Complex Soil Systems Research Articles

Survival, growth, detoxifying and antioxidative responses of earthworms (Eisenia fetida) exposed to soils with industrial DDT contamination

The survival, growth, activity of the biotransformation system phase II enzyme glutathione-S-transferase (GST) and the oxidative defense enzyme catalase (CAT) of earthworms exposed to the contaminated soils from a former DDT plant and reference soils were investigated, and compared with the corresponding indicators in simulated soil-earthworm system, unpolluted natural soils with spiked-in DDT series, to identify the toxic effects of DDT on earthworms and their cellular defense system in complex soil system. The results indicated that DDT level in the contaminated soils was significantly higher than that in the reference soils with similar level of other pollutants and soil characters. The mortality, growth inhibition rates, GST and CST activities of earthworms exposed to the contaminated soils were significantly higher than that in reference soils. The contribution of historical DDT in contaminated soils to earthworms was confirmed by the DDT spiked tests. DDT spiked in soils at rates of higher than 200mg·kg−1 was significantly toxic to both the survival and the growth of earthworms. DDT significantly stimulated GST and CAT activity in earthworms after 14days. The CAT and GST activities were also stimulated by DDT exposure at rates of 100mg·kg−1 after chronic exposure (42days). The results provide implications for validating the extrapolation from laboratory simulated soils criteria to contaminated soils and for making site risk assessments.

Rhizoctonia communities in soybean fields and their relation with other microbes and nematode communities

Soybean root rot, caused by Rhizoctonia solani, is one of the most serious soybean diseases in the North Central Region of the United States. There is no report of the relationship between Rhizoctonia root rot and soil physical and chemical properties, or microbial and nematode communities. A commercial soybean field with a long history of Rhizoctonia root rot was examined to explore this relationship. Results demonstrated that high disease incidence in sampled areas was positively correlated with high levels of nitrogen, phosphorus, manganese, populations of soil Rhizoctonia, thermophiles and fungi, root Rhizoctonia colonies, populations of lesion and stunt nematodes, and negatively correlated with high levels of calcium, magnesium, sodium, base saturation, and populations of Pseudomonas based on correlation analysis and canonical correspondence analysis (CCA). Cluster analysis showed that the communities of both Rhizoctonia and bacteria in sampled areas were separated based on healthy and diseased plants using denaturing gradient gel electrophoresis (DGGE); however, there was no clear separation for Fusarium, Pythium and Trichoderma communities in sampled areas based on healthy and diseased plants, indicating these species might not be directly associated with Rhizoctonia root rot. Moreover, the disease suppression seems to be more related to the quantity of soil beneficial microorganisms rather than specific species. In addition, DGGE is a reliable technique to characterize microbial communities and identify fungal and bacterial species in complex soil systems.

Metatranscriptomic census of active protists in soils.

The high numbers and diversity of protists in soil systems have long been presumed, but their true diversity and community composition have remained largely concealed. Traditional cultivation-based methods miss a majority of taxa, whereas molecular barcoding approaches employing PCR introduce significant biases in reported community composition of soil protists. Here, we applied a metatranscriptomic approach to assess the protist community in 12 mineral and organic soil samples from different vegetation types and climatic zones using small subunit ribosomal RNA transcripts as marker. We detected a broad diversity of soil protists spanning across all known eukaryotic supergroups and revealed a strikingly different community composition than shown before. Protist communities differed strongly between sites, with Rhizaria and Amoebozoa dominating in forest and grassland soils, while Alveolata were most abundant in peat soils. The Amoebozoa were comprised of Tubulinea, followed with decreasing abundance by Discosea, Variosea and Mycetozoa. Transcripts of Oomycetes, Apicomplexa and Ichthyosporea suggest soil as reservoir of parasitic protist taxa. Further, Foraminifera and Choanoflagellida were ubiquitously detected, showing that these typically marine and freshwater protists are autochthonous members of the soil microbiota. To the best of our knowledge, this metatranscriptomic study provides the most comprehensive picture of active protist communities in soils to date, which is essential to target the ecological roles of protists in the complex soil system.

Conference Examines Complex Soil Systems

Conference Examines Complex Soil Systems

Assessing the origin of carbonates in a complex soil with a suite of analytical methods

Stable isotope C analysis is the most reliable method used for the distinction and understanding of soil carbonates origin. However, in soils with a complex geological setting the carbonate δ13C signature could lead to incorrect interpretations if used alone. Thus coupling this technique to other methods may be necessary. In this work we evaluated advantages and disadvantages of several methods, some of which are well known while others are still unused, to distinguish among carbonates of different origins in a soil developed on “Valle Versa Chaotic Complex”, a marly geological formation in North-western Italy. For a better evaluation of their potentialities the methods were also applied to simpler situations used as a reference for carbonate of pedogenic and lithogenic origins. Thin sections analysis revealed the presence of three kinds of carbonates in the investigated complex soil: one was pedogenic, while two showed clear lithogenic origin. The lithogenic carbonate that showed a low δ13C (about −9‰) was interpreted as freshwater while isotopic signature increased up to −4‰ with the presence of marls, thus no evidence of pedogenic precipitations could be obtained with isotopic analysis. The mean crystallite domain (L104) was highly variable and related to the amounts of co-precipitated impurities in the carbonates. Thus these methods provided important information about the formation environment. These rarely used techniques permitted to distinguish between pedogenic and lithogenic material in simple systems, but did not adequately support the presence of pedogenic carbonates in the complex soil. Surface areas and porosity evaluated by N2 adsorption are particularly influenced by the processes occurring during calcification such as the development of coatings and pore infillings. The comparison between additive models and measured specific surface area, indeed allowed us to observe the effect of pedogenic carbonate on the physical properties, although it did not permit any quantification. These results indicated that, although all the methods were able to distinguish between pedogenic and lithogenic origins in simple systems, only micromorphology and N2 adsorption techniques allowed for the identification of pedogenic carbonate in a more complex soil system.

Three Principles of Soil Change and Pedogenesis in Time and Space

Improved understanding of complex soil system's change over time and space can advance our forecasts and plans for changes related to critical societal needs. Taking a holistic and evolutionary view, this paper synthesizes three general principles of soil change and pedogenesis in time and space (especially time). First, the principle of conservation plus evolution provides the reconciliation of fast and slow changes in multiphase soil systems. Incomplete closure and partial irreversibility of many cyclic processes of soil functioning produce a range of residual solid products that are accumulated over time, giving rise to structured and informative soil profiles. Second, the principle of dissipation plus organization explains the simultaneous occurrence of soil matrix and soil structure during pedogenesis. Soil entropy changes provide potential indices for the degree of soil weathering (residuals) and soil structural development (fluxes) once appropriate quantification is made. Third, the principle of space plus time highlights the fundamental differences and intimate links between time and space. While space is reversible, conservative, and structured, time is irreversible, evolutionary, and nonstructured. Both time and space, however, share the common characteristics of preferentiality and threshold that govern soil functions and soil evolution. Many unknowns, however, remain regarding how complex soil systems work. The three principles offer useful perspectives for modeling and predicting soil change and pedogenesis. Considerable efforts are needed to reach a more quantitative treatment of the complex interaction between soil systems and their environment across time and space. This is an important direction for future soil science and its sustained contributions to societal needs.

Magnetic susceptibility as a proxy for rainfall: Worldwide data from tropical and temperate climate

The magnetic susceptibility of soils has been linked with climate, mainly through rainfall, by numerous investigators. For this study we assembled a worldwide dataset of 272 samples, both published and new, to determine the nature of the relationship between MS and rainfall. On a worldwide basis there is a crude relationship ( r 2 = 0.265) between MS and rainfall. MS increases with increasing rainfall from about 200 mm/yr to 1000–1200 mm/yr. Above 1200 mm/yr, MS decreases as rainfall increases up to about 2000 mm/yr. Under arid and semi-arid conditions, below about 200 mm/yr of rainfall, MS and rainfall exhibit no relationship, likely the result of limited pedogenic activity. When tropical and temperate localities are analyzed separately, the correlation between MS and rainfall exhibits a dramatic improvement, r 2 = 0.568 and 0.520, respectively. For similar amounts of rainfall tropical localities generally exhibit lower MS values which may be related to differences in the seasonal variation of rainfall. Because the soil environment is highly variable, it is unlikely that a global or even regional equation could accurately estimate rainfall from MS. Using data from Morocco and Mali we demonstrate that local equations using only MS to estimate rainfall produce reasonable results, r 2 = 0.700 for Morocco and 0.611 for Mali. However, a single independent variable is unlikely to capture the variability of the complex soil system. To the local equations described above we experimented with adding several independent variables in addition to MS including diffuse reflectance spectral data (DRS), x-ray diffraction (XRD), and x-ray fluorescence (XRF). For DRS data, % reflectance and red, yellow, and near-infrared wavelengths appear important; for XRD illite and kaolinite counts are important whereas for XRF Fe 2O 3 is important. The addition of these other independent variables dramatically improves prediction quality. In the case of the Mali transect, estimating rainfall from these variables produces an r 2 that exceeds 0.9. Based on these data we conclude that MS has the potential to be a reasonable proxy of rainfall for mean annual precipitation values from 200 to 2000 mm/yr, especially if local equations are used. Predictions can be improved by including other independent variables that show sensitivity to climate and are related to MS through the chemistry of the weathering process; we included DRS, XRD, and XRF data with good results.

Microbe-clay mineral interactions

Clays and clay minerals are common components in soils, sediments, and sedimentary rocks, and they play an important role in many environmental processes. Iron is ubiquitous in clays and clay minerals and its oxidation state, in part, controls the physical and chemical properties of these fine-grained minerals. The structural ferric iron in clay minerals can be reduced either chemically or biologically. Biological reductants include mesophilic and thermophilic microorganisms from diverse environments such as soils, sediments, sedimentary rocks, and hydrothermal hot springs. Multiple clay minerals have been used for microbial reduction studies, including dioctahedral smectite-illite series, palygorskite, chlorite, and their various mixtures in natural soils and sediments. All of these clay minerals are reducible by microorganisms under various conditions with smectite (nontronite) being the most reducible and illite the least. The rate and extent of bioreduction depends on many experimental factors, such as the type of microorganisms and clay minerals, solution chemistry, and temperature. Despite significant efforts, current understanding of the mechanisms of microbial reduction of ferric iron in clay minerals is still limited. Whereas some studies have presented evidence for a solid-state reduction mechanism, others argue that the clay mineral structure partially dissolves when the extent of reduction is high. This inconsistency may be related to several experimental conditions, and their specific effects are discussed in this paper. Whereas past experiments have been largely conducted in well-controlled laboratory systems, recent efforts have attempted to transfer knowledge to the field to improve our understanding of more complex soil systems for better agricultural practices. Biologically reduced clay minerals are also important agents in remediating inorganic and organic contaminants in soil and groundwater systems. This paper reviews the most recent developments and suggests some directions for future research

Correlation of Methane Production and Functional Gene Transcriptional Activity in a Peat Soil

The transcription dynamics of subunit A of the key gene in methanogenesis (methyl coenzyme M reductase; mcrA) was studied to evaluate the relationship between process rate (methanogenesis) and gene transcription dynamics in a peat soil ecosystem. Soil methanogen process rates were determined during incubation of peat slurries at temperatures from 4 to 37 degrees C, and real-time quantitative PCR was applied to quantify the abundances of mcrA genes and transcripts; corresponding transcriptional dynamics were calculated from mcrA transcript/gene ratios. Internal standards suggested unbiased recovery of mRNA abundances in comparison to DNA levels. In comparison to those in pure-culture studies, mcrA transcript/gene ratios indicated underestimation by 1 order of magnitude, possibly due to high proportions of inactive or dead methanogens. Methane production rates were temperature dependent, with maxima at 25 degrees C, but changes in abundance and transcription of the mcrA gene showed no correlation with temperature. However, mcrA transcript/gene ratios correlated weakly (regression coefficient = 0.76) with rates of methanogenesis. Methanogen process rates increased over 3 orders of magnitude, while the corresponding maximum transcript/gene ratio increase was only 18-fold. mcrA transcript dynamics suggested steady-state expression in peat soil after incubation for 24 and 48 h, similar to that in stationary-phase cultures. mcrA transcript/gene ratios are therefore potential in situ indicators of methanogen process rate changes in complex soil systems.

Modeling toxic compounds from nitric oxide emission measurements

Determining the amount and rate of degradation of toxic pollutants in soil and groundwater is difficult and often requires invasive techniques, such as deploying extensive monitoring well networks. Even with these networks, degradation rates across entire systems cannot readily be extrapolated from the samples. When organic compounds are degraded by microbes, especially nitrifying bacteria, oxides or nitrogen (NO x ) are released to the atmosphere. Thus, the flux of nitric oxide (NO) from the soil to the lower troposphere can be used to predict the rate at which organic compounds are degraded. By characterizing and applying biogenic and anthropogenic processes in soils the rates of degradation of organic compounds. Toluene was selected as a representative of toxic aromatic compounds, since it is inherently toxic, it is a substituted benzene compound and is listed as a hazardous air pollutant under Section 12 of the Clean Air Act Amendments of 1990. Measured toluene concentrations in soil, microbial population growth and NO fluxes in chamber studies were used to develop and parameterize a numerical model based on carbon and nitrogen cycling. These measurements, in turn, were used as indicators of bioremediation of air toxic (i.e. toluene) concentrations. The model found that chemical concentration, soil microbial abundance, and NO production can be directly related to the experimental results (significant at P < 0.01) for all toluene concentrations tested. This indicates that the model may prove useful in monitoring and predicting the fate of toxic aromatic contaminants in a complex soil system. It may also be useful in predicting the release of ozone precursors, such as changes in reservoirs of hydrocarbons and oxides of nitrogen. As such, the model may be a tool for decision makers in ozone non-attainment areas.

Identification and Visualization of Complex Spatial Pattern of Coastal Dune Soil Properties Using GIS-Based Terrain Analysis and Geostatistics

Coastal dunes display complex relationships among soil properties, vegetation, and geomorphology driven by marine and atmospheric dynamics. Considering topography as a fundamental control of the relations, this study investigated its influence on the spatial pattern of soil attributes in a coastal dune. We systematically collected 193 soil samples at intervals of 20 m from the Sindu coastal dunefield, South Korea, and analyzed 11 soil attributes. Principal component analysis extracted four main factors explaining ca. 75% of total soil variance. Correlation between each soil factor and topographic attributes calculated from raster digital elevation models permitted us to infer relationships between dune configuration and soil spatial variability. Interpretation of the first two factors demonstrated that nutrient input from marine sources by aeolian processes and topographic relief, an indirect measure of depth to the freshwater table, were two major determinants of the spatial distribution of soil properties. For the first factor, distance from the seashore proved to be the most significant indicator of edaphic conditions. Upslope area and wetness index were good proxies for the second factor, dune relief. These two variables significantly explained the distribution of soil moisture. A conceptual model is presented to describe how complex dune soil systems are created from simple topographic effects. The model addresses the importance of integrating foredune, dune slack, and inner dune ridge into one continuous system because topography, geomorphic (aeolian) processes, vegetation, and edaphic conditions are closely connected in a causal chain across the whole dune area.

Two-Dimensional DNA Gel Electrophoresis Mapping: a Novel Approach to Diversity Analysis of Bacterial Communities in Environmental Soil

The diversity analysis of bacteria is useful for the environmental assessment of soil. Traditional molecular-based methods such as denaturing gradient gel electrophoresis (DGGE) and terminal restriction fragment length polymorphism (T-RFLP) analysis achieve a low-resolution display of bacterial DNA fragments on a gel. To improve the resolution, a novel two-dimensional DNA gel electrophoresis (2-DGE) method was designed. This method can generate a high-resolution DNA map that facilitates the detailed analysis of soil bacteria. This map can be obtained by utilizing 2-DGE to separate genomic DNA fragments produced by polymerase chain reaction (PCR) amplification on the basis of chain length and G+C content. To develop this 2-DGE method further and to apply it to the assessment of bacterial diversity, we carried out a 2-DGE mapping of bacterial DNA fragments from different environmental soils and computed Shannon index as well as plotted rank-abundance curves on the basis of the relative intensity of each spot on the maps. DGGE mapping was also performed to compare the resolution of the two methods. 2-DGE mapping was capable of generating a higher resolution display by a factor of more than 2 using a DGGE fingerprint pattern on a piece of gel. Furthermore, the higher number of detected spots from the 2-DGE map enabled the assessment of differences in bacterial diversity in complex soil systems using a logarithmic normal rank-abundance plot.

Joint Hydrological–Geophysical Inversion for Soil Structure Identification

Reliable prediction of subsurface flow and contaminant transport depends on the accuracy with which the values and spatial distribution of process‐relevant model parameters can be identified. Successful characterization methods for complex soil systems are based on (i) an adequate parameterization of the subsurface, capable of capturing both random and structured aspects of the heterogeneous system, and (ii) site‐specific data that are sufficiently sensitive to the processes of interest. We present a stochastic approach in which the high‐resolution imaging capability of geophysical methods is combined with the process‐specific information obtained from the inversion of hydrological data. Geostatistical concepts are employed as a flexible means to describe and characterize subsurface structures. The key features of the proposed approach are (i) the joint inversion of geophysical and hydrological raw data, avoiding the intermediate step of creating a (nonunique and potentially biased) tomogram of geophysical properties and (ii) the concurrent estimation of hydrological and petrophysical parameters, in addition to (iii) the determination of geostatistical parameters from the joint inversion of hydrological and geophysical data. This approach is fundamentally different from inference of geostatistical parameters from an analysis of spatially distributed property data. The approach has been implemented into the iTOUGH2 inversion code and is demonstrated for the joint use of synthetic time‐lapse ground penetrating radar (GPR) travel times and hydrological data collected during a simulated ponded infiltration experiment at a highly heterogeneous site.

Effect of Soil Stress on Cadmium Transport in Saturated Soils

Prediction of the pollutant migration in complex soil systems requires an understanding of advection, dispersion, and adsorption processes. This paper focuses on the influence of the effective stress of soil on the pollutant transport processes. One-dimensional laboratory and centrifuge column tests under identical seepage conditions but with different stress distribution were conducted. One-dimensional numerical simulation of the contaminant transport model, using the computer software, POLLUTE Ver. 6, was carried out to curve fit the two column test results and to determine the transport parameters based on the best curve fitting. The transport parameters such as hydraulic conductivity, hydrodynamic dispersion, and distribution coefficient determined from the bench-scale and centrifuge columns were compared. The possible effects of soil stresses on contaminant transport were discussed. The experimental results from the bench-scale column and centrifuge column studies apparently illustrate that the stres...

Superior survival and degradation of dibenzo- p -dioxin and dibenzofuran in soil by soil-adapted Sphingomonas sp. strain RW1

The dibenzo-p-dioxin(DD)- and dibenzofuran(DF)-degrading bacterium, Sphingomonas sp. strain RW1, was tagged by insertion of a mini-Tn5 lacZ transposon in order to follow its fate in complex laboratory soil systems. The tagged strain was tested for its ability to survive in soil and degrade DF and DD applied at a concentration of 1 mg/g. Bacteria pre-adapted to soil conditions were found to survive better in DF- and DD-amended soil and degrade the substrate more efficiently than bacteria that had not been subjected to pre-adaptation. The concentration of soil-applied DF and DD, individually and in combination, decreased to less than 2% of the original concentrations within 3 weeks of addition of the RW1 derivative, accompanied by a short, but significant exponential increase in RW1 viable cells. During the same period the native bacterial population in soil was stable while viable fungi declined.

Determining the effects of pollutants on soil faunal communities and trophic structure using a refined microcosm system

AbstractWe used a refined microcosm technique to investigate the toxicity of copper, cadmium, malathion, and the polychlorinated biphenyl, Aroclor 1254, to trophic groups of soil nematodes and to the microarthropod community. Comparisons of changes in nematode abundance in control soils through time indicated that day 7 was the most appropriate time to sample the microcosms after chemical application. Nematode abundance was reduced after exposure to copper at 100 μg/g, with fungivore, bacterivore, and omnivore–predator nematodes being the most sensitive groups. Cadmium did not affect the nematode or microarthropod communities. Microarthropods were far more sensitive to malathion than were nematodes, and total microarthropod abundance was lower than controls at 400 μg/g. Prostigmatid mites and “other” arthropods were the most affected groups. Aroclor 1254 also had a greater negative impact on microarthropods than on nematodes. Total microarthropod abundance declined at 2,500 μg/g, with prostigmatid and oribatid mites exhibiting the highest susceptibility. Strong differential sensitivity between nematode and microarthropod communities indicates that both groups should be examined to fully evaluate the biological impact of chemicals on soils. We conclude that microcosms with field‐collected soil microfaunal communities offer high resolution of the ecotoxicologic effects of chemicals in complex soil systems.

An ecosystem approach to soil toxicity testing: a study of copper contamination in laboratory soil microcosms

An ecosystem approach to soil toxicity testing allows for integration of the effects of chemical contaminants on different components of the soil food web (system structure) and ecosystem-level processes (system function). We used this approach to study copper contamination in small laboratory soil microcosms. Microcosm soils were treated with CuSO 4 at the following concentrations: 0, 50, 100, 200, 400, and 800 mg Cu kg −1 soil. Five, 10, 20 and 40 days after soil treatment, we made the following organism-level measurements: microbial biomass N, substrate-induced respiration (SIR) and soil urease activity; total nematode numbers; earthworm mortality, growth and body accumulation of Cu. Our process-level measurements were net N mineralization and litter decomposition. SIR was the most sensitive of the parameters measured with significant effects observed at Cu concentrations as low as 50 mg kg −1. Microbial biomass N and earthworm growth showed intermediate sensitivity with effects at 200 mg kg −1 Cu. The least sensitive organism-level parameters were soil urease activity and nematode abundance, both showing significant effects only at 800 mg kg −1 Cu. At the process-level, there was an inhibition of litter decomposition starting at 100 mg kg −1 Cu, and a sharp increase in net N mineralization at 800 mg kg −1 Cu. By examining both the structure and function of the soil system, we were able to link the direct effects of copper on organisms to indirect effects on ecosystem-level processes and were able to suggest mechanisms to account for our results. The release of nitrogen from microbial cells killed by direct toxicity of Cu at 800 mg kg −1 resulted in a transient increase in dissolved organic N, followed by a flush of N mineralization, resulting in large increase in NH 4N compared with the untreated control. Microbial mortality also apparently led to the inhibition of litter decomposition. Measuring the effects of contamination at different trophic levels simultaneously, and linking them to ecosystem processes, provided insights into the ecological mechanisms of the observed effects. This makes the ecosystem approach particularly valuable for analyzing the highly complex soil system. We suggest that the information obtained in a laboratory test based on the ecosystem approach is the most appropriate method for extrapolation to field situations.

PREDICTION OF SOLUTE TRANSPORT USING A TRANSFER FUNCTION MODEL AND THE CONVECTION-DISPERSION EQUATION

The convection-dispersion equation (CDE) is the most commonly used process representation for describing solute movement through soils. A transfer function is a model for studying complex soil systems in a simple way by characterizing the output flux as a function of the input flux. Extensive solute transport data from a laboratory experiment conducted through long soil columns were used to validate the intrinsic assumptions of the CDE and the transfer function. Analyses of the experimental data showed that the observed dispersion coefficient increased with the travel distance for both homogeneous and heterogeneous soils. The dispersion coefficients had a two-order change within the 1250-cm soil columns and were described using a linear function of the solute travel distance. At the same travel distance, the dispersion coefficients in the heterogeneous soil column were about 50 times higher than those in the homogeneous soil. The experimental data better supported the assumptions of the transfer function than those of the CDE. An excellent linear relationship was found between the mean of log of the travel time and log of the travel distance. In turn, the relationship well described the scale-dependent dispersion coefficients of the homogeneous and heterogeneous soil columns. The convection-dispersion equation and the transfer equation were utilized to predict solute transport in homogeneous and heterogeneous porous media. Compared with the experimental data, the transfer function predicted solute transport in the porous media much more accurately than did the CDE for these examples. In addition, the soil spatial variability had a less profound effect on the transfer function predictions than on the CDE predictions.

Soil microcosm for testing the effects of chemical pollutants on soil fauna communities and trophic structure

AbstractA microcosm technique is presented that uses community and trophic‐level analysis of soil nematodes and microarthropods to determine the effects of chemicals on soil systems. Forest soil was treated with either copper (0, 100, 200, 400, and 600 m̈g g−1), p‐nitrophenol (0, 20, 40, 80, and 160 m̈g g−1), or trinitrotoluene (0, 25, 50, 100, and 200 m̈g g−1). Nematodes were sorted into bacterivore, fungivore, herbivore, and omnivore‐predator trophic groups, and a hatchling category. Microarthropods were sorted to the acarine suborders Prostigmata, Mesostigmata, and Oribatida; the insectan order Collembola; and a miscellaneous group. Omnivore‐predator nematodes and mesostigmatid and oribatid mites were the groups most sensitive to copper and were significantly reduced at levels as low as 100 m̈g g−1 copper. Total nematode and microarthropod numbers declined above 200 m̈g g−1 copper. Trophic structure analysis suggested that high sensitivity of nematode predators to intermediate levels of copper reduced predation on herbivore nematodes and resulted in greater numbers of nematodes compared to controls. p‐Nitrophenol was very toxic to the nematode community, and all trophic groups were significantly reduced above 20 m̈g g−1. However, there was no effect of p‐nitrophenol on microarthropods. Trinitrotoluene had no significant negative effect on total abundance of either group of soil fauna, but oribatids were significantly reduced at 200 m̈g g−1. Our results demonstrated that soil nematodes and microarthropods were sensitive indicators of environmental contaminants and that trophic‐structure and community analysis has the potential to detect more subtle indirect effects of chemicals on soil food‐web structure. We conclude that microcosms with field communities of soil microfauna offer high resolution of the ecotoxicological effects of chemicals in complex soil systems.

Multicomponent Adsorption of Polycyclic Aromatic Hydrocarbons in Manufactured Gas Plant Soils

Abstract Adsorption is an important process in the bioremediation of Manufactured Gas Plant (MGP) soils contaminated with high levels of polycyclic aromatic hydrocarbons (PAH). Over 2,000 sites nationwide exist that are contaminated with complex mixtures of PAH and other pollutants. Many PAH are classified as EPA priority pollutants. The adsorption properties of weathered contaminated soils are difficult to measure using pulse or step perturbations due to heterogeneous contaminant distributions and heterogeneous soil physical structure. This study compares the use of cyclical perturbations with step change perturbations to analyze these complex soil systems. The sinusoidal method proved to be more robust than the step perturbation method. Sinusoidal response was easier to interpret and was continuous. The step change method produced a transient response that was more difficult to interpret. Two parameters, period and amplitude, were available when using sinusoidal perturbation methods while only one param...