Nanoparticle (NPs) containing essential metals are being considered in formulations of fertilizers to boost plant nutrition in soils with low metal bioavailability. This paper addresses whether colonization of wheat roots by the bacterium, Pseudomonas chlororaphis O6 (PcO6), protected roots from the reduced elongation caused by CuO NPs. There was a trend for slightly elongated roots when seedlings with roots colonized by PcO6 were grown with CuO NPs; the density of bacterial cells on the root surface was not altered by the NPs. Accumulations of reactive oxygen species in the plant root cells caused by CuO NPs were little affected by root colonization. However, bacterial colonization did reduce the extent of expression of an array of genes associated with plant responses to stress induced by root exposure to CuO NPs. PcO6 colonization also reduced the levels of two important chelators of Cu ions, citric and malic acids, in the rhizosphere solution; presumably because these acids were used as nutrients for bacterial growth. There was a trend for lower levels of soluble Cu in the rhizosphere solution and reduced Cu loads in the true leaves with PcO6 colonization. These studies indicate that root colonization by bacterial cells modulates plant responses to contact with CuO NPs.
In arid and semiarid regions, calibrating bulk soil salinity sensing technologies such as electromagnetic induction (EMI) relies on the assumption of uniformity of all soil factors influencing the reading, except soil salinity, to create a calibration model. When potentially perturbing factors are non‐homogeneous or interact in a non‐systematic way, conditional mean calibration models based on the least squares method fail to completely describe the entire salinity distribution due to the violation of model assumptions (i.e., homogeneity of perturbing factors). Therefore a new approach is needed. The main objective of this study is to produce a salinity calibration model capable of reasonably predicting salinity directly from the EMI signal readings irrespective of the heterogeneity of perturbing factors. Toward this end we collected ground‐truth samples and corresponding EMI measurements in 35 agricultural fields covering 495 ha of the Irrigated Middle Bear (IMB) subbasin of Cache County in Utah. Using quantile regression (QR), which makes no assumption about the distribution of error, we estimated a subset of conditional quantiles of salinity as a function of EMI reading. We found that the mean effects estimated by previous models are misleading because they model behavior around the 0.9 th quantile of the distribution, and thus grossly underestimate salinities in the lower quantiles. We developed a new EMI weighting procedure to account for the high heterogeneity that may have caused the upper‐tailed distributional behavior. Variability was effectively captured and well modeled at specified quantiles of the salinity distribution using the QR technique. Independent validation of selected multiple QR models indicates that at low salinity ranges corresponding to conditional quantile (τ) ≤ 0.25, the QR models may be applied to any soil with low range salinity.
Abstract Forest species control the quantity and chemistry of organic matter input, which in interaction with the soil physicochemical properties, environmental conditions and microbial community associated with a given ecosystem may result in specific patterns of soil organic carbon (SOC) stabilization and chemistry. The objectives of this study were: (a) to characterize the chemistry of soil organic matter and SOC fractions across the gradient from pure aspen ( Populus tremuloides Michx.) to pure conifer ( Abies lasiocarpa (Hook.) Nutt. and Pseudotsuga menziesii (Mirbel) Franco) stands in semi‐arid montane forests, and (b) to determine whether the effect of overstory composition on SOC chemistry was patent beyond the influence of site conditions and microbial decomposer community. We used Fourier transform infrared spectroscopy to analyse the chemistry of bulk soil (BS), light fraction (LF) and mineral‐associated SOC (MoM) from mineral soils (0–15 cm) sampled across the natural gradient of aspen and mixed conifer stands from northern and southern Utah. Vegetation overstory had a subtle effect on the MoM fraction, indicating higher proportion of aliphatic C with aspen dominance, whereas there were no differences in LF chemistry between vegetation types. Independently of the vegetation cover type, the MoM fraction was enriched in aliphatic C compared to the LF, although the proportion of polysaccharides and C‐O groups increased in the MoM fraction for plot samples. Differentiation between spectra from soils developed on sedimentary rock and soils developed on basalt, quartzite and limestone, highlighted the influence of parent material and mineralogy on MoM chemistry. The patterns in SOC fractions' chemistry do not allow an affirmation that greater SOC storage under aspen is due to the accumulation of recalcitrant compounds (i.e., aliphatic C) and controlled by litter chemistry. Rather, they suggest that the ensemble of litter chemistry, microbial community and soil properties in aspen stands enhances SOC storage. Highlights Vegetation overstory and site characteristics (e.g., parent material) influence SOC chemistry and stabilization patterns. Light fraction SOC spectra did not differ between forest species in the aspen‐conifer ecotone. The proportion of aliphatic C in mineral‐associated organic carbon (MoM) increased with aspen dominance. The effect of overstory composition on MoM chemistry was patent beyond the influence of site conditions and microbial decomposer community.
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