Pore distances of particulate organic matter predict N2O emissions from intact soil at moist conditions - Ortega-Ramírez, Patricia; Pot, Valérie; Laville, Patricia; Schlüter, Steffen; Amor-Quiroz, David Arturo; Hadjar, Dalila; Mazurier, Arnaud; Lacoste, Marine; Caurel, Chloé; Pouteau, Valérie; Chenu, Claire; Basile-Doelsch, Isabelle; et al. (Geoderma, 2023)
Denitrification in soils is a very complex phenomenon due to the multiple factors it depends on. Therefore, making accurate predictions has been an elusive task. In this study we measured N2O emissions daily during 7 days from a set of 20 undisturbed small soil cores that were subsequently scanned using X-ray micro-tomography. Macropores, particulate organic matter (POM) and the mineral matrix were detected based on a locally-adaptive segmentation method. We proposed an indicator based on the morphology of the soil micro-structure to predict the N2O emissions. The indicator, IdPOM-air, relies on the hypothesis that more N2O will be emitted when POM is occluded in the soil matrix, i.e. is located at large distances from the next air-filled pore, most likely leading to anoxic conditions, favorable to the production of N2O. We computed IdPOM-air as the average value of the geodesic distances from the surface of every POM to the closest air-filled pore. For each of the 7 days of measurements IdPOM-air showed a linear trend (each day with an r2>0.75) with respect to the N2O emissions, indicating that the spatial distributions of the POM and air-filled pores were key factors to determine the N2O emissions in our soil cores. •The distribution of POM and air-filled pores in soils affects N2O emissions.•The distribution of POM and air-filled pores is more important than their size.•Computation of Geodesic distance in 3D images to predict N2O emissions in soil.•Local segmentation in 3D micro tomography images to identify POM.•Comparison of POM mass measurements and POM volume computed using image analysis.