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Degradability of organic matter (OM) in soil depends on its spatial location in the soil matrix. A recent breakthrough in 3D-localization of OM combined dual-energy X-ray CT-scanning with OsO 4 staining of OM. The necessity for synchrotron-based µCT and the use of highly toxic OsO 4 severely limit applications in soil biological experiments. Here, we evaluated the potential of alternative staining agents (silver nitrate, phosphomolybdenic acid (PMA), lead nitrate, lead acetate) to selectively enhance X-ray attenuation and contrast of OM in CT volumes of soils containing specific mineral soil particle fractions, obtained via lab-based X-ray µCT. In comparison with OsO 4 , administration of Ag + and Pb 2+ resulted in insufficient contrast enhancement of OM versus fine silt (< 20 µm) or clay (< 2 µm) mineral particles. The perfusion procedure used in this work induced changes in soil structure. In contrast, PMA staining resulted in a selective increase of OM's attenuation contrast, which was comparable to OsO 4 . However, OM discrimination from other soil phases remained a challenge. Further development of segmentation algorithms accounting for grey value patterns and shape of stained particulate OM may enable its automated identification. If successful in undisturbed soils, PMA staining may form an alternative to OsO 4 in non-synchrotron based POM detection.

The rising demand for feed and food has put an increasing pressure on agriculture, with agricultural intensification as a direct response. Notwithstanding the higher crop productivity, intensive agriculture management entails many adverse environmental impacts. Worldwide, soil organic carbon (SOC) decline is hereby considered as a main danger which affects soil fertility and productivity. The life cycle perspective helps to get a holistic overview when evaluating the environmental sustainability of agricultural systems, though the impact of farm management on soil quality aspects is often not integrated. In this paper, we introduce an indicator called Agricultural Biomass Productivity Benefit of SOC management (ABB&#95;SOC), which, relying on natural resource consumption, enables to estimate the net effect of the efforts made to attain a better soil quality. Hereby the focus is put on SOC. First, we introduce a framework to describe the SOC trend due to farm management decisions. The extent to which remediation measures are required are used as a measure for the induced SOC losses. Next, ABB&#95;SOC values are calculated as the balance between the natural resource consumption of the inputs (including remediation efforts) and the desired output of arable crop production systems. The models RothC and EU-Rotate&#95;N are used to simulate the SOC evolution due to farm management and the response of the biomass productivity, respectively. The developed indicator is applied on several rotation systems in Flanders, comparing different remediation strategies. The indicator could be used as a base for a method to account for soil quality in life cycle analysis., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

Historic long-term P application to sandy soils in NW-Europe has resulted in abundant sorption, saturation and eventually leaching of P from soil to the groundwater. Although many studies recognize the control of site-specific factors like soil texture and phosphate saturation degree (PSD), the regional-scaled relevance of effects exerted by single factors controlling P leaching is unclear. Very large observational datasets of soil and groundwater P content are furthermore required to reveal indirect controls of soil traits through mediating soil variables. We explored co-variation of phreatic groundwater orthophosphate (o-P) concentration and soil factors in sandy soils in Flanders, Belgium. Correlation analyses were complemented with an exploratory model derived using 'path analysis'. Data of oxalate-extractable Al, Fe, P and pH KCl , phosphate sorption capacity (PSC) and PSD in three depth layers (0-30, 30-60, 60-90 cm), topsoil SOC, % clay and groundwater depth (fluctuation) were interpolated to predict soil properties on exact locations of a very extensive net of groundwater monitoring wells. The mean PSD was only poorly correlated to groundwater o-P concentration, indicating the overriding control of other factors in the transport of P to the groundwater. A significant (P < 0.01) positive non-linear relationship was found between groundwater o-P concentrations and pH KCl for all depth layers. Likewise, lower SOC% (P < 0.01) and shallower groundwater level (MHL or MLL) corresponded (P < 0.01) with higher o-P concentrations. Groundwater o-P unexpectedly correlated positively to clay% and path analysis indicated this to be an indirect effect of the groundwater level. Path analysis furthermore indicated an important indirect control of pH on groundwater o-P concentrations and a considerable direct effect of P ox, 0-90 , Al ox, 0-90 and MHL. The fact that groundwater o-P concentration was stronger controlled by soil pH and groundwater table depth than by PSD indicates the likely oversimplification of the latter index to measure the long-term potential risk of P leaching. Accounting for controls on leaching not included in PSD via an alternative index, however, seems problematic as in Flanders for example groundwater o-P turned out to be higher in finer textured soils or soils with higher pedogenic Fe content, probably because of their lower pedogenic Al content and higher soil pH. Path analysis of extensive soil and groundwater datasets seems a viable way to identify prime local determinants of soil P leaching and could be further on used for 'ground-truthing' more complex P-migration simulation models., (Copyright © 2017 Elsevier Ltd. All rights reserved.)