黄土高原(土娄)覆盖层与黏化层的土壤水文效应

黄土高原(土娄)土在《中国土壤系统分类(修订方案)》中属土垫旱耕人为土类的相应亚类,其土壤水分状况是诊断表层所属人为表层类堆垫表层(覆盖层)和诊断表下层(黏化层)的重要诊断特征。以土壤持水性能、蒸发性能和水分移动性能为切入点,对(土娄)土覆盖层和黏化层的土壤水文效应进行研究论证,以期对土垫旱耕人为土类及其亚类的诊断层与诊断特征获取更深层的认识。

Retention behavior of hydrophobic organic chemicals as a function of temperature in soil leaching column chromatography

To study the transport mechanism of hydrophobic organic chemicals (HOCs) and the energy change in soil/solvent system, a soil leaching column chromatographic (SLCC) experiment at an environmental temperature range of 20-40 degreesC was carried out, which utilized a reference soil (SP 14696) packed column and a methanol-water (1:4 by volume ratio) eluent. The transport process quickens with the increase of column temperature. The ratio of retention factors at 30 and 40 degreesC (k'(30)/k'(40)) ranged from 1.08 to 1.36. The lower enthalpy change of the solute transfer in SLCC (from eluent to soil) than in conventional reversed-phase liquid chromatography (e.g., from eluent to C-18) is consistent with the hypothesis that HOCs were dominantly and physically partitioned between solvent and soil. The results were also verified by the linear solvation energy relationships analysis. The chief factor controlling the retention was found to be the solute solvophobic partition, and the second important factor was the solute hydrogen-bond basicity, while the least important factors were the solute polarizability-dipolarity and hydrogen-bond acidity. With the increase of temperature, the contributions of the solute solvophobic partition and hydrogen-bond basicity gradually decrease, and the latter decreases faster than the former. (C) 2002 Elsevier Science Ltd. All rights reserved.

Effects of inoculated Microcoleus vaginatus on the structure and function of biological soil crusts of desert

Microcoleus vaginatus Gom., the dominant species in biological soil crusts (BSCs) in desert regions, plays a significant role in maintaining the BSC structure and function. The BSC quality is commonly assessed by the chlorophyll a content, thickness, and compressive strength. Here, we have studied the effect of different proportions of M. vaginatus, collected from the Gurbantunggut Desert in northwestern China, on the BSC structure and function under laboratory conditions. We found that when M. vaginatus was absent in the BSC, the BSC coverage, quantified by the percentage of BSC area to total land surface area, was low with a chlorophyll a content of 4.77 x 10(-2) mg g(-1) dry soil, a thickness of 0.86 mm, and a compressive strength of 12.21 Pa. By increasing the percentage of M. vaginatus in the BSC, the BSC coverage, chlorophyll a content, crust thickness, and compressive strength all significantly increased (P < 0.01). The maximum chlorophyll a content (13.12 mg g(-1)dry soil), the highest crust thickness, and the compressive strength (1.48 mm and 36.60 Pa, respectively) occurred when the percentage of inoculated M. vaginatus reached 80% with a complex network of filaments under scanning electron microscope. The BSC quality indicated by the above variables, however, declined when the BSC was composed of pure M. vaginatus (monoculture). In addition, we found that secretion of filaments and polymer, which stick sands together in the BSC, increased remarkably with the increase of the dominant species until the percentage of M. vaginatus reached 80%. Our results suggest that not only the dominant species but also the accompanying taxa are critical for maintaining the structure and functions of the BSC and thus the stability of the BSC ecosystems.

Estimation of soil organic partition coefficients: from retention factors measured by soil column chromatography with water as eluent

The retention factors (k) of 104 hydrophobic organic chemicals (HOCs) were measured in soil column chromatography (SCC) over columns filled with three naturally occurring reference soils and eluted with Milli-Q water. A novel method for the estimation of soil organic partition coefficient (K-oc) was developed based on correlations with k in soil/water systems. Strong log K-oc versus log k correlations (r>0.96) were found. The estimated K-oc values were in accordance with the literature values with a maximum deviation of less than 0.4 log units. All estimated K-oc values from three soils were consistent with each other. The SCC approach is promising for fast screening of a large number of chemicals in their environmental applications. (C) 2002 Elsevier Science B.V. All rights reserved.

Influence of methanol on retention of hydrophobic organic chemicals in soil leaching column chromatography

The influence of methanol in methanol-water mixed eluents on the capacity factor (P), an important parameter which could depict leaching potential of hydrophobic organic chemicals (HOCs) in soil leaching column chromatography (SLCC), was investigated. Two reference soils, GSE 17201 obtained from Bayer Landwirtschaftszentrum, Monheim, Germany and SP 14696 from LUFA, Spencer, Germany, were used as packing materials in soil columns, and isocratic elution with methanol-water mixtures at different volume fractions of methanol (phi) were tested. Shortterm exposure of the column (packed with the GSE 17201 soil) to the eluents increased solute retention by a certain (23% log-unit) degree evaluated through a correlation with the retention on the same soil column but unpreconditioned by methanol-containing eluents. Long-term exposure of soil columns to the eluents did not influence the solute retention. A log-linear equation, log k' = log k'(w) - Sphi, could well and generally describe the retention of HOCs in SLCC. For the compounds of homologous series, logk'(w), had good linear relationship with S, indicating the hydrophobic partition mechanism existing in the retention process. (C) 2002 Elsevier Science Ltd. All rights reserved.

Linear solvation energy relationships regarding sorption and retention properties of hydrophobic organic compounds in soil leaching column chromatography

The capacity factors of a series of hydrophobic organic compounds (HOCs) were measured in soil leaching column chromatography (SLCC) on a soil column, and in reversed-phase liquid chromatography on a C-18 column with different volumetric fractions (phi) of methanol in methanol-water mixtures. A general equation of linear solvation energy relationships, log(XYZ) = XYZ(0) + mV(1)/100 + spi* + bbeta(m) + aalpha(m), was applied to analyze capacity factors (k'), soil organic partition coefficients (K-oc) and octanol-water partition coefficients (P). The analyses exhibited high accuracy. The chief solute factors that control log K-oc, log P, and log k' (on soil and on C-18) are the solute size (V-1/100) and hydrogen-bond basicity (beta(m)). Less important solute factors are the dipolarity/polarizability (pi*) and hydrogen-bond acidity (alpha(m)). Log k' on soil and log K-oc have similar signs in four fitting coefficients (m, s, b and a) and similar ratios (m:s:b:a), while log k' on C-18 and log P have similar signs in coefficients (m, s, b and a) and similar ratios (m:s:b:a). Consequently, log k' values on C-18 have good correlations with log P (r > 0.97), while log k' values on soil have good correlations with log K-oc (r > 0.98). Two K-oc estimation methods were developed, one through solute solvatochromic parameters, and the other through correlations with k' on soil. For HOCs, a linear relationship between logarithmic capacity factor and methanol composition in methanol-water mixtures could also be derived in SLCC. (C) 2002 Elsevier Science Ltd. All rights reserved.

Prediction of soil adsorption coefficients from retention parameters on three reversed-phase liquid chromatographic columns

Reversed-phase high-performance liquid chromatographic (RP-HPLC) retention parameters, which are determined by the intermolecular interactions in retention process, can be considered as the chemical molecular descriptors in linear free energy relationships (LFERs). On the basis of the characterization and comparison of octadecyl-bonded silica gel (ODS), cyano-bonded silica gel (CN), and phenyl-bonded silica gel (Ph) columns with linear solvation energy relationships (LSERs), a new multiple linear regression model using RP-HPLC retention parameters on ODS and CN columns as variables for estimation of soil adsorption coefficients was developed. It was tested on a set of reference substances from various chemical classes. The results showed that the multicolumn method was more promising than a single-column method was for the estimation of soil adsorption coefficients. The accuracy of the suggested model is identical with that of LSERs.

Estimation of Correlation Distance of Soil Properties by Geostatistics

Random field theory has been used to model the spatial average soil properties, whereas the most widely used, geostatistics, on which also based a common basis (covariance function) has been successfully used to model and estimate natural resource since 1960s. Therefore, geostistics should in principle be an efficient way to model soil spatial variability Based on this, the paper presents an alternative approach to estimate the scale of fluctuation or correlation distance of a soil stratum by geostatistics. The procedure includes four steps calculating experimental variogram from measured data, selecting a suited theoretical variogram model, fitting the theoretical one to the experimental variogram, taking the parameters within the theoretical model obtained from optimization into a simple and finite correlation distance 6 relationship to the range a. The paper also gives eight typical expressions between a and b. Finally, a practical example was presented for showing the methodology.

Extracellular carbohydrate polymers from five desert soil algae with different cohesion in the stabilization of fine sand grain

Extracellular polymeric substances (EPS) from four filamentous cyanobacteria Microcoleus vaginatus, Scytonema javanicum, Phormidium tenue and Nostoc sp. and a coccoid single-cell green alga Desmococcus olivaceus that had been separated from desert algal crusts of Tegger desert of China, were investigated for their chemical composition, structure,and physical properties. The EPS contained 7.5-50.3% protein (in polymers ranging from 14 to more than 200 kD, SDS-PAGE) and 16.2-46.5% carbohydrate (110-460 kD, GFC). 6-12 kinds of monosaccharides, including 2-O-methyl rhamnose, 2-O-methyl glucose, and N-acetyl glucosamine were found. The main carbohydrate chains from M. vaginatus and S. javanicum consisted mainly of equal proportion of Man, Gal and Glc, that from P. tenue consisted mainly of arabinose, glucose and rhamnose. Arabinose was present in pyranose form, mainly alpha-L 1 --> 3 linked, with branches on C4 of almost half of the units. Glucose was responsible for the terminal units, in addition of having some units as beta1 --> 3 and some as beta1 --> 4 linked. Rhamnose was mainly 1 --> 3 linked with branches on C2 on half of the units. The carbohydrate polymer from D. olivaceus was composed mainly of beta1 --> 4 linked xylose, galactose and glucose. The galactose part was present both in beta-pyranose and -furanose forms. Arabinose in alpha-L-furanose form was mainly present as 1 --> 2 and 1 --> 2, 5 linked units, rhamnose only as alpha 1 --> 3 and xylose as beta 1 --> 4. The backbone of the polysaccharide from Nostoc sp. was composed of beta-1 --> 4 linked xylose, galactose and glucose. Most of the glucose was branched on position C6, terminal glucose and 2-O-methyl glucose units are also present. The relationship between structure, physical properties and potential biological function is discussed. (C) 2003 Elsevier Ltd. All rights reserved.

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.

Retention modeling and simultaneous optimization of pH value and gradient steepness in RP-HPLC using feed-forward neural networks

A novel approach is proposed for the simultaneous optimization of mobile phase pH and gradient steepness in RP-HPLC using artificial neural networks. By presetting the initial and final concentration of the organic solvent, a limited number of experiments with different gradient time and pH value of mobile phase are arranged in the two-dimensional space of mobile phase parameters. The retention behavior of each solute is modeled using an individual artificial neural network. An "early stopping" strategy is adopted to ensure the predicting capability of neural networks. The trained neural networks can be used to predict the retention time of solutes under arbitrary mobile phase conditions in the optimization region. Finally, the optimal separation conditions can be found according to a global resolution function. The effectiveness of this method is validated by optimization of separation conditions for amino acids derivatised by a new fluorescent reagent.

Retention modeling and optimization of pH value and solvent composition in HPLC using back-propagation neural networks and uniform design

A novel method for the optimization of pH value and composition of mobile phase in HPLC using artificial neural networks and uniform design is proposed. As the first step. seven initial experiments were arranged and run according to uniform design. Then the retention behavior of the solutes is modeled using back-propagation neural networks. A trial method is used to ensure the predicting capability of neural networks. Finally, the optimal separation conditions can be found according to a global resolution function. The effectiveness of this method is validated by optimization of separation conditions for both basic and acidic samples.

Soil microbial community analysis using denaturing gradient gel electrophoresis

The most biological diversity on this planet is probably harbored in soils. Understanding the diversity and function of the microbiological component of soil poses great challenges that are being overcome by the application of molecular biological approaches. This review covers one of many approaches being used: separation of polymerase chain reaction (PCR) amplicons using denaturing gradient gel electrophoresis (DGGE). Extraction of nucleic acids directly from soils allows the examination of a community without the limitation posed by cultivation. Polymerase chain reaction provides a means to increase the numbers of a target for its detection on gels. Using the rRNA genes as a target for PCR provides phylogenetic information on populations comprising communities. Fingerprints produced by this method have allowed spatial and temporal comparisons of soil communities within and between locations or among treatments. Numerous samples can be compared because of the rapid high throughput nature of this method. Scientists now have the means to begin addressing complex ecological questions about the spatial, temporal, and nutritional interactions faced by microbes in the soil environment.