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Accumulation of soluble organic nitrogen (SON) in soil poses a significant threat to groundwater quality and plays an important role in regulating the global nitrogen cycle; however, most related studies have focused only on the upper 100-cm soil layers. Surface land-use management and soil properties may affect the vertical distribution of SON; however, their influence is poorly understood in deep soil layers. Therefore, this study assessed the response of SON concentration, pattern, and storage in deep regoliths to land-use conversion from woodlands to orchards in a subtropical hilly region. Our results showed that the SON stocks of the entire soil profile (up to 19.5 m) ranged from 254.5 kg N ha

Increased soil organic carbon (OC) in China has been reported in the past two decades, suggesting the sequestration of atmospheric carbon dioxide into soil, mitigating climate change and improving soil health. On the other hand, soil pH decrease had also been reported nationwide. If the two are related, the strategy of increasing soil OC could negatively affect soil quality for food production and the environment. We investigate this thread based on large-scale soil survey data from two provinces with typical soil and cropping patterns in the east and south of China, Jiangsu (102,600 km

Soil acidification along with base cations loss degrades soil quality and is a major environmental problem, especially in agroecosystems with extensive nitrogen (N) fertilization. So far, the rates of proton (H

The soil's pH is the single most important indicator of the soil's quality, whether for agriculture, pollution control or environmental health and ecosystem functioning. Well documented data on soil pH are sparse for the whole of China — data for only 4700 soil profiles were available from China's Second National Soil Inventory. By combining those data, standardized for the topsoil (0–20 cm), with 17 environmental covariates at a fine resolution (3 arc-second or 90 m) we have predicted the soil's pH at that resolution, that is at more than 109 points. We did so by parallel computing over tiles, each 100 km × 100 km, with two machine learning techniques, namely Random Forest and XGBoost. The predictions for the tiles were then merged into a single map of soil pH for the whole of China. The quality of the predictions were assessed by cross-validation. The root mean squared error (RMSE) was an acceptable 0.71 pH units per point, and Lin's Concordance Correlation Coefficient was 0.84. The hybrid model revealed that climate (mean annual precipitation and mean annual temperature) and soil type were the main factors determining the soil's pH. The pH map showed acid soil mainly in southern and north-eastern China, and alkaline soil dominant in northern and western China. This map can provide a benchmark against which to evaluate the impacts of changes in land use and climate on the soil's pH, and it can guide advisors and agencies who make decisions on remediation and prevention of soil acidification, salinization and pollution by heavy metals, for which we provide examples for cadmium and mercury.

To decipher Cu migration in paddy soils, which is important for understanding Cu supply in rice cultivation, Cu concentrations and isotope compositions were measured in a paddy soil profile in Suzhou, Eastern China, in the central Yangtze Delta. The results show that the variations in δ

Nitrogen (N)-induced soil acidification has received much attention worldwide. Nitrification and soil N mineralization are two key N cycle processes that affect soil acidification. However, the seasonal dynamics of soil pH under their combined influence is unclear. We studied the effect of N fertilization on soil pH and N transformations using 15N tracing in field lysimeters with soils developed from different parent materials (Quaternary red clay, sandstone, and basalt). Maize was planted with 200 kg N ha−1 yr−1 15N-labeled urea addition. During 7–45 days after fertilization, proton (H+) production due to nitrification of fertilizer N, nitrate (NO3−) leaching, and plant uptake exceeded H+ consumption by base cations mobilization and leaching, resulting in a significant soil pH decline. When nitrification activity decreased (after 45 days), due to exhausted ammonium (NH4+) availability, soil pH rose again. During the fallow period, acid neutralization due to base cation mobilization, and ammonification of soil organic N (SON) offset H+ production caused by nitrification of mineralized SON, leading to a sustained rise in soil pH. After the one-year experiment, no significant soil pH decrease was observed in any of the soils. Parent material had little effect on the seasonal dynamics of soil acidification, which appeared to be controlled by fertilization, environmental factors (temperature and moisture), and plant uptake. In subtropical regions, monitoring of soil pH on an annual basis may mask the effect of N fertilization on soil acidification.

Accurate estimation of soil carbon is essential for accounting carbon cycling on the background of global environment change. However, previous studies made little contribution to the patterns and stocks of soil inorganic carbon (SIC) in large scales. In this study, we defined the structure of the soil depth function to fit vertical distribution of SIC based on pedogenic knowledge across various landscapes. Soil depth functions were constructed from a dataset of 99 soil profiles in the alpine area of the northeastern Tibetan Plateau. The parameters of depth functions were mapped from environmental covariates using random forest. Finally, SIC stocks at three depth intervals in the upper 1 m depth were mapped across the entire study area by applying predicted soil depth functions at each location. The results showed that the soil depth functions were able to improve accuracy for fitting the vertical distribution of the SIC content, with a mean determination coefficient of R2 = 0.93. Overall accuracy for predicted SIC stocks was assessed on training samples. High Lin's concordance correlation coefficient values (0.84–0.86) indicate that predicted and observed values were in good agreement (RMSE: 1.52–1.67 kg m− 2 and ME: − 0.33 to − 0.29 kg m− 2). Variable importance showed that geographic position predictors (longitude, latitude) were key factors predicting the distribution of SIC. Terrain covariates were important variables influencing the three-dimensional distribution of SIC in mountain areas. By applying the proposed approach, the total SIC stock in this area is estimated at 75.41 Tg in the upper 30 cm, 113.15 Tg in the upper 50 cm and 190.30 Tg in the upper 1 m. We concluded that the methodology would be applicable for further prediction of SIC stocks in the Tibetan Plateau or other similar areas.