Soil Heterogeneity Research Articles

Spectral Heterogeneity Analysis and Soil Organic Matter Inversion across Differences in Soil Types and Organic Matter Content in Dryland Farmland in China

Soil organic matter (SOM) plays an important role in agricultural production and arable land quality improvement. Hyperspectral technology enables frequent surveys over large areas. In this study, we explored the spectral heterogeneity of differences in soil types and SOM content, and proposed a method for measuring SOM content in large areas using spectroscopy. The results indicate regional variations in factors affecting soil spectral absorption peaks, with noticeable latitudinal disparities. The first-order differential partial-least-squares method provided the best prediction for the SOM inversion. The coefficient of determination (R2) for the SOM inversion model was 0.93, and the root mean square error (RMSE) was 3.42, with an 8.49 g/kg difference in the SOM content. When the difference in SOM content fell between 8 and 15 g/kg, the inversion effect model performed best. The optimal model R2 exceeded 0.95, and the RMSE was less than 5. The comprehensive analysis showed that the organic matter content was an important factor affecting the SOM content estimate and must be considered in the real process. In addition, it is crucial to categorize soil samples on the basis of distinct soil types while maintaining a consistent range of SOM content within the same soil type, ideally between 8 and 15 g/kg. Subsequently, the first-order differential partial least squares method is applicable. These results are expected to contribute to the acquisition of high-quality information on variations in the SOM of complex large-scale areas.

Investigating multiscale meteorological controls and impact of soil moisture heterogeneity on radiation fog in complex terrain using semi-idealised simulations

Abstract. Coupled surface–atmosphere high-resolution mesoscale simulations were carried out to understand meteorological processes involved in the radiation fog life cycle in a city surrounded by complex terrain. The controls of mesoscale meteorology and microscale soil moisture heterogeneity on fog were investigated using case studies for the city of Ōtautahi / Christchurch, New Zealand. Numerical model simulations from the synoptic to microscale were carried out using the Weather Research and Forecasting (WRF) model and the Parallelised Large-Eddy Simulation Model (PALM). Heterogeneous soil moisture, land use, and topography were included. The spatial heterogeneity of soil moisture was derived using Landsat 8 satellite imagery and ground-based meteorological observations. Nine semi-idealised simulations were carried out under identical meteorological conditions. One contained homogeneous soil moisture of about 0.31 m3 m−3, with two other simulations of halved and doubled soil moisture to demonstrate the range of soil moisture impact. Another contained heterogeneous soil moisture derived from Landsat 8 imagery. For the other five simulations, the soil moisture heterogeneity magnitudes were amplified following the observed spatial distribution to aid our understanding of the impact of soil moisture heterogeneity. Analysis using pseudo-process diagrams and accumulated latent heat flux shows significant spatial heterogeneity of processes involved in the simulated fog. Our results showed that soil moisture heterogeneity did not significantly change the general spatial structure of near-surface fog occurrence, even when the heterogeneity signal was amplified and/or when the soil moisture was halved and doubled. However, compared to homogeneous soil moisture, spatial heterogeneity in soil moisture can lead to changes in fog duration. These changes can be more than 50 min, although they are not directly correlated with spatial variations in soil moisture. The simulations showed that the mesoscale (10 to 200 km) meteorology controls the location of fog occurrence, while soil moisture heterogeneity alters fog duration at the microscale on the order of 100 m to 1 km. Our results highlight the importance of including soil moisture heterogeneity for accurate spatiotemporal fog forecasting.

Mechanisms of increased small nanoplastic particle retention in water-saturated sand media with montmorillonite and diatomite: Particle sizes, water components, and modelling

The processes by which small nanoplastics (NPs) accumulate in soil are unclear. To clarify the different deposition processes that affect small NPs (< 30 nm) compared to larger NPs in the soil environment, due to their interaction with clays as major soil components, the transport behavior of two-sized NPs (20 and 80 nm) with two clays (diatomite (Diat) and montmorillonite (Mont)) in NaCl and CaCl2 solutions were investigated in water-saturated quartz sand columns. The experimental results showed that more 20 nm NPs could enter the lattice structure of Diat than Mont in NaCl solution. This contributed to the stronger deposition of 20 nm NPs by Diat on sand, which was associated with a lower k1d/k1 value (obtained from two-site kinetic attachment model). In contrast, 80 nm NPs had a stronger reversible retention than 20 nm NPs with Mont, even though both sizes of NPs-Mont displayed a similar transportability. In CaCl2 solution, the larger NPs-Mont hetero-aggregates formed with a stronger suppressed depth of φmax based on Derjaguin-Landau-Verwey-Overbeek theory. Thus, Mont had a stronger transport inhibition than Diat for both NPs sizes, with a lower k1d/k1. These findings could benefit in predicting the size-based deposition of NPs in a heterogenous soil environment.

Fractal thermal conductivity of unsaturated soils considering pore heterogeneity

Accurately predicting the thermal conductivity of unsaturated soils is crucial for assessing and simulating the long-term environmental impact of subterranean engineering structures. This study presents a fractal thermal conductivity model for unsaturated soils that considers the influence of heterogeneous pore topology, water content and volumetric deformation. Based on the results from the scanning electron microscopy (SEM) and mercury intrusion-extrusion cyclic porosimetry (MIECP) tests on Shanghai clay and Kaolin, we introduce the pore-throat structure to describe the soil heterogeneity and deal with the coupling of solid-pore thermal properties through the mixing law at the pore scale. Together with the self-similar fractal law, the thermal conductivity model is upscaled from the pore scale to the representative element volume (REV) scale. During the process, heterogeneity factors are introduced to describe differences between local and bulk properties, such as porosity and saturation. Thermal property tests of Shanghai clay and Kaolin with varying porosities are then conducted to validate the proposed thermal conductivity model. Additionally, nineteen published datasets on thermal conductivity are also utilized to confirm the adaptability and robustness of the model. The results show that the proposed model predicts well the thermal conductivity of unsaturated soils. Moreover, when compared to existing models, the proposed model offers superior performance in describing the thermal properties of unsaturated soils.

Groundwater heavy metal(loid)s risk prediction based on topsoil contamination and aquifer vulnerability at a zinc smelting site

Groundwater pollution is a recurrent problem in abandoned non-ferrous metal smelting sites, and its severity is influenced by topsoil contamination, hydrogeological characteristics, and hydrogeochemical conditions. In such unique areas, traditional methods for evaluating groundwater pollution risk are biased, as the long production history of these sites have led to highly polluted and heterogeneous soil and groundwater. Herein, based on a typical lead-zinc smelting site, As, Pb, Zn, Cd, Mn, and Ni were found to be the predominant heavy metal (loid)s in groundwater, with respective exceedance rates of 44.4%, 50.0%, 72.2%, 88.9%, 88.9%, and 61.1%. Combined with the groundwater pollution characteristics, the representative hydrogeochemical factors were screened out to optimize the following aquifer vulnerability evaluation using the AHP-DRASTICH method. A comprehensive evaluation model (DI-NCPI) for groundwater pollution risk was established by combining the DRASTICH index (DI) obtained after optimization and the Nemerow comprehensive contamination index (NCPI) of topsoil. The fit between DI-NCPI and groundwater heavy metal (loid) pollution index reached 0.956, which laterally confirms that the model has some reference value. In terms of distribution, the high-risk and very high-risk zones were mainly concentrated in the zinc smelting system, located in the southeastern and central-western parts of the site. These areas have relatively high levels of topsoil contamination and aquifer vulnerability and require focused attention in site remediation. This research highlights the importance of combining topsoil contamination and aquifer vulnerability to evaluate groundwater pollution risk in smelting areas. It provides a more targeted reference for groundwater remediation strategies in abandoned smelting sites, as well as severely polluted industrial areas.

A new method for spatial three-dimensional prediction of soil heavy metals contamination

Soil heavy metals contamination are highly correlated to human health. It is crucial to employ three-dimensional heavy metals modeling and mapping for site assessment and remediation. However, current methods are limited due to the poor consideration of both spatial auto-correlation and stratified heterogeneity concurrently. The present study established a novel methodology 3D-MSN to model soil metals, encompassing autocorrelation and heterogeneity. In addition to considering in-strata correlation and between-strata heterogeneity like traditional methods, 3D-MSN accounted for the between-strata correlation to enhance the accuracy of prediction. A former agrochemical plant was used as a case to validate the superiority of the 3D-MSN method over traditional approaches. The accuracy of different methods was evaluated using mean absolute error (MAE) and root-mean-square error (RMSE), through leave-one-out cross-validation. Results demonstrated significant spatial autocorrelation and stratified heterogeneity for the presence of As and Cu in soil. 3D-MSN exhibited the lowest MAEs (2.424 mg/kg for As, 4.863 mg/kg for Cu) and RMSEs (3.439 mg/kg, 7.279 mg/kg) compared to 3D-ordinary kriging (MAEs (2.949 mg/kg, 6.482 mg/kg) and RMSEs (3.890 mg/kg, 8.364 mg/kg)) and 3D-stratified kriging (MAEs (2.571 mg/kg,5.184 mg/kg) and RMSEs (3.570 mg/kg, 7.412 mg/kg)). 3D-MSN also accounted for estimation uncertainties. Considering autocorrelation and stratified heterogeneity, 3D-MSN presented superior performance. This research contributes to advancing the field of three-dimensional heavy metal modeling and provides valuable insights for site assessment and remediation efforts.

Mechanism of seismic liquefaction for heterogeneous soil

In addition to inducing uncertainty in the predicted response, natural spatial variability of soil properties affects the mechanical response of geotechnical structures. When a failure surface is involved in the response, this surface can deviate from its theoretical location to pass through weaker zones of material. For the case of seismically induced soil liquefaction, it has been found that a larger amount of excess pore water pressure is generated in a soil exhibiting small-scale variability of its properties than in the corresponding uniform soil having geomechanical properties equal to the average properties of the heterogeneous soil. An explanation for this important phenomenon is provided in this paper based on the results of centrifuge experiments and numerical simulations of heterogeneous and homogeneous saturated soil deposits subjected to seismic loads. It is demonstrated, based on a detailed analysis of the results, that partial drainage during the earthquake, consisting of pore water inflow from loose soil zones that liquefy first toward surrounding dense areas, may trigger softening of dilative soils. The water inflow effects in terms of volumetric strains leading to reduced cyclic resistance of dense sands are compared with results of specially designed cyclic triaxial tests reported by other researchers.

Response of Organic Carbon Mineralization to Nitrogen Addition in Micro-aerobic and Anaerobic Layers of Paddy Soil

In field conditions, a micro-aerobic layer with 1 cm thickness exists on the surface layer of paddy soil owing to the diffusion of dissolved oxygen via flooding water. However, the particularity of carbon and nitrogen transformation in this specific soil layer is not clear. A typical subtropical paddy soil was collected and incubated with13C-labelled rice straw for 100 days. The responses of exogenous fresh organic carbon(13C-rice straw) and original soil organic carbon mineralization to nitrogen fertilizer addition[(NH4)2SO4]in the micro-aerobic layer(0-1 cm) and anaerobic layer(1-5 cm) of paddy soil and their microbial processes were analyzed based on the analysis of 13C incorporation into phospholipid fatty acid(13C-PLFAs). Nitrogen addition promoted the total CO2 and 13C-CO2 emission from paddy soil by 11.4% and 12.3%, respectively. At the end of incubation, with the addition of nitrogen, the total soil organic carbon (SOC) and13C-recovery rate from rice straw in the anaerobic layer were 2.4% and 9.2% lower than those in the corresponding micro-aerobic layer, respectively. At the early stage(5 days), nitrogen addition increased the total microbial PLFAs in the anaerobic layer with a consistent response of bacterial and fungal PLFAs. However, there was no significant effect from nitrogen on microbial abundance in the micro-aerobic layer. Nitrogen addition had no significant impact on the abundance of total 13C-PLFAs in the micro-aerobic and anaerobic layers, but the abundance of 13C-PLFAs for bacteria and fungi in the micro-aerobic layer was decreased dramatically. At the late stage(100 days), the effect of nitrogen addition on microbial PLFAs was consistent with that at the early stage. The abundances of total, bacterial, and fungal 13C-PLFAs were remarkably increased in the anaerobic layer. However, the abundance of 13C-PLFAs in the micro-aerobic layer showed no significant response to nitrogen addition. During the incubation, the content of NH4+-N in the anaerobic soil layer was higher than that in the micro-aerobic soil layer. This indicates that nitrogen addition increased microbial activity in the anaerobic soil layer caused by the higher NH4+-N concentration, as majority of microorganisms preferred to use NH4+-N. Consequently, the microbial utilization and decomposition of organic carbon in the anaerobic soil layer were accelerated. By contrast, richer available N existed in the form of NO3--N in the micro-aerobic soil layer owing to the ammoxidation process. Thus, the shortage of NO3--N preference microorganisms in the paddy soil environment prohibited the microbial metabolism of organic carbon in the micro-aerobic layer. As a whole, nitrogen fertilization enhanced organic carbon loss via microbial mineralization in paddy soil with a weaker effect in the micro-aerobic layer than that in the anaerobic layer, indicating the limited microbial metabolic activity in the surface micro-aerobic layer could protect the organic carbon stabilization in paddy soil. This study emphasizes the heterogeneity of paddy soil and its significant particularity of carbon and nitrogen transformation in micro-aerobic layers. Consequently, this study has implications for optimizing the forms and method for the application of nitrogen fertilizer in paddy cropping systems.

Machine learning prediction and interpretation of the impact of microplastics on soil properties

The annual microplastic (MP) release into soils is 4–23 times higher than that into oceans, significantly impacting soil quality. However, the mechanisms underlying how MPs impact soil properties remain largely unknown. Soil-MP interactions are complex because of soil heterogeneity and varying MP properties. This lack of understanding was exacerbated by the diverse experimental conditions and soil types used in this study. Predicting changes in soil properties in the presence of MPs is challenging, laborious, and time-consuming. To address these issues, machine learning was applied to fit datasets from peer-reviewed publications to predict and interpret how MPs influence soil properties, including pH, dissolved organic carbon (DOC), total P, NO3−-N, NH4+-N, and acid phosphatase enzyme activity (acid P). Among the developed models, the gradient boost regression (GBR) model showed the highest R2 (0.86–0.99) compared to the decision tree and random forest models. The GBR model interpretation showed that MP properties contributed more than 50% to altering the acid P and NO3−-N concentrations in soils, whereas they had a negligible impact on total P and 10–20% impact on soil pH, DOC, and NH4+-N. Specifically, the size of MPs was the dominant factor influencing acid P (89.3%), pH (71.6%), and DOC (44.5%) in soils. NO3−-N was mainly affected by the MP type (52.0%). The NH4+-N was mainly affected by the MP dose (46.8%). The quantitative insights into the impact of MPs on soil properties of this study could aid in understanding the roles of MPs in soil systems.

Zoom-in to molecular mechanisms underlying root growth and function under heterogeneous soil environment and abiotic stresses.

The review describes tissue-specific and non-cell autonomous molecular responses regulating the root system architecture and function in plants. Phenotypic plasticity of roots relies on specific molecular and tissue specific responses towards local and microscale heterogeneity in edaphic factors. Unlike gravitropism, hydrotropism in Arabidopsis is regulated by MIZU KUSSIE1 (MIZ1)-dependent asymmetric distribution of cytokinin and activation of Arabidopsis response regulators, ARR16 and ARR17 on the lower water potential side of the root leading to higher cell division and root bending. The cortex specific role of Abscisic acid (ABA)-activated SNF1-related protein kinase 2.2 (SnRK2.2) and MIZ1 in elongation zone is emerging for hydrotropic curvature. Halotropism involves clathrin-mediated internalization of PIN FORMED 2 (PIN2) proteins at the side facing higher salt concentration in the root tip, and ABA-activated SnRK2.6 mediated phosphorylation of cortical microtubule-associated protein Spiral2-like (SP2L) in the root transition zone, which results in anisotropic cell expansion and root bending away from higher salt. In hydropatterning, Indole-3-acetic acid 3 (IAA3) interacts with SUMOylated-ARF7 (Auxin response factor 7) and prevents expression of Lateral organ boundaries-domain 16 (LBD16) in air-side of the root, while on wet side of the root, IAA3 cannot repress the non-SUMOylated-ARF7 thereby leading to LBD16 expression and lateral root development. In root vasculature, ABA induces expression of microRNA165/microRNA166 in endodermis, which moves into the stele to target class III Homeodomain leucine zipper protein (HD-ZIP III) mRNA in non-cell autonomous manner. The bidirectional gradient of microRNA165/6 and HD-ZIP III mRNA regulates xylem patterning under stress. Understanding the tissue specific molecular mechanisms regulating the root responses under heterogeneous and stress environments will help in designing climate-resilient crops.

Can we use X-ray CT to generate 3D penetration resistance data?

Noninvasive imaging of soils with X-ray CT has proven to be a useful method to assess soil structure from a pore space perspective. In contrast, methods like cone penetration tests reflect soil structure from the perspective of the soil matrix as assessed by its mechanical strength. Because both the gray value (GV) obtained with X-ray CT and the penetration resistance (PR) obtained with a cone penetration test depend on soil density there should be a relationship between the two. To the best of our knowledge, no studies attempted so far to investigate the nature of the PR ∼ GV relationship and to understand how well PR and GV are correlated. We aimed at bridging that gap and carried out a combined analysis of local GV and PR with undisturbed soil cores sampled in two soil textures, i.e., loam and sand. To carry out the GV measurements, we developed a new approach which considers an adaptive volume of the zone of influence of the penetrometer tip as a function of soil density. For sand and when looking at samples individually, the correlation between PR and GV was best when the soil microscale heterogeneity was high, i.e., when dense and loose zones of soil were present on the course of the penetrometer tip. For loam, the correlation between PR and GV was not dependent on soil heterogeneity. When looking at the whole dataset, the agreement between PR and GV was better in loam than in sand, with a distance correlation metric of 0.66 for loam and 0.34 for sand, respectively. For loam, the relationship PR ∼ GV had a trend which was similar to that of a hyperbola, i.e., with escalating PR values in a narrow GV range. For sand, no particular model could be recognized. In order to provide a proof-of-concept on how to generate 3D PR maps, the co-located measurements of GV and PR were used to establish an empirical relationship and X-ray CT was used to extrapolate it in 3D. This was carried out with the loam dataset by fitting a hyperbolic function to the PR ∼ GV data pairs. This model was then used to convert GVs into PR values, at a spatial resolution equal to that of the shaft diameter of the penetrometer tip we have used. Notwithstanding the fact that the suggested approach is dependent on numerous experimental conditions and edaphic factors, we advocate for the use of 3D PR maps. These maps could be used in root-soil interactions research, for which the study and breeding of cultivars that could show plastic response in their root systems under mechanical stress is becoming more and more important. This is particularly relevant in the context of mechanized modern agriculture.

Analysis of spatial heterogeneity of soil physicochemical properties in northern Malawi

Topography and fertility management practices are critical when examining distribution of spatial heterogeneity of soil properties. The study was carried out on a 52-ha land with undulating topography of a village in Northern Malawi to analyze spatial soil heterogeneity with attention to topography and soil fertility management practices in 2021. The spatial heterogeneity of 12 soil chemical properties and soil texture were examined using geostatistical analysis. At 0–20 cm depth, 115 geocoded surface soil samples were collected. Remotely sensed images were captured using an unmanned aerial vehicle, processed, and analyzed to generate and visualize topographic data. Soil fertility management practices were described using field observations and questionnaire survey. The geostatistical analysis revealed spatial heterogeneity of most soil properties at a scale of 80–650 m. The spatial structure of soil pH, available phosphorus (P), total carbon (TC), total nitrogen (TN), and clay showed strong spatial autocorrelation (Q value <0.25). Calcium (Ca2+) and potassium (K+) had moderate spatial autocorrelations (Q values >0.25–< 0.75), whereas magnesium (Mg2+), sodium (Na+), sand, and silt had weak spatial autocorrelations (Q value >0.75). The spatial heterogeneity in TC, K+, Mg2+, CEC, clay, silt, and sand was influenced by the area's topography, whereas pH, P, TN, and Ca2+ were influenced by soil fertility management practices. While change can be negative or positive, differences in topography and fertility management practices significantly changed the physicochemical soil properties, and consequently affected their distribution. TN and P increased with the application of fertilizer, and manure, respectively. Increase in elevation and slope induced positive changes in CEC, K+, Mg2+ and clay. These results could be helpful in the development and application of precision agriculture in the village.

Annual 30 m winter wheat yield mapping in the Huang-Huai-Hai plain using crop growth model and long-term satellite images

There are great challenges for the accurate prediction of wheat yield at large-scale region due to the spatial heterogeneity of soil, management and meteorological conditions. The Huang-Huai-Hai plain (HHHP) is the most important wheat producing area in China. Timely and effective prediction of wheat yield in the HHHP is of great significance for ensuring food security. However, there is still a lack of studies on long-term wheat yield prediction with high spatial resolution in the HHHP. In this study, the simulation results (including phenological information, LAI and yield) of WheatGrow model and the meteorological variables were used to train regression model, which was applied in the corresponding satellite images and gridded meteorological variables to develop wheat yield prediction model (SCYMvp). Then time-series yield maps of wheat in the HHHP (2001-2020) were obtained and the digitization footprint was estimated. We found that SCYMvp model developed by combining machine learning algorithm (ML) with two state variables (phenological information and GCVI) had the best performance (r = 0.7, NRMSE = 15 %) for wheat yield prediction in the HHHP. Compared with other yield prediction models, SCYMvp model reduced the error of yield prediction to some extent. Meanwhile, SCYMvp model showed good accuracy in wheat yield prediction at the irrigated fields and rainfed fields. In addition, extreme climate events had a weak influence on the SCYMvp model in wheat yield prediction. The yield prediction with high spatial resolution generated by SCYMvp model in the HHHP during past 20 years had good consistency and low error with the statistical yield in the spatio-temporal scale. Compared with the GlobalWheatYield4km product, the SCYMvp model had a better ability to capture spatial heterogeneity of wheat yield at site scale. In addition, required data size per hectare for predicting wheat yield showed a significant increasing trend. The results indicated that the SCYMvp model developed in this study can effectively map wheat yield with high spatial resolution in the study area, and has good potential in smallholder farming economy with large spatial heterogeneity of management conditions.

Analytical solution for dynamic responses of offshore wind turbines supported by pipe pile in radially heterogeneous soil

Offshore wind turbines (OWTs) are subject to the combined action of dynamic environmental loads including wind, waves, and earthquake loads. This paper proposes an analytical solution for the dynamic response of OWTs supported by pipe pile in heterogeneous viscoelastic soil. The analytical model accounts for various interactions that affect OWTs dynamic response. The pipe pile-internal soil is calculated by utilizing the Helmholtz method, the pipe pile-external soil is calculated by utilizing the transfer matrix method, the pipe pile-wave is evaluated by utilizing the diffraction wave theory, and the tower drum-wind is calculated by utilizing the Bernoulli method. The dynamic responses of the pipe pile and tower are established by enforcing the boundary conditions of the displacement continuity and stress equilibrium. The developed analytical solution is degenerated into simplified analytical solutions under various conditions, which was validated by comparing its predictions with the results of available numerical and analytical solutions. The validated simplified solution is then utilized investigate the effects of some critical parameters on OWTs response. The results show that the OWTs response under the combined action of earthquake, wave and wind loads is strongly affected by the presence of water and soil inside the pipe pile, soil radial heterogeneity.

Study on Spatiotemporal Transport Characteristics of Soil Moisture in Layered Heterogeneous Vadose Zone Based on HYDRAS-3D

The heterogeneity of layered soils affects the transport processes of water in the vadose zone. However, the mechanism of soil moisture transport in the vadose zone under heterogeneous media conditions, especially the three-dimensional transport mechanism, is a frontier problem to be studied. In order to reveal the law of soil water transport in the vadose zone under heterogeneous media, this paper constructs a three-dimensional model of water transport using HYDRAS-3D (V 2.x) software through in situ tests of water transport in 3 × 3 × 4 m sample and verifies and analyzes the model. The vertical distribution and variability of soil water content and the temporal and spatial rules of soil water transversal transport at the soil–layer interface were analyzed. The results indicate that after adjusting the parameters in the HYDRAS-3D model using measured values, the simulation results are reasonable, and the model has high reliability. To represent the water content variability characteristics of the test tube profile, water movement in the vadose zone was classified as follows: (I) steady period (April–September, less affected by rainfall), (II) slow change period (January–March), and (III) rainfall rapid change period (June, when the impact of rainfall on the test cylinder was greater). The two largest values of the soil water potential variation gradient, 19.9 and 17.8 cm/d, were observed in the silty clay layer of the test cylinder, and the influence of evaporation and infiltration in the silty clay layer was most notable at the interface. The lateral transport of soil water at the interface was influenced to a certain degree by the layered heterogeneity, wherein the fine sand layer exhibited the most pronounced impact. This was followed by silt and silty clay layers, with the silt layer showing the lowest degree of influence. The research results can provide scientific reference for the rational planning of water resources in the Yinchuan Plain.

Differential fungal assemblages and functions between the plastisphere of biodegradable and conventional microplastics in farmland

The heterogeneity of plastisphere and soil can lead to variation in microbiome, potentially impacting soil functions. Current studies of the plastisphere have mainly focused on bacterial communities, and fungal communities are poorly understood. Biodegradable and conventional microplastics may recruit specific microbial taxa due to their different biodegradability. Herein, we collected polyethylene (PE) and polybutylene adipate terephthalate/polylactide (PBAT/PLA) microplastics in farmland (Hebei, China) and characterized the fungal community in PE and PBAT/PLA plastisphere. Results from high-throughput sequencing showed significantly lower alpha diversity and distinct composition of fungal community in PBAT/PLA plastisphere compared to PE plastisphere. Additionally, the PBAT/PLA plastisphere demonstrated a significant enrichment of fungal taxa with potential plastic-degrading capability such as Nectriaceae, Pleosporaceae and Didymellaceae. The stochasticity of drift (28.7–43.5 %) and dispersal limitation (38.6–39.4 %) were dominant in the assembly of PE and PBAT/PLA plastisphere fungal community. Higher stable and more complex network in PBAT/PLA plastispheres were observed as compared to PE plastisphere. Besides, the total relative abundance of plant and animal pathogens were higher in PBAT/PLA plastisphere than that in PE plastisphere, suggesting that biodegradable microplastics may pose a higher threat to soil health. This study contributes to our understanding of the characteristics of plastisphere fungal communities in soil environments and the associated risks to terrestrial ecosystems resulting from microplastic accumulation.

Soil nutrient heterogeneity alters productivity and diversity of experimental plant communities under multiple global change factors

Plant communities in nature are often challenged by multiple global change factors (GCFs) and also ubiquitously encountered with soil nutrient heterogeneity. So far, however, we know little about the interactive effect of multiple GCFs and soil nutrient heterogeneity on plant communities. We conducted an outdoor mesocosm experiment in which a plant community was either grown in heterogeneous soils consisting of high‐ and low‐nutrient patches, or in homogeneous soils where the same amount of nutrients was evenly distributed. These plant communities were exposed to none (control), single, or a combination of two or four GCFs (i.e. drought, nitrogen deposition, microplastic and cadmium). Biomass of the plant community exposed to drought and nitrogen deposition were greater in heterogeneous than in homogeneous soils, but evenness of the plant community exposed to microplastics was lower. Increasing the number of GCFs increased community biomass more in heterogeneous than in homogeneous soils, but it generally reduced community evenness, independent of soil nutrient heterogeneity. These contrasting responses were related to changing competitive hierarchies and root foraging responses under different treatments. Our results suggest that soil nutrient heterogeneity can alter community productivity and diversity via changing competitive interactions of the component species, depending on both the identity and the number of GCFs acting on the community. These results have important implications for the maintenance of ecosystem functions and services under rapid and complex ongoing global changes.

Combined effects of soil 3D spatial heterogeneity and biotic spatial heterogeneity (plant clumping) on ecosystem processes in grasslands.

Soil heterogeneity has been shown to enhance plant diversity, but its effect on grassland productivity is less clear. Even less is known about the effect of plant clumping (intraspecific aggregation) and its potential interaction with soil heterogeneity. The combined effects of soil 3D spatial heterogeneity and species clumping were experimentally studied in grassland mesocosms consisting of four grassland species. These species were planted in three patterns (i.e. completely mixed, clumped by 9 or 36 individuals of the same species) on soils with heterogeneous cells of alternating nutrient-poor and rich soil differing in size from 0 (mixed soil) to 12, 24, and 48 cm (complete poor or rich mesocosm). Moderate soil cell sizes (12-24 cm) consistently increased whole-mesocosm aboveground productivity by more than 20%, which mainly originated from the increased growth of the plants growing on the poor soil cells. In contrast, total mesocosm productivity was not affected by species clumping although there were some species-specific effects, both of clumping and of the interaction of clumping with soil heterogeneity. Our results show that intermediate soil heterogeneity promotes productivity. Clumping can improve the growth of inferior species, thus promoting coexistence, without affecting overall productivity. We found no interaction effect of clumping and soil heterogeneity on productivity at the community level and some minor species-specific effects.

Design to Failure: What Went Wrong?

Failures resulted from a lack of awareness of the dangers involved, a lack of competent geotechnical engineering engagement, poor communication, and a tendency to invest insufficient resources to complete a thorough design. Various factors, including changes in the water table, progressive soil erosion, soil heterogeneity, excavation activities, soil liquefaction, and natural disasters such as earthquakes and landslides, can cause geotechnical failures. This demonstrates the need for geotechnical engineers to have the necessary knowledge and skills to build safe structures with a low risk of geotechnical failure. Prediction and anticipation are the arts of geotechnical design rather than a comprehensive quantitative analysis. As a result, this paper will offer various case studies of geotechnical failures to provide recommendations.

Estimating soil water content in a thorny forest ecosystem by time‐lapse electrical resistivity tomography (ERT) and HYDRUS 2D/3D simulations

AbstractDetermination of soil volumetric water content in forest ecosystems is particularly challenging due to deep rooting systems and unknown soil vertical and spatial heterogeneity. This research aims to test two undisturbed methods, electrical resistivity tomography (ERT) and HYDRUS 2D/3D, for 2D determination in a thorny forest ecosystem. The experiment consisted of infiltrating 10 L of water lasting 60 min. During infiltration, ERT measured apparent resistivity by time‐lapse measurements, and was measured with an FDR probe (EnviroSCAN) at 33, 63, 83, 97, and 163 cm depth close to the infiltration site. At the end of infiltration, a soil pit was dug, and 100 measurements of were performed with a TDR in a 10 × 10 cm regular grid. Archie law transformed soil resistivity (ERT) into using manual calibration, verified by an independent dataset. The 2D profile obtained by ERT was qualitatively compared with the HYDRUS 2D/3D one. HYDRUS 2D/3D was parametrized with calibrated parameters obtained with HYDRUS 1D using 106 days of obtained with EnviroSCAN. The results of HYDRUS 1D calibration and verification were satisfactory, with RMSE and Nash‐Sutcliffe coefficients ranging from 0.021 to 0.034 cm3 cm−3 and 0.11 to 0.77, respectively. The forward HYDRUS 2D/3D simulation disagrees with EnviroSCAN data for 33 cm depth. However, it follows the trend with near to zero variation of water content at 63 cm depth. Water content determination by ERT was satisfactory with RMSE for calibration and verification of 0.017 and 0.021 cm3 cm−3. HYDRUS 2D/3D and ERT comparisons were not equal, with a shallower wetting front by ERT and a deeper one for HYDRUS. Still, both wetting fronts agree with the wetting depth estimated by EnviroSCAN. We conclude that both methods are an alternative for determination in heterogeneous and deep soils of forest ecosystems.