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Tillage and straw returning are promising practices to improve soil quality, especially because of the unclear controlling effects on microbial communities and functions. A 5‐year field experiment in a winter wheat‐summer maize cropping system was implemented in the North China Plain to address this research gap. Management practices were deep tillage, rotary tillage, and no‐tillage, each with either wheat only or both wheat and maize straw returning. Shotgun metagenomic sequencing was performed to investigate the microbial community, diversity, co‐occurrence network, and function in the topsoil (0–20 cm). The associations between soil physiochemical properties and microbial community characteristics were also evaluated. Rotary tillage with only wheat straw returning (RTS) significantly increased Shannon's diversity index by 0.24%–1.71% compared to other treatments. No‐tillage with only wheat straw returning (NTS) showed the most stable microbial network with the highest betweenness centrality (199.09), average path distance (2.31), and modularity (0.50). NTS had the highest relative abundance of microbial carbon (C), nitrogen (N) metabolisms, and C fixation pathways. Among deep tillage practices, both wheat and maize straw returning (DTD) were more beneficial to the stability of microbial networks than only wheat straw returning (DTS), yet without improvement in microbial diversity and function. In conclusion, microbial community and function are practical predictors of variations in soil nutrient availability, and pH value in response to different tillage and residue management practices. In particular, our study provides a basis for the development of a sustainable crop residue management system. [ABSTRACT FROM AUTHOR]

Intercropping, particularly within legume‐based systems, has been shown to enhance yields and optimize resource use efficiency. Yet, the potential contribution of intercropping on soil microbial communities and functions to soil nutrients cycling are not fully understood. We conducted the same field experiments at Youyu (Site1) and Zhangbei (Site2) in Northern China to evaluate the impact of oat/soybean intercropping on the rhizosphere soil bacterial community structure, composition, and co‐occurrence networks. Our results indicated that intercropping significantly modified the bacterial community structure for both oat and soybean at Site1, with changes observed only in the oat community at Site2. Specifically, intercropping led to a substantial increase in the relative abundance of Bacteroidetes and Patescibacteria in the oat rhizosphere by 48.3% and 65.4% (Site1), respectively. Conversely, in the soybean rhizosphere at Site1, there was a notable decrease in the abundance of Patescibacteria and Nitrospirae by 32.4% and 40.0%, respectively. The soil bacterial functional groups demonstrated robust positive correlations with key soil parameters such as available nitrogen (Nmin), available phosphorus (Avail‐P), and the activities of nitrogen‐ and phosphorus‐acquiring enzymes in the rhizosphere. In conclusion, intercropping is an effective agricultural practice for enhancing nitrogen and phosphorus cycling by reshaping the soil bacterial community, offering a distinct advantage over monoculture practices. This insight underscores the potential of intercropping to foster sustainable soil nutrient management, highlighting the importance of integrating such practices into modern agricultural strategies to ensure long‐term productivity and environmental sustainability. [ABSTRACT FROM AUTHOR]

Water N-NO3− (mg L−1) pollution is attracting global concern in the face of combating climate change and human health risks. However, there have been comparatively few comprehensively researched studies on water N-NO3− pollution with respect to N-NO3− deposition, soil nitrogen, and land-use changes. We collected a total of 7707 published sampling points on N-NO3− surface and groundwater during flooding and non-flooding seasons during 2000–2020 in China. The types of water N-NO3− pollution (>20) can be categorized as point pollution (ΔTN ≤ 0 or > 1.5) and non-point pollution (0 < ΔTN ≤ 1.5), which were then assessed with respect to soil nitrogen (ΔTN g kg−1) and water N-NO3− changes in this study. We found non-point pollution was concentrated in the Huaihe River Basin and Haihe River Basin with higher urbanization (+6%, +4%), cropland (72%, 45%), nitrogen fertilization (g m−2 yr−1) (>10), and increased wet N-NO3− deposition (WND) (kg ha−1 yr−1) (+4.6, +3). The Haihe River Basin was found to have the highest N-NO3− on its surface (306) and in its groundwater (868) and nitrogen fertilization (32). Point pollution was concentrated in the Songhua and Liaohe River Basin with the highest WND (+7.9) but slow urbanization (+1%). N-NO3− increased during the flooding season compared with the no-flooding season in serious pollution areas. N-NO3− increased in the Liaohe River and middle and low Yangtze River but was reduced in the Weihe River. Therefore, stringent criteria and management, especially during the flooding season are urgently required to mitigate the degree of N-NO3− water pollution that occurs due to intensive agriculture and urbanization with increased N-NO3− deposition. [ABSTRACT FROM AUTHOR]

Agricultural practices of nitrogen and irrigation overuse bring lots of environmental problems, such as greenhouse gases (GHGs) emissions, soil, and water pollution. With the fast expansion of saline and alkaline agricultural soils in the Tarim River Basin, field practice must be very cautious facing water limitations and global warming. The GHGs were measured 1–2 times weekly and water and fertilizer use efficiency were evaluated under five treatments: (1) fallow (Control); (2) no N (kg N ha−1) and no irrigation (mm) (0N0W); (3) 200 and 355 (LNLW); (4) 230 and 475 (MNMW), and (5) 320 and 655 (HNHW) (traditional treatment) from 2018 to 2019 under maize in Aksu in the Tarim River Basin. The GHGs increased with fertilization and irrigation. The cumulative GHGs were 0.6–5.9 Mg CO2–C ha−1, 0.2–3.6 kg N2O–N ha−1, and increased significantly with biomass increase. The cumulative CH4 was −0.03 to −0.12 kg C ha−1. The MNMW resulted in the highest average water use efficiency (27 kg ha−1 mm−1), irrigation water use efficiency (32 kg ha−1 mm−1), and agronomic N use efficiency (44 kg kg−1), but the lowest greenhouse gas intensity (0.4 kg CO2‐eq ha−1 grain yield). The MNMW reduced the average of 10 mm water, 5 kg N ha−1 fertilizer, and 4 × 10−3 kg CO2‐eq ha−1 GHGI earning 1 t ha−1 maize compared to HNHW. The CO2 emission had a strong relationship with temperature (T) and soil moisture (W) (CO2 emission = (exp (a + bW + cW2)) Q10(T‐20)/10)) (R2 = 0.59–0.92). The lowest was in the LNLW treatment in 2019; the highest was in the HNHW in 2018). The emission of CO2 responding to fertilization was below the global trend, but that of N2O was above under maize in saline and alkaline soils (pH 7–9). In conclusion, MNMW was the best field management to mitigate GHGs with the highest water and fertilizer use efficiency under maize in saline and alkaline soils in Tarim River Basin, where had the higher N2O emission risk. [ABSTRACT FROM AUTHOR]

Splitting nitrogen (N) application is beneficial for achieving higher grain yields and N use efficiency (NUE), but the responses of N utilization efficiency of different maize cultivars to top-dressing N fertilizer rates are still unclear. This study investigated the effects of fertilization managements on N uptake and utilization derived from topdressing fertilizers of maize hybrids (Ludan981 and Denghai605) with contrasting NUEs. The N fate derived from topdressing fertilizer was determined using the 15N tracing method. Grain yields, dry matter and N accumulation of both maize hybrids were significantly increased under low N levels but decreased under high N levels. Under N-deficient and excess conditions, Denghai605 had higher NUE than Ludan981. The N rates of topdressing significantly affected N uptake and utilization, but no difference was detected between two maize hybrids, and excessive N use led to higher rates of N loss and residual in soil. The N metabolism enzyme activities did not differ between the two maize hybrids. Our findings suggest optimized N management strategies by adjusting topdressing N application rate and timing are necessary to increase NUE and to minimize environmental costs in maize cropping system. [ABSTRACT FROM AUTHOR]

Although a number of studies have provided information on soil texture, soil classification, and depth to bedrock throughout China, few studies have combined this information, which is the basis for agricultural field management. A total of 81% of China's cultivated lands are distributed among the Middle–Lower Yangtze Plain (18.2%), arid and semiarid North China Plain (18.2%), Northeast Plain (17%), Huang-Huai-Hai Plain (16.1%), and Yunnan–Guizhou Plateau (11.6%). The Huang-Huai-Hai Plain has the highest density of agricultural land (58.5%) and the greatest depth to bedrock of cultivated land (243–402 m). The lowest cultivated depth to bedrock (4–84 m) is concentrated in the Sichuan Basin and its surrounding regions. The main cultivated soil types are Anthrosols, Fluvisols, Cambisols, Phaeozems, Luvisols, Kastanozems, Leptosols, and Acrisols, under the main topsoil texture classes of loam, clay loam, silty clay loam, silt loam, sandy loam, and clay. The Fluvisols had the largest depth to bedrock (156 m) on the Middle–Lower Yangtze Plain and Huang-Huai-Hai Plain, with the highest silt soil distributions but comparable lower sand contents. The Yunnan–Guizhou Plateau had the highest clay soil content. The cultivation under Kastanozems and Leptosols on the Qinghai–Tibet Plateau and in arid and semiarid North China and under Phaeozems on the Northeast Plain should be restricted and managed very cautiously facing erosion risk. The higher percentages of Anthrosols are on the Middle–Lower Yangtze Plain (37%), in Southern China (32%), and on the Yunnan–Guizhou Plateau (26%). The same cultivation aim (i.e., more crop 0production) has produced a similar range of properties over time among the soils developed on agricultural fields, which are classified as Anthrosols. However, various soil types can still be found in agroecosystems because of the variations in climate and topography. Our results highlight that the agriculture-based soil climate and topography shape the interaction of the soil development and not only the pedogenic history of the soil development under variations in the soil depth to bedrock but also the cultivation of distinct pedogenic features. This study provides cultivated soil information on the depth to bedrock, soil classification, and soil texture in China, as well as instructions for field strategies for sustainable agricultural development. [ABSTRACT FROM AUTHOR]

Over-fertilization has a significant impact on soil microbial properties and its ecological environment. However, the effects of long-term fertilization on microbial properties on a large scale are still vague. This meta-analysis collected 6211 data points from 109 long-term experimental sites in China to evaluate the effects of fertilizer type and fertilization duration, as well as soil and climate conditions, on the effect sizes on various microbial properties and indices. The organic fertilizers combined with straw (NPKS) and manure (NPKM) had the highest effect sizes, while the chemical fertilizers N (sole N fertilizer) and NPK (NPK fertilizer) had the lowest. When compared with the control, NPKM treatment had the highest effect size, while N treatment had the lowest effect size on MBN (111% vs. 19%), PLFA (110% vs. −7%), fungi (88% vs. 43%), Actinomycetes (97% vs. 44%), urease (77% vs. 25%), catalase (15% vs. −11%), and phosphatase (58% vs. 4%). NPKM treatment had the highest while NPK treatment had the lowest effect size on bacteria (123% vs. 33%). NPKS treatment had the highest while N treatment had the lowest effect sizes on MBC (77% vs. 8%) and invertase (59% vs. 0.2%). NPKS treatment had the highest while NPK treatment had the lowest effect size on the Shannon index (5% vs. 1%). The effect sizes of NPKM treatment were the highest predominantly in arid regions because of the naturally low organic carbon in soils of these regions. The effect sizes on various microbial properties were also highly dependent on soil texture. In coarse-textured soils the effect sizes on MBC and MBN peaked sooner compared with those of clayey or silty soils, although various enzymes were most active in silty soils during the first 10 years of fertilization. Effect sizes on microbial properties were generally higher under NPKM and NPKS treatments than under NPK or N treatments, with considerable effects due to climate conditions. The optimal field fertilizer regime could be determined based on the effects of fertilizer type on soil microorganisms under various climate conditions and soil textures. This will contribute to the microbial biodiversity and soil health of agricultural land. Such controls should be used for adaptation of fertilization strategies to global changes. [ABSTRACT FROM AUTHOR]

Soil salinization is one of the main causes of global desertification and soil degradation. Although previous studies have investigated the hyperspectral inversion of soil salinity using machine learning, only a few have been based on soil types. Moreover, agricultural fields can be improved based on the accurate estimation of the soil salinity, according to the soil type. We collected field data relating to six salinized soils, Haplic Solonchaks (HSK), Stagnic Solonchaks (SSK), Calcic Sonlonchaks (CSK), Fluvic Solonchaks (FSK), Haplic Sonlontzs (HSN), and Takyr Solonetzs (TSN), in the Hetao Plain of the upper reaches of the Yellow River, and measured the in situ hyperspectral, pH, and electrical conductivity (EC) values of a total of 231 soil samples. The two-dimensional spectral index, topographic factors, climate factors, and soil texture were considered. Several models were used for the inversion of the saline soil types: partial least squares regression (PLSR), random forest (RF), extremely randomized trees (ERT), and ridge regression (RR). The spectral curves of the six salinized soil types were similar, but their reflectance sizes were different. The degree of salinization did not change according to the spectral reflectance of the soil types, and the related properties were inconsistent. The Pearson's correlation coefficient (PCC) between the two-dimensional spectral index and the EC was much greater than that between the reflectance and EC in the original band. In the two-dimensional index, the PCC of the HSK-NDI was the largest (0.97), whereas in the original band, the PCC of the SSK400 nm was the largest (0.70). The two-dimensional spectral index (NDI, RI, and DI) and the characteristic bands were the most selected variables in the six salinized soil types, based on the variable projection importance analysis (VIP). The best inversion model for the HSK and FSK was the RF, whereas the best inversion model for the CSK, SSK, HSN, and TSN was the ERT, and the CSK-ERT had the best performance (R2 = 0.99, RMSE = 0.18, and RPIQ = 6.38). This study provides a reference for distinguishing various salinization types using hyperspectral reflectance and provides a foundation for the accurate monitoring of salinized soil via multispectral remote sensing. [ABSTRACT FROM AUTHOR]

The long-term overuse of fertilizers negatively affects soil chemical properties and health, causing unsustainable agricultural development. Although many studies have focused on the effects of long-term fertilization on soil properties, few comparative and comprehensive studies have been conducted on fertilization management over the past 35 years in China. This meta-analysis (2058 data) evaluated the effects of the fertilizer, climate, crop types, cultivation duration and soil texture on the soil chemical properties of Chinese croplands. NPKM (NPK fertilizers + manure) led to the highest increase in pH (−0.1), soil organic carbon (SOC) (+67%), total nitrogen (TN) (+63%), alkali-hydrolysable nitrogen (AN) (+70%), total phosphorus (TP) (+149%) and available potassium (AK) (+281%) compared to the unfertilized control, while the sole nitrogen fertilizer (N) led to the lowest increase. The SOC (+115%) and TN (+84%) showed the highest increase under the influence of NPKM in an arid region. The increase in the chemical properties was higher in unflooded crops, with the maximum increase in the wheat–maize rotation, compared to rice, under NPKM. The SOC and TN increased faster under the influence of organic fertilizers (manure or straw) compared to mineral fertilization. Fertilizers produced faster effects on the change in the SOC and TN in sandy loam compared to the control. Fertilizers showed the highest and lowest effects on change in pH, organic C to total N ratio (C/N), TP and TK in clay loam with the cultivation duration. NPKM greatly increased the C/N compared to NPK in an arid region by 1.74 times and in wheat by 1.86 times. Reaching the same SOC increase, the lowest TN increase was observed in wheat, and the lowest increase in TP and AK was observed in rice, compared to the other crops. These results suggest that organic fertilizers (manure or straw) play important roles in improving soil fertility and in acidification. NPKM greatly increased the potential for soil C sequestration in wheat and in the arid region. The small increases in TP and TK can increase the SOC in rice and in the humid region. Therefore, considering the crop types and climatic conditions, reduced fertilization and the combination of mineral fertilizers with manure may be the best ways to avoid agricultural soil deterioration and increase soil carbon sequestration. [ABSTRACT FROM AUTHOR]

Inorganic and organic fertilizers have been widely used to maintain crop yields. However, several studies have demonstrated that the dissolution of carbonates in agricultural soils by the acidification induced by N-fertilizers can result in their total or partial loss in the tilled layer of some agricultural soils. The effect of inorganic and organic fertilization on carbonates in calcareous semiarid Mediterranean soils has been less studied and is still unclear. Based on a 25-year field experiment, we investigated the effects of different fertilization strategies on the soil pH, inorganic C content, and in the proportion of pedogenic carbonates in the topsoil (0-30 cm) of a carbonate-rich soil in Navarre (N Spain). Five treatments were compared: no amendments as a control (SC), mineral fertilization (MF), and the application of sewage sludge at different doses (80 Mg ha-1 every year (80-1), 40 Mg ha-1 every year (40-1) and 40 Mg ha-1 every four years (40-4). Results showed a decrease in soil pH values by increasing the amount of sewage sludge and a small alteration in the calcite structure particularly in 40-4. However, no significant differences between treatments were found in the total content of carbonates nor in the proportion of pedogenic carbonates. The high concentration of total carbonates in the soil (16.09 ± 0.48%), and of the proportion of pedogenic carbonates (40.21 ± 1.29%, assuming a d13C of primary carbonates = 0 ?) seemed elevated enough to compensate for the observed acidification in the studied soil. In the case of MF, no changes were observed in the pH values, nor in the carbonate content (total and pedogenic). This suggests that the use of sewage sludge could induce changes in the future at a faster rate and of greater dimension than the use of mineral fertilizers such as the ones used in this field (46% urea, superphosphate and ClK). [ABSTRACT FROM AUTHOR]

The soil microbial community is a key indicator to evaluate the soil health and productivities in agricultural ecosystems. Monoculture and conversions of forests to tea plantations have been widely applied in tea plantation globally, but long-term monoculture of tea plantation could lead to soil degradation and yield decline. Understanding how long-term monoculture systems influence the soil health and ecosystem functions in tea plantation is of great importance for soil environment management. In this study, through the comparison of three independent tea plantations across eastern China composed of varying stand ages (from 3 to 90 years after conversion from forest), we found that long-term tea monoculture led to significant increases in soil total organic carbon (TOC) and microbial nitrogen (MBN). Additionally, the structure, function, and co-occurrence network of soil bacterial communities were investigated by pyrosequencing 16S rRNA genes. The pyrosequencing analysis revealed that the structures and functions of soil bacterial communities were significantly affected by different stand ages, but sampling sites and land-use conversion (from forest to tea plantation) had stronger effects than stand age on the diversity and structure of soil bacterial communities. Soil bacterial diversity can be improved with increasing stand ages in tea plantation. Further RDA analysis revealed that the C and N availability improvement in tea plantation soils led to the variation of structure and function in soil bacterial communities. Moreover, co-occurrence network analysis of soil bacterial communities also demonstrated that interactions among soil bacteria taxa were strengthened with increasing stand age. Our findings suggest that long-term monoculture with proper managements could be beneficial to soil ecosystems by increasing the C and N content and strengthening bacterial associations in tea plantations. Overall, this study provides a comprehensive understanding of the impact of land-use change and long-term monoculture stand age on soil environments in tea plantation. [ABSTRACT FROM AUTHOR]

An accurate estimation of soil electrical conductivity (EC) using hyperspectral techniques is of great significance for understanding the spatial distribution of solutes and soil salinization. Although spectral transformation has been widely used in data pre-processing, the performance of different pre-processing techniques (or combination methods) on different models of the same data set is still ambiguous. Moreover, extremely randomized trees (ERT) and light gradient boosting machine (LightGBM) models are new learning algorithms with good generalization performance (soil moisture and above-ground biomass), but are less studied in estimating soil salinity in the visible and near-infrared spectra. In this study, 130 soil EC data, soil measured hyperspectral data, topographic factors, conventional salinity indices such as Salinity Index 1, and two-band (2D) salinity indices such as ratio indices, were introduced. The five spectral pre-processing methods of standard normal variate (SNV), standard normal variate and detrend (SNV-DT), inverse (1/OR) (OR is original spectrum), inverse-log (Log(1/OR) and fractional order derivative (FOD) (range 0–2, with intervals of 0.25) were performed. A gradient boosting machine (GBM) was used to select sensitive spectral parameters. Models (extreme gradient boosting (XGBoost), LightGBM, random forest (RF), ERT, classification and regression tree (CART), and ridge regression (RR)) were used for inversion soil EC and model validation. The results reveal that the two-dimensional correlation coefficient highlighted EC more effectively than the one-dimensional. Under SNV and the second order derivative, the two-dimensional correlation coefficient increased by 0.286 and 0.258 compared to the one-dimension, respectively. The 13 characteristic factors of slope, NDI, SI-T, RI, profile curvature, DOA, plane curvature, SI (conventional), elevation, Int2, aspect, S1 and TWI provided 90% of the cumulative importance for EC using GBM. Among the six machine models, the ERT model performed the best for simulation (R2 = 0.98) and validation (R2 = 0.96). The ERT model showed the best performance among the EC estimation models from the reference data. The kriging map based on the ERT simulation showed a close relationship with the measured data. Our study selected the effective pre-processing methods (SNV and the 2 order derivative) using one- and two-dimensional correlation, 13 important factors and the ERT model for EC hyperspectral inversion. This provides a theoretical support for the quantitative monitoring of soil salinization on a larger scale using remote sensing techniques. [ABSTRACT FROM AUTHOR]

Treating soils with pyrolyzed biomass, that is biochar, is proposed as a conditioner and a carbon geoengineering measure. Rice is known as a strategic crop and rice husk is a cheap and available feedstock material for biochar in particular in Asia. We conducted a field experiment with laboratory biochar (LB) and locally produced [in‐situ biochar (IB)] applied at rates of 10 and 20 t ha−1 using a randomized block design in three replicates to examine the efficiency of IB for improving soil condition for rice production, and to propose a cheap and in‐farm applicable measure to decrease greenhouse gases (GHGs) emissions from the agricultural sector. Grain yield significantly increased following biochar addition by 52.2%, 53.2%, 65.4%, and 67.2% in LB10, IB10, LB20, and IB20, respectively. Total biomass in all biochar treatments had a significant difference (p < 0.05) compared with our control and the highest biomass belonged to LB20 and IB20 with 12.2 and 15.7 t ha1, respectively. The highest grain nitrogen, phosphorus, and potassium was in IB20. Compared to the control, IB20 significantly decreased emissions of CH4 by 72.3%, N2O by 85.8%, and CO2 by 32.9%. IB is as effective as LB. IB production and application provide a sustainable management approach for dealing with crop residues, improves soil conditions (aeration and nutrients availability) for crop growth, and directly and in a practical way involves farmers in GHGs reduction policies. [ABSTRACT FROM AUTHOR]

Although the Urmia Lake has undergone remarkable drought conditions within the past decades mainly due to climate change, drought studies covering the entire Urmia Lake Basin and all drought aspects are lacking. The present study investigated the spatial and temporal drought conditions in the Urmia Lake Basin for the past (1988-2017) and future (2021-2050 and 2051-2080) periods using five general circulation models (GCMs) under the IPCC (Intergovernmental Panel on Climate Change) scenarios RCP 2.6, RCP 4.5, and RCP 8.5. The standardized precipitation index (SPI) and standardized precipitation and evapotranspiration index (SPEI) were compared. The SPEI predicted more drought events than the SPI, and it seemed to be a more suitable drought index than the SPI for the basin. In general, the future periods would encounter less drought conditions in terms of significant drought trends and duration than the observed period under all scenarios, but the frequency of quarterly severe drought events in the future periods would be higher than in the observed period. Furthermore, the stations Urmia (western bank) and Tabriz and Maragheh (eastern banks) would face the highest frequency of different types of quarterly drought events in the future periods compared with the observed period. The predicted high frequencies of drought events for the future periods can intensify the current low water level situation of the Urmia Lake, which seriously threatens all types of ecosystems in the basin. Therefore, serious actions need to be taken into account for efficient ecosystem and water resources management in the basin. [ABSTRACT FROM AUTHOR]