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Ecological safe management of rice paddy landscapes is in focus of a joint research project comprising five German working groups and Chinese partners. The project is aiming at characterizing the scale-depending structures and processes of agricultural landscape of terraced paddy fields in southeast China. The specific objectives were the enlightenment of the linkage between remote sensible information and the spatial distribution of soil features, as well as soil structural processes and their relation to vertical and lateral water losses and solute leaching.The experimental watershed is located in southeast China. The soils which either developed from quaternary clay or red sandstone exhibit a (man-made) layered structure with three hydraulic-functional horizons: puddled layer, plough pan and the (water unsaturated) subsoil. The analysis of soil texture and selected chemical parameters on the catenary and catchment scale confirmed that even in old terraced and thoroughly modified landscapes, the original structures (unaffected by man) of catenary soil property distributions persist. Thus, the application of coregionalization techniques incorporating topographical attributes as explaining variables was found to be suitable to characterize soil property distributions on both the catenary and the catchment scale. On-site field scale investigations revealed that paddy soils exhibit a dynamic soil-water system which is driven by the mechanical seed bed preparation (puddling) on the one hand and drying and wetting cycles including ponded/flooded periods on the other. It was found that the hydraulic properties depend mainly on the duration of cultivation as a rice paddy. In contrast to earlier studies, we found that a further decrease in the Saturated hydraulic conductivity of the plough pan may still occur after 20 years. Even in older rice paddies, however, water losses may be significant mainly because of ineffective functioning of the surrounding bunds. Pedon and aggregate investigations demonstrated the pronounced dual porosity nature of the paddy soils with a macropor network consisting of cracks and biopores penetrating both the plough pan and the bunds. The shrinkage potential of the puddle layer was higher in older paddy fields than in younger ones while it was vice versa for soil from the plough pan. Swelling and shrinkage affected also the living conditions for soil microorganisms especially after drainage when the habitable pore space was significantly reduced. Pore scale and micro-biological investigations revealed that drainage induced stress reduced micro-biodiversity and decreased abundances of soil inhabiting microorganisms. In addition to newly proposed management strategies with recurrent wetting and drying cycles, we suggest maintaining (saturated) equilibrium conditions over longer periods to reduce soil structural dynamics and the risks of water losses and chemical leaching involved with preferential flow. (C) 2008 Elsevier B.V. All rights reserved.

An extensive knowledge of the temporal variability of soil fertility parameters and how this variation affects the environment is imperative to a wide range of disciplines within agricultural science for optimal crop production and ecosystem preservation. This paper examines the temporal variability of soil pH, organic matter (OM), cation exchange capacity (CEC), total nitrogen (TN), total phosphorus (TP), available phosphorus (P Av ), and available potassium (K Av ) on Cambosols (Entisols) ( n = 179) and Anthrosols (Inceptisols) ( n = 95) in Zhangjiagang County, China from 1980 to 2004. Nutrient input was monitored from 1983 to 2004. Annual N fertilizer rates were significantly different during three periods (1983–1989, 1989–1999, 1999–2004), where annual rates increased significantly after 1989 and then decreased after 1999. Annual P fertilizer rates were significantly different during two periods (1983–1993, 1993–2004) where annual rates increased after 1993. No change was found in K fertilizer rates. Soil pH marginally increased by 0.14 units in Cambosols, but significantly decreased by 1.02 units in Anthrosols. OM, CEC, and TN increased in both soil orders an average of 2.15 g kg −1 , 1.6 cmol kg −1 , and 0.21 g kg −1 , respectively. TP decreased in Anthrosols by 70 mg kg −1 , P Av increased in Cambosols by 4.83 mg kg −1 , and K Av decreased in Cambosols by 15 mg kg −1 . Fertilizer input rates are causing nutrient imbalances, contributing to acidification in Anthrosols, and decreasing C/N ratios. Nutrient loading of N and deficiency of K is also a potential problem in the area. Efforts should be made to readjust soil nutrient inputs to reach an optimal, sustainable level.

Selenium (Se) deficiency and excess in agricultural ecosystems are related to many human health problems through the food chain and depend on the spatial variability and bioavailability of Se in soils. This paper examines the spatial variability of Se in soils as affected by geologic and pedogenic processes and its effects on rice grains, groundwater, and human health using Rugao County, Jiangsu Province, an agricultural area in Yangtze River Delta Region, which has a high level of nonagenarians, as a case study. The results showed that total soil Se (T-Se) concentration in the study area (average 0.13 ± 0.02 mg kg-1, n = 203) was close to the Se Clark value, the Se mean concentration in earth crust, and had narrow spatial variation as a result of consistent geological processes. As a fraction of the potential bio-available Se in ecosystems, soil water soluble Se (WS-Se) (average 2.27 ± 1.09 μg kg-1, n = 203) had wide spatial variation. The higher concentrations of WS-Se were spatially distributed on loamy and highly weathered soils in the east and north of the county. Spatial heterogeneity of WS-Se was primarily due to changes in soil physicochemical properties caused by pedogenic processes related to cultivation. Average Se concentration in the rice grains and groundwater were 97 ± 69 μg kg-1 (n = 93) and 0.19 ± 0.21 μg L-1 (n = 95), respectively. Similar spatial variability and correlation between WS-Se and rice Se, groundwater Se, and longevity ratio (an index of nonagenarians per 100,000 inhabitants), were found, indicating that the soluble fractions of Se in soils play an important role in biogeochemical cycling in the ecosystem and might be an important indicator of Se deficiency or excess in soils. Thorough small-scale surveys of element availability in the soil should be emphasized where geologic settings are simple but pedogenic processes are complex due to intensive human activities. So WS-Se in soils was advised as a better indicator for Se environmental effect than T-Se, especially when dealing with simple geologic settings and complex pedogenic processes on a small scale.

One of the most important functions of soils is to regulate rainwater and mitigate flooding and associated damages; this function can be estimated by the rainwater regulation ratio (η), i.e., percent of regulated rainwater. Fifteen experimental plots were set up on the hills in Yingtan of Jiangxi Province, southern China. These plots were under three land use patterns, cultivated cropland, noncultivated land, and orchard interplanted with cash crops. With aid of an artificial rainfall simulator and Guelph method, rainfall, runoff, soil infiltration, and so on were measured in situ. Results showed that the orchard interplanted with cash crops was more effective in regulating rainwater than the other two land use patterns. When the maximum infiltration intensity was three times higher than the observed mean,η was higher than 70% for all plots. η was related to land use, slope gradient, and soil properties such as soil infiltration, organic carbon, bulk density, and texture. There is still more room to improve capacity of rainwater drainage (underground percolation) than that of rainwater storage in soils. Therefore, enhancing soil permeability is vital to improve the rainwater regulation efficiency in soils.

Vegetation stress diagnoses based on plant sampling and physiochemical analysis using traditional methods are commonly time-consuming, destructive and expensive. The measurement of field spectral reflectance is one basis of airborne or spaceborne remote sensing monitoring. In this study, paddy plants were grown in the barrels evenly filled with 10.0 kg soil that was mixed respectively with 0, 2.5 × 207.2 and 5.0 × 207.2 mg Pb per 1,000 g soil. Rice canopy spectra were gathered by mobile hyper-spectral radiometer (ASD FieldSpec Pro FR, USA). Meanwhile, canopy leaves in the field-of-view (FOV) of spectroradiometer were collected and then prepared in the laboratory, (1) for chlorophyll measurement by Model 721 spectrophotometer, and (2) for Pb determination by atomic absorption spectrophotometer (SpectraAA-220FS). Canopy spectral reflectance in the region of visible-to-near-infrared light (VNIR) increased, because ascended Pb concentration caused the decrease of canopy chlorophyll content. In the agro-ecosystem, however, heavy metal contamination is presented typically as mixture and their interactions strongly affect actually occurring effects. Normalized spectral absorption depth (D n), and shifting distance (DS) of red edge position (REPs) revealed the differences in Pb concentration for canopy leaves, especially at the early tillering stage. Due to insufficient biomass of rice plants, the 30th day was not reliable enough for the selection of crucial growth stages. Some special sensitive bands might be omitted at the same time because of limited sample sets. Our initial experiments are still too few in the amounts of both metals and plants neither to build accurate prediction models nor to discuss the transformation from ground to air/spaceborne remote sensing. However, we are pleased to communicate that ground remote sensing measurements would provide reliable information for the estimation of Pb concentration in rice plants at the early tillering stage when proper features (such as DS and D n) of reflectance spectra are applied. Hyper-spectral remote sensing is a potential and promising technology for monitoring environmental stresses on agricultural vegetation. Further ground remote sensing experiments are necessary to evaluate the possibility of hyper-spectral reflectance spectroscopy in monitoring different kinds of metals’ stress on various plants.

Soil organic carbon (SOC) is an important soil component of farming systems and plays a key role in terrestrial ecosystems. However, there is a large variation in SOC estimates at both regional and global scales. The widely used soil type method is usually projected using a planimetric approach, and hence SOC estimates vary notably compared to those generated from more rigorous 3-D surfaces describing rugged terrain. In order to improve the accuracy of SOC storage estimates for regions with complex landforms, this paper examined the causes of variability in estimated SOC storage and SOC density in the upper 1 m soil depth based on 798 soil profiles from Southwest China. The study area is a region with rugged terrain, including the Guangxi Zhuang Autonomous Region, and the Guizhou and Yunnan Provinces. Three methods, the soil profile statistics (SPS), the GIS-based planar soil type (GST-2D), and the GIS-based three-dimensional soil type (GST-3D), were applied to estimate SOC storage. Results demonstrate that the GST-3D, which used soil surface area data, was more accurate than the other two methods. The SOC storages estimated by the SPS and the GST-2D methods were lower than the GST-3D mainly due to the underestimation of soil acreage. Of the four geomorphologic units represented in the study area, the complex landforms with slopes greater than 18.2° covered more than 30%. There is a relatively big difference (> 6%) between planimetric projection area and surface area in this region, making the effect of landform on the estimate of SOC an important factor to be considered. However, such thresholds (30% and 18.2°) as terrain descriptor boundaries need to be further verified in other mountainous regions.

Topsoil samples (0–20 cm) (n = 237) were collected from Rugao County, China. Geostatistical variogram analysis, sequential Gaussian simulation (SGS), and principal component (PC) analysis were applied to assess spatial variability of soil nutrients, identify the possible areas of nutrient deficiency, and explore spatial scale of variability of soil nutrients in the county. High variability of soil nutrient such as soil organic matter (SOM), total nitrogen (TN), available P, K, Fe, Mn, Cu, Zn, and B concentrations were observed. Soil nutrient properties displayed significant differences in their spatial structures, with available Cu having strong spatial dependence, SOM and available P having weak spatial dependence, and other nutrient properties having moderate spatial dependence. The soil nutrient deficiency, defined here as measured nutrient concentrations which do not meet the advisory threshold values specific to the county for dominant crops, namely rice, wheat, and rape seeds, was observed in available K and Zn, and the deficient areas covered 38 and 11%, respectively. The first three PCs of the nine soil nutrient properties explained 62.40% of the total variance. TN and SOM with higher loadings on PC1 are closely related to soil texture derived from different parent materials. The PC2 combined intermediate response variables such as available Zn and P that are likely to be controlled by land use and soil pH. Available B has the highest loading on PC3 and its variability of concentrations may be primarily ascribed to localized anthropogenic influence. The amelioration of soil physical properties (i.e. soil texture) and soil pH may improve the availability of soil nutrients and the sustainability of the agricultural system of Rugao County.

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.

The presence and condition of roadways control the utilization of natural resources, which are associated with direct and indirect impacts on soil erosion in undeveloped countries. This paper addresses the relationship between soil erosion and distance to roadways in Xingguo County, an undeveloped area in Jiangxi Province of South China, for four time periods, 1958, 1975, 1982, and 2000. Soil erosion maps for each time period were interpreted using remote sensing and GIS technology for buffer zones four kilometers wide, subdivided into eight strips, each 0.5 kilometers wide, which were located alongside various types of road classes, namely trunk, town, village, and unpaved. The distribution patterns of various types of erosion were identified by GIS overlay of buffer strips and soil erosion maps. Results demonstrate that soil erosion cases found in buffer zones along both sides of trunk and town roads are the most severe, and areas with severe erosion decrease as distance from the strip to the road increases. However, moderate and slight erosion cases only have a minor relationship to the strip to road distance. There are more severe erosion cases than moderate and light erosion cases alongside village and unpaved roads, but the total area is not distinctly different from moderate and slight erosion cases, and severe erosion cases tend to decrease with an increase in the strip to road distance. Also, areas with severe erosion differentiated by time periods in the strips alongside roadways of all classes, except trunk roads, rank from highest to lowest as follows: 1975, 1958, 1982, and 2000. Notably, severe erosion areas in 1975, 1958 and 1982 are all quite extensive. Soil erosion alongside roadways of various classes is impacted jointly by historical policy, distance to roadways, and landscape. In undeveloped countries and areas, much more attention should be paid to the impacts of road construction, specifically soil erosion associated with road edge construction, and relevant measures for forest resource conservation should be formulated before initiating road construction projects.

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.

A total of 540 topsoil samples (0–15 cm), 188 subsoil samples (20–40 cm), and four individual soil profiles were collected in this study for mapping the Cu- and Pb-contaminated areas in soils of Zhangjiagang city, an industrialized city in the Yangtze River Delta region of China. Robust geostatistical methods were applied for identifying possible spatial outliers of Cu and Pb data, and then a sequential Gaussian simulation was employed for delineating the potential areas where Cu or Pb concentration was affected by diffuse pollution. The results showed that the spatial outliers of Cu and Pb were strongly associated with various types of factories. The anthropogenic input of Cu to soils at local hotspots was closely related to emissions of printing and dyeing, metallurgical, and chemical factories, whereas a lead oxide factory and a chemical factory resulted in a considerable increase of Pb in the topsoil of the study area. Approximately 30% of the total land area of the study was at potential risk from the Cu or Pb diffuse pollution resulting from rapid industrialization of the area over the past 20 years.

In industry-oriented pen-urban areas, the heavy metal accumulation in soils caused by industrialization has become a potential threat. The top soil samples from 27 paddy fields and 75 vegetable fields were collected from a typical industry-based pen-urban area of about 8km^2 in Wuxi, China, to study the accumulation and distribution of As, Hg, Cu, Zn, Pb, Cr, and Cd in comparison with heavy metal contents in soils near developed industrial sites (Guangzhou, China; Wallsend Burn of Tyneside, UK; and Osnabruck, Germany). Kriging interpolation was used to determine the metals' spatial distribution. The results showed that most soils, compared to the background values, contained elevated contents of As, Hg, Cu, Zn, and Pb with some having elevated contents of Cd and Cr. Except for less than 10% of the soil samples of Cu, Zn and Cd contents, these heavy metal contents were lower than the soil threshold levels of the Grade Ⅱ criteria for the Chinese environmental quality standard. Probably, because of the scattered distribution and diversity of industries in the study area, spatial distributions of these heavy metals from Kriging interpolation indicated little similarity. Nevertheless, when compared with other areas in the Taihu Lake region, mean contents of Cu, Zn, Pb, and Cd were relatively high in the Wuxi pen-urban area. Additionally, compared to soils in agricultural areas around Guangzhou, Osnabruck, or Wallsend Burn, contents of most heavy metals in soils from this area were lower.

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 China's 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.

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.

Detailed surveys of surface water in two contrasting peri-urban areas in the Yangtze River Delta region of China were conducted to determine the distribution of heavy metals, nitrogen (N) and phosphorus (P) as well as the speciation of N and P. A factory-based (FB) area was compared with a vegetable-based (VB) area during the dry season. The concentrations of heavy metals in the surface water in the FB area were higher than those in the VB area, suggesting modest contamination of surface water with Zn, Cu, Cr and Pb but not Cd, from discharge of factory effluent in the FB area but not the VB area. Although total N (TN) and total P (TP) levels in the surface water were high in both areas, the surface water in the VB area had significantly higher levels of nitrate N (NO3–N), organic N (ON) and TN than those in the FB area. In both areas, the levels of water-soluble P (WP), organic P (OP) and TP were high in the river water that received municipal wastewater. The distribution of N and P species throughout the surface water system indicated that the NO3–N and ON mainly came from vegetable fields, while ammonium N (NH4–N), WP and OP were mainly from municipal wastewater. Treatment of municipal wastewater prior to discharge to reduce N and P by purification is recommended together with research and extension to develop more efficient use of N and P fertilizer by vegetable farmers.

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.

Digital soil maps of different scales have been compiled in China, but exactly how map scale affects the estimation of regional SOC (soil organic carbon) stocks remains unclear. To test the effect, median, mean, and a pedological professional knowledge based method (PKB) were used to link soil profiles to soil maps at five scales ranging from 1:500000 to 1:10000000 for the Hebei Province. Excluding the 1:4000000 soil map, SOC stocks decreased as the map scale decreased. The estimated SOC stocks obtained using the mean were always higher than those using the median or PKB method. The changes in estimation due to different map scales and linking methods affected the process of assigning SOCD (soil organic carbon density) values to digital soil surveys. The differences in SOCD values resulted from the change in the total nonurban land area of each soil type as a result of the different methods and scales of maps used in the regional SOC stock estimation process.

The relationships between soil erodibility factor (K) and soil saturated permeability (K(subscript fs) for cultivated Acrisols derived from Quaternary red clay and Cambisols derived from red sandstone were studied and quantified using a rainfall simulator and Guelph permeameter in a hilly area of subtropical China. A negative correlation existed between K(subscript fs) of the topsoil (0-5 cm) and K. The empirical expression K≈a×K(superscript -b subscript fs)+c, where a, b and c are the structural coefficients related to soil properties, such as soil type, soil parent material, organic matter, pH and mechanical composition, best described the relationship between soil saturated permeability and soil erodibility.

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

There is growing concern about food safety and environmental contamination in the rapidly expanding peri-urban interface in Asia. Here, we present an integrated study of farming practices and the quality of water, sediments, soils and agricultural products in small-scale vegetable farming systems in two contrasting peri-urban areas with different levels of industrial development in the Yangtze River Delta Region of China. Application of large amounts of cow manure to vegetables in Nanjing, a vegetable-based peri-urban area, had caused an accumulation of N, P, Cu, Zn and available Cd in soil. This resulted in high Cd in some vegetables and high concentrations of N and P in surface water. Because of a shorter history of vegetable production in Wuxi, an industrialized peri-urban area, the accumulation of N and P in soils was less, but high available Cd due to low soil pH associated with application of large amounts of inorganic fertilizers had resulted in high Cd in some vegetables. Heavy metal pollution in the Wuxi area mainly came from atmospheric deposition and discharge of effluent from factories and was higher than in the less industrialized area in Nanjing. Development and dissemination of strategies for more efficient use of fertilizers in vegetable farming could benefit both farm profitability and the environment and should be coupled with treatment of municipal waste before discharge and control of factory emissions. Bringing about change in farming, municipal and industrial practice will require good relationships amongst a number of stakeholders. The uncertain status of immigrant vegetable farmers in Wuxi hampers their interaction with agricultural service providers and local governance structures and effective channels for communication need to be established.

Soil classification systems are not consistent among countries or organizations thereby hindering the communication and organizational functions they are intended to promote. The development of translations between systems will be critical for overcoming the gap in understanding that has resulted from the lack of a single internationally accepted classification system. This paper describes the application of a process that resulted in the translation of the Genetic Soil Classification of China (GSCC) to Soil Taxonomy (ST). A brief history of soil classification in China is also provided to familiarize readers with GSCC and its origins. Genetic Soil Classification of China is the attribute base for the recently assembled digital form of the 1:1 000 000 soil map of The People's Republic of China. The translation between GSCC and ST was based on profile, chemical, and physical descriptions of 2540 soil series. First, the 2540 soil series were classified to their equivalent soil order, suborder, great group, and subgroup according to ST and GSCC subgroup descriptors. Order names for both classification systems were then linked to corresponding map units in the 1:1 000 000 digital soil map of China using a geographic information system (GIS). Differences in classification criteria and in the number of orders of the two systems (there are more GSCC orders than ST orders) meant that each GSCC order could possibly be assigned to more than one ST order. To resolve the differences, the percent correspondence in area between orders was determined and used as the criterion for assigning GSCC orders to ST orders. Some percentages of correspondence were low so additional processing was used to improve the assignment process. The GSCC suborders were then matched with ST orders. When the area for each order was summarized, the percentage of correspondence increased except for two subgroups in the Ferrasols order.

The spatial patterns of soil organic carbon (SOC) are closely related to the global climate change. In quantifying the spatial patterns of SOC density, the concept of uncertainty of the SOC density values at unsampled locations is particularly important because such uncertainty can be propagated into the subsequent global climate change modelling and has fundamental impacts on the ultimate results of the model. A total of 361 SOC density data of topsoil (0-20 cm) in Hebei province and sequential indicator simulation (SIS) were applied to perform a conditional stochastic simulation in this study to quantitatively assess the uncertainty of mapping SOC density. The results showed that a great variation exists in the SOC density data. The conditional variance of 500 realizations generated by SIS was larger in mountainous areas of the study area where the SOC density fluctuated the most, and the uncertainty was smaller on the plain area where SOC density was consistently small. Realizations generated by SIS can represent the possible spatial patterns of SOC density without smoothing effect. A set of realizations can be used to explore all possible spatial patterns of SOC density and provide a visual and quantitative measure of the spatial uncertainty of mapping SOC density. With a given threshold of SOC density, SIS can quantitatively assess both local uncertainty and spatial uncertainty of SOC density that is greater the threshold.

Summary Southern China has abundant natural resources and is a major region of agricultural production. However, soil erosion is increasingly threatening the agricultural productivity of this region. Increases in soil erosion are caused by improper land use practices with soils of high rainfall erosivity. Much of the area prone to accelerated erosion was previously forested and subsequently logged four times since the 1920s. This paper discusses the effects of biological control practices on soil erosion according to erosion types, soil properties, and terrain.

[1] Fourteen grid data sets of different cell resolutions were generated, from 0.5 × 0.5 km to 64 × 64 km, to estimate CH4 and N2O emissions from paddy soils in the Tai Lake region of China using the Denitrification-Decomposition (DNDC) model. The grids were derived from a polygon-based data set (1:50,000 digital soil map/database), which was the most detailed soil database for the region. Comparison of simulated CH4 and N2O concentrations from input of the 14 grid data sets with the original polygon data demonstrated (1) no distinct variability (relative errors 10%) in the results when grid data sets with cell size of >8 km were applied as input. A grid data set with a cell size of 8 km was found to be optimal based on accuracy and computational efficiency of DNDC simulations. The results can be used as a guideline for optimizing field sampling strategies for locations where there is a lack of or insufficient soil data, whereby soil data can be collected through sampling in cell centers of designed grid frames.

Subtropical broad-leaved forests in southeastern China support a high diversity of woody plants. Using a comparative study design with 30×30 m plots (n1/427) from five successional stages (1 m in height in each plot and counted all woody recruits (bank of all seedlings ≤1 m in height) in each central 10×10 m quadrant of each plot. In addition, we measured a number of environmental variables (elevation, slope, aspect, soil moisture, pH, C, N, and C/N ratio) and biotic structural variables (height and cover of layers). Adult species richness varied from 25 to 69 species per plot, and in total 148 woody species from 46 families were recorded. There was a clear successional gradient in species composition as revealed by nonmetric multidimensional scaling (NMDS), but only a poor differentiation of different successional stages with respect to particular species. Adult richness per 100 individuals (rarefaction method) increased with successional stage. None of the measured abiotic variables were significantly correlated with adult species richness. We found no evidence that rare species were responsible for the increasing adult species richness, as richness of rare species among both adults and recruits was independent of the successional stage. Furthermore, the similarity between established adults and recruits did not increase with successional stage. There was a constant number of recruit species and also of exclusive recruit species, i.e., those that had not been present as adult individuals, across all successional stages, suggesting a continuous random immigration over time. © 2011 by the Ecological Society of America.

To quantify the spatial distribution of SOC in Hebei Province five models were compared: multiple linear regression (MLR), universal kriging (UK), regression-kriging (RK), artificial neural network combined with kriging (ANN-kriging), and regression tree (RT). The modelling was supported by 359 SOC density (total SOC by volume, SOCD) data points, as well as relief parameters derived from a 100m × 100m resolution DEM, and NDVI calculated from NOAA AVHRR data to map SOCD (to a depth of 1m) spatial distributions. Only 19.5% of the total SOCD variation can be explained by MLR method, the UK method resulted in a wider range of SOCD compared with MLR method. The UK method and RK method explain 53 and 65% of the total variation, respectively, and the local variation of lower SOCD in the southeast of the province was detected. The ANN-kriging and RT mapping both explained 67% of the total variation. Compared to ANN-kriging, the RT method has lower root mean square prediction error. The sequential indicator simulation (SIS) was applied for assessing topsoil SOCD (0–20 cm) uncertainty at unsampled locations. The conditional variance of 1,000 realizations generated by SIS was greater in mountainous areas where SOCD fluctuated the most, and the uncertainty was less on the plain area where SOCD was consistently low. The RT model is of best performance for mapping the spatial distribution of SOCD, and the SIS technique can quantitatively assess the local and spatial uncertainty of SOCD being greater than a given threshold.

This study was carried out in the Xujiawan watershed in Sichuan Province, China. The area is characterized by easy weathering of bedrock (sedimentary sandstone and shale) and vulnerability to erosion due to coarse soil texture and weak soil structure. The objective of this study was to understand the dynamics of nitrogen (N) and phosphorus (P) losses during typical storm events. The results showed that runoff generation was sudden and ephemeral, giving rise to flash floods with sharp, narrow hydrographs and short time lags in this type of agricultural ecosystems. The time lag effect of runoff formation depended on soil conditions before storm events. Suspended solids (SS) concentration peaks occurred at the beginning of the storm flow and decreased as rainfall progressed. Meanwhile, SS losses increased at the beginning of runoff flow, then decreased due to flow volume change. Concentrations of NO 3 − -N were four times higher than NH 4 + -N in runoff. NO 3 − -N concentrations first decreased as runoff volume increased until reaching relatively low concentrations, then increased again as runoff volume decreased. Both NH 4 + -N and dissolved phosphorus (DP) in runoff remained at low concentrations with a small magnitude of variation. Suspended particulate nitrogen (SN) was the dominant N form. Losses of NO 3 − -N were higher than NH 4 + -N in the dissolved nitrogen (DN). Suspended particulate nitrogen losses were several times higher than DN in the early period of runoff formation, but the ratio of SN/DN decreased gradually as rainfall progressed, and by the end of the storm event the rate was lower than 1, indicating DN took the main form after the early physical flush. In the early period of storm events, suspended particulate phosphorus (SP)/DP was above 70 and decreased as rainfall progressed, but remained higher than 1, which showed that SP was the main form of P loss. The transport of N, and particularly P, was intimately linked to sediment in the runoff, indicating an obvious soil erosion-associated nutrient transport, especially in relation to P loss.

Accurate characterization of heavy-metal contaminated areas and quantification of the uncer- tainties inherent in spatial prediction are crucial for risk assessment, soil remediation, and effective management recommendations. Topsoil samples (0-15 cm) (n=547) were collected from the Zhangjiagang suburbs of China. The sequential indicator co-simulation (SIcS) method was applied for incorporating the soft data derived from soil organic matter (SOM) to simulate Hg concentrations, map Hg contaminated areas, and evaluate the associated uncer- tainties. High variability of Hg concentrations was observed in the study area. Total Hg concentrations varied from 0.004 to 1.510 mg kg −1 and the coefficient of variation (CV) accounts for 70%. Distribution patterns of Hg were identified as higher Hg concen- trations occurred mainly at the southern part of the study area and relatively lower concentrations were found in north. The Hg contaminated areas, identified using the Chinese Environmental Quality Standard for Soils critical values through SIcS, were limited and distributed in the south where the SOM concentration is high, soil pH is low, and paddy soils are the dominant soil types. The spatial correlations between Hg and SOM can be preserved by co-simulation and the realizations generated by SIcS represent the possible spatial patterns of Hg concentrations without a smooth- ing effect. Once the Hg concentration critical limit is given, SIcS can be used to map Hg contaminated areas and quantitatively assess the uncertainties inherent in the spatial prediction by setting a given critical probability and calculating the joint probability of the obtained areas.

[1] Organic carbon storage in agricultural soils plays a key role in the terrestrial ecosystem carbon cycle. Paddy soils support important croplands in many parts of the world, especially in Asia. A thorough understanding of organic carbon storage in Chinese paddy soils would be helpful to both greenhouse gases emission and carbon sequestration studies. This paper examines soil organic carbon density (SOCD) and storage (SOCS) of paddy soils in China using the newly compiled 1:1,000,000 digital soil map of China as well as data from 1490 paddy soil profiles. Results show that paddy soils in China cover about 45.7 M ha, nearly 1.5 times more than the results of other studies. In China, the mean SOCD of paddy soils at a depth of 0–100 cm is 111.4 t C ha−1, with a SOCS of 5.1 Pg. These results are 66–75% higher than studies from other scientists. However, the mean SOCD of paddy soils from 0 to 20 cm is 37.6 t C ha−1, with a SOCS of 1.7 Pg, which is 89% higher than studies from other scientists.

In this paper, the references between Genetic Soil Classification of China (GSCC) and the Chinese Soil Taxonomy (CST) for GSCC-Semi-Luvisols were conducted, and their quantitative and spatial distribution characteristics within CST were studied, based on the 1 : 1 M Soil Database of China, which consists of 1 : 1 M digital soil map, soils profiles attribution database and soil reference system of China. Being a reference system for converting soil names in GSCC into those in CST, ST and WRB, respectively, Chinese Soil Reference System was a computerized retrieving system jointly developed by the experienced scientists of pedology and computer science. The comparison fields and laboratory investigation data of their soil profiles with diagnostic horizons and characteristics related in the target soil classification systems, and 2,540 typical soil species names corresponding in CST, ST and WRB systems were determined, respectively, which were selected from Soil Attributes Database because of their complete sets of attribute data. Finally, the system and reference database were established. "GIS linkage based soil type" method linked the records in the Soil Reference Database to the Soil Spatial Database. In this method, all records of soil profiles in Soil Reference Database as well as their soil reference name in other classification systems were allocated one by one onto corresponding soil type polygons in Soil Spatial Database on the GIS platform, according to the principles of soil type identity and similarity, parent material identity and likeness, and the location of soil profiles relative to linked target polygons. Area statistcs of all soils were conducted based on the polygons. The results showed that GSCC-Semi-Luvisols was a type of GSCC soil with a total area of 427,843.1 km2,which could be sorted to 4 CST Orders, i. e., Luvisols (51.3%), Cambosols (35.2%), Isohumosols (10.7%) and Anthrosols (2.8%), and further into CST 22 Groups and 38 Subgroups. All dark grey forest soil, superficial gleyed black soil, and leached dry red soil of GSCC subgroups could be sorted to Calcaric Hapli-Gelic Cambosols, Pachic Argi-Udic Cambosols and Typic Ferri-Ustic Luvisols of CST subgroups, respectively, and all grey cinnamon-like soil, calcareous grey cinnamonic soil and dry cinnamon soil could be sorted to Typic Ustic Cambosols. Making the reference was so complicated that there was no one to one reference relationship among other soils. The analysis of the area ratios and standard deviations of a certain GSCC soil classified by CST showed that the lower the unit for reference, the easier the reference would be. The results of this study were of high reference value to proper reference GSCC and CST, and to the application and development of CST.

Locust plague is a kind of the world-wide biological calamity to agriculture. In China's history, more than 90% of locust plagues were caused by the oriental migratory locust, Locusta migratoria manilensis (Meyen). At the present time, it is difficult for monitoring and forecasting systems in this country to provide real time information of locust plague outbreak in large area. In order to adopt timely measures for prevention and control of locust outbreak, it is necessary to apply advanced remote sensing technology for monitoring and forecasting locust outbreak This paper introduces a case study on monitoring oriental migratory locust plague with remote sensing technology in 3 pilot sites, namely, Huangzao, Yangguangzhuang, and Tengnan, which were the 3 major locust damaged areas in Huanghua City, Hebei Province, China during the period of large scale oriental migratory locust breakout in 2002. In this study, locust damage intensity, areas with various damage intensities and their distribution in pilot sites are determined by means of comparison between Landsat ETM+ image of locust damaged vegetation on 31st May, 2002 and TM image of healthy vegetation before damage on 23rd May, 2002. Then, information of various locust distribution density in pilot sites is extracted by establishing the Locust Density Index (LDI).

Based on 1:1,000,000 soil database, and employing the methods of spatial expression, this paper estimated the soil organic carbon storage (SOCS) and density (SOCD) of China. The database consists of 1:1,000,000 digital soil map, soil profile attribution database, and soil reference system. The digital soil map contained 926 soil mapping units, 690 soil families, and 94 000 or more polygons, while the soil profile attribution database collected 7292 soil profiles, including 81 attribution fields. The SOCDs of soil profiles were calculated and linked to the soil polygons in the digital soil map by the method of "GIS linkage based on soil type", resulting in a vector map of 1:1,000,000 China SOCD. The SOCS of the country or of a soil could be estimated by summing up the SOCS of all polygons or the polygons of a soil, and their SOCD were the SOCS of them derived by their areas. The estimated SOCS and SOCD of the country was 89. 14 Pg (1 Pg = 10(15) g) and 9.60 kg m(-2), respectively, covered all the soils with a total area of 928.10 x 10(4) km2, which might be considered closest to the real value.

8.29 � 10 15 g, representing 5.9–8.7% of the total global N storage. The total N storage in China is on average or slightly above the average of its share in the global N storage, even though low nitrogen content soils cover a large area in China. N density varies substantially with soil types and regions. Peat soils in the southeast of Tibet, southwest China, show the highest averaged N density with a value of 7314.9 g/m 3 among all soil types. This is more than 30 times of the lowest N density of brown desert soils in the western desert and arid region. The highest N storages among all the soil types are the felty soil in southeast of Tibet, dark-brown earths in northeast China, and red earths in southeast China with values of 921.1, 611.4, and 569.6 Tg, respectively. N density also varies with land cover types in China. Wetlands in southwest China exhibit the highest N density at 6775.9 g/m 3 and deserts in northwest China have the least at 447.5 g/m 3 . Our analysis also indicates that land cover types are poor predictors of N content. Further research is needed to examine how transformation from organic agriculture to increased use of fertilizers and pesticides has influenced N storage in China.

about 8.3 � 10 2 g/m 3 and 5.4 g/m 3 , respectively. The total national soil P pool in the surface half meter is 3.5 Pg (10 15 g). The available P density ranges from 0.7 g/m 3 in the Lithosols to 16.7 g/m 3 in the Irrigated Silting Soils. The total P density ranges from 1.2 � 10 2 g/m 3 in the Lithosols to 19 � 10 2 g/m 3 in the Frigid Desert Soils. The ratio of available P to total P density ranges from 0.6 � 10 � 3 in Aeolian Soils to 21.6 � 10 � 3 in Coastal Solonchaks. The available P content and its vertical distribution show a complex pattern among soil orders of different development stages, possibly indicating the important role of biota’s control over soil available P content. There are large variations of P content in different climatic regions. The tropical and subtropical region has the lowest available P density (4.8 g/m 3 ) and the second lowest total P density (8.2 � 10 2 g/m 3 ) among all climatic regions. The large variation in the soil P content suggests that further study is needed to investigate climatic and land-use controls over the soil P content.

Soil classification forms the basis for the exchange and extension of research findings in soil science and for the modernization of management of soil resources. This paper systematically reviews the compatibility of the genetic soil classification of China (GSCC) and soil taxonomy (ST). This includes a study of the evolution and consummation of the GSCC and assessment of the databases and methods of the study. Using the “Soil Species of China (six volumes)” and some provincial soil species as the basic material, the authors gathered information from 2540 soil species. Based on the key described in ST, the 2540 soil species were taxonomically classified into corresponding soil orders, suborders, great groups and subgroups and then matched with corresponding map units in the 1: 1000000 digital soil map of China. Using the high-level classification units of the two soil classification systems, and the attributes of each soil species, the sizes of distribution areas were mapped. The soil distribution results were analyzed and compared statistically. The reference compatibility between the great groups used in GSCC system and the soil orders of the ST is discussed. It is believed that 20 great groups display maximum referencibility>95% and 15 great groups depict maximum referencibility in the range of 70%–95%, which can be cited as reference benchmarks. The remaining 25 great groups are less compatible (with maximum referencibility