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Soil fertility is vital for the growth of tea plants. The physicochemical properties of soil play a key role in the evaluation of soil fertility. Thus, realizing the rapid and accurate detection of soil physicochemical properties is of great significance for promoting the development of precision agriculture in tea plantations. In recent years, spectral data have become an important tool for the non-destructive testing of soil physicochemical properties. In this study, a support vector regression (SVR) model was constructed to model the hydrolyzed nitrogen, available potassium, and effective phosphorus in tea plantation soils of different grain sizes. Then, the successful projections algorithm (SPA) and least-angle regression (LAR) and bootstrapping soft shrinkage (BOSS) variable importance screening methods were used to optimize the variables in the soil physicochemical properties. The findings demonstrated that soil particle sizes of 0.25-0.5 mm produced the best predictions for all three physicochemical properties. After further using the dimensionality reduction approach, the LAR algorithm (R 2 C = 0.976, RPD = 6.613) performed optimally in the prediction model for hydrolytic nitrogen at a soil particle size of 0.25~0.5. The models using data dimensionality reduction and those that used the BOSS method to estimate available potassium (R 2 P = 0.976, RPD = 6.613) performed optimally in the prediction model for hydrolytic nitrogen at a soil particle size of 0.25~0.5. The models using data dimensionality reduction and those that used the BOSS method to estimate available potassium (R 2 C = 0.964, RPD = 5.163) had the best accuracy. In order to offer a reference for the accurate detection of soil physicochemical properties in tea plantations, this study investigated the modeling effect of each physicochemical property under various soil particle sizes and integrated the regression model with various downscaling strategies.2 P = 0.981, RPD = 7.222) and effective phosphorus (R 2 C = 0.969, R 2 P = 0.964, RPD = 5.163) had the best accuracy. In order to offer a reference for the accurate detection of soil physicochemical properties in tea plantations, this study investigated the modeling effect of each physicochemical property under various soil particle sizes and integrated the regression model with various downscaling strategies.

Biochar is important for soil improvement, fertilizer innovation, and greenhouse gas reduction. In this paper, Mg-modified biochar was prepared from rice and corn straw and mixed with soil at a 1% ( w / w ) addition in an indoor soil simulation experiment to study the effect of Mg-modified biochar on the chemical properties of acidic soil. The results showed that the addition of Mg-modified biochar reduced soil acidity and improved soil fertility. Compared with the control group, the Mg-modified biochar treatment significantly increased the concentrations of available potassium, available phosphorus, total phosphorus, organic carbon and exchangeable calcium and magnesium in the soil, and effectively increased the concentration of total nitrogen. Rice straw Mg-modified biochar treatment was more effective in increasing the soil-available potassium, available phosphorus, total phosphorus and exchangeable magnesium concentration, while corn straw Mg-modified biochar was more effective in increasing the soil organic carbon and exchangeable calcium concentration. In addition, the high pyrolysis temperature of Mg-modified biochar was more effective in promoting the soil-available potassium, available phosphorus and total nitrogen concentration, while the low pyrolysis temperature of Mg-modified biochar was more effective in promoting soil alkaline nitrogen, exchangeable calcium and magnesium.

The prediction of soil properties at different depths is an important research topic for promoting the conservation of black soils and the development of precision agriculture. Mid-infrared spectroscopy (MIR, 2500-25000 nm) has shown great potential in predicting soil properties. This study aimed to explore the ability of MIR to predict soil organic matter (OM) and total nitrogen (TN) at five different depths with the calibration from the whole depth (0-100 cm) or the shallow layers (0-40 cm) and compare its performance with visible and near-infrared spectroscopy (vis-NIR, 350-2500 nm). A total of 90 soil samples containing 450 subsamples (0-10 cm, 10-20 cm, 20-40 cm, 40-70 cm, and 70-100 cm depths) and their corresponding MIR and vis-NIR spectra were collected from a field of black soil in Northeast China. Multivariate adaptive regression splines (MARS) were used to build prediction models. The results showed that prediction models based on MIR (OM: RMSE p = 1.07-3.82 g/kg, RPD = 1.10-5.80; TN: RMSE p = 0.11-0.15 g/kg, RPD = 1.70-4.39) outperformed those based on vis-NIR (OM: RMSE p = 1.75-8.95 g/kg, RPD = 0.50-3.61; TN: RMSE p = 0.12-0.27 g/kg; RPD = 1.00-3.11) because of the higher number of characteristic bands. Prediction models based on the whole depth calibration (OM: RMSE p = 1.09-2.97 g/kg, RPD = 2.13-5.80; TN: RMSE p = 0.08-0.19 g/kg, RPD = 1.86-4.39) outperformed those based on the shallow layers (OM: RMSE p = 1.07-8.95 g/kg, RPD = 0.50-3.93; TN: RMSE p = 0.11-0.27 g/kg, RPD = 1.00-2.24) because the soil sample data of the whole depth had a larger and more representative sample size and a wider distribution. However, prediction models based on the whole depth calibration might provide lower accuracy in some shallow layers. Accordingly, it is suggested that the methods pertaining to soil property prediction based on the spectral library should be considered in future studies for an optimal approach to predicting soil properties at specific depths. This study verified the superiority of MIR for soil property prediction at specific depths and confirmed the advantage of modeling with the whole depth calibration, pointing out a possible optimal approach and providing a reference for predicting soil properties at specific depths.

Precision agriculture is crucial for ensuring food security in a growing global population. Nutrients, their presence, concentration, and effectiveness, are key components in data-driven agriculture. Assessing macro and micro-nutrients, as well as factors such as water and pH, helps determine soil fertility, which is vital for supporting healthy plant growth and high crop yields. Insufficient soil nutrient assessment during continuous cropping can threaten long-term agricultural viability. Soil nutrients need to be measured and replenished after each harvest for optimal yield. However, existing soil testing procedures are expensive and time-consuming. The proposed research aims to assess soil nutrient levels, specifically nitrogen and phosphorus concentrations, to provide critical information and guidance on restoring optimal soil fertility. In this research, a novel chip-level colorimeter is fabricated to detect the N and P elements of soil onto a handheld colorimeter or spectrophotometer. Chemical reaction with soil solution generates color in the presence of nutrients, which are then quantitatively measured using sensors. The test samples are collected from various farmlands, and the results are validated with laboratory analysis of samples using spectrophotometers used in laboratories. ANOVA test has been performed in which F value > 1 in our study indicates statistically significant differences between the group means. The alternate hypothesis, which proposes the presence of significant differences between the groups, is supported by the data. The device created in this paper has crucial potential in terms of environmental and biological applications.

Biochar and nitrogen fertilizers are known to increase soil carbon storage and reduce soil nitrogen loss as amendments, suggesting a promising strategy for highly effectively increasing soil productivity. However, few studies have explored the mechanisms of their effects on crop yield in terms of active carbon fraction and enzyme activity, which ultimately limits the potential for the application of biochar in combination with nitrogen fertilizers. To evaluate the effect of biochar and nitrogen fertilizer on the improvement of black soils in northeast China, a field experiment was conducted in the black soil to compare and analyze the application methods on total organic carbon (TOC), total nitrogen (TN), enzyme activities, and maize yields. Biochar rates: CK, C1, C2, and C3 (0, 9.8, 19.6, and 29.4 Mg·ha -1 ); N fertilizer rates: N1/2 and N (30 and 60 kg·ha -1 ). Results indicated that biochar and N fertilizer amendments significantly ameliorated soil fertility, such as TOC and TN, compared to the unamended soil. The TOC levels in the C3 treatment increased by 35.18% and the TN levels by 23.95%. The improvement in TN is more significant when biochar is blended with N fertilizer. Biochar blended with N fertilizer increased maize cellulase, urease, and invertase activities by an average of 53.12%, 58.13%, and 16.54%, respectively. Redundancy analysis showed that TOC, TN, and MBN contributed 42%, 16.2%, and 22.2%, respectively, to the maize yield indicator. Principal component analysis showed that reduced N fertilizer was more effective in improving yields, with a maximum yield increase of 50.74%. Biochar blended with N fertilizer is an effective strategy to improve the fertility and productivity of black soils in northeast China, while nitrogen fertilizer reduction is feasible and necessary for maintaining grain yield.

Rice-duck and rice-crayfish co-culture patterns can increase soil productivity and sustainability and reduce the use of chemical pesticides and fertilizers, thereby reducing the resulting negative environmental impacts. However, most studies have focused on the rice-duck and rice-crayfish binary patterns and have ignored integrated systems (three or more), which may have unexpected synergistic effects. To test these effects, a paddy field experiment was carried out in the Chaohu Lake Basin, Hefei city, Southeast China. Four groups, including a rice-duck-crayfish ecological co-culture system (RDC), idle field (CK), single-season rice planting system (SSR), and double-season rice planting system (DSR), were established in this study. The results showed that the RDC improved the soil physical properties, fertility, humus content, and enzyme activity. In the RDC system, the soil total nitrogen content ranged from 8.54% to 28.37% higher than other systems in the 0-10 cm soil layer. Similar increases were found for soil total phosphorus (8.22-30.53%), available nitrogen (6.93-22.72%), organic matter (18.24-41.54%), urease activity (16.67-71.51%), and acid phosphatase activity (23.41-66.20%). Relative to the SSR treatment, the RDC treatment reduced the total losses of nitrogen and phosphorus runoff by 24.30% and 10.29%, respectively. The RDC also did not cause any harm to the soil in terms of heavy metal pollution. Furthermore, the RDC improved the yield and quality of rice, farmer incomes, and eco-environmental profits. In general, the RDC can serve as a valuable method for the management of agricultural nonpoint-source pollution in the Chaohu Lake area and the revitalization of the countryside.

Biochar addition has been recommended as a potential strategy for mitigating climate change. However, the number of studies simultaneously investigating the effects of biochar addition on CO 2 , N 2 O and CH 4 emissions and sequentially global warming potential (GWP) is limited, especially concerning its effect on native soil organic carbon (SOC) mineralization. An incubation experiment was conducted to investigate soil physicochemical properties, CO 2 , N 2 O and CH 4 emissions and GWP in the treatments with 0% (CK), 1% (BC1) and 4% (BC4) cornstalk biochar additions, and clarify the priming effect of biochar on native SOC mineralization by the 13 C tracer technique. Generally, biochar addition increased soil pH, cation exchange capacity, SOC and total nitrogen, but decreased NH 4 + -N and NO 3 - -N. Compared with CK, BC1 and BC4 significantly reduced CO 2 emissions by 20.7% and 28.0%, and reduced N 2 O emissions by 25.6% and 95.4%, respectively. However, BC1 significantly reduced CH 4 emission by 43.6%, and BC4 increased CH 4 emission by 19.3%. BC1 and BC4 significantly reduced the GWP by 20.8% and 29.3%, but there was no significant difference between them. Biochar addition had a negative priming effect on native SOC mineralization, which was the reason for the CO 2 emission reduction. The negative priming effect of biochar was attributed to the physical protection of native SOC by promoting microaggregate formation and preferentially using soluble organic carbon in biochar. The N 2 O emission decrease was rooted in the reduction of nitrification and denitrification substrates by promoting the microbial assimilation of inorganic nitrogen. The inconsistency of CH 4 emissions was attributed to the different relative contributions of CH 4 production and oxidation under different biochar addition ratios. Our study suggests that 1% should be a more reasonable biochar addition ratio for mitigating greenhouse gas emissions in sandy loam, and emphasizes that it is necessary to furtherly investigate nitrogen primary transformation rates and the relative contributions of CH 4 production and oxidation by the 15 N and 13 C technique, which is helpful for comprehensively understanding the effect mechanisms of biochar addition on greenhouse gas emissions.

In order to combat land desertification and to evaluate the soil quality of different cover land types, and thereby determine the best land use strategy for vegetation restoration, this research comprehensively analyzed the soil quality of different land use/cover types in the hilly sandy area of the Loess Plateau by using the Kruskal-Wallis test (K-W test) and principal component analysis (PCA) technique for order preference by the similarity to ideal solution (TOPSIS), and the potential ecological risk index ( RI ). The result indicated that the cropland abandonment over a period of time could improve the soil quality to a certain extent; however, the process of natural restoration was very slow compared with that of the planted mixed shrubs. The soil quality of all land use/cover types in the hilly sandy area of Youyu County clearly improved after 10-25 years of revegetation, but the degree of improvement varied greatly with the different planted species and their combinations. The low levels of soil organic matter, total nitrogen and available phosphorus were the major limiting factors affecting soil quality improvement under different land use/cover types, not metal toxicity. Pioneer species of H. rhamnoide , C. korshinskii and Pinus sylvestris var. mongolica , etc. are vital to vegetation restoration of the study area. Revegetation using these species is therefore recommended to combat future desertification in this area.

Synthetic nitrogen (N) fertilizers and their increased production and utilization have played a great role in increasing crop yield and in meeting the food demands resulting from population growth. Nitrate (NO 3 ) is the common form of nitrogen absorbed by plants. It has high water solubility and low retention by soil particles, making it prone to leaching and mobilization by surface water, which can seriously contaminate biological environments and affect human health. Few methods exist to measure nitrate in the soil. The development of ion selective sensors provides knowledge about the dynamics of nitrate in the soil in real time, which can be very useful for nitrate management. The objective of this study is to analyze the performance of three commercial probes (Nutrisens, RIKA and JXCT) under the same conditions. The performance was analyzed with respect to electrical conductivity (EC) (0-50 mS/cm) and nitrate concentration in aqueous solution and in sand (0-180 ppm NO - ) at 35% volumetric soil moisture. Differences were shown among probes when studying their response to variations of the EC and, notably, only the Nutrisens probe provided coherent accurate measurements. In the evaluation of nitrate concentration in liquid solution, all probes proved to be highly sensitive. Finally, in the evaluation of all probes' response to modifications in nitrate concentration in sand, the sensitivity decreased for all probes, with the Nutrisens probe the most sensitive and the other two probes almost insensitive.3 - ) at 35% volumetric soil moisture. Differences were shown among probes when studying their response to variations of the EC and, notably, only the Nutrisens probe provided coherent accurate measurements. In the evaluation of nitrate concentration in liquid solution, all probes proved to be highly sensitive. Finally, in the evaluation of all probes' response to modifications in nitrate concentration in sand, the sensitivity decreased for all probes, with the Nutrisens probe the most sensitive and the other two probes almost insensitive.

The quantification of the effects of global changes on soil nutrients is crucial for the prediction of future terrestrial ecosystem changes. Combined with 100 articles and 1129 observations from all over China, the meta-analysis method was applied to explore the effects of various global change factors on soil nutrients, including precipitation change, nitrogen addition, warming, and carbon dioxide (CO 2 ) concentration rise. Results indicated that among all the individual drivers, soil nutrients are most sensitive to N addition. Significant positive effects of N addition on carbon concentration (+4.6%), nitrogen concentration (+6.1%), organic carbon (+5.0%), and available nitrogen (+74.6%) were observed considering all the land-use types. The results highlighted that the combined and interactive effects of multiple global change factors on soil nutrients were of great significance. The interaction of the two drivers is usually additive, followed by antagonism and synergy. Our findings contribute to better understanding of how soil nutrients will change under future global change.

Visible and near-infrared spectroscopy (VIS-NIRS) is a fast and simple method increasingly used in soil science. This study aimed to investigate VIS-NIRS applicability to predict soil black carbon (BC) content and the method's suitability for rapid BC-level screening. Forty-three soil samples were collected in an agricultural area remaining under strong industrial impact. Soil texture, pH, total nitrogen (N tot ) and total carbon (C tot ), soil organic carbon (SOC), soil organic matter (SOM), and BC were analyzed. Samples were divided into three classes according to BC content (low, medium, and high BC content) and scanned in the 350-2500 nm range. A support vector machine (SVM) was used to develop prediction models of soil properties. Partial least-square with SVM (PLS-SVM) was used to classify samples for screening purposes. Prediction models of soil properties were at best satisfactory (N tot : R 2 = 0.76, RMSE CV = 0.59 g kg -1 , RPIQ = 0.65), due to large kurtosis and data skewness. The RMSE CV were large (16.86 g kg -1 for SOC), presumably due to the limited number of samples available and the wide data spread. Given our results, the VIS-NIRS method seems efficient for classifying soil samples from an industrialized area according to BC content level (training accuracy of 77% and validation accuracy of 81%).

Different land use practices may improve soil quality or lead to soil deterioration. Recently, environmental problems, such as heavy pollution and soil erosion, have led to serious land degradation in the Taojia River basin. In this study, we explored the soil fertility characteristics (mechanical composition; pH; soil organic matter (SOM); soil total nitrogen (TN); and the activity of four enzymes, i.e., urease, hydrogen peroxide, alkaline phosphatase, and sucrose enzymes) under different types of land use in the Taojia River basin. Soil samples were taken from 0-10 cm, 10-20 cm, and 20-40 cm depths from four different land use types that were widely used in the Taojia river basin, including cultivated land, vegetable fields, woodlands, and wastelands. The results showed that the soil enzyme activity and the constituents of the soil were closely related and significantly affected each other ( p < 0.05). Woodland soil exhibited the highest content of SOM in all soil depths. Soil total nitrogen mainly depended on the accumulation of biomass and the decomposition intensity of organic matter, so the changes in TN followed the trends of the changes in SOM. Woodland soil showed an improved mechanical composition. We were also able to observe an increased clay content in woodland soil. Woodland soil also exhibited the reversal of soil desertification and an increase in nutrient/water retention capacity. Therefore, an increase in woodland areas would be an appropriate goal in terms of land use in order to improve the eco-environmental quality of the Taojia River basin.

This study investigated the effect of different doses of fertilization with biomass combustion ash ( Salix viminalis L. willow) on changes in the biological, chemical, and physical properties of soil. The experiment was carried out on podzolic and chernozem soils in a one-way field experiment (fertilization dose: control (without fertilization), NPK (nitrogen (N), phosphorus (P) and potassium (K)), 100, 200, 300, 400, 500 kg K 2 O ha -1 ). The biomass ash was characterized by a pH value of 12.83 ± 0.68 and a high content of macronutrients. The samples were collected from 0-5, 10-15, and 20-25 cm soil layers under the cultivation of spring barley ( Hordeum vulgare L) cv. Planet in April and August 2021. Mass spectrometry (MALDI-TOF MS) was used for microbiological analyses, which revealed the presence of 53 culturable species from 11 genera: Bacillus, Pseudomonas, Paenibacillus, Lysinibacillus, Pseudarthrobacter, Arthrobacter, Staphylococcus, Paenarthrobacter, Micrococcus, Rhodococcus , and Flavobacterium. The podzolic and chernozem soils exhibited the presence of 28 and 44 culturable species, respectively. The study showed an increase in the number of microorganisms in the top layer of the soil profile. However, the number of bacteria decreased at the depths of 10-15 cm and 20-25 cm. With depth, the bulk density (BD) and moisture increased.

Traditional soil nitrogen detection methods have the characteristics of being time-consuming and having an environmental pollution effect. We urgently need a rapid, easy-to-operate, and non-polluting soil nitrogen detection technology. In order to quickly measure the nitrogen content in soil, a new method for detecting the nitrogen content in soil is presented by using a near-infrared spectrum technique and random forest regression (RF). Firstly, the experiment took the soil by the Xunsi River in the area of Hubei University of Technology as the research object, and a total of 143 soil samples were collected. Secondly, NIR spectral data from 143 soil samples were acquired, and chemical and physical methods were used to determine the content of nitrogen in the soil. Thirdly, the raw spectral data of soil samples were denoised by preprocessing. Finally, a forecast model for the soil nitrogen content was developed by using the measured values of components and modeling algorithms. The model was optimized by adjusting the changes in the model parameters and Gini coefficient (∆Gini), and the model was compared with the back propagation (BP) and support vector machine (SVM) models. The results show that: the RF model modeling set prediction R 2 C is 0.83, and the RMSEP is 0.141; the detection of the soil nitrogen content can be realized by using a near-infrared spectrum technique and random forest algorithm, and its prediction accuracy is better than that of the BP and SVM models; using ∆ Gini to optimize the RF modeling data, the spectral information of the soil nitrogen content can be extracted, and the data redundancy can be reduced effectively.2 P is 0.83, and the RMSEP is 0.141; the detection of the soil nitrogen content can be realized by using a near-infrared spectrum technique and random forest algorithm, and its prediction accuracy is better than that of the BP and SVM models; using ∆ Gini to optimize the RF modeling data, the spectral information of the soil nitrogen content can be extracted, and the data redundancy can be reduced effectively.

Soil moisture, soil organic carbon, and nitrogen content prediction are considered significant fields of study as they are directly related to plant health and food production. Direct estimation of these soil properties with traditional methods, for example, the oven-drying technique and chemical analysis, is a time and resource-consuming approach and can predict only smaller areas. With the significant development of remote sensing and hyperspectral (HS) imaging technologies, soil moisture, carbon, and nitrogen can be estimated over vast areas. This paper presents a generalized approach to predicting three different essential soil contents using a comprehensive study of various machine learning (ML) models by considering the dimensional reduction in feature spaces. In this study, we have used three popular benchmark HS datasets captured in Germany and Sweden. The efficacy of different ML algorithms is evaluated to predict soil content, and significant improvement is obtained when a specific range of bands is selected. The performance of ML models is further improved by applying principal component analysis (PCA), a dimensional reduction method that works with an unsupervised learning method. The effect of soil temperature on soil moisture prediction is evaluated in this study, and the results show that when the soil temperature is considered with the HS band, the soil moisture prediction accuracy does not improve. However, the combined effect of band selection and feature transformation using PCA significantly enhances the prediction accuracy for soil moisture, carbon, and nitrogen content. This study represents a comprehensive analysis of a wide range of established ML regression models using data preprocessing, effective band selection, and data dimension reduction and attempt to understand which feature combinations provide the best accuracy. The outcomes of several ML models are verified with validation techniques and the best- and worst-case scenarios in terms of soil content are noted. The proposed approach outperforms existing estimation techniques.

Soil phosphorus accumulation resulting in a high risk of phosphorus pollution is due to high multiple vegetable cropping indexes and excessive fertilizer input in protected fields. Therefore, this study explored the bioavailability of soil-accumulated phosphorus to improve fertilization and reduce the risk of soil phosphorus contamination in protected fields. A field trial was performed in Yanbian Prefecture, China to study the phosphorus bioavailability after continuous spinach planting without phosphate fertilizer applications. Results indicated that with increasing numbers of planting stubbles, soil inorganic phosphorus and occluded phosphorus changed little, while water-soluble and loose phosphorus, aluminum-phosphate, iron-phosphate, and calcium-phosphorus decreased first and then increased. Soil available phosphorus declined linearly. For planting spinach in protected fields, the threshold of soil phosphorus deficiency is 200 mg kg -1 . A soil phosphorus supply potential model was established between x (the soil available phosphorus) and y (the numbers of planting stubbles): y = 6.759 + 0.027 x , R = 0.99, which can be used to predict how planting stubbles are needed to raise the soil available phosphorus above the critical value of phosphorus deficiency for spinach. These results will provide the theoretical guidance for rational phosphorus fertilizer applications and control agricultural, non-point pollution sources in protected fields.

Soil microbial biomass (SMB) and soil microbial communities (SMCs) are the key factors in soil health and agricultural sustainability. We hypothesized that low bioavailable carbon (C) and energy were the key limiting factors influencing soil microbial growth and developed a new fertilization system to address this: the simultaneous application of mineral fertilizers and high-energy-density organic amendments (HED-OAs). A microcosm soil incubation experiment and a Brassica rapa subsp. chinensis pot culture experiment were used to test the effects of this new system. Compared to mineral fertilizer application alone, the simultaneous input of fertilizers and vegetable oil (SIFVO) achieved a bacterial abundance, fungal abundance, and fungal:bacterial ratio that were two orders of magnitude higher, significantly higher organic C and nitrogen (N) content, significantly lower N loss, and nearly net-zero N 2 O emissions. We proposed an energy and nutrient threshold theory to explain the observed bacterial and fungal growth characteristics, challenging the previously established C:N ratio determination theory. Furthermore, SIFVO led to microbial community improvements (an increased fungal:bacterial ratio, enriched rhizosphere bacteria and fungi, and reduced N-transformation bacteria) that were beneficial for agricultural sustainability. A low vegetable oil rate (5 g/kg) significantly promoted Brassica rapa subsp. chinensis growth and decreased the shoot N content by 35%, while a high rate caused severe N deficiency and significantly inhibited growth of the crop, confirming the exceptionally high microbial abundance and indicating severe microbe-crop competition for nutrients in the soil.

To explore the correlations between nutrients and stoichiometric characteristics in the rhizosphere and bulk soils of understory Smilax china L. in forest ecosystems at different altitudes and to clarify the rhizosphere effect of understory vegetation in forest ecosystems and its response strategy to altitude, providing a theoretical basis for better forest ecological environment protection and high-quality development in Fanjing Mountain. Understory Smilax china L. at four different altitudes were selected, with the differences and influencing factors of carbon (C), nitrogen (N), phosphorus (P) and potassium (K) mass fractions and stoichiometric ratios in their rhizosphere and bulk soils analyzed. The average mass fractions of total C, total N and alkali-hydrolyzed N in the rhizosphere and bulk soils of Smilax china L. at different altitudes were 224.43 and 181.55 g·kg -1 ; 9.56 and 6.81 g·kg -1 ; and 648.19 and 600.70 g·kg -1 , respectively. The rhizosphere effect of Smilax china L. was significant at altitudes of 500 m and 1000 m but became not so prominent with the rise of altitude. The C:N ratio in the rhizosphere and bulk soils ranged from 19.51 to 39.75 and the C:P ratio ranged from 225.29 to 543.05. C accumulation is greater than N accumulation in the rhizosphere and bulk soils of Smilax china L., and both present P limitation. Based on the comprehensive analysis of the mass fractions and eco-stoichiometric ratios of soil nutrients, the P limitation in Fanjing Mountain forest ecosystem is commonly seen and should be addressed.

The application of iron powder stimulated the growth of iron-reducing bacteria as a respiratory substrate and enhanced their nitrogen (N)-fixing activity in flooded paddy soils. High N fertilization (urea) in the flooded paddy soils has caused adverse environmental impacts such as ammonia (NH 3 ) volatilization, nitrous oxide (N 2 O) emissions, and nitrate (NO 3 - ) leaching. This study aims to investigate the effects of N fertilization rates in combination with an iron amendment on rice yields and N losses from flooded paddy fields. We performed a 2-year field plot experiment with traditional rice-wheat rotation in China's Yangtze River Delta. The investigation consisted of seven treatments, including 100%, 80%, 60%, and 0% of the conventional N (urea and commercial organic manure) fertilization rate, and 80%, 60%, and 0% of the conventional N with the iron powder (≥99% purity) amendment. The rice yields decreased with a reduction in the conventional N fertilization rate, whereas they were comparable after the iron application under the 80% and 60% conventional N rate. The critical N losses, including NH 3 volatilization, N 2 O emissions, and NO 3 - and NH 4 volatilization. The iron amendment significantly increased soil Fe + leaching, generally decreased with a reduction in the conventional N fertilization rate. These N losses were significantly greater after the iron amendment compared with the non-amended treatments under the 80% and 60% conventional N fertilization rate in the first rice-growing season. However, it was comparable between the iron-amended and the non-amended treatments in the second season. Furthermore, NO 3 - leaching was the most significant N loss throughout the two rice seasons, followed by NH 3 volatilization. The iron amendment significantly increased soil Fe 2+ content compared with the non-amended treatments irrespective of N fertilization, suggesting the reduction of amended iron by iron-reducing bacteria and their simultaneous N fixation. A combination of the iron application with 60-80% of the conventional N fertilization rate could maintain rice yields similar to the conventional N fertilization rate while reducing the critical N losses in the flooded paddy field tested in this study. Our study leads to the establishment of novel and practical rice cultivation, which is a step towards the development of green agriculture.

Vegetation restoration is considered a potentially useful strategy for controlling soil erosion and improving soil organic carbon (SOC) in arid and semiarid ecosystems. However, there is still debate regarding which vegetation restoration type is the best choice. In this study, four vegetation restoration types (i.e., grasslands, shrubs, forests and mixed forests) converted from sloping farmlands were selected to explore the SOC variation among the four types and to investigate which soil factors had the greatest effect on SOC. The results showed while the magnitude of effect differed between vegetation restoration type, all studied systems significantly increased SOC and labile organic carbon contents (p < 0.01), soil nutrients such as total nitrogen (TN) (p < 0.01), available nitrogen (AN) (p < 0.01), total phosphorus (TP) (p < 0.05) and available phosphorus (AP) (p < 0.05), soil enzyme activities such as phosphatase (p < 0.01), soil microbial biomass carbon (MBC) (p < 0.05), and basal respiration (BR) (p < 0.05), but had significant negative correlationswith polyphenol oxidase (p < 0.05). However, the effects of vegetation restoration of farmland converted to natural grasslands, shrubs, forests and mixed forests varied. Among the types studied, the mixed forests had the largest overall positive effects on SOC overall, followed by the natural grasslands. Soil nutrients such as N and P and soil microbial activities were the main factors that affected SOC after vegetation restoration. Mixed forests such as Robinia pseudoacacia and Caragana korshinskii are the best choice for farmland conversion on the central of the Loess Plateau.

Soil erodibility (K factor) and saturated hydraulic conductivity (Ks) are essential indicators for the estimation of erosion intensity and can potentially influence soil nutrient losses, making them essential parameters for the evaluation of land reclamation quality. In this study, 132 soil samples from 22 soil profiles were collected to measure soil physicochemical properties (e.g., particle size distribution, bulk density and soil nutrient content) and calculate the K factor and Ks of reclaimed soils across the South Dump of the Pingshuo opencast coalmine in the Loess Plateau, China. Geostatistical analysis and the kriging interpolation were employed to quantify the spatial variations in the K factor and Ks in different layers. The results show that the K factor at 0−10 cm is obviously lower than that of other soil layers due to the external input of organic matter, while the Ks tends to decrease along with soil depth. Horizontally, the K factor at 0−10 cm and 50−60 cm shows a decreasing tendency from west to east, while that of other soil layers seems not to show any spatial distribution pattern along latitude or longitude. Meanwhile, the Ks at 0−10 cm presents a striped distribution pattern, while that of other soil layers shows a patchy pattern. On the other hand, the independent-sample t-test and Spearman’s correlation analysis were carried out to determine the effects of soil erodibility on total nitrogen (TN), soil organic matter (SOM), available phosphorus (AP) and potassium (AK). Overall, the K factor is negatively correlated with TN (r = −0.362, p < 0.01) and SOM contents (r = −0.380, p < 0.01), while AP and AK contents are mainly controlled by Ks. This study provides insight on the optimization of reclamation measures and the conservation of soil nutrients in reclaimed land of similar ecosystems.

Rapid and accurate determination of soil nitrogen supply capacity by detecting nitrogen content plays an important role in guiding agricultural production activities. In this study, near-infrared hyperspectral imaging (NIR-HSI) combined with two spectral preprocessing algorithms, two characteristic wavelength selection algorithms and two machine learning algorithms were applied to determine the content of soil nitrogen. Two types of soils (laterite and loess, collected in 2020) and three types of nitrogen fertilizers, namely, ammonium bicarbonate (ammonium nitrogen, NH 4 -N), sodium nitrate (nitrate nitrogen, NO 3 -N) and urea (urea nitrogen, urea-N), were studied. The NIR characteristic peaks of three types of nitrogen were assigned and regression models were established. By comparing the model average performance indexes after 100 runs, the best model suitable for the detection of nitrogen in different types was obtained. For NH 4 -N, R 2 p = 0.92, RMSE P = 0.77% and RPD = 3.63; for NO 3 -N, R 2 p = 0.92, RMSE P = 0.57% and RPD = 5.24. It can therefore be concluded that HSI spectroscopy combined with multivariate models is suitable for the high-precision detection of various soil N in soils. This study provided a research basis for the development of precision agriculture in the future.2 p = 0.96, RMSE P = 0.57% and RPD = 5.24. It can therefore be concluded that HSI spectroscopy combined with multivariate models is suitable for the high-precision detection of various soil N in soils. This study provided a research basis for the development of precision agriculture in the future.

Soil construction and revegetation are essential for ecological restoration in mining areas. The influence of vegetation on the horizontal and vertical distribution patterns of soil properties should be fully understood. However, most studies on reconstructed soils in mining areas only concentrate on the surface soil, without exploring the vertical variations in soil properties. Overall, this study aims to explore the potential mechanisms by which surface vegetation exerts some influence on the spatial distribution of soil physicochemical properties, and to provide some insight into revegetation and soil reclamation in mining areas. Descriptive statistics and one-way analysis of variance (one-way ANOVA) were employed to evaluate the differences in the soil physicochemical properties in horizontal and vertical directions under different land-use types in the south dump of Antaibao opencast mine in Pingshuo, Shanxi Province, China. The main results of this study are as follows: (1) In the horizontal direction, except for the strong variation (variation coefficient ≥ 100%) in soil organic matter (SOM) content at some depths, the degree of variation in other soil physicochemical properties at various depths was moderate or weak (variation coefficient < 100%). The soil physicochemical properties gradually remained constant after years of reclamation. In the vertical direction, the soil bulk density (SBD), soil porosity, SOM content, soil C/N ratio, soil total nitrogen (STN) content, soil available phosphorus (SAP) content, and soil available potassium (SAK) content showed significant variations ( p < 0.05) between soil depths. In contrast, no significant difference was found for other physicochemical properties. (2) The SBD, STN, SAK, soil porosity, and soil clay content were significantly different ( p < 0.05) under different vegetation cover types, but the influence of vegetation on other soil physicochemical properties seemed to be limited. The results reveal that trees have a stronger ability to reduce soil grain sizes and enhance SAP contents than shrubs or herbs; however, the beneficial effects of herbs on the physicochemical properties of shallow soil are more obvious than those of trees and shrubs. (3) This study indicates that more shrubs and trees should be planted in the areas with low vegetation coverage, and more measures should be taken to improve soil physicochemical properties in order to prevent the occurrence of large-scale degradation. The reconstruction of soil structure should be preferentially considered in the process of soil reconstruction and revegetation in areas under similar conditions. Herbs should first be planted in the early reclamation stage. At the same time, shrubs or trees can be adopted in the middle and late stages of vegetation reconstruction in order to achieve comprehensive revegetation.

In recent years, highway construction in the Qinghai-Tibet Plateau (QTP) has developed rapidly. When the highway passes through grassland, the soil, vegetation, and ecological environment along the line are disturbed. However, the impact on soil bacteria is still unclear. Soil bacteria play an important role in the ecological environment. The Qinghai-Tibet Highway (QTH) was selected as the research object to explore the changes in bacterial community structure, vegetation, soil, and other indicators. The results showed that the highway-related activities increased the degradation of vegetation along the road, significantly changed the physical and chemical properties of soil, and caused heavy metal pollution. These environmental factors affected the diversity and community structure of soil bacteria. This kind of disturbance shows a trend of gradually increasing from near to far from the highway. Gemmatimonas , Terrimonas , Nitrospira and Bacillus are more tolerant to environmental changes along the highway, while Barnesiella , and Blastococcus are more sensitive. The content of nitrate decreased and the content of ammonium nitrogen increased in the disturbed area, increasing the abundance of nitrifying bacteria. Therefore, the main factor of the disturbance of the QTH on the grassland is the decline of soil nutrient content, and the supplement of soil nutrients such as carbon and nitrogen should be taken into account in the process of ecological restoration of grassland along the line.

The impact of chemical to organic fertilizer substitution on soil labile organic and stabilized N pools under intensive farming systems is unclear. Therefore, we analyzed the distribution of soil total N (STN), particulate organic N (PON), microbial biomass N (MBN), dissolved organic N (DON), and mineral N (NO 3 - and NH 4 + ) levels down to 100 cm profile under wheat-maize rotation system in northern China. The experiment was established with four 270 kg ha -1 N equivalent fertilizer treatments: Organic manure (OM); Organic manure with nitrogen fertilizer (OM + NF); Nitrogen fertilizer (NF); and Control (CK). Results found that the OM and OM + NF treatments had significantly higher STN, PON, MBN, DON, and NO 3 - contents in 0-20 cm topsoil depths. Conversely, the NF treatment resulted in the highest ( p < 0.01) under OM treatment. The correlations between STN and its fractions were positively significant at 0-10 and 10-20 cm topsoil depths. Our results suggest that partial substitution of chemical fertilizer with organic manure could be a sustainable option for soil N management of intensive farming systems.3 - depositions in 40-100 cm subsoil depths. The NH 4 + contents in selected profile depths were significantly highest ( p < 0.01) under OM treatment. The correlations between STN and its fractions were positively significant at 0-10 and 10-20 cm topsoil depths. Our results suggest that partial substitution of chemical fertilizer with organic manure could be a sustainable option for soil N management of intensive farming systems.

As one of the nitrogen (N) limitation ecosystems, alpine meadows have significant effects on their structure and function. However, research on the response and linkage of vegetation-soil to short-term low-level N deposition with rhizosphere processes is scant. We conducted a four level N addition (0, 20, 40, and 80 kg N ha - 1 ) field experiment in an alpine meadow on the Qinghai-Tibetan Plateau (QTP) from July 2014 to August 2016. We analyzed the community characteristics, vegetation (shoots and roots), total carbon (TC), nutrients, soil (rhizosphere and bulk) properties, and the linkage between vegetation and soil under different N addition rates. Our results showed that (i) N addition significantly increased and decreased the concentration of soil nitrate nitrogen (NO -1 -N) and ammonium nitrogen, and the soil pH, respectively; (ii) there were significant correlations between soil (rhizosphere and bulk) NO 3 -N and total nitrogen (TN), and root TN, and there was no strong correlation between plant and soil TC, TN and total phosphorus, and their stoichiometry under different N addition rates. The results suggest that short-term low-N addition affected the plant community, vegetation, and soil TC, TN, TP, and their stoichiometry insignificantly, and that the correlation between plant and soil TC, TN, and TP, and their stoichiometry were insignificant.- -N) and ammonium nitrogen, and the soil pH, respectively; (ii) there were significant correlations between soil (rhizosphere and bulk) NO 3 - -N and total nitrogen (TN), and root TN, and there was no strong correlation between plant and soil TC, TN and total phosphorus, and their stoichiometry under different N addition rates. The results suggest that short-term low-N addition affected the plant community, vegetation, and soil TC, TN, TP, and their stoichiometry insignificantly, and that the correlation between plant and soil TC, TN, and TP, and their stoichiometry were insignificant.

Isotopocule signatures of N 2 O (δ 15 N bulk , δ 18 O and site preference) are useful for discerning soil N 2 O source, but sometimes, N fertilizer is needed to ensure that there is enough N 2 O flux for accurate isotopocule measurements. However, whether fertilizer affects these measurements is unknown. This study evaluated a gradient of NH 4 NO 3 addition on N 2 O productions and isotopocule values in two acidic subtropical soils. The results showed that N 2 O production rates obviously amplified with increasing NH 4 NO 3 ( p < 0.01), although a lower N 2 O production rate and an increasing extent appeared in forest soil. The δ 15 N bulk of N 2 O produced in forest soil was progressively enriched when more NH 4 NO 3 was added, while becoming more depleted of agricultural soil. Moreover, the N 2 O site preference (SP) values collectively elevated with increasing NH 4 NO 3 in both soils, indicating that N 2 O contributions changed. The increased N 2 O production in agricultural soil was predominantly due to the added NH 4 NO 3 via autotrophic nitrification and fungal denitrification (beyond 50%), which significantly increased with added NH 4 NO 3 , whereas soil organic nitrogen contributed most to N 2 O production in forest soil, probably via heterotrophic nitrification. Lacking the characteristic SP of heterotrophic nitrification, its N 2 O contribution change cannot be accurately identified yet. Overall, N fertilizer should be applied strictly according to the field application rate or N deposition amount when using isotopocule signatures to estimate soil N 2 O processes.

Fertilization can significantly affect the quality of crop and soil. To determine the effects of long-term fertilization on crop yield and carbon:nitrogen:phosphorus (C:N:P) stoichiometry in soil, a study was conducted on the terraced fields of the Loess Plateau from 2007 to 2019. Nine fertilization treatments were included: no fertilizer; organic fertilizer (O); organic and nitrogen fertilizers (ON); organic, nitrogen, and phosphorus fertilizers (ONP); organic and phosphorus fertilizers (OP); phosphorus and nitrogen fertilizers; potash and nitrogen fertilizers; potash, nitrogen, and phosphorus fertilizers; and potash and phosphorus fertilizers. Under these treatments except for CK and PK, crop yields initially decreased but later increased. The nutrient content and C:N:P stoichiometry increased in soil depth of 0-20 cm. The soil available nutrients did not change significantly with the duration of fertilization. The O, ON, ONP, and OP had the most evident effect on the enhancement of soil nutrient content, whereas O and ON had the most evident effect on the increase in soil organic carbon (SOC):total phosphorus (TP) and total nitrogen (TN):TP. In soil depth of 0-20 cm, crop yield, SOC:TN, SOC:TN, SOC:TP, and TN:TP significantly correlated with soil nutrients. This study indicated that long-term fertilization can effectively improve crop yield, soil fertility, and soil C:N:P stoichiometry. Meanwhile, the single application of an organic fertilizer or the combination of organic and nitrogen fertilizers can improve the condition of nitrogen limitation in arid and semi-arid areas.

Understanding the deposition and tracking the source of soil organic carbon (C) and nitrogen (N) within agricultural watersheds are critical for assessing soil C and N budgets and developing watershed-specific best management practices. Few studies have been conducted and reported on highly eroded hilly-gully watersheds. In this field study, a constructed dam-controlled hilly-gully watershed in northeastern China was selected to identify the sources of soil C and N losses. Soils at various land uses and landscape positions, and sediments near the constructed dam, were collected and analyzed for selected physiochemical properties, total organic carbon (TOC), total nitrogen (TN), and stable isotopes ( 13 C and 15 N). Soil C and N loss and deposition in the watershed were assessed and the relative contributions of each source quantified by a stable isotope mixing model (SIAR). Results indicated that soil C loss was primarily from cropland, accounting for 58.75%, followed by gully (25.49%), forest (9.2%), and grassland (6.49%). Soil N loss was similar to soil C, with cropland contribution of 80.58%, gully of 10.30%, grassland of 7.54%, and forest of 1.59%. The C and N deposition gradually decreased along the direction of the runoff pathway near the constructed dam, and the deposited C and N from cropland and gullies showed an order: middle-dam > bottom-dam > upper-dam and upper-dam > bottom-dam > middle-dam, respectively. A high correlation between soil TOC or TN and the sediment properties suggested that the deposition conditions could be the major factors affecting the C and N pools in the sedimentary zones. This study would provide a scientific insight to develop effective management practices for soil erosion and nutrient loss control in highly eroded agriculture watersheds.

Understanding the spatial pattern of soil chemical properties (SCPs) together with topological factors and soil management practices is essential for land management. This study examines the spatial changes in soil chemical properties and their impact on China's subtropical mountainous areas. In 2007 and 2017, 290 and 200 soil samples, respectively, were collected in Hefeng County, a mountainous county in central China. We used descriptive statistics and geostatistical methods, including ANOVA, semivariance, Moran's I, and fractal dimensions, to analyze the characteristics and spatial autocorrelation changes in soil organic matter (OM), available phosphorus (AP), available potassium (AK), and pH value from 2007 to 2017. We explored the relationship between each SCP and the relationship between SCPs with topographic parameters, soil texture, and cropping systems. The results show that the mean value of soil OM, AP, AK, and pH in Hefeng increased from 2007 to 2017. The spatial variation and spatial dependency of each SCP in 2007, excluding AP and AK in 2007, were higher than in 2017. The soil in areas with high topographic relief, profile curvature, and planform curvature had less AP, AK, and pH. Soil at higher elevation had lower OM (r = -0.197, p < 0.01; r = -0.334, p < 0.01) and AP (r = -0.043, p < 0.05; r = -0.121, p < 0.05) and higher AK (r = -0.305, p < 0.01; r =0.408, p < 0.01) in 2007 and 2017. Soil OM and AK in 2007 were significantly ( p < 0.05) correlated with soil texture ( p < 0.05). In contrast, oil AP and soil pH in 2007 and all SCPs in 2017 were poorly correlated with soil texture. The cropping systems played an important role in affecting all SCPs in 2007 ( p < 0.01), while they only significantly affected AK in 2017 ( p < 0.05). Our findings demonstrate that both topological factors, that is, the changes in cropping management and the changes in acid rain, impact soil chemical properties. The local government should place more focus on reducing soil acid amounts, soil AP content, and soil erosion by improving water conservancy facilities.

The soil and human health issues are closely linked. Properly managed nitrogen (N) does not endanger human health and increases crop production, nevertheless when overused and uncontrolled, can contribute to side effects. This research was intended to highlight that there is a need for carrying out monitoring studies in agricultural areas in order to expand the available knowledge on the content of N forms in agricultural lands and proper management in farming practice. The impact of two types of fertilization, concerning spatially variable (VRA) and uniform (UNI) N dose, on the distribution of N forms in soils was analyzed. The analysis was performed on the basis of soil monitoring data from agricultural fields located in three different experimental sites in Poland. The analyses performed at selected sites were supported by statistical evaluation and recognition of spatial diversification of N forms in soil. It was revealed that the movement of unused N forms to deeper parts of the soil, and therefore to the groundwater system, is more limited due to VRA fertilization. Finally, it was also concluded that the management in agricultural practice should be based on the prediction of spatial variability of soil properties that allow to ensure proper application of N fertilizers, resulting in the reduction of possible N losses.

We hypothesized that female and male individuals of the dioecious tree species, Juniperus communis , exhibit different strategies of resource allocation when growing under stress conditions. To test this hypothesis, we performed a two-year pot experiment on plants exposed to different levels of nutrient availability. Analysis of the plants revealed a higher concentration of carbohydrates, carbon, and phenolic compounds in needles of female plants, indicating that females allocate more resources to storage and defense than males. This difference was independent of nutrient availability. Differences in carbohydrates levels between the sexes were most often significant in June, during the most intensive phase of vegetative growth in both sexes, but could also be attributed to female resources investment in cone development. A higher level of nitrogen and other macroelements was observed in males than in females, which may have been connected to the accumulation of resources (nitrogen) for pollen grain production in males or greater allocation of these elements to seeds and cones in females. The interaction between sex and soil fertilization for the C:N ratio may also indicate sex-specific patterns of resource allocation and utilization, which is impacted by their availability during specific periods of J. communis annual life cycle.

Due to the impacts of unwise industrial agriculture, extreme precipitation events are increasing in frequency and are accelerating the process of global warming in the karst area. The dynamic change in soil organic carbon (SOC) and its driving factors in cultivated land in the last 35 years were studied by using data from the second national soil survey of China and measurements made in 2015. The results indicated that the SOC per unit area of cultivated land increased by 32.45 × 10 3 t in the last 35 years in the study area, exhibiting basically the same levels and a slight increasing trend, and the annual average change rate was 0.02 kg C·hm -2 ·a -1 . In terms of spatial distribution, carbon loss areas were mainly concentrated in the middle northern region, western region, and scattered eastern regions of the county. The main factors affecting the change in SOC in the cultivated land in the study area in the last 35 years include nitrogen fertilizer application, stubble, soil thickness, soil total nitrogen, C/N, rock coverage, gravel content, soil organic carbon density (SOCD 1980 ), etc. This study will provide a database for the management of SOC in cultivated land in the future.

The effects of different agronomic practices, such as fertilization regimes, can be experimentally tested in long-term experiments (LTE). Here, we aimed to evaluate the effect of different nitrogen fertilizations on the bacterial microbiota in both rhizosphere and bulk soil of sugar beet, in the Giessen-LTE (Germany). Fertilization treatments included mineral-N, manure, mineral-N + manure and no N-amendment. Metabarcoding and co-occurrence analysis of 16S rRNA genes, qPCR of amoA , nirK , nirS , nosZ -I and nosZ -II genes and soil physico-chemical analyses were performed. The effect of the fertilization treatments was more evident in the bulk soil, involving 33.1% of the microbiota. Co-occurrence analysis showed a rhizosphere cluster, dominated by Proteobacteria, Actinobacteria and Verrucomicrobia (hub taxa: Betaproteobacteriales ) , and a bulk soil cluster, dominated by Acidobacteria , Gemmatominadetes and " Latescibacteria " (hub taxa: Acidobacteria ). In the bulk soil, mineral N-fertilization reduced nirK , amoA , nosZ -I and nosZ -II genes. Thirteen Operational taxonomic units (OTUs) showed 23 negative correlations with gene relative abundances. These OTUs likely represent opportunistic species that profited from the amended mineral-N and outgrew the species carrying N-cycle genes. Our results indicate trajectories for future research on soil microbiome in LTE and add new experimental evidence that will be helpful for sustainable management of nitrogen fertilizations on arable soils.

Soil erosion has become a serious ecological problem in many catchments. Soil erodibility K factor can be estimated based on a series of soil properties, however, the identification of dominant soil properties that affect K factor prediction at different soil types has been little concerned. In this study, 3 soil profiles from the Jiulongjiang River Catchment (JRC) of granite region in Fujian province and 18 soil profiles from the Chenqi Catchment (CC) of karst region in Guizhou province were selected. Soil properties, including soil particle size distribution, soil organic carbon (SOC) and soil organic nitrogen (SON) content, and soil pH, were determined, and the K factors were estimated in the erosion productivity impact calculator (EPIC) model. The soils in the granite region were characteristic for coarse texture, low SOC and SON, and strong acidity compared with limestone soils. Although the K factors in both regions ranged from 0.009 to 0.018, they were overestimated in limestone soils due to frequent soil aggregation, which enhanced soil permeability, hence reduced soil erodibility. The results of principal component analysis (PCA) and structural equation model (SEM) showed that (1) K factor estimation in the soils of the granite region mainly depended on soil texture, of which silt was the most important factor; (2) while K factor in limestone soils was mainly controlled by soil organic matter (SOM) content, other soil properties, including soil pH, clay and silt contents, could indirectly affect prediction of K factor by affecting SOM accumulation., Competing Interests: The authors declare no conflict of interest.

Population growth and social changes have recently contributed to an exaggerated increase in kitchen wastes in China. Vermicomposting has recently been recognized as an effective and eco-friendly method of organic waste treatment through the combination of earthworms and microbes. However, the influence of salt in kitchen wastes on vermicomposting have been unknown. The goal of this study was to analyze the influence of different salinities on earthworms ( Eisenia fetida ) and the products during the vermicomposting of kitchen wastes. In our research, kitchen wastes were divided into four different salinities: 0% (A), 0.1% (B), 0.2% (C) and 0.3% (D). The chemical characters of substrates and earthworm growth were measured on the 14th day and the 28th day of composting. Our results show that the high salinity (measured >0.2%) prevented earthworms from properly growing and had negative effects on quality of products in composting. T2 (measured salinity = 0.2%) had the highest average body weight, nitrate nitrogen, and available phosphorus. Thus, the salinity of kitchen wastes should be pretreated to less than 0.2% before vermicomposting.

Soil aggregate stability can indicate soil quality, and affects soil organic carbon (SOC) and soil organic nitrogen (SON) sequestration. However, for erodible soils, the effects of soil aggregate stability on SOC and SON under land use change are not well known. In this study, soil aggregate distribution, SOC and SON content, soil aggregate stability, and soil erodibility were determined in the soils at different depths along the stages following agricultural abandonment, including cropland, abandoned cropland, and native vegetation land in an erodible region of Southwest China. Soil aggregation, soil aggregate stability, and SOC and SON content in the 0-20 cm depth soils increased after agricultural abandonment, but soil texture and soil erodibility were not affected by land use change. Soil erodibility remained in a low level when SOC contents were over 20 g·kg -1 , and it significantly increased with the loss of soil organic matter (SOM). The SOC and SON contents increased with soil aggregate stability. This study suggests that rapidly recovered soil aggregate stability after agricultural abandonment promotes SOM sequestration, whereas sufficient SOM can effectively maintain soil quality in karst ecological restoration.

Soil nitrogen is the key parameter supporting plant growth and development; it is also the material basis of plant growth. An accurate grasp of soil nitrogen information is the premise of scientific fertilization in precision agriculture, where near-infrared (NIR) spectroscopy is widely used for rapid detection of soil nutrients. In this study, the variation law of soil NIR reflectivity spectra with soil particle sizes was studied. Moreover, in order to precisely study the effect of particle size on soil nitrogen detection by NIR, four different spectra preprocessing methods and five different chemometric modeling methods were used to analyze the soil NIR spectra. The results showed that the smaller the soil particle sizes, the stronger the soil NIR reflectivity spectra. Besides, when the soil particle sizes ranged 0.18-0.28 mm, the soil nitrogen prediction accuracy was the best based on the partial least squares (PLS) model with the highest Rp 2 of 0.983, the residual predictive deviation (RPD) of 6.706. The detection accuracy was not ideal when the soil particle sizes were too big (1-2 mm) or too small (0-0.18 mm). In addition, the relationship between the mixing spectra of six different soil particle sizes and the soil nitrogen detection accuracy was studied. It was indicated that the larger the gap between soil particle sizes, the worse the accuracy of soil nitrogen detection. In conclusion, soil nitrogen detection precision was affected by soil particle sizes to a large extent. It is of great significance to optimize the pre-treatments of soil samples to realize rapid and accurate detection by NIR spectroscopy.

Pavements have remarkable effects on topsoil micro-organisms, but it remains unclear how subsoil microbial communities respond to pavements. In this study, ash trees ( Fraxinus Chinensis ) were planted on pervious pavement (PP), impervious pavement (IPP), and non-pavement (NP) plots. After five years, we determined the soil bacterial community composition and diversity by high-throughput sequencing of the bacterial 16S rRNA gene. The results of our field experiment reveal that the presence of pavement changed soil bacterial community composition and decreased the Shannon index, but had no impact on the Chao 1 at the 0-20 cm layer. However, we achieved the opposite result at a depth of 20-80 cm. Furthermore, there was a significant difference in bacterial community composition using the Shannon index and the Chao 1 at the 80-100 cm layer. Soil total carbon (TC), total nitrogen (TN), available phosphorus (AP), NO 3 -N, and available potassium (AK) were the main factors that influenced soil bacterial composition and diversity across different pavements. Soil bacterial composition and diversity had no notable difference between PP and IPPs at different soil layers. Our results strongly indicate that pavements have a greater impact on topsoil bacterial communities than do subsoils, and PPs did not provide a better habitat for micro-organisms when compared to IPPs in the short term.- -N, and available potassium (AK) were the main factors that influenced soil bacterial composition and diversity across different pavements. Soil bacterial composition and diversity had no notable difference between PP and IPPs at different soil layers. Our results strongly indicate that pavements have a greater impact on topsoil bacterial communities than do subsoils, and PPs did not provide a better habitat for micro-organisms when compared to IPPs in the short term.

Vegetation restoration is an available way to ameliorate degraded lands. In order to study the response of soil microbes to vegetation restoration in coal mining subsidence areas, the composition and distribution of soil microbes were discussed through three plots: unsubsided area (CA), new subsided area (NSA), and old subsided area (OSA) with different vegetation restoration time in Huabei coal mine. Meanwhile, changes in soil catalase and urease activity were explored and the correlation between soil bacteria, fungi, and environmental factors was analysed. The results demonstrated that Nitrospira was the dominant bacteria in all areas sampled. Microorganisms in the 0-20 cm and 40-60 cm soil layers of OSA had the highest Simpson index, whereas the index in NSA was lowest (at all soil depths). The catalase activity in NSA was significantly higher than that in CA, and there was no significant difference in catalase activity with soil depth, while the urease activity declined gradually with increasing soil depth. The urease activity in the 20-60 cm soil layer of NSA and OSA was significantly higher than that of CA. Furthermore, the distribution of bacteria was mainly affected by soil organic matter, available potassium, available phosphorus, and alkali-hydrolyzable nitrogen, whereas pH and catalase activity mainly affected fungal distribution. These results implied that soil catalase activity in NSA and urease activity in the 20-40 cm soil layer of NSA and OSA were significantly enhanced after vegetation restoration, and that long-term plant restoration could improve soil fertility and soil microbial community diversity in coal mining areas.

The conversion of organic wastes into biochar via the pyrolysis technique could be used to produce soil amendments useful as a source of plant nutrients. In this study, we investigated the effects of fruit peels and milk tea waste-derived biochars on wheat growth, yield, root traits, soil enzyme activities and nutrient status. Eight amendment treatments were tested: no amendment (CK), chemical fertilizer (CF), banana peel biochar 1% (BB1 + CF), banana peel biochar 2% (BB2 + CF), orange peel biochar 1% (OB1 + CF), orange peel biochar 2% (OB2 + CF), milk tea waste biochar 1% (TB1 + CF) and milk tea waste biochar 2% (TB2 + CF). The results indicated that chlorophyll values, plant height, grain yield, dry weight of shoot and root were significantly ( p < 0.05) increased for the TB2 + CF treatment as compared to other treatments. Similarly, higher contents of nutrients in grains, shoots and roots were observed for TB2 + CF: N (61.3, 23.3 and 7.6 g kg -1 ), P (9.2, 10.4 and 8.3 g kg -1 ) and K (9.1, 34.8 and 4.4 g kg -1 ). Compared to CK, the total root length (41.1%), surface area (56.5%), root volume (54.2%) and diameter (78.4%) were the greatest for TB2 + CF, followed by BB2 + CF, OB2 + CF, TB1 + CF, BB1 + CF, OB1 + CF and CF, respectively. However, BB + CF and OB + CF treatments increased β-glucosidase and dehydrogenase, but not urease activity, as compared to the TB + CF amendment, while all enzyme activity decreased with the increased biochar levels. We concluded that the conversion of fruit peels and milk tea waste into biochar products contribute the benefits of environmental and economic issues, and should be tested as soil amendments combined with chemical fertilizers for the improvement of wheat growth and grain yield as well as soil fertility status under field conditions.

A comprehensive understanding of the spatial distribution and dynamic changes of soil properties are the basis for sustainable land management. Topography and land use types are key factors affecting soil property variability. This study analyzed the effects of land use types and landscape locations on soil properties, based on data from 111 points of surface soil (0⁻20 cm) in the Zhujiagou catchment on the Loess Plateau of Northwest China. Soil properties include clay, silt, bulk density (BD), soil organic matter (SOM), total nitrogen (TN) and total phosphorus (TP). Land use types include slope farmland (SFL), terrace farmland (TFL), check-dam farmland (CDL), woodland (WL), shrub land (SL) and grassland (GL). Landscape locations include crest (CT), upper slope (US), middle slope (MS), lower slope (LS) and flat valley (FV). Topographical attributes were divided into primary and secondary (or compound) attributes. Correlation analyses were carried out between soil properties and terrain attribute, and multiple-linear regression models were established to estimate soil properties using land use types and topographic attributes as independents. Results indicated that significant differences in soil properties existed between six land use types, except for bulk density. Higher values of clay, silt, SOM and TN occurred in soils from check-dam farmland, but lower values in soils from shrub land. Significant differences among landscape positions were observed for clay, BD, SOM and TN. Clay, SOM and TN contents on flat valley (FV) positions were higher than those of other positions. Different correlations were found between soil properties and terrain attributes. The regression models explained 13% to 63% of the variability of the measured soil properties, and the model for Clay had the highest R² value, followed by TN, silt, BD, SOM and TP. Validation results of the regression models showed that the model was precise for soil bulk density, but the variation was large and a high smoothing effect existed for predicted values of other soil properties. For TP, the predicted result was poor. Further observations suggested that land use was the dominant factor affecting soil chemical properties. But for soil physical properties, especially for BD, topography was the dominant factor.

Ecological stoichiometry has been widely used to determine how plant-soil systems respond to global change and to reveal which factors limit plant growth. Arbuscular mycorrhizal fungi (AMF) can increase plants' uptake of nutrients such as nitrogen (N) and phosphorus (P), thereby altering plant and soil stoichiometries. To understand the regulatory effect of AMF feedback on plants and soil stoichiometry under global change, a microcosm experiment was conducted with warming and N input. The C₄ grass Setaria viridis , C₃ grass Leymus chinensis , and Chenopodiaceae species Suaeda corniculata were studied. The results showed that the mycorrhizal benefits for the C₄ grass S. viridis were greater than those for the C₃ grass L. chinensis , whereas for the Chenopodiaceae species S. corniculata , AMF symbiosis was antagonistic. Under N input and a combination of warming and N input, AMF significantly decreased the N:P ratios of all three species. Under N input, the soil N content and the N:P ratio were decreased significantly in the presence of AMF, whereas the soil C:N ratio was increased. These results showed that AMF can reduce the P limitation caused by N input and improve the efficiency of nutrient utilization, slow the negative influence of global change on plant growth, and promote grassland sustainability.

Phosphorus in agro-ecosystems has attracted much attention due to its impact on the nutrient supply of plants and the risk of loss of non-point source pollution. This study investigated the fraction distribution and release of phosphorus from soil aggregates structure under different land uses (rice, maize and soybean). The soil aggregates were characterized as large macro-aggregates (L-mac, >1 mm), small macro-aggregates (S-mac, 0.25⁻1 mm), micro-aggregates (MIC, 0.053⁻0.25 mm) and silt clay (SC, <0.053 mm) with the wet-sieving method. A sequential chemical extraction scheme was used to separate phosphorus into labile inorganic phosphorus (L-Pi), labile organic phosphorus (L-Po), moderately labile organic phosphorus (Ml-Po), iron-aluminum bound phosphorus (Fe.Al-P), calcium-magnesium bound phosphorus (Ca.Mg-P), humic phosphorus (Hu-P) and residual phosphorus (Re-P). Experimental results indicated that soil aggregates were mainly S-mac and MIC, followed by L-mac and SC, and they accounted for 52.16%, 25.20%, 14.23% and 8.49% in rice fields, 44.21%, 34.61%, 12.88% and 8.30% in maize fields, and 28.87%, 47.63%, 3.52% and 19.99% in soybean fields, respectively. Total nitrogen (TN), soil organic matter (SOM), Fe and Mn in soil aggregate fractions decreased with the reduction in soil aggregate grain-sizes. For phosphorus fractions (P-fractions), Fe.Al-P and Re-P tended to condense in L-mac and S-mac. MIC and SC were the primary carriers of Ca.Mg-P. Adsorption isotherm simulation results demonstrated that L-mac and S-mac have a strong capacity to retain phosphorus. In rice fields, phosphorus bioavailability and utilization rate were high. However, the P-fractions there were easily changed under aerobic-anaerobic conditions. Therefore, the risk of phosphorus loss during drainage should be given considerable attention.

A multi soil layering (MSL) treatment bioreactor was developed aiming at nutrients removal from anaerobically digested swine wastewater (ADSW). The start-up of the MSL bioreactor and its performance in nutrients removal at different hydraulic loading rate (HLR) were investigated. Results showed that the MSL bioreactor was successfully started up after operation for 28 days, and at this time, the removal efficiencies of ammonia-N, total nitrogen (TN) and total phosphorus (TP) in the ADSW reached 63.6%, 58.5%, and 46.5%, respectively. The MSL bioreactor showed a stable performance during the whole working process with varying HLR from 80 to 200 L/(m²·day). Maximum removal efficiencies of ammonia-N, TN and TP were obtained at 160 L/(m²·day), and was appeared as 94.2%, 94.4%, and 92.5%, respectively. It was worth noting that iron scraps were the key factor that enhanced the independent capability of the MSL bioreactor in TP removal, because there was only 21.4⁻25.8% of the TP was removed when the MSL bioreactor run with no iron addition.

Inappropriate grazing management is one of the most common causes of grassland degradation, and thus, an assessment of soil properties under different grazing intensities is critical for understanding its effects on ecosystem nutrient cycling and for formulating appropriate management strategies. However, the responses of certain main elements, including soil carbon, nitrogen, and phosphorus, to grazing in alpine meadow ecosystems remain insufficiently clarified. Here, we measured carbon, nitrogen, and phosphorus contents in the topmost 30 cm of soil in an alpine meadow under three grazing intensities (light, moderate, and heavy) and found clear differences in soil physical and chemical properties among different grazing intensities and soil layers. As grazing intensity increased, soil water content, carbon and nitrogen contents and stocks, and carbon to phosphorus and nitrogen to phosphorus ratios decreased, whereas soil bulk density increased. However, soil phosphorus and carbon to nitrogen ratio remained stable. Our findings highlight the negative impacts of heavy grazing intensity, in terms of soil carbon and nitrogen loss and phosphorus mineralization. Moreover, we emphasize that further related studies are necessary to gain a more comprehensive understanding of the effects of grazing on grassland ecosystems, and thereby provide information for sustainable management practices and eco-compensation policies.

Soil total nitrogen (TN) plays a major role in agriculture, geochemical cycles and terrestrial ecosystem functions. Knowledge regarding the TN distribution is crucial for the sustainable use of soil resources. This paper therefore aims to characterize the spatiotemporal distribution of soil TN and improve the current understanding of how various factors influence changes in TN. Natural characteristics and remote sensing (RS) variables were used in conjunction with the random forest (RF) model to map the TN distribution in a low hilly region of southeastern China in 1979, 2004 and 2014. The means and changes of TN in different geographic regions and farmland protection regions were also analyzed. The results showed that: (1) the TN showed an increasing trend in the early periods and exhibited a decreasing trend from 2004 to 2014; (2) the geographic and RS variables played more important roles in predicting TN distribution than did the other variables; and (3) changes in the fertilization and crop planting structure caused by soil testing and formulated fertilization techniques (STFFT-Soil Testing and Formulated Fertilization Techniques) as well as farmland protection policies influenced the spatiotemporal variability of TN. Evidently, more attention should be focused on improving the quality and soil fertility in the surrounding low mountainous areas.

Long-term unregulated mining of ion-adsorption clays (IAC) in China has resulted in severe ecological destruction and created large areas of wasteland in dire need of rehabilitation. Soil amendment and revegetation are two important means of rehabilitation of IAC mining wasteland. In this study, we used sludge biochar prepared by pyrolysis of municipal sewage sludge as a soil ameliorant, selected alfalfa as a revegetation plant, and conducted pot trials in a climate-controlled chamber. We investigated the effects of alfalfa revegetation, sludge biochar amendment, and their combined amendment on soil physicochemical properties in soil from an IAC mining wasteland as well as the impact of sludge biochar on plant growth. At the same time, we also assessed the impacts of these amendments on the soil microbial community by means of the Illumina Miseq sequences method. Results showed that alfalfa revegetation and sludge biochar both improved soil physicochemical properties and microbial community structure. When alfalfa revegetation and sludge biochar amendment were combined, we detected additive effects on the improvement of soil physicochemical properties as well as increases in the richness and diversity of bacterial and fungal communities. Redundancy analyses suggested that alfalfa revegetation and sludge biochar amendment significantly affected soil microbial community structure. Critical environmental factors consisted of soil available K, pH, organic matter, carbon⁻nitrogen ratio, bulk density, and total porosity. Sludge biochar amendment significantly promoted the growth of alfalfa and changed its root morphology. Combining alfalfa the revegetation with sludge biochar amendment may serve to not only achieve the revegetation of IAC mining wasteland, but also address the challenge of municipal sludge disposal by making the waste profitable., Competing Interests: The authors declare no conflict of interest.

Precipitation is a key environmental factor determining plant community structure and function. Knowledge of how community characteristics and leaf stoichiometric traits respond to variation in precipitation is crucial for assessing the effects of global changes on terrestrial ecosystems. In this study, we measured community characteristics, leaf stoichiometric traits, and soil properties along a precipitation gradient (35-209 mm) in a desert ecosystem of Northwest China to explore the drivers of these factors. With increasing precipitation, species richness, aboveground biomass, community coverage, foliage projective cover (FPC), and leaf area index (LAI) all significantly increased, while community height decreased. The hyperarid desert plants were characterized by lower leaf carbon (C) and nitrogen/phosphorus (N/P) levels, and stable N and P, and these parameters did not change significantly with precipitation. The growth of desert plants was limited more by N than P. Soil properties, rather than precipitation, were the main drivers of desert plant leaf stoichiometric traits, whereas precipitation made the biggest contribution to vegetation structure and function. These results test the importance of precipitation in regulating plant community structure and composition together with soil properties, and provide further insights into the adaptive strategy of communities at regional scale in response to global climate change., Competing Interests: The authors declare no conflict of interest.

Overgrazing is a severe problem in several regions in Northwestern China and has caused serious land degradation. Secondary natural succession plays an important role in the accumulation of soil carbon and nitrogen contents. Estimating the effects of grazing exclusion on soil quality and plant diversity will improve our understanding of the succession process after overgrazing and promote judicious management of degraded pastures. This experiment was designed to measure soil properties and plant diversity following an age chronosequence of grasslands (ages ranged from one year, 12 years, 20 years, and 30 years) in Northwestern China. The results showed that continuous fencing resulted in a considerable increase in plant coverage, plant biomass (above- and below-ground biomass), and plant diversity, which can directly or indirectly improve the accumulation of soil organic carbon and total nitrogen content. The plant coverage and the above- and below-ground biomass linearly increased along the succession time, whereas soil organic C and N contents showed a significant decline in the first 12 years and, subsequently, a significant increase. The increased plant biomass caused an increase in soil organic carbon and soil total nitrogen. These results suggested that soil restoration and plant cover were an incongruous process. Generally, soil restoration is a slow process and falls behind vegetation recovery after grazing exclusion. Although the accumulation of soil C and N stocks needed a long term, vegetation restoration was a considerable option for the degraded grassland due to the significant increase of plant biomass, diversity, and soil C and N stocks. Therefore, fencing with natural succession should be considered in the design of future degraded pastures., Competing Interests: The authors declare no conflict of interest.