Kooperativer Bibliotheksverbund

Language: English

In: Soil Science Society of America Journal, Jan-Feb, 2012, Vol.76(1), p.51(10)

Description: Solute diffusivity in soil plays a major role in many important processes with relation to plant growth and environmental issues. Soil solute diffusivity is affected by the volumetric water content as well as the morphological characteristics of water-filled pores. The solute diffusivity in intact soil samples from two different tillage treatments (soil from below the depth of a harrow treatment and soil from within a moldboard plowed plow layer) was estimated based on concentration profiles using a newly developed method. The method makes use of multiple tracers (two sets of counterdiffusing tracers) for a better determination of the diffusivity. The diffusivity was higher in the below-till soil than the plowed soil at the same soil water matric potential due to higher water content but also due to higher continuity and lower tortuosity of the soil pores. We measured identical solute diffusivities independent of the tracer set used. We analyzed the whole data set using Archie's law and found a linear relation between Arcbie's exponent and the logarithm of the soil water matric suction in centimeters of water (pF). An analysis of seven data sets from the literature showed that this was a general trend for soils with moderate to low clay contents. doi: 10.2136/sssaj2011.0043

Keywords: Clay ; Data Collection ; Soil Water Content ; Soil Pore System ; Soil Treatment ; Solutes ; Soil Sampling ; Soil Water ; Plowing ; Tracer Techniques ; Plant Growth ; Water Content ; Harrows ; Diffusivity;

ISSN: 0361-5995

E-ISSN: 14350661

DOI: 10.2136/sssaj2011.0043

Language: English

In: Soil Biology and Biochemistry, Feb, 2013, Vol.57, p.706(7)

Description: To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.soilbio.2012.08.032 Byline: Soren O. Petersen (a), Per Ambus (b), Lars Elsgaard (a), Per Schjonning (a), Jorgen E. Olesen (a) Abstract: The potential for N.sub.2O emissions outside the main growing season may be influenced by long-term effects of cropping system. This was investigated by collecting intact soil cores (100 cm.sup.3, 0-4 cm depth) under winter wheat in three organic cropping systems and a conventional reference within a long-term crop rotation experiment. Average annual inputs of C in crop residues and manure ranged from 1.7 to 3.3 Mg ha.sup.-1. A simulated freeze-thaw cycle resulted in a flush of CO.sub.2 during the first 48 h, which could be mainly from microbial sources. Other samples were adjusted to approximately -10, -30 or -100 hPa and amended with excess.sup.15NO.sub.3.sup.- prior to freezing and thawing. Denitrification was the main source of N.sub.2O during a 72-h incubation at 22 [degrees]C, as judged from N.sub.2O and total.sup.15N evolution. Although the input of C in the conventionally managed cropping system was significantly less than in the organic cropping systems, it showed higher N.sub.2O evolution at all three matric potentials. Estimates of relative gas diffusivity (D.sub.P /D.sub.0) in soil from the four cropping systems indicated that C input affected soil aeration. Soil from the two cropping systems with highest C input showed N.sub.2O evolution at D.sub.P /D.sub.0 in excess of 0.02, which is normally considered a threshold for development of anaerobic sites in the soil, presumably because the oxygen demand was also high. The study shows that cropping system affects both soil gas diffusivity and C availability, and that both characteristics significantly influence the N.sub.2O emission potential. Author Affiliation: (a) Department of Agroecology, Aarhus University, Tjele, Denmark (b) Department of Chemical and Biochemical Engineering, Technical University of Denmark, Roskilde, Denmark Article History: Received 4 May 2012; Revised 28 August 2012; Accepted 29 August 2012

Keywords: Wheat -- Analysis ; Cropping Systems -- Analysis ; Denitrification -- Analysis ; Soil Aeration -- Analysis

ISSN: 0038-0717

Source: Cengage Learning, Inc.

Language: English

In: Soil & Tillage Research, 2015, Vol.152, p.52(15)

Description: To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.still.2015.03.002 Byline: Per Schjonning, Matthias Stettler, Thomas Keller, Poul Lassen, Mathieu Lamande Abstract: Display Omitted Author Affiliation: (a) Aarhus University, Department of Agroecology, Research Centre Foulum, Blichers Alle 20, P.O. Box 50, DK-8830 Tjele, Denmark (b) Bern University of Applied Sciences, Langgasse 85, CH-3052 Zollikofen, Switzerland (c) Agroscope, Department of Natural Resources & Agriculture, Reckenholzstrasse 191, CH-8046 Zurich, Switzerland (d) Swedish University of Agricultural Sciences, Department of Soil & Environment, Box 7014, SE-75007 Uppsala, Sweden Article History: Received 21 November 2014; Revised 2 March 2015; Accepted 5 March 2015

ISSN: 0167-1987

Source: Cengage Learning, Inc.

Language: English

In: Soil Science Society of America Journal, July-August, 2010, Vol.74(4), p.1084(8)

Description: Solute diffusion controls important processes in soils: plant uptake of nutrients, sorption-desorption processes, degradation of organic matter, and leaching of radionuclides through clay barriers. We developed a new method for measuring the solute diffusivity (solute diffusion coefficient in the soil relative to water) in intact soil samples (the Multiple Tracer, Filter Separated half-cell method using a Dynamic Model for parameter estimation [MT-FSDM]). The MT-FS-DM method consists of half-cell diffusion of two pairs of counter diffusing anionic tracers and a parameter estimation scheme that allows diffusion coefficients for tracers in the two half-cells to be estimated on the basis of two concentration profiles in each sample. The parameter estimation scheme uses a fully dynamic (time-resolved) simulation model. From sensitivity and uncertainty analyses of the dynamic model, we found that the MT-FS-DM method provided reliable results. We compared diffusivities measured on a sandy loam soil using the MT-FS-DM method with diffusivities from six sandy loam test soils from the literature. The new method can be used to estimate solute diffusivity in intact structured soil and provides a more confident estimate for solute diffusion due to the use of two tracer profiles in the same soil sample. Especially when we are interested in determining the diffusivity of a single intact soil sample, such as when relating solute diffusivity to other properties of the soil (e.g., microbial activity), this method will be an improvement over existing methods. Abbreviations: DFBA, 2,6-difluorobenzoic acid; MT-FS-DM, Multiple Tracer, Filter Separated half-cell method using a Dynamic Model for parameter estimation; PFBA, pentafluorobenzoic acid. doi: 10.2136/sssaj2009.0285

Keywords: Loams -- Mechanical Properties ; Tracers (Chemistry) -- Usage ; Solute Transport (Hydrology) -- Observations ; Diffusion (Physics) -- Measurement ; Soil Mechanics -- Research

ISSN: 0361-5995

E-ISSN: 14350661

DOI: 10.2136/sssaj2009.0285

Language: English

In: Soil Biology and Biochemistry, Dec, 2012, Vol.55, p.17(3)

Description: To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.soilbio.2012.05.018 Byline: Soren Christensen (a), Marie Dam (a), Mette Vestergard (a), Soren O. Petersen (b), Jorgen E. Olesen (b), Per Schjonning (b) Abstract: There are no methods at hand with a long and proven record for assessing the relative contribution of fungi and bacteria to decomposer activity in soil. Whereas a multitude of methods to determine fungal and bacterial biomass are available, activity assays traditionally relied on the substrate-induced respiration (SIR) inhibition approach. Here we compare fungal contribution to the microbial active biomass assessed by the SIR inhibition method with the contribution of fungal-feeding nematodes to the microbial-feeding nematode community. Four cultivation systems on the same soil that differ in carbon inputs with a factor two ranked exactly the same with the two methods. A conventionally farmed rotation with low organic input had the lowest fungal fraction, while three organically farmed soils ranked higher. Author Affiliation: (a) Terrestrial Ecology, Biological Institute, Copenghagen University, Universitetsparken 15, DK-2100 Kobenhavn O, Denmark (b) Institute for Agroecology, Aarhus University, Blichers Alle 20, DK-8830 Tjele, Denmark Article History: Received 9 February 2012; Revised 19 April 2012; Accepted 28 May 2012

Keywords: Roundworms ; Antibiotics ; Soil Microbiology ; Soil Carbon

ISSN: 0038-0717

Source: Cengage Learning, Inc.

Language: English

In: Soil Science Society of America Journal, Nov-Dec, 2013, Vol.77(6), p.1965(12)

Description: Soil structure maintains prime importance in determining the ability of soils to carry out essential ecosystem functions and services. This study quantified the newly formed structure of 22-mo field-incubated physically disturbed (2-mm sieved) samples of varying clay mineralogy (illite, kaolinite, and smectite) amended with organic material (7.5 Mg ha-1). The newly formed structure was compared with that of sieved, repacked (SR) and natural intact samples described in previous studies. Assessment and comparison of structural complexity and organization was done using water retention (pore size distribution), soil gas diffusivity, air permeability, and derived pore network complexity parameters. Significant decreases in bulk density and increases in pores 〉100 ?m were observed for incubated samples compared with SR samples. For the soils studied, the proportion of pores 〉100 ?m increased in the order: smectite 〈 illite 〈 kaolinite, with no effect of organic amendment. Soil structural complexity, quantified by soil gas diffusivity, air permeability, and derived pore network indices, was greater for incubated than SR samples. For illitic soils, incubated samples had lower water content and higher air-filled porosity and air permeability than natural intact samples at a matric potential of -10 kPa. Despite this, soil pore organization was similar for both natural and incubated soils, but pore network complexity increased in the order: SR 〈 incubated 〈 natural soils. Finally, the air permeability percolation threshold corresponding to the physically based diffusion threshold increased with structural complexity (SR = 0.02 ?m2; incubated = 0.20 ?m2; natural = 0.70 ?m2). Thus, critical reexamination is needed of the often-used 1.0-?m2 percolation threshold for convective air transport when analyzing pore network complexity. Lack of a clear effect of organic amendment for incubated samples suggests using higher application rates in future studies.

Keywords: Porosity -- Analysis ; Soil Permeability -- Analysis ; Soil Research

ISSN: 0361-5995

E-ISSN: 14350661

DOI: 10.2136/sssaj2013.07.0270

Language: English

In: Soil Science Society of America Journal, Jan-Feb, 2012, Vol.76(1), p.18(10)

Description: Accurate estimation of soil gas diffusivity ([D.sub.p]/[D.sub.o], the ratio of gas diffusion coefficients in soil and free air) and air permeability ([k.sub.a]) from basic texture and pore characteristics will be highly valuable for modeling soil gas transport and emission and their field-scale variations. From the topsoil of two Danish arable fields representing two natural clay gradients, [D.sub.p]/[D.sub.o] and [k.sub.a] were measured at soil water matric potentials between -1 and -100 kPa on undisturbed soil cores. The Rosin-Rammler particle size distribution parameters [alpha] and [beta] (characteristic particle size and degree of sorting, respectively) and the Campbell water retention parameter b were used to characterize particle and pore size distributions, respectively. Campbell b yielded a wide interval (4.6-26.2) and was highly correlated with [alpha], [beta], and volumetric clay content. Both [D.sub.p]/[D.sub.o] and [k.sub.a] followed simple power-law functions (PLFs) of air-filled porosity [[epsilon].sub.a]). The PLF tortuosity--connectivity factors ([X.sup.*]) for [D.sub.p]/[D.sub.o] and [k.sub.a] were both highly correlated with all basic soil characteristics, in the order of volumetric clay content = Campbell b 〉 gravimetric clay content 〉 [alpha] 〉 [beta]. The PLF water blockage factors (H) for [D.sub.p]/[D.sub.o] and [k.sub.a] were also well (but relatively more weakly) correlated with the basic soil characteristics, again with the best correlations to volumetric clay content and b. As a first attempt at developing a simple [D.sub.p]/ [D.sub.o] model useful at the field scale, we extended the classical Buckingham [D.sub.p]/ [D.sub.o] model ([[epsilon.sub.a.sup.2]) by a scaling factor based on volumetric clay content. The scaled Buckingham model provided accurate predictions of [D.sub.p]([[epsilon].sub.a])/[D.sub.o] across both natural clay gradients. doi: 10.2136/sssaj 2011.0125

Keywords: Clay ; Particle Size ; Topsoil ; Texture ; Prediction ; Porosity ; Models ; Soil Water ; Soil Air ; Sorting ; Air ; Particle Size Distribution ; Permeability ; Diffusivity;

ISSN: 0361-5995

Language: English

In: Agriculture, Ecosystems and Environment, Sept 15, 2012, Vol.159, p.9(10)

Description: To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.agee.2012.06.021 Byline: Emmanuel Arthur (a), Per Moldrup (b), Martin Holmstrup (c), Per Schjonning (a), Anne Winding (d), Philipp Mayer (d), Lis W. de Jonge (a) Keywords: Soil contamination; Dehydrogenase activity; Clay dispersibility; Air permeability; Compression; Resilience Abstract: a* Microbial activity decreased significantly at copper concentration [approximately equal to]500mgkg.sup.-1. a* Soil compression resistance had an increasing trend with copper concentration. a* Copper contaminated soils had higher amounts of water dispersible clay. a* Clay dispersibility correlated with microbial activity in a copper contaminated field. Author Affiliation: (a) Department of Agroecology, Faculty of Science and Technology, Aarhus University, Blichers Alle 20, P.O. Box 50, DK-8830 Tjele, Denmark (b) Department of Biotechnology, Chemistry and Environmental Engineering, Aalborg University, Sohngaardsholmsvej 57, DK-9000 Aalborg, Denmark (c) Department of Bioscience, Aarhus University, Vejlsovej 25, DK-8600 Silkeborg, Denmark (d) Department of Environmental Science, Faculty of Science and Technology, Aarhus University. Frederiksborgvej 399, DK-4000 Roskilde, Denmark Article History: Received 23 February 2012; Revised 1 June 2012; Accepted 15 June 2012

Keywords: Soil Pollution ; Permeability ; Soil Microbiology ; Universities And Colleges

ISSN: 0167-8809

Source: Cengage Learning, Inc.

Language: English

In: Soil Science Society of America Journal, July-August, 2011, Vol.75(4), p.1315(15)

Description: Accurate predictions of the soil-gas diffusivity ([D.sub.p]/[D.sub.o], where [D.sub.p] is the soil-gas diffusion coefficient and [D.sub.o] is the diffusion coefficient in free air) from easily measureable parameters like air-filled porosity ([epsilon]) and soil total porosity ([PHI]) are valuable when predicting soil aeration and the emission of greenhouse gases and gaseous-phase contaminants from soils, Soil type (texture) and soil density (compaction) are two key factors controlling gas diffusivity in soils, We extended a recently presented density-corrected [D.sub.p]([epsilon])/[D.sub.o] model by letting both model parameters ([alpha] and [beta]) be interdependent and also functions of [PHI]. The extension was based on literature measurements on Dutch and Danish soils ranging from sand to peat. The parameter, showed a promising linear relation to total porosity, while [beta] also varied with, following a weak linear relation, The thus generalized density-corrected (GDC) model gave improved predictions of diffusivity across a wide range of soil types and density levels when tested against two independent data sets (total of 280 undisturbed soils or soil layers) representing Danish soil profile data (0-8 m below the ground surface) and performed better than existing models. The GDC model was further extended to describe two-region (bimodal) soils and could describe and predict [D.sub.p]/[D.sub.o] well for both different soil aggregate size fractions and variably compacted volcanic ash soils, A possible use of the new GDC model is engineering applications such as the design of highly compacted landfill site caps. Abbreviations: D-C, density-corrected; GDC, generalized density-corrected; MQ, Millington and Quirk; WLR, water-induced linear reduction. doi: 10.2136/sssaj2010.0405

Keywords: Soil Density -- Research ; Soil Aeration -- Research ; Diffusion (Physics) -- Research

ISSN: 0361-5995

E-ISSN: 14350661

DOI: 10.2136/sssaj2010.0405

Language: English

In: Geoderma, June 15, 2018, Vol.320, p.115

Description: Keywords Pedotransfer function; Bulk density; Matric potential; Soil texture Highlights * Soil precompression stress, [sigma].sub.pc, was estimated from stress-strain curves. * Bulk density and pF = log(matric potential) explained up to 90% of variation in [sigma].sub.pc. * Bulk density, pF and soil content of clay predicted [sigma].sub.pc well across soil depths. * Predicted [sigma].sub.pc at pF = 2 was constant across clay content for a given bulk density. * Model predictions corresponded to trends in two independent data sets. Abstract Compaction of the subsoil is an almost irreversible damage to the soil resource. Modern machinery exerts high mechanical stresses to the subsoil, and a range of studies report significant effects on soil functions. There is an urgent need for quantitative knowledge of soil strength in order to evaluate sustainability of current field traffic. The aim of this study was to identify the most important drivers of soil precompression stress, [sigma].sub.pc, and to develop pedotransfer functions for prediction of [sigma].sub.pc. We revisited previously published data on [sigma].sub.pc for a silty clay loam soil at a range of soil matric potentials. [sigma].sub.pc was estimated from the original stress-strain curves by a novel, numerical method for estimating the stress at maximum curvature, assumingly partitioning the curve into elastic and plastic sections. Multiple regression was used to identify the drivers best describing the variation in [sigma].sub.pc data. For the plough layer, [sigma].sub.pc increased with bulk density (BD), which explained 77% of the variation. For the subsoil layer just beneath the ploughing depth, the model best describing [sigma].sub.pc data included the drivers BD and pF, with pF defined as the log to the negative matric potential. The model was strongly significant with R.sup.2 = 0.90. The same trend was found for three subsoil layers from 0.35--0.95 m depth, but the model accounted for only 16% of the variation in [sigma].sub.pc. A model involving samples from all soil layers and including BD, pF and soil clay content accounted for 38% of the variation. This model predicted [sigma].sub.pc to be constant at pF ~2 across soil clay contents for a given soil BD. For pF 2). Model predictions correlated well with measured data in two independent data sets from the literature. However, the predictions were approximately double those of one of the data sets. This may relate to the longer stress application used in laboratory compression tests for these data compared to the other calibration data set and to the procedure used in this study. We encourage further studies of the effect of stress application procedures in compression tests. The prediction equations established in this investigation have to be verified based on measurements of [sigma].sub.pc for a range of soil types, soil horizons and soil moisture conditions. Author Affiliation: Aarhus University, Department of Agroecology, Research Centre Foulum, Blichers Alle 20, P.O. Box 50, DK-8830 Tjele, Denmark * Corresponding author. Article History: Received 7 November 2017; Revised 12 January 2018; Accepted 21 January 2018 (miscellaneous) Handling Editor: Morgan Cristine L.S. Byline: Per Schjonning [per.schjonning@agro.au.dk] (*), Mathieu Lamande

Keywords: Stress-Strain Curves – Analysis ; Soil Moisture – Analysis ; Soil Structure – Analysis ; Loams – Analysis

ISSN: 0016-7061

E-ISSN: 18726259

DOI: 10.1016/j.geoderma.2018.01.028