Soil organic carbon of an intensively reclaimed region in China: Current status and carbon sequestration potential.

Land reclamation has been highly intensive in China, resulting in a large amount of soil organic carbon (SOC) loss to the atmosphere. Evaluating the factors which drive SOC dynamics and carbon sequestration potential in reclaimed land is critical for improving soil fertility and mitigating global warming. This study aims to determine the current status and factors important to the SOC density in a typical reclaimed land located in Eastern China, where land reclamation has been undergoing for centuries. A total of 4746 topsoil samples were collected from 2007 to 2010. The SOC density of the reclaimed land (3.18±0.05kgCm(-2); mean±standard error) is significantly lower than that of the adjacent non-reclaimed land (5.71±0.04kgCm(-2)) (p<0.05). A Random Forest model is developed and it captures the relationships between the SOC density and the environmental/anthropogenic factors (R(2)=0.59). The soil pH, land use, and elevation are the most important factors for determining SOC dynamics. In contrast, the effect of the reclamation age on the SOC density is negligible, where SOC content in the land reclaimed during years 1047-1724 is as low as that reclaimed during years 1945-2004. The scenario analysis results indicate that the carbon sequestration potential of the reclaimed lands may achieve a maximum of 5.80±1.81kgCO2m(-2) (mean±SD) when dryland is converted to flooded land with vegetable-rice cropping system and soil pH of ~5.9. Note that in some scenarios the methane emission substantially offsets the carbon sequestration potential, especially for continuous rice cropping system. With the optimal setting for carbon sequestration, it is estimated that the dryland reclaimed in the last 50years in China is able to sequester 0.12milliontons CO2 equivalent per year.

A Comparative Assessment of the Influences of Human Impacts on Soil Cd Concentrations Based on Stepwise Linear Regression, Classification and Regression Tree, and Random Forest Models.

Soil cadmium (Cd) contamination has attracted a great deal of attention because of its detrimental effects on animals and humans. This study aimed to develop and compare the performances of stepwise linear regression (SLR), classification and regression tree (CART) and random forest (RF) models in the prediction and mapping of the spatial distribution of soil Cd and to identify likely sources of Cd accumulation in Fuyang County, eastern China. Soil Cd data from 276 topsoil (0-20 cm) samples were collected and randomly divided into calibration (222 samples) and validation datasets (54 samples). Auxiliary data, including detailed land use information, soil organic matter, soil pH, and topographic data, were incorporated into the models to simulate the soil Cd concentrations and further identify the main factors influencing soil Cd variation. The predictive models for soil Cd concentration exhibited acceptable overall accuracies (72.22% for SLR, 70.37% for CART, and 75.93% for RF). The SLR model exhibited the largest predicted deviation, with a mean error (ME) of 0.074 mg/kg, a mean absolute error (MAE) of 0.160 mg/kg, and a root mean squared error (RMSE) of 0.274 mg/kg, and the RF model produced the results closest to the observed values, with an ME of 0.002 mg/kg, an MAE of 0.132 mg/kg, and an RMSE of 0.198 mg/kg. The RF model also exhibited the greatest R2 value (0.772). The CART model predictions closely followed, with ME, MAE, RMSE, and R2 values of 0.013 mg/kg, 0.154 mg/kg, 0.230 mg/kg and 0.644, respectively. The three prediction maps generally exhibited similar and realistic spatial patterns of soil Cd contamination. The heavily Cd-affected areas were primarily located in the alluvial valley plain of the Fuchun River and its tributaries because of the dramatic industrialization and urbanization processes that have occurred there. The most important variable for explaining high levels of soil Cd accumulation was the presence of metal smelting industries. The good performance of the RF model was attributable to its ability to handle the non-linear and hierarchical relationships between soil Cd and environmental variables. These results confirm that the RF approach is promising for the prediction and spatial distribution mapping of soil Cd at the regional scale.

Topographic dependence of cropland transformation in China during the first decade of the 21st century.

Terrain plays a critical role in the selection of cropland. As a physical and geographical element of the landscape, terrain is an important limiting factor in land use change and has a strong influence on human activities. The objectives of this study are to investigate the topographic characteristics of cropland-related transformations in China during the first decade of the 21st century and to explore the implications of land use change as it relates to securing a national food supply. A 2010 satellite-based land use dataset and the DEM data were used to conduct spatial statistical analysis using altitude, slope, and fragmentation data. The results showed the following. (1) As the urbanization and industrialization of China occur, and China attempts to replace this occupied cropland with newly reclaimed cropland, the topography of the most recently reclaimed cropland has been more poorly suited to farming than the topography of the occupied cropland it replaces in most provinces. (2) The area of occupied cropland was much larger than of those reclaimed; the qualities of occupied and reclaimed cropland were significantly different. (3) Land reclamation mainly occurred in northern China, instead of in southern China, which has a higher level of economic development. Our findings imply that the potential area available for cropland production may be limited.