Depth-dependent soil organic carbon dynamics of croplands across the Chengdu Plain of China from the 1980s to the 2010s.

Agricultural soils have tremendous potential to sequester soil organic carbon (SOC) and mitigate global climate change. However, agricultural land use has a profound impact on SOC dynamics, and few studies have explored how agricultural land use combined with soil conditions affect SOC changes throughout the soil profile. Based on a paired soil resampling campaign in the 1980s and 2010s, this study investigated the SOC changes of the soil profile caused by agricultural land use and the correlations with parent material and topography across the Chengdu Plain of China. The results showed that the SOC content increased by 3.78 g C/kg in the topsoil (0-20 cm), but decreased in the 20-40 cm and 40-60 cm soil layers by 0.90 and 1.26 g C/kg respectively. SOC increases in topsoil were observed for all types of agricultural land. Afforestation on former agricultural land also caused SOC decreases in the 20-60 cm soil layers, while SOC decreases only occurred in the 40-60 cm soil layer for agricultural land using a traditional crop rotation (i.e. traditional rice-wheat/rapeseed rotation) and with rice-vegetable rotations converted from the traditional rotations. For each agricultural land use, SOC decreases in deep soils only occurred in high relief areas and in soils formed from Q4 (Quaternary Holocene) grey-brown alluvium and Q4 grey alluvium that had a relatively low soil bulk density and clay content. The results indicated that SOC change caused by agricultural land use was depth dependent and that the effects of agricultural land use on soil profile SOC dynamics varied with soil characteristics and topography. Subsoil SOC decreases were more likely to occur in high relief areas and in soils with low soil bulk density and low clay content.

Divergent responses of cropland soil organic carbon to warming across the Sichuan Basin of China.

Cropland soils are considered to have the potential to sequester carbon (C). Warming can increase soil organic C (SOC) by enhancing primary production, but it can also cause carbon release from soils. However, the role of warming in governing cropland SOC dynamics over broad geographic scales remains poorly understood. Using over 4000 soil samples collected in the 1980s and 2010s across the Sichuan Basin of China, this study assessed the warming-induced cropland SOC change and the correlations with precipitation, cropland type and soil type. Results showed mean SOC content increased from 11.10 to 13.85 g C kg-1. Larger SOC increments were observed under drier conditions (precipitation < 1050 mm, dryland and paddy-dryland rotation cropland), which were 1.67-2.23 times higher than under wetter conditions (precipitation > 1050 mm and paddy fields). Despite the significant associations of SOC increment with crop productivity, precipitation, fertilization, cropland type and soil type, warming also acted as one of major contributors to cropland SOC change. The SOC increment changed parabolically with the rise in temperature increase rate under relatively drier conditions, while temperature increase had no impact on cropland SOC increment under wetter conditions. Meanwhile, the patterns of the parabolical relationship varied with soil types in drylands, where the threshold of temperature increase rate, the point at which the SOC increment switched from increasing to decreasing with warming, was lower for clayey soils (Ali-Perudic Argosols) than for sandy soils (Purpli-Udic Cambosols). These results illustrate divergent responses of cropland SOC to warming under different environments, which were contingent on water conditions and soil types. Our findings emphasize the importance of formulating appropriate field water management for sustainable C sequestration and the necessity of incorporating environment-specific mechanisms in Earth system models for better understanding of the soil C-climate feedback in complex environments.

Soil acidification of the soil profile across Chengdu Plain of China from the 1980s to 2010s.

Soil acidification is a major environmental issue associated with intensive agricultural land use. Rapid urbanization has inevitably caused great changes in agricultural land use around urban areas. However, the effects of agricultural land-use change and soil parent material on the pH dynamics of the whole soil profile remain poorly understood. Based on a paired soil resampling campaign in the 1980s and 2010s, this study evaluated the effects of agricultural land-use change and parent materials on the pH dynamics of the soil profile across the Chengdu Plain of China. The results showed that soil pH significantly decreased by 1.20, 0.72, 0.66 and 0.68 units at the 0-20, 20-40, 40-60 and 60-100 cm soil depths, respectively. Conversions of traditional rice-wheat/rapeseed rotations to rice-vegetable rotations and afforested land significantly increased the magnitude of pH decline at the 0-60 cm soil depth. Soils formed from Q4 grey-brown alluvium and Q4 grey alluvium, which had a lower soil bulk density (BD) and higher sand content, showed a much higher magnitude of pH decline than soils formed from Q3 (Quaternary Pleistocene) old alluvium, and significant acidification of deep soils only occurred in soils formed from Q4 (Quaternary Holocene) grey-brown alluvium and Q4 grey alluvium. These results suggested that agricultural land-use change aggravated acidification in the soil profile and the soil acidification degrees were parent material-dependent; in particular, significant acidification of deep soils was more inclined to occur in soils with lower soil BD and higher sand content due to their effects on the downward movement of acids and the penetration resistance of plant roots. More attention should be given to minimizing or preventing acidification of both topsoil and deep soils aggravated by agricultural land-use change across urban agricultural areas.

[Profile Distribution of Paddy Soil Organic Carbon and Its Influencing Factors in Chengdu Plain].

Understanding the effects of environmental factors on the profile distribution of soil organic carbon (SOC) is a base to accurately modeling the continuous change of SOC in vertical and three-dimensional spatial distributions, as well as precisely estimating SOC storage. Based on 171 soil profiles collected from Chengdu Plain, the effects of environmental factors (including the parent material, soil type, elevation, distance from river, and land use) on the profile distribution of paddy SOC to a depth of 1 m were evaluated through the exponential decay function. The results indicated that SOC was estimated at 19.42, 9.59, 5.99, and 5.20 g·kg-1 at depths of 0-20, 20-40, 40-60, and 60-100cm, respectively, showing a significant decrease with increased depth. Soil organic carbon was mainly concentrated above a 40 cm soil depth, accounting for 72.17% of the total profile, which could be crucial to studying the carbon source/sink of paddy soils in Chengdu Plain. The parameters of the exponential decay function had a similar spatial pattern, indicating their spatial dependence. The nugget coefficients for C and k were 55.400% and 47.671%, respectively, indicating that paddy SOC in the study area was affected by both structural and random factors. Regression analysis implied that the parent material and soil genius were the dominant factors influencing the profile distribution of SOC. Nevertheless, elevation, distance from river, and land use should also be taken into consideration. It has been concluded that the parent material and soil genius should be premeditated when fitting the vertical distribution of SOC, modeling the three-dimensional prediction of soil organic carbon, and estimating soil carbon storage in the paddy soils of Chengdu Plain.

Prediction of soil cadmium distribution across a typical area of Chengdu Plain, China.

A suitable method and appropriate environmental variables are important for accurately predicting heavy metal distribution in soils. However, the classical methods (e.g., ordinary kriging (OK)) have a smoothing effect that results in a tendency to neglect local variability, and the commonly used environmental variables (e.g., terrain factors) are ineffective for improving predictions across plains. Here, variables were derived from the obvious factors affecting soil cadmium (Cd), such as road traffic, and were used as auxiliary variables for a combined method (HASM_RBFNN) that was developed using high accuracy surface modelling (HASM) and radial basis function neural network (RBFNN) model. This combined method was then used to predict soil Cd distribution in a typical area of Chengdu Plain in China, considering the spatial non-stationarity of the relationships between soil Cd and the derived variables based on 339 surface soil samples. The results showed that HASM_RBFNN had lower prediction errors than OK, regression kriging (RK) and HASM_RBFNNs, which didn't consider the spatial non-stationarity of the soil Cd-derived variables relationships. Furthermore, HASM_RBFNN provided improved detail on local variations. The better performance suggested that the derived environmental variables were effective and HASM_RBFNN was appropriate for improving the prediction of soil Cd distribution across plains.