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.     

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     

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.     

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.     

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.     

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.     

Construction of a chemical ranking system of soil pollution substances for screening of priority soil contaminants in Korea

The Korean government recently proposed expanding the number of soil-quality standards to 30 by 2015. The objectives of our study were to construct a reasonable protocol for screening priority soil contaminants for inclusion in the planned soil quality standard expansion. The chemical ranking system of soil pollution substances (CROSS) was first developed to serve as an analytical tool in chemical scoring and ranking of possible soil pollution substances. CROSS incorporates important parameters commonly used in several previous chemical ranking and scoring systems and the new soil pollution parameters. CROSS uses soil-related parameters in its algorithm, including information related to the soil environment, such as soil ecotoxicological data, the soil toxic release inventory (TRI), and soil partitioning coefficients. Soil TRI and monitoring data were incorporated as local specific parameters. In addition, CROSS scores the transportability of chemicals in soil because soil contamination may result in groundwater contamination. Dermal toxicity was used in CROSS only to consider contact with soil. CROSS uses a certainty score to incorporate data uncertainty. CROSS scores the importance of each candidate substance and assigns rankings on the basis of total scores. Cadmium was the most highly ranked. Generally, metals were ranked higher than other substances. Pentachlorophenol, phenol, dieldrin, and methyl tert-butyl ether were ranked the highest among chlorinated compounds, aromatic compounds, pesticides, and others, respectively. The priority substance list generated from CROSS will be used in selecting substances for possible inclusion in the Korean soil quality standard expansion; it will also provide important information for designing a soil-environment management scheme.     

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.     

Geostatistical analysis of Palmerton soil survey data

This paper presents a literature review focused on predictive technique audits, one of the types of audit considered to have the greatest potential role in improving environmental impact assessment practice. The literature review is limited to US literature with the exception of a few UK audits, one undertaken by Tomlinson at the University of Aberdeen. The authors are, however, aware that literature from other countries exists on this subject, for example from Canada and South Africa.In the review, predictive technique audits performed for or by the US Bureau of Land Management, the Electric Power Research Institute, the US Nuclear Regulatory Commission, the US Corps of Engineers, together with the Wisconsin Power Plant Impact Study are described. In addition, articles describing the auditing of models designed to predict environmental change are reviewed, before details of auditing activity in the UK are presented.     

Assessing soil quality indicator under different land use and soil erosion using multivariate statistical techniques

Soil degradation associated with soil erosion and land use is a critical problem in Iran and there is little or insufficient scientific information in assessing soil quality indicator. In this study, factor analysis (FA) and discriminant analysis (DA) were used to identify the most sensitive indicators of soil quality for evaluating land use and soil erosion within the Hiv catchment in Iran and subsequently compare soil quality assessment using expert opinion based on soil surface factors (SSF) form of Bureau of Land Management (BLM) method. Therefore, 19 soil physical, chemical, and biochemical properties were measured from 56 different sampling sites covering three land use/soil erosion categories (rangeland/surface erosion, orchard/surface erosion, and rangeland/stream bank erosion). FA identified four factors that explained for 82 % of the variation in soil properties. Three factors showed significant differences among the three land use/soil erosion categories. The results indicated that based upon backward-mode DA, dehydrogenase, silt, and manganese allowed more than 80 % of the samples to be correctly assigned to their land use and erosional status. Canonical scores of discriminant functions were significantly correlated to the six soil surface indices derived of BLM method. Stepwise linear regression revealed that soil surface indices: soil movement, surface litter, pedestalling, and sum of SSF were also positively related to the dehydrogenase and silt. This suggests that dehydrogenase and silt are most sensitive to land use and soil erosion.     

The use of parent material/slope positions as soil mapping units in irrigation soil surveys of Northern Nigeria

The problems of different mapping units which hitherto formed the basis for irrigation soil surveys of the savanna landscapes in Nigeria are discussed. Using data from a semi-detailed soil survey, the possibility of establishing the major variations in soil properties which are relevant to irrigation by using a combination of parent material and slope position as mapping units are examined. In the mapping units considered, thirteen topsoil and eleven subsoil properties are significantly different between mapping units and have smaller variances within than between the mapping units. The variations of these topsoil and subsoil properties are also adequately accounted for by using parent material/slope position as a basis for mapping, suggesting that units based on parent material/slope position are of high utility for establishing the irrigation potentials of areas at the feasibility level of survey.     

Effects of anthropogenic nitrogen deposition on soil nitrogen mineralization and immobilization in grassland soil under semiarid climatic conditions

Earlier studies by the authors on English soils under grassland strongly supported their hypothesis that soil/plant systems have naturally evolved to conserve nitrogen (N) by having a close match between the dynamics of mineral-N production in soils and the dynamics of plant N requirements. Thus, maximum mineral-N production in soils occurred in spring when plant N requirements were greatest and were very low in mid to late summer. Low temperature and a high C:N ratio of senescing material helped to conserve N in winter, but mobile N was associated with pollution inputs. We test the hypothesis that under the much more arid conditions of Pakistan, soil/plant systems naturally have evolved to conserve mineral-N, especially over the very dry and cooler months between October and February. When soils from a grassland site were incubated at ambient temperatures after removal of plant roots and exclusion of atmospheric N inputs, there was consistent evidence of immobilization of nitrate and immobilization and possibly volatilization of ammonia/ammonium. In the wetter months of July and August, the soil at 0–10 cm depth showed no evidence of significant ammonium-N production in July and only small ammonium production at 10–20 cm depth in August, but was associated with significant nitrate-N immobilization in August. Nitrate leaching only appeared likely towards the end of the rainy season in September. The results strongly suggest that, under grass, the retention of atmospheric N inputs over the long dry periods is regulating the pools of available N in the soils, rather than the N produced by mineralization of soil organic matter.     

TiO2 and ZnO nanoparticles negatively affect wheat growth and soil enzyme activities in agricultural soil

The properties of nanoparticles and their increased use have raised concerns about their possible harmful effects within the environment. Most studies on their effects have been in aqueous systems. Here we investigated the effect of TiO(2) and ZnO nanoparticles on wheat growth and soil enzyme activities under field conditions. Both of the nanoparticles reduced the biomass of wheat. The TiO(2) nanoparticles were retained in the soil for long periods and primarily adhered to cell walls of wheat. The ZnO nanoparticles dissolved in the soil, thereby enhancing the uptake of toxic Zn by wheat. The nanoparticles also induced significant changes in soil enzyme activities, which are bioindicators of soil quality and health. Soil protease, catalase, and peroxidase activities were inhibited in the presence of the nanoparticles; urease activity was unaffected. The nanoparticles themselves or their dissolved ions were clearly toxic for the soil ecosystem.     

Effect of humic deposit (leonardite) on degradation of semi-volatile and heavy hydrocarbons and soil quality in crude-oil-contaminated soil

In order to investigate the bioremedial potential of humic deposit (leonardite), the effects of the treatments of leonardite and a commercial bioaugmentation agent on the degradation of a variety of petroleum hydrocarbons (C13–C31) and soil enzyme activities (urease acid-alkaline phosphatase and dehydrogenase) were tested within a soil incubation experiment lasting 120 days. Experimentally crude-oil-contaminated soil (2.5%) was regulated to a C:N:P ratio (100:15:1; Oilcon), amended with 5% of leonardite and regulated to the same C:N:P ratio (Oilcon-L) or mixed with a commercial bioaugmentation product (Oilcon-B), respectively. In the short period of incubation (60 days), Oilcon and Oilcon-B treatments showed higher hydrocarbon degradations, whereas Oilcon-L showed higher hydrocarbon degradation over Oilcon and Oilcon-B treatments in the long-term (120 days). Applying contaminated soil with leonardite increased urease (LSD, 4.978, *P?<?0.05) and dehydrogenase (LSD, 0.660, *P?<?0.05) activities. However, acid and alkaline phosphatase activities showed no certain inclination between different treatments. Dehydrogenase seemed to be more related to hydrocarbon degradation process. Overall results showed that leonardite enhanced biodegradation of petroleum hydrocarbons and also stimulated soil ecological quality measured as soil enzyme activities.     

Non-target effect of organic insecticides: effect of two plant extracts on soil microbial biomass and enzymatic activities in soil

Efficacious botanical derivatives can provide an alternative to synthetic pesticides for organic farming systems. However, there is lack of information regarding the side effects of organic pesticides on key soil ecological processes. In this study, we investigated the effects of aqueous extracts from Urginea maritima and Euphorbia myrsinites exhibiting translaminar and systemic activity against pests on microbial biomass and enzymatic activities in soil. Two grams of plant material was extracted with 100 ml of water and then diluted 1:100, 2:100, and 4:100 with distilled water. Diluted plant extracts were applied around hypocotyl of tomato by soil drench. The effect of both plant extracts on microbial biomass C, amount of total N and organic C, and enzymatic activity in soil was significant. After the last application, the highest microbial biomass C was determined in the lowest U. maritima concentration (U 1:100). Soils treated with the highest concentration of U. maritima (U 4:100) had always lower SMBC content than control soil. All concentrations of E. myrsinites decreased microbial biomass C by 18% to 27% compared to the control. Total nitrogen and organic carbon decreased in soils without (control) and with treated U. maritima extract from first application to last application. Phosphatase, urease, and β-glucosidase activities were monitored in plant extract-treated soils. Except U. maritima 1:100 treatments of second and fourth applications, the other treatments of plant extracts negatively affected enzymatic activity in soil. U. maritima and E. myrsinites plant extracts exhibited different effects on soil microbial biomass and activity, probably because of their different chemical contents.     

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.     

Metabolic degradation of imidacloprid in paddy field soil

The metabolic degradation and persistence of imidacloprid in paddy field soil were investigated following two applications of imidacloprid at 20 and 80 g a.i. ha^?1 at an interval of 10 days. The soil samples were collected at various time intervals. The limit of quantification for the analysis of imidacloprid and its metabolites was obtained at the concentration of 0.01 mg kg^?1. The initial deposits of total imidacloprid were found to be 0.44 and 1.61 mg kg^?1 following second applications. These residues could not be detected after 60 and 90 days following second applications of imidacloprid at lower and higher dosages, respectively. In soil, urea metabolite was found to be the maximum, followed by olefine, nitrosimine, 6-chloronicotinic acid, 5-hydroxy and nitroguanidine. The half-life values (t _1/2) of imidacloprid were worked out to be 12.04 and 11.14 days, respectively, when applied at lower and higher doses, respectively.     

Conversion of grazing land into Grevillea robusta plantation and exclosure: impacts on soil nutrients and soil organic carbon

Different studies have shown that the effect of land use conversion on soil nutrients and soil organic carbon (SOC) is variable, which indicates that more investigations that focus on different specific geographical locations and land use types are required. The objectives of this study were (1) to evaluate the effect of grazing land (GL) conversion into Grevillea robusta plantation and exclosure (EX) on soil nutrients and soil organic carbon (SOC) and (2) to examine the impact of soil organic matter (SOM) on soil nutrients. To achieve these objectives, soil samples were taken from a soil depth of 20 cm (n?=?4) in each of the studied land areas. Each soil sample was analysed in a soil laboratory following a standard procedure. Analysis of variance (ANOVA) and Pearson’s correlation coefficient were used for the data analysis. The result indicated that conversion of GL into EX improved the soil electrical conductivity (EC), exchangeable K, cation exchange capacity (CEC), total N and available P (p?<?0.05), while the exchangeable Mg, SOC, available K and SOM were decreased (p?<?0.05). Conversion of GL into G. robusta improved the soil EC, exchangeable (K, Ca, Mg), CEC, SOC, total N, available K and SOM (p?<?0.05). There was a significant relationship between SOM and available P, total N, SOC and EC. There were no significant relationships between SOM and pH, available K and CEC. Finally, the results indicate that both land uses, established in acidic Nitosols, have variable impacts on soil chemical properties and that G. robusta plantation improved most of the soil nutrients and SOC much better than the EX land use.     

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.