Populus euphratica, Tamarix ramosissima, and Sophora alopecuroides are, respectively, typical arboreal, shrubby, and herbaceous species in oases of arid regions. It is important to study the difference in metabolic characteristics of the rhizosphere fungal community of these plant species and their relationships with soil factors for the preservation of delicate arid oasis ecosystems with future environmental changes. In this study, we, respectively, collected 18 rhizosphere soil samples of P. euphratica, T. ramosissima, and S. alopecuroides to explore the difference in rhizosphere fungal metabolic characteristics of different plant life forms and their underlying driving factors. The results showed that (1) soil physicochemical properties (including soil water content, pH, etc.) were significantly different among different plant species (p < 0.05). (2) Rhizosphere fungal metabolic characteristics were significantly different between S. alopecuroides and T. ramosissima (ANOSIM, p < 0.05), which was mainly caused by the different utilization of carboxylic carbon. (3) The RDA showed that the main driving factors of the variations in rhizosphere fungal metabolic characteristics were different among different plant species. The main explanatory variables of the variations in the metabolic characteristics of the rhizosphere fungal community were carbon to nitrogen ratio (23%) and available potassium (17.4%) for P. euphratica, while soil organic carbon (23.1%), pH (8.6%), and total nitrogen (8.2%) for T. ramosissima, and soil clay content (36.6%) and soil organic carbon (12.6%) for S. alopecuroides. In conclusion, the variations in rhizosphere fungal metabolic characteristics in arid oases are dominantly affected by soil factors rather than plant life forms.

Predicting soil heavy metal (SHM) content is crucial for understanding SHM pollution levels in urban residential areas and guide efforts to reduce pollution. However, current research indicates low SHM prediction accuracy in urban areas. Therefore, we employed a deep learning method (fully connected deep neural network) alongside four other methods (muti-layer perceptron, radial basis function neural network, multiple stepwise linear regression, and Kriging interpolation) to predict SHM content in the urban residential areas of Beijing and demonstrated the strength of deep learning in improving prediction accuracy. We found the contents of the evaluated heavy metals (Cd, Cu, Pb, and Zn) exhibited significant correlations with numerous other soil physicochemical properties and environmental factors. The prediction accuracy for Cu, Pb, and Zn contents was relatively high across different methods. Notably, deep learning showed considerable strength in predicting the contents of the four heavy metals, with the R2 for the test set of the model ranging from 0.75 to 0.91. Compared to other methods, deep learning achieved markedly higher prediction accuracy according to different accuracy evaluation indicators (e.g., deep learning showed increases in the cumulative R2 of the four heavy metals ranging from 53.16 % to 187.36 % compared to other methods). Our study indicates that deep learning can significantly improve SHM content prediction accuracy in urban areas and is highly applicable in urban residential areas with complex environmental influences.

Recent pesticide use is alarmingly high and unregulated in several parts of the world. Pesticide fate in soil is controlled by sorption processes which affect the subsequent transport and chemical reactivity in the environment, as well as uptake by plants. Sorption processes are dependent on soil composition and properties, but these are beginning to be affected by global warming-linked factors leading to soil depletion. Thus, it is vital to decipher soils\' response, especially in the sub-Sahara (SS), to the depletion of some inherent components in the presence of pesticides. This was ascertained by monitoring a model pesticide (atrazine) sorption and desorption on whole SS soil (WS), and the same soil whose organic matter (OMR) and iron oxides (IOR) were substantially depleted, as well as studying atrazine uptake from these soils by fast-growing vegetables. Organic matter depletion enhanced equilibrium in OMR. Sorption was enhanced at lower ambient pH, higher initial atrazine concentration, and higher temperature. Hysteresis was low resulting in high desorption. Overall, atrazine desorption of ≥65 % was observed; it was higher in OMR (≥95 %) since SOM enhanced hysteresis. Though sub-Saharan soils are rich in iron oxides, SOM played a significantly higher role in sorption than iron oxides in this soil. This result suggests a high potential for atrazine to leach into the aquifer in the sub-Saharan. Atrazine uptake experiment by waterleaf and spinach showed that it could be detected in soil after 63 d, and its presence significantly affected the growth of both vegetables especially in soils with depleted SOM and iron oxides, and at high (100 µg/kg) atrazine spiking. Spinach may be a higher atrazine accumulator than waterleaf. It may be concluded that waterleaf and spinach grown on atrazine-contaminated soils, especially on SOM/iron oxide-depleted soils, are likely to accumulate atrazine.

The excavation of Chinese pangolin (Manis pentadactyla) is expected to alter habitat heterogeneity and thus affect the functioning and structure of forest ecosystems. In this study, the bioturbation of Chinese pangolin on forest soils in three regions (Heping, Tianjingshan, and Wuqinzhang) across Guangdong province was quantified. Overall, a mean of 2.66 m3·ha-1 and 83.1 m2·ha-1 of burrows and bare mounds, respectively, was excavated by Chinese pangolin; the disturbed soils had significantly lower water content and P, C, available N concentrations, but higher bulk density, pH, and microbial abundance than those undisturbed soils. The unevenness of habitat heterogeneity improvement was mainly ascribed to the stronger soil disturbance caused in resting burrows by pangolins. Patterns of altering habitat heterogeneity were site-specific, with high-intensity soil disturbance occurring most in shrubs, meadows, steep habitats at high elevations, and mountain tops in Heping, while in broad-leaved, coniferous and mixed coniferous and broad-leaved forests away from human settlements in Tianjingshan and upper mountains at high elevations far away from roads and human settlements in Wuqinzhang. Road networks are the main interference for the burrow distribution in Heping and Wuqinzhang and should be programmed.

Arsenic (As) can accumulate in edible plant parts and thus pose a serious threat to human health. Identifying the contributions of various factors to soil available As is crucial for evaluating environmental risks. However, research quantitatively assessing the importance of soil properties on available As is scarce. In this study, we utilized 442 datasets covering total As, available As, and properties of farmland soils. The five machine learning models were employed to predict soil available As content, and the model with the best predictive performance was selected to calculate the importance of soil properties on available As and interpret the model results. The Random Forest model exhibited the best predictive performance, with R2 for the test set of dryland and paddy fields being 0.83 and 0.82 respectively, while also outperforming other machine learning models in terms of accuracy. Concurrently, evaluating the contribution of soil properties to soil available As revealed that increases in soil total arsenic, pH, organic matter (OM), and cation exchange capacity (CEC) led to higher soil available As content. Among these factors, soil total As had the greatest impact, followed by CEC. The influence of pH on soil available As was greater in dryland compared to OM, while in paddy fields, it was smaller than OM (p < 0.01). Sensitivity analysis results indicated that reducing soil total As content had the greatest effect on available As. In both dryland and paddy field soils, reducing soil total As had the most pronounced effect on available As, leading to reductions of 10.09% and 8.48%, respectively. Therefore, prioritizing the regulation of soil total As and CEC is crucial in As contamination management practices to alter As availability in farmland soils.

Mechanochemical techniques have been garnering growing attention in remediation of contaminated soil. This paper summarizes the performance, mechanism, influential factors, and environmental impacts of mechanochemical remediation (MCR) for persistent organic pollutants (POPs) contaminated soil and heavy metal(loid) s (HMs) contaminated soil. Firstly, in contrast to other technologies, MCR can achieve desirable treatment of POPs, HMs, and co-contaminated soil, especially with high-concentration pollutants. Secondly, POPs undergo mineralization via interaction with mechanically activated substances, where aromatic and aliphatic pollutants in soil may go through varied degradation routes; inorganic pollutants can be firmly combined with soil particles by fragmentation and agglomeration induced by mechanical power, during which additives may enhance the combination but their contact with anionic metal(loid)s may be partially suppressed. Thirdly, the effect of MCR primarily hinges on types of milling systems, the accumulation of mechanical energy, and the use of reagents, which is basically regulated through operating parameters: rotation speed, ball-to-powder ratio, reagent-to-soil ratio, milling time, and soil treatment capacity; minerals like clay, metal oxides, and sand in soil itself are feasible reagents for remediation, and alien additives play a crucial role in synergist and detoxification; additionally, various physicochemical properties of soil might influence the mechanochemical effect to varying degrees, yet the key influential performance and mechanism remain unclear and require further investigation. Concerning the assessment of soil after treatment, attention needs to be paid to soil properties, toxicity of POPs\' intermediates and leaching HMs, and long-term appraisement, particularly with the introduction of aggressive additives into the system. Finally, proposals for current issues and forthcoming advancements in this domain are enumerated in items. This review provides valuable insight into mechanochemical approaches for performing more effective and eco-friendly remediation on contaminated soil.

Soil matrix infiltration is an important pathway for plantations to obtain water, which affects ecological benefits and water conservation function of plantations. The changes of soil matrix infiltration and its influencing factors in different growth stages of Chinese fir plantations remain unclear. We measured soil matrix infiltration process using a tension infiltrometer in Chinese fir plantations (5, 8, 11, and 15 years old) of Beijiang River Forest Farm in Rongshui, Guangxi, and analyzed soil basic physicochemical properties to identify the dominant factors influencing soil matrix infiltration. The results showed that initial infiltration rate, stable infiltration rate, and cumulative infiltration increased with stand ages. The ranges of different stand ages were 141-180 mm·h-1, 109-150 mm·h-1, and 188-251 mm, respectively. The initial infiltration rate, stable infiltration rate, and cumulative infiltration were significantly positively correlated with soil capillary porosity, soil organic matter, soil water stable macroaggregate, sand content, and clay content, while negatively correlated with soil bulk density and silt content. Early thinning had a positive effect on soil matrix infiltration, but thinning measures after 11 years did not enhance soil matrix infiltration further. Philip model was optimal for describing soil matrix infiltration process in this region. In conclusion, soil matrix infiltration capacity of Chinese fir plantations gradually increased from young to middle-aged stands, but matrix infiltration capacity tended to stabilize after 11 years old. Silt content and water stable macroaggregate were the dominant factors influencing matrix infiltration.
土壤基质入渗是人工林获取水分的重要途径,影响着人工林的生态效益和水源涵养能力,目前杉木人工林不同生长阶段土壤基质入渗变化及其影响因素尚不明确。本研究以广西国营贝江河林场杉木人工林(5、8、11和15年)为研究对象,采用表置式环式入渗仪测定土壤基质入渗过程,分析土壤理化性质以明确土壤基质入渗的主导因素。结果表明: 初始入渗率、稳定入渗率和累积入渗量随林龄的增加而增加,不同林龄变化范围分别为141～180 mm·h-1、109～150 mm·h-1和188～251 mm。初始入渗率、稳定入渗率和累积入渗量与土壤毛管孔隙度、有机质、水稳性团聚体、砂粒和黏粒含量呈显著正相关,与土壤容重和粉粒含量呈显著负相关。早期间伐对土壤基质入渗有促进作用,但超过11年后的间伐措施不会进一步促进土壤基质入渗。Philip模型是描述该区域土壤基质入渗过程的最佳模型。综上,在幼龄林到中龄林的生长过程中,杉木人工林的土壤基质入渗能力逐渐提升,在第11年后基质入渗能力趋于稳定;土壤粉粒含量和水稳性团聚体是影响基质入渗的主导因素。.

In our previous study, the decontamination efficiency of cesium-137 (137Cs) by Napier grass (Pennisetum purpureum Schum.) in the field was shown to be variable and often influenced by natural environmental factors. To elucidate the factors influencing this variable 137Cs-decontamination efficiency, we investigated the influences of soil type and drought stress on Cs accumulation using cesium-133 (133Cs) in Napier grass grown in plastic containers. The experiment was performed using two soil types (Soil A and B) and three different soil moisture conditions: well-watered control (CL), slight drought stress (SD), and moderate drought stress (MD). Overall, our results indicate that soil type and drought have a significant impact on plant growth and 133Cs accumulation in Napier grass. Plant height (PH), tiller number (TN), leaf width (Wleaf), and dry matter weight of aboveground parts (DWabove) and root parts (DWroot) in Soil B were greater than those in Soil A. Drought stress negatively affected chlorophyll fluorescence parameters (maximal quantum efficiency of photosystem (PS) II photochemistry and potential activity of PS II), PH, TN, Wleaf, DWabove, DWroot, and total 133Cs content (TCs), but it had a positive effect on 133Cs concentration. The 133Cs concentration in the aboveground parts (Csabove) was increased by MD approximately 1.62-fold in Soil A and 1.11-fold in Soil B compared to each CL counterpart. The TCs in the aboveground parts (TCsabove) decreased due to drought by approximately 19.9%-39.0% in Soil A and 49.9%-62.7% in Soil B; however, there was no significant effect on TCsabove due to soil type. The results of this study indicate that soil moisture is a key factor in maintaining Napier grass 137Cs-decontamination efficiency.

UNASSIGNED: The slash disposal-burning forest-in high-intensity management Eucalyptus grandis × urophylla plantation has accelerated soil degradation.
UNASSIGNED: Slash disposals is a contributing factor, but its specific role in the correlation between rainfall-runoff and soil erosion remains elusive.
UNASSIGNED: his study investigated the characteristics of rainfall-runoff and soil erosion resistance in different methods of slash disposals in plantation.
UNASSIGNED: Three methods of slash disposal, namely burning forest (BF), moving away (MA), and spreading evenly (SE), were established. A field simulation experiment of rainfall was conducted, and path analysis was used.
UNASSIGNED: The findings revealed that the water holding, infiltrating properties and the time the rainfall-runoff generated of SE were increased by approximately 10∼20 %, 100 %, and 80 %, respectively, compared with BF and MA. Water loss, soil loss and nutrient loss were significantly reduced by 62.23 % and 61.56 %, 69.06 % and 49.55 %, and 58.8 % and 65.42 % in SE and BF compared to MA. Path analysis suggested that different from BF and MA, the correlation between soil water properties and rainfall-runoff factors in SE was weakened, simultaneously considering the result that SE had the lower proportions of silt for sediment component (75.31 %), it stabilized the soil structure.
UNASSIGNED: Consequently, SE mitigated the erosion force by reducing rainfall-runoff and enhancing the anti-erosion of soil through improved water properties, making it a viable slash disposal. This work provides a detailed description of the soil erosion characteristics of plantation, including water, soil, and nutrient losses caused by rainfall-runoff, as well as the soil anti-erosion due to different slash disposals. These findings offer valuable insights for the management of high-intensity Eucalyptus grandis × urophylla plantations.

The composition and stability of soil aggregates are important indicators for measuring soil quality, which would be affected by land use changes. Taking wetlands with different returning years (2 and 15 years) in the Yellow River Delta as the research object, paddy fields and natural wetlands as control, we analyzed the changes in soil physicochemical properties and soil aggregate composition. The results showed that soil water content, total organic carbon, dissolved organic carbon and total phosphorus of the returning soil (0-40 cm) showed an overall increasing trend with returning period, while soil pH and bulk density was in adverse. There was no significant change in clay content, electrical conductivity, and total nitrogen content. The contents of macro-aggregates and micro-aggregates showed overall increasing and decreasing trend with returning period, respectively. The stability of aggregates in the topsoil (0-10 cm) increased with returning years. Geometric mean diameter and mean weight diameter increased by 8.9% and 40.4% in the 15th year of returning, respectively, while the mass proportion of >2.5 mm fraction decreased by 10.5%. There was no effect of returning on aggregates in subsoil (10-40 cm). Our results indicated that returning paddy field to wetland in the Yellow River Delta would play a positive role in improving soil structure and aggregate stability.
土壤团聚体组成及稳定性是衡量土壤质量的重要指标,土地利用方式的转变会对其产生不同程度的影响。本研究以黄河三角洲不同退耕年限土地(退耕2年和15年)为对象,以退耕前土地(稻田)和未开垦的自然湿地为对照,分析退耕前后土壤理化性质和土壤团聚体组成及稳定性的变化。结果表明: 稻田退耕后土壤(0～40 cm)含水量、总有机碳、溶解性有机碳和全磷整体上呈现随退耕年限延长而增加的趋势,而土壤pH和容重呈下降趋势,但黏粒含量、电导率和全氮含量无明显变化。随退耕年限延长,土壤大团聚体含量整体上呈增加趋势,而小团聚体含量呈减少趋势。表层土壤(0～10 cm)团聚体稳定性随退耕年限延长而增加,退耕15年后,团聚体几何平均直径和平均重量直径较退耕前增加了8.9%和40.4%,而>0.25 mm团聚体质量分数则减少了10.5%;退耕对下层土壤(10～40 cm)团聚体的影响不明显。综上,黄河三角洲退耕还湿对改善土壤结构、提升团聚体稳定性起到积极作用。.