Assessing the soil quality of alpine grasslands in the Qinghai-Tibetan Plateau using a modified soil quality index

Soil degradation has caused various problems on the planet. Human disturbance and land use changes always negatively affect soil quality. In this study, we used a modified soil quality index (SQI) to assess soil quality under differing degrees of human disturbance and land use. The alpine grasslands were studied at different levels of degradation [i.e., severely degraded grassland, heavily degraded grassland, moderately degraded grassland, and non-degraded grassland (NDG)] in a case study conducted in Qinghai-Tibetan Plateau (QTP) to test the feasibility of using the SQI. Fifteen chemical, physical, and biological soil parameters were measured in each type of grassland. Significant variations in SQI were found across the different types of grasslands according to severity of human disturbance and changes in land use. Urease, the ratio of microbial biomass nitrogen to total nitrogen, proteinase, and soil organic carbon were found to be the most important indicators for assessing soil quality. NDG had a higher SQI than the other three types of grasslands. It was concluded that SQI is effective for assessing the soil quality of alpine grasslands in the QTP. The intensity of human disturbance had a negative effect on soil quality in the QTP.     

Soil fauna and soil microflora as possible indicators of soil pollution

Research on biological indicators of soil pollution is hampered by soil variability and temporal and spatial fluctuations of numbers of soil animals. These characters on the other hand promote a high biological diversity in the soil. A high diversity combined with persistent soil pollutants increases the chance to select good indicators. However research on these topics is still limited. Examples of specific indicators are the changed arthropod species patterns due to pesticide influence and the changed soil enzyme activity under the influence of specific heavy metals. Another approach is to look for organisms that give a general indication of soil pollution. In this respect the earthworm species Allolobophora caliginosa proved to be sensitive for different types of manure especially pig manure with copper, for sewage sludge, for municipal waste compost and for fly ash. A third way of indication is by organisms accumulating pollutants. For some heavy metals (Cd, Zn), earthworms are very efficient accumulators. More research is needed especially on the specific relation between biological responses and abiotic soil characteristics.     

Geochemistry in the modern soil survey program

Elemental analysis has played an important role in the characterization of soils since inception of the soil survey in the US. Recent efforts in analysis of trace and major elements (geochemistry) have provided necessary data to soil survey users in a variety of areas. The first part of this paper provides a brief overview of elemental sources, forms, mobility, and bioavailability; critical aspects important to users of soil survey geochemical data for appropriate use and interpretations. Examples are provided based on data gathered as part of the US soil survey program. The second part addresses the organization of sample collection in soil survey and how soil surveys are ideally suited as a sampling strategy for soil geochemical studies. Geochemistry is functional in characterization of soil types, determining soil processes, ecological evaluation, or issues related to soil quality and health, such as evaluating suitability of soils for urban or agricultural land use. Applications of geochemistry are on-going across the US and are documented herein. This analytical direction of soil survey complements historic efforts of the National Cooperative Soil Survey Program and addresses the increasing need of soil survey users for data that assists in understanding the influence of human activities on soil properties.     

日本土壤环境质量标准与污染现状

介绍了日本土壤污染的环境质量标准以及日本市区、农用地土壤和有毒有害化学物质的污染现状     

Spatial variability of soil salinity in coastal saline soil at different scales in the Yellow River Delta,China

The objectives of this study were to explore the spatial variability of soil salinity in coastal saline soil at macro, meso and micro scales in the Yellow River delta, China. Soil electrical conductivities (ECs) were measured at 0–15, 15–30, 30–45 and 45–60 cm soil depths at 49 sampling sites during November 9 to 11, 2013. Soil salinity was converted from soil ECs based on laboratory analyses. Our results indicated that at the macro scale, soil salinity was high with strong variability in each soil layer, and the content increased and the variability weakened with increasing soil depth. From east to west in the region, the farther away from the sea, the lower the soil salinity was. The degrees of soil salinization in three deeper soil layers are 1.14, 1.24 and 1.40 times higher than that in the surface soil. At the meso scale, the sequence of soil salinity in different topographies, soil texture and vegetation decreased, respectively, as follows: depression >flatland >hillock >batture; sandy loam >light loam >medium loam >heavy loam >clay; bare land >suaeda salsa >reed >cogongrass >cotton >paddy >winter wheat. At the micro scale, soil salinity changed with elevation in natural micro-topography and with anthropogenic activities in cultivated land. As the study area narrowed down to different scales, the spatial variability of soil salinity weakened gradually in cultivated land and salt wasteland except the bare land.     

A field study of the influence of land management and soil properties on runoff and soil loss in central Spain

Since the 1950s afforestation of degraded land has been the principal means of combatting erosion in a seasonally arid area of central Spain. In the 1970s tree planting of steep hillsides and gully sides was preceded by bench terracing. Experimental sites have been established to monitor runoff and soil losses under mature Pinus forest, 12-year-old Pinus forest, and Cistus matorral. The experiment is being conducted at three scales: large gully or small watershed (c. 3.5 ha), runoff erosion plot (10–21.5 m²), and rainfall simulation plot (1 m²). Monitoring began in October 1992. Discharge was recorded continuously, while sediment loss and soil moisture content were measured on a storm basis. The paper presents summary data on runoff and soil erosion for the three scales and comments on relationships between land management, site characteristics, and these losses. We stress the crucial role of vegetation and its interrelationship with soil properties such as structure and aggregate stability. Matorral was effective in combatting water and soil loss, but we question the practice of afforesting seasonally arid, steeply sided areas that have highly erodible soils.     

Parameter values to model the soil ingestion pathway

Soil ingestion is an important exposure pathway for contaminants that are not otherwise very mobile in the environment. Health of both humans and animals can be affected. This paper summarizes the literature and recommends models and probabilistic parameter values for risk assessment applications. Models of the pathway require estimates of the amounts of soil ingested, the concentration of contaminants relative to the original soil, and the bioavailability in the gut of the contaminants ingested with soil. Using a lead-contaminated sandbox as an example, the modelling recommendations suggest that a child typically may consume 50 mg d^–1 of the sandbox soil, the soil ingested will have a tenfold higher lead concentration than the original soil, and the lead will be as bioavailable as if ingested as inorganic lead in water.The Canadian Government right to retain a non-exclusive, royalty free licence in and to any copyright is acknowledged.     

The effectiveness of digital soil mapping to predict soil properties over low-relief areas

This study investigates the ability of different digital soil mapping (DSM) approaches to predict some of physical and chemical topsoil properties in the Shahrekord plain of Chaharmahal-Va-Bakhtiari province, Iran. According to a semi-detailed soil survey, 120 soil samples were collected from 0 to 30 cm depth with approximate distance of 750 m. Particle size distribution, coarse fragments (CFs), electrical conductivity (EC), pH, organic carbon (OC), and calcium carbonate equivalent (CCE) were determined. Four machine learning techniques, namely, artificial neural networks (ANNs), boosted regression tree (BRT), generalized linear model (GLM), and multiple linear regression (MLR), were used to identify the relationship between soil properties and auxiliary information (terrain attributes, remote sensing indices, geology map, existing soil map, and geomorphology map). Root-mean-square error (RMSE) and mean error (ME) were considered to determine the performance of the models. Among the studied models, GLM showed the highest performance to predict pH, EC, clay, silt, sand, and CCE, whereas the best model is not necessarily able to make accurate estimation. According to RMSE%, DSM has a good efficiency to predict soil properties with low and moderate variabilities. Terrain attributes were the main predictors among different studied auxiliary information. The accuracy of the estimations with more observations is recommended to give a better understanding about the performance of DSM approach over low-relief areas.     

红外光度法测定土壤中的石油类

以CCl4为萃取剂,以Na2SO4(无水硫酸钠)或一水合硫酸镁MgSO4·H2O为干燥剂,用红外光度法(GB/T16488-1996)来测定土壤中的石油类。     

Basal soil monitoring scheme in the protected areas of the Czech Republic

The purpose and aims of environmental monitoring are discussed, particularly in the context of soils as part of the environment, and examples of such schemes currently in operation within Europe are outlined. These are compared with the Basal Soil Monitoring Scheme (BSMS) in the Czech Republic which is the product of collaboration between the Ministries of Agriculture and the Environment and five agricultural, forestry and environmental research institutes. The BSMS consists of over 250 monitoring plots covering three distinct land uses: agriculture, forestry and environmentally protected areas. Each land use class has its own subsystem of monitoring plots which together comprise the whole system. The main principles and methodologies employed in the environmentally protected areas of the Czech Republic are described in some detail.     

火焰原子吸收法测定土壤中的铅

建立了一种以 HNO3-HCl-HCl O4 -HF对土壤样品进行消化 ,火焰原子吸收测定铅的方法。该法用于实际样品的测定时 ,相对标准偏差小于 2 .3 % ,加标回收率为 98%～ 1 0 2 %。     

The determination of the extractability of selected elements from agricultural soil

Concentrations of Ag, Al, Ba, Cd, Co, Cr, Cu, Fe, K, Mn, Na, Ni, Pb, Sr, and Zn—isolated by sequential extraction steps from apple orchard soil—were analyzed by inductively coupled plasma-atomic emission spectroscopy and compared to the total amount of metal in soil determined by XRF. The extractable amount of each metal was calculated by the extraction yields of the four steps. The LODs of the different elements in all extracts ware below 3 μg/L except for Ba (steps 1 and 2), Cu (step 1), Fe (all steps), K (steps 1–3), Mn (step 2), Na (steps 1–3), Ni (step 1), Pb (steps 1 and 4), and Zn (steps 1 and 2). The highest LOD (>10 μg/L) was found for Fe, K, and Na (step 1). The recovery of all metals after four sequential extraction steps was 90–112%. The repeatability (<1.1%), the intermediate precision (<5.3%), the day-to-day reproducibility (<6.2%), and the overall uncertainty of measurement (approximately 4–8.5%) for all analyzed metals supports the choice of the method used.     

Mutagenicity assessment of contaminated soil in the vicinity of industrial area

In the industrial area of Chinhat, Lucknow (India) wastewater coming from pesticide manufacturing and other industries is used to irrigate the agricultural crops. This practice has been polluting the soil and pollutants might reach the food chain. Gas chromatographic analysis revealed the presence of certain organochlorine pesticides in soil samples. Samples were extracted using different solvents, i.e., hexane, acetonitrile, methanol, chloroform, and acetone (all were HPLC-grade, SRL, India). Soil extracts were assayed for mutagenicity using Ames Salmonella/mammalian microsome test. Mutagenicity was observed in the test samples and TA98 was the most responsive strain for all the soil extracts (irrigated with wastewater) in terms of mutagenic index in the presence (+S9) and absence (−S9) of metabolic activation. In terms of slope (m) of linear dose–response curve for the most responsive strain TA98 exhibited highest sensitivity against the soil extracts in the presence and absence of S9 fraction. Hexane-extracted soil sample (wastewater) exhibited maximum mutagenicity in terms of net revertants per gram of soil in the presence and absence of S9 mix as compared to the other soil extracts. Groundwater-irrigated soil extracts displayed low level of mutagenicity as compared to wastewater-irrigated soil. The soil is accumulating a large number of pollutants due to wastewater irrigation and this practice of accumulation has an adverse impact on soil health.     

Monitoring soil productive potential

Desertification involves the loss of soil productive potential, but a means of assessing and monitoring the progress of desertification on the soil has been elusive. Soil is so varied and complex that methods of assessing condition are too slow, tedious, and expensive for routine use. Moreover, differences in soil type can be confused with soil condition. This paper presents a structured method of assessing soil condition. This method is based on recognizing and classifying soil surface features and examining soil properties that reflect the status of the processes of erosion, infiltration, and nutrient cycling. Published in the form of a user manual, the method has the following three stages: (1) defining the geomorphic setting of the site, (2) recognizing patch/interpatch associations and the mode of erosion at the landscape scale, and (3) assessing soil surface condition ratings in quadrats sited within the landscape pattern patches. Stage 3 is achieved by observing each of 11 features in the field and classifying their status according to detailed fieldnotes and photographs. The method applies to a wide range of soil types and biogeographical regimes and has proven to be repeatable among observers and quickly transferred to new observers.     

Effect of elevated CO2 on degradation of azoxystrobin and soil microbial activity in rice soil

An experiment was conducted in open-top chambers (OTC) to study the effect of elevated CO₂ (580?±?20 μmol mol^?1) on azoxystrobin degradation and soil microbial activities. Results indicated that elevated CO₂ did not have any significant effect on the persistence of azoxystrobin in rice-planted soil. The half-life values for the azoxystrobin in rice soils were 20.3 days in control (rice grown at ambient CO₂ outdoors), 19.3 days in rice grown under ambient CO₂ atmosphere in OTC, and 17.5 days in rice grown under elevated CO₂ atmosphere in OTC. Azoxystrobin acid was recovered as the only metabolite of azoxystrobin, but it did not accumulate in the soil/water and was further metabolized. Elevated CO₂ enhanced soil microbial biomass (MBC) and alkaline phosphatase activity of soil. Compared with rice grown at ambient CO₂ (both outdoors and in OTC), the soil MBC at elevated CO₂ increased by twofold. Elevated CO₂ did not affect dehydrogenase, fluorescein diacetate, and acid phosphatase activity. Azoxystrobin application to soils, both ambient and elevated CO₂, inhibited alkaline phosphates activity, while no effect was observed on other enzymes. Slight increase (1.8–2 °C) in temperature inside OTC did not affect microbial parameters, as similar activities were recorded in rice grown outdoors and in OTC at ambient CO₂. Higher MBC in soil at elevated CO₂ could be attributed to increased carbon availability in the rhizosphere via plant metabolism and root secretion; however, it did not significantly increase azoxystrobin degradation, suggesting that pesticide degradation was not the result of soil MBC alone. Study suggested that increased CO₂ levels following global warming might not adversely affect azoxystrobin degradation. However, global warming is a continuous and cumulative process, therefore, long-term studies are necessary to get more realistic assessment of global warming on fate of pesticide.     

Estimation of soil specific surface area using some mechanical properties of soil by artificial neural networks

Soil specific surface area (SSA) is an important property of soil. Depending on the measurement techniques, determination of the SSA is costly and time consuming. Hence, a limited number of studies have been conducted to predict the SSA from the soil variables. In this study, the soil samples were taken from the literature. Fractal parameters (FP) were calculated by the model of Bird et al. (European Journal of Soil Science 51, 55–63, 2000) used as the input variables to predict the SSA. Some studies have been carried out on the prediction capability of the different parameters using the artificial neural networks (ANNs). The ANNs were further used and 20 models were developed to investigate the value of input variables to predict the SSA. The results showed that the PTF13 (RMSE?=?0.13) and PTF18 (RMSE?=?0.13) with the input variables of particle-size distribution and Atterberg limits revealed better performance than the other PTFs (in the training step). It is because of the fact that free swelling index (FSI) and Atterberg limits were closely correlated to the soil clay mineralogy as one of the important factors controlling the SSA. In general, this results demonstrated that the PTF9 with the variables of sand, clay, plastic limit (PL), liquid limit (LL), and FSI showed the best (RMSE?=?0.37) results in the estimation of the SSA. In conclusion, there was not a strong correlation between the soil mechanical properties and SSA but also ANNs were a suitable method to predict the SSA from the soil variables.     

Comparison of soil solution sampling techniques to assess metal fluxes from contaminated soil to groundwater

The unsaturated zone plays a major role in elemental fluxes in terrestrial ecosystems. A representative chemical analysis of soil pore water is required for the interpretation of soil chemical phenomena and particularly to assess Trace Elements (TEs) mobility. This requires an optimal sampling system to avoid modification of the extracted soil water chemistry and allow for an accurate estimation of solute fluxes. In this paper, the chemical composition of soil solutions sampled by Rhizon® samplers connected to a standard syringe was compared to two other types of suction probes (Rhizon®?+?vacuum tube and Rhizon®?+?diverted flow system). We investigated the effects of different vacuum application procedures on concentrations of spiked elements (Cr, As, Zn) mixed as powder into the first 20 cm of 100-cm columns and non-spiked elements (Ca, Na, Mg) concentrations in two types of columns (SiO₂ sand and a mixture of kaolinite?+?SiO₂ sand substrates). Rhizon® was installed at different depths. The metals concentrations showed that (i) in sand, peak concentrations cannot be correctly sampled, thus the flux cannot be estimated, and the errors can easily reach a factor 2; (ii) in sand?+?clay columns, peak concentrations were larger, indicating that they could be sampled but, due to sorption on clay, it was not possible to compare fluxes at different depths. The different samplers tested were not able to reflect the elemental flux to groundwater and, although the Rhizon®?+?syringe device was more accurate, the best solution remains to be the use of a lysimeter, whose bottom is kept continuously at a suction close to the one existing in the soil.     

Pre-incubation in soil improves the nitrogen fertiliser value of hair waste

Global generation of human hair waste and its disposal at landfills could contribute to the leaching of nitrates into ground water. High concentrations of nitrogen (N) and other elements suggest that the waste could be a source of plant nutrients and differences in ethnic hair types could affect nutrient release and fertiliser value. The objective of this study was to determine the effects of hair type, as an N source, and pre-incubation time on dry-matter yield, nutrient uptake by spinach (Spinacia oleracea L.) and residual soil nutrients. Salons in Pietermaritzburg provided bulk African and Caucasian hair waste, without distinguishing age, sex, health status or livelihood of the individuals. The hair waste was analysed for elemental composition. A pot experiment was set up under glasshouse conditions. The hair waste was incorporated (400 kg N ha^?1) into a loamy oxisol and pre-incubated for 0, 28, 56 and 84 days before planting spinach. Potassium (K) and phosphorus (P) were corrected to the same level for all treatments. Spinach seedlings were then cultivated for 6 weeks. Shoot dry-matter and the uptake of all nutrients, except P, were increased by the pre-incubation of hair. African hair pre-incubated for 28 days resulted in greater dry-matter, N, K, Mn and S uptake than Caucasian hair. Increasing pre-incubation resulted in a decline in the residual soil pH and exchangeable K. The findings suggested that pre-incubation improves the N fertiliser value of hair and that African hair has greater value than Caucasian hair when pre-incubated for a short period.