Soil Total Nitrogen Content Research Articles

Deep Straw Burial Accelerates Straw Decomposition and Improves Soil Water Repellency

The continuous input, slow decomposition, and retention of straw can impede tillage and crop growth, and the decomposition process of the straw in soil is affected by its composition and the method of application. Experimental Station of Jilin Agricultural University, Changchun City, Jilin Province. The soil type was Argiudolls, the experimental field area was 30 m2, and the maize was planted continuously for 12 years without returning the straw to the field. There were four treatments: (1) control (CK), 10 g of straw was placed on the surface of a nylon mesh bag, and the nylon mesh bag was separated from the soil by polyethylene film without contacting with the soil; (2) straw mulching (CM), a nylon mesh bag with 10 g of straw was placed on the soil surface; (3) straw burying (CD), a nylon mesh bag with 10 g of straw was buried at a depth of 40 cm from the soil surface; (4) straw burying (CE), a nylon mesh bag with 40 cm of soil depth. Fifteen micro-zones were set up with a micro-zone area of 1 m2 and each micro-zone consisted of four treatments randomly grouped in three replicates per treatment. The on-site nylon bag burying trial started on 20 April 2021 and ended on 15 April 2022. Nylon bag and soil samples were collected on days 0, 30, 90, 180, 270, and 360. SOC, TN, straw component decomposition, and water droplet-soil contact angle were determined. Our results showed that the CE treatment increased soil organic carbon (SOC) and total nitrogen (TN) content compared to the CM and CD treatments. Compared with CK, straw decomposition rates increased by 13.3%, 30.8%, and 22.3% in the CM, CD, and CE treatments, respectively. Lignin decomposition rates increased by 7.8%, 27.3%, and 16.2%; cellulose decomposition rates increased by 14.6%, 35.4%, and 27.3%; and hemicellulose decomposition rates increased by 17.2%, 31.7% and 23.7% in the CD treatment, respectively. Compared with CK, the contact angle of droplets in the CD treatment was statistically significantly increased by 91.5% when the droplets remained on the soil surface for 5 s. The rate of decrease of droplet contact angle with time was statistically significantly decreased by 11.8%, and the penetration rate of droplets on the soil surface was slower. Overall, the CD treatment promoted straw decomposition and increased SWR compared to the CM and CE treatments. which are important attributes to enhance soil quality and improve soil structural stability.

Moss biocrusts buffer soil CO2 effluxes in a subtropical karst ecosystem

Biocrusts, specialized communities comprised of mosses, lichens, cyanobacteria, fungi, and bacteria occurring on the ground surface, are famous as ecological engineers on Earth, but less is understood in humid karst areas, where they are often widespread and provide important ecosystem services. To better understand how biocrusts affect soil carbon cycles, we performed an in situ study monitoring net soil exchange (NSE) of CO2, soil respiration (Rs), soil temperature and moisture, and determined soil nutrient contents and carbon-related enzyme activities over three different microcosms (soils covered by moss biocrusts, soils deprived of biocrust-forming mosses, and bare soils) in a subtropical karst ecosystem in southwest China. The results showed that, in comparison with bare soils, moss biocrusts increased Rs by 40% but decreased NSE by 49% and the temperature sensitivity of Rs by 35%. However, disturbance to moss biocrusts decreased Rs by 26% but increased NSE by 104% and the temperature sensitivity of Rs by 93%. Although moss biocrusts increased the content of soil organic carbon and total nitrogen and the activity of β-glucosidase, this effect was reversed by disturbance to moss biocrusts. While Rs was significantly correlated with soil temperature and moisture, the effect of moss biocrusts on Rs was partly explained by soil organic carbon, total nitrogen, and β-glucosidase. Overall, this study adds to the scarce number of experiments characterizing biocrust ecology in humid karst ecosystems and calls for management efforts to protect and restore biocrusts to buffer soil CO2 emissions under global change scenarios.

Responses of Deep Soil Carbon and Nitrogen Contents to Long-Term Retention of Alfalfa Pasture on Infertile Loess: A Synthesis Study

Incorporating perennial pastures into annual crop systems is an efficient means of improving soil carbon (C) sequestration and reducing the application of nitrogen (N) fertilizer on farmlands. How the soil C and N at different soil depths respond to the length of pasture duration and rainfall conditions is still being determined. In this study, we conducted a meta-analysis of data from 63 published studies to investigate the impacts of the alfalfa pasture on the incorporation of soil organic carbon (SOC), total nitrogen (STN), and available nitrogen (SAN) contents in the 0–300 cm soil profile of the Loess Plateau. An annual crop field was taken as a reference. The results showed that the average SOC content at soil depths of 0–100 and 100–200 cm in the alfalfa pasture increased by 17% and 8% (p < 0.001) compared to the crop field, respectively, while that at 200–300 cm decreased (p > 0.05). The SOC content increased with pasture age; it was the highest when the alfalfa had been planted for 5–9 years and decreased thereafter. The STN content at soil depths of 0–100 and 100–200 cm increased by 19% and 14% (p < 0.001), respectively; the content at depths of 200–300 cm only increased slightly (p > 0.05). It also increased the most when the alfalfa was 5–9 years old. The increments in the SAN content at the 0–100 and 100–200 cm soil depths were higher than those of the STN, with values of 29% and 18%, respectively, while those at depths of 200–300 cm also changed insignificantly (p > 0.05). The SAN content continuously increased with the age of the alfalfa, and the average increment in the 0–300 cm profile was as high as 21% when the alfalfa was ≥10 years old. The SOC and STN content increased the most under moderate rainfall conditions (350–500 mm), while the SAN content maintained the highest increment under high rainfall (500–650 mm) conditions. Therefore, ley farming with the alfalfa pasture contributed substantially to the soil C and N at depths of 200 cm in deep loess. Alfalfa should be removed in its middle ages to increase C sequestration while utilizing soil N efficiently.

Spatial Distribution of Leymus chinensis Is Not Determined by Its Ecological Stoichiometry

Leymus chinensis is a widely distributed species of Eurasian grasslands that is well adapted to a range of environmental conditions. In this study, we measured soil and plant chemical elements to examine the basis of the ecological adaptations of L. chinensis to temperate steppe. We sampled leaves of L. chinensis and soil layers at different latitudes in temperate steppe for three consecutive years from 2012 to 2014. One-way analysis of variance and linear regression were used to analyze the variation in foliar nitrogen (N) and phosphorus (P) contents and the N:P ratio in L. chinensis. The correlations between the foliar N:P ratio and the variation in soil total nitrogen (TN) and total P contents with latitudinal gradient were measured to explore the homeostasis stoichiometry of foliar N and P in L. chinensis. With increasing latitude, both the foliar N and P contents of L. chinensis showed parabolic trends with significant negative correlations. The population of L. chinensis was limited by N, and the soil TN content showed a significant increasing trend with the increase in the foliar N:P ratio. The variation in the foliar N:P ratio of L. chinensis was determined through the variation in the soil N content. In different latitude intervals, the foliar N, P, and N:P ratio of L. chinensis showed absolute stability and strong internal stability, and the values of HN:P were high and similar in different latitudes. In conclusion, the population of L. chinensis in the temperate steppe is highly adaptable; and, thus, can maintain a dominant position in the variable environment and has a wide distribution range.

Occurrence, distribution and risk assessment of polycyclic aromatic hydrocarbons in soils around main water source areas of Beijing, China.

Polycyclic aromatic hydrocarbons (PAHs) in urban environments have been globally concerned due to their significant health impacts on residents. However, little is known about potential risks of PAHs from centralized water source areas. In the present study, 326 soils samples from the main water source areas of Beijing were collected and the occurrence, source appointment, and risks of PAHs were systematically investigated based on the monitoring results from high-performance liquid chromatography (HPLC). The total PAHs (∑16 PAHs) concentrations ranged from 5.70 to 1512ng/g with median value of 44.2ng/g, in which 4-ring and 5-ring groups were the major components. PAHs concentrations in the cultivated land were significantly higher than other areas, which could reflect significant impact of soil organic matter and total nitrogen contents on the spatial variations of PAHs. Further source identifications through positive matrix factorization model (PMF) revealed that biomass (22.5%), coal (21.4%), gasoline (17.6%) and diesel (16.4%) combustion were dominant sources of soil PAHs in the study area. Moreover, the risk assessment indicated that total ecological and health risk of PAHs were negligible, but individual PAH, including pyrene and benzo(b)fluoranthene, should be concerned due to their potential risks in several monitored stations located in the secondary protection area of four reservoirs. Our study provided new insights into environmental risks of soils in main water source areas from PAHs and could be helpful for organic micropollutant controlling and drinking water safety in rapidly urbanizing cities.

Changes in grassland soil types lead to different characteristics of bacterial and fungal communities in Northwest Liaoning, China.

Soil microbial communities are critical in regulating grassland biogeochemical cycles and ecosystem functions, but the mechanisms of how environmental factors affect changes in the structural composition and diversity of soil microbial communities in different grassland soil types is not fully understood in northwest Liaoning, China. We investigated the characteristics and drivers of bacterial and fungal communities in 4 grassland soil types with 11 sites across this region using high-throughput Illumina sequencing. Actinobacteria and Ascomycota were the dominant phyla of bacterial and fungal communities, respectively, but their relative abundances were not significantly different among different grassland soil types. The abundance, number of OTUs, number of species and diversity of both bacterial and fungal communities in warm and temperate ecotone soil were the highest, while the warm-temperate shrub soil had the lowest microbial diversity. Besides, environmental factors were not significantly correlated with soil bacterial Alpha diversity index. However, there was a highly significant negative correlation between soil pH and Shannon index of fungal communities, and a highly significant positive correlation between plant cover and Chao1 index as well as Observed species of fungal communities. Analysis of similarities showed that the structural composition of microbial communities differed significantly among different grassland soil types. Meanwhile, the microbial community structure of temperate steppe-sandy soil was significantly different from that of other grassland soil types. Redundancy analysis revealed that soil total nitrogen content, pH and conductivity were important influencing factors causing changes in soil bacterial communities, while soil organic carbon, total nitrogen content and conductivity mainly drove the differentiation of soil fungal communities. In addition, the degree of connection in the soil bacterial network of grassland was much higher than that in the fungal network and soil bacterial and fungal communities were inconsistently limited by environmental factors. Our results showed that the microbial community structure, composition and diversity of different grassland soil types in northwest Liaoning differed significantly and were significantly influenced by environmental factors. Microbial community structure and the observation of soil total nitrogen and organic carbon content can predict the health changes of grassland ecosystems to a certain extent.

Correlations between plant and soil for their C, N, P contents and stoichiometry on the steep gully slopes

Steep gully slope is the primary geomorphic composition on the Loess Plateau with serious soil erosion. The impact of plant (leaf, litter and root) on soil nutrients and their stoichiometric characteristics, and the correlations between them are not yet fully understood on steep gully slopes. This study was conducted to identify the correlations of carbon (C), nitrogen (N), phosphorus (P) contents and their stoichiometry between soil, and leaf, litter and root under typical plant communities on Chinese Loess Plateau's steep gully slopes. Total six communities (two shrubs and four grasses) and one farmland planted with Zea mays (control) were tested. Within the selected quadrat (shrub of 2 m × 2 m, grass of 1 m × 1 m), the fresh and mature leaves were firstly taken in different positions of the plant, and then all the surface litters were gathered. Root and soil were taken from the 0–120 cm depth, which was divided into seven soil layers (0–10, 10–20, 20–30, 30–40, 40–60, 60–80 and 80–120 cm). Our results revealed that significant differences were detected in C, N, P contents and stoichiometry of plant (leaf, litter and root) and soil among most of plant communities. For various plant communities, shrub communities had higher contents of C, N and P in leaves, litter and roots. Soil organic carbon and total nitrogen contents declined with soil depth by 61% to 87% and 45% to 77%, respectively. Total contents of soil P and root C, N, P varied irregularly along with soil. It was proved that shrub communities were relatively P-deficient, while farmland and grass communities were N-limited. Besides, partial N and P nutrients were released to soil from litter on steep gully slopes. Significant correlations between soil C, N, P contents and that of the root and litter were examined. Furthermore, the correlations became more significant when C, N and P nutrients of root and litter were quantified by their storages. This study offers a deep understanding of the interactions between soil and plant nutrients, which is conducive to future ecological environment management and improvement in the semi-arid region.

Forage Radish Cover Crops Improve Soil Quality and Fruit Yield of Lycium barbarum L. in an Arid Area of Northwest China

Intercropping orchards with cover crops is an important practice for achieving sustainable soil management. However, little research has addressed the development of a soil quality index (SQI) to evaluate cover crop effects on orchard soil quality. The aim of this study was to ascertain whether cover cropping improves soil quality and fruit yield of Goji (Lycium barbarum L.) while reducing or replacing organic fertilizer application. The main treatments were the traditional management of L. barbarum as a monocrop (M) and intercropping Goji with radish (Raphanus sativus L.) as an annual cover crop (I). Within the main treatments, different levels of organic fertilizer were applied at 0 kg·plant−1 (M0), 2 kg·plant−1 (M1), and 4 kg·plant−1 (M2). After six years of planting, we analyzed the changes in soil quality caused by cover cropping with different organic fertilizer levels based on the SQI method. Goji yields were used for validation of the SQI derived from a minimum data set of soil quality indicators. In contrast with traditional monocropping, cover cropping increased soil total nitrogen, available nitrogen, and available phosphorus contents (by 78.60%, 30.30%, and 138.08%, respectively). There were also increased microbial biomass carbon and nitrogen contents (by 79.01% and 184.01%, respectively), enhanced urease and sucrase activities (by 41.02% and 56.81%, respectively), and reduced bulk density (by 1.92%) in the soil as a result of cover cropping. Compared with IM0 treatment, soil microbial biomass carbon and nitrogen contents considerably increased under IM1 treatment, whereas soil available nitrogen and potassium contents as well as electrical conductivity increased under IM2 treatment. The SQI, which varied among treatments in the order IM1 > IM2 > MM2 > MM1 > IM0 > MM0, was positively correlated with Goji yield. From the soil quality and Goji yield perspective, cover cropping with a medium level of organic fertilizer is the optimal soil management practice for the L. barbarum planting system in arid areas of Ningxia, Northwest China.

Long-Term Chemical Fertilization Drove Beneficial Bacteria for Rice Soil to Move from Bulk Soil to the Rhizosphere

Overuse of chemical fertilizer (CF) causes damage to soil and the environment. To reveal the process of the response of crop rhizospheric and bulk soil fertility and the bacterial community to long-term CF conditions, CF application and nonfertilization (CK, control) treatments were used in a long-term (12-year) fertilization experiment. Long-term CF application significantly increased the soil organic matter, total nitrogen, and available phosphorus contents (p < 0.05), increased the available nitrogen (AN) and potassium (AK) contents to varying degrees, and decreased the soil pH in both rice rhizospheric soil and bulk soil. In addition, the bacterial Shannon and Ace indices in rice rhizospheric soil under the CF treatment were all higher than those under the control (CK) treatment, and the bulk soil bacteria showed the opposite trend. The LEfSe results showed that unidentified_Gammaproteobacteria and Geobacter (genera) were significantly enriched in the rhizospheric and bulk soil of rice under the CK treatment, respectively. Gemmatimonadetes (phylum) and Nitrospirae (phylum) + Thiobacillus (genus) were significantly enriched in the rice rhizospheric and bulk soil under the CF treatment. Only AK and AN had strong positive correlations with soil bacteria. Long-term CF application accelerated the migration of soil bacteria from the bulk soil to the rhizosphere, thus improving soil fertility and nutrient cycling.

Estimating the spatial distribution of soil organic carbon and soil total nitrogen concentrations by remote sensing methods: a case study in a forest-dominated Alpine Watershed, Western China

ABSTRACT In ecologically fragile areas, accurate estimation of soil organic carbon (SOC) and soil nitrogen (STN) concentrations is a prerequisite for sustainable development. On the basis of field sampling data and remote sensing technology, this study divided the topsoil (0–30 cm) into three soil layers of 0–10 cm, 10–20 cm, and 20–30 cm to carry out SOC and STN concentrations estimation experiments in the Qilian Mountains in western China. To estimate SOC and STN concentrations, a stepwise multiple linear regression model was used. A total of 119 topsoil samples and nine remotely sensed environmental variables were collected and used for model development and validation. The results show that the stepwise multiple linear regression model has stable simulation performance. The modified soil-adjusted vegetation index (MSAVI), perpendicular vegetation index (PVI), aspect, elevation, and solar radiation were the key environmental variables affecting soil organic carbon and total nitrogen content. The ranking of SOC concentrations in the 0–30 cm soil layer was bush woods > spruce forests > sabina forests > alpine meadows > steppes, with mean concentrations of 117.98 g/kg, 101.35 g/kg, 83.09 g/kg, 78.76 g/kg, and 37.08 g/kg, respectively. The ranking of STN concentrations in the 0–30 cm soil layer was bush woods > alpine meadows >spruce forests > sabina forests > steppes, with mean concentrations of 4.77 g/kg, 3.71 g/kg, 3.19 g/kg, 3.27 g/kg, and 1.92 g/kg, respectively. Both SOC and STN concentrations decreased significantly with increasing soil depth.

Mutual feeding mechanism of carbon, nitrogen and enzyme activity in Northeast China black soil under snow cover change

Projected future changes in snow cover patterns associated with global warming in cold zone ecosystems could affect soil biochemical cycling. However, the effects of snow cover changes on soil available carbon, nitrogen and enzyme activities and their potential response mechanisms have not been clarified. Therefore, from November 2021 to April 2022, this study conducted a snow depth manipulation test of four treatments in the northeast black soil region, and divided the test period into five stages to measure soil temperature and humidity, microbial biomass, enzyme activity, and available carbon and nitrogen. The results showed that the decrease of snow cover increased the freeze-thaw cycle frequency and freezing temperature of soil, but decreased the soil water content. Soil total organic carbon and inorganic nitrogen contents were increased in early and deep snow periods, while snow treatment was on the contrary. Due to the release of soluble nutrients caused by frequent freeze-thaw processes, Soil soluble organic carbon and Soil soluble organic nitrogen contents increased with the decrease of snow depth in deep snow period, snowmelt period and subsequent early crop growth period. Snow treatment increased soil microbial carbon and nitrogen content in early winter and early spring because snow provided heat insulation. Soil enzyme activities increased with the increase of snow cover. Compared with the control, soil urease activities and sucrase activities increased by 18.5 % and 11.5 % under snow treatment, and decreased by 23.2 % and 10.8 % under snow reduction treatment. In addition, soil soluble organic matter was a controlling factor for soil microbial biomass and enzyme activity throughout winter. The direct effect of soil soluble organic carbon and nitrogen on soil enzymes will make soil enzymes participate in the cyclic transformation process of available carbon, thus forming a closed loop of mutual feedback between soil available carbon and nitrogen and enzymes. These results demonstrated that the changes of snow cover in the future will have certain effects on soil carbon and nitrogen cycles and enzyme activities and hence biogeochemical cycling in terrestrial system of earth.

Dodder Parasitism Leads to the Enrichment of Pathogen Alternaria and Flavonoid Metabolites in Soybean Root

Dodders (Cuscuta chinensis) are rootless and holoparasitic herbs that can infect a variety of host plants, including the vitally important economic and bioenergy crop soybean (Glycine max). Although dodder parasitism severely affects the physiology of host plants, little is known about its effects on fungal communities and root secondary metabolites in hosts. In this study, variations in root-associated fungal communities and root metabolites of soybean under different parasitism conditions were investigated using ITS rRNA gene sequencing and UPLC–MS/MS metabolome detection technologies. The results showed that dodder parasitism significantly altered the composition and diversity of the fungal communities in the rhizosphere and endosphere of soybean. The relative abundance of the potential pathogenic fungus Alternaria significantly increased in the root endosphere of dodder-parasitized soybean. Furthermore, correlation analysis indicated that the fungal community in the root endosphere was susceptible to soil factors under dodder parasitism. Meanwhile, the content of soil total nitrogen was significantly and positively correlated with the relative abundance of Alternaria in the rhizosphere and endosphere of soybean. Metabolomic analysis indicated that dodder parasitism altered the accumulation of flavonoids in soybean roots, with significant upregulation of the contents of kaempferol and its downstream derivatives under different parasitism conditions. Taken together, this study highlighted the important role of dodder parasitism in shaping the fungal communities and secondary metabolites associated with soybean roots, providing new insights into the mechanisms of multiple interactions among dodder, soybean, microbial communities and the soil environment.

Effects of Different Types of Plastic Film Mulching on Soil Quality, Root Growth, and Yield

Aiming to address the problem of soil environmental pollution caused by the large-scale use of plastic film in agricultural production in China, field experiments were carried out by applying degradable plastic film. Pumpkin was used as the research material to explore the effects of black common plastic film (CK), white degradation plastic film (WDF), black degradation plastic film (BDF), and black CO2-based degradable plastic film (C-DF) on soil physicochemical properties, root growth and yield, and soil quality. The results showed that the soil water content and temperature of the three degradable plastic films were lower than those of ordinary plastic films to different degrees; there was no significant difference in soil organic matter content among the treatments. The soil available potassium content of the C-DF treatment was lower than that of CK, and WDF and BDF had no significant effect. Compared with those in CK and WDF, soil total nitrogen and available nitrogen contents in the BDF and C-DF treatments were lower, and the difference between treatments reached a significant level. Compared with that of CK, the catalase activities of the three types of degradation membranes were significantly increased by 2.9%-6.8%, and the sucrase was significantly decreased by 33.3%-38.4%. Compared with that in CK, the soil cellulase activity in the BDF treatment was significantly increased by 63.8%, whereas WDF and C-DF had no significant effects. The three types of degradable film treatments could promote the growth of underground roots, and the growth vigor was obviously enhanced. The yield of pumpkin treated with BDF and C-DF was close to that of CK, and the yield of pumpkin treated with BDF was significantly lower than that of CK by 11.4%. The experimental results showed that the effects of the BDF and C-DF treatments on soil quality and yield were comparable to those of CK. According to the results, two types of black degradable plastic film can effectively replace ordinary plastic film in the high-temperature production season.

Correlation between Non-Structural Carbohydrates and C:N:P Stoichiometric Ratio of Haloxylon ammodendron under Different Water–Salt Gradients

Growth is restricted by both water and phosphorus (P), and balancing the relationship between non−structural carbohydrates (NSCs) and carbon: nitrogen: phosphorus (C:N:P) is essential for Haloxylon ammodendron to adapt to arid habitats. The survival and growth strategies of the dominant species H. ammodendron in a desert ecosystem were examined in order to better serve the restoration of degraded ecosystems and desertification control. Three water and salt gradients (high water and high salinity, medium water and salinity, and low water and low salinity) in the Aibi Lake Reserve were selected. We analyzed the accumulation and distribution of NSCs in the assimilation branches and secondary branches of H. ammodendron and the changes in the measurement ratio characteristics of C:N:P, as well as the soil organic carbon (SOC), total nitrogen (TN), and total phosphorus (TP) content. The results showed that: (1) With the decrease of soil water and salt content, the basal diameter, plant height, crown area, and NSC content of H. ammodendron significantly decreased. This morphological adjustment in the aboveground part is similar to a “self thinning” behavior, aimed at reducing transpiration area and balancing carbon distribution in the body. The carbon accumulation in the body helps the H. ammodendron to resist the dual stresses of drought and salt. (2) With the decrease of water and salt content, the C content of assimilating branches increased significantly, while there was no significant change in secondary branches. However, the N and P content of both branches decreased significantly, and the N: P of both branches was greater than 16, indicating that it was mainly limited by P. (3) The NSC of the two branches was significantly negatively correlated with C, and significantly positively correlated with N and P, and there was a strong positive correlation between the assimilation branches NSC: C: P and NSC: C: P. The synthesis and accumulation of NSC of H. ammodendron were influenced by the content and relationship of C, N, and P, and the abundance of P content transported by the root system to the aboveground portion may have an important and decisive role in regulating nutrient balance and non-structural carbon dynamics.

Effects of Combined Application of Chemical Fertilizer and Biochar on Soil Physio-Biochemical Properties and Maize Yield

Excessive, long-term chemical fertilizer application adversely affects soil quality and maize yield. The combined application of biochar with chemical fertilizer can increase maize yield and improve soil fertility. A four-year field experiment was conducted to determine soil physio-biochemical properties and maize yield under a soybean–maize rotation in the black soils of Northeast China. There were five treatments, including no fertilization (CK), fertilizer (NPK), fertilizer + biochar (15.75 t·hm−2, BC1), fertilizer + biochar (31.50 t·hm−2, BC2), and fertilizer + biochar (47.25 t·hm−2, BC3). Compared with CK, the number of macroaggregates and the average weight diameter of soil aggregates in BC2 treatment increased significantly by 10.3% and 24.5%, respectively. The soil pH in the study area was 7.03, and it increased in all treatments except for BC1. The highest pH of 7.17 was recorded in NPK and BC2 treatments, which was around the optimal soil pH. In contrast to the CK and NPK treatments, the biochar application increased soil organic carbon (SOC) and total nitrogen (TN) content. The BC2 treatment improved soil C/N and increased the copy number of soil bacteria by 25.6% compared to CK. The combined application of chemical fertilizer and biochar was better than NPK treatment alone, and improved soil mechanical composition and fine soil particle contents (powder and clay). Mixed biochar with chemical fertilizer application also significantly increased maize yield and the weight of 100 grains increased from 9.5% to 10.9% compared to CK. The maize yield of the three fertilizer and biochar treatments was higher than treatments with applied chemical fertilizer alone, in the order of BC2 > BC3 > BC1 > NPK > CK (BC2 treatment increased by 34.8%). Additionally, the maize yield was significantly and positively correlated with soil aggregates, organic carbon and total nitrogen (p < 0.05) as well as the 100-grain weight (p < 0.01). The application of 31.50 t·hm−2 (BC2 treatment) of biochar can enhance soil physicochemical properties and improve maize yield.

Comparison of Machine Learning Methods for Predicting Soil Total Nitrogen Content Using Landsat-8, Sentinel-1, and Sentinel-2 Images

Soil total nitrogen (STN) is a crucial component of the ecosystem’s nitrogen pool, and accurate prediction of STN content is essential for understanding global nitrogen cycling processes. This study utilized the measured STN content of 126 sample points and 40 extracted remote sensing variables to predict the STN content and map its spatial distribution in the northeastern coastal region of Hebei Province, China, employing the random forest (RF), gradient boosting machine (GBM), and extreme gradient boosting (XGBoost) methods. The purpose was to compare the ability of remote sensing images (Landsat-8, Sentinel-1, and Sentinel-2) with different machine learning methods for predicting STN content. The research results show the following: (1) The three machine learning methods accurately predicted the STN content and the optimal model provided by the XGBoost method, with an R2 of 0.627, RMSE of 0.127 g·kg−1, and MAE of 0.092 g·kg−1. (2) The combination of optical and synthetic aperture radar (SAR) images improved prediction accuracy, with the R2 improving by 45.5%. (3) The importance of optical images is higher than that of SAR images in the RF, GBM, and XGBoost methods, with optical images accounting for 87%, 76%, and 77% importance, respectively. (4) The spatial distribution of STN content predicted by the three methods is similar. Higher STN contents are distributed in the northern part of the study area, while lower STN contents are distributed in coastal areas. The results of this study can be very useful for inventories of soil nitrogen and provide data support and method references for revealing nitrogen cycling.

Assessment of machine-learning methods for the prediction of STN using multi-source data in Fuzhou city, China

This study evaluated the performance of machine-learning approaches to predict Soil Total Nitrogen (STN) using remote sensing and environmental data in the coastal city of Fuzhou, Fujian Province, China. Multisource environmental data was combined to identify important variables for topsoil STN distribution prediction. Additionally, STN content was assessed based on environmental covariates. The results from this study showed that random forest (RF), support vector machine (SVM), artificial neural network (ANN), multi-linear regression (MLR), and locally weighted regression (LWR) can achieve high R2 values of 0.96, 0.92, 0.80, 0.97, and 0.93 with respective RMSECV values of 0.08, 0.35, 0.37, 0.43, and 0.65, respectively. Random Forest (RF) was the most effective model among these methods, with the corrosponding highest R2 and lowest RMSECV. RF and SVM models were used to select important predictors; accordingly, RF selected mainly vegetation indexes while SVM selected Visible-Near-Infrared (VIS-NIR) spectra of the soil. Additionally, STN contents had relationships with most environmental covariates derived from remote sensing, soil spectra, and topographic variables. Spectral transformations improved the correlations with STN where the second derivative and standard normal variate transformations produced the best results. This study suggests that machine-learning methods are practical approaches for the prediction of STN and can be used in similar complex coastal environments.

Effects of Combined Long-Term Straw Return and Nitrogen Fertilization on Wheat Productivity and Soil Properties in the Wheat-Maize-Soybean Rotation System in the Pannonian Plain

The study, conducted to evaluate the effects of long-term straw management combined with the application of increasing nitrogen rates on the yield of twenty winter wheat varieties, as well as on soil properties, was carried out in a long-term field trial established in 1971. The trial was monitored for twenty growing seasons under rainfed conditions in a typical chernozem zone of the southern part of the Pannonian Plain. The cropping system was a winter wheat-maize-soybean rotation. The ten SN-treatments (combinations of straw management (S) and N-fertilization) were as follows: In the plot (treatment) with straw return (S1), seven variants of nitrogen fertilization (0–180 kg N ha−1) were included, while on the plot without straw return (S0) the variants of N-fertilization were 0, 90 and 150 kg N ha−l. Based on the high relative share in the total sum of squares, variance analysis showed that wheat grain yield (GY) was significantly affected by years, SN-treatments, and their interaction, and they can explain the largest part of the total variance of GY. The results showed that straw return integrated with N fertilization could increase wheat yield to varying degrees over 20 years. On average, for all years, the highest GYs were obtained in the treatment S1 and fertilization with 180 and 150 kg N ha−1. The overall results showed that long-term straw returning significantly increased GY by an average of 8.4 ± 4.5%, with a considerable simultaneous increase in yield stability compared to straw removal. In addition, straw incorporation (SI) significantly increased soil humus, total nitrogen (TN), and soil organic carbon (SOC) contents at a soil depth of 0–30 cm by an average of 4.2, 3.8, and 11.3%, respectively. The results of our study have demonstrated that the long-term practice of straw return, in combination with the application of mineral fertilizers, has the potential to serve as a sustainable soil management strategy that is economically viable and environmentally acceptable. However, additional research is required to investigate its interactive effects on both grain yield and soil productivity.

Spatial estimation of soil carbon and nitrogen in a grassland shrubland transition

Shrub encroachment via anthropogenic introduction has been used for ecological restoration in degraded desert grassland. However, there have been debates concerning whether this activity can be effective, as contrasting results were frequently reported. The objectives of this study were to address if various Caragana korshinskii planting conditions (planting year and density) had varying influences on soil organic carbon (SOC), soil total nitrogen (STN), and their spatial heterogeneities along the transition from desert grassland to shrubland. We investigated SOC and STN at the community and landscape scales, with the former containing eight land types of enclosed grassland, grazed grassland, and shrubland with varying levels of planting years (3, 12, or 22 years) and planting intervals (2, 6, or 40 m), and the latter consisting of 43 grassland-shrubland mosaic sites (desert grassland, grassland-shrubland edge, and shrubland) covering approximately 2,976 km2 area. At the community scale, the SOC and STN contents from 0 to 100 cm soil depth in shrubland, regardless of varying planting years and densities, were higher than those observed in grazed grassland. Though it appeared that short-term of shrub establishment (3 and 12 years) in shrubland outscored enclosed grassland in SOC accumulation, it was still questionable if this can be consistent for a longer time period as no significant difference was seen for SOC contents between enclosed grassland and shrubland after 22 years of shrub establishment. At the landscape scale, the SOC contents were higher in shrubland than those in desert grassland. However, no significant difference was observed for STN among shrubland and desert grassland. Regarding their spatial heterogeneities, SOC exhibited stronger spatial autocorrelation in grassland-shrubland edge than in desert grassland and shrubland, while STN did not evidently differ in spatial autocorrelation among these transition states. In brief, we have observed differences in soil carbon and nitrogen at community scales, but when crossing over to broad scales do not show the kind of significant spatial heterogeneity that we thought would be present in shrub introductions over the past 30 years. There may be a certain lag in the evolution of soil carbon and nitrogen responses from the introduction of shrubs from the community scale to the landscape scale.

Spatial mapping of topsoil total nitrogen in mountainous and hilly areas of southern China using a continuous convolution neural network

Rapid and accurate acquisition of soil nutrient information using remote sensing technology is a prerequisite for precision agriculture. However, soil information is weak in remote sensing images of mountainous and hilly areas with high vegetation coverage. Therefore, a continuous convolutional neural network (CNN)-based method was developed for spectral inversion of soil total nitrogen (STN) content in mountainous and hilly areas of southern China. First, the correlation between laboratory-measured soil spectra, remote-sensing image spectra, and STN content under different land use types was analyzed. Image spectra were then transformed to laboratory-measured spectra by two deep learning methods: convolutional neural network (CNNT) and multilayer perceptron (MLPT). The transformed spectra were used for STN modeling based on deep learning models (CNNS and MLPS), and the modeling results were corrected for residuals using ordinary kriging interpolation. The results showed that in vegetated areas, vegetation spectral features provided indirect evidence for soil nutrient status. Consequently, image spectra were successfully transformed into laboratory-measured spectra, and CNNT outperformed MLPT for spectral transformation. All bands of transformed spectra had high correlations with STN content and could therefore be used for STN inversion. Despite the rough estimation of STN content based on transformed spectra, the modeling results of CNNS and MLPS improved after residual correction. Overall, the corrected CNNS model achieved the highest inversion accuracy in terms of the coefficient of determination (0.702), root mean squared error (0.489 g∙kg−1), and ratio of performance to interquartile range (3.009), which was ∼ 20% higher than before correction. The optimal model estimated STN content accurately and achieved spatial mapping of regional surface-layer STN content. The study develops a powerful tool for real-time quantitative monitoring of STN changes in mountainous and hilly areas, and provides new possibilities for precision agriculture.