectively. The key stone taxa of bacterial and fungal communities in apple-pear orchard soils and their strong correlation with soil properties could provide useful clues toward sustainable management of orchards.

This study examines the latest innovation in wooden pile foundation models using a combination of wood and concrete materials for house construction on swampy land. The focus of the research is on developing joints and materials that enhance the load-bearing capacity and stability of building structures on swampy terrain. The methods used include field observations, laboratory experiments, and descriptive analysis. The results show that the combination of wood and concrete in foundation piles can increase structural strength, reduce deformation, and extend the service life of buildings. The new joint techniques developed in this research are effective in improving structural integrity and minimizing the negative impacts of soft soil conditions. The conclusion emphasizes the importance of material innovation and joint techniques in construction on swampy land, providing practical guidance for construction practitioners and researchers in this field.

Organic soil amendments, such as composts, mitigate the environmental burdens associated with wasting organic resources. Although compost application to soil enhances an agroecosystem's capacity to store carbon and produce food, studies investigating the agronomical efficacy and their ability to ameliorate drought stress when used as a soil amendment are minimal. In this study, we produced and used a nutrient rich co-compost through the composting of sludge, a nitrogen-rich organic material with carbon rich municipal solid wastes (MSW) to evaluate the agronomic efficacy of the MSW derived co-compost and their ability to ameliorate drought stress. Application of co-compost significantly enhanced growth and yield of lettuce and maize, by a magnitude comparable to chemical fertilizers. Furthermore, under drought stress, lettuce plants grown under co-compost soil amendment grew much better with less wilting, more biomass and yield, and improved root growth. Also, co-compost application enhanced relative root mass ratio (RRMR) under drought stress, indicative that co-compost amendment increased the allocation of biomass to the roots, which is an important morphological attribute for drought adaptability. K content in both leaves and roots of plants amended with co-compost was also higher under drought stress, which may have played a role in osmotic adjustment, consequently, the plants exhibited higher leaf relative water content (RWC). Other nutrient elements that were significantly enhanced by co-compost application included Mg, Ca, Fe and Cu. These results provide evidence that MSW co-composting could optimize organic resource recycling for climate change mitigation and agricultural productivity while minimizing nutrient losses from agroecosystems.

Faced with increasing climate challenges, this pioneering study introduces groundbreaking approaches to ensure the resilience of potato crops in east-central Poland. Our research aimed to develop an innovative, cost-effective system tailored to the diverse local conditions of this region. Conducted between 2018 and 2020, the study analyzed integrated and organic production systems across different soil types and potato varieties. The experiment was conducted using a randomized block design with three replications in two locations. Integrated practices, enhanced by mineral fertilization and chemical protection, notably delayed the onset of late blight by 16 days and extended the critical infection period by 17% compared to their organic counterparts. Remarkably, the integrated systems resulted in a 49% increase in total production and a 52% increase in commercial yields, demonstrating their effectiveness in enhancing crop resilience. Different potato varieties exhibit varied responses to cultivation systems, influencing both yield and disease resistance. Further investigation into these varietal responses can help optimize cultivation practices, leading to improved efficiency and sustainability in potato farming. Location and soil conditions have a significant impact on potato yield and the spread of potato blight. Further research into specific soil properties and the adaptation of varieties to local conditions can contribute to increased productivity and stability in potato production. This study not only paves the way towards sustainable agriculture but also highlights the crucial role of soil diversity in shaping resilient farming practices.

Organic fertilizer application in agricultural land is known to improve soil microbial processes, fertility, and yield. In particular, stable changes in soil chemical composition through multi-year fertilization of organic fertilizers are thought to cause changes in the microbial community. Here, the effects of oil cake amendments (OC) on soil bacterial diversity, community profile and enzyme activity were evaluated and compared to those amended with chemical fertilizer (NPK). The comparison of diversity indices between OC and NPK amended soils shows that application of oil cake has increased microbial diversity potentially with an increase in the number of different microbial groups. The ordination plot distinguished and clustered both treatments showing differential effects of soils chemical factors on the microbial communities of each treatment. Proteobacteria, Verrucomicrobia and Bacteriodetes were significantly abundant in OC amended soil than in the NPK received soil, indicating alterations in community structure, composition, and diversity con-current to the changes in pH, Ca and Mg contents of the soil. These shifts in bacterial community structure and composition could also be observed from the phylum to the genus level in both NPK and OC amended soils partially explained by differences in soil chemical factors. The OC soil compared to the NPK amended soil also contain significantly higher abundance of predicted genes corresponding to enzymes related to biogeochemical cycling, decomposition and plant growth promotion. Collectively, these results support the use of an unconventional organic fertilizer positively altering bacterial populations in jujube orchards. The application of oil cake-based organic fertilizer improved microbial diversity and enhanced potential ecosystem functions related to bio-geochemical cycles, mineralization and plant growth promotion.

The design is described of a readily useable technology for routine paddock-scale soil porosity estimation. The method is non-contact (proximal) and typically from sensors mounted on a small farm vehicle around 1 m above the soil surface. Challenges arise from the need to have a compact low-power rigid structure and to allow for pasture cover and surface roughness. The high-frequency regime for acoustic reflections from a porous material is a function of the porosity , the tortuosity , and the angle of incidence . There is no dependence on frequency, so measurements must be conducted at two or more angles of incidence in order to obtain two or more equations in the unknown soil properties and . A system requiring a single transmitter/receiver pair to be moved from one angle to another is not viable for rapid sampling. Therefore, the design includes at least two transmitter/reflector pairs placed at identical distances from the ground so that they would respond identically to power reflected from a perfectly reflecting surface. A single 25 kHz frequency is a compromise which allows for the frequency-dependent signal loss from a natural rough agricultural soil surface. Multiple-transmitter and multiple-microphone arrays are described which give a good signal to noise ratio while maintaining a compact system design. The resulting arrays have a diameter of 100 mm. Pulsed ultrasound is used so that the reflected sound can be separated from sound travelling directly through the air horizontally from transmitter to receiver. The average porosity estimated for soil samples in the laboratory and in the field is found to be within around 0.04 of the porosity measured independently. This level of variation is consistent with uncertainties in setting the angle of incidence, although assumptions made in modelling the interaction of ultrasound with the rough surface no doubt also contribute.

Antimony (Sb) has gained significance as a critical raw material (CRM) within the European Union (EU) due to its strategic importance in various industrial sectors, particularly in the textile industry for flame retardants and as a component of Sb-based semiconductor materials. Moreover, Sb is emerging as a potential alternative for anodes used in lithium-ion batteries, a key element in the Energy transition. This study focused on exploring the feasibility of identifying and quantifying Sb mineralizations through the spectral signature of soils using reflectance spectroscopy, a non-invasive remote sensing technique, and by employing deep learning algorithms such as Convolutional Neural Networks (CNNs). Common signal preprocessing techniques were applied to the spectral data, and the soils were analyzed by Inductively Coupled Plasma Mass Spectrometry (ICP-MS). Despite achieving high R-squared values, the study faces a significant challenge of generalization of the model to new data. Despite the limitations, this study provides valuable insights into potential strategies for future research in this field.

Detecting and monitoring changes in soil salinity through remote sensing provides an opportunity for field assessment in regions where on-site measurements are limited. This investigation, carried out in Siwa Oasis, Egypt, aimed to assess the efficacy of several soil salinity indices derived from Landsat 5 and 7 satellite images. To achieve this, 56 on-site ground measurements were utilized for evaluation purposes. The study aimed to improve the correlation between EC and index values and explore the relationship between salinity and changes in land cover. Eleven spectral indices were calculated for nine scenes captured in different months from August to December. The first approach involved stacking the data to identify the index with the strongest correlation with ground EC values, without the need for complex analysis or EC value ranging. In the second approach, the ground EC measurements were classified into seven different salinity categories, and the correlation coefficient was calculated between each index and each salinity category. The third approach analyzed the data temporally, considering different salinity levels. Lastly, a spatial correlation analysis was conducted between EC and index values in the fourth scenario. The initial approach revealed a weak correlation due to substantial variation in EC values. However, the SI index demonstrated the highest correlation coefficient of 0.38. In the second scenario, the S2 index exhibited the highest correlation of 0.96 for moderate salinity samples. The third scenario showed that the S1 index achieved the highest correlation value of 0.99 for moderately saline areas. In the fourth scenario, the SI index exhibited the strongest correlation among all four ponds with correlation coefficients of 0.23, 0.23, 0.18, and 0.61. Notably, the correlations observed in the second and third scenarios demonstrated higher correlation coefficients compared to both the first and fourth scenarios. The study highlighted significant variations in EC levels related to land cover types and pond elevation. Additionally, remote sensing methods detected a 48% increase in total vegetated area over 17 years, showing the potential of remote sensing techniques in salinity monitoring for expanding agriculture and improving land management.

In the field of engineering, tracked vehicles play a significant role in accessing challenging terrains. Maintaining trafficability is of the utmost importance when it comes to tracked vehicles traversing rugged terrains; it provides stability, traction, and adaptability for a wide range of applications, including deep-sea exploration. The terrain characteristics pertain to the interactions that determine the mobility of tracked vehicles. Traditional Terramechanics models are in-adequate in depicting the correlation between tracks and soil. An important issue is the lack of consideration for the moisture content in the soil and the rate at which sinking occurs in these models. Examining sinkage speed helps describe the ability of tracked vehicles to move at high speeds. The focus is on the critical factors influencing the mobility of tracked vehicles, precisely the sinkage speed and its relationship with pressure. Experimental tests in a soil bin, utilizing Bentonite/Diatom sediment soil, aim to measure these terrain factors. The study introduces a rubber-tracked vehicle, pressure, and moisture sensors to monitor pressure sinkage and moisture, evaluating cohesive soils (Bentonite/Diatom) in combination with sand and gravel mixtures. Findings reveal that higher moisture content in Bentonite soil leads to increased track slippage and sinkage compared to Diatom soil. Regarding soil behavior, diatom soil exhibited notable compaction and sinkage characteristics in contrast to bentonite soil. The distinct behaviors of these soils underscore the complexity of terrains, emphasizing the need for a meticulous understanding of soil properties before applying them in natural environments. Furthermore, this study contributes precision in assessing natural terrains, enhancing tracked vehicle design, and advancing terrain mechanics comprehension for off-road exploration. This knowledge contributes to better vehicle design and a deeper comprehension of terrain mechanics.

Urban gardens have important social, environmental and economic roles in big cities, contributing to their sustainability. However, food production in urban gardens may be compromised due to soil pollution that resulted from decades of industrial non-regulated environmental activity and mobile transport. In this study, 12 soils from the urban agricultural area of Rome (Italy) were analyzed for the metals Be, Ba, Pb, Co, Ni, V, Zn, Hg, Cd, As, Cu, and Cr. All but one of the soils under analysis were characterized by at least one metal concentration above the threshold limit defined by the Italian Legislative Decree 152/2006 (ILD) for agricultural soils. Multivariate analysis showed that the soils could be classified into five clusters: clusters I and II had relatively lower mean metal concentrations; clusters III, IV, and V had relatively higher mean metal concentrations with several metal concentrations above the threshold proposed by ILD. Three factors contributing to the variability of the metal’s concentration in the soils under investigation were identified: geological factor, related with metals As, Ba, Be, and V; anthropogenic factor, related with Pb and Cu; and, a mixed factor related with Co, Cr, Ni, and Zn. High metal content may limit the utilization of urban soils as urban gardens for food production.

Tracked vehicles play a vital role in accessing challenging terrains, offering stability, traction, and versatility for various applications, including deep-sea exploration. However, the seafloor and sediment contain valuable but poorly understood resources, making it a significant challenge for tracked vehicles during exploration. Consequently, it is imperative to conduct comprehensive studies before considering these terrains for off-road purposes. In this study, we developed a rigid, flexible track vehicle equipped with various sensors, focusing on monitoring pressure sinkage. Cohesive soils like Bentonite and Diatom soil, particularly when combined with sand and gravel mixtures, were used for the investigation and assessed for ground pressure, bearing capacity, and sinkage in rigid-flexible tracked vehicles on these characterized terrains under varying moisture conditions. Our findings indicated that increased moisture content in bentonite soil resulted in significantly higher track slippage and sinkage compared to diatomaceous earth soil. Regarding soil behavior, diatom soil exhibited notable compaction and sinkage characteristics compared to bentonite soil. These significant variations between these two soil types under changing moisture conditions highlight the complexity of such terrains. Therefore, understanding the soil and its physical properties is crucial before applying them to natural terrains. Furthermore, this study emphasizes the importance of precision in assessing the physical properties of natural terrains for the development of tracked vehicles for off-road exploration. This knowledge contributes to better vehicle design and a deeper comprehension of terrain mechanics.

This study aimed to simulate dynamic irrigation management zones (MZs) in two maize fields for a variable rate hose-reel fertigation machine (VRFM) with a 4-section boom control. Soil moisture content was measured from nine and four soil moisture sensors in Field 1 (8.2 ha) and Field 2 (2.5 ha), respectively in different dates during the 2022 crop season. Three- and five-MZs scenarios were simulated per irrigation and the theoretical maps were processed for implementation. The application maps fitted to the VRFM showed significant spatiotemporal variations in irrigation requirements. For instance, in Field 1, 3-MZs modelling showed that the areas requiring High (H), Medium (M), and Low (L) level irrigation on July 21 were 1.60, 4.84, and 1.85 ha, respectively, whereas the farmer applied uniform rate over the whole field. H level sub-areas ranged between 1.22 ha (July 25) and 3.25 ha (July 7), showing a coefficient of variation (CV) of 43.32% for the 3-MZs, whereas H level sub-areas for 5-MZs varied from 0.41 ha (July 2) to 1.49 ha (July 7) with a CV value of 48.84%. High levels of within-field variability can be addressed using precise and dynamic irrigation MZs fitted to the irrigation technology used.

This study conducts a comprehensive analysis of the presence of heavy metals, including zinc (Zn), lead (Pb), copper (Cu), chromium (Cr), and arsenic (As), in the dust found inside educational buildings and the top layer of soil in different areas of Vilnius. The study focuses on the analysis of topsoil samples gathered between 2011 and 2023, with a specific emphasis on dust samples obtained from 24 schools in 2022. The research reveals significant variations in the concentrations of heavy metals, providing a clear understanding of the complex relationship between sources of urban pollution, environmental processes, and the correlation between soil and dust contamination by heavy metals. Indoor dust in schools shows unique contamination patterns in contrast to topsoil, suggesting distinctive sources of indoor pollution, while there are some general similarities. This finding emphasizes similarities and distinctions between soil and dust in educational environments. The study utilizes advanced statistical methods such as Pearson correlation, Principal Component Analysis (PCA), and hierarchical clustering to examine the distribution and characteristics of these metals. This study distinguishes itself by examining indoor dust in educational facilities and topsoil in Vilnius, providing crucial insights into the relationship between these two environmental matrices.

The cycling of soil phosphorus (P) is inherently linked with soil organic carbon-iron (C-Fe) cycling, yet empirical integration of these processes within paddy soils remains scarce. In this study, we conducted a microcosm experiment using paddy soils subjected to six distinct fertilization regimes involving varying P inputs for five years. In addition to evaluating P activation under reflooding conditions, we assessed the Fe reduction process and characterized the properties of dissolved organic matter (DOM) at the molecular level using Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS), alongside profiling the composition of soil microbial communities with high-throughput sequencing. Our findings revealed that after 25 days of reflooding, soil Olsen-P content increased by an average of 73% compared to its initial state, showing a strong correlation with the Fe reduction process. Specifically, treatments involving pig manure application exhibited higher Fe reduction rates and enhanced P activation, highlighting the role of organic matter in facilitating Fe reduction. Investigations on the relative abundance of typical iron-reducing microbes further supported their importance in P activation, but the rate of iron reduction is limited by soil organic matter content. Delving deeper into DOM properties, soil DOM composition profiling and network analysis suggested that high-molecular-weight DOM, particularly lignins, served as the primary resources driving Fe reduction by iron-reducing microbes, consequently promoting Fe reduction and P release. Taken together, our study assembled the C-Fe-P cycling dynamics in paddy soils, emphasizing the pivotal role of microbial-driven Fe reduction facilitated by soil DOM in P availability and subsequently sustainable agricultural practices.

Keywords: Mandra flash flood, soil erosion, slope failure, RES, mitigation measures, landslide susceptibility

Dissolved organic matter (DOM) derived from organic fertilizers may increase soil phosphorus (P) availability. However, the frequently observed correlation between soil P availability and dissolved organic carbon (DOC) content has led to an excessive focus on DOC content at the expense of DOM properties. The present study investigated the influence of DOM characteristics on soil P availability by using a 6-year field experiment and microcosms of P sorption in paddy soil. Our results showed that partial replacement of chemical P fertilizer with manure or crop straw increased P fertilizer-use efficiency, even when decreasing chemical P input by 34 %, compared to normal chemical fertilization. The microcosm experiment demonstrated that DOM properties, rather than total DOC content, determine soil P sorption capacity, despite the significant correlation between DOC content and P availability observed in the field experiment. Manure-DOM exerted stronger inhibitory effects on P sorption than straw-DOM, and high molecular weight (HMW)-fractionated DOM exerted stronger inhibitory effects on P sorption than low-molecular-weight-fractionated DOM by 16-20%. The mechanism was rooted in the HMW DOM with unique characteristics (e.g., strong aromaticity, hydrophobicity, abundant humic-like components, carboxyl groups, and benzene ring structures) competing for soil P sorption sites (e.g., reduction in specific surface area and micropore volume), decreasing the soil surface charge (e.g., zeta potential), and thereby suppressing P sorption in paddy soil. Our study points out a promising avenue for regulating organic matter properties with organic fertilization to improve P use efficiency in agricultural soils.

Considering future tasks in soil health, resources management and environmental protection, farmers are challenged to develop sustainable strategies for managing soil and land resources. In this study, the long-term sustainability of two fertilization strategies, - current, with synthetic fertilizers (SYN) vs conservative, with organic sources of nitrogen (organic amendments plus green manure with a legume - CONS) - was assessed in a processing tomato/durum wheat rotation. The EPIC model was used, validated with field data then run to simulate the management for 30 years under 3 current and future climates. Yield, soil organic carbon (SOC) stock change, nitrogen use efficiency (NUE), water use efficiency (WUE) and nitrate leaching were considered as sustainability indicators. Under all the future climate scenarios, tomato yield increased in CONS, remaining almost stable in SYN. Wheat yield increased both in CONS and SYN, but the average yield in CONS was considerably lower than in SYN. NUE and nitrate leaching followed the same trend, both decreasing in CONS, while WUE was higher in CONS compared to SYN. The effect of CONS on SOC was always positive. Thus, the alternative N fertilization strategy proposed can be a favorable option for maintaining soil health and a sustainable crop production.

The functioning of forest ecosystems depends on the taxonomic and ecological diversity of soil fungi. Urbanization is increasing worldwide and is regarded a major driver of environmental change altering local species assemblages in urban forest. We investigated whether the degree of urbanization and local forest characteristics affect the soil fungal community in 20 beech forests located along a rural–urban gradient in the city of Basel and its suburbs (Switzerland). We analyzed their soil fungal communities by DNA metabarcoding of the rDNA ITS2 region and related these data to local forest vegetation characteristics and soil properties. The number of fungal OTUs in the 20 forests examined ranged from 170 to 303. Richness, diversity and evenness of fungal OTUs were all significantly affected by the degree of urbanization, but in different ways. OTU richness was highest in forests in areas with a low degree of urbanization and lowest in forests in rural areas. In contrast, the diversity of OTUs increased with increasing degree of urbanization. Different fungal phyla and fungal guilds showed distinct patterns in their relative abundance along the rural-urban gradient. The degree of urbanization reduced the relative abundance of symbiotrophic fungi, but increased that of saprotrophic and pathotrophic fungi. Our results show that urbanization alters soil fungal community, which in turn can lead to changes in forest ecosystems.

Grazing exclusion (GE) and rest grazing (RG) are important management to restore grassland ecosystems. In order to evaluate the effects and mechanisms of different grazing management on species diversity, vegetation community indices and soil variables were determined in the plots of Qilian Mountains in Gansu Province. The results showed that diversity effects and their regulating mechanisms had space-scale dependence under different grazing management. Species richness and species diversity indices of RG in grassland were significantly higher than that of GE at the regional scale. Additionally, three grazing management in mountain meadows had only a significant effect on species richness, but different management in mountain meadows and temperate steppes had a significantly different effect on species diversity indices. Meanwhile, soil variables only influenced species diversity at the regional scale. Most of community and soil variables at each scale had positive effects on species diversity, except that the direction of biodiversity effects was negative for species coverage, mean plant height, soil porosity (SK) and bulk density (BD) under two contrasting grazing management. In conclusion, choosing RG at the regional scale and select grazing management according to different grassland types at the local scale to restore degraded grassland vegetation.

Among the main elements that contribute to climate change are degradation processes and the ecological level of the landscape. These two topics have been discussed and researched for many years and many studies have been conducted. The idea of the article is to determine the correlation between the ecological stability of the territory and the intensity of degradation processes and find out how the ecological stability affects the intensity of soil erosion and vice versa. The ecological stability was calculated based on various methods during the years analyzed, i.e., 1990, 2006, 2012, and 2018. The soil water erosion was performed for the same period in order to identify the relationship between the ecological stability and intensity of soil erosion. The investigated area is located in the Slovak Republic while each year reflects different management of the territory reflecting the current situation in the catchment according to the year evaluated. The intensity of the erosion process was conducted using a phycially-based EROSION-3D model and based on the precipitation derived using Community Land Model (the CLM model). In addition to identifying the relationship between the level of ecological stability and the intensity of erosion, this study also describes the development the ecological stability during the evaluated period together with changes in soil erosion processes.

Seepage erosion is one of the main reasons for the local collapse or instability of embankments. To investigate the characteristics and mechanism of seepage erosion for cohesionless soils, the model tests by using an independently developed seepage erosion device and the numerical simulations based on the Discrete Element Method-Computational Fluid Dynamics (DEM-CFD) coupling model were carried out. The results show that the seepage erosion process of the cohesionless soil can be characterized by four stages: stable seepage stage, fine particles upward migration stage, sand samples boiling stage, and erosion damage stage. The skeleton structure of soil sample under seepage flow is continually changed due to the loss of fine soil particles, which results in a significant decrease in the sample strength and may ultimately lead to the failure of the sample. The results of this study can provide references and bases for the design, construction, and long-term service of embankments or earth dams under the complex seepage condition, reducing the risk of seepage erosion.

This study investigates the long-term impact of soil tillage systems and crop residue incorporation on agrophysical properties. A long-term field experiment has been conducted since 1999 at the Ex-perimental Station of Vytautas Magnus University Agriculture Academy. According to the latest edition of the International Soil Classification System, the soil in the experimental field was classified as Planosol, with a silty medium loam texture at a depth of 0–20 cm and a silty light loam at a depth of 20–40 cm. This investigation aimed to assess the long-term impact of reduced tillage systems, straw, and green manure combinations on soil physical properties, including soil shear strength, and soil aggregate stability. Studies were carried out on winter wheat crops in 2014, 2017, and 2023. The treatments were arranged using a split-plot design. In a two-factor field experiment, one part of the experimental field had straw removed, while the other part had the entire straw yield chopped and spread at harvest (Factor A). The subplot factor (Factor B) included three different tillage sys-tems: conventional deep ploughing, cover cropping for green manure with no-till, and no-tillage. Soil samples were analysed in the Laboratory of Agrobiology at Vytautas Magnus University Ag-riculture Academy. The findings indicate that long-term application of reduced tillage significantly increases soil shear strength. Shallower tillage depths lead to higher soil shear strength, while the effect of spreading plant residues is relatively lower. Long-term tillage of different intensities, spreading plant residues, and catch crop cultivation for green manure did not significantly affect soil structure. However, soil structural stability was found to be highly dependent on soil tillage. Cover cropping for green manure with no-till and no-tillage positively affected soil aggregate sta-bility in the upper (0–10 cm) and 10–25 cm layers.

Stevia Rebaudiana Bertoni Morita II, a perennial plant native to Paraguay and Brazil, is also widely cultivated in the state of Colima, Mexico, for its use as a sweetener in food and beverages. The op-timization of soil parameters is crucial for maximizing biomass production and stevioside levels in stevia crops. This research presents the development and implementation of a monitoring system to track essential soil parameters, including pH, temperature, humidity, electrical conductivity, ni-trogen, phosphorus, and potassium. The system employs a wireless sensor network to collect qua-si-real-time data, which is transmitted and stored in a web-based platform. A Mamdani-type fuzzy logic model is utilized to process the collected data and provide to farmers an integrated assessment of soil quality. By comparing the quality data output of the fuzzy logic model with a line-ar-regression model, the system demonstrated acceptable performance, with a determination coef-ficient of 0.532 for random data and 0.906 for gathered measurements. The system enables farmers to gain insights into the soil quality of their stevia crops and empowers them to take preventive and corrective actions to improve the soil quality specifically for stevia crops.

Soil moisture maps are essential for hydrological, agricultural and risk assessment applications. To best meet these requirements, it is essential to develop soil moisture products at high spatial resolution which is now made possible using the free Sentinel-1 (S1) SAR (Synthetic Aperture Radar) data. Some soil moisture retrieval techniques using S1 data relied on the use of a priori weather information in order to increase the precision of soil moisture estimates, which required access to a weather forecasting framework. This paper presents an improved and fully automated solution for high-resolution soil moisture mapping in bare agricultural areas. The proposed solution derives a priori weather information directly from the original Sentinel images, thus bypassing the need for a weather forecasting framework. For soil moisture estimation, the neural network technique was implemented to ensure the optimum integration of radar information. The neural networks were trained using synthetic data generated by the modified Integral Equation Model (IEM) model and validated on real data from two study sites in France and Tunisia. Main findings showed that the use of radar signal averaged over grids of a few km2 in addition to radar signal at plot scale instead of a priori weather information, provides good soil moisture estimations. The accuracy is even slightly better comparatively to the accuracy obtained using a priori weather information.

The difficulty in obtaining commercial fertilizers by smallholder farmers in sub-Saharan Africa makes it very important to optimize the use of local organic resources. In VilanKulo, Mozambique, a study was carried out on okra (Abelmoschus esculentus) over two growing seasons in a haplic Lixisol, a loamy-sand textured soil, applying both bat guano and biochar prepared by an artisanal process. Bat guano was applied at two rates (5 and 10 t ha−1), one month and just before sowing. Biochar was also used at two rates (5 and 10 t ha−1) applied close to sowing. Mixtures of biochar and guano at two rates (1 and 4 t ha−1, and 2 and 8 t ha−1, respectively) were also used along with a non-fertilized control. Field trials were arranged in a completely randomized design with three replicates. The treatments receiving high rates of guano tended to show significantly higher fruit yields (&gt; 10 t ha−1, being the two-year average) in comparison to the control, which showed the lowest average okra fruit yield (6.21 t ha−1). In guano treatments, the apparent recovery by okra of some important nutrients, such as nitrogen (N), was greater than the amount of nutrient contained in the guano itself. This result, together with many others related to tissue nutrient concentration, soil properties and residual fertilizing value in guano plots, indicates a strong mineralization of guano during the growing season, probably due to its low carbon (C)/N ratio and favourable environmental conditions for the mineralization process, such as high temperature and well-aerated soil. The result also suggests some kind of manuring effect, i.e., a fertilizing effect of guano beyond what can be explained by the nutrient supply. The use of biochar increased total organic C in the soil and cation exchange capacity (CEC) compared to the control, but did not affect variables related to plant performance, such as tissue nutrient concentration or plant growth and yield.

Regeneration is crucial for forest continuity in natural and managed stands. Analyzing intra-annual dynamics improves the understanding between growth and climate, identifying survival thresholds. The objective was to determine microclimate constraints (rainfall, air and soil temperatures) over Nothofagus antarctica regeneration growing at closed, open, and edge forests in Patagonia. We measured stand characteristics (forest structure, understory, soil properties, animal use), microclimate, and daily growth of regeneration using dendrometers (n = 6) during two growing seasons. We found significant differences in the studied variables (e.g. overstory, light, soil, understory, animal use). These changes defined microclimate across overstory gradient (e.g. soil moisture), influencing the daily growth across seasons (lag, exponential, stationary). Rainfall influenced more than temperature. Daily growth in closed forests indicating shrinkage (-0.0082 mm day-1 without rain, and -0.0008 mm day-1 with 0.0-0.2 mm day-1 rainfall), while above 0.2 mm day-1 rainfall, growth always increased. Open forests presented shrinkage during days without rain (-0.0051 mm day-1), showing positive growths according rainfall. Edge forests always presented positive daily growths. The resilience of regeneration under these changed conditions was related with overstory. Main outputs indicated that regeneration was vulnerable during non-rainy days, suggesting the needs of long-term monitoring to develop better silvicultural proposals.

This paper reports on a series of dynamic simple shear tests conducted to investigate the influence of particle shape on the damping ratio of dry sand. The tests were conducted on sand samples subjected to simple cyclic shear tests to evaluate their cyclic behavior. The particle shape was quantified using three shape parameters: roundness, sphericity, and regularity. The sand samples were subjected to twelve different scenarios with varying vertical stresses and cyclic stress ratios (CSR), in both constant and controlled stress states. Each scenario involved five cyclic tests, using the same sand that was reconstructed from its previous cyclic test. After each cyclic test, hysteresis loops were created to determine the damping ratio. The results showed that the shape of the sand particles changed during cyclic loading, becoming more rounded and spherical, which resulted in an increase in damping ratio. Moreover, the paper presents two artificial intelligence models, an artificial neural network (ANN) and a support vector machine (SVM), which were developed to predict the effect of grain shape on the damping ratio. The models were found to be effective in predicting the damping ratio based on the shape of the grain, vertical stress, CSR, and number of loading cycles. Furthermore, a parameter analysis was conducted to identify the most important shape parameter, which was found to be vertical stress and regularity, while parameter CSR was the least important. Overall, this study contributes to a better understanding of the relationship between particle shape and damping ratio, which could have practical implications for geotechnical engineering applications.

Fresh water is an increasingly scarce resource in both urban and rural developments. As a response to this challenge, non-potable water reuse is on the rise. This research explored a potential off-grid system for water purification, consisting of a staircase wetland with terracotta pot plants working as a filter for greywater. The study further investigated the physicochemical properties of the greywater and the soil before and after the wetland purification. Results showed that the filtered water satisfied all requirements for water reuse, e.g., pH, turbidity, and total coliforms. The research then uniquely investigated the effect of greywater on the soil biodiversity and soil biomass using soil DNA extraction and the tea bag index testing method. The filtered greywater absorbed by soil decomposed the soil faster and stabilized it better compared to tap water-absorbed soil or unfiltered greywater. The DNA generation sequencing revealed no significant differences in alpha diversity between control and treatment samples. The beta diversity differences were significant. This nature-based solution can lead to reduced load on the sewage system, resulting in less wastewater generation.

Maize (Zea mays) is one of the most important staple food and primary source of livestock feed in the world. As the consumption of maize grown on the selenium-enriched soils of Naore Valley is one of the apparent causes of selenosis in the area, this work collected and analyzed total Se, Se fractions, and Se species distributions in maize plant samples, including grains, leaves, stalks, roots, rhizosphere soils, and the most representative parent rock materials from Naore Valley, Ziyang County, China. The Se distribution in soils markedly correlated with the weathered Se-enriched bedrocks, but most of the Se in the analyzed soils is enclosed as recalcitrant residual Se and organic-sulfide bound Se. In contrast, Se in rocks had a comparatively higher bioavailability and is bounded mainly to organic matter and sulfides minerals, with very few of the Se enclosed in the residual fraction. Maize plants might take a large amount of Se from the organic-sulfide bound Se fraction in the Se-rich soils, the weathered products from bedrocks or plant litters. Total Se concentrations in the collected samples were observed in descending order soil>leaf>root>grain>stalk. The predominant Se species detected in maize plants was SeMet. Se inorganic forms, mainly Se(VI), decreased from root to grain and were possibly assimilated into organic forms. Se (IV) was barely present. The natural increases in Se concentration affected mainly leaf and root dry-weight biomass as they are the organs that coped with the highest Se accumulation. This paper offers an insight into the uptake, accumulation, and distribution of Se forms in natural Se-rich maize crops and an opportunity for shifting Se-rich soils from menaces to valuable resources for growing Se-rich agricultural products.

For the soil in different regions, the nutrient fertility contained in it is different, and the detection and zoning management of soil nutrients before tillage every year can improve grain yield. In this paper, an integrated learning strategy model based on black soil hyperspectral data is designed for rapid classification of organic matter content classification of black soil. Soil hyperspectral image dataset of Xiangyang Experimental Base was collected; by changing the internal structure of the stacking model, an LSVM-stacking model with (MLP, SVC, DTree, XGBl, kNN) five classifiers as the L1 layer was built, and the simulated annealing algorithm was used for hyperparameter optimization. Compared to other stacking models, the LSVM-stacking metrics are significantly improved. The accuracy rate of hyperparameter optimization is improved by 38.6515%, the accuracy rate of the independent test data set is 0.9488, and the comparison of individual learners can improve the recognition classification accuracy of label"1" to 1.0.

Plant and animal agriculture is a part of a larger system where the environment, soil, water, nutrient management interact. Biochar (a pyrolyzed biomass) has been shown to affect the single components of this complex system positively. Biochar is a soil amendment, which has been documented for its benefits as soil enhancer particularly to increase soil carbon, improve soil fertility, and better nutrient retention. These effects have been documented in the literature. Still, there is a need for a broader examination of these single components and effects that aims at the complementarity and synergy attainable with biochar and the animal and crop production system. Thus, we report a comprehensive dataset documenting the interactions of biochar with manure, soil, and plants. We evaluated three biochars mixed with manure alongside both manure and soil controls for improvement in soil quality, reduction in nutrient movement, and increase in plant nutrient availability. We explain the experiments and the dataset which contains the physicochemical properties of each biochar-manure mixture, the physicochemical properties of soil amended with each biochar-manure mixture, and the biomass and nutrient information of plants grown in biochar-manure mixture amended soil. This dataset is useful for continued research examining both the short and long-term effects of biochar-manure mixtures on both plant and soil systems. In addition, these data will be beneficial to extent the findings to field settings for practical and realized gains.

Reducing the amount of precipitation in summer in the Chernozems area alters soil organic matter (SOM). To compensate for the lack of moisture, farmers are introducing new agricultural technologies such as no-till cultivation. In turn, no-till practices influence the composition of SOM. We examined the impacts of the rise of aridity and no-till technology on the chemical composition of bioavailable and recalcitrant pools of OM. The properties of SOM were assessed using double-shot pyrolysis with gas chromatography/mass spectrometry (GC/MS). The thermolabile substances that are volatilised in the first stage of pyrolysis (300°C) are considered the bioavailable pool. Accordingly, substances are obtained in the second pyrolysis stage (500°C) were attributed to the recalcitrant pool. Identified in both steps of pyrolysis, products were assigned to different chemical groups (lignin-derivative, polysaccharide-fragments, indoles, etc.) and relative abundances were calculated. In work for the separation of substances, a polar column was used for chromatography of the thermolabile fraction. With an increase in aridity in Сhernozems, the content in the bioavailable pool of polysaccharide fragments decreased and the proportion of indoles increased. In the recalcitrant pool, the abundance of six-membered rings with nitrogen and aromatic compounds decreases at the same time the contents of unsubstituted and O-substituted acyclic compounds as well as pyridine increases. The influence of the NT was more noticeable in the recalcitrant OM. The NT practice promotes biological activity and to rich in nitrogen compounds the bioavailable OM; this process contributes to the accumulation of carbon in the recalcitrant OM.

Apple replant disease (ARD) is a severe problem in orchards and tree nurseries caused by yet unknown soil biota that accumulate over replanting cycles. This study tested the contribution of nematodes to ARD, and cultivation of Tagetes as a control option. In a pot experiment, Tagetes patula or Tagetes tenuifolia were grown in ARD soil, incorporated or removed. Nematodes extracted from untreated ARD soil and washed on 20 µm-sieves induced ARD symptoms when inoculated to apple saplings growing in a sterile substrate. In contrast, nematodes from Tagetes treated ARD soil did not reduce root growth compared to uninoculated plants, irrespective of Tagetes species and incorporation. In plots of five apple tree nurseries or orchards, either Tagetes or grass was grown on ARD soil. Nematodes extracted from the grass plots and inoculated to apple saplings significantly reduced plant growth compared to nematodes from Tagetes plots for all five farms. Apple rootstocks showed overall a significantly higher increase in shoot base diameter when grown on Tagetes-treated plots compared to grass plots, while this effect differed among farms. Plant-parasitic nematodes were too low in abundance to explain plant damage. In conclusion, the free-living nematodes involved in ARD can be controlled by Tagetes.

In the current scenario of changing climatic conditions and rising global population, there is always a need to explore novel, efficient, and economical natural products for the benefit of human kind. Biosurfactant is one of the latest explored microbial biomolecules that have been used in numerous fields, including agriculture, pharmaceuticals, cosmetics, food processing, and environment-cleaning industries as raw material, lubrication, wetting, foaming softening, making emulsions, and stabilizing dispersions. The amphiphilic nature of biosurfactant biomolecules showed great advantage, distributing themselves into two immiscible surfaces by reducing interfacial surface tension and increasing the solubility of hydrophobic compounds. Furthermore, their eco-friendly nature, low or even no toxic nature, durability at higher temperatures, and wide range of pH fluctuations making the microbial surfactants preferable compared to their chemical counterparts. Additionally, the biosurfactants can obviate the oxidation flow by eliciting the antioxidant property, antimicrobial, anticancer activity, and drug delivery system, further broadening their applicability in the food, pharmaceutical, and pharma industries. Nowadays, biosurfactant has been broadly utilized to improve the soil quality by improving the concentration of trace elements and mixed with pesticides or applied singly on the plant surfaces for plant disease management. In the present review, we summarise the latest aspect of microbial synthesized biosurfactant compounds, limiting factors of biosurfactant production, and their application in improving soil quality, plant disease management.

In the context of seismic risk, studying the characteristics of urban soils and of the built environment means adopting a holistic vision of the city taking a step forward compared to the current microzonation approach. Based on this principle, CLARA WebGIS aims to collect, organise, and disseminate the available information on soils and buildings in the urban area of Matera. The geodatabase is populated with i) 488 downloadable geological, geotechnical, geophysical, surveys; ii) geological, geomorphological, and seismic homogeneous microzones maps and iii) a new Digital Surface Model. The CLARA WebGIS (https://smartcities-matera-clara.imaa.cnr.it/) is the first publicly available database reporting for the whole urban area the spatial distribution of the fundamental frequencies for soils and the overlying 4043 buildings, along with probability levels of soil-building resonance. The WebGIS is addressed to a broad target of end users (local government, engineers, and geologists, etc.) as a support to the implementation of seismic risk mitigation strategies in terms of urban planning, seismic retrofitting, and management of post-earthquake crises. We recommend that the database be managed by local administrators, who would also have the task of deciding on future developments and continuous updating as new data becomes available.

Convective rainfall can cause dangerous flash floods within less than six hours. Thus, simple approaches are required for issuing quick warnings. The Flash Flood Guidance (FFG) approach pre-calculates rainfall levels (thresholds) potentially causing critical water levels for a specific catchment. Afterwards, only rainfall and soil moisture information is required to issue warn-ings. This study applied the principle of FFG to the Wernersbach Catchment (Germany) with excellent data coverage using the BROOK90 water budget model. The rainfall thresholds were determined for durations of 1 to 24 hours, by running BROOK90 in “inverse” mode, identifying rainfall values for each duration that led to exceedance of critical discharge (fixed value). After calibrating the model based on its runoff, we ran it in hourly mode with four precipitation types and various levels of initial soil moisture for the period 1996 – 2010. The rainfall threshold curves showed a very high probability of detection (POD) of 91% for the 40 extracted flash flood events in the study period, however, the false alarm rate (FAR) of 56% and the critical success index (CSI) of 42% should be improved in further studies. The approach proved potential as an early flood indicator for head-catchments with limited available information.

Intercropping cover crops have become mandatory in areas at risk of nitrogen leaching to groundwater. These covers include several attractive late-flowering entomophilous species. They can therefore represent crucial floral resources (pollen and nectar) for pollinating insects in early autumn. Pesticides used in previous crops, however, represent a potential risk for pollinators when they are transferred to the intercropping cover plants and their floral resources. We studied the potential transfer of clothianidin (a neonicotinoid insecticide), applied two years earlier in a beet cultivation, from soil to plants and to the floral resources of three common cover species: Phacelia tanacetifolia, Sinapis alba, and Vicia faba. Soils, entire plants, flowers, and nectar were collected from plants grew in greenhouses, and soils and pollen were collected on a treated field. Our results showed that clothianidin was still present in soils (4.5 ng g−1). The residues accumulated in plants (5-15 times higher concentrations than in soils) and were present in pollen of both Vicia faba (0.07 ng g−1) and Sinapis alba (1.7 ng g−1) and in nectar of both Sinapis alba and Phacelia tanacetifolia.

This study investigated the spatial variability of soil organic carbon (SOC), total nitrogen (TN), soil microbial biomass carbon (SMBC) and soil microbial biomass nitrogen (SMBN) in Hongqipao reservoir dominated by different vegetation types and the possible relationships with other soil properties. Top 0–50cm soil samples were collected in sites dominated by different vegetation types within the reservoir littoral zone. There was high spatial variability for SOC, TN, SMBC and SMBN in the Hongqipao reservoir. In addition, the SOC, TN, SMBC and SMBN contents decreased with increasing soil depth. This could be attributed by the fact that when plants detritus decompose, most of their organic matter is mineralized and a new soil layer which contains a greater amount of organic carbon is formed at the top. According to Pearson's correlation values and redundancy analysis (RDA) results, SOC was significantly and positively correlated with TN likely because the vegetation organic matter and liter could be the main nitrogen sources. Similarly, soil moisture content (MC) was significant positive correlated with SOC and TN. Conversely, BD was significant negative correlated with SOC and TN contents in the 0-50 cm soil profiles. However, no significant correlations were observed between SOC, TN, SMBC and SMBN contents and soil pH values. SMBN was significantly and positive correlated with C:N ratio and BD and negative related with MC. Multiple linear regression model revealed that all measures soil properties in this study could explain higher significant variability of the response variables (SOC, TN, SMBC and SMBN contents). This implies that all the measured soil variables within the different vegetation types in the reservoir played a crucial role in determining the contents of SOC, TN, SMBC and SMBN. This study further suggests that vegetation types play a major role in determining the spatial characteristics of SOC and TN. Any changes in the vegetation types in the reservoir may influence the distribution of SOC and TN. This may affect the global carbon budget and the atmospheric greenhouse gas concentration significantly.

Soil organic carbon (SOC) mineralization is closely related to carbon source or sink of terrestrial ecosystem. Understanding soil organic carbon (SOC) mineralization under plum plantation is essential for improving our understanding of SOC responses to land-use change in karst rocky desertification ecosystem. In this study, 2-y, 5-y and 20-y plum plantations and adjacent woodland were sampled and a 90-day incubation experiment was conducted to investigate the effect of plum plantation with different years on SOC mineralization in subtropical China. Results showed that: (1) there was no significant difference in SOC content between different planting years, but there were significant differences in accumulative SOC mineralization (C_t) and potential SOC mineralization (C₀); (2) the dynamics of the SOC mineralization was a good fit to a first-order kinetic model. Both C₀ and C_t in calcareous soil of this study was several to ten folds lower than that in other soils, indicating that SOC in karst region has higher stability. (3) Correlation analysis revealed that both C_t and C₀ was significantly correlated with soil calcium (Ca) and C/N, indicating the important role of Ca and C/N in SOC mineralization in karst rocky desertification area.

Soil microbial diversity in areas affected by coal mining subsidence is closely associated with vegetation restoration. In this study, we compared the diversity of soil bacteria and fungi under different vegetation restoration modes in the subsidized Daliuta coal mining region in western China. The dominant bacteria, Actinobacteria, Proteobacteria, Chloroflexi, and Acidobacteria, were found at abundances of 29.43–34.68%, 15.87–24.75%, 13.09–19%, and 12.06–15.36%, respectively. The dominant fungi, Ascomycetes and Zygomycetes, had abundances of 23.96–71.08% and 10.42–56.26%, respectively. The diversity indices (Sobs, Shannon, and Chao1) of the rhizosphere soil bacteria and fungi were significantly lower in the primary Stipa breviflora phytocommunity than in the phytocommunities of transplanted trees. Among physicochemical soil parameters, total nitrogen (TN), total phosphorus (TP), water content (WC), and pH affected soil bacterial diversity, and available phosphorus (AP) and TN affected bacterial community structure the most. Furthermore, WC affected soil fungal diversity, whereas TP and TN mostly affected the fungal community structure. However, edaphic factors did not uniformly affect all microbial groups. Although TN, WC, and AP significantly influenced the species richness of Actinobacteria and Proteobacteria (p<0.05), TP was significantly negatively correlated with species richness in Acomycota, Basidiomycota, and Zygomycota (p<0.05). However, TN influenced the species richness of Zygomycota (p<0.05) . Furthermore, we found that the rhizosphere microbial diversity of the CK phytocommunity differed from that of the transplanted tree communities in the study area; i.e., the transplanted trees promoted soil microbial diversity in phytocommunities, and moreover, different edaphic factors varied in their effect on the community composition of rhizosphere bacteria and fungi. We will continue to monitor the soil microbial diversity in the study area with the goal to provide guidance for environmental remediation of areas affected by coal mining subsidence.

Land use and land cover change (LULCC) is a critical factor for enhancing the soil erosion risk and land degradation process in the Wabi Shebelle Basin. Up-to-date spatial and statistical data on basin-wide erosion rates can provide an important basis for planning and conservation of soil and water ecosystems. The objectives of this study were to examine the magnitude of LULCC and consequent changes in the spatial extent of soil erosion risk, and identify priority areas for Soil and Water Conservation (SWC) in the Erer Sub-Basin, Wabi Shebelle Basin, Ethiopia. The soil loss rates were estimated using an empirical prediction model of the Revised Universal Soil Loss Equation (RUSLE) outlined in the ArcGIS environment. The estimated total annual actual soil loss at the sub-basin level was 1.01 million tons in 2000 and 1.52 million tons in 2018 with a mean erosion rate of 75.85 t ha^–1 y^–1 and 107.07 t ha^–1 y^–1, respectively. The most extensive soil loss rates were estimated in croplands and bare land cover, with a mean soil loss rate of 37.60 t ha^–1 y^–1 and 15.78 t ha⁻¹ y⁻¹, respectively. The soil erosion risk has increased by 18.28% of the total area, and decreased by 15.93%, showing that the overall soil erosion situation is worsening in the study area. We determined SWC priority areas using the Multi-Criteria Decision Rule (MCDR) approach, indicates that the top three levels identified for intense SWC account for about 2.50%, 2.38%, and 2.14%, respectively. These priority levels are typically situated along the steep slopes in Babile, Fedis, Fik, Gursum, Gola Oda, Haramaya, Jarso, and Kombolcha districts that need emergency SWC measures.

Interactions of soil moisture with plant root systems are very important for plant growth. For non-invasive determination of volumetric soil moisture in a rhizobox, a microwave system based on transmittance of electromagnetic waves in the microwave frequency range was developed using microstrip patch antennas. Vector Network Analyzers (VNAs) were used to measure the S-parameters at frequency ranges close to 5 GHz. A transmission system with microstrip patch antennas was developed. The result of this attenuation is in the frequency domain. The antennae were designed as resonant microstrip antennae. The antennae were placed on both sides of a rhizobox, which allowed non-invasive measuring soil moisture in the box. The attenuation (S21(dB)) was used to measure the effect of temperature, and different types of soil; as well as sensitivity, reproducibility and repeatability of the system. In this work we present quantitative results of soil moisture in rhizobox. The microwave technique, using microstrip patch antennas, is a reliable and accurate system, and showed very promising potential applications for rhizobox-based investigations of root performance.

If given the correct remotely sensed information, machine learning can accurately describe soil moisture conditions in a heterogeneous region at the large scale based on soil moisture readings at the small scale through rule transference across scale. This paper reviews an approach to increase soil moisture resolution over a sample region over Australia using the Soil Moisture Active Passive (SMAP) sensor and Landsat 8 only and a validation experiment using Sentinal-2 and the Advanced Microwave Scanning Radiometer (AMSR-E) over Nevada. This approach uses an inductive localized approach, replacing the need to obtain a deterministic model in favor of a learning model. This model is adaptable to heterogeneous conditions within a single scene unlike traditional polynomial fitting models and has fixed variables unlike most learning models. For the purposes of this analysis, the SMAP 36 km soil moisture product is considered fully valid and accurate. Landsat bands coinciding in collection date with a SMAP capture are down sampled to match the resolution of the SMAP product. A series of indices describing the Soil-Vegetation-Atmosphere Triangle (SVAT) relationship are then produced, including two novel variables, using the down sampled Landsat bands. These indices are then related to the local coincident SMAP values to identify a series of rules or trees to identify the local rules defining the relationship between soil moisture and the indices. The defined rules are then applied to the Landsat image in the native Landsat resolution to determine local soil moisture. Ground truth comparison is done via a series of grids using point soil moisture samples and air-borne L-band Multibeam Radiometer (PLMR) observations done under the SMAPEx-5 campaign. This paper uses a random forest due to its highly accurate learning against local ground truth data yet easily understandable rules. The predictive power of the inferred learning soil moisture algorithm did well with a mean absolute error of 0.054 over an airborne L-band retrieved surface over the same region.

Hydrological models have been widely used for many purposes in water sector projects, including streamflow prediction and flood risk assessment. Among the input data used in such hydrological models, the spatial-temporal variability of rainfall datasets has a significant role on the final discharge estimation. Therefore, accurate measurements of rainfall are vital. On the other hand, ground-based measurement networks, mainly in developing countries, are either nonexistent or too sparse to capture rainfall accurately. In addition to in-situ rainfall datasets, satellite-derived rainfall products are nowadays available globally with high spatial and temporal resolution. An innovative approach called SM2RAIN that estimates rainfall from soil moisture data has been applied successfully to various regions. In this study, firstly soil moisture content derived from the Advanced Microwave Scanning Radiometer for the Earth observing system (AMSR-E) is used as input into the SM2RAIN algorithm to estimate daily rainfall, SM2R-AMSRE, at different sites in the Karkheh river basin (KRB), southwest Iran. Secondly, the SWAT (Soil and Water Assessment Tool) hydrological model is applied to simulate runoff using both ground-based observed rainfall and SM2R-AMSRE rainfall as input. The results reveal that the SM2R-AMSRE rainfall data are, in most cases, in good agreement with ground-based rainfall, with correlations R ranging between 0.58 and 0.88, though there is some underestimation of the observed rainfall, due to soil moisture saturation, not accounted for in the SM2RAIN equation. The subsequent SM2R-AMSRE- SWAT- simulated monthly runoff reproduces well the observations at the 6 gauging stations (with coefficient of determination, R² > 0.72), though with slightly worse performances in terms of bias (Bias) and root-mean-square error (RMSE) and, again, some systematic flow underestimation than the SWAT model with ground-based rainfall input. Furthermore, rainfall estimations of two satellite products of the Tropical Rainfall Measuring Mission (TRMM), 3B42 and 3B42RT, are used in the calibrated SWAT- model. The monthly runoff obtained with 3B42- rainfall have 0.39< R2 < 0.70 and are slightly better than those obtained with 3B42RT- rainfall, but not as good as the SM2R-AMSRE- SWAT- simulated runoff above. Therefore, in spite of the afore-mentioned limitations, using SM2R-AMSRE rainfall data in a hydrological model like SWAT, appears to be a viable approach in basins with limited ground-based rainfall data.

In order to follow the Preventive Chemotherapy for the transmission control as recommended by WHO, Gabon initiated in 2014 the mapping of Schistosomiasis and Soil Transmitted Helminthiasis (STH). Here we report the results of the Northern and Eastern health regions, representing a third of the land area and 12% of its total population. All the 9 departments of the two regions were surveyed and from each, 5 schools were examined with 50 schoolchildren per school. The parasitological examinations were realized using the filtration method for urine and the Kato-Katz technique for stool samples. Overall 2245 schoolchildren (1116 girls and 1129 boys), mean aged 11.28 ± 0.04 years, were examined. Combined schistosomiasis and STH affected 1270 (56.6%) with variation between regions, departments and schools. For schistosomiasis, prevalence were 1.7% across the two regions, with no significant difference (p>0.05) between the Northern (1.5%) and the Eastern (1.9%). Schistosomiasis is mainly caused by Schistosoma haematobium with a prevalence of 1.5%, 1.9% and 1.7%, respectively in the North, East and globally. STH are more common than schistosomiasis, with an overall prevalence of 56.1% significantly different between the Northern (58.1%) and Eastern (53.6%) regions (p = 0.034). Trichuris trichiura is the most abundant infection with a prevalence of 43.7% followed by Ascaris lumbricoides 35.6% and hookworms 1.4%. According to these results, an appropriate mass drug administration strategy is given for the control of each neglected tropical disease group surveyed.

Increased attention has been paid to the influence of coal mining subsidence on ecological environment. Restoration of ecosystem in damaged mining area is critical for restoring disturbed environment. The comparing of plant communities and microbial communities in the artificial restoration and natural restoration areas provides an effective method for evaluating the restoration effects. However, such studies are limited in coal mining subsidence restoration areas. Subsidence area in Shendong mining area, located in the semi-arid region of Western China, was restored from 2003 with 5 ecological restoration plant species. In July 2017, the comparison and analysis of plant and microbial communities were conducted at the artificial restoration areas (AR) and the natural remediation areas (NR). The results showed that the artificial ecological restoration in Shendong mining area has achieved some success, but it has not recovered to a similar ecosystem before the destruction. A higher plant species, coverage and bacterial community diversity were observed in AR. However, these features have lower similarity compared with those in NR sites. Potential soil factors, such as pH, moisture content, total carbon content, organic matter, nitrogen and bulk density, have a greater impact on soil bacterial community structure and diversity. In the ecological restoration of the mining area, attention should be paid to the restoration of soil properties in the mining area. This study can provide theoretical guidance for more scientific ecological restoration in the damaged mining area.

Field experiments were carried out during 2011-2014 at the Research and Experimental Center to Combating Desertification located in the Elsen Tasarkhai station of central Mongolia. The study was aimed to identify the effects of oxidized brown coal humic acid fertilizer on the relative growth rate of several trees for forest rehabilitation. The trees used were Populus sibirica, Salix ledebouriana and Acer tataricum. The experiment was carried out with the concentrations of 2,000, 10,000 and 20,000 mg L-1 of humic acid fertilization treatments. The measurement of relative height growth rate (RHGR) was conducted for a period of 4 years. The treatments showed significant differences within humic fertilizer concentrations which differed depending on the species. Compared to the monthly RHGR over the study, the treatment of fertilizers were significantly better for tree growth. P. sibirica in the 10,000 and 20,000 mg L-1 humic acid fertilizers had significant height growth rates. In addition, when the humic acid treatments were compared to control, A. tataricum decreased over the years which were statistically significant for high growth rate and a positive effect of humic acid fertilization treatments was observed. Furthermore, results showed that oxidized brown coal humic acid fertilizers as organic fertilizer can have a positive effect for the growth of A. tataricum during the study years. The results showed that the soil chemical properties EC, CO2, NO3, and K2O were significant among all the treatments compared to the control. The effect on P2O5 statistically significantly increased among all the treatments. However, pH and Mg were not significant effect among all the treatments. Combining the results obtained from the oxidized brown coal humic acid fertilization with sustainable land management practices can help improve soil organics for environmental issues in degraded sandy soil regions.

Subseasonal-to-seasonal (S2S) weather forecasting has improved in recent years, thanks partly to better representation of physical variables in models. For instance, realistic initializations of snow and soil moisture in models yield enhanced predictability on S2S time scales. Snow depth and soil moisture also mediate month-to-month persistence of near-surface air temperature. Here the role of snow depth as predictor of temperature one month ahead in the Northern Hemisphere is probed via two causal pathways. Through the first pathway, snow depth anomalies in month 1 cause snow depth anomalies in month 2, which then cause temperature anomalies in month 2. This pathway represents the snow–albedo feedback, as well as cooling due to insulation, emissivity and heat loss. It is active from fall to summer, and its effect peaks in March/April in the midlatitudes and in May/June at high latitudes. A complementary second pathway, where snow depth anomalies in month 1 cause soil moisture anomalies in month 2, which then cause temperature anomalies in month 2 through soil moisture–temperature feedbacks, is only active in spring and summer. Its effect peaks later in the warm season than the effect of the first pathway. Geographically, snow depth mediates north of, and soil moisture south of, the areas with the highest temperature predictability from snow depth. These results indicate that the two pathways describe complementary physical mechanisms. The first pathway embodies month-to-month persistence of snow depth, and the second pathway represents melting of snow from one month to the next.

This study investigated the effects of soil crust development on the underlying soil properties. The field sampling work was conducted in June 2016 in the Hobq Desert in Inner Mongolia, North China. Soil crust samples and 0–6, 6–12, 12–18, 18–24, 24–30 cm deep underlying soil samples were taken from five representative areas of different soil crust development stages. All samples were analyzed for physicochemical properties including water content, bulk density, aggregate content, organic matter content, enzyme activities, and microbial biomass carbon and nitrogen. The results showed that the thickness, water content, macroaggregate (>250 μm) content, organic matter content, microbial biomass and enzyme activities of the soil crusts gradually increased along the soil crust development gradient, while the bulk density of the soil crusts decreased. Meanwhile, the physicochemical and biological properties of the soils below the algal and moss crusts were significantly ameliorated when compared with the physical crust. Moreover, the amelioration effects were significant in the upper horizons (approx. 0–12 cm deep) and diminished quickly in the deeper soil layers.

Rodents are known to be reservoirs of Toxoplasma gondii and keep the parasite circulation in the environment. We conducted biomonitoring to assess the role of sylvatic rodents in maintaining T. gondii and to analyse the prevalence and seroprevalence of the parasite in seven wild rodent species. Rodents were collected in our study sites (woodland and open grasslands) located in northeastern Poland and dissected. We collected brain, spleen, blood and serum samples. We applied both molecular (PCR assay, nested-PCR assay) and serological (ELISA and agglutination tests) methods to indicate the best approach for application in the biomonitoring of T. gondii in small mammals. We screened samples from 95 individuals sing PCR assays and found no T. gondii DNA. The agglutination test showed no signal. We found antibodies against T. gondii in 6 sera samples out of 74 analysed (seroprevalence = 8.11% [4.0-17.1]). Our results confirm that rodents participate in the life cycle of T. gondii as reservoirs of this parasite in the sylvatic environment. However, biomonitoring should be performed with the ELISA tests to search for T. gondii antigens, rather than a molecular approach only.

The phenomenon of pathogens co-infection detected in the half fed on humans I. persulcatus tick in the south of the Far East was studied. Researchs were carried out on PEK, Vero, Vero-E6 cell lines, outbred mice, chicken embryos, using ELISA, PCR, IMFA, plaque formation, and electron microscopy. The tick contained an antigen and a genetic marker of the tick-borne encephalitis virus (TBEV). The patient had post-vaccination antibodies in a titer of 1:200, as a result of which, obviously, an antibody-dependent elimination of TBEV occurred. The tick-borne co-isolate also contained an unknown pathogen (Kiparisovo-144 virus), which, in our opinion, was a trigger for the activation of chronic infection in suckling white mice. In the laboratory coisolate, ectromelia virus was present, as evidenced by paw edema during intradermal infection of mice, characteristic rashes on the chorion-allantoic envilope of chicken embryos, and typical plaques on Vero-E6. The Kiparisovo-144 virus was not pathogenic for white mice and chicken embryos, but successfully multiplied in the PEK, Vero, and Vero-E6 lines. Viral co-infection was confirmed by electron microscopy. Passaging on mice contributed to an increase in the virulence of the co-isolate, whose titer increased by 10,000 times by the 5th passage, which poses a serious epidemiological danger.

Soil carbon (C) cycling under anoxic conditions is mechanistically linked to dissimilatory iron (Fe) reduction, which could be regulated by exogenous dissolved organic matter (DOM). However, the impact of complex exogenous DOM on soil microbial activity and C-Fe coupling in paddy soils remains underexplored. With a 100-day microcosm experiment, we determined that the molecular composition of DOM derived from organic fertilizers and biochar on paddy soil affects soil microbial community, Fe reduction, and C emissions. Our results indicated that biochar-DOM significantly promoted Fe reduction and accelerated CH₄ and CO₂ emissions, and organic manure-DOM increased soil CO₂ emissions, which was closely related to the molecular composition of exogenous DOM. DOM molecules with high aromaticity (AI_mod) and high DBE, including lignins-vascular plant-derived polyphenols, lignins-polycyclic aromatics (PA), and condensed aromatics-PA, promoted soil Fe reduction and CH₄ emissions by enriching soil Fe-reducing bacteria (FeRB), reducing methanotrophs, and facilitating r-strategists at the early stage of incubation. Conversely, DOMs with low AI_mod, low DBE and high H/C, such as lignins-highly unsaturated and phenolic compounds and proteins-aliphatic compounds, enhanced CO₂ emissions by facilitating recalcitrant C degradation and CH₄ oxidation at the late stage of incubation. In conclusion, our study highlights the importance of the molecular composition of DOMs derived from organic amendments in regulating soil Fe reduction and C emissions. The findings offer novel insights into the effective utilization of agricultural resources and the mitigation of soil C emissions.

The high spatial complexities of soil temperature modelling over semiarid land have challenged the calibration—predication framework, whose composited objective lacks comprehensive evaluation. Therefore, this study, based on the Noah land surface model and its full parameter table, utilizes two global searching algorithms and eight kinds of objective with dimensional—varied metrics, combined with dense site soil moisture and temperature observations of central Tibet, to explore different metrics’ performances on the spatial heterogeneity and uncertainty of regional land surface parameters, calibration efficiency and effectiveness, as well as spatiotemporal complexities in surface forecasting. Results have shown that metrics’ diversity has shown greater influence on the calibration—predication framework than the global searching algorithms themselves. Besides being significantly better than other metrics, the enhanced multi objective metric (EMO) and the enhanced Kling-Gupta efficiency (EKGE) have their own advantages and disadvantages in simulations and parameters respectively. Especially, EMO that composited with four metrics as correlated coefficient, root mean square error, mean absolute error, and Nash–Sutcliffe efficiency, has shown relatively balanced performance in surface forecasting when compared to EKGE. In general, the calibration—predication framework that benefited from EMO could greatly reduce the spatial complexities in soil temperature modelling of the semiarid land.

Concern over microplastics (MPs) in the environment is rising. Microplastics are generally known to exist in aquatic settings, but less is known about their occurrence in soil ecosystems. When plastic waste builds up in agricultural areas, it can have a negative impact on the environment and food sources, as well as have an indirect effect on all trophic levels of the food chain. This paper addresses the relationship between microplastics and the management of plastic waste, which contributes to their accumulation, and it describes the sources and primarily the movement processes of microplastics in agricultural soils as a result of natural events. Evaluating the impact of weather on coastal microplastic contamination is critical, as extreme weather events have become more frequent in recent years. This study sheds light on how weather patterns affect the dispersion of plastic waste in terrestrial habitats, including the impacts of seasonality and extreme weather. According to our data, typhoons, monsoons, rainfall, and floods all contribute significantly more microplastics to the surface sediment through surface runoff and wind transport, particle redistribution caused by agitated waves, and fragmentation under intense abrasion forces. Severe weather conditions have the potential to disperse larger and more varied kinds of microplastics.

Evaluation ecosystem service value (ESV) is critical for “lucid waters and lush mountains are invaluable assets”. However, the ESV estimation and spatial-temporal analysis for mountainous soil erosion area is rare, e.g., Changting county, China. In this study, we developed a remote sensing driven mountainous equivalent factor (RS-MEF) method to estimate the ESV of soil erosion area in subtropical mountain. It is a hybrid of a conventional equivalent factor framework and the remote sensing techniques for mountains, and achieves several highlights of spatial adjustment using carbon sink with vegetation canopy, improvement spatial resolution, and removal topographic effect. Using the RS-MEF method, we estimated that the ESV of Changting county was about 15.80 billion CNY in 2010 and 34.83 billion CNY in 2022. Specifically, the ESV per unit area of major soil erosion area (MSEA) in the county was less than that of non-major soil erosion area (n-MSEA), however, the ESV growth rate of MSEA from 2010 to 2022 was faster than that of n-MSEA. Therefore, the ESV gap between two areas was shortened from 28.99% in 2010 to 15.83% in 2022. Topographic gradient effect analysis illustrates that the area with high elevation and small slope is one control focus in the next step. Our study indicates that the ecological restoration in the county has made great achievements in the ESV perspective, with low ESV area shrank evidently in MSEA; and the achieved knowledge of the ESV growth and inherent factors is valuable and instructive for the next soil and water conservation.

In order to explore the yield-increasing mechanism of mechanized potato planting with corn straw mulching, a two-year ( 2021 and 2022 ) field experiment was conducted to study the effects of mechanized no-tillage with straw mulching on potato yield and water use efficiency. This experiment included corn straw mulching potato mechanized no-tillage planting ( JG ), plastic film mulching ( HM ) and open flat planting ( CK ). The results showed that mechanical no-tillage with straw mulching had significant effects on soil water content, yield and water use efficiency in 0-100 cm soil layer (p&lt; 0.05). There was no significant difference in yield between JG and HM, but it was significantly higher than that of CK. The yield of JG was 3.09 %~12.27 % higher than that of CK. The yield increase was mainly achieved by increasing the potato weight per plant ( 0.697 ~ 0.862** ) and the average single potato weight ( 0.048 ~ 0.631 ). The tuber weight per plant was positively correlated with the plant height at seedling stage ( 0.03 ~ 0.92** ), and positively correlated with the dry weight of stems and leaves at tuber expansion stage and starch accumulation stage ( 0.74** ~ 0.95**). It was negatively correlated with the number of branches at tuber formation stage ( -0.33 ~ -0.88** ). Compared with CK, JG could significantly improve the water use efficiency of potato and reduce the water consumption during the whole growth period of crops. In 2021, JG was 6.5 % higher than CK, and HM was 6.88 % lower than CK. In 2022, JG and HM increased water use efficiency by 26.17 % and 14.50 % compared with CK. It can be seen that JG is a green and efficient mechanized potato cultivation technology suitable for dry farming areas.

Soil organic matter (SOM) is essential for nutrient cycling and soil carbon (C) accumu-lation, both of which are heavily influenced by the quality and quantity of plant litter. Since SOM dynamics in relation to plant diversity are poorly understood we investigated the effects of willow variety and mixture, and site on the soil C stocks, SOM chemical composition and ther-mal stability. Using pyrolysis-field ionization mass spectrometry we analysed the top 10 cm of soil from two 7-year-old experimental sites in Germany and Sweden, with monocultures and mixtures of two willow varieties (Salix spp.) belonging to different species. Overall, site had the strongest effect on SOM quality. Results showed significant variability across sites for willow identity and mixture effects on C accumulation and SOM chemistry. In the German site (Ros-tock), yearly soil C accumulation was higher (p < 0.05) for variety ‘Loden’ (1.0 Mg C ha-1 year-1) compared to ‘Tora’ (0.5 Mg C ha-1 year-1), whilst in the Swedish site (Uppsala), both varieties ex-hibited similar soil C accumulation rates of around 0.6 Mg C ha-1 year-1. Willow variety identity significantly affected SOM quality at both sites, while mixing had minor effects. Our findings emphasize the significance of site-specific context and variety or species identity in shaping soil C accumulation in willow plantations.

Our study aimed to assess sprinkler irrigation's impact on the activity of selected soil enzymes concerning nitrogen metabolism and oxidation-reduction processes in the soil with different doses of inorganic nitrogen fertilizers. The soil Alfisol was sampled from the experimental field of spring barley in the University Research Center in the central part of Poland in the moderate transitory climate during the growing seasons 2015–2017. The index resistance (RS) was derived to recognise the resistance enzymes of drought. In the maturity phase, nitrate reductase activity was at an 18% higher level in irrigated soils and the activity of other enzymes was higher in no-irrigated treatments by 25% in dehydrogenase, 22% in peroxydase 33% in catalase and 17% in urease case. The development stage of barley influenced nitrate reductase activity. Enzymatic activity has been changing in the examined years of the research, depending on the weather conditions. During the maturity stage, the soil's lower ammonium nitrogen content resulted from higher spring barley uptake due to drought stress. Irrigation probably contributes to increased leaching of nitrate in soil. The highest index of resilience was presented in the soil catalase activity.

Linear alkylbenzene sulfonate (LAS) anionic surfactants are widely used, present in wastewater, and can be discharged causing environmental damage. Without considering biodegradation, sorption and desorption reactions play an important role and depend on the characteristics of the aquifer medium such as the content of organic matter and clay. These processes are modelled with PHREEQC using laboratory-obtained data on columns with an input LAS pulse. LAS adsorption and desorption step experiments carried out in sand columns were also modelled with this software and distribution constants were similar to those obtained for pulse. The values of the starting distribution constant provided by batch tests with sand and agricultural soil mixtures establish the maximum value that must be obtained for column modelling. Distribution constants from column experiments obtained by Freundlich and linear isotherms provided very similar results, the latter with more consistent achievement. The modelling results showed longer elution times in the case of the heavier homologues and with a higher percentage of agricultural soil, which would translate into the great persistence of these compounds in the environment. In the case of soil contamination with wastewater-containing surfactants, these results would allow the development of mitigation strategies for these environmental impacts.

In forests, the microbial populations living in the soil can directly affect the carbon decomposed by the surface plants, and promote carbon storage and stability. In this study, 3 plots of 25.82 m×25.82 m were set up in 5 stand types, respectively. Soil samples were collected from 0~20 cm, 20~40 cm and 40~60 cm layers. Soil microbial composition, organic carbon component, pH, water content, bulk density, nitrogen, phosphorus, potassium and other physicochemical indexes and correlations were determined, and the correlations between soil carbon components and soil microbial functional modules in different mixed modes were analyzed. The results showed that: (1) The SOC of the same soil layer varied significantly, which also showed significant differences on the composition of soil bacteria and fungal microbial communities. Moreover, the bacterial community was more sensitive to the vegetation change environment, and the fungal community structure was more resistant to the influence of soil environment changes. (2) Fun_mod 1,6 and Bac_mod 7 were the microbial functional modules that played a decisive role in the process of soil carbon pool change, and the diversity and composition of bacterial community had more positive effects on soil organic carbon than that of fungal community. (3) Linear fitting and RDA results showed that POC in soil had the strongest correlation with SOC content, indicating that soil microorganisms affected the storage and stability of soil carbon mainly by regulating the conversion of surface plants (carbon sources) into POC. The soil environment of different mixed modes has different effects on soil carbon accumulation. Soil microorganisms affect soil carbon storage and stability mainly by regulating the conversion of surface plants (carbon sources) into POC forms.

The chestnut tree (Castanea sativa Mill.) is gaining importance in the mountainous regions of southern Europe due to the high value of its fruits. It is essential to establish effective cultivation protocols, considering that this species is still relatively understudied. In this study, we present the outcomes of the initial establishment of a chestnut orchard conducted through a nutrient omission trial for four years. The treatments included a fertilization plan with nitrogen, phosphorus, potassium, and boron (NPKB), the control, and four other treatments corresponding to the omission of each nutrient (-NPKB, N-PKB, NP-KB, NPK-B). The -NPKB and NP-KB treatments showed significantly lower trunk circumferences and canopy volumes compared to the other treatments. The NPK-B treatment resulted in the lowest fruit production, with a total accumulated yield (2020-2022) of 0.56 kg tree–1, a value significantly lower than that of NPKB (1.12 kg tree–1) and N-PKB (1.19 kg tree–1). The assessment of nutrient concentrations in the leaves revealed plants with deficient levels of B and K in treatments that did not receive these nutrients. Conversely, N levels in the leaves in the -NPKB treatment fell within the sufficiency range (20 to 28 g kg–1). This suggests that the sufficiency range should be adjusted to higher values, given the treatment's effect on tree growth. It was also observed that the -NPKB treatment led to lower soil organic matter compared to the other treatments, likely due to reduced herbaceous vegetation development under the canopy, leading to decreased organic substrate deposition in the soil. The main findings of this study are that N and K were crucial elements for the optimal growth of chestnut trees, while B played a significant role in fruit production.

Climate warming is expected to have pronounced effects on Arctic and Subarctic ecosystems, especially regions underlain by discontinuous and relatively warm permafrost. The main goal of this research is to evaluate the vulnerability and dynamics of permafrost under climate warming across the various ecotypes in respect of ecosystem stability, socioeconomic impact, and for better understanding possible future environmental changes. We suggested the new version of the spatially distributed permafrost dynamics model (GIPL2-MPI), which is developed in the Geophysical Institute, University of Alaska Fairbanks. This model is based on the ecosystem approach to simulate the permafrost dynamics, which we are discussing in this paper. We combined ground-based observations and numerical freeze/thaw modeling using climate-ecosystem-permafrost interactions to understand the physical processes and mechanisms controlling permafrost physical state. We predict the changes in permafrost conditions using output from two GCMs (NCAR-CCSM4 and GFDL-CM3) and Five-Model Average Ensemble for the RCP-4.5 and RCP-8.5 scaled down to 1 by 1 km spatial resolution (https://uaf-snap.org/) across entire Alaska. Our result shows that by the end of the current century widespread near-surface permafrost degradation could begin everywhere in Alaska southward of the Brooks Range as well as across some spots at the North Slope Alaska.

Soil extracellular enzyme activity (EEAs) and enzymatic stoichiometry (ES) can provide a crucial indication of changes in soil ecosystem's nutrient availability and the microbial resource limitations. However, the changing characteristics of soil EEAs and ES at different stages of the native succession process and their key drivers are unclear. In order to investigate the soil EEAs, ES and driving factors of soil under vegetation at different succession stages, we adopted the "spatio-temporal substitution" method to collect the surface soil of bryophyte community, herbaceous community, shrub community and tree community in the new volcanic lava platform of Wudalianchi Volcanic Nature Reserve. We measured seven soil EEA, including carbon(C)-acquiring enzyme (β-1,4-glucosidase (BG)), N-acquiring enzymes (β-N-acetyl-glucosaminidase (NAG) and leucine aminopeptidase (LAP)) and phosphorus (P)-acquiring enzyme (acid phosphatase (AP)) activities. The length and angle of vectors defined by ratios of enzyme activities (BG/(NAG + LAP) vs. BG/AP) were used to indicate relative microbial investments in C- (length), and N- and P- (angle) acquiring enzymes. Our results showed that the contents of TC, TN, TP, MBC, DOC and NO3-N in shrub community soil were significantly higher than those in bryophyte, herb and tree communities, and increased by 441%, 246%, 137%, 5570%, 12% and 484%, respectively. The highest soil EEA of C-, N- and P-acquiring were found in shrub community, and the soil EEAs/MBC of C-, N- and P-acquiring were the highest in bryophyte community. Enzyme C:N, C:P and N:P ratios increased progressively in the order of bryophyte, herb and shrub community, but the enzyme C:N, C:P and N:P ratios of tree community were both far less than shrub community. Vector lengths increased progressively in the order of bryophyte (1.16), herb (1.27), tree (1.29) and shrub (1.40), and Vector angles decreased progressively in the order of bryophyte (49.15°), herb (45.65°), Tree (45.31°) and shurb (44.54°), suggested that as succession progresses, soil microbial nutrients transforms from P limitation (angle＞45°) to N limitation (angle＜45°). Redundancy analysis showed that TC, TN, EC and C:N were important drivers of variation in soil EEAs and ES in vegetation at different succession stages. Our findings highlight that the primary succession process cause nutrient limitation transformation. Soil ES might be a sensitive indicator mediated by soil microorganisms to the relative resource limitation at different stages of the primary succession process.

Environment pollution is one of the major problem that faces by our civilization . Textile industry is one of the factor for pollute the environment. In this study various causes that occurs by textile industry and pollute the environment will be shown and described. In textile industry for energy to run the factory various kind of fuel are used and in the industry there are many chemicals and dyes are used for the textile products. Plastic is one of the main substance for making the synthetic fabric. They pollute the air, water, soil and also they pollute the ecosystem of the various animals and destroy the ozone surface of the earth. For various kind of pollution that causes by textile industry the life of normal life hampered. They got ill and many time men and women lost their organs and sometimes they got attacked by various life taking illness.

The objective of this study was to investigate the liquefaction resistance of chemically improved sandy soils in a straightforward and accurate manner. Using only the existing experimental databases and artificial intelligence, the goal was to make predictions without conducting physical experiments. Emphasis was placed on the significance of data from 20 loading cycles of cyclic undrained triaxial tests to determine the liquefaction resistance and the contribution of each explanatory variable. Different combinations of explanatory variables were considered. Regarding the predictive model, it was observed that a case with the liquefaction resistance ratio as the dependent variable and other parameters as explanatory variables yielded favorable results. In terms of exploring combinations of explanatory variables, it was found advantageous to include all variables as doing so consistently resulted in a high coefficient of determination. The inclusion of the liquefaction resistance ratio in the training data was found to improve the predictive accuracy. In addition, the results obtained when using a linear model for the prediction suggested the potential to accurately predict the liquefaction resistance using historical data.

In recent decades, large-scale forest disturbances such as windthrow and bark beetle infestations have significantly impacted the carbon balance of Earth and forest ecosystems, mainly by altering soil respiration (SR) in addition to decreased gross primary productivity. SR is considered the second highest flux on Earth, emitting 78-98 Gt C yr-1 to the atmosphere, thus contributing to global warming. Post-disturbance development is marked by changes in the size of SR. To investigate the impact of bark beetle (Ips typographus) infestations in mountain spruce forests on SR, we measured SR at infested sites by bark beetles and adjacent undisturbed stands in the High Tatra Mountains (Slovakia). The measurements were conducted during the vegetation period (May-September) in 2016 and 2017, five to six years after the initial attack by bark beetles, at an altitudinal gradient (1100-1400 m a.s.l.). SR varied throughout different months and altitudes, and we observed that SR at infested sites reached higher values (in most cases) than at uninfested stands. Average monthly and altitude SR rates during both vegetation periods showed higher values at infested sites, but not all of them were statistically significant. We observed an insignificant change in SR rate between 2016 and 2017 at both infested and uninfested sites. The highest rates of SR were observed in 2016 from July to August at both infested and undisturbed sites. On the other hand, in 2017 the highest SR rates were observed in June and July at undisturbed sites and from June to August at infested sites. However, yearly SR from May-September at infested sites showed significantly higher rates than uninfested ones in both years. SR showed a decreasing pattern with elevation gain in 2016 at infested sites. However, this pattern was not observed in 2017. Based on our observation and results we postulate that SR rates at infested sites are boosted by needle fall and debris from dead and dying trees, which increases heterotrophic SR and compensates the decrease of autotrophic SR from tree roots. This study provides important insights into the impact of bark beetle infestations on SR and highlights the need for further research on the long-term effects of forest disturbances on carbon cycling.

The overuse of chemical fertilisers degrades the soil ecosystem and restricts the natural development of plants. Within the coffee industry, various by-products are produced throughout the process of coffee production and consumption, which are significant in terms of environmental waste. SCG (spent coffee grounds) contain a variety of bioactive compounds that have demonstrated potential applications in various fields. These compounds can enhance soil quality by improving its chemical, physicochemical, physical properties, and biological fertility, ultimately leading to improved plant growth. This study examines the impact of SCG, vermicompost, and chemical fertilisers on the growth of organic red radish (Ravanello Cherry Belle) and soil quality. The experiment, conducted in a greenhouse, tested various concentrations and applications of SCG. Results showed that the SCGT 0.5 gm treatment yielded the highest mean plant length (18.47 cm) and fresh weight (27.54 grammes), while the SCG 10% treatment resulted in the lowest mean plant length (4.54 cm) and fresh weight (0.07 grammes). Vermicompost at 50% concentration produced the highest mean leaf surface area (58.32). These findings suggest the potential of SCG as a sustainable fertiliser alternative, contributing to improved plant growth and soil quality, thus supporting sustainable agricultural practices and a circular economy.

Saline water irrigation contributes significantly to forage yield. However, the salinity threshold for safe saline water irrigation of tall wheatgrass in coastal saline-alkaline land remains unclear. In this study, 2 g L‒1, 3 g L‒1, 4 g L‒1, 5 g L‒1, and 8 g L‒1 saline waters were used for irrigation. Two irrigations with 2+3 g L‒1 saline waters produced the highest yield, followed by one irrigation with 4 g L‒1 or 5 g L‒1 saline water. After rainfall’s leaching, the soil electrical conductivity (EC1:5) reduced by 41.7%‒79.3% for the saline water irrigation treatments. In combination with saline water irrigation, plastic film mulching can be used for sward establishment of seed propagated tall wheatgrass. However, irrigation with high salinity of drainage water enhanced the risk of plant death. Further, a pot experiment demonstrated that irrigation with 5 g L‒1 saline water led to the least reduction of forage yield and the highest crude protein content in leaves. However, the plants irrigated with ≥7 g L‒1 saline water enhanced soil salinity and reduced plant height, leaf size, and gas exchange rate. Conclusively, one irrigation with ≤5 g L‒1 saline water at the end of April or early May could be acceptable to maximize the forage yield of tall wheatgrass and minimize soil salinization risk in the coastal saline-alkaline land around the Bohai Sea.

We enhanced the agro-hydrologic VegET model to include snow accumulation and melt processes and the separation of runoff into surface runoff and deep drainage. Driven by global weather datasets and parameterized by Land Surface Phenology (LSP), the enhanced VegET model was implemented in the cloud to simulate daily soil moisture (SM), actual evapotranspiration (ETa), and runoff (R) for the conterminous United States (CONUS) and the Greater Horn of Africa (GHA). Evaluation of the VegET model with independent data showed satisfactory performance, capturing the temporal variability of SM (Pearson correlation r: 0.22–0.97), snowpack (r: 0.86–0.88), ETa (r: 0.41–0.97), and spatial variability of R (r: 0.81–0.90). Absolute magnitudes showed some biases, indicating the need of calibrating the model for water budget analysis. The seasonal Landscape Water Requirement Satisfaction Index (L-WRSI) for CONUS and GHA showed realistic depictions of drought hazard extent and severity, indicating the usefulness of the L-WRSI for the convergence of evidence toolkit used by the Famine Early Warning System Network to monitor potential food insecurity conditions in different parts of the world. Using projected weather datasets and landcover-based LSP, the VegET model can be used not only for global monitoring of drought conditions, but also for evaluating scenarios on the effect of a changing climate and land cover on agriculture and water resources.

The objective of this study is to investigate the use of excavation behavior prediction and analysis software in the field of civil en-gineering. PLAXIS and SoilWorks, widely used in the engineering and academic communities, were employed as research tools for analyzing gravel layers and deriving appropriate ranges of soil elastic modulus for different software programs. By collecting excavation cases in the Xindian area of New Taipei City, Taiwan, and conducting deep excavation analysis using the displacement of retaining walls, this study provides recommended ranges for localized selection of soil elastic modulus. The suggested range for PLAXIS is 7,840 N/m² to 9,800 N/m², while Soil-Works suggests a range of 2,450 N/m² to 3,430 N/m². These ranges allow for reasonable estimation of maximum deformations during the final excavation stage. Based on the research findings, it is recommended that engineers refer to the provided ranges when selecting soil elastic modulus for excavation analysis in gravel layers using different soft-ware programs in the Xindian area of Taiwan to improve the accuracy of deformation predictions during the final excavation stage. These results serve as important references for engineers and contribute to the effective prediction and management of excavation behavior in civil engineering projects.

A large set of undrained compression triaxial tests was carried out on different types of cohesionless soils, from sands to silty-sands and silts. Shear wave velocity measurements were carried out alongside. These tests exhibited distinct state transitions ranging from flow liquefaction to strain softening or strain hardening. With the purpose of defining a framework to assess soil liquefaction, it was found that the ratio between the shear wave velocity (VS0) and the peak undrained deviatoric stress, qpeak, VS0/qpeak, could be accurately used to define a boundary between liquefaction and strain hardening for sands, and between strain softening and strain hardening for silty-sands and silts. Since this ratio is a function of the tested material, it was also discovered that the prediction of these boundaries could be made as a function of soil grading, namely via the coefficient of uniformity, CU. Despite not being regarded as a strong geomechanical parameter, CU is easily determined from a grain-size distribution test and it has an empirically proven correlation with critical state parameters.

Weeds can have both positive and negative effects on agricultural environments. However, despite the growing interest in the ecology of weed communities in agricultural areas, few studies have been carried out in the northern region of the Andes of Colombia, where urban and agricultural expansion have gen-erated highly disturbed scenarios. The aim of this study is to analyze the diversity of vegetation and weed seed banks in three agricultural production systems and a forest ecosystem in the northern Andes of Colombia. Hill numbers were used to compare diversity, Beta diversity to assess changes in composition, and range-abundance-dominance curves at different sites. Likewise, indicator species were analyzed to find species associations to each system. The results revealed differences in the composition of weeds between the forest ecosystem and the agricultural production systems, with higher equitability in the forest ecosystem and higher dominance in agricultural systems. A higher differentiation was observed in the dominant species of each agricultural system, highlighting those considered pests due to their life history traits, giving them greater success against various anthropogenic selection pressures. These findings highlight the impact of anthropogenic disturbances on the ecological dynamics of weed com-munities in different ecosystems, which should be considered when planning integrated weed manage-ment techniques.

Plants do need a fixed proportion of carbon (C), nitrogen (N) and phosphorus (P) elements to maintain normal metabolic activities. The P fertilizers are widely used to supplement nutrients in subtropical plantations. Stoichiometric homeostasis reflects the strategy of plants to cope with various environments (including P fertilizer supply rate). It is thus of great significance to understand C:N:P stoichiometry in the plant-litter-soil system under P addition and stoichiometric homeostasis of plant tissues for fertilization management of slash pine (Pinus elliottii Engelm) plantations. We measured the C, N and P contents in root, branch, needle, litter and soil in slash pine plantations fertilized with four treatments - P1 (25 kg P ha−1 yr−1), P2 (50 kg P ha−1 yr−1), P3 (100 kg P ha−1 yr−1), and a control (CK) in subtropical China and calculated stoichiometric homeostasis of plant tissues. Results showed that P addition increased the capacity of needle to obtain C, N and P elements and altered the C:N:P stoichiometry of plant tissues, as well promoted the accumulation of C and P elements in soil, but had no significant effect on soil stoichiometry. The nutrient contents of needle and branch were higher than those of root and litter, indicating that slash pine was more inclined to allocate nutrient to the aboveground tissues. The stoichiometric homeostasis of C, N and P among plant tissues was ranked as follows: root > branch > needle, and homeostasis of nutrient elements in the needle was C > N > P. This indicated that the C, N and P stoichiometric homeostasis was various among plant tissues and elements types under P addition. These findings suggest P addition would alleviate the P limitation of slash pine growth in subtropical regions. In the future, long-term observation experiments should be conducted and the trade-off between P addition rates and economic and ecological benefits should be considered.

With climate change projected to increase the frequency and severity of episodic insect outbreak events, assessing potential consequences for soil microbial communities and nutrient dynamics is of importance for understanding forest resilience. The forest tent caterpillar (Malacosoma disstria) is an important defoliator of deciduous tree species in temperate and mixed forests of eastern North America with an invasion cycle every 10-12 years and outbreak events that can last 3-6 years. Following a defoliation episode on trembling aspen (Populus tremuloides) from 2015 to 2017 in Abitibi-Témiscamingue, QC, Canada, we sought to test if defoliation resulted in changes to soil bacterial and fungal communities. We hypothesized an increase in soil microbial biomass due to increased caterpillar frass inputs and potential changes in community structure following the event. Soils were sampled in July 2018, May 2019 and July 2019 from sites that had been subject to defoliation during the outbreak and from sites where no defoliation had been recorded. We assessed soil microbial biomass and fungal to total microbial activity ratio on all sampling dates, and Community Level Physiological Profiles (CLPPs) for 2018 only using a substrate induced respiration method. Contrary to our hypothesis, we observed a significant 50% decrease in microbial biomass (g biomass-C g-1 soil hour-1) in defoliated stands suggesting tree carbon normally allocated towards root exudates was reallocated towards foliage regeneration. We noted a differentiated carbon-based substrate usage following defoliation, but no change in the fungal to total microbial activity ratio. The observed changes in the two years following the defoliation event suggest that defoliation episodes aboveground could trigger changes in soil chemistry belowground with effects on soil microbial communities that may, in turn, feedback to influence forest plant dynamics.

So that the levels of water stress are not harmful to the development of the crop and affect its productivity, its detection and monitoring are necessary, and it can occur in different ways. One of them is through the Crop Water Stress Index (CWSI). This index quantifies water stress through the normalization of leaf temperature between the maximum and minimum plant temperatures as a function of evaporation conditions. The responses of a low-cost infrared (IR) sensor were crossed with image processing through segmentation by the Excess Green model to develop a water stress detection system using CWSI. A soil/plant temperature map was generated through a point-to-point scan of the IR sensor. And when it overlaid with a segmented image of the experimental area, only points identified as plants had their temperature values maintained. The Non-Water-Stressed Baseline (NWSB) equation was parameterized for the same conditions of the experiment and external environmental. The experimental area was divided into three different treatments, maintained under stable water conditions throughout the experiment and the system was able to identify stably different stress values between treatments. Although the relationship between crop and environment affected the results, this work showed that using an irrigation system based on CWSI is possible.

Human leptospirosis cannot be investigated without studying zoonotic and environmental as-pects of the disease. The objectives of this study are to explore the abundance of Leptospira in dif-ferent climate zones of Sri Lanka and to describe the presence of Leptospira in same water source at different time points. First, water and soil samples were collected from whole-island, secondly, water sampling continued only in dry-zone, finally serial sampling of water from ten open wells was performed at five different time points. Quantitative PCR for water and metagenomic se-quencing for soil were used to detect Leptospira. In first component, 2 out of 12 water sites were positive and both are situated in wet-zone. Very small quantities of Genus Leptospira was detect-ed by metagenomic analysis of soil. Only 5 out of 26 samples were positive in the second compo-nent. Six, five, four, five, six wells were positive respectively in serial measurements of third component. All wells were positive at least one measurement while only one well was positive in all measurements. Closer to tank and higher distance from main road were significant risk fac-tors associated with well positivity. Presence of Leptospira seems not consistent indicating ran-dom abundance of Leptospira in natural environment.

Most smallscale farmers still use the traditional way of agricultural crop farming, and relay mostly use of chemical fertilizers (CF). Recently CF have become expensive and could in some way have a negative impact on soil quality after long term application. However, co-application of biogas slurry (BGS) with CF could help reduce farming costs while improving dry matter yields, grain yields, primary macronutrient uptake of (Nitrogen) N, (Phosphorus) P, (Potasium) K, (Calcium) Ca and (Magnesium) Mg and soil concentration of pH, (organic carbon) OC, N, P, K, Ca and Mg after crop harvest. The study was a field experiment conducted in 2016-2017 and 2017-2018 growing seasons. The field experiment was arranged in a randomized complete block design with four replicates. The treatments were based on percentages of recommended N rates of 120 kg N ha-1 for maize production. The BGS/CF treatments were (i) 0/0, (ii) 0/120, (iii) 24/96, (iv) 48/72, (v) 72/48, (vi) 96/24, (vii) 120/0 kg N ha-1. The spreading of the combination of BGS/CF treatments was performed by hand and incorporated into the top soil (0-10 cm) in each experimental plots. BGS/CF (48/72) treatment resulted into higher dry matter yield in 2016-2017, which was higher than all other treatment combinations, while in the 2017-2018 season, treatment of (0/120) resulted into higher dry matter than all other treatment combinations. The 48/72 and 0/120 treatments resulted into similar grain yield in 2016-2017 season which were higher than all other treatments. Treatments of 48/72, 72/48 and 120/0 had higher N, P, K, Ca and Mg uptake than 0/0, 0/120, 24/96 and 96/24 treatments in both seasons. Soil pH, total N, K, and Mg were high from the treatment of (120/0) than all other treatments in 2016-2017 while in the 2017-2018 season, treatment of (48/72) had higher OC, P and K after maize harvest. The findings of his study show that co-application of BGS/CF at 48/72 and 72/48 have maize yield benefits compared to the two resources, BGS/CF (120/0) and BGS/CF (0/120), applied separately in soil especially in the arid and semi-arid regions.

An experimental series of shearing tests with water infiltration were performed on compacted unsaturated soil to simulate the behavior of shallow slope failures. Soil samples were compacted at moisture contents from dry to wet of optimum moisture content with the degree of saturation varying from 24.0% to 59.5% while maintaining the degree of compaction at 80%. Two series of shearing with infiltration tests were performed in this study. In Series-I, just before the start of shearing, matric suction was decreased by increasing pore water pressure to start water infiltration i.e. shearing is carried simultaneously with water infiltration. In Series-II, the soil was first sheared with drained pore air and undrained pore water to pre-defined value of deviatoric stress, after which matric suction was decreased by increasing pore water pressure to start water infiltration and shearing is performed by keeping deviatoric stress constant on the specimen. The test results showed that the decrease in matric suction has an effect on the volume of infiltrated water and degree of saturation. The soil slopes compacted on the dry side of optimum moisture content showed better performance than other soils, they require more decrease in matric suction to start water infiltration and showed higher deviatoric stress. In addition to this, water infiltration alone can cause the failure of shallow slopes without having to have any further loading.

Here we evaluate the chemistry of mineral soil solutions collected by suction lysimeters in a small mountain catchment that was affected by acidification-related spruce die-back. The aim was to obtain new insights into spatial patterns of nutrient partitioning during acidification recovery. This was achieved by comparing nutrient concentrations in soil solutions, collected along a V-shaped valley, with those in runoff. Five nests of suction lysimeters were installed in the 33-ha UDL catchment at different topographic positions (hilltops, slopes and valley). Following a 1-year equilibration, monthly samples of soil solutions were collected over a 2-year period. In the vicinity of each lysimeter nest, soil pits were excavated for a study of soil chemistry. Soil solutions were analyzed for SO42-, NO3-, DOC, NH4+, Na+, K+, Ca2+, Mg2+, and total dissolved Al concentrations, DOC and pH. For a P release estimation, ammonium oxalate extraction of soil samples was performed. Comparison of soil water data from this study with other European studies indicated that major environmentally relevant chemical species at UDL had concentrations similar to median concentrations across numerous previously acidified sites. CEC (≤ 58 meq kg-1) and BS (≤ 13 %), however, were significantly lower at UDL than at other European sites, documenting incomplete recovery from acidification. Spatial trends and seasonality in soil water chemistry support belowground inputs from mineral-stabilized legacy pollutants and soil nutrients. Seasonal variability of soil water sulfate and nitrate was significant. High nitrate in soil solutions during summer originated during the preceding dormant season, and high sulfate concentrations observed during the winter originating from recycled organic S during the summer. Higher concentrations of SO42-, NO3-, and base cations in runoff than in soil solutions may be explained by lateral surficial runoff leaching pollutants and nutrients from very shallow soil horizons. Nearly 30 years after peak acidification, solutions in mineral subsoil at UDL exhibited similar concentrations of SO42-, Ca2+ and Mg2+ as median values at the Pan-European International Co-operative Program (ICP) Forest sites, yet NO3- concentrations were an order of magnitude higher than the ICP sites. Calcium applied on soil surface by liming 32 to 11 years ago affected runoff more than soil solutions, suggesting contribution of both shallow soil water and groundwater to runoff.

This study aims to assess the potential of the LDAS-Monde a land data assimilation system developed by Météo-France to monitor the impact of the 2018 summer heatwave over western Europe vegetation state. The LDAS-Monde is forced by the ECMWF’s (i) ERA5 reanalysis, and (ii) the Integrated Forecasting System High Resolution operational analysis (IFS-HRES), used in conjunction with the assimilation of Copernicus Global Land Service (CGLS) satellite derived products, namely the Surface Soil Moisture (SSM) and the Leaf Area Index (LAI). Analysis of long time series of satellite derived CGLS LAI (2000-2018) and SSM (2008-2018) highlights marked negative anomalies for July 2018 affecting large areas of North Western Europe and reflects the impact of the heatwave. Such large anomalies spreading over a large part of the considered domain have never been observed in the LAI product over this 18-yr period. The LDAS-Monde land surface reanalyses were produced at spatial resolutions of 0.25°x0.25° (January 2008 to October 2018) and 0.10°x0.10° (April 2016 to December 2018). Both configuration of the LDAS-Monde forced by either ERA5 or HRES capture well the vegetation state in general and for this specific event, with HRES configuration exhibiting better monitoring skills than ERA5 configuration. The consistency of ERA5 and IFS HRES driven simulations over the common period (April 2016 to October 2018) allowed to disentangle and appreciate the origin of improvements observed between the ERA5 and HRES. Another experiment, down-scaling ERA5 to HRES spatial resolutions, was performed. Results suggest that land surface spatial resolution is key (e.g. associated to a better representation of the land cover, topography) and using HRES forcing still enhance the skill. While there are advantages in using HRES, there is added value in down-scaling ERA5, which can provide consistent, long term, high resolution land reanalysis. If the improvement from LDAS-Monde analysis on control variables (soil moisture from layers 2 to 8 of the model representing the first meter of soil and LAI) from the assimilation of SSM and LAI was expected, other model variables benefit from the assimilation through biophysical processes and feedbacks in the model. Finally, we also found added value of initializing 8-day land surface HRES driven forecasts from LDAS-Monde analysis when compared with model only initial conditions.

Biochar application to soil has been proposed as a means for reducing soil greenhouse gas emissions and mitigating climate change. The effects, however, of interactions between biochar, moisture and temperature on soil CO₂ and N₂O emissions, remain poorly understood. Furthermore, the applicability of lab-scale observations to field conditions in diverse agroecosystems remains uncertain. Here we investigate the impact of a mixed wood gasification biochar on CO₂ and N₂O emissions from loess-derived soils using: (1) controlled laboratory incubations at three moisture (27, 31 and 35%) and three temperature (10, 20 and 30°C) levels, and (2) a field study with four cropping systems (continuous corn, switchgrass, low diversity grass mix, and high diversity grass-forb mix). Biochar reduced N₂O emissions under specific temperatures and moistures in the laboratory and in the continuous corn cropping system in the field. However, the effect of biochar on N₂O emissions was only significant in the field, and no effect on cumulative CO₂ emissions was observed. Cropping system also had a significant effect in the field study, with soils in grass and grass-forb cropping systems emitting more CO₂ and less N₂O than corn cropping systems. Observed biochar effects were consistent with previous studies showing that biochar amendments can reduce soil N₂O emissions under specific, but not all, conditions. The disparity in N₂O emission responses at the lab and field scales suggests that laboratory incubation experiments are not reliable for predicting the impact of biochar at the field scale.

Decomposition of natural and synthetic polymeric materials (peat, humates, biochar, strongly swelling hydrogels and other soil conditioners) in a biologically- and chemically- active soil environment inevitably leads to their degradation and ability to improve the structure, water-retention, absorptive capacity and actual fertility of artificial soil constructions in urbanized ecosystems and agro landscapes (constructozems). Quantitative assessment of the biodegradation process using field and laboratory incubation experiments, as well as mathematical modeling, showed the possibility of significant (up to 30-50% per year) losses of organic matter of constructozems and a corresponding deterioration in their quality. Incubation experiments with the analysis of carbon dioxide emission for polymeric materials under given thermodynamic conditions allow to estimate the potential rates of their decomposition (half-life) and their dependence on the dose of inhibitors of microbial activity. Special nomographs provide an opportunity to determine the optimum depth of the arrangement of organic components in soil constructions to ensure their stable functioning during a fixed operating time in urban conditions. The results of the study are useful for geo-engineers and landscaping practitioners.

Environmental monitoring plays a central role in diagnosing climate and management impacts on natural and agricultural systems, enhancing the understanding hydrological processes, optimizing the allocation and distribution of water resources, and assessing, forecasting and even preventing natural disasters. Nowadays, most monitoring and data collection systems are based upon a combination of ground-based measurements, manned airborne sensors or satellite observations. These data are utilized in describing both small and large scale processes, but have spatiotemporal constraints inherent to each respective collection system. Bridging the unique spatial and temporal divides that limit current monitoring platforms is key to improving our understanding of environmental systems. In this context, Unmanned Aerial Systems (UAS) have considerable potential to radically evolve environmental monitoring. UAS-mounted sensors offer an extraordinary opportunity to bridge the existing gap between field observations and traditional air- and space-borne remote sensing, by providing not just high spatial detail over relatively large areas in a cost-effective way, but as importantly providing an entirely new capacity for enhanced temporal retrieval. As well as showcasing recent advances in the field, there is also a need to identify and understand the potential limitations of UAS technology. For these platforms to reach their monitoring potential, a wide spectrum of unresolved issues and applications specific challenges require focused community attention. Indeed, to leverage the full potential of UAS-based approaches, sensing technologies, measurement protocols, post-processing techniques, retrieval algorithms and evaluations techniques need to be harmonized. The aim of this paper is to provide a comprehensive general overview of the existing research on studies and applications of UAS in environmental monitoring in order to suggest users and researchers on future research directions, applications, developments and challenges.

Crimean-Congo hemorrhagic fever virus is one the most important and wide spread tick-borne viruses. Very little is known about the transmission from the tick and the early aspects of pathogenesis. Here, we generate human cutaneous antigen presenting cells: dermal dendritic cells and Langerhans cells, from umbilical cord progenitor cells. In order to mimic the environment created during tick feeding, tick salivary gland extract was generated from semi-engorged Hyalomma marginatum ticks. Our findings indicate that human dermal dendritic cells and Langerhans cells are susceptible and permissive to Crimean-Congo hemorrhagic fever virus infection, however, to different degrees. Infection leads to cell activation and cytokine/chemokine secretion, although these responses vary between the different cell types. Hyalomma marginatum salivary gland extract had minimal effect on cell responses, with some synergy with viral infection with respect to cytokine secretion. However, salivary gland extract appeared to inhibit antigen presenting cell (APC) migration. Based on the findings here we hypothesize that human dermal dendritic cells and Langerhans cells serve as early target cells. Rather affecting Crimean-Congo hemorrhagic fever virus replication, tick saliva likely immunomodulates and inhibits migration of these APC from the feeding site.

The Temperate Highland Peat Swamps on Sandstone (TPHSS), unique to the Sydney Basin of Australia, were burnt during the 2019-2020 wildfire season. This study assessed the post fire recovery of swamps and the ability of remote sensing technique to determine the post-fire recovery patterns. Specifically, the study investigated differences in fire recovery between swamps where groundwater level and soil moisture content have been impacted by underground mining and unimpacted by mining. Two mined and one non-mined under swamps were investigated. Soil moisture measurements were taken at five sites and previously conducted vegetation field surveys (from 2016 to 2022) were used. Using remote sensing information, Normalised Differenced Vegetation Index (NDVI) and Soil Moisture Index (SMI) time-series were calculated and compared with ground data to map responses over the swamps following the fire impact. This study revealed that hydrological conditions of swamps have a direct effect on post-fire recovery of swamps, with slower recovery in mined under swamps compared with non-mined under swamps. This study indicated that NDVI and SMI indices can exhibit the recovery pattern of swamps in terms of vegetation and hydrology. However, the evaluation of recovery pattern of a specific vegetation species requires a frequent field survey.

Incorporating sewage sludge (SS) into soils presents a cost-effective and environmentally friendly option compared to conventional farming practices. However, SS could be perceived as a double-edged sword, as it may contain a broad spectrum of contaminants, posing threats to soil, underground waters, food chains and human health. Even from an epidemiology perspective, the COVID-19 pandemic has instigated debates regarding the potential health risks associated with SS. The handling of SS is emerging as a significant issue in the European Union (EU), primarily due to its increasing utilization and the presence of contaminants such as heavy metals (HMs), microplastics (MPs), Pharmaceuticals in the Environment (PIE), and personal care products (PSPs). The Council Directive 86/278/EEC governs the limits of HMs when SS is utilized in agriculture. However, the Directive is enacted diversely throughout EU member states (MS), with their national legislations highlighting differences, gaps and various approaches in implementing the Council Directive. The Directive, which has been in force since 1986, has not undergone any significant revisions until the recent disclosure of a revised version in May 2023. The executive summary of the evaluation of the Council Directive 86/278/EEC (SWD-2023) – {final 158} specifies maximum concentrations of six HMs in SS among its regulatory measures. This article delves into capturing the current legal framework that defines and delimits the processes and obligations of EU MS regarding SS's management, treatment, and agriculture amendment. The primary objective is to explore the qualitative and quantitative differences/discrepancies between the MS National legislation and point out discontinuities and gaps, thus setting forward a cohesive step for future revisions and updates of the relevant legislation. Part of the article's results reflect the different approaches to permissible limits of HMs concentrations in the EU MS and between international organizations such as the Food and Agriculture Organization (FAO) and the World Health Organization (WHO). Moreover, the total absence of MPs and other Common Soil Pollutants (antibiotics, pharmaceuticals, etc.) limit values are evidence of the gaps in the current legislative framework.

Variable retention harvesting (VRH) was designed for timber purposes and biodiversity conservation in natural forests. This system was globally tested, but few studies are related to soil microbial components. The objective was to evaluate different retention types (aggregated and dispersed retention) considering different years-after-harvesting (6, 9, 16 YAH) on soil microbial community attributes compared with unmanaged primary forests (PF) in Nothofagus pumilio forests of Tierra del Fuego (Argentina). We also evaluated the influence of climate, soil and understory vegetation. Results showed that aggregated retention increased microbial biomass carbon (MBC), microbial biomass nitrogen (MBN) and soil basal respiration (SBR) compared to dispersed retention, but with similar values than PF. However, harvested areas decreased MBC:MBN values compared with PF. We found an overall decreasing of microbial biomass and activity in 9 YAH stands, with a positive recovery at 16 YAH. Soil pH, mean annual temperature and understory vegetation cover showed a positive relationship with MBC, MBN, and SBR. The recovery after 16 YAH reaching to a different microbial community. Therefore, maintenance of retention components in managed stands for longer periods is needed. Our results highlight some advantages of VRH as a tool for conservation of forest-dwelling soil microorganisms (microbial biomass and activity).

This work discusses seismic isolation technologies and analyses the concept of geotechnical seismic isolation (GSI) system, which is characterized by new principles of operation, using geomaterial with modified properties to reduce inertial seismic loads on buildings and structures. The aim of the study is to develop a geotechnical seismic isolation system in the form of vertical barriers, with different geometrical characteristics, using rubber-soil mixture (RSM). The novelty of the work consists in determination of effective constructive and technical solutions of vertical seismic barriers from RSM, which are characterized by reliability in providing seismic isolation of construction objects. Soil and superstructure interactions are modeled in Plaxis software, using the Northridge earthquake accelerogram. The results confirm the positive impact of using RSM as an effective material for GSI vertical barriers. The present numerical and experimental results show that the GSI system using RSM can significantly reduce the seismic hazard. The results of computational-experimental modeling will become a research, analytical and design basis for the development of new ways to ensure earthquake resistance of construction objects.

Arthropods, the most abundant group in ecosystems, play crucial roles in human production. Soil physicochemical properties reflect soil health and are linked to arthropods through cascading effects. Gravel-sand mulching, commonly practiced in dry farming regions, initially aids in water retention and temperature regulation. However, long-term cultivation can lead to land degradation and habitat fragmentation. This study aimed to investigate field systems using multiple comparison, linear, and nonlinear correlation analyses to explore the effects of different tillage durations on soil properties and arthropod diversity under gravel-sand mulching. Results indicate that arthro-pod diversity was lower while the fields maintained better soil fertility than the desert steppe. Both soil fertility and arthropod diversity declined significantly with increased years of cultivation. Mantel tests revealed no significant response of desert steppe arthropods to the altered soil properties of gravel-sand mulched fields. However, the Generalized Additive Model analysis indicated significant linear correlations between arthropod occurrence and total nitrogen (positive), available phosphorus, and water content (negative). Arthropod abundance showed significant nonlinear correlations with total potassium, alkali hydrolyzable nitrogen, and organic matter (OM), with OM changes having the most pronounced impact. Thus, gravel-sand mulching can maintain soil fertility over time but at the expense of local arthropod diversity.

Addressing the significant challenge in high-speed cotton dibbling operations in Xinjiang—specifically, the duck bill’s ("Duck bill" is a type of duck-billed bunch planting mechanism or component). shortened opening duration leading to seed throwing and floating—a new crawler-type delayed hole-forming mechanism has been designed. This mechanism extends the duck bill horizontally, thereby prolonging its opening time, enabling cotton sowing speeds of up to 6 km/h. Following agronomic principles for cotton planting, the overall layout of the crawler-type hole-forming mechanism, the structural parameters of the key components and the trajectory of the hole-forming are determined. We use the Discrete Element Method (DEM) and multi-body dynamics coupling method to simulate and analyze the motion process of the device. The fixed the tilt angle of the duck bill α(A), the depth of the duck bill hole-forming into the soil h(B), and the angle of rotation of the moving duck bill β(C) were taken as the experimental factors, with the longitudinal length of cotton seed hole (Y1) and the hole-forming depth of cotton seed hole (Y2) as the response values. The parameter range of each factor and the preliminary influence on the response value were determined through pre-experiments and single-factor simulation test. Based on RecurDyn-EDEM coupling, a quadratic regression orthogonal rotation combination simulation test was carried out. The results show that the order of the primary and secondary factors affecting the Y1 of the time-lapse hole-forming device was: A > C > B. The order of primary and secondary factors affecting the Y2 of the delayed hole forming device was: B > C > A. When the A was 2.4 °, the B was 42.4 mm, and the C was 30.5 °, the performance of the hole-forming was the best, and the Y1 was 26.4 mm, and the Y2 was 25.0 mm. The bench verification test results show that under the optimized combination of operating parameters, the average Y1 was 29.1 mm, and the average Y2 was 23.2 mm. Compared with the results of the previous coupled simulation model, the average relative errors of the two are 7.23 % and 4.36 %, respectively, indicating the accuracy and effectiveness of the established DEM simulation model and virtual test analysis. The hole-forming area and the opening time of the duck bill after the stable operation of the machine were recorded and measured. The calculated hole dislocation rate Hc was 4.33 %, which did not exceed the national standard requirement of 6 %. The qualified rate of hole distance Hx was 94.33 %, which was much higher than the national standard requirement of 80 %. The average opening time of the duck bill at a speed of 6 km/h is 0.45 s, which is much longer than the time required for cotton seeds to fall from the duck bill 0.11 s. It meets the requirements of high-speed cotton planting in China and facilitating advancements in future high-speed planter technology.

Soil management in orchards can have several economic and environmental implications. In this study, three different soil management systems were compared in a dry-farmed olive grove: conventional tillage (Tillage), glyphosate-based herbicide (Herbicide) and Sheep Walking. The experiment lasted eleven years (2011-2022) and was carried out after a previous trial conducted on the same plot with the same treatments and duration (2001-2011). However, in the earlier trial, the Herbicide and Sheep Walking treatments switched positions in the plot, while the tillage treatment remained in its original place. The average total accumulated olive yields between 2011 and 2022 were 225.1, 230.9, and 245.0 kg tree–1 for the Sheep Walking, Tillage, and Herbicide treatments, respectively. However, no significant differences were observed between the treatments. The levels of total organic carbon in the soil, measured in samples collected in the last year of the study, were 41.3, 33.7, and 37.3 g kg–1, respectively for the same treatments. These findings indicated that the Tillage treatment exhibited lower soil organic matter content and reduced bioavailability of some nutrients, which raises concerns about its sustainability. On the contrary, employing Sheep Walking with an appropriate stocking rate, effectively controlling vegetation in the spring, ensured favourable soil properties and olive yields comparable to the other treatments. Moreover, the Sheep Walking approach provides supplementary advantages to the farmer, including revenue from the sale of animal products and the opportunity to transition to organic farming systems, which better align with the preferences of contemporary societies.

The high reliable correlations between CBR and DCP in general proposed are presented in this paper. We analyzed the test data and correlations from many researchers to find the best equation for prediction the CBR from DCP test. The findings show that all correlations from existing paper are based on local material and cannot apply to soil in a different location in general purpose. New correlations between CBR and DCP were proposed and validated in this paper for general uses. The validation confirmed that these new correlations can predict well with higher R2.