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Biochar addition to soils is heralded to reduce N 2 O emissions, but still, the explanatory mechanisms have not been resolved. Moreover, it is uncertain whether N 2 O emission reductions would persist after prolonged biochar incorporation in the field. In this study, we incorporated four biochar types in a loam textured cropland field and intact soil cores were sampled to investigate the physical control of biochar on denitrification after 7 months. During a first incubation experiment, we measured N 2 O emissions from undisturbed and disturbed (i.e. sieved (2 mm) and grounded) soil cores. Both in the disturbed and undisturbed soil cores biochar at water filled pore space (WFPS) of 80% reduced the N 2 O emissions by 50–90%, refuting the hypothesis that biochar exerts an indirect physical control over soil denitrification several months after incorporation. Secondly, we hypothesized that biochar creates denitrification ‘hotspots’ in soil, where complete reduction of N 2 O to N 2 is promoted compared to non-amended soil. In these hotspots biochar particles could act as microlocations with local anaerobic conditions and local higher pH, stimulating in this way complete denitrification. Via the acetylene inhibition method we did not observe a reduction in the N 2 O/(N 2 O + N 2 ) ratio, which could suggest that biochar did not promote the reduction of N 2 O to N 2 . Manipulations likely to promote labile C bioavailability, here either by glucose addition or by soil particulate OM disclosure after disruption of soil aggregates, resulted in the most prominent biochar-induced N 2 O emission reductions. [ABSTRACT FROM AUTHOR]

Although the amendment of various forms of exogenous organic matter (EOM) is a common practice in cropland production, it is to date not clear if its mineralisation in soil depends on application rate. Previous research suggested that spatial concentration of EOM in soil positively impacts its degradability. Here, we seek to test these reports and furthermore to investigate if an interactive effect exists with native soil organic carbon (SOC) concentration. We hypothesised that at a low EOM dose, more EOM remains undecomposed in soil and that this effect becomes stronger at lower SOC level. Moreover, as a secondary goal, we explored if priming of native SOC mineralisation depends on EOM dose. Therefore, we set up seventy-day soil incubation experiments with six varying C4-maize residue (δ13C = −12.7‰) doses (0–6 g kg−1) in soil mesocosms of loamy sand subsoils (δ13C = −25.7‰) with three different native SOC levels (i.e. 0.1, 0.5, and 1.0%). Soil CO 2 emissions and isotopic signature measurements of CO 2 allowed to discern EOM and SOC mineralisation. We found that EOM-derived C mineralisation increased proportionally to EOM dose, refuting the hypothesised relative undecomposed EOM at low concentration. Volumes of larger pore neck size diameter classes (60–100 and >300 μm) almost doubled at high EOM dose, demonstrating formation of macropores. Yet, this apparently did not impact EOM mineralisation, probably because O 2 supply was always sufficient to allow unlimited activity of EOM degraders, even at higher EOM doses, as indicated by generally higher measured redox potential. With EOM dose, fungal marker PLFA abundances increased in the 1% SOC soil and protozoan abundances increased in all three soils, but apparently these shifts did not result in an enhanced relative degradation of the EOM. Increasing EOM doses induced negative priming, e.g. EOM ≥1 g kg−1 reduced SOC mineralisation by >43% and >24% compared to the control in the 0.1 and 0.5% SOC soils, respectively; whereas no priming occurred in soil with 1% SOC. These results were largely explained by the amount of added C relative to microbial biomass carbon, and the theorised switch of slow decomposers (so called K-strategists and involved in recalcitrant compound decomposition) from SOM to preferentially decompose EOM at higher doses. We also postulate that at low SOC %, the obvious increased O 2 consumption with higher EOM dose more readily results in local anaerobic conditions in finer pores, i.e. where SOC is located and mineralised. We conclude that on the short term, agricultural management for SOM thus does not need to consider EOM doses but only the total amount of EOM. • We hypothesised relative OM decomposition to increase at higher concentration in soil. • Dose of maize straw however did not impact its relative degradability in soil. • High doses did enhance soil macroporosity and generally increased soil Eh. • Increasing maize straw dose induced stronger negative priming of SOC at low SOC. [ABSTRACT FROM AUTHOR]

Abstract: The techniques available for sterilisation or defaunation of soil in ecological experiments mostly have strongly unwanted effects on soil structure and the dynamics of major nutrients such as nitrogen. The potential for using gamma irradiation to prepare defaunated soil microcosms was investigated by subjecting undisturbed soil cores to a range of irradiation doses (0, 5, 10, 20 and 40 kGy). The absence of living nematodes at the lowest irradiation dose was confirmed by microscopic observation. The effects of irradiation dose on mineral nitrogen (as NO3 − and NH4 +), microbial biomass C (Cmic), and phospholipid fatty acid (PLFA) concentration and composition were determined over a 4 week incubation period. An increase in the concentration of NO3 − occurred during the incubation period after exposure to 0, 5 and 10 kGy but was barely detectable at 20 and 40 kGy. The effect of irradiation dose on NH4 + release was complex and highly variable within treatments, with the 10 kGy dose resulting in the highest concentrations. Microbial biomass carbon was significantly reduced following a 20 kGy irradiation dose and below detection at 40 kGy. Most remarkably, the sum of all measured PLFAs did not differ significantly between most treatments and was not correlated with microbial biomass. In most cases the concentration of signature fatty acids only differed significantly between the control and the highest irradiation dose treatments. To ascertain the sensitivity of microbial taxa to acute gamma irradiation with accuracy, measures of microbial community structure other than PLFA analysis are needed. [Copyright &y& Elsevier]

Abstract: For the investigation of many geometrical features of soils, computer-assisted image analysis has become a method of choice over the last few decades. This analysis involves numerous steps, regarding which subjective decisions have to be made by the individuals conducting the research. This is particularly the case with the thresholding step, required to transform the original (color or greyscale) images into the type of binary representation (e.g., pores in white, solids in black) needed for fractal analysis or simulation with Lattice–Boltzmann models. Limited information exists at present on whether different observers, analyzing the same soil, would be likely to obtain similar results. In this general context, the first objective of the research reported in this article was to determine, through a so-called “round-robin” test, how much variation exists among the outcomes of various image thresholding strategies (including any image pre-treatment deemed appropriate), routinely adopted by soil scientists. Three test images – of a field soil, a soil thin section, and a virtual section through a 3-dimensional CT data set – were thresholded by 13 experts, worldwide. At the same time, variability of the outcomes of a set of automatic thresholding algorithms, applied to portions of the test images, was also investigated. The experimental results obtained illustrate the fact that experts rely on very different approaches to threshold images of soils, and that there is considerable observer influence associated with this thresholding. This observer dependence is not likely to be alleviated by adoption of one of the many existing automatic thresholding algorithms, many of which produce thresholded images that are equally, or even more, variable than those of the experts. These observations suggest that, at this point, analysis of the same image of a soil, be it a simple photograph or 3-dimensional X-ray CT data, by different individuals can lead to very different results, without any assurance that any of them would be even approximately “correct” or best suited to the objective at hand. Different strategies are proposed to cope with this situation, including the use of physical “standards”, adoption of procedures to assess the accuracy of thresholding, benchmarking with physical measurements, or the development of computational methods that do not require binary images. [Copyright &y& Elsevier]