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Soil compaction is a major disturbance associated with logging, but we lack a fundamental understanding of how this affects the soil microbiome. We assessed the structural resistance and resilience of the microbiome using a high-throughput pyrosequencing approach in differently compacted soils at two forest sites and correlated these findings with changes in soil physical properties and functions. Alterations in soil porosity after compaction strongly limited the air and water conductivity. Compaction significantly reduced abundance, increased diversity, and persistently altered the structure of the microbiota. Fungi were less resistant and resilient than bacteria; clayey soils were less resistant and resilient than sandy soils. The strongest effects were observed in soils with unfavorable moisture conditions, where air and water conductivities dropped well below 10% of their initial value. Maximum impact was observed around 6–12 months after compaction, and microbial communities showed resilience in lightly but not in severely compacted soils 4 years post disturbance. Bacteria capable of anaerobic respiration, including sulfate, sulfur, and metal reducers of the Proteobacteria and Firmicutes, were significantly associated with compacted soils. Compaction detrimentally affected ectomycorrhizal species, whereas saprobic and parasitic fungi proportionally increased in compacted soils. Structural shifts in the microbiota were accompanied by significant changes in soil processes, resulting in reduced carbon dioxide, and increased methane and nitrous oxide emissions from compacted soils. This study demonstrates that physical soil disturbance during logging induces profound and long-lasting changes in the soil microbiome and associated soil functions, raising awareness regarding sustainable management of economically driven logging operations.

Peanut ( Arachis hypogaea L.) is an important oil crop globally because of its high edible and economic value. However, its yield and quality are often restricted by certain soil factors, especially nitrogen (N) deficiency, and soil compaction. To explore the molecular mechanisms and metabolic basis behind the peanut response to N deficiency and soil compaction stresses, transcriptome and metabolome analyses of peanut root were carried out. The results showed that N deficiency and soil compaction stresses clearly impaired the growth and development of peanut's aboveground and underground parts, as well as its root nodulation. A total of 18645 differentially expressed genes (DEGs) and 875 known differentially accumulated metabolites (DAMs) were identified in peanut root under differing soil compaction and N conditions. The transcriptome analysis revealed that DEGs related to N deficiency were mainly enriched in “amino acid metabolism”, “starch and sucrose metabolism”, and “TCA cycle” pathways, while DEGs related to soil compaction were mainly enriched in “oxidoreductase activity”, “lipids metabolism”, and “isoflavonoid biosynthesis” pathways. The metabolome analysis also showed significant differences in the accumulation of metabolisms in these pathways under different stress conditions. Then the involvement of genes and metabolites in pathways of “amino acid metabolism”, “TCA cycle”, “lipids metabolism”, and “isoflavonoid biosynthesis” under different soil compaction and N deficiency stresses were well discussed. This integrated transcriptome and metabolome analysis study enhances our mechanistic knowledge of how peanut plants respond to N deficiency and soil compaction stresses. Moreover, it provides new leads to further investigate candidate functional genes and metabolic pathways for use in improving the adaptability of peanut to abiotic stress and accelerating its breeding process of new stress-resistant varieties.

This study presents a novel procedure and mathematical model employing four artificial intelligence AI algorithms to predict the cumulative degree of soil compaction CDSC during dynamic compaction DC. The four AI algorithms used in this study involve artificial neural network ANN, support vector regression SVR, gradient boosting machine GBM, and random forest RF. Input variables involve the average SPT N value N ini before dynamic compaction, cumulative applied energy normalized with a cross-sectional area of tamper E a , and the number of the tamper drops N drops . Apart from cross-validation with a testing set, additional in situ test data gathered from a different section within the study site are used to assess the generalization capacity of the AI models. In addition, out-of-distribution analyses for the four AI algorithms are conducted in the context of parametric studies. The CDSC prediction performance for the four AI models leads to high prediction metrics of accuracy with the r 2 greater than 0.9 for the testing scenario while the r 2 of the other AI models is greater than 0.9 when out-of-sample data are considered except for the GBM. The ANN appears to be the best model as the parametric study takes into account out-of-distribution data and suggests a robust relationship between input variables and CDSC that is more coherent with engineering principles for DC. Finally, the ANN model is utilized to develop a new mathematical model for CDSC prediction.

The bearing capacity of traditional prestressed high‐strength concrete (PHC) pipe pile is hampered by the poor mechanical properties of surrounding soil in soft soil areas, and the PHC nodular pile can improve the behavior of pile foundation in soft soils. The PHC nodular pile installation process will induce larger disturbance to the surrounding soil compared to the PHC pipe pile, and there is little research on the installation effect of the PHC nodular pile. In this paper, the coupled Eulerian‐Lagrangian (CEL) finite element method was adopted to simulate the penetration process of PHC nodular piles and pipe piles in soft soil. The radial stress and displacement in soil induced by the PHC nodular pile and pipe pile and the soil resistance at different parts of the PHC nodular pile were analyzed. The simulation results showed that the penetration resistance of the PHC nodular pile was larger than that of the PHC pipe pile. The penetration resistance of PHC nodular piles was mainly provided by the pile shaft resistance. The uplift height of soil surface caused by the PHC nodular pile and pipe pile penetration was approximately the same. The influence range of compaction effect for PHC nodular pile and pipe pile was both concentrated on 10 R ( R is the pile diameter).

Degree of compactness (DC) is a useful parameter to evaluate management effects on soil structure and crop growth and development. We used DC in soil structure evaluation in a Typic Paleudalf with the following land uses: (1) native disturbed forest with undergrowth of shrub species; (2) 5-year-old pasture; (3) 20-year-old Eucalyptus saligna stand (eucalyptus 20); and (4) 4.5-year-old, second-rotation Eucalyptus saligna stand (eucalyptus 4.5). We determined soil bulk density (BD), porosity, saturated hydraulic conductivity, and reference bulk density (BDref) of compacted soil at −33 kPa matric potential compressed at 200, 400, 800, and 1,600 kPa (respectively, 29, 58, 116, and 232 psi) loads. DC was calculated as the ratio between field BD and BDref at 200, 400, 800, and 1,600 kPa until a DC (using BDref at 1,600 kPa) of 75% soil microporosity increases and then decreases with a further increase in compactness. BD and BDref depend directly on clay content, but their ratio, DC, depends only indirectly on soil texture. DC is affected by land use and varies with soil depth: in pasture, compaction caused by animal trampling is more pronounced in the layer 0.00–0.10 m, whereas in eucalyptus 4.5 harvest in first-rotation DC increases until the 0.40 m soil depth. For eucalyptus and native forest, the layer 0.00–0.10 m shows low DC associated with high organic matter, biological activity, and roots.

Soil compaction in alfalfa fields has become increasingly severe due to the mechanization of animal husbandry and the increased use of heavy agricultural machinery. Perennial alfalfa land undergoes mechanical compaction several times during the planting period without mechanical tillage. The compacted soil structure may recover through moisture changes, freezing and thawing cycles, and plant growth, but the extent and rate of this recovery remain unknown. In this study, alfalfa plots with two different soil types (medium loam and sandy) in Gansu, China, were selected to address these issues. The areas of the plots were 120 m × 25 m and 80 m × 40 m, respectively. In the third year after sowing, three types of agricultural machinery with grounding pressures of 88 kPa, 69 kPa, and 48 kPa were used to compact the soil one, three, five, and seven times. The interval between replicates was 1 h. Each treatment had one plot of 10 m × 5 m, and the experiment was repeated 4 times, totaling 44 plots. Changes in soil bulk density, soil cone index, and saturated hydraulic conductivity were measured after 1, 4, 8, and 17 weeks, respectively. The results showed that the post-compaction soil bulk density and soil cone index largely influenced the recovery of the compacted soil. Recovery became problematic once the soil bulk density exceeded 1.5 g/cm3. The soil bulk density recovery rate varied across different soil layers, with the top layer recovering faster than more profound layers. The initial state could be restored when the change in post-compaction soil bulk density was minimal. Sandy soil recovered faster than medium-loam soil. The recovery of the soil cone index in each layer of medium-loam soil under lower compaction was more noticeable than that under severe compaction. However, with undergrounding pressures of 88 kPa and 69 kPa, the soil cone index could not fully recover after multiple compactions. The recovery of soil-saturated hydraulic conductivity in both soil types was slower and less pronounced. The recovery of soil-saturated hydraulic conductivity in medium-loam soil was slower than that in sandy loam. After 7 compactions and 17 weeks under a grounding pressure of 88 kPa, the saturated hydraulic conductivity remained below 20% of its initial value of 20 mm/h. In contrast, sandy soils recovered faster, reaching 60 mm/h within a week of each compaction event. This research is crucial for ensuring high and stable alfalfa yields and supporting sustainable agricultural practices.

Conventional methods for determining soil density compaction and moisture are often time-consuming, destructive, and rely heavily on laboratory analyses. Similarly, standard ground-penetrating radar (GPR) systems generate images that are difficult to interpret, lacking direct access to key parameters such as delay times and phase shifts. This study presents a modified straight-tapered Vivaldi antenna (STVA) for non-destructive soil compaction measurement. This tapered section of the traditional Vivaldi antenna is modified with a straight side instead of the traditional curved shape. The proposed antenna is designed and printed on an FR4 substrate with a dielectric constant of 4.3 and a thickness of 1.6 mm with dual-impedance bandwidths of 0.74–1.00 GHz (31%) and 2.2–2.85 GHz (26%). With the aid of the CST software program, the desired antenna is constructed and simulated, occupying a physical area of (100 × 115) mm . The electrical size of the antenna is (0.266 × 0.306) . Consequently, the antenna achieves a gain of 2–6.5 dB and radiation efficiencies of 99 and 98.2% at the lower and upper bands, respectively. The experimental results demonstrate that the STVA antenna achieves a strong agreement between the measured and simulated reflection coefficients (S11). Using a vector network analyzer, the system directly extracts phase and delay parameters, eliminating the need for complex GPR image interpretation requirements. The measured data, processed through an artificial neural network, accurately predict soil compaction levels. As compaction increases, air-filled voids decrease, raising the soil’s effective dielectric constant ( ᵣ), which in turn alters the signal’s phase and delay-providing a reliable indicator for compaction. This integrated approach outperforms conventional GPR techniques, offering real-time, accurate, and cost-effective soil characterization for geotechnical applications.

This paper reviews the works related to the effect of soil compaction on cereal yield and focuses on research of field experiments. The reasons for compaction formation are usually a combination of several types of interactions. Therefore one of the most researched topics all over the world is the changes in the soil’s physical and chemical properties to achieve sustainable cereal production conditions. Whether we are talking about soil bulk density, physical soil properties, water conductivity or electrical conductivity, or based on the results of measurements of on-line or point of soil sampling resistance testing, the fact is more and more information is at our disposal to find answers to the challenges. Thanks to precision plant production technologies (PA) these challenges can be overcome in a much more efficient way than earlier as instruments are available (geospatial technologies such as GIS, remote sensing, GPS with integrated sensors and steering systems; plant physiological models, such Decision Support System for Agrotechnology Transfer (DSSAT), which includes models for cereals etc.). The tests were carried out first of all on alteration clay and sand content in loam, sandy loam and silt loam soils. In the study we examined especially the change in natural soil compaction conditions and its effect on cereal yields. Both the literature and our own investigations have shown that the soil moisture content changes have the opposite effect in natural compaction in clay and sand content related to cereal yield. These skills would contribute to the spreading of environmental, sustainable fertilizing devoid of nitrate leaching planning and cereal yield prediction within the framework of the PA to eliminate seasonal effects.

Although compacted soil can be recovered through root development of planted seedlings, the relationship between root morphologies and soil physical properties remain unclear. We investigated the impacts of soil compaction on planted hybrid larch F1 (Larix gmelinii var. japonica×L. kaempferi, hereafter F1) seedlings with/without N loading. We assumed that N loading might increase the fine root proportion of F1 seedlings under soil compaction, resulting in less effects of root development on soil recovery. We established experimental site with different levels of soil compaction and N loading, where two-year-old F1 seedlings were planted. We used a hardness change index (HCI) to quantify a degree of soil hardness change at each depth. We evaluated root morphological responses to soil compaction and N loading, focusing on ectomycorrhizal symbiosis. High soil hardness reduced the total dry mass of F1 seedlings by more than 30%. Significant positive correlations were found between HCI and root proportion, which indicated that F1 seedling could enhance soil recovery via root development. The reduction of fine root density and its proportion due to soil compaction was observed, while these responses were contrasting under N loading. Nevertheless, the relationships between HCI and root proportion were not changed by N loading. The relative abundance of the larch-specific ectomycorrhizal fungi under soil compaction was increased by N loading. We concluded that the root development of F1 seedling accelerates soil recovery, where N loading could induce root morphological changes under soil compaction, resulting in the persistent relationship between root development and soil recovery.

Controlled traffic farming is a machinery management system that confines all field vehicles to the least possible area of permanent traffic lanes. It has developed in response to research evidence of widespread soil damage from compaction due to field traffic. The history of research on soil compaction is explored and found to be a relatively new phenomenon. Controlled traffic farming as a topic for research did not appear until the 1980s although its principles and benefits were well established before then. Research expanded over the next decades but changed subtly to more reviews on the topic as well as emphasis on environmental deliverables and some economics studies. Few if any researchers attempted to develop on-farm systems using existing machinery until the mid 1990s when a small and dedicated team in Australia encouraged farmers to experiment. This quickly led to rapid expansion across the continent to its present day c. 13% of the cropped area. Despite changes to extension services in northern Europe at around the turn of the century and a move to subsidiarity, this did not alter the model of controlled traffic adoption. This followed a similar pattern to that in Australia involving individuals rather than organizations.