Prediction of soil organic carbon partition coefficients by soil column liquid chromatography

To avoid the limitation of the widely used prediction methods of soil organic carbon partition coefficients (K-OC) from hydrophobic parameters, e.g., the n-octanol/water partition coefficients (K-OW) and the reversed phase high performance liquid chromatographic (RP-HPLC) retention factors, the soil column liquid chromatographic (SCLC) method was developed for K-OC prediction. The real soils were used as the packing materials of RP-HPLC columns, and the correlations between the retention factors of organic compounds on soil columns (k(soil)) and K-OC measured by batch equilibrium method were studied. Good correlations were achieved between k(soil) and K-OC for three types of soils with different properties. All the square of the correlation coefficients (R-2) of the linear regression between log k(soi) and log K-OC were higher than 0.89 with standard deviations of less than 0.21. In addition, the prediction of K-OC from K-OW and the RP-HPLC retention factors on cyanopropyl (CN) stationary phase (k(CN)) was comparatively evaluated for the three types of soils. The results show that the prediction of K-OC from k(CN) and K-OW is only applicable to some specific types of soils. The results obtained in the present study proved that the SCLC method is appropriate for the K-OC prediction for different types of soils, however the applicability of using hydrophobic parameters to predict K-OC largely depends on the properties of soil concerned. (C) 2004 Elsevier B.V. All rights reserved.

Natural 13C abundance as a tracer for studies of soil organic matter dynamics

A method for measuring the long- and medium-term turnover of soil organic matter is described. Its principle is based on the variations of 13C natural isotope abundance induced by the repeated cultivations of a plant with a high 13C/12C ratio (C4 photosynthetic pathway) on a soil which has never carried any such plant. The 13C/12C ratio in soil organic matter being about equal to the 13C/12C ratio of plant materials from which it is derived, changing the 13C content of the organic inputs to the soil (by altering vegetation from C3 type into C4 type) is equivalent to a true labelling in situ of the organic matter. Two cases of continuous corn cultivation (Zea mays: δ13C = −12%.) on soils whose initial organic matter average δ13C is −26%. were studied. The quantity of organic carbon originating from corn (that is the quantity which had turned-over since the beginning of continuous cultivation) was estimated using the 13C natural abundance data. After 13 yr, 22% of total organic carbon had turned-over, in the system studied. Particle size fractions coarser than 50μm on the one hand, and finer than 2μm on the other. contained the youngest organic matters. The turnover rate of silt-sized fractions was slower

Methods for physical separation and characterization of soil organic matter fractions

Turnover of soil organic matter (SOM) is coupled to the cycling of nutrients in soil through the activity of soil microorganisms. Biological availability of organic substrate in soil is related to the chemical quality of the organic material and to its degree of physical protection. SOM fractions can provide information on the turnover of organic matter (OM), provided the fractions can be related to functional or structural components in soil. Ultrasonication is commonly used to disrupt the soil structure prior to physical fractionation according to particle size, but may cause redistribution of OM among size fractions. The presence of mineral particles in size fractions can complicate estimations of OM turnover time within the fractions. Densiometric separation allows one to physically separate OM found within a specific size class from the heavier-density mineral particles. Nutrient contents and mineralization potential were determined for discrete size/density OM fractions isolated from within the macroaggregate structure of cultivated grassland soils. Eighteen percent of the total soil C and 25% of the total soil N in no-till soil was associated with fine-silt size particles having a density of 2.07-2.21 g/cm3 isolated from inside macroaggregates (enriched labile fraction or ELF). The amount of C and N sequestered in the ELF fraction decreased as the intensity of tillage increased. The specific rate of mineralization (mug net mineral N/mug total N in the fraction) for macroaggregate-derived ELF was not different for the three tillage treatments but was greater than for intact macroaggregates. The methods described here have improved our ability to quantitatively estimate SOM fractions, which in turn has increased our understanding of SOM dynamics in cultivated grassland systems.

Surface modelling of soil pH

In addition to classical methods, namely kriging, Inverse Distance Weighting (IDW) and splines, which have been frequently used for interpolating the spatial patterns of soil properties, a relatively more accurate surface modelling technique is being developed in recent years, namely high accuracy surface modelling (HASM). It has been used in the numerical tests, DEM construction and the interpolation of climate and ecosystem changes. In this paper, HASM was applied to interpolate soil pH for assessing its feasibility of soil property interpolation in a red soil region of Jiangxi Province, China. Soil pH was measured on 150 samples of topsoil (0-20 cm) for the interpolation and comparing the performance of HASM, kriging. IDW and splines. The mean errors (MEs) of interpolations indicate little bias of interpolation for soil pH by the four techniques. HASM has less mean absolute error (MAE) and root mean square error (RMSE) than kriging, IDW and splines. HASM is still the most accurate one when we use the mean rank and the standard deviation of the ranks to avoid the outlier effects in assessing the prediction performance of the four methods. Therefore, HASM can be considered as an alternative and accurate method for interpolating soil properties. Further researches of HASM are needed to combine HASM with ancillary variables to improve the interpolation performance and develop a user-friendly algorithm that can be implemented in a GIS package. (C) 2009 Elsevier B.V. All rights reserved.

Study on spatial pattern of land-use change in China during 1995-2000

It is more and more acknowledged that land-use/cover dynamic change has become a key subject urgently to be dealt with in the study of global environmental change. Supported by the Landsat TM digital images, spatial patterns and temporal variation of land-use change during 1995 -2000 are studied in the paper. According to the land-use dynamic degree model, supported by the 1km GRID data of land-use change and the comprehensive characters of physical, economic and social features, a dynamic regionalization of land-use change is designed to disclose the spatial pattern of land-use change processes. Generally speaking, in the traditional agricultural zones, e.g., Huang-Huai-Hai Plains, Yangtze River Delta and Sichuan Basin, the built-up and residential areas occupy a great proportion of arable land, and in the interlock area of farming and pasturing of northern China and the oases agricultural zones, the reclamation I of arable land is conspicuously driven by changes of production conditions, economic benefits and climatic conditions. The implementation of "returning arable land into woodland or grassland" policies has won initial success in some areas, but it is too early to say that the trend of deforestation has been effectively reversed across China. In this paper, the division of dynamic regionalization of land-use change is designed, for the sake of revealing the temporal and spatial features of land-use change and laying the foundation for the study of regional scale land-use changes. Moreover, an integrated study, including studies of spatial pattern and temporal process of land-use change, is carried out in this paper, which is an interesting try on the comparative studies of spatial pattern on change process and the change process of spatial pattern of land-use change.

Effects of soil type on leaching and runoff transport of rare earth elements and phosphorous in laboratory experiments

Through leaching experiments and simulated rainfall experiments, characteristics of vertical leaching of exogenous rare earth elements (REEs) and phosphorus (P) and their losses with surface runoff during simulated rainfall in different types of soils (terra nera soil, cinnamon soil, red soil, loess soil, and purple soil) were investigated. Results of the leaching experiments showed that vertical transports of REEs and P were relatively low, with transport depths less than 6 cm. The vertical leaching rates of REEs and P in the different soils followed the order of purple soil > terra nera soil > red soil > cinnamon soil > loess soil. Results of the simulated rainfall experiments (83 mm h(-1)) revealed that more than 92% of REEs and P transported with soil particles in runoff. The loss rates of REEs and P in surface runoff in the different soil types were in the order of loess soil > terra nera soil > cinnamon soil > red soil > purple soil. The total amounts of losses of REEs and P in runoff were significantly correlated.

Spatial distribution of soil heavy metal pollution estimated by different interpolation methods: Accuracy and uncertainty analysis

Mapping the spatial distribution of contaminants in soils is the basis of pollution evaluation and risk control. Interpolation methods are extensively applied in the mapping processes to estimate the heavy metal concentrations at unsampled sites. The performances of interpolation methods (inverse distance weighting, local polynomial, ordinary kriging and radial basis functions) were assessed and compared using the root mean square error for cross validation. The results indicated that all interpolation methods provided a high prediction accuracy of the mean concentration of soil heavy metals. However, the classic method based on percentages of polluted samples, gave a pollution area 23.54-41.92% larger than that estimated by interpolation methods. The difference in contaminated area estimation among the four methods reached 6.14%. According to the interpolation results, the spatial uncertainty of polluted areas was mainly located in three types of region: (a) the local maxima concentration region surrounded by low concentration (clean) sites, (b) the local minima concentration region surrounded with highly polluted samples; and (c) the boundaries of the contaminated areas. (C) 2010 Elsevier Ltd. All rights reserved.

Drivers of soil net nitrogen mineralization in the temperate grasslands in Inner Mongolia, China

Soil net nitrogen mineralization (NNM) of four grasslands across the elevation and precipitation gradients was studied in situ in the upper 0-10 cm soil layer using the resin-core technique in Xilin River basin, Inner Mongolia, China during the growing season of 2006. The primary objectives were to examine variations of NNM among grassland types and the main influencing factors. These grasslands included Stipa baicalensis (SB), Aneulolepidum Chinense (AC), Stipa grandis (SG), and Stipa krylovii (SK) grassland. The results showed that the seasonal variation patterns of NNM were similar among the four grasslands, the rates of NNM and nitrification were highest from June to August, and lowest in September and October during the growing season. The rates of NNM and nitrification were affected significantly by the incubation time, and they were positively correlated with soil organic carbon content, total soil nitrogen (TN) content, soil temperature, and soil water content, but the rates of NNM and nitrification were negatively correlated with available N, and weakly correlated with soil pH and C:N ratio. The sequences of the daily mean rates of NNM and nitrification in the four grasslands during the growing season were AC > SG > SB > SK, and TN content maybe the main affecting factors which can be attributed to the land use type.

Probabilistic modelling of soil moisture dynamics of irrigated cropland in the North China Plain

A probabilistic soil moisture dynamic model is used to estimate the soil moisture probability distribution and plant water stress of irrigated cropland in the North China Plain. Soil moisture and meteorological data during the period of 1998 to 2003 were obtained from an irrigated cropland ecosystem with winter wheat and maize in the North China Plain to test the probabilistic soil moisture dynamic model. Results showed that the model was able to capture the soil moisture dynamics and estimate long-term water balance reasonably well when little soil water deficit existed. The prediction of mean plant water stress during winter wheat and maize growing season quantified the suitability of the wheat-maize rotation to the soil and climate environmental conditions in North China Plain under the impact of irrigation. Under the impact of precipitation fluctuations, there is no significant bimodality of the average soil moisture probability density function.

Effects of soil pH and organic matter on distribution of thorium fractions in soil contaminated by rare-earth industries

The labilities of thorium fractions including mobility and bioavailability vary significantly with soil properties. The effects of soil pH and soil organic matter on the distribution and transfer of thorium fractions defined by a sequential extraction procedure were investigated. Decrease of soil pH could enhance the phytoavailability and the potential availability of thorium in soil. Increase of organic matter reduced the phytoavailability of thorium, but enhanced the potential availability of it.