Soil Type Research Articles

Identification study of soil types based on feature factors of XRF spectrum combining with machine learning

Soil type significantly influences the detection accuracy of heavy metals using X-ray fluorescence (XRF) technology. Rapid and accurate soil type identification is crucial for selecting appropriate XRF quantitative analysis methods for soil heavy metals, thereby enhancing analysis accuracy. This study utilized 26 soil samples from 10 distinct soil types, extracting 13 feature factors for soil type identification by analyzing XRF spectral variability. These factors were then integrated with three machine learning methods: Random Forest (RF), Support Vector Machine (SVM), and Backpropagation Neural Network (BPNN). The effectiveness of these methods in soil type identification was compared, highlighting the importance of XRF spectral feature factor extraction. The results demonstrate that identification based on feature factor extraction from XRF spectral variability markedly improves identification accuracy, stability and speed compared to full-spectrum XRF analysis. When identifying soil types by the gross area of spectral peaks of XRF feature factors, the accuracies of three machine learning methods—RF, SVM, and BPNN—were 99.62%, 99.04%, and 98.85%, respectively. Random Forest achieved the highest accuracy (99.62%) and fastest operation speed (0.179 s). Therefore, by extracting the differential features of XRF spectra and combining them with machine learning methods, it is possible to quickly and accurately recognize and judge soil types. This study demonstrates the successful and accurate identification of soil types using machine learning combined with XRF spectroscopy.It establishes an important methodological foundation for the future development of fast and accurate field testing equipment for soil heavy metals using XRF technology.

Reference site selection based on state-and-transition models for soil health gap evaluation within cropland reference ecological units

Comparative soil health studies are critical in soil conservation and gauging the success of different management practices in soil health improvement. A primary challenge in these studies is the selection of a consistent natural reference site. Current choices vary widely, from minimally disturbed areas to pristine prairies. This methodological paper underscores the need for deliberate and thoughtful reference site selection for benchmark soil properties. Utilizing the State &Transition models, the study introduces a framework for this selection, drawing upon the ecological site (ES) and reference plant communities detailed in an ecological site description (ESD) within a respective Major Land Resource Area (MLRA). This study advocates for a localized classification within the framework of the Cropland Reference Ecological Unit (CREU), emphasizing the significance of local precipitation and soil data to ensure unbiased comparisons. Soil samples from eastern (MLRA 106) and western (MLRA 67A) Nebraska were collected, representing distinct pedogenetic and climatic differences. Analysis of soil organic matter between MLRAs displayed substantial variations, suggesting potential biases and complexities in soil health gap calculations when using reference sites and croplands not in the same MLRA, soil types (texture class), or precipitation zones. However, refining the comparisons by delineating the MLRA, soil, and precipitation zones within the framework of CREU yielded more consistent and realistic comparative data. Integrating the MLRA and ES, complemented by granular soil and precipitation data, provides a robust method for establishing soil health benchmark data.

Neonicotinoids as emerging contaminants in China's environment: a review of current data.

Neonicotinoids (NEOs), the most widely used class of insecticides, are pervasive in the environment, eliciting concerns due to their hydrophilicity, persistence, and potential ecological risks. As the leading pesticide consumer, China shows significant regional disparities in NEO contamination. This review explores NEO distribution, sources, and toxic risks across China. The primary NEO pollutants identified in environmental samples include imidacloprid, thiamethoxam, and acetamiprid. In the north, corn cultivation represents the principal source of NEOs during wet seasons, while rice dominates in the south year-round. The high concentration levels of NEOs have been detected in the aquatic environment in the southern regions (130.25ng/L), the urban river Sects.(157.66ng/L), and the downstream sections of the Yangtze River (58.9ng/L), indicating that climate conditions and urban pollution emissions are important drivers of water pollution. Neonicotinoids were detected at higher levels in agricultural soils compared to other soil types, with southern agricultural areas showing higher concentrations (average 27.21ng/g) than northern regions (average 12.77ng/g). Atmospheric NEO levels were lower, with the highest concentration at 1560pg/m3. The levels of total neonicotinoid pesticides in aquatic environments across China predominantly exceed the chronic toxicity ecological threshold of 35ng/L, particularly in the regions of Beijing and the Qilu Lake Basin, where they likely exceed the acute toxicity ecological threshold of 200ng/L. In the future, efforts should focus on neonicotinoid distribution in agriculturally developed regions of Southwest China, while also emphasizing their usage in urban greening and household settings.

Simultaneous determination of sixteen phthalic acid esters (PAEs) in soil and evaluation of matrix effect using a QuEChERS/GC/MS-internal standard method.

Phthalic acid esters (PAEs) are emerging pollutants that need to be analyzed precisely. Chromatography-based determination of PAE content in soils are frequently affected by matrix effect, which may limit the quantification of different kinds of PAEs from different types of soil. Here we optimized a QuEChERS protocol combined with gas chromatography-mass spectrometry (GC-MS) for simultaneous determination of 16 PAEs in different soils. PAEs in different type of soils (fluvo-aquic soil, red soil, and black soil) were extracted with acetonitrile followed by GC-MS detection based on quantitative ion internal standard method. All 16 PAEs showed excellent linear relationships with mass peak areas (R2 > 0.99). The limits of detection (LOD) and limits of quantitation (LOQ) of all the samples were in the range of 0.91-66.97µg/kg and 2.7-200.9µg/kg, respectively. The accurate test at 0.5, 0.1, and 1.0mg/kg spiking level recorded recovery rate between 80.11% and 100.99% with relative standard deviations (RSDs) ranging from 0.37 to 8.50% in tested matrices. No significant matrix effect was observed for most tested PAEs. This is a simple method with high sensitivity and strong stability, which is suitable and reproducible for quantifying large number of PAEs in different types of soil.

Ratio of physical model parameters can retrieve aggregate size from different types of soil in cultivated regions

Soil aggregate size, which is a proxy used to guide agricultural decisions and tillage management, can be estimated using optical remote sensing techniques. However, limited investigation has been conducted into the potential of using a physical model to retrieve soil aggregate size (< 2 mm) from different types of soil. This study is based on the multi-angular spectral measurements of seven soil samples from five soil types with 14 aggregate size fractions collected in Northeast China, three versions of the Hapke model were inverted using the Bayesian method. The findings confirmed that all three versions of the Hapke model can well characterize the angular reflection characteristics of all soil samples with different aggregate sizes. The inverted photometric parameters such as single scattering albedo ω, shape parameter b, and asymmetry parameter c were found to be sensitive to soil aggregate size, but the relationships rely on soil types because of the dependence of parameters related to soil composition. In order to obtain a general model that can be applied to different types of soil, the ratio of parameters (RoP) = (b + c)/ω, which is controlled by the external structure of soil aggregates, was proposed to retrieve the aggregate size from different soil types. Results show that the RoP can robustly capture the aggregate size of the soil with high accuracy and is insensitive to soil types. The combination of photometric parameters related to soil aggregate size provides a new method for retrieving the structural properties of the soil by eliminating interfering factors.

Spatial Prediction of Organic Matter Quality in German Agricultural Topsoils

Soil organic matter (SOM) and the ratio of soil organic carbon to total nitrogen (C/N ratio) are fundamental to the ecosystem services provided by soils. Therefore, understanding the spatial distribution and relationships between the SOM components mineral-associated organic matter (MAOM), particulate organic matter (POM), and C/N ratio is crucial. Three ensemble machine learning models were trained to obtain spatial predictions of the C/N ratio, MAOM, and POM in German agricultural topsoil (0–10 cm). Parameter optimization and model evaluation were performed using nested cross-validation. Additionally, a modification to the regressor chain was applied to capture and interpret the interactions among the C/N ratio, MAOM, and POM. The ensemble models yielded mean absolute percent errors (MAPEs) of 8.2% for the C/N ratio, 14.8% for MAOM, and 28.6% for POM. Soil type, pedo-climatic region, hydrological unit, and soilscapes were found to explain 75% of the variance in MAOM and POM, and 50% in the C/N ratio. The modified regressor chain indicated a nonlinear relationship between the C/N ratio and SOM due to the different decomposition rates of SOM as a result of variety in its nutrient quality. These spatial predictions enhance the understanding of soil properties’ distribution in Germany.

The Content of Soil Glomalin Concerning Selected Indicators of Soil Fertility

The glomalin content is generally considered an indicator of the soil organic matter (SOM) quality. The content of easily extractable glomalin (EEG) and the total glomalin (TG) content was investigated across 71 different sites in the Czech Republic with arable soil and crop production (12 chernozems, 30 luvisols, 17 cambisols, and 12 fluvisols). The majority of the crops in the crop rotation were cereals (45.5%—mainly winter wheat, winter barley, and spring barley). The proportion of winter canola within the crop rotation was 15.9%. The contribution of other crops was substantially smaller (alfalfa, clover, potatoes, beet, silage maize, grain maize). The representation of crops in the crop rotation is standard for conventional farming in the Czech Republic. Based on the results of long-term field monitoring at 71 sites in different soil–climate conditions, we can state the following. The TG content was significantly correlated with the soil organic matter carbon content (CSOM), as well as another important indicator of SOM quality (humic and fulvic acid carbon content ratio—CHA/CFA). A significant and positive correlation was also determined for the TG and clay content (size &lt; 0.002 mm), as well as particles smaller than 0.01 mm. The easily extractable glomalin content (EEG) did not differ based on the reference soil group (RSG). On the other hand, the total glomalin content (TG) was significantly higher in the chernozem RSG in comparison with other RSGs (luvisols, cambisols, fluvisols). There was no relationship between the pHCaCl2 and glomalin (EEG; TG). The same can be said about the relationship between glomalin (EEG; TG) and the bulk density and porosity. No link was established between the glomalin content (EEG; TG) and phosphorus plant-available content. There was no relationship between the amount of applied organic matter (carbon inputs) and the soil glomalin content (EEG; TG). This relationship was not influenced by the type of applied organic fertilizer. No significant relationship was found for either straw, manure, or compost. The data on the glomalin content are significantly influenced by the site (soil type and soil texture).

Spatial Multi Criteria Analysis for Evaluation of Residential Land in South Jambi, Jambi City

The land is a landscape on the earth's surface, dynamic to changes, such as converting to settlements. Settlement is driven by changes in population, the greater the population, the greater the need for land to be converted into housing. Based on data from 2018 to 2022, there has been an increasing population in the South Jambi sub-district, which is a strong indication of residential development. This research aims to evaluate the suitability of settlements in the South Jambi sub-district in 2022, using five variables namely, distance from the road, distance from the river, slope, soil type, and flood hazard index. The method of analysis uses the Spatial Multi-Criteria Analysis (SMCA) method. The research results show that the South Jambi sub-district is dominated by the suitable criteria of 568.0 hectares or 86.4%, very suitable criteria obtain 5.8 hectares or 0.9%, and somewhat suitable areas of 80.8 hectares or 12.3%. This means that the South Jambi area has a relatively high level of suitability for settlement. It is hoped that these results can provide information for various stakeholders in determining areas that are suitable for residential development, especially those that are at risk of flooding.

Long-term evaluation of surface topographic and topsoil grain composition changes in an agricultural landscape

Understanding long-term changes in topography and topsoil grain composition is crucial for the management of agricultural landscapes, especially in areas prone to wind erosion. This study investigates long-term changes in topography and topsoil grain composition within an agricultural landscape in south-western Slovakia. To analyse topographic changes over time, we used high-precision positioning measurements and airborne laser scanning to create digital terrain models (DTM) for the years 2011, 2017 and 2020. To assess changes in soil grain composition, we performed grain size analyses on soil samples collected during three different periods: M1 (1961–1970), M2 (2009–2015) and M3 (2015–2016). Changes in soil texture were evaluated to understand the impact of wind erosion on soil composition. The influence of windbreaks was also analysed by comparing the accumulation and deflation processes. The results showed significant changes in both topography and soil texture over the study period. The DTMs showed marked differences in the accumulation and deflation processes, highlighting areas affected by wind erosion. Comparisons of soil samples showed a shift in dominant soil types from loam and clay loam to silty loam, highlighting the effects of wind erosion. Analysis revealed a decrease in clay and silt content and an increase in sand content, indicating wind-induced soil degradation. The presence of windbreaks played a crucial role in reducing soil erosion by reducing wind speed, promoting soil accumulation and stabilising the landscape up to 80 m windward and 20 m leeward. The study highlights the complex interplay of climate and wind factors in shaping topography and soil properties and emphasises the protective role of windbreaks in agricultural landscapes over time. Our results show that wind erosion significantly alters soil texture, which can affect agricultural productivity. However, windbreaks have proven to be an effective measure in reducing soil erosion and maintaining soil quality.

Assessment of Crop water requirement using FAO CROPWAT 8.0 for Groundnut in South Odisha

Water has a major impact on crop growth, output, and quality and increased production with less water consumption is crucial due to increased demand from domestic and industrial sectors. With evaporative demand-based irrigation scheduling the water consumption gets reduced and improves water productivity. The type of soil, growing season, weather, and crop type affect specific crops' water needs. To compute crop water requirement, irrigation requirement, and its schedule for groundnut cultivated during the rabi season in south Odisha, India, the FAO CROPWAT 8 program was used, with the meteorological data of Centurion University, Paralakhemundi, and NASA power. The water requirement for groundnut was 362.1 mm, the irrigation requirement for groundnut crops was 323.7 mm, and crop evapotranspiration (ETc) was 373.4 mm during rabi season. At 50% critical depletion of soil moisture and soil replenishment to field capacity, the yield did not decrease. These results indicate that irrigation schedules can be practiced for different regions' crops without experimental results by estimating crop water requirements and irrigation schedules obtained through the FAO CROPWAT 8 model.

Single-cell exploration of active phosphate-solubilizing bacteria across diverse soil matrices for sustainable phosphorus management.

Phosphate-solubilizing bacteria (PSB) are crucial for enhancing phosphorus bioavailability and regulating phosphorus transformation processes. However, the in situ phosphorus-solubilizing activity and the link between phenotypes and genotypes for PSB remain unidentified. Here we employed single-cell Raman spectroscopy combined with heavy water to discern and quantify soil active PSB. Our results reveal that PSB abundance and in situ activity differed significantly between soil types and fertilization treatments. Inorganic fertilizer input was the key driver for active PSB distribution. Targeted single-cell sorting and metagenomic sequencing of active PSB uncovered several low-abundance genera that are easily overlooked within bulk soil microbiota. We elucidate the underlying functional genes and metabolic pathway, and the interplay between phosphorus and carbon cycling involved in high phosphorus solubilization activity. Our study provides a single-cell approach to exploring PSB from native environments, enabling the development of a microbial solution for the efficient agronomic use of phosphorus and mitigating the phosphorus crisis.

Assessing critical plant sulfur concentration and nitrogen to sulfur ratio in spring canola production

AbstractAimsPlant S concentration (Sc) and nitrogen (N) to S ratio (N:S) in canola are important indicators for diagnosing S deficiency. A field study was conducted on sandy and clay loam soils at two sites in eastern Canada for three growing seasons to determine plant critical Sc and N:S ratios across various growth stages (GSs).MethodsFor each site year, factorial experiments consisting of combinations of four N levels (0, 80, 160, and 240 kg N ha–1) as urea (46–0–0) and four S levels (0, 20, 30, and 40 kg S ha–1) as potassium sulfate (0–0–50–18) were classified orthogonally to form 16 combinations. Muriate of potash (0–0–60) was also applied as needed to ensure all plots receiving the equal amount of potassium (K).ResultsOur study found that S fertilization increased plant Sc at each GS but reduced the whole‐plant N:S ratio, and the effect was stronger during the flowering stage. Both whole‐plant Sc and N:S ratios varied with GS, environment, and soil type and declined with plant aging. Our results showed that whole‐plant S analysis combined with visual signs of plant S deficiency (purple‐edged and cup‐shaped leaves with less green; stunted growth, slow blooming, and fewer flowers) appeared to be the best way to identify S problems in the field, and whole‐plant Sc and N:S ratios could confirm S deficiencies.ConclusionOur findings indicated that if the whole‐plant Sc in the rosette stage is &lt;0.35% and the N:S ratio is &gt;9.6, the plant may be S‐deficient, and timely supplementary S fertilization measures may be beneficial to canola crop yield.

A Review of Drip Irrigation’s Effect on Water, Carbon Fluxes, and Crop Growth in Farmland

The substantial depletion of freshwater reserves in many pivotal agricultural regions, attributable to the dual pressures of global climate change and the excessive extraction of water resources, has sparked considerable apprehension regarding the sustainability of future food and water security. Drip irrigation, as an efficient and precise irrigation method, reduces water loss caused by deep percolation, soil evaporation, and runoff by controlling the irrigation dosage and frequency, thus improving the efficiency of water resource utilization. Studies have shown that compared with traditional irrigation methods, drip irrigation can significantly decrease water consumption, optimize the water–energy relationship by reducing soil evaporation, increase the leaf area index, and promote crop growth, thereby enhancing plant transpiration. Although more wet and dry soil cycles from drip irrigation may increase soil CO2 emissions, it also enhances crop photosynthesis and improves crop net ecosystem productivity (NEP) by creating more favorable soil moisture conditions, indicating greater carbon sequestration potential. The advantages of drip irrigation, such as a short irrigation cycle, moderate soil moisture, and obvious dry and wet interfaces, can improve a crop’s leaf area index and biomass accumulation, improve root dynamics, promote the distribution of photosynthetic products to the aboveground parts, and thus enhance crop yields. This study highlights the potential for the application of drip irrigation in arid regions where resource optimization is sought, providing strong technical support for the achievement of sustainable agricultural development. Future research needs to consider specific agricultural practices, soil types, and environmental conditions to further optimize the implementation and effectiveness of drip irrigation.

Numerical Simulation Study of Cavity Formation in Soil under Blast Load

The main applications of civil explosives in soils are soil compaction, mass excavation, and in situ pile creation. The suitability of explosives for each of these applications strongly depends upon the explosive properties and the soil properties. For those reasons, a reliable estimation or process simulation regarding cost efficiency and explosive work ability in the soil with known soil parameters is relevant. This paper presents a numerical simulation study of different types of soil (different amounts of gravel, sand, silt, and clay) under a blast load modeled using Ansys 2020 R1 Autodyn 2D hydrocode, with different types of explosives. The calculated results from the Ansys 2020 R1 Autodyn 2D and the experimental results obtained from the in situ cavity formation caused by blasting are presented. The Jones–Wilkins–Lee (JWL) equation of state parameters was calculated using EXPLO5 V7.01.01 supported by experimental data, while the soil and explosive properties were measured in laboratory and in situ.

Mechanized No-Tillage Planting with Maize Straw Mulching Improves Potato Yield and Water Use Efficiency in Arid Regions of Northwest China

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 mechanized no-tillage potato planting with corn straw mulch covering (JG), plastic film mulching (HM), and open flat planting (CK). The results showed that mechanical no-tillage with straw mulching significantly affected soil water content in the 0–100 cm soil layer, yield, and water use efficiency (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 the seedling stage (0.03~0.92 **) and positively correlated with the dry weight of stems and leaves at the tuber expansion stage and starch accumulation stage (0.74 **~0.95 **). It was negatively correlated with the number of branches at the tuber formation stage (−0.33~−0.88 **). Compared with CK, JG could significantly improve the water use efficiency of potatoes and reduce 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. When HM is applied in heavy soil areas, soil compaction can easily occur, which affects seedling emergence and reduces yield. At the same time, JG has strong adaptability to soil types and good yield stability. It can be seen that JG is a green and efficient mechanized potato cultivation technology suitable for dry farming areas.

Experimental Study of Soil Compaction with Proctor Standard Test Equipment

Soil is the surface layer of the earth which consists of minerals, organic materials, air, living things. Clay soil is one type of soil that is important in determining the bearing capacity of subgrade required for construction. The bearing capacity of the soil is obtained by compacting it, using the TS-365 Automatic Standard Proctor. Soil compaction is the process of removing air from the pores of the soil, and is effective for improving soil properties in order to increase the density (density) of the soil so that shear strength increases, soil settlement decreases, and soil permeability decreases. The standard proctor test uses 5 separate soil samples weighing 2 kg, with a mixture of 16%, 19%, 22%, 25% and 28% air respectively. The test results show that the soil obtained from the Pojok sub-district area. Mojoroto, East Java obtained the results of soil compaction data using a standard proctor test, it was obtained that the optimum dry volume weight of the soil was 1,630 gr/cm3 and the optimum water content was 32%. So that the results of soil testing in the laboratory can be used as a reference for controlling soil compaction in construction.

Adverse effects of Ca2+ on soil structure in specific cation environments impacting macropore-crack transformation

The traditional view of Na+ as harmful and Ca2+ as beneficial doesn't always apply in multi-cationic soil solutions. Initially, adding Ca2+ promotes Na+ leaching, reducing salinity, but excess Ca2+ becomes counterproductive. As Na+ leaches, the soil's Ca2+-Na+-Mg2+ mix shifts to Ca2+-K2+-Mg2+, Ca2+'s function changes, even causing the opposite effect. To investigate the complex mechanism of Ca2+ to Na+-Mg2+ and K+-Mg2+, we conducted an indoor soil column experiment using saline water (4 dS m−1) with different cation compositions [Na+-Ca2+-Mg2+ (NCM), Na+-Mg2+ (NM), K+-Ca2+-Mg2+ (KCM), K+-Mg2+ (KM)] and deionized water as the control (CK). The results showed that NM exhibited the highest crack volume, while KM had the greatest macropore volume, with NM having approximately 15 % more crack volume than KM. Notably, only NM displayed a more pronounced inclination towards pore anisotropy value of 0 when compared to CK. NCM and KCM had higher pore anisotropy values than NM and KM. KM and KCM had more cracks angled ranging from 45–90° than NM and NCM. KCM notably decreased transitional macropores < 5.5 mm in length compared to KM, with no significant difference (P > 0.05) observed in widths < 2.5 mm between KCM and KM. NM displayed the shallowest macropore distribution and the highest variability in macropore length among all treatments. Only NCM showed significantly reduced variability in both macropore length and width compared to CK. In summary, Ca2+ exhibited distinct action patterns on K+-Mg2+ and Na+-Mg2+. For specific soil types and cationic compositions, Ca2+ may not fully exert its amendment effects. However, Ca2+'s effect is soil-specific, necessitating comprehensive studies across varied soil types.

Distribution characteristics of selenium and influencing factors in the plant–soil system of an arid oasis

A total of 323 topsoil samples, 63 profile soil samples, and 55 plant root samples were collected from an oasis area on the eastern margin of the Tarim Basin in China and the selenium content and other physical and chemical indicators were analyzed. The results showed that the average selenium content in the surface soil was 0.15 mg/kg, which was lower than the national background value, and only about 4% of the surveyed land area was classified as rich in selenium. The vertical distribution of selenium was characterized by surface accumulation. The organic carbon and clay content were positively correlated and the pH levels negatively correlated with the selenium content. Soil type had little effect on selenium content, though the selenium levels in Anthrosols and Gleysols were relatively high. The selenium content for cultivated land and garden soil was higher than for other land use types. The enrichment of selenium in plant roots was highest for Apocynum venetum L., followed by Pulicaria dysenterica (L.). Bernh., Populus euphratica Olive, Tamarix chinensis Lour., Phragmites australis (Cav.) Trin. ex Steud, and Pyrus bretschneideri Rehder. Correlation analysis revealed that the enrichment of selenium in the soil was mainly controlled by supergenesis in conjunction with long-distance migration and deposition. Overall, this study provides useful information for the rational development and utilization of regional land resources.

Large-scale assessment of characteristic plant species on Eurasian saline and alkaline soda ecosystems

From an ecological standpoint, saline and alkaline habitats are considered as extreme environments for vascular plants because salinity and alkalinity serve as primary structuring factors that significantly influence the species richness of vegetation cover. The non-alkaline salinity stress on plants primarily results from interactions of NaCl, Na2SO4, and other neutral salts, whereas alkalinity stress is caused by NaHCO3 and Na2CO3, accompanied by an increase in pH. Some halophytes and salt-tolerant plants are well-adapted to such permanent abiotic stress. Surprisingly, they are able to survive and reproduce under environmental conditions of more than 200 mM NaCl concentration and are also able to live permanently in extreme conditions. The aim of this study was to identify characteristic and indicator plant species for permanently alkaline soda and non-alkaline saline wetland habitats, and to analyze the relationship between the chemical composition of water and the plant’s saturation index. Based on the obtained results we can conclude that plant species identified to live in high saline conditions may also grow under high alkaline conditions. Two groups were distinguished based on the salinity and alkalinity: “Saline group” includes all types of halophytes and halotolerant species, while “Soda group” includes obligate alkalophytes and alkalotolerant species. However, the diversity of plants in alkaline environment is bigger than in saline environment, and most of the halotolerant species grow in both alkaline soda and saline habitats. It is possible to identify three indicator species requiring alkaline soda habitats to live in (Aster tripolium, Puccinellia limosa, Suaeda pannonica) and three indicator species that dominantly grow in non-alkaline saline habitats (Juncus maritimus, Salicornia prostrata, Suaeda salsa). Different independent variables have been identified and analyzed to understand their influence on the species saturation index by calculating percentage of characteristic plant species of the entire region. It was identified that the plant saturation index has a significant positive relationship with the Mean Temperature of the Warmest Quarter, Topsoil Sand, and Clay fraction variables, and there is a significant negative relationship with the Solid Earth surface heat flow, as the heating can increase the extremity of the environment. Identification of indicator species of salinity and alkalization makes it possible to determine the type of soil, water bodies and habitats as a rapid biomonitoring method as a visual observation, without the use of expensive equipment and chemical laboratory tests.

Hydro-mechanical response of volcanic ash on removal of fines: Shear stiffness to critical state mechanics

Natural volcanic soils containing pumice particles are commonly found in Hokkaido, Japan, and this type of soil is prone to landslides, internal erosion, and liquefaction. Therefore, the purpose of this paper is to summarise the hydro-mechanical response of volcanic ash soil subjected to internal erosion using the modified erosion triaxial apparatus, based on the literature and additional investigations. The results of the study show that the rate of erosion and shear strain during the erosion process are influenced by initial density, stress state, and hydraulic gradient. Notably, anisotropic consolidation is experienced by specimens under seepage flow. Additionally, the removal of fines leads to a slight decrease in the grading state index. Moreover, suffosion increases the maximum shear modulus and Poisson’s ratio of the soil, while increasing seepage time stabilises the peak shear strength of eroded specimens. Furthermore, the critical state line does not change much with internal erosion. To sum up, this study offers valuable insights into the behaviour of volcanic ash soil subjected to internal erosion and provides an integrated interpretation of hydro-mechanical response of volcanic ash on removal of fines.