## 4 Discussion  
The main approach for soil PSD analysis, textural triangle is limited by the arbitrary classification of PSD scales [36; 37; 38]. To date, there remains no general agreement about what PSD of sediments and other soils types attributes should be monitored and described based on different PSD scales and PSC systems, worldwide [28]. During our research, different PSD scales and descriptive terminologies including China (1987), Katschinski (1957), USDA (1993), ISSS (1929), ISO14688 (2002), and Blott & Pye (2012) PSC systems were selected. The China (1987), USDA (1993), ISO14688 (2002), and Blott & Pye (2012) PSC systems have almost the same range of clay, silt, and sand scales. However, [PERSON] (1957) PSC system has a larger range of clay scale, while ISSS (1929) PSC system has a larger range of sand scale. Apparently, fully dividing the soil fractions like clay, silt, and sand could display the most information of integrated indicators and of soil property characteristics, but the existing schemes do not contribute to a completely true logical or sufficient basis for description and comparison of soil PSD. For example, [PERSON] (1957) PSC system divides the \(<\)1 \(\upmu\)m particle into colloidal, fine, and coarse clay fraction, while USDA (1993) PSC system divides the \(>\)50 \(\upmu\)m particle into fraction into very fine, fine, medium, coarse and very coarse sand fraction. In this study, Blott & Pye (2012) PSC system is recommended due to its sufficient subdivisions of clay, silt, and sand classes. Fractal method can be applied for various disciplines like soil science, computer science and network, etc. [39; 40; 41; 42; 43; 44; 45; 46; 47]. Fractal analysis associate with laser diffraction could provide opportunity  
Figure 9: Variations of Lg (\(V/V_{T}\)) and Lg (\(R_{i}/R_{\rm max}\)) under different PSC systems. Dash line is 1:1 line. **(a)** presents China (1987) PSC system, **(b)** presents [PERSON] (1957) PSC system, **(c)** presents USDA (1993) PSC system, **(d)** presents ISSS (1929) PSC system, **(e)** presents ISO14688 (2002) PSC system, **(f)** presents Blott & Pye (2012) PSC systems. of revealing soil information [13; 38; 40]. Recent studies showed the \(D\)s increased with clay and silt fractions but decreased with sand fractions following a linear trend [32; 41; 43], and our research results agree with the mentioned studies above. Moreover, in the previous studies, topsoil profile of vegetation solutions could obviously prevent land desertification and thus the clay and silt contents would be increased, then it usually had higher \(D\)s [8; 44]. Since accumulative fine particles like clay and silt fractions can be rapidly eroded and lost than sand fraction [18; 45]. In our study, anti-desertification solutions like MPPs establishment had a considerable effect in the increase of the clay and silt fractions, also with the forest densities of MPPs increased. Though \(D\)s calculated by China (1987), Katschinski (1957), USDA (1993), ISSS (1929), ISO14688 (2002), and Blott & Pye (2012) PSC systems varied differently, they were highly correlated with correlation coefficients above 0.970 (\(p<0.01\)), and great strength of correlations between \(D\)s and forest densities (\(p<0.01\)). The PSD prediction has been used for comparing and converting texture measurements from diverse PSC systems [2; 27; 21]. For instance, in the Second National Soil Surveys of China, soil textures were measured by ISSS (1929) and Katschinski (1957) PSC systems, in which the conversion from ISSS and Katschinski's to the widely used USDA (1993) PSC system [48; 49]. In this study, PSD characteristics which are described by fractal method were investigated because of its simplicity and effectiveness to compare the different PSC systems. To our knowledge, a few studies have been performed with such the purpose.