Abstract
With the advent of computed microtomography (μCT), in situ 3D visualization of soil at micron scale became easily achievable. However, most μCT-based research has focused on visualization and quantification of soil pores, roots, and particulate organic matter (POM), while little effort was been put in exploring the soil matrix itself. This study aims to characterize spatial heterogeneity of soil matrix in macroaggregates from three differing long term managements: conventionally managed and biologically based row-crop agricultural systems and primary successional unmanaged system and explore the utility of using grayscale gradients as a proxy of soil organic matter (SOM). To determine spatial characteristics of the soil matrix, we completed a geostatistical analysis of the aggregate matrix. It demonstrated that, while the treatments had the same range of spatial correlation, there was much greater overall variability in soil from the biologically based system. Since soil from both managements has the same mineralogy and texture, we hypothesized that greater variability is due to differences in SOM distributions, driven by spatial distribution patterns of soil pores. To test this hypothesis, we applied osmium (Os) staining to intact micro-cores from the biologically based management, and examined Os staining gradients every 4 μm from 26 to 213 µm from pores of biological or non-biological origin. Biological pores had the highest SOM levels adjacent to the pore, which receded to background levels at distances of 100-130 μm. Non-biological pores had lower SOM levels adjacent to the pores and returned to background levels at distances of 30-50 μm. This indicates that some of the spatial heterogeneity within the soil matrix can be ascribed to SOM distribution patterns as controlled by pore origins and distributions. Lastly, to determine if the grayscale values could be used as a proxy for SOM levels, gradients of grayscale values from biological and non-biological pores were compared with the Os gradients. Grayscale gradients matched Os gradients for biological pores, but not non-biological pores due to an image processing artifact. Grayscale gradients would, therefore, be a good proxy for SOM gradients near biological origin pores, while use for non-biological pores should be used with caution.
Highlights
The use of computed microtomography has allowed for the in situ characterization of the physical structure of soil, positions, size distributions, and shapes of soil pores (Gibson et al, 2006; Chun et al, 2008; Peth et al, 2008; Papadopoulos et al, 2009; Kravchenko et al, 2011; Wang et al, 2012)
Solid material is represented in μCT images by a range of grayscale values that are correlated to the attenuation of x-rays, which is controlled by the density and atomic number (Z) of the elements occurring within an image voxel (Ketcham, 2005; Peth, 2010)
The soil was dry sieved and aggregates of 4–6.3 mm were collected for imaging. μCT images were obtained from beamline 13-BM-D of the GeoSoilEnvironCARS (GSECARS) at the Advanced Photon Source (APS), Argonne National Laboratory (ANL) in Argonne, Illinois
Summary
The use of computed microtomography (μCT) has allowed for the in situ characterization of the physical structure of soil, positions, size distributions, and shapes of soil pores (Gibson et al, 2006; Chun et al, 2008; Peth et al, 2008; Papadopoulos et al, 2009; Kravchenko et al, 2011; Wang et al, 2012) It enabled identification of large organic fragments, including particulate organic matter (POM) (Kravchenko et al, 2014a) and intact plant roots (Mooney et al, 2012). Overall SOM distribution patterns are likely controlled by a combination of mineralogy and pore architecture, i.e., pore size and connectivity (Dungait et al, 2012; Kravchenko et al, 2015)
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