Soil Heterogeneity Research Articles

Initial microbiome and tree root status structured the soil microbial community discrepancy of the subtropical pine-oak forest in a large urban forest park.

Plant-microbe-soil interactions control over the forest biogeochemical cycling. Adaptive plant-soil interactions can shape specific microbial taxa in determining the ecosystem functioning. Different trees produce heterogeneous soil properties and can alter the composition of soil microbial community, which is relevant to the forest internal succession containing contrasting stand types such as the pine-oak forests. Considering representative microbial community characteristics are recorded in the original soil where they had adapted and resided, we constructed a soil transplant incubation experiment in a series of in situ root-ingrowth cores in a subtropical pine-oak forest, to simulate the vegetational pine-oak replacement under environmental succession. The responsive bacterial and fungal community discrepancies were studied to determine whether and how they would be changed. The pine and oak forest stands had greater heterogeneity in fungi composition than bacteria. Original soil and specific tree root status were the main factors that determined microbial community structure. Internal association network characters and intergroup variations of fungi among soil samples were more affected by original soil, while bacteria were more affected by receiving forest. Specifically, dominant tree roots had strong influence in accelerating the fungi community succession to adapt with the surrounding forest. We concluded that soil microbial responses to forest stand alternation differed between microbiome groups, with fungi from their original forest possessing higher resistance to encounter a new vegetation stand, while the bacteria community have faster resilience. The data would advance our insight into local soil microbial community dynamics during ecosystem succession and be helpful to enlighten forest management.

OPTIMAL LIMA BEAN PLOT SIZE

It is important to determine optimal experimental plot size in order to ensure accurate results and correct decision making. There are no studies of this nature for lima bean cultivation. As such, the aim of this study was to determine the optimal plot size to estimate lima bean yield in family farming and experimental areas, combining the number of treatments, repetitions, and accuracy levels. Experiments were conducted in two 12[Formula: see text]m × 16[Formula: see text]m plots, each subdivided into 192 basic units (BUs) measuring 1[Formula: see text]m2. Bean weight was assessed in each of the units (g). Smith’s index of soil heterogeneity and optimal plot size were estimated using the Modified Maximum Curvature Method and Hatheway’s Method. The index of soil heterogeneity was higher than 0.7 for all the variables analyzed. Plot size between 10[Formula: see text]m2 and 15[Formula: see text]m2 is considered efficient in estimating lima bean weight. These first estimated optimal plot sizes will allow researchers and farmers who work with the crop to obtain more robust yield estimates.

Characterisation of the heterogeneity of a sand specimen in triaxial compression using x-ray CT and representative elementary volumes

Standard laboratory tests, such as the triaxial test, are often considered to be element tests. But, when observing such a test, it becomes obvious that this assumption of homogeneity is far from accurate. The localisation of strain is often visible to the naked eye and becomes even more obvious when observed on the grain scale. Other variables, such as those describing the soil fabric, are expected to localise as well. In this work, two sand samples are analysed at different loading states regarding the heterogeneity of three soil variables: void ratio, coordination number and contact orientation anisotropy. For this purpose, the size of a Representative Elementary Volume (REV) is determined using three criteria: the convergence of the mean and variance of the variables with increasing element size as well as a χ2-test. The size of the REV is varying depending on the chosen variable but almost the same for the two specimens when related to the mean grain diameter d50. The REV is placed in a regular grid throughout the specimen and the three variables are determined for each REV. The stochastic as well as spatial heterogeneity is identified for each specimen. As one of the samples is analysed for different loading states throughout a triaxial test, the evolution of the soil heterogeneity is identified. A localisation of all three variables can be observed at the end of the triaxial test as well as a strong initial heterogeneity for both sand samples.

Soil Quality Indicators under Different Smallholder Managed Cropping and Landuse Practices in Abuja, Nigeria

There are limited reports about the impacts of smallholder-managed cropping and land-use practices (CLUPs) on soil quality, especially in developing countries. This study investigates the impact of six different Cropping Land Use Practices (CLUPs) on soil quality parameters in Abuja, Nigeria, focusing on sesame mono-cropping (SM), guinea corn mono-cropping (GCM), yam mono-cropping (YM), maize + yam mixed cropping (MYM), maize mono-cropping (MM), and natural forest (NF). The objectives are to determine Soil Organic Carbon (SOC), Total Nitrogen (TN), and pH values in the six CLUPs and assess differences under various CLUPs and soil depths. The study conducted in the University of Abuja Permanent Site, covers 11,000 hectares and analyzes soil samples from three replicate plots per CLUP, considering topsoil (0-15cm) and subsoil (20-30cm). The results indicate slightly acidic soils with low SOC and TN contents. Significant differences in SOC, TN, and C/N ratio are observed among cropping systems, with mixed cropping (MYM) promoting higher SOC. The C/N ratio is consistently low across CLUPs, indicating accelerated decomposition. While intra-plot soil heterogeneity is low, significant declines in soil quality indicators are noted under cropping systems compared to the natural forest. The study recommends site-specific, sustainable land management practices tailored to each cropping system. Encouraging organic matter additions, such as using animal and farmyard manure, is proposed to enhance soil fertility and reverse degradation trends. The findings contribute to understanding how diverse cropping practices impact soil quality, providing valuable insights for sustainable land management in the Abuja region.

Soil-structure interaction effects on out-of-plane seismic response and damage of masonry buildings with shallow foundations

A significant amount of damage and casualties induced by several strong-motion earthquakes which recently stroke South-East Mediterranean area is due to the major seismic vulnerability of residential buildings. In small villages and mid-size towns, those buildings very often consist of two- to four-story, unreinforced masonry (URM) structures not designed for earthquake resistance, with direct foundations usually corresponding to an in-depth extension of load-bearing walls. For such structures, especially when founded on soft soils, site amplification and soil-foundation-structure interaction (SFSI) can significantly affect the seismic performance; conversely, such phenomena should be investigated through methods that allow a trade-off between accuracy and computational effort, hence encouraging their implementation in engineering practice. This paper provides a comprehensive updated description of the studies carried out in the last years by the authors, which are based on both linear and nonlinear, parametric, dynamic analyses of complete soil-foundation-structure (SFS) models representative of existing residential building configurations on different soils. Specifically, the parametric study investigated SFS models with different masonry types, aspect ratios, and code-conforming homogeneous and heterogeneous soil profiles. The methodology and analysis results allowed for reaching the following objectives: (i) predicting the elongation of the fundamental period and the variation of equivalent damping of the SFS system with respect to fixed-base conditions, through a simplified approach based on an equivalent simple oscillator; and (ii) estimating the probability of exceeding increasing damage levels associated with out-of-plane overturning of URM walls, through fragility functions that take into account SFS interaction. The effectiveness of these simplified tools was successfully validated against well-documented case studies, at the scales of both single instrumented buildings and urban area.

Experiment and Simulation of Groundwater Salt Transport Based on Different Contact Relations in Heterogeneous Soil Layers

With the expansion of reserve cultivated land resources in coastal saline–alkali areas, the problem of soil salinization is becoming more and more prominent. In order to reveal the influence of different soil media and contact modes on soil water movement, a two-domain Hydrus-3D model was established to verify its performance in heterogeneous soil layers, and the characteristics of water, salt, and wet peak transport of surface soil and sandy soil under horizontal contact and inclined contact conditions were analyzed through experiments and simulations. The measured data show that in horizontal contact mode, probe 3 and probe 2 are close to the interface of the two layers of soil, and their maximum values are measured in about 60 min. The time difference between probe 1 and probe 2 is about 15 min. In the inclined contact mode, probe 4 in the topsoil reached 45% in 10 min and remained stable; the peak lag time of probes 3 and 2 was 10 min, and the peak lag time of probes 2 and 1 was 15 min; the water in the surface soil gradually increases and then stabilizes; and the water in the sand soil is similar to the normal curve. The salt characteristics in the surface soil are similar to the normal curve, while the salt characteristics in the sandy soil gradually increase and then stabilize. The simulation results show that the water content in the topsoil is more than 40%, and the maximum water content in the center of the sand is only 36.9%, which is roughly the same as the experimental results. The results showed that the Hydrus-3D model had a good simulation effect on the groundwater salt transport of heterogeneous soil under two contact methods. The RMSE value and E value are close to 0 and 1, respectively, indicating that the simulation has good feasibility and can be applied to the simulation of water and salt transport processes under different contact modes of soil media.

DEM simulation of subsoiling for soil disturbance as affected by soil layering and working speed

Although the discrete element method (DEM) has been used to simulate soil-subsoiler interactions, the degree of soil heterogeneity along the depth profile has not been well documented. Models of a layered soil structure were developed using the DEM, and they were a heterogeneous soil model (HeS Model) with seven layers, a semi-heterogeneous soil model (SHeS Model) with three layers, and a homogeneous soil model (HoS Model) with one layer. The models simulated the soil dynamic behavior resulting from a subsoiler travelling at speeds from 2 to 6 km h−1. Simulations were compared with field measurements. Results showed that soil particles flow in front of the subsoiler formed three distinguished zones: “pushing”, “rising”, and “passive” zones, with the “pushing” zone having the highest particle velocities. Compared with the measurements, the overall relative errors of the simulated soil disturbance widths (W) within the range of working speed from 2 to 6 km h−1 were below 20 % for all three models. Whereas the overall relative errors of the simulated soil surface flatness (F) were larger than 20 % for all three models. These suggest that all three models are suitable for predicting W, but not for predicting F, if a 20 % relative error was used as the judging criterion. The overall relative errors of the simulated elevated soil area (A) were 11.1 %, 18.8 %, and 25.7 % for the HeS, SHeS, and HoS Models, respectively, which suggest that HeS Model had the highest accuracy in predicting A. This study provides critical information for determining the degree of soil heterogeneity in simulations of the dynamics of soil-subsoiler interaction.

Experimental study on mechanical behavior deterioration of undisturbed loess considering freeze-thaw action

To solve the problem that the mechanical behavior of undisturbed loess in seasonally frozen soil area is affected by freeze-thaw action, triaxial shear tests of undisturbed loess under freeze-thaw condition were carried out. The results show that the mechanical properties of undisturbed loess are greatly affected by factors including freeze-thaw process, water content, natural density and confining pressure. Freeze-thaw action has a certain impact on the failure surface shape and stress-strain curve. Before and after freeze-thaw, the shape of the shear failure surface is complex, including single oblique failure surface, double oblique failure surface, vertical failure surface, X-shaped failure surface, bulging failure, etc. And under the conditions of low water content, low confining pressure and high dry density, the stress-strain curve tends to be softened. Conversely, the curve tends to harden. Freeze-thaw action can make the stress-strain curve transition from softening to hardening. In addition, the freeze-thaw action significantly weakens the failure strength, shear strength, cohesion, initial tangent modulus and failure ratio of undisturbed soil, but does not change the internal friction angle obviously. Also, the heterogeneity of natural soil is also an important factor affecting the mechanical parameters, failure surface shape and stress-strain curve of undisturbed loess.

InSAR Monitoring Using Persistent Scatterer Interferometry (PSI) and Small Baseline Subset (SBAS) Techniques for Ground Deformation Measurement in Metropolitan Area of Concepción, Chile

InSAR capabilities allow us to understand ground deformations in large metropolitan areas, this is key to assessing site conditions in areas in an inherently expanding context. The multi-temporal interferometry of SAR data records ground surface displacement velocities over large metropolitan areas, identifying anomalous and potential geological hazards. The metropolitan city of Concepción, Chile, is an alluvial basin in one of the world’s most seismically active subduction zones, where many subduction earthquakes have occurred throughout history. In this study, we monitored the deformations of the ground surface in the metropolitan area of Concepción using two interferometric techniques, the first being Persistent Scatterer Interferometry (PSI) and the second, the Small Baseline Subset (SBAS) technique. To do this, we have used the same Sentinel-1 dataset, obtaining ground movement rates between 2019 and 2021. The velocities were aligned with the GNSS station available in the area. Ground deformation patterns show local deformations depending on factors such as soil type and heterogeneity, and regional deformations due to geographical location in the subduction area. Our results highlight the similarity of the deformation rates obtained with different processing techniques and have also allowed us to identify areas of deformation and compare them to site conditions. These results are essential to evaluate ground conditions and contribute to urban planning and risk management in highly seismic areas.

Development of Soil Fertility Index Using Machine Learning and Visible-Near-Infrared Spectroscopy

An accurate assessment of soil fertility is crucial for monitoring environmental dynamics, improving agricultural productivity, and achieving sustainable land management and utilization. The inherent complexity and spatiotemporal heterogeneity of soils result in significant challenges in soil fertility assessment. Therefore, this study focused on developing a rapid, economical, and precise approach to evaluate soil fertility through the application of visible-near-infrared spectroscopy (VNIR). To achieve this, we utilized the Land Use and Cover Area Frame Survey (LUCAS) dataset and employed a variety of prediction models, including partial least squares regression, support vector machines (SVMs), random forest, and convolutional neural networks, to estimate various soil properties and overall soil fertility. The results showed that the SVM model had the highest prediction accuracy, particularly for clay content (coefficient of determination (R2) = 0.79, ratio of performance to interquartile range (RPIQ) = 3.04), pH (R2 = 0.84, RPIQ = 4.54), total nitrogen (N) (R2 = 0.80, RPIQ = 2.40), and cation exchange capacity (CEC) (R2 = 0.83, RPIQ = 3.16). A soil fertility index (SFI) was developed based on factor analysis, integrating nine essential soil properties: clay content, silt content, sand content, pH, carbonate content, N, soluble phosphorus, soluble potassium, and CEC. We compared direct and indirect prediction models for estimating SFI and found that both models showed high accuracy (mean value of R2 = 0.80, mean value of RPIQ = 2.21). Additionally, SFI was classified into five classes to provide insights for precision agriculture. The kappa coefficient was 0.63, which indicated that the SFI evaluation results between VNIR and chemical analysis were relatively consistent. This study provides a theoretical foundation of real-time soil fertility monitoring for the optimization of agricultural practices.

Multiple spatial scales of bacterial and fungal structural and functional traits affect carbon mineralization.

Studying the functional heterogeneity of soil microorganisms at different spatial scales and linking it to soil carbon mineralization is crucial for predicting the response of soil carbon stability to environmental changes and human disturbance. Here, a total of 429 soil samples were collected from typical paddy fields in China, and the bacterial and fungal communities as well as functional genes related to carbon mineralization in the soil were analysed using MiSeq sequencing and GeoChip gene microarray technology. We postulate that CO2 emissions resulting from bacterial and fungal carbon mineralization are contingent upon their respective carbon consumption strategies, which rely on the regulation of interactions between biodiversity and functional genes. Our results showed that the spatial turnover of the fungal community was 2-4 times that of the bacterial community from hundreds of meters to thousands of kilometres. The effect of spatial scale exerted a greater impact on the composition rather than the functional characteristics of the microbial community. Furthermore, based on the establishment of functional networks at different spatial scales, we observed that both bacteria and fungi within the top 10 taxa associated with carbon mineralization exhibited a prevalence of generalist species at the regional scale. This study emphasizes the significance of spatial scaling patterns in soil bacterial and fungal carbon degradation functions, deepening our understanding of how the relationship between microbial decomposers and soil heterogeneity impacts carbon mineralization and subsequent greenhouse gas emissions.

The study on the effect of mercury pollution on soil microorganisms around mercury mining area

In order to further explore the effects of soil mercury pollution on soil microbial diversity and community structure, soil samples were randomly collected from 2 m, 20 m, 30 m, 500 m and 650 m periphery of Wanshan mining area, as 5 different treatments. Each treatment had 4 replicates. Soil microbial DNA was extracted from 20 soil samples, and then high-throughput sequencing technology was used to analyse the structure and distribution of bacterial and fungal communities. The results showed that the number of bacterial and fungal communities in T0–T30 treatments was significantly larger than that in T500–T650 treatments at order, family and genus level. Whatever, the number of uniquely distributed bacterial and fungal communities among 4 replicates soil samples was quite different at order, family and genus level. The results of the effect on the microbial community structure showed that there were both the same dominant bacterial and fungal communities, and the different dominant bacterial and fungal communities at any classification level, moreover, the number of same dominant bacterial and fungal communities was larger than that of different dominant bacterial and fungal communities. The results of relationship between soil environment factors and bacterial and fungal community structure showed that distance (Hg2+), EC and pH had a high correlation with community structure, especially the distance factor, that is, the content of mercury in soil had the highest effects on community structure. The internal heterogeneity of soil caused significant differences in bacterial and fungal community structure, and the emergence of dominant bacterial and fungal communities was a manifestation of better adaptability to long-term mercury stress and other stresses in soil, which will provide a scientific reference for further exploring the mechanism of mercury enrichment between microorganisms and plants.

Remote Sensing and Kriging with External Drift to Improve Sparse Proximal Soil Sensing Data and Define Management Zones in Precision Agriculture

The precision agriculture scientific field employs increasingly innovative techniques to optimize inputs, maximize profitability, and reduce environmental impacts. Therefore, obtaining a high number of soil samples to make precision agriculture feasible is challenging. This data bottleneck has been overcome by identifying sub-regions based on data obtained through proximal soil sensing equipment. These data can be combined with freely available remote sensing data to create more accurate maps of soil properties. Furthermore, these maps can be optimally aggregated and interpreted for soil heterogeneity through management zones. Thus, this work aimed to create and combine soil management zones from proximal soil sensing and remote sensing data. To this end, data on electrical conductivity and magnetic susceptibility, both apparent, were measured using the EM38-MK2 proximal soil sensor and the contents of the thorium and uranium elements, both equivalent, via the Medusa MS1200 proximal soil sensor for a 72-ha grain-producing area in São Paulo, Brazil. The proximal soil sensing attributes were mapped using ordinary kriging (OK). Maps were also made using kriging with external drift (KED), and the proximal soil sensor attributes data, combined with remote sensing data, such as Landsat-8, Aster, and Sentinel-2 images, in addition to 10 terrain covariables derived from the digital elevation model Alos Palsar. As a result, three management zone maps were produced via the k-means clustering algorithm: using data from proximal sensors (OK), proximal sensors combined with remote sensors (KED), and remote sensors. Seventy-two samples (0–10 cm in depth) were collected and analyzed in a laboratory (1 sample per hectare) for concentrations of clay, calcium, organic carbon, and magnesium to assess the capacity of the management zone maps created using analysis of variance. All zones created using the three data groups could distinguish the different treatment areas. The three data sources used to map management zones produced similar map zones, but the zone map using a combination of proximal and remote data did not show an improvement in defining the management zones, and using only remote sensing data lowered the significance levels of differentiating each zone compared to the OK and KED maps. In summary, this study not only underscores the global applicability of proximal and remote sensing techniques in precision agriculture but also sheds light on the nuances of their integration. The study’s findings affirm the efficacy of these advanced technologies in addressing the challenges posed by soil heterogeneity, paving the way for more nuanced and site-specific agricultural practices worldwide.

Effects of random heterogeneity of soil on VH failure envelopes of the torpedo anchor

ABSTRACTTorpedo anchor is one offshore anchoring which has been gaining popularity recently for floating structures. The torpedo anchor was expected to resist the environmental loading transferred from the floating platform. Thus, the understanding of the holding capacity of torpedo anchors under vertical and horizontal combined loading is the key concern of its design. Nonetheless, most of the previous studies are deterministic without considering the common existing random heterogeneity nature of marine soil. In light of this situation, this paper reports a large deformation random finite element study under the framework of the Monte Carlo method. VH failure envelopes of torpedo anchors in heterogeneous soil were obtained by conducting simulations of continuous extraction procedures along different directions. Furthermore, the strain-softening behaviour of the soil was also accounted for considering the server deformation of the soil. The results show that both the size and shape of the VH failure envelope are significantly affected by random heterogeneity of soil. A series of VH failure envelopes of various probabilities of failure was thus given to guide the design. Results in this paper may be constructive for the safety design of the torpedo anchor.

Contribution of HVSR, MASW, and geotechnical investigations in seismic microzonation for safe urban extension: A case study in Ghabt Admin (Agadir), western Morocco

Ghabt Admin, located in western Morocco, is prone to seismic activity and site effects due to its position within an alluvial basin situated between two faulted mountain belts. The region has experienced several devastating earthquakes, including the 1960 Agadir earthquake that resulted in the loss of 12,000 lives and the destruction of over 75% of the city. Moreover, the area has recently undergone rapid urbanization, necessitating the implementation of seismic studies to make informed decisions regarding land use. This study aims to conduct the first seismic microzonation and site characterization studies by using HVSR, 1D-MASW, and geotechnical investigations. The datasets consist of 80 microtremors, 15 1D-MASW profiles, detailed geological observations, boreholes, and soil/rock identification tests. Due to challenges related to anthropogenic sources and soil heterogeneities, only 31 H/V measurements met the SESAME criteria. The HVSR results indicate the following: (i) the predominant peak frequency (f0) ranges from 1.4 to 15.7 Hz, with lower values (1.4–3 Hz) observed in the Oued Issen alluvial fans and the sand dune area, while moderate to high values (4–15.7 Hz) are found in the lacustrine limestone and Tagragra’s dome. (ii) The amplitude peak frequency (A0) ranges from 2 to 7.7, with higher values observed in the southwestern zone and certain parts of the glacis-fans zone, particularly in the Oued Issen zone. (iii) The seismic vulnerability index (Kg) ranges from 0.28 to 39.5. The Oued Issen area, which is composed of recent unconsolidated deposits and affected by the Oued Issen fault, exhibits high Kg values. Analysis of HVSR curve typology reveals complex geology. The VS30 map shows VS values ranging from 179 m/s to 830 m/s, classifying the study area into soil classes A, B, and C according to Eurocode 8. Furthermore, the 1D-MASW results are compatible with the HVSR results and the distribution of the geological units.

Suaeda salsa spectral index for Suaeda salsa mapping and fractional cover estimation in intertidal wetlands

Suaeda Salsa (S. salsa), with short and red-purplish plants, is a typical pioneer saltmarsh species in the intertidal wetlands of temperate East Asia. It has important ecological, economic, and recreational values. In the past few decades, S. salsa has severely degraded in coastal China, which has brought widespread attention from regional and local governments. As a result, extensive S. salsa restoration projects have been initiated in recent years. It is urgently needed to develop satellite-based methods for both S. salsa mapping and fractional cover (FC) estimation because degradation and recovery of S. salsa are manifested by changes in both area and plant cover. However, accurate mapping and FC estimation of S. salsa are challenging because (1) S. salsa in intertidal areas have low FC and (2) heterogeneous soil backgrounds in wetlands greatly impact the spectral reflectance observed by satellites. To address these issues, this study proposed a new Suaeda Salsa Spectral Index (SSSI) to support accurate detection and FC estimation of S. salsa. The SSSI was designed based on the laboratory spectral measurements by considering variations in wetland soil moisture and by taking advantage of the reddish color of S. salsa. It consists of two components, one of which utilized blue, green and red bands to separate S. salsa from green vegetation, and the other component utilized a modification of the Soil Adjusted Vegetation Index (SAVI) to reduce the impact of soil background and maintain a linear relationship with S. salsa FC. SSSI was then applied on Sentinel-2/GF-1 images over the Yellow River Delta (YRD) and Liao River Delta (LRD), China. Based on SSSI, a simple thresholding approach was used to identify S. salsa, and a linear regression model was used to estimate FC. With reference datasets provided from field investigations, Unmanned Aerial Vehicle multispectral images and high-spatial resolution satellite images, our results show that the SSSI was able to detect low-coverage S. salsa (FC > 20 % in YRD and FC > 10 % in LRD), and the S. salsa maps had an overall accuracy over 94%. The SSSI-FC models achieved good estimation accuracies (R2 = 0.77 ∼ 0.86, RMSE = 7.55 % ∼ 9.79 %). Compared to the Normalized Difference Vegetation Index (NDVI) and SAVI, SSSI alleviated the impacts from soil backgrounds and provided better S. salsa FC estimations, particularly for low-coverage S. salsa. SSSI has great potential in supporting continuous monitoring of S. salsa dynamics and evaluating the effectiveness of S. salsa restoration projects.

Analytical plasticity‐based model for soil–structure interaction of lumped system on heterogeneous soil media

AbstractIn the present study, an analytical approach is developed for the soil–structure interaction for the linear, eq. linear and elastic‐perfectly plastic layered soil strata. The amplification factor is calculated at the top of a lumped structure incorporating layered soil, foundation, and super‐structure deformation. The equation of motion of the system under the normalized earthquake excitation is solved using the direct integration method. MATLAB script is developed to carry out the parametric study, and nonlinear time history analysis is performed. The present methodology is compared with the finite element model (FEM), which shows good agreement. The computational time is much less than the FEM method. A parametric study is carried out in terms of soil heterogeneity, mass ratio, slenderness ratio, excitation frequency, and material model. The results indicate that due to the heterogeneity of the soil, the response of the structure is increased significantly; with the increase in the mass ratio, the amplification factor decreases with excitation frequency up to resonance, and the effect of mass ratio is negligible at the higher frequency range; with the increase in slenderness ratio, the amplification factor increases up to resonance, however, at higher frequency ranges there is no effect of slenderness ratio.

Assessing the structure and diversity of fungal community in plant soil under different climatic and vegetation conditions

IntroductionUnderstanding microbial communities in diverse ecosystems is crucial for unraveling the intricate relationships among microorganisms, their environment, and ecosystem processes. In this study, we investigated differences in the fungal community structure and diversity in soils from two contrasting climatic and vegetation conditions: the Xinjiang western China plateau and the Fujian southeastern coastal province.MethodsA total of 36 soil samples collected from two climatic regions were subjected to high-throughput ITS gene sequencing for fungal community analysis. In conjunction soil physicochemical properties were assessed and compared. Analyses included an examination of the relationship of fungal community structure to environmental factors and functional profiling of the community structure was using the FUNGuild pipeline.ResultsOur data revealed rich fungal diversity, with a total of 11 fungal phyla, 31 classes, 86 orders, 200 families, 388 genera, and 515 species identified in the soil samples. Distinct variations in the physicochemical properties of the soil and fungal community structure were seen in relation to climate and surface vegetation. Notably, despite a colder climate, the rhizosphere soil of Xinjiang exhibited higher fungal (α-)diversity compared to the rhizosphere soil of Fujian. β-diversity analyses indicated that soil heterogeneity and differences in fungal community structure were primarily influenced by spatial distance limitations and vegetation type. Furthermore, we identified dominant fungal phyla with significant roles in energy cycling and organic matter degradation, including members of the Sordariomycetes, Leotiomycetes, Archaeosporomycetes, and Agaricomycetes. Functional analyses of soil fungal communities highlighted distinct microbial ecological functions in Xinjiang and Fujian soils. Xinjiang soil was characterized by a focus on wood and plant saprotrophy, and endophytes, whereas in Fujian soil the fungal community was mainly associated with ectomycorrhizal interactions, fungal parasitism, and wood saprotrophy.DiscussionOur findings suggest fungal communities in different climatic conditions adapt along distinct patterns with, plants to cope with environmental stress and contribute significantly to energy metabolism and material cycling within soil-plant systems. This study provides valuable insights into the ecological diversity of fungal communities driven by geological and environmental factors.

Linking horizontal crosshole GPR variability with root image information for maize crops

AbstractNon‐invasive imaging of processes within the soil–plant continuum, particularly root and soil water distributions, can help optimize agricultural practices such as irrigation and fertilization. In this study, in‐situ time‐lapse horizontal crosshole ground penetrating radar (GPR) measurements and root images were collected over three maize crop growing seasons at two minirhizotron facilities (Selhausen, Germany). Root development and GPR permittivity were monitored at six depths (0.1–1.2 m) for different treatments within two soil types. We processed these data in a new way that gave us the information of the “trend‐corrected spatial permittivity deviation of vegetated field,” allowing us to investigate whether the presence of roots increases the variability of GPR permittivity in the soil. This removed the main non‐root‐related influencing factors: static influences, such as soil heterogeneities and rhizotube deviations, and dynamic effects, such as seasonal moisture changes. This trend‐corrected spatial permittivity deviation showed a clear increase during the growing season, which could be linked with a similar increase in root volume fraction. Additionally, the corresponding probability density functions of the permittivity variability were derived and cross‐correlated with the root volume fraction, resulting in a coefficient of determination (R2) above 0.5 for 23 out of 46 correlation pairs. Although both facilities had different soil types and compaction levels, they had similar numbers of good correlations. A possible explanation for the observed correlation is that the presence of roots causes a redistribution of soil water, and therefore an increase in soil water variability.

Unravelling mixed sources of polycyclic aromatic hydrocarbons (PAH) in urban soils by visual characterization of anthropogenic substrates and coal particles, 71 PAH and alkylated PAH patterns

The identification of polycyclic aromatic hydrocarbon (PAH) sources in heterogeneous urban soils containing pyrogenic and/or petrogenic anthropogenic substrates is a common task for risk assessment. Here, for the first time, the results of source identification using analysis of 71 PAH, alkylated PAH patterns and PAH Alkylation Index were related to visually identified and quantified anthropogenic substrates in 50 soil samples. Only the combination of chemical methods with visual characterization enabled the deeper understanding of varying alkylated PAH patterns used for source apportionment and their superimposition if multiple sources occur. Pyrogenic substrates show homogenic slope-shape PAH patterns despite large visual variety. Petrogenic substrates (bituminous coals), show prevailingly bell-shape patterns but pyrogenic patterns also occur, probably due to residues from industrial processes and/or sorption of other pyrogenic PAH. Superimposition of both PAH patterns within a sample results in intermediate patterns, which are determined by the abundance of substrates and their individual PAH contents. A discrepancy between the share of petrogenic substrates and petrogenic PAH was observed due to low-medium PAH contents from coals/tailings. This may lead to misinterpretations if only chemical source identification methods are applied. With increasing proportion of petrogenic PAH in the mixture, the intermediate V-shape pattern (later bell-shape) appears in lower molecular weight PAH and moves progressively to higher molecular weight PAH. ∑71 PAH contents vary from 1.77 to 326.5 mg/kg (median 26.5 mg/kg). Non-EPA PAH measured include highly toxic ∑4 dibenzopyrene isomers (0.045–6.23 mg/kg, median 0.79 mg/kg) and 7H-benzo[c]fluorene (0.008–1.57 mg/kg, median 0.12 mg/kg). Most common anthropogenic substrates are bottom ashes, slags, bituminous coals/tailings and coke/coke ash. The PAH Alkylation Index identifies reliably samples dominated by either petrogenic (<0.4) or pyrogenic (>0.9) PAH, independently of the PAH content. Mixed or primarily pyrogenic PAH sources (0.4–0.9) need further investigations, like the presented combination of methods, which enables a reliable source apportionment.