Hong-Jie Wang

National Scale Analysis of Soil Organic Carbon Storage in China Based on Chinese Soil Taxonomy

Patterns of soil organic carbon (SOC) storage and density in various soil types or locations are the foundation for examining the role of soil in the global carbon cycle. An assessment of SOC storage and density patterns in China based on soil types as defined by Chinese Soil Taxonomy (CST) and the recently compiled digital 1:1000000 Soil Database of China was conducted to generate a rigorous database for the future study of SOC storage. First, SOC densities of 7292 soil profiles were calculated and linked by soil type to polygons of a digital soil map using geographic information system resulting in a 1:1000000 SOC density distribution map of China. Further results showed that soils in China covered 9281×10km^2 with a total SOC storage of 89.14 Gt and a mean SOC density 96.0t ha^(-1). Among the 14 CST orders, Cambosols and Argosols constituted high percentage of Chinas total SOC storage, while Andosols, Vertosols, and Spodsols had a low percentage. As for SOC density, Histosols were the highest, while Primosols were the lowest. Specific patterns of SOC storage of various soil types at the CST suborder, group, and subgroup levels were also described. Results obtained from the study of SOC storage and density of all CST soil types would be not only useful for international comparative research, but also for more accurately estimating and monitoring of changes of SOC storage in China.

Major nutrient balances in small-scale vegetable farming systems in peri-urban areas in China

Balances of major nutrients such as nitrogen (N), phosphorus (P), and potassium (K) in small-scale farming systems are of critical importance to nutrient management and sustainable agricultural development. Mass balances of N, P, and K and some of their influencing factors were studied for two years from July 2003 to July 2005 on small-scale vegetable-farming systems in two contrasting peri-urban areas (Nanjing and Wuxi) of the Yangtze river delta region of China. This balance approach considered organic fertilizer inputs (cow manure, pig manure, and human biosolids), inorganic fertilizer inputs (urea, composite fertilizer, and phosphates), irrigation water, and atmospheric deposition; and considered outputs by vegetables. Input via organic fertilizers was significant for all element balances in the Nanjing area. Inorganic and organic fertilizer, particularly inorganic fertilizer, contributed major nutrient inputs to the system in the Wuxi area. Compared with nutrient output by vegetables, there were significant surpluses of N and P on two vegetable farm systems. Furthermore, N surplus in the Nanjing area was higher than that in the Wuxi area with an inverse relationship to P surplus. In contrast, the general trend of K balances was negative on both sites; hence, the nutrient use efficiency was significantly lower for N and P than K. The nutrient imbalance may be attributed to the differences between fertilizer types and management modes driven by social economic status differences among farmer households. The large N and P net excess creates an environmental threat because of potential losses to ground or surface waters, whereas negative K balance creates soil fertility risks. The results highlight researchers’ and farmers’ need to develop rational fertilization technology to optimize nutrient management on vegetable farmlands to promote sustainable agricultural development in peri-urban areas.

Cross-Reference Benchmarks for Translating the Genetic Soil Classification of China into the Chinese Soil Taxonomy

ABSTRACT Soil classification is the foundation for exchange and extension of research findings in soil science and for modern management of soil resources. This study explained database and research methodology to create a cross-reference system for translating the Genetic Soil Classification of China (GSCC) into the Chinese Soil Taxonomy (CST). With the help of the CST keys, each of the 2540 soil species in GSCC has been interpreted to its corresponding soil order, suborder, great group, and sub-group in CST. According to the methodology adopted, the assigned soil species have been linked one another to their corresponding polygons in the 1:1000000 digital soil map of China. Referencibility of each soil species between the GSCC and CST systems was determined statistically on the basis of distribution area of each soil species at a high taxon level of the two systems. The soils were then sorted according to their maximum referencibility and classified into three categories for discussion. There were 19 soil great groups in GSCC with maximum referencibility > 90% and 22 great groups between 60%–90%. These soil great groups could serve as cross-reference benchmarks. There were 19 great groups in GSCC with maximum referencibility

Storage and Spatial Variation of Phosphorus in Paddy Soils of China

Abstract Due to the growing concern about the agricultural phosphorus (P) losses pollution, an in-depth understanding of P in paddy soils of China would be helpful in providing a national perspective of the environmental impact of P cycling and fertility on Chinas farms. In this study, we evaluated the P storage and the P density of paddy soils in China, characterized the spatial variations of P among the subgroups of paddy soils and soil regions in China, and evaluated the P data using GIS-based analysis, which included a newly compiled 1:1 000 000 digital soil map of China, and using 1 490 soil profiles. The available and total P densities of paddy soils were 6.7 and 698.5 g m −3 , respectively. Overall in China, the total P storage within 1 m of paddy soils was estimated to be 330.2 Tg. The P density of paddy soils varied substantially with subgroups due to the different soil water regimes such as groundwater table and soil drainage. The P availability in paddy soils, especially in surface layer, was higher in high temperature and precipitation areas. Further research is needed to examine more anthropogenic impact factors, such as increasing use of chemical fertilizer.

Scale Effect of Climate and Soil Texture on Soil Organic Carbon in the Uplands of Northeast China

Abstract Understanding how spatial scale influences commonly-observed effects of climate and soil texture on soil organic carbon (SOC) storage is important for accurately estimating the SOC pool at different scales. The relationships among climate factors, soil texture and SOC density at the regional, provincial, city, and county scales were evaluated at both the soil surface (0–20 cm) and throughout the soil profile (0–100 cm) in the Northeast China uplands. We examined 1 022 profiles obtained from the Second National Soil Survey of China. The results indicated that the relationships between climate factors and SOC density generally weakened with decreasing spatial scale. The provincial scale was optimal to assess the relationship between climate factors and SOC density because regional differences among provinces were covered up at the regional scale. However, the relationship between soil texture and SOC density had no obvious trend with increasing scale and changed with temperature. There were great differences in the impacts of climate factors and soil texture on SOC density at different scales. Climate factors had a larger effect on SOC density than soil texture at the regional scale. Similar trends were seen in Heilongjiang and eastern Inner Mongolia at the provincial scale. But, soil texture had a greater effect on SOC density compared with climate factors in Jilin and Liaoning. At the city and county scales, the influence of soil texture on SOC density was more important than climate factors.

Source identification and spatial variability of nitrogen, phosphorus, and selected heavy metals in surface water and sediment in the riverine systems of a peri-urban interface

This study was conducted, using an elaborate sampling activity of surface water and sediment within an industrially developed peri-urban interface with a riverine system in Wuxi, Taihu Lake area, China, to address the following objectives: (i) to identify possible sources of selected nutrients such as N and P, and heavy metals such as Cu, Zn, Pb, Cr, and Cd in surface water and sediments, and (ii) to determine the spatial variability of these elements around the source areas. The results showed that concentrations of N and P in the surface water and Cu, Zn, Cr, and Pb in most of sediments had exceeded trigger levels established by the nation, while all metal concentrations in surface water were still below the levels. The source identification of these pollutants in water and sediments in terms of their spatial distribution pattern and principal component analysis showed that: (i) Pb, N and organic carbon (OC) were closely related to the influence of urban runoff and domestic wastewater; (ii) Cu and Cr were related to the influence of industries; and (iii) P and Zn were related to the effect of both urban and industries. The results of this study showed that urbanization is the main contributor for N and P in the peri-urban interface instead of agricultural sources. The concentrations of N, P, Cu, Zn, Pb, and Cr in the sediment along the main river decreased with the distance away from the source area. The concentrations of these elements decreased to the background levels at about 4.5–5.5 km downstream of the source of origin.

Effect of Soil Sampling Density on Detected Spatial Variability of Soil Organic Carbon in a Red Soil Region of China

Abstract Spatial variability of soil organic carbon (SOC) of different land use patterns and soil types was examined in a county-wide red soil region of South China, using six sampling densities, 14, 34, 68, 130, 255, and 525 samples designed by the method of grid sampling in 6 different grid sizes, labeled as D14, D34, D68, D130, D255, and D525, respectively. The results showed that the coefficients of variation (CVs) of SOC decreased gradually from 62.8% to 47.4% with the increase in soil sampling densities. The SOC CVs in the paddy field change slightly from 30.8% to 28.7%, while those of the dry farmland and forest land decreased remarkably from 58.1% to 48.7% and from 99.3% to 64.4%, respectively. The SOC CVs of the paddy soil change slightly, while those of red soil decreased remarkably from 82.8% to 63.9%. About 604, 500, and 353 ( P 0.05) samples would be needed a number of years later if the SOC change was supposedly 1.52 g kg −1 , based on the CVs of SOC acquired from the present sampling densities of D14, D68, and D525, respectively. Moreover, based on the same SOC change and the present time CVs at D255, the ratio of samples needed for paddy field, dry farmland, and forest land should be 1:0.81:3.33, while the actual corresponding ratio in an equal interval grid sampling was 1:0.74:0.46. These indicated that the sampling density had important effect on the detection of SOC variability in the county-wide region, the equal interval grid sampling was not efficient enough, and the respective CV of each land use or soil type should be fully considered when determining the sampling number in the future.

Relationship between oriental migratory locust plague and soil moisture extracted from MODIS data

Abstract Locust plagues have been the source of some of the most severe natural disasters in human history. Soil moisture content is among the most important of the numerous factors influencing plague onset and severity. This paper describes a study initiated in three pilot locust plague monitoring regions, i.e., Huangzao, Yangguanzhuang, and Tengnan in Huanghua county, Hebei province, China, to examine the impact of soil moisture status on oriental migratory locust [ Locusta migratoria manilensis (L.) Meyen] plague breakout as related to the life cycle, oviposition in autumn, survival in winter, and incubation in summer. Thirty-nine temperature vegetation dryness index (TVDI) data sets, which represent soil moisture content, were extracted from MODIS remote sensing images for two representative time periods: a severe locust plague breakout year (2001–2002) and a slight plague year (2003–2004). TVDI values demonstrated distinctive soil moisture status differences between the 2 years concerned. Soil moisture conditions in the severe plague year were shown to be lower than those in slight plague year. In all three pilot regions, average TVDI value in the severe plague year was 0.07 higher than that in slight plague year, and monthly TVDI values in locust oviposition period (September and October) and incubation period (March, April and May) were higher than their corresponding monthly figures in slight plague year. No remarkable TVDI differences were found in other months during the locust life cycle between the 2 years. TVDI values for September and October (2001), March, April and May (2002) were 0.11, 0.08, 0.16, 0.11 and 0.16 higher than their corresponding monthly figures in 2003–2004 period, respectively.

Application of categorical information in the spatial prediction of soil organic carbon in the red soil area of China

Abstract Predicting soil organic carbon (SOC) content distribution accurately from limited soil samples has received a great deal of attention recently in an effort to support soil fertility mapping and to improve our understanding of carbon sequestration variability. Kriging methods combined with auxiliary variables are frequently used at present. However, studies using categorical information, such as soil type and land use, which are closely related to local trends in SOC spatial variation, as auxiliary variables are seldom conducted. In the present investigation, a total of 254 surficial soil samples were collected in the study area, Yujiang county in the hilly red soil region of South China, and a comparison of performance of four kriging approaches was conducted, ordinary kriging (OK), kriging combined with soil-type information (KST), land use (KLU) and combined land use–soil type information (KLUST). Results of the assessment were based on 85 validation samples. The results indicate that the best correlation between the measured and predicted values for validation location was obtained with KLUST (r = 0.854), whereas the lowest was obtained using OK (r = 0.383). Furthermore, the root mean square error (RMSE) from KLUST (3.47 g kg−1) is the lowest, whereas the one obtained using OK (6.49 g kg−1) is the highest. The correlation coefficient and RMSE from KST (r = 0.784, RMSE = 4.15 g kg−1) and KLU (r = 0.795, RMSE = 3.95 g kg−1) are the second and third most correlated, respectively. Comparing the SOC distribution maps generated by the four prediction approaches, the KLUST rendering best reflects the local change associated with soil types and land uses, whereas the map from the OK is the least representative. The results demonstrate that soil type and land use have an important impact on SOC spatial distribution, and KLUST, which reduces their influence as a local trend, is an efficient and practical prediction approach for the hilly red soil region of South China.

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.