Different Soil Particle-Size Classification Systems for Calculating Volume Fractal Dimension—A Case Study of Pinus sylvestris var. Mongolica in Mu Us Sandy Land, China

Abstract

Characterizing changes in the soil particle-size distributions (PSD) are a major issue in environmental research because it has a great impact on soil properties, soil management, and desertification. To date, the use of soil volume fractal dimension (D) is a feasible approach to describe PSD, and its calculation is mainly dependent on subdivisions of clay, silt, sand fractions as well as different soil particle-size classification (PSC) systems. But few studies have developed appropriate research works on how PSC systems affect the calculations of D. Therefore, in this study, topsoil (0–5 cm) across nine forest density gradients of Pinus sylvestris var. mongolica plantations (MPPs) ranging from 900–2700 trees ha–1 were selected in the Mu Us sandy land, China. The D of soil was calculated by measuring soil PSD through fractal model and laser diffraction technique. The experimental results showed that: (1) The predominant PSD was distributed within the sand classification followed by clay and silt particle contents, which were far less prevalent in the study area. The general order of D values (Ds) was USDA (1993) > ISO14688 (2002) > ISSS (1929) > Katschinski (1957) > China (1987) > Blott & Pye (2012) PSC systems. (2) Ds were significantly positively related to the contents of clay and silt, and Ds were significantly negatively to the sand content. Ds were susceptible to the MPPs establishment and forest densities. (3) Ds of six PSC systems were significantly positive correlated, which indicated that they not only have difference, but also have close connection. (4) According to the fractal model and descriptions of soil fractions under different PSC systems, refining scales of clay and sand fractions could increase Ds, while the refining scale of silt fraction could decrease Ds. From the conclusions above, it is highly recommended that USDA (1993) and Blott & Pye (2012) PSC systems be used as reliable and practical PSC systems for describing and calculating D of soil PSD.

Occurrence Regularity of Silt–Clay Minerals in Wind Eroded Deserts of Northwest China

“…For different vegetation types in the same area, such as the Hulunbuir sands, the four vegetation species differed greatly, indicating that the selection of shrub species still needs to be analyzed and compared with the actual conditions and suitability of each area. Studies on different vegetation covers showed that when the vegetation cover was low (<15%), the area was in a more serious stage of land desertification, and the silt-clay content was below 10% [47,[63][64][65][66][67]. With the increase in vegetation cover, the silt-clay content gradually increased to 20-25% at a more moderate rate, indicating that the effect of the initial vegetation establishment on the silt-clay particle content was not significant.…”

“…Different coverage of vegetation and silt-clay content (Data from reference[47,[63][64][65][66][67]). …”

The Evaluation of the Accuracy of Interpolation Methods in Crafting Maps of Physical and Hydro-Physical Soil Properties

“…The seventh digit specifies one of five categories of soil texture [21]. Of the available physical, hydro-physical and chemical soil properties observed during the survey, only the soil types according to soil texture (based on Novák's classification adapted from the Kachinski system [23][24][25]) were "projected" into mapping and included in ESEUs. However, the informative value of those datasets is decreasing, as updates are elaborated only in terms of the definition of agricultural land (by drawing possible changes in the forest boundary) and slope conditions processed by geodetic activity in the landscaping process [25,26].…”

Determination of the Fractal Dimension of the Fracture Network System Using Image Processing Technique

“…Under various circumstances, frequency-size distribution of fractures, faults, mineral deposits, oilfields, earthquakes, and topography can be represented by the concept of fractals [8]. Some studies have reported the use of a fractal-based model in the geology to investigate relationships between the properties of pore structure, soil, and FD in different locations, such as tight sandstone and mudstone [18][19][20]. Gong et al [21] utilized a FD-based method to describe and predict the complex natural fractures in the tight conglomerate reservoirs.…”