Soil Pore Network Complexity Changes Induced by Wetting and Drying Cycles-A Study Using X-ray Microtomography and 3D Multifractal Analyses

Abstract

Soils are dynamic and complex systems in their natural state, which are subjected to profound changes due to management. Additionally, agricultural soils are continuously exposed to wetting and drying (W-D) cycles, which can cause modifications in the complexity of their pores. Thus, we explore how successive W-D cycles can affect the pore network of an Oxisol under contrasting managements (conventional tillage-CT, minimum tillage-MT, no tillage-NT, and secondary forest-F). The complexity of the soil pore architecture was evaluated using a 3D multifractal approach combined with lacunarity, Shannon's entropy, and pore geometric parameters. Our results showed that the multifractal approach effectively identified and quantified the changes produced in the soil pore architecture by the W-D cycles. The lacunarity curves revealed important aspects of the modifications generated by these cycles. Samples under F, NT, and MT suffered the most significant changes. Pore connectivity and tortuosity were largely affected by the cycles in F and NT. Our findings demonstrated that the 3D geometric parameters and normalized Shannon's entropy are complementary types of analysis. According to the adopted management, they allowed us to separate the soil into two groups according to their similarities (F and NT; CT and MT).

Keywords: 3D geometric parameters; conservation agriculture; generalized fractal dimension; no-tillage system; soil structure.

Figure 1

3D lacunarities (Λ) of the samples submitted to 0 and 12 wetting and drying (W-D) cycles. (a) Secondary forest—F; (b) conventional tillage—CT; (c) minimum tillage—MT; (d) no tillage—NT. The divisions into two parts (first and second) were made based on the regions where the best linear adjustments occurred in the curves. ε is the box size.

Figure 2

First derivative ($\raisebox{1ex}{$dLn\mathsf{\Lambda }$}\!\left/ \!\raisebox{-1ex}{$dLn\epsilon $}\right.$) of the 3D lacunarities of the samples submitted to 0 and 12 wetting and drying (W-D) cycles. (a) Secondary forest—F; (b) conventional tillage—CT; (c) minimum tillage—MT; (d) no tillage—NT. ε is the box size.

Figure 2

First derivative ($\raisebox{1ex}{$dLn\mathsf{\Lambda }$}\!\left/ \!\raisebox{-1ex}{$dLn\epsilon $}\right.$) of the 3D lacunarities of the samples submitted to 0 and 12 wetting and drying (W-D) cycles. (a) Secondary forest—F; (b) conventional tillage—CT; (c) minimum tillage—MT; (d) no tillage—NT. ε is the box size.

Figure 3

Multifractal spectra (f(α) versus α) of the samples subjected to 0 and 12 wetting and drying (W-D) cycles. (a) Secondary forest—F; (b) conventional tillage—CT; (c) minimum tillage—MT; (d) no tillage—NT.

Figure 4

The 3D normalized Shannon’s entropy (H*(ε)) of the samples submitted to 0 and 12 wetting and drying (W-D) cycles. (a) Secondary forest—F; (b) conventional tillage—CT; (c) minimum tillage—MT; (d) no tillage—NT. The smaller graphs represent a zoomed-in region with the most significant variation (F and NT) between the curves. ε is the box size.

Figure 5

Variation of the 3D normalized Shannon’s entropy (H*(ε)) of the samples submitted to 0 and 12 wetting and drying (W-D) cycles. Secondary forest—F; conventional tillage—CT; minimum tillage—MT; no tillage—NT. ε is the box size.