Shengxiang Xu

Effects of Soil Data and Simulation Unit Resolution on Quantifying Changes of Soil Organic Carbon at Regional Scale with a Biogeochemical Process Model

Soil organic carbon (SOC) models were often applied to regions with high heterogeneity, but limited spatially differentiated soil information and simulation unit resolution. This study, carried out in the Tai-Lake region of China, defined the uncertainty derived from application of the DeNitrification-DeComposition (DNDC) biogeochemical model in an area with heterogeneous soil properties and different simulation units. Three different resolution soil attribute databases, a polygonal capture of mapping units at 1∶50,000 (P5), a county-based database of 1∶50,000 (C5) and county-based database of 1∶14,000,000 (C14), were used as inputs for regional DNDC simulation. The P5 and C5 databases were combined with the 1∶50,000 digital soil map, which is the most detailed soil database for the Tai-Lake region. The C14 database was combined with 1∶14,000,000 digital soil map, which is a coarse database and is often used for modeling at a national or regional scale in China. The soil polygons of P5 database and county boundaries of C5 and C14 databases were used as basic simulation units. Results project that from 1982 to 2000, total SOC change in the top layer (0–30 cm) of the 2.3 M ha of paddy soil in the Tai-Lake region was +1.48 Tg C, −3.99 Tg C and −15.38 Tg C based on P5, C5 and C14 databases, respectively. With the total SOC change as modeled with P5 inputs as the baseline, which is the advantages of using detailed, polygon-based soil dataset, the relative deviation of C5 and C14 were 368% and 1126%, respectively. The comparison illustrates that DNDC simulation is strongly influenced by choice of fundamental geographic resolution as well as input soil attribute detail. The results also indicate that improving the framework of DNDC is essential in creating accurate models of the soil carbon cycle.

Zonal Differences in Correlation Patterns Between Soil Organic Carbon and Climate Factors at Multi-extent

Studying the relationship between climate factors and soil organic carbon (SOC) is vitally important. However, how SOC responses to climate (temperature and precipitation) at cohesive extents is poorly studied. Two transects of approximately the same length (transect P and transect T) were selected to examine the variation of SOC content in relation to mean annual temperature (MAT) and mean annual precipitation (MAP). The coefficients of partial correlation between SOC density and MAT (Rt) and MAP (Rp) were determined to quantify the relationships between SOC density and the two climate factors. The results indicated that for transect T, Rt was statistically significant once the extent level was greater than or equal to two fundamental extent units, while for transect P, Rp showed statistical significance only at extent levels which were greater than two fundamental extent units. At the same extent levels but in different transects, Rts exhibited no zonal difference, but Rps did once the extent level was greater than two fundamental extent units. Therefore, to study the relationship between SOC density and different climate factors, different minimum extent levels should be examined. The results of this paper could deepen the understanding of the impacts that SOC pool has on terrestrial ecosystem and global carbon cycling.

A WebGIS system for relating genetic soil classification of China to soil taxonomy

Soil classification is the basis for the exchange of soil science research results and the foundation for the application of modern soil resource management methods. A WebGIS-based system designed to relate genetic soil classification of China (GSCC) to soil taxonomy (ST) was developed to enhance global cooperation and to support communication between China and the other countries on important agricultural and environmental issues. The system has a Browse Server (B/S) structure and exploits the 1:1,000,000 soil databases of China using WebGIS functionality. This paper describes the application of the WebGIS system for easily accessing cross-reference information between GSCC to ST. First, we describe the three-level B/S structure of the system. The cross-reference methodologies, referenceability and maximum referenceability, are then explained and applied at three geographic scales (i.e. nation, region and pedon). Finally, three sub-modules based on the supported scales are described and illustrated with application scenarios to familiarize users with the inquiry system and its usage. The main advantage of the system is that it considers statistical similarity in the spatial distributions between the two different classification systems. Users with limited knowledge are able to obtain soil cross-reference information using an intuitive interface, which supports query, visualization and analysis via a web browser at the most detailed level. The inquiry system benefits the development of soil classification science and international academic exchange.

Economics- and policy-driven organic carbon input enhancement dominates soil organic carbon accumulation in Chinese croplands

Significance Soil organic carbon (C) stock in Chinese croplands increased by about 140 kg C ha−1 year−1 from 1980 to 2011. This soil organic C sequestration was largely due to drastic changes in management practices, such as fertilization, tillage, and residue treatments, induced by economic and policy incentives. Our analysis also indicates that excessive N inputs and inability to incorporate residue C into deeper soils will likely constrain the future C sequestration in Chinese croplands. These findings provide new insights into the causes and limitations of economics- and policy-driven soil C sequestration in China and offer some guidance for soil C management in many developing countries that are going through the similar economic and social transformations. China’s croplands have experienced drastic changes in management practices, such as fertilization, tillage, and residue treatments, since the 1980s. There is an ongoing debate about the impact of these changes on soil organic carbon (SOC) and its implications. Here we report results from an extensive study that provided direct evidence of cropland SOC sequestration in China. Based on the soil sampling locations recorded by the Second National Soil Survey of China in 1980, we collected 4,060 soil samples in 2011 from 58 counties that represent the typical cropping systems across China. Our results showed that across the country, the average SOC stock in the topsoil (0–20 cm) increased from 28.6 Mg C ha−1 in 1980 to 32.9 Mg C ha−1 in 2011, representing a net increase of 140 kg C ha−1 year−1. However, the SOC change differed among the major agricultural regions: SOC increased in all major agronomic regions except in Northeast China. The SOC sequestration was largely attributed to increased organic inputs driven by economics and policy: while higher root biomass resulting from enhanced crop productivity by chemical fertilizers predominated before 2000, higher residue inputs following the large-scale implementation of crop straw/stover return policy took over thereafter. The SOC change was negatively related to N inputs in East China, suggesting that the excessive N inputs, plus the shallowness of plow layers, may constrain the future C sequestration in Chinese croplands. Our results indicate that cropland SOC sequestration can be achieved through effectively manipulating economic and policy incentives to farmers.

Climatic effect on soil organic carbon variability as a function of spatial scale

ABSTRACT Soil organic carbon (SOC) is spatially heterogeneous. Understanding SOC variability as a function of varying scale is important for accurately estimating the SOC stock. We selected three zones in the Huang-Huai-Hai agricultural region of China to define temperature (T Zone), precipitation (P Zone) and temperature + precipitation (PT Zone) gradients, respectively. The zonal differences in SOC variability as a function of increasing scale were examined. The results demonstrated that the SOC stock varied substantially among the different zones. The coefficient of variation (CV) of the SOC stock was more elevated in the PT Zone and was influenced by scale level. The mean CV increased by 12.5%, 4.6% and 2.9% from 1C to 12C for PT, T and P Zone, respectively. Zonal SOC variability differences were not obvious at small scale, with the CV ratio consistently less than 0.003 in the three zones; however, they became detectable at higher scales (6C and 12C), with the CV ratio showing as: PT Zone > T Zone > P Zone. SOC zonal variability must be considered to reduce uncertainty for soil carbon stock estimation.

Effects of Subsetting by Parent Materials on Prediction of Soil Organic Matter Content in a Hilly Area Using Vis–NIR Spectroscopy

Assessment and monitoring of soil organic matter (SOM) quality are important for understanding SOM dynamics and developing management practices that will enhance and maintain the productivity of agricultural soils. Visible and near-infrared (Vis–NIR) diffuse reflectance spectroscopy (350–2500 nm) has received increasing attention over the recent decades as a promising technique for SOM analysis. While heterogeneity of sample sets is one critical factor that complicates the prediction of soil properties from Vis–NIR spectra, a spectral library representing the local soil diversity needs to be constructed. The study area, covering a surface of 927 km2 and located in Yujiang County of Jiangsu Province, is characterized by a hilly area with different soil parent materials (e.g., red sandstone, shale, Quaternary red clay, and river alluvium). In total, 232 topsoil (0–20 cm) samples were collected for SOM analysis and scanned with a Vis–NIR spectrometer in the laboratory. Reflectance data were related to surface SOM content by means of a partial least square regression (PLSR) method and several data pre-processing techniques, such as first and second derivatives with a smoothing filter. The performance of the PLSR model was tested under different combinations of calibration/validation sets (global and local calibrations stratified according to parent materials). The results showed that the models based on the global calibrations can only make approximate predictions for SOM content (RMSE (root mean squared error) = 4.23–4.69 g kg−1; R2 (coefficient of determination) = 0.80–0.84; RPD (ratio of standard deviation to RMSE) = 2.19–2.44; RPIQ (ratio of performance to inter-quartile distance) = 2.88–3.08). Under the local calibrations, the individual PLSR models for each parent material improved SOM predictions (RMSE = 2.55–3.49 g kg−1; R2 = 0.87–0.93; RPD = 2.67–3.12; RPIQ = 3.15–4.02). Among the four different parent materials, the largest R2 and the smallest RMSE were observed for the shale soils, which had the lowest coefficient of variation (CV) values for clay (18.95%), free iron oxides (15.93%), and pH (1.04%). This demonstrates the importance of a practical subsetting strategy for the continued improvement of SOM prediction with Vis–NIR spectroscopy.